Global climate collaborative regulation system based on multi-stage relay network

Abstract

A global climate collaborative regulation system based on a multi-stage relay network comprises: a global heat balance regulation module to realize cross-latitude regulation of cold and warm air masses through successive transfer and layered delivery paths according to a source-site regulation priority principle; a multi-stage cloud cluster regulation network, which is composed of a space-air AI base and a macroscopic telescopic pipeline to form a standardized relay unit, to realize rain and snow pre-programmed control through a three-stage process and to internally build a four-layer safety protection system; a light wind gust manufacturing subsystem to utilize the chimney effect driven by temperature difference and air pressure difference and passive aerodynamic acceleration output to output a perceptible cool wind; a sunshade cloud layer and precipitation collaborative cooling module to realize persistent maintenance of cloud layers and polar protection through a tri-service technology; an extreme weather super-early intervention module to form a full-chain prevention and control system mainly through prelude cloud intervention and supplemented by embryo period remediation; a quantum-classical hybrid decision-making hub to maximize the livability index and collaborate with each module; and a climate engineering risk control module internally built with a risk assessment, teleconnection monitoring and fairness fuse mechanism.

Description

Technical Field

[0001] This invention belongs to the technical field of climate engineering, atmospheric physics and artificial intelligence collaborative control, specifically involving a global climate collaborative regulation system based on a multi-level relay network. Background Technology

[0002] Climate is a fundamental factor affecting the quality of human life. For thousands of years, humanity has dreamed of an ideal home with mild winters, cool summers, and favorable weather. To realize this vision, pioneers in meteorology and climate engineering have conducted extensive and fruitful work, accumulating rich theoretical achievements and practical experience in areas such as artificial rain enhancement, hail suppression, and cloud physics detection, laying a solid foundation for the proposal of this invention.

[0003] Meanwhile, the high complexity of the climate system and the limitations of existing technologies mean that current climate intervention capabilities still have considerable room for improvement to achieve the aforementioned vision. In general, existing technologies face the following typical challenges: regulation methods primarily rely on aircraft-based condensation seeding, which is limited by range and airspace, making large-scale, continuous, and precise intervention difficult; there is a lack of effective means for efficient cross-regional allocation of cloud water resources; the ability to actively control precipitation intensity and phase is insufficient, lacking a complete chain from particle size pre-setting to time-based control; technical solutions for active intervention in the early stages of energy accumulation are still immature, particularly the need to explore differentiated prelude cloud identification and joint prevention and control systems for various types of extreme weather; there is a lack of systematic prevention and control mechanisms for the potential chain reaction risks triggered by the convergence of prelude clouds with upper-level primary cloud clusters; furthermore, existing climate intervention technologies have not yet established a comprehensive assessment and management framework for potential long-range teleconnection impacts and cross-regional equity issues.

[0004] Based on the above background and the work of predecessors, this invention attempts to provide a more comprehensive and systematic technical solution, in order to contribute a prudent and exploratory force to realizing the beautiful vision of "warm winters and cool summers, and favorable weather". Summary of the Invention

[0005] The purpose of this invention is to provide a global climate collaborative regulation system based on a multi-level relay network, achieving precise global climate control and further expanding the technological boundaries of climate intervention based on previous work. Specifically, it attempts to provide a system capable of both large-scale climate regulation and the generation of localized light winds and gusts with extremely low energy consumption. It can also regulate heavy, medium, and light rain and snow on demand through a three-stage process, supporting customized precipitation periods based on public preferences. Furthermore, it can maintain persistent shading clouds and establish a year-round polar protection process through a three-in-one technology. For various extreme weather events such as typhoons, storms, blizzards, hail, and thunderstorms, it primarily uses pre-storm cloud intervention to transform them into winds and stable precipitation below a preset level, with embryonic stage remediation as a backup plan. It can also minimize the butterfly effect of pre-storm cloud convergence with primary cloud clusters during transport and transformation, and can cope with various types of weather events. In the event of concurrent extreme weather events, joint prevention and control measures can be implemented. Global heat allocation can be achieved through stratified transport of cold and warm air masses, channel isolation, cold air mass circulation relay, and buoyancy control of warm air masses. At the same time, a closed-loop management system is achieved through a full-chain early prevention and control system. The system establishes a three-tiered energy efficiency optimization principle of "prioritizing source location regulation, followed by nearby transport, and long-distance transport as a backup." It follows the energy efficiency philosophy of "prioritizing natural forces, structural gains, and source location" and is a comprehensive system deployed in stages according to the principle of progressive capability. With the stability of polar ice caps as a hard constraint, it adopts an AI-controlled and human-supervised mode to achieve the climate regulation vision of "warm winters and cool summers, and favorable weather" through closed-loop optimization control.

[0006] To achieve the above objectives, the present invention provides a global climate coordinated regulation system based on a multi-level relay network, comprising:

[0007] The global thermal balance regulation module is used to maintain a dynamic thermal balance between at least one target area and the polar region, with the stability of the polar ice cap as a hard constraint. The global thermal balance regulation module follows a three-tiered energy efficiency optimization principle: prioritizing source location regulation, followed by nearby transport, and with long-distance transport as a backup.

[0008] The multi-level cloud cluster control network module comprises multiple standardized relay units distributed along vertical height, used to capture, vertically transport, temporarily store and condition, and release cloud clusters. This module achieves pre-programmed control of precipitation intensity within predetermined levels and active switching of precipitation phases between rain and snow through a three-stage process of particle size preset, height adjustment, and time-period control, by combining and controlling cloud temperature, condensation nucleus type, and release height. Each standardized relay unit integrates an aerospace AI mobile base and a macroscopic telescopic pipe into a single independent force-bearing structure. The aerospace AI mobile base adopts a lifting body configuration, possessing a high lift-to-drag ratio and rotational symmetry. Flexible transmission between each standardized relay unit is achieved through a relay airspace, without rigid mechanical connections.

[0009] The light breeze / gust generation subsystem, relying on the standardized relay units, utilizes natural physical processes as the driving force to support a multi-level relay network remote wind generation mode, a near-ground local wind generation mode using a single standardized relay unit, and a multi-base array collaborative wind generation mode. The near-ground local wind generation mode utilizes the natural temperature and pressure differences between the ground and upper atmosphere to create a chimney effect that draws in airflow. This airflow is accelerated by a passive aerodynamic acceleration structure at the outlet of the macroscopic telescopic pipe. The outlet airflow is then guided to the ground via an adjustable guide structure to form a localized closed-loop circulation or diffused airflow, generating a cool breeze due to the wind-cooling effect. The multi-base array collaborative wind generation mode uses multiple standardized relay units arranged in an array. Each standardized relay unit works in conjunction with a soft wall in the airspace to jointly generate a wide-coverage light breeze or gust.

[0010] The quantum-classical hybrid decision-making center, based on a digital twin Earth model, aims to maximize the global livability index and coordinate the control of various modules. The livability index is composed of multiple sub-indices, including winter comfort, summer comfort, precipitation temperature, and humidity.

[0011] The Extreme Weather Early Intervention Module is used to identify the cloud structure of typhoons, rainstorms, blizzards, hail, and thunderstorms in the early cloud stage before the energy of extreme weather systems has accumulated significantly. It attempts to identify the cloud structure of typhoons, rainstorms, blizzards, hail, and thunderstorms in advance through a classification-based cloud identification standard. The module uses cloud intervention strategy as the main strategy to try to transform extreme weather events into winds and stable precipitation below the preset level. It also has a backup plan for embryonic stage remedial intervention after missing the cloud window. The module has the ability to jointly prevent and control multiple types of extreme weather concurrently. It works in conjunction with the Climate Engineering Risk Management Module to form an early prevention and control system covering the entire chain of "cloud identification - cloud intervention - embryonic stage remedial intervention - circuit breaker protection".

[0012] The climate engineering risk management module has a built-in quantitative risk assessment matrix, an upper-air environmental disturbance assessment unit, a teleconnection monitoring unit, a cumulative effect early warning unit, and a cross-regional fairness assessment algorithm. It is used to conduct multi-dimensional risk assessments before, during, and after intervention. When the negative climate impact caused by global regulation in any region exceeds a preset threshold, it triggers circuit breaker or compensatory regulation.

[0013] The human supervision interface module is used to receive decision instructions from the human supervision layer and automatically switch the system's operating mode according to preset human intervention trigger conditions.

[0014] In one embodiment of the present invention, the global heat balance regulation module adopts a sequential transfer mechanism, in which heat is transferred step by step along the horizontal latitudinal gradient; and different paths are used for the long-distance horizontal transport of cold and hot air masses, wherein: the cold air mass takes the lower stratosphere as the main channel, and the hot air mass takes the middle and lower troposphere as the main channel.

[0015] The complete transport path of the cold air mass is as follows: after being collected from the polar regions, it is vertically lifted to the lower stratosphere, where it is horizontally transported using the low turbulence environment and the constraints of the relay airspace. During short-distance transport, the settling rate is controlled by the soft walls of the relay airspace, allowing the air mass to naturally settle to the target area. During medium- and long-distance transport, a cyclic relay mode of "transport-sinking-conditioning-lifting" is adopted, with dynamic cooling and conditioning by the relay airspace along the way, and relay lifting when the air mass approaches the preset minimum allowable height. Finally, it is temporarily stored and released in the relay airspace in the low cloud region.

[0016] The complete transport path of the hot air mass is as follows: after being collected from the hot zone, it rises to the lower troposphere using the chimney effect. After being heated and conditioned by the relay airspace, it is transported horizontally in this layer. During the transport process, the buoyancy ascent rate is controlled by the bidirectional regulation capability of the soft wall of the relay airspace, and a maximum allowable height is set as a hard constraint. After arriving near the target cold zone, precipitation is triggered at an appropriate height, transferring heat to the ground. The cold air mass transport channel and the hot air mass transport channel are physically isolated in the vertical direction.

[0017] When there is a cooling demand, the global thermal balance regulation module evaluates and implements the response according to the priority of source location regulation, nearby delivery, and long-distance delivery; when there is a heating demand, it also evaluates and implements the response according to the priority of source location regulation, nearby short-distance delivery, and long-distance delivery.

[0018] The global thermal balance regulation module also includes a local warm and humid air mass precipitation and cooling mode.

[0019] In one embodiment of the present invention, the natural physical processes utilized by the light wind and gust generation subsystem include the chimney effect, passive aerodynamic acceleration effect, and gravity-thermal driving effect. The chimney effect refers to the natural temperature and pressure difference between the ground and the upper atmosphere driving the air around the bottom opening of the macroscopic telescopic pipe to flow centripetally, forming a centripetal wind. At the same time, the hot air inside the pipe cools due to adiabatic expansion during its ascent and is passively accelerated and ejected after passing through the outlet contraction configuration. The gravity-thermal driving effect includes the sinking and diverging of cold air masses and the rising and drawing of warm air masses. The active energy consumption of the gravity-thermal driving effect is zero.

[0020] In the multi-base array collaborative wind-generating mode, multiple standardized relay units are arranged in an array, and each standardized relay unit works in conjunction with the airspace soft wall to jointly generate light winds or gusts with a wide coverage area. In the near-ground local wind-generating mode of a single set of standardized relay units, the system's active energy consumption is only used to maintain the base's flight attitude and micro-unit guidance and adjustment, and the wind-generating power itself is provided by natural physical processes.

[0021] In one embodiment of the present invention, the aerospace AI mobile base adopts a lifting body configuration, has a high lift-to-drag ratio and rotational symmetry aerodynamic shape, is provided with a central through channel to accommodate the macroscopic telescopic pipe, and has a built-in ducted propulsion system and integrated buoyancy adjustment structure, so as to realize long-term residence in the stratosphere, or return to the ground base for maintenance, repair, energy replenishment and material resupply before redeployment.

[0022] The macroscopic telescopic pipe adopts a multi-level nested telescopic structure, forming a vertically penetrating airflow channel in the extended state, and can be completely stored inside the aerospace AI mobile base in the contracted state; the macroscopic telescopic pipe adopts a honeycomb composite structure; and a quick-connect and quick-disconnect interface structure is provided at the bottom.

[0023] In one embodiment of the present invention, the aerospace AI mobile base is equipped with a cloud processing and control system, including at least one of an aerodynamic atomization unit, a heat exchange unit, a condensation nucleus dispersing unit, and a charge control unit; the aerodynamic atomization unit is driven by the air pressure difference generated by the chimney effect to achieve cloud droplet size control without additional power consumption; the condensation nucleus dispersing unit disperses condensation nuclei of a type that can be adapted to the target precipitation phase.

[0024] The three-stage process includes: a particle size preset stage, where heavy rain activates the eddy current pre-fragmentation unit, moderate rain activates the combination of eddy current pre-fragmentation and passive aerodynamic atomization, and light rain activates all fragmentation units, and achieves drizzle or only humidification without precipitation by suppressing collisions through charge regulation; an altitude adjustment stage, where heavy rain is released from high cloud areas, moderate rain is released from mid-cloud areas, and light rain is released from low cloud areas; and a time period control stage, where the release timing is controlled by relay airspace temporary storage, achieving daytime rain avoidance, nighttime water replenishment, staggered release, emergency response, and differentiated scheduling based on public preferences.

[0025] In one embodiment of the present invention, the quantum-classical hybrid decision-making center adopts a multi-level computing architecture, including a quantum heuristic layer, a quantum acceleration layer, a classical supercomputing layer, and a hybrid interface layer. The quantum heuristic layer is used to deploy tensor network algorithms to simulate quantum parallel exploration and scan global atmospheric data around the clock. The quantum acceleration layer is used to deploy quantum optimization algorithms to improve the search efficiency of high-dimensional parameter space. The classical supercomputing layer is used to run high-resolution atmospheric circulation models and integrate intelligent micro-unit sensing data for four-dimensional variational assimilation. The hybrid interface layer is used to realize real-time task scheduling and data collaboration between computing units at all levels.

[0026] In one embodiment of the present invention, the livability index is composed of three sub-indices: winter comfort, summer comfort, and precipitation temperature; the quantum-classical hybrid decision center takes "maximizing the global livability index under the premise of stable growth of polar ice cap" as the optimization objective and dynamically generates control strategies; the system adopts the principle of relative optimization, allowing different regions to maintain preset temperature preference differences and precipitation period preferences on their own climate benchmarks.

[0027] In one embodiment of the present invention, the multi-level cloud cluster control network module further includes an intelligent micro-unit cluster, which is carried and deployed to the operational area by the aerospace AI mobile base and is fully recovered after the task is completed. The intelligent micro-unit cluster adopts a swarm rotation working mode, returning to the aerospace AI mobile base or ground base for rapid charging and status detection after a single task is completed, while a backup batch is launched to take over. The working mode of the intelligent micro-unit cluster includes at least one of cloud generation, cloud guidance, shading cloud generation and maintenance, prelude cloud identification, prelude cloud intervention, embryonic stage remediation, ecological monitoring, and relay airspace soft wall maintenance.

[0028] The intelligent micro-unit cluster adopts a serialized and modular design, divided into several dedicated models: the sensing type is equipped with a micro-sensor array for pre-cloud identification and ecological monitoring; the seeding type is equipped with a replaceable catalyst payload chamber for precise seeding of condensation nuclei; the soft-wall type is equipped with pulse heating or cooling elements for maintaining intermittent temperature gradients at the airspace edge; the guiding type is equipped with directional heating and vector thrusters for guiding cloud paths; the water replenishment type is equipped with water vapor collection and atomization devices for dynamic water replenishment of shading clouds; and the communication relay type is equipped with a laser communication terminal for cross-spatial data transmission. Each model of the intelligent micro-unit cluster uses a unified communication protocol, positioning interface, and charging specifications, and can be flexibly combined and deployed according to mission requirements.

[0029] In one embodiment of the present invention, in the relay airspace soft wall maintenance mode, the intelligent micro-unit cluster generates a temperature gradient field at the edge of the relay airspace through intermittent pulsed local heating or cooling. It uses the density stratification and buoyancy effect of the atmosphere itself to constrain the diffusion of cloud or air mass, and generates lifting force through bottom heating to counteract the gravitational sinking trend of cold air mass and the kinetic energy of the sinking divergent wind of cold air mass, or generates downforce through top cooling to counteract the buoyancy upward trend of hot air mass. For long-cycle missions, the intelligent micro-unit cluster is deployed in the form of tethered balloons or aerostats and is directly powered by the base.

[0030] In one embodiment of the present invention, the ultra-early intervention module for extreme weather includes a typed prelude cloud identification unit, a prelude cloud intervention unit, a joint prevention and control unit, and an embryonic period remediation unit.

[0031] The categorized prelude cloud identification unit integrates multi-source data and establishes differentiated prelude cloud identification standards for strong typhoons, rainstorms, blizzards, hail, and thunderstorms. It attempts to identify prelude clouds in advance before their energy has accumulated significantly. Since prelude cloud identification has a certain false alarm rate, the system reduces the risk of false alarms by integrating multi-source data and ensemble forecasting, and performs counterfactual analysis before intervention to avoid unnecessary intervention in unnaturally developing cloud clusters.

[0032] The prelude cloud intervention unit, as the main strategy, first performs de-energization preprocessing on the prelude cloud passing through the macroscopic telescopic pipe within the standardized relay unit after identifying the prelude cloud. Then, the preprocessed prelude cloud is confined within a safe container formed by the soft wall of the relay airspace for transportation and conditioning. Subsequently, the corresponding intervention plan is activated: for strong typhoons, convective competitive seeding combined with sea surface cooling and wind shear enhancement is implemented; for storms, supercooled water consumption and precipitation pre-release are implemented; for blizzards, ice crystal concentration regulation and temperature stratification control are implemented; for hail and thunderstorms, competitive seeding and charge neutralization are implemented. After intervention, the cloud cluster is regulated through a three-stage process to achieve stable precipitation, and residual wind is further reduced through a multi-base array collaborative wind-generating mode.

[0033] The joint prevention and control unit is used to deal with multiple types of extreme weather scenarios. It identifies all candidate points of foreshadowing clouds through encrypted scanning of the space-based sensing layer, sorts them according to risk priority, and mobilizes multiple relay chains to coordinate and execute type-specific interventions, residual wind energy dissipation, and precipitation regulation. During the joint prevention and control process, the cumulative impact of multiple intervention operations on the same weather system is assessed simultaneously to prevent the systemic risk of "paying attention to one thing but neglecting another".

[0034] The embryonic stage rescue unit serves as a backup plan. It is activated when the prelude cloud intervention window is missed for any reason, and performs graded rescue based on the delay time. When the rescue window is completely closed, it switches to monitoring, early warning, and ground protection mode.

[0035] In one embodiment of the present invention, an artificial shading cloud application module is also included, which adopts a three-in-one persistent maintenance technology of soft wall constraint, dynamic water replenishment and particle size control. Specifically, it constrains the cloud boundary diffusion by relaying the temperature gradient field at the edge of the airspace; it continuously extracts water vapor from the ocean or land surface water for atomization replenishment; it suppresses collision and sedimentation by applying the same charge to cloud droplets; it supports a coordinated deployment mode of shading cloud reflection cooling and local warm and humid air mass precipitation cooling, and establishes an all-season operation process for polar ice sheet protection.

[0036] The protection of the polar ice cap adopts a synergistic strategy of "shading and reducing heat loss + increasing snowfall." Specifically, during the polar day, the shading cloud layer reduces the absorption of solar radiation and slows down the melting rate. Artificial snowfall strives to achieve material accumulation during the polar day's decline and the polar night, following a trial strategy of "high at the beginning and low at the end" with relatively high intensity snowfall growth in the early stage and gradually decreasing intensity in the later stage.

[0037] In one embodiment of the present invention, the multi-level cloud cluster control network module further includes a cloud cluster remote transport safety management unit, used to prevent extreme weather caused by the convergence with the primary cloud layer at high altitude during the remote transport of cloud clusters, and to prevent cold and warm air masses from converging due to gravity sinking or buoyancy rising in their respective transport channels and deviating from the safe altitude layer; the safety management unit adopts a four-layer protection system, namely: prediction and avoidance, active intervention, enhanced monitoring and early warning, and circuit breaking and emergency response; the cold air mass transport channel and the warm air mass transport channel are physically isolated in the vertical direction.

[0038] In one embodiment of the present invention, the climate engineering risk management module includes a cross-regional equity assessment unit, a teleconnection monitoring unit, and a cumulative effect early warning unit; the cross-regional equity assessment unit has a built-in regional climate regulation gain-loss index, and automatically initiates compensatory regulation or a circuit breaker mechanism when the negative climate impact exceeds a preset threshold; the teleconnection monitoring unit automatically reduces or suspends source area intervention when abnormal signals appear in teleconnection sensitive areas; the cumulative effect early warning unit tracks the cumulative intensity of intervention through a global intervention activity index.

[0039] In one embodiment of the present invention, the human supervision interface module has a built-in three-level decision-making authority system, namely: the AI ​​autonomous decision-making layer is responsible for routine operations; the AI ​​suggestion and human confirmation layer is responsible for major matters; and the human special decision-making layer is responsible for extreme matters. The human intervention triggering mechanism includes at least one of the following: abnormal monitoring of polar ice caps, continuous decline in regional livability index, unexpected disturbance in non-target areas, large-scale disconnection of intelligent micro-unit clusters, cloud cluster transportation process triggering circuit breaker, abnormal signals in remote sensing sensitive areas, and cumulative effect index exceeding the warning level.

[0040] The system also includes a habitable zone dynamic evolution unit and a global carbon cycle collaborative management module;

[0041] The system follows a phased and incremental deployment approach and a capability progression principle, attempting to achieve economic feasibility through phased and incremental investment and large-scale cost reduction.

[0042] The system incorporates multi-layered fault tolerance and mistake-proofing designs, and includes multiple security safeguards to prevent the misuse of technology. These safeguards include: all intervention operations are conducted within the final decision-making authority framework of the human oversight layer; the system's core control protocol adheres to the principles of transparency and auditability under the international climate governance framework; and key intervention decisions are subject to review by a multidisciplinary expert group composed of multiple countries. Attached Figure Description

[0043] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0044] Figure 1 This is a schematic diagram of the overall architecture of the global climate coordinated regulation system of the present invention.

[0045] Figure 2 This is a schematic diagram of the structure of a standardized relay unit in one embodiment of the present invention.

[0046] Figure 3 This is a schematic diagram of the standardized relay unit in its stowed state.

[0047] Figure 4 This is a schematic diagram illustrating the relay transmission principle of a multi-level cloud cluster control network in one embodiment of the present invention.

[0048] Figure 5 This is a schematic diagram of the stratified transport path of hot and cold air masses in one embodiment of the present invention.

[0049] Figure 6 This is a schematic diagram of the internal processing hierarchy layout of a space-based AI mobile base in one embodiment of the present invention.

[0050] Figure 7 This is a schematic diagram of the monocentric near-ground deployment of the light wind and gust generation subsystem in one embodiment of the present invention.

[0051] Figure 8 This is a schematic diagram illustrating the passive acceleration principle of airflow in a pipe outlet contraction configuration according to an embodiment of the present invention.

[0052] Figure 9 This is a schematic diagram of the quick-connect and quick-disconnect interface and the ground anchoring system in one embodiment of the present invention.

[0053] Figure 10 This is a flowchart of the intelligent micro-unit cluster bee colony rotation mechanism in one embodiment of the present invention.

[0054] Figure 11 This is a diagram of a multi-level computing architecture for a quantum-classical hybrid decision-making center in one embodiment of the present invention.

[0055] Figure 12 This is a diagram of a four-level collaborative sensing architecture based on space, air, and ground in one embodiment of the present invention.

[0056] Figure 13 This is a schematic diagram of the relay airspace temporary storage principle and soft wall formation mechanism in one embodiment of the present invention.

[0057] Figure 14 This is a flowchart of a three-level decision-making authority system and manual intervention mechanism in one embodiment of the present invention.

[0058] Figure 15 This is an overall flowchart of a global climate coordinated regulation method in one embodiment of the present invention.

[0059] Figure 16 This is a phased implementation roadmap for one embodiment of the present invention.

[0060] Figure 17 This is a diagram illustrating a multi-layered fault-tolerant and mistake-proofing design mechanism in one embodiment of the present invention.

[0061] Figure 18 This is a schematic diagram of a three-in-one technology for the persistent maintenance of a sunshade cloud layer in one embodiment of the present invention.

[0062] Figure 19 This is a flowchart of the all-season sunshade operation for polar ice cap protection in one embodiment of the present invention.

[0063] Figure 20 This is a diagram illustrating the prelude cloud identification and intervention strategy for extreme weather classification in one embodiment of the present invention.

[0064] Figure 21 This is a schematic diagram of the closed-loop early prevention and control system in one embodiment of the present invention.

[0065] Figure 22 This is a schematic diagram of a four-layer security protection system for remote cloud transportation in one embodiment of the present invention.

[0066] Figure 23 This is a schematic diagram of a three-layer energy efficiency optimization system based on the source location control priority principle in one embodiment of the present invention.

[0067] Figure 24 This is a schematic diagram of a multi-base array collaborative wind generation mode in one embodiment of the present invention.

[0068] Figure 25 This is a schematic diagram illustrating the process of extreme weather prelude cloud intervention transforming into gentle winds and steady precipitation in one embodiment of the present invention.

[0069] Figure 26 This is a schematic diagram of a five-step method for joint prevention and control of multiple types of extreme weather in one embodiment of the present invention.

[0070] Figure 27 This is a schematic diagram of a four-layer prevention and control mechanism to prevent conflict with the original cloud cluster during the prelude cloud transformation process in one embodiment of the present invention.

[0071] Figure 28 This is a schematic diagram of the closed-loop operation and maintenance of the aerospace AI base, which involves "staying-returning-resupplying-maintenance-redeployment" in one embodiment of the present invention.

[0072] Figure labeling: 101-Global thermal balance regulation module; 102-Multi-level cloud cluster control network module; 103-Light wind and gust generation subsystem; 104-Quantum-classical hybrid decision-making center; 105-Extreme weather ultra-early intervention module; 106-Climate engineering risk management module; 107-Human supervision interface module; 108-Human supervision layer; 109-Artificial shading cloud layer application module; 110-Habitable zone dynamic evolution unit; 111-Global carbon cycle collaborative management module; 112-Hybrid interface layer; 113-Quantum computing layer; 1131-Quantum inspiration layer; 1132-Quantum acceleration layer; 114-Classical supercomputing layer; 20-Standardized relay unit; 201-Space-based AI mobile base; 202-Macroscopic telescopic pipe; 203-Buoyancy regulation cabin; 204-Thin-film photovoltaic conversion component. Detailed Implementation

[0073] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0074] like Figures 1-28 As shown, this invention provides a global climate collaborative regulation system based on a multi-level relay network, comprising:

[0075] The global thermal balance regulation module 101 is used to maintain a dynamic thermal balance between at least one target area and the polar region, with the stability of the polar ice cap as a hard constraint. The global thermal balance regulation module 101 follows a three-tiered energy efficiency optimization principle of prioritizing source location regulation, followed by nearby transport, and with long-distance transport as a backup.

[0076] The multi-level cloud cluster control network module 102 includes multiple standardized relay units 20 distributed along the vertical height, used to realize cloud cluster capture, vertical transport, temporary storage and conditioning, and directional release. The multi-level cloud cluster control network module 102 achieves pre-programmed control of precipitation intensity between predetermined levels and active switching of precipitation phase between rain and snow by combining the control of cloud cluster temperature, condensation nucleus type, and release height, and adopts a three-stage process of particle size preset-height adjustment-time period control. Each standardized relay unit 20 is integrated into an integrated independent force-bearing structure by the aerospace AI mobile base 201 and the macroscopic telescopic pipe 202. The aerospace AI mobile base 201 adopts a lifting body configuration, with high lift-to-drag ratio and rotational symmetry. Each standardized relay unit 20 achieves flexible transmission through the relay airspace without rigid mechanical connection.

[0077] The light breeze / gust generation subsystem 103, relying on the standardized relay unit 20, utilizes natural physical processes as the driving force to support a multi-level relay network remote wind generation mode, a near-ground local wind generation mode for a single standardized relay unit 20, and a multi-base array collaborative wind generation mode. The near-ground local wind generation mode utilizes the natural temperature and pressure differences between the ground and upper atmosphere to create a chimney effect that draws in airflow. The airflow is accelerated by a passive aerodynamic acceleration structure at the outlet of the macroscopic telescopic pipe 202. The outlet airflow can be guided to the ground through an adjustable guide structure to form a local closed-loop circulation or diffused airflow, producing a cool breeze due to the wind-cooling effect (see...). Figure 2 As shown); the multi-base array collaborative wind generation mode uses multiple standardized relay units 20 arranged in an array, each standardized relay unit 20 relays the airspace soft wall to work together to generate light winds or gusts covering a wider area;

[0078] The quantum-classical hybrid decision-making hub 104, based on a digital twin Earth model, aims to maximize the global livability index and coordinate the control of various modules. The livability index is composed of a weighted average of multiple sub-indices, including winter comfort, summer comfort, precipitation temperature, and humidity.

[0079] The Extreme Weather Early Intervention Module 105 is used to identify the precursor cloud structure of typhoons, rainstorms, blizzards, hail, and thunderstorms in advance during the precursor cloud stage before the energy of extreme weather systems has significantly accumulated. This is achieved through a categorized precursor cloud identification standard. The precursor cloud intervention strategy is then used as the primary strategy to try to transform extreme weather events into winds and stable precipitation below a preset level. Figure 25 As shown, the embryonic stage remedial intervention after missing the prelude cloud window is used as a backup plan, and it has the joint prevention and control capability to deal with multiple types of extreme weather concurrently. It works in conjunction with the climate engineering risk management module 106 to form an early prevention and control system covering the entire chain of "prelude cloud identification - prelude cloud intervention - embryonic stage remedial - circuit breaker protection".

[0080] The Climate Engineering Risk Management Module 106 incorporates a quantitative risk assessment matrix, an upper-air environmental disturbance assessment unit, a teleconnection monitoring unit, a cumulative effect early warning unit, and a cross-regional fairness assessment algorithm. It is used to conduct multi-dimensional risk assessments before, during, and after interventions. When the negative climate impact caused by global regulation in any region exceeds a preset threshold, it triggers circuit breaker or compensatory regulation.

[0081] The human supervision interface module 107 is used to receive decision instructions from the human supervision layer 108 and automatically switch the system's operating mode according to preset human intervention trigger conditions.

[0082] To clearly demonstrate the global climate coordinated regulation system based on a multi-level relay network of the present invention, the technical solution of the present invention will be described in detail below.

[0083] 1. Overall System Architecture

[0084] The system of this invention comprises a global thermal balance regulation module 101, a multi-level cloud cluster regulation network module 102, a light wind and gust generation subsystem 103, an artificial shading cloud application module 109, a quantum-classical hybrid decision-making center 104, an extreme weather early intervention module 105, a climate engineering risk management module 106, a human supervision interface module 107, and optional habitable zone dynamic evolution unit 110 and global carbon cycle collaborative management module 111. All modules operate collaboratively under the unified scheduling of the quantum-classical hybrid decision-making center 104, forming a complete climate regulation capability spectrum from local to global, and from source prevention to end-of-pipe control.

[0085] The system adopts an "AI-controlled, human-supervised" model. Daily operations are handled entirely by AI, while major decisions are approved by a human oversight layer. Human intervention is automatically triggered when safety thresholds are reached. The system feeds real-time monitoring data back to the quantum-classical hybrid decision-making center 104 to form a closed-loop optimization control system.

[0086] The system of this invention attempts to establish an energy efficiency philosophy of "prioritizing natural forces, structural gains, and source location" at the design level. During air mass transport and regulation, natural driving forces such as the chimney effect, gravity sinking, and buoyancy rising are prioritized to complete the vertical transport and horizontal movement of air masses. Where enhanced functionality is required, passive gains are achieved through geometric structural design, including but not limited to Venturi contraction acceleration, adjustable guide structures at pipe outlets, porous diffusers, adjustable grids, guide vanes, and Venturi-like arrays formed by clusters of micro-units. Active energy consumption units, including heat exchange units, condensation nucleus dissemination units, and charge regulation units, are only activated when structural means cannot meet regulation requirements. This energy efficiency philosophy strives to keep the system's active energy consumption at a low level.

[0087] 2. Quantum-Classical Hybrid Decision Center 104

[0088] The quantum-classical hybrid decision-making center 104 adopts a multi-level computing architecture combining quantum and classical approaches, such as... Figure 11 As shown, from top to bottom, it is divided into a human supervision layer 108, a hybrid interface layer 112, a quantum computing layer 113, and a classical supercomputing layer 114. The quantum computing layer includes two sub-layers: a quantum inspiration layer 1131 and a quantum acceleration layer 1132.

[0089] The quantum-inspired layer 1131 deploys parallel exploration algorithms, scanning global atmospheric data around the clock (processing over 100TB daily) to identify energy anomalies, candidate preludes, polar risks, etc., with early warnings possible more than 14 days in advance. This layer employs the tensor network method—a mathematical framework that decomposes high-dimensional data into multiple low-dimensional tensor products—capable of efficiently simulating quantum algorithms on classical computers, improving computational efficiency by 2-3 orders of magnitude. The quantum acceleration layer 1132 deploys quantum optimization algorithms, replacing traditional Gaussian processes with quantum kernel functions, improving the search efficiency of high-dimensional parameter spaces by 2-3 orders of magnitude. The classical supercomputing layer runs high-resolution atmospheric circulation models with a resolution of 1-10km and 50-100 vertical layers, fusing intelligent micro-unit sensing data for four-dimensional variational assimilation, improving prediction accuracy by more than 30% compared to traditional methods. The hybrid interface layer 112 enables real-time task scheduling and data collaboration between computing units at all levels, forming a closed-loop verification. The Human Oversight Layer 108 consists of a 21-member interdisciplinary expert group that exercises approval authority over major decisions such as regulation of ecologically sensitive areas, cross-seasonal intervention, polar protection, and fairness review.

[0090] Quantum computing has a solid technological foundation for applications in meteorology. In 2013, Academician Pan Jianwei's team at the University of Science and Technology of China achieved the world's first experiment using a quantum computer to solve a system of linear equations, with results published in *Physical Review Letters*. Weather forecasting is a typical application scenario requiring the establishment and solution of linear equations containing millions of variables—solving an equation system with 100 trillion variables would take traditional supercomputers hundreds of years, while a quantum computer could do it in just 10 seconds. In 2024, a research team led by Pan Jianwei, Dou Xiankang, Zhang Qiang, and Xue Xianghui achieved the world's first open-atmosphere dual-comb spectral measurement at a scale of hundreds of kilometers, providing a revolutionary means for global-scale greenhouse gas monitoring and precise calibration.

[0091] The livability index is a weighted average of three sub-indices: winter comfort, summer comfort, and precipitation temperature. Winter comfort is indicated by the average temperature of the coldest month, with a baseline temperature of 18°C; summer comfort is indicated by the average temperature of the hottest month, with a baseline temperature of 24°C; precipitation temperature is indicated by the frequency and intensity of extreme precipitation events. The selection of 18°C ​​for winter is based on the actual accessibility of the outdoor environment and the human body's adaptive clothing for winter (approximately 0.9 clo). The selection of 24°C for summer is based on a reasonable outdoor extension of the summer operating temperature range in international standards ISO 7730 and ASHRAE Standard 55. The Quantum-Classical Hybrid Decision Center 104 aims to "maximize the global livability index under the premise of stable growth of the polar ice cap." It adopts the principle of "relative optimization," allowing different regions to maintain preset temperature preference differences based on their own climate baselines, while respecting the different regions' preferences for precipitation time periods, precipitation phases, and other local customs and preferences. According to the theory of adaptive thermal comfort, the human body adapts physiologically and behaviorally to its long-term climate environment, and people from different climate zones and cultural backgrounds have significant differences in their temperature preferences. Therefore, the system of this invention does not pursue a globally uniform ideal temperature, but allows for the expression of preferences such as the preference of residents in tropical regions for relatively high temperatures and the preference of residents in high-latitude regions for snowfall.

[0092] The human-machine collaboration in layer 108 employs a three-tiered decision-making authority system. (See also...) Figure 14 The AI ​​autonomous decision-making layer is responsible for routine operations such as optimizing daily operating parameters, dynamically adjusting relay paths, and starting and stopping near-ground wind generation at single bases, with a response time of milliseconds to seconds. The AI ​​suggestion + human confirmation layer is responsible for major matters such as the initial deployment of relay units, the use of polar cold resources, large-scale shading deployment, prelude cloud intervention, daytime shading + daytime precipitation coordinated cooling, and joint prevention and control. The AI ​​generates no fewer than three candidate solutions with probability prediction results, with a response time of minutes to hours. The human expert decision-making layer is responsible for system architecture changes, international compliance reviews, cross-regional fairness dispute adjudication, emergency shutdowns, and accident investigations, with a response time of hours to days. Human intervention trigger mechanisms include anomalies in polar ice cap monitoring, a continuous decline in the regional habitability index, unexpected disturbances in non-target areas, large-scale disconnection of intelligent micro-unit clusters, cloud transport processes triggering circuit breakers, abnormal signals in teleconnection sensitive areas, and cumulative effect indices exceeding warning levels.

[0093] 3. Global thermal balance regulation module 101

[0094] This module aims to provide cooling in summer and heating in winter, with the stability of the polar ice cap as a hard constraint.

[0095] 3.1 Adopting a sequential transfer mechanism

[0096] Unlike traditional direct two-point heat exchange, this invention employs a sequential transfer mechanism, allowing heat to be transferred gradually along a horizontal latitudinal gradient. The first stage collects hot air from high-temperature regions, extracts some heat through a heat exchange unit for local use, and transports the remaining heat to mid-temperature regions. The second stage transfers heat to high-latitude, low-temperature regions, achieving a heat utilization rate of 40-50%. The third stage transports the remaining heat to the polar edges for precise temperature control. The overall heat utilization rate is 60-80%, with surface temperature differences at each stage controlled within 2-3°C. It is important to note that the term "sequential" here refers to the surface temperature differences between adjacent geographical areas during the horizontal, latitudinal transfer of heat, not the environmental temperature differences between different altitudes during vertical relay transfer.

[0097] 3.2 Layered Path Strategy Based on Cold and Hot Air Bulk Transport

[0098] This is a key step in understanding the technical solution of this invention; see [link / reference]. Figure 5 As shown. It should be noted first that the long-distance transport path for hot and cold air masses described in this invention is the third priority scheme when source-level regulation and adjacent transport cannot meet the requirements. Under general cooling or heating needs, the system prioritizes the source-level regulation mode (see 3.5 below), and only activates the long-distance transport path when neither source-level regulation nor adjacent transport is feasible.

[0099] The complete transport of cold and warm air masses is not completed at a single altitude level, but rather employs a stratified strategy: long-distance horizontal transport uses the lower stratosphere as a stable channel, while terminal release utilizes the lower troposphere as an effective window. Cold and warm air masses, due to their drastically different temperature characteristics, utilize different main horizontal transport channels.

[0100] 1) Transport path and distance-based strategy of cold air masses

[0101] Cold air masses (temperatures ranging from approximately -15°C to -60°C, depending on season and region) are collected from near-surface polar regions and lifted into the lower stratosphere (approximately 12-25 km) via a vertical relay chain. The lower stratosphere is an inversion layer, dominated by horizontal movement with almost no vertical convection, and the air is dry and clean. Due to the extremely small temperature difference between polar cold air masses (especially those below -40°C) and the stratospheric environment (approximately -50°C), the heat loss from the air masses to the environment is minimal, resulting in very low energy consumption for transport.

[0102] Cold air masses do not maintain a constant altitude during their transport over thousands of kilometers. Due to their low temperature and high density, they descend slowly under gravity, with a typical descent rate of approximately 0.1-0.5 m / s (actual value after mitigation by environmental turbulence and horizontal wind shear). The system employs differentiated strategies based on the transport distance. For short-distance transport, the descent rate is controlled by soft walls in the relay airspace, ensuring the air mass reaches the target area precisely within the low-cloud release window, eliminating the need for relay lifting. For medium-distance transport, free transport is the primary method, with dynamic cooling and conditioning and fine-tuning of the descent rate in the relay airspace along the route. For long-distance transport, a cyclical relay mode of "transport-descent-conditioning-lifting" is adopted—after the air mass is transported horizontally for a distance in the stratosphere, it gradually descends under gravity. When the air mass approaches the preset lower limit of the safe altitude for that latitude, downstream standardized relay units perform dynamic cooling and conditioning and relay lifting, elevating the air mass back to the lower stratosphere for continued transport.

[0103] Why must a cold air mass move through low cloud regions at its terminus? This choice seems counterintuitive—the ambient temperature in low cloud regions is 10-25℃, a temperature difference of 35-85℃ compared to the cold air mass's -15℃ to -60℃. The answer is: cold air can only exert its cooling effect on the ground due to gravity if it is transported directly above the target area. If released in the mid-cloud region, the adiabatic compression heating during descent would generate a foehn effect, completely negating its cooling function. The system actively cools to counteract ambient heating through heat exchange units; this energy consumption is used to achieve the fundamental engineering goal of "effectively acting on the ground."

[0104] 2) Transport path and buoyancy control of hot air masses

[0105] Warm, moist air masses (temperatures approximately 30-45°C) are collected near the surface of tropical regions and naturally rise to the lower troposphere (approximately 2-8 km) driven by a combination of buoyancy and the chimney effect of expansion channels. Why not use stratospheric transport? Stratospheric temperatures are too low (approximately -50°C), with temperature differences as high as 80-95°C, making insulation energy consumption unacceptable. The ambient temperature in the lower troposphere is approximately 0 to -20°C, with temperature differences reduced to 30-65°C. Why not travel through low cloud regions? If warm air masses travel through low cloud regions, they would mix with surface turbulence due to unstable buoyancy, making directional transport impossible.

[0106] The transport of hot air masses also faces physical challenges. Due to their significantly higher temperature and lower density compared to ambient temperature, they rise slowly and continuously under buoyancy, with a typical ascent rate of approximately 0.2-0.8 m / s. The system addresses this by utilizing the bidirectional control capability of the soft wall in the relay airspace: the soft wall can generate lifting force through heating at the bottom and downward pressure through slight cooling at the top, thus controlling the ascent rate within a safe range. Simultaneously, a "maximum permissible height" is set as a hard constraint.

[0107] 3) Physical isolation and cross-control of cold and warm air mass transport channels

[0108] Cold air masses are transported in the lower stratosphere, while warm air masses are transported in the middle and lower troposphere, maintaining a sufficient vertical safety distance between them. When a cold air mass needs to descend and cross the transport level of a warm air mass, safety control is achieved through temporal or spatial staggering. If staggering is not possible, the transport of one side is suspended. When unexpected proximity of cold and warm air masses is detected, the system responds according to priority: avoidance, active intervention, and circuit breaker.

[0109] 4) Closed-loop design for combined cooling and heating and water-heat balance

[0110] The system coordinates three major tasks: transporting cold polar air masses, delivering precipitation from warm, humid air masses in habitable zones, and warming the regulated air masses, forming a complete thermodynamic-water vapor cycle. This closed loop fully utilizes the Earth's own gravitational field, pressure field, and solar radiation as driving forces.

[0111] 3.3 Air mass temperature characteristics and differentiated transport strategies

[0112] The temperature of cold air masses collected in the polar regions varies greatly depending on the season and the area where they are collected. In winter, temperatures can reach below -60°C on the East Antarctic Plateau, around -15 to -30°C along the Antarctic coast, around -30 to -50°C at the top of the Greenland ice sheet, and around -25 to -40°C in the Arctic sea ice areas. In summer, the temperature of cold air masses at the polar edges is relatively mild, around -5 to -15°C.

[0113] The long-distance transport of cold air masses at medium and low temperatures (-10 to -20°C) is only applicable in the following special scenarios: the target area is controlled by a warm high-pressure system, resulting in abnormally warm upper troposphere, where the natural low temperatures at altitudes of 6000-10000 meters are insufficient to meet cooling requirements; or there are no available warm and humid cloud masses in the target area, making in-situ precipitation cooling through source-level regulation impossible; or special operations such as frost prevention with dry cold air masses are required (natural cold air at high altitudes usually contains a lot of water vapor, which actually increases the risk of frost formation). Under general cooling requirements, the system prioritizes the in-situ precipitation cooling mode using local warm and humid air masses in source-level regulation—utilizing the chimney effect to draw warm and humid air masses to the mid-to-high altitudes for natural cooling. Temperatures at altitudes of 6000-10000 meters in the target area are usually below -10 to -20°C, sufficient to meet most cooling needs, eliminating the need for long-distance transport of cold air masses of the same temperature level from the polar regions.

[0114] Extremely low temperature cold air masses (-40℃ and below) are suitable for ultra-long-distance transport or as a "cold source" for temperature regulation in multiple regions along the route. Because the temperature difference with the stratosphere is only about 10℃, active cooling is almost unnecessary—the lower the air mass temperature, the easier it is to transport in the stratosphere with low energy consumption. Upon arrival, the air is not released directly but is warmed up to a suitable temperature before being released.

[0115] Warm air masses (30-45℃) are transported in the lower troposphere, and rapid transport strategies can be adopted to reduce cumulative heat loss.

[0116] 3.4 Local Warm and Moist Air Mass In-situ Precipitation and Cooling Pattern

[0117] By utilizing the chimney effect, warm, moist air masses near the city surface are drawn into the mid-to-high atmosphere, where they naturally cool and condense to form clouds, triggering precipitation. The combined effect of low-temperature rainwater and evaporative heat absorption cools the ground. This model simultaneously achieves the triple benefits of urban cooling, air purification, and water replenishment.

[0118] 3.5 Priority Principle of Source-Location Regulation and Comprehensive Regulation Strategy

[0119] The system of this invention establishes a three-tiered energy efficiency optimization principle at the design level: "prioritizing source location control, followed by nearby transportation, and using long-distance transportation as a backup." (See [link to relevant documentation]). Figure 23 Source-based regulation refers to achieving climate control objectives within the target region by utilizing existing natural resources such as cold sources, heat sources, water sources, and cloud sources, without the need for cross-regional transport. Under the premise of meeting the same climate control objectives, the system prioritizes the technical path with the lowest energy consumption, shortest transport distance, and least disturbance to the atmospheric environment.

[0120] 1) Tiered Response to Cooling Demand. First priority is source-level control: Assess whether the target area has the conditions for implementing local warm and humid air mass precipitation and cooling—whether there is a warm and humid air mass near the surface and whether there is a natural low-temperature layer in the mid-to-high atmosphere. If conditions are met, initiate this priority, without any long-range transport. Second priority is adjacent transport: If there is no available warm and humid air mass in the target area, assess whether it is possible to guide the natural descent of cold air from nearby mountains, plateaus, or polar edges to the target area. Utilize relay airspace soft walls to guide and control the descent rate; the transport distance is usually no more than 500 kilometers to prevent the formation of downbursts or foehn effects. Third priority is long-range transport: Only when the first two modes are not feasible will long-range transport of polar cold air masses be initiated.

[0121] 2) Tiered response to heating demand. The first priority is source-level regulation: assessing the potential for collecting industrial waste heat, geothermal resources, and urban heat island effects in the target area. This involves collecting near-surface warm air using expansion pipes, temporarily storing it in relay airspace, and releasing it during the nighttime low-temperature period; or, when an inversion layer exists, locally guiding upper-layer warm air to the ground. The second priority is adjacent transport: assessing whether warm air masses from nearby low-latitude regions can be transported to the target area over a short distance. The third priority is long-distance transport: initiating long-distance transport of warm air masses only when the above modes are not feasible.

[0122] 3) Source-level control of humidification and drying requirements. Humidification requirements are assessed by prioritizing the evaporation potential of the target area and adjacent water bodies, utilizing the chimney effect to lift water vapor to the mid-to-low altitudes to form a moist air mass. Drying requirements are assessed by prioritizing the presence of a dry, cold air layer in the upper atmosphere of the target area, using a relay airspace soft wall to guide the controlled descent of dry air, strictly controlling the descent rate to avoid the formation of foehn winds.

[0123] 4) Safety Protection During Source Location Control. All source location control operations operate within the framework of the system's four-layer safety protection system. The following additional protective measures are implemented: Downdraft Rate Control – When guiding cold or dry air down, the downdraft rate is controlled within a safe range using a relay airspace soft wall to prevent downbursts or foehn effects caused by excessively rapid descent; Precipitation Intensity Control During Humidification Operations – During on-site humidification, cloud droplet size and release height are controlled through a three-stage process to prevent excessive humidification from triggering heavy rainfall; Convection Suppression During Heat Collection Operations – When collecting industrial waste heat or urban heat island heat, soft wall constraints prevent hot air from rising too quickly and triggering local convection; Stable Maintenance of Inversion Layer Guidance – When guiding warm air down from the inversion layer, the overall stability of the inversion layer is ensured not to be disrupted.

[0124] 4. Light Breeze / Gust Generation Subsystem 103

[0125] The breeze and gust generation subsystem 103 is one of the core innovative modules of this invention. It is essentially a "natural force collector" that collects and amplifies the three driving forces that already exist in nature.

[0126] The primary driving force is the chimney effect for air intake and adiabatic cooling. A natural temperature difference of 3-6°C exists between the ground and hundreds of meters above the ground, leading to a difference in air density and creating a vertical pressure gradient force. When the telescopic duct extends vertically, the air inside is heated by the ground, reducing its density, and under the drive of the pressure gradient force, it generates a continuous upward buoyancy, drawing air in. The intake process causes air around the bottom of the duct to flow inwards—the intake process itself generates wind, requiring no electrical power. The hot air drawn into the duct cools during its ascent due to adiabatic expansion. The duct outlet uses a converging configuration, such as... Figure 8 As shown, based on the principle of continuity and Bernoulli's equation, the outlet wind speed accelerates to 8-20 m / s. In a preferred implementation, an adjustable-angle guide head can be installed at the duct outlet to directly guide the high-speed airflow towards the ground. The airflow impacts the ground at a certain angle and then diffuses horizontally in all directions, creating a comfortable breeze covering a certain area. Part of the diffused airflow is then re-inhaled through the duct bottom under the chimney effect, forming a local closed-loop cycle of "suction-acceleration-guidance-diffusion-re-suction". This closed-loop design further improves wind generation efficiency, while the guide head is merely a geometric extension of the duct outlet and does not consume additional electrical energy. The high-speed airflow further reduces the perceived temperature due to the wind-cooling effect, ultimately creating a comfortable, cool breeze.

[0127] The second driving force is passive aerodynamic acceleration, achieved through pipe geometry without additional electrical energy. The third driving force is gravitational sinking and thermal buoyancy, with zero active energy consumption in this stage.

[0128] The subsystem supports three deployment modes. Mode 1 is remote air generation, utilizing a multi-level relay network to transport cold and warm air masses from polar regions or remote areas for large-scale air generation. Mode 2 is single-site near-ground air generation, using only one standardized relay unit 20 deployed near the ground (100-500 meters altitude) in the target area. The macroscopic telescopic duct 202 outlet can be equipped with a guide head to form a closed loop, suitable for precise, targeted air delivery, such as... Figure 7 As shown. When large-scale open air supply or directional dispersion of pollutants is required, the guide head can be retracted or the guide angle adjusted to a horizontal direction. The guide head can be combined with passive structures such as porous diffusers and adjustable grids according to actual needs. Mode 3 is a multi-base array collaborative wind generation, with multiple standardized relay units 20 arranged in an array. Each unit works together to generate light winds or gusts covering a wider area. After the micro-unit cluster is released from the base, it ascends to the airspace near the outlet of the upper extension section to form a soft wall array. The outlet of each base duct adopts a horizontal or slightly downward inclined diffusion configuration. The spacing between bases, the array shape, and the outlet angle are dynamically optimized by the decision center according to the terrain and wind field requirements of the target area. Mode 3 is suitable for scenarios requiring large-scale ventilation and cooling, pollutant dispersion, and combined ventilation in agricultural areas. Through multi-base collaboration, the coverage of a single base can be extended to a wider area.

[0129] The air generation methods include descending and diverging cold air masses, rising and drawing in warm air masses, guiding airflow through relay airspace soft walls, and passive aerodynamic acceleration. Gusts are achieved through valve pulsation, alternating release, intermittent release, and artificial turbulence. Application scenarios cover urban cooling and ventilation, smog removal, heat island circulation, agricultural ventilation, frost prevention, pollination assistance, and pollutant dispersion in industrial areas.

[0130] 5. Multi-level cloud cluster control network module 102

[0131] 5.1 Standardized Relay Unit 20

[0132] The space-based AI mobile base 201 and the macroscopic telescopic pipeline 202 are integrated into a standardized relay unit 20, serving as an independent, self-sustaining operating platform. Depending on mission requirements, 500-1000 units can be deployed globally, forming relay chains along meridians or parallels. Based on atmospheric circulation characteristics and climate zone distribution, approximately 80-120 major relay chains need to be constructed globally, with denser deployment in key climate zones such as the Intertropical Convergence Zone, monsoon regions, and mid-latitude cyclone paths, and moderately sparse deployment in uninhabited ocean and polar regions. Each relay chain consists of 15-30 standardized relay units deployed at different altitudes, covering a vertical range from the ground to the stratosphere (see [reference needed]). Figure 4 and Figure 6 .

[0133] The macroscopic telescopic duct 202 employs a multi-level nested telescopic structure as a preferred implementation: its total length in the extended state is approximately 1000 meters, and it can be completely stored inside the base when retracted. The duct's inner diameter is designed in multiple specifications according to mission requirements: smaller diameters (30-50 meters) are used for localized wind generation and localized precipitation; medium diameters (50-100 meters) are used for regional cloud cluster control and maintaining shading clouds; and larger diameters (100-200 meters) are used for prelude cloud capture and long-range air mass transport. The duct uses a hexagonal honeycomb composite structure, with carbon fiber and titanium alloy composite materials, achieving a high axial folding ratio while ensuring strength.

[0134] 5.2 Lifting Body Configuration Design of the Space-to-Air AI Mobile Base 201

[0135] The Space-Based AI Mobile Base 201 adopts a lifting body configuration, featuring a high lift-to-drag ratio and rotational symmetry in its aerodynamic shape. As a preferred embodiment, its shape is a flat, disc-shaped or saucer-shaped fuselage, commonly known as a flying saucer, with a smoothly transitioned upper convex and lower flat curved surface, and streamlined, narrowing edges. The base has a diameter of approximately 200-500 meters and a central thickness of approximately 50-80 meters, with a central vertical through-passage to accommodate macroscopic telescopic pipes, forming a "hollow, thick disc" configuration. The base has a spacious interior, allowing for the arrangement of multiple cloud processing chambers and curved flow paths.

[0136] In terms of aerodynamic advantages, the airflow velocity increases and the pressure decreases as it flows over the upper surface of the lifting body, creating a significant wall-attachment lift due to the pressure difference between the upper and lower surfaces. The optimized lifting body configuration achieves a lift-to-drag ratio of 17-25 at moderate angles of attack, reducing cruise energy consumption by more than 40%. The lifting body's rotational symmetry ensures its aerodynamic characteristics remain unchanged regardless of the incoming flow direction, eliminating the need for active wind adjustments and significantly reducing control energy consumption.

[0137] In terms of structural advantages, multiple vector ducted thrusters can be embedded inside the lifting body casing, forming a fully ducted design. Airflow is accelerated within the duct, resulting in stronger thrust, lower noise, and no exposed blades. The lifting body has ample internal space, allowing for the installation of thin-film photovoltaic conversion components 204 on the upper surface, and the arrangement of buoyancy adjustment structures, such as... Figure 2 The buoyancy regulating chamber 203 shown forms an integrated buoyancy structure, which can achieve stratospheric stay for 5-10 years.

[0138] The base possesses the capability to autonomously return to its ground base. The ground base is not only a maintenance and repair site but also a ground support hub for the system—providing energy replenishment (including nuclear fuel replacement, solar panel cleaning and maintenance, and energy storage system testing), material resupply (condensation nuclei, coolant, and other consumable materials), and centralized charging and maintenance for the intelligent micro-unit clusters. When completing a phase of its mission or requiring resupply, the base fully retracts its telescopic pipes and glides back to its ground base in a high lift-to-drag ratio aerodynamic configuration. After completing maintenance, resupply, and charging, it can be redeployed to a designated airspace. This closed-loop operation and maintenance system of "stay-and-return-resupply-maintenance-redeployment" ensures reliable operation throughout the system's decades-long lifecycle. Figure 28 As shown.

[0139] 5.3 Quick-connect / Quick-disconnect interface and anchoring system

[0140] The standardized relay unit 20 has an integrated quick-connect port at the bottom, such as... Figure 9 As shown, a multi-claw self-locking chuck design is adopted. A conical guide cone is located at the center of the interface, with a laser rangefinder and visual recognition marker installed at the tip. A rope end connector is located at the top of the traction rope, with an integrated fiber optic communication interface and power contact ring at the center of the rope end. The ground anchoring system includes a rope end delivery vehicle and a heavy-duty anchoring traction vehicle, working in three coordinated phases: connection phase, operation phase, and disengagement phase.

[0141] 5.4 Four-Level Collaborative Perception Architecture

[0142] See Figure 12 The space-based sensing layer deploys a constellation of satellites with onboard intelligent processing capabilities, carrying on-orbit AI models. Remote sensing data is analyzed in real-time on-orbit, reducing data processing latency from minutes to seconds. Satellites are interconnected at high speed via laser links, enabling macroscopic identification of remote sensing data (accuracy >85%).

[0143] The front-end sensing layer (intelligent micro-unit cluster) is equipped with GPS / BeiDou + relative positioning, lidar, optical particle counter, miniature thermistor, capacitive humidity sensor, MEMS barometer, hot-wire anemometer, inertial measurement unit, miniature electric field sensor, etc. for each unit.

[0144] The mid-level fusion layer (Aerospace AI Mobile Base 201) is equipped with Doppler radar, lidar, infrared imager, atmospheric profiler, atmospheric electric field meter, and hyperspectral imager. The base fuses local observations of micro-unit clusters with its own long-range detection data to obtain cloud state estimates with position errors of <10 meters and velocity errors of <0.5 meters per second.

[0145] The backend decision-making layer receives all the sensing data, uses Kalman filtering to fuse multi-source data, and predicts the trajectory of the cloud cluster in the next 30-60 minutes.

[0146] 5.5 Multi-stage aerodynamic handling unit and precipitation pre-programming

[0147] The space-based AI mobile base 201 is equipped with seven independent and activatable processing levels (L1-L7), such as... Figure 6 As shown, they are: L1 eddy current pre-breakup unit, L2 passive pneumatic atomization unit, L3 porous plate micronization unit, L4 jet counter-impact unit (using the chimney effect to drive a pressure difference of about 12,000 Pa to achieve zero additional power consumption), L5 heat exchange unit (heating rate 5-10℃ / min, cooling rate 3-5℃ / min), L6 condensation nucleus dissemination unit (significantly improving nucleation efficiency and greatly reducing the amount of nucleating agent used), and L7 charge control unit (can reduce collisions by 80% or increase collisions by 2-5 times).

[0148] The L4 jet collision unit features a symmetrically arranged array of jet nozzles inside a telescopic duct. Utilizing the chimney effect pressure difference, it accelerates the airflow to subsonic speeds. Multiple airflows collide with each other at a preset angle in the central region of the duct. The collision zone generates an extreme turbulent shear field and instantaneous pressure fluctuations. Under the action of shear force and pressure fluctuations, cloud droplets undergo secondary bursting, further pulverizing from 10-50 μm to 0.5-5 μm.

[0149] The L5 heat exchange unit employs a large-area thin-film thermoelectric material array laid on the inner wall of the pipe, achieving bidirectional heating / cooling control based on the Peltier effect. The total area of ​​the thin-film thermoelectric material can reach tens of thousands of square meters, with a total heat exchange power of 2-4MW. Combined with airflow turbulence mixing and a staged series design, it achieves rapid and uniform temperature control of the air mass. For scenarios requiring higher energy efficiency ratios or more precise temperature control, novel solid-state refrigeration technologies (such as high-efficiency thin-film thermoelectric arrays, electrocaloric refrigeration, etc.) can be selected as the preferred direction for the technological iteration of this unit.

[0150] The L6 condensation nucleus seeding unit pre-forms condensation nuclei into ultra-fine particles, which are then directly injected into temperature- and humidity-conditioned clouds via a multi-point injection array. This creates a localized, transient supersaturated environment, rapidly activating the nuclei. The type of seeding agent is selected based on the target precipitation phase: hygroscopic nuclei are seeded for rain, while ice-nucleated active substances are seeded for snow.

[0151] The L7 charge control unit applies a controllable charge to cloud droplets through an array of ionizing electrodes. When the same charge is applied, Coulomb repulsion is used to suppress collisions between cloud droplets; when the opposite charge is applied, Coulomb attraction is used to accelerate collisions between cloud droplets. The electric field strength and the amount of charge are adjustable.

[0152] Precision control of precipitation intensity employs a three-stage process: particle size pre-setting, altitude adjustment, and time-based control. In the particle size pre-setting stage, heavy rain uses only L1 particles with large nuclei, moderate rain uses L1+L2 particles with organic nuclei, and light rain uses a full range of particles with fine nuclei. In the altitude adjustment stage, heavy rain is released in high-cloud areas, moderate rain in mid-cloud areas, and light rain in low-cloud areas. In the time-based control stage, relay airspace storage enables daytime rain avoidance, nighttime water replenishment, staggered release, emergency response, and differentiated scheduling based on daytime cooling precipitation, nighttime water replenishment precipitation, and public preferences.

[0153] The relationship between cloud droplet size and precipitation intensity is based on the classic theory of cloud microphysics—the collision-coalescence growth model. Precipitation intensity depends on the collision-coalescence growth rate of cloud droplets during their descent, which is determined by the initial cloud droplet size spectrum. Cloud droplets with an initial size of 20-50 μm have a large collision cross-sectional area and a fast settling velocity, resulting in efficient collision-coalescence during descent and rapid growth into raindrops, forming heavy rain. Cloud droplets with an initial size of 5-20 μm have a moderate collision cross-sectional area and settling velocity, resulting in moderate collision-coalescence efficiency, forming moderate rain. Cloud droplets with an initial size of 0.5-5 μm have a small collision cross-sectional area and a slow settling velocity, resulting in insufficient collision-coalescence growth, forming light rain. The secondary regulation by release height is based on the difference in collision-coalescence growth time of cloud droplets descending from their release height to the ground: cloud droplets released from high-cloud areas have a longer descent path, resulting in sufficient collision-coalescence growth; cloud droplets released from low-cloud areas have a shorter descent path, resulting in insufficient collision-coalescence growth.

[0154] The system can flexibly select precipitation periods based on the actual needs of the target area. In general water resource replenishment scenarios, nighttime rainfall is prioritized to minimize the impact on daytime production and daily life. In extreme summer heat and cooling scenarios, daytime rainfall mode is activated, and it is prioritized for coordinated deployment with shading clouds. At the same time, the system fully respects the local customs, industrial characteristics, and cultural preferences of different regions, supporting flexible customization of precipitation periods. When formulating precipitation plans, the Quantum-Classical Hybrid Decision Center 104 comprehensively considers climate needs, industrial characteristics, and local preferences, adapting to local differentiated needs as much as possible while meeting the overall goal of "favorable weather."

[0155] The precipitation phase is ensured by an ice crystal formation layer, continuous cooling, and a near-surface cooling pad to achieve rain / snow switching. The snowfall preferences of different regions are also fully respected.

[0156] During intervention in prelude clouds, not all L1-L4 processing levels are activated. Instead, the decision-making center dynamically selects to activate one, two, three, or four types, or bypass all of them (i.e., activate zero types), depending on the specific type, development stage, and energy state of the prelude cloud. Typical L1-L4 activation strategies for each type of prelude cloud are as follows:

[0157] 1) Prelude to thunderstorms and strong winds: L1 and L4 are activated. L1 is slightly broken up to maintain the inertia of cloud droplets, while L4 jet collision generates a turbulent shear field to suppress the concentration of descending airflow.

[0158] 2) Prelude clouds to heavy rain: L1, L2 and L3 are activated. They break down into particles of 1-10 μm, broadening the precipitation particle spectrum and transforming heavy rain into mild precipitation.

[0159] 3) Hailstorm Prelude Cloud: Activate L1 and L2. Moderately break up to 5-20μm, and use L7 charge regulation to inhibit hail embryo growth.

[0160] 4) Blizzard Prelude Cloud: All bypasses (0 types). Maintain larger ice crystals to preserve snow crystal structure, and intervene only through L5 temperature regulation and L6 ice core seeding.

[0161] 5) Typhoon precursor clouds: L1 and L2 are activated. Moderately fragmented, combined with external intervention measures such as convective competitive dispersal and sea surface cooling.

[0162] 6) Prelude to Concurrent Events (Heavy Rain + Strong Winds): Activate all 4 types (L1+L2+L3+L4) to achieve comprehensive conditioning.

[0163] This flexible control mechanism ensures the precision and energy efficiency of the intervention—achieving the best intervention effect with minimal cloud disturbance and avoiding energy waste or unexpected side effects caused by excessive fragmentation.

[0164] 5.6 Intelligent Micro-unit Cluster and Bee Colony Rotation Mechanism

[0165] A single deployment can reach thousands of units, with swarm rotation ensuring continuous operation. The intelligent micro-unit cluster employs an "air-ground" dual-base mode for charging and maintenance. During routine operations, micro-units return to the maintenance bay of the Space AI Mobile Base 201 for rapid charging (10C fast charging, reaching 80% in 6 minutes). While Space AI Base 201 returns to the ground base for resupply, the micro-unit cluster can undergo deep charging, comprehensive condition checks, and component replacement at the ground base. The ground base is equipped with a large-scale charging array and maintenance workshop, capable of simultaneously charging and maintaining tens of thousands of micro-units in batches. This dual-base mode ensures the continuous availability of the micro-unit cluster during high-intensity, long-cycle operations.

[0166] The intelligent micro-unit cluster adopts a serialized and modular design, and is divided into various dedicated models according to task requirements, such as... Figure 10As shown, the Sensing Type (Type A) is equipped with a miniature sensor array for pre-cloud identification and ecological monitoring, boasting the lowest power consumption and longest endurance; the Spreading Type (Type B) features a replaceable catalyst payload chamber for precise dissemination of condensation nuclei; the Soft Wall Type (Type C) is equipped with high-power pulse heating / cooling elements for maintaining intermittent temperature gradients at the airspace edge, exhibiting high peak power but extremely low duty cycle, resulting in controllable average power consumption; the Guiding Type (Type D) is equipped with directional heating and vector thrusters for guiding cloud paths; the Hydration Type (Type E) is equipped with water vapor collection and atomization devices for dynamic hydration of shading clouds; and the Communication Relay Type (Type F) is equipped with a laser communication terminal for cross-spatial data transmission. All models utilize a unified communication protocol, positioning interface, and charging specifications, allowing for flexible deployment combinations based on mission requirements. A swarm rotation mechanism is universal across all models, ensuring uninterrupted operation for different micro-unit types.

[0167] A standardized intelligent micro-unit cluster configuration may include: approximately 40% type A sensing units, approximately 25% type B dissemination units, approximately 20% type C soft wall units, approximately 5% type D guiding units, approximately 5% type E water replenishment units, and approximately 5% type F communication relay units. However, this is not a limitation; in actual tasks, the proportions of each type can be dynamically adjusted by the quantum-classical hybrid decision center 104 according to the task type.

[0168] 5.7 Relay Airspace Principle

[0169] The relay airspace is a functional spatial concept, whose location and scale can be flexibly adjusted according to the type of mission. For example... Figure 13 As shown, in long-range cloud transport missions, the relay airspace is typically located between standardized relay units, with a horizontal scale of 20-50 kilometers and a vertical thickness of 500-2000 meters. In multi-base array coordinated wind-generating missions, after being released from the base, the micro-unit cluster ascends to the airspace near the outlet of the upper telescoping section, forming a soft wall. The soft walls at each base work together to generate light winds covering a wider area. The micro-unit cluster generates a temperature gradient field through intermittent pulsed local heating or cooling to constrain cloud diffusion and possesses bidirectional control capabilities, such as... Figure 24 As shown.

[0170] The relay airspace soft wall does not rely on a "hard barrier" to constrain cloud clusters, but rather utilizes the density stratification and buoyancy effect of the atmosphere itself. Micro-unit clusters intermittently pulse-heat the airspace edge, generating an edge temperature gradient of approximately 0.5-2°C. According to the ideal gas law and the principle of hydrostatic equilibrium, this temperature difference produces a density difference of approximately Δρ / ρ≈ΔT / T≈2 / 300≈0.67%. Although seemingly small, this density difference, acting on an air mass on a horizontal scale of tens of kilometers, generates a binding force sufficient to significantly weaken the outward diffusion tendency of the air mass. As the air mass diffuses towards the edge, it encounters slightly lower density regions, and its outward diffusion driving force is greatly weakened. Simultaneously, the micro-unit clusters work alternately within the airspace through multiple heating and cooling points, forming artificial small-scale convective circulation. The air mass moves slowly within these circulations, and its kinetic energy is naturally dissipated through internal friction and turbulent mixing.

[0171] 5.8 Systematic Application of the Venturi Effect

[0172] The macroscopic expansion and contraction of the pipe outlet of the 202 achieves passive acceleration of the airflow; the L2 atomizing unit uses a contraction-expansion flow channel to achieve zero additional electrical energy breakup of cloud droplets; the micro-units are arrayed to form a Venturi-like array to enhance constraint.

[0173] 5.9 Security Management of Remote Cloud Transmission

[0174] During the long-range transport of cloud clusters, the transported cloud clusters may intersect with native high-altitude clouds, triggering an ice crystal effect. The system of this invention ensures safety through a four-layer protection system: the first layer is prediction and avoidance, setting a minimum permissible altitude for cold air masses and a maximum permissible altitude for warm air masses; the second layer is active intervention, including pre-treatment, temperature control, and charge management; the third layer is enhanced monitoring, including space-based encryption and real-time data from micro-units; the fourth layer is a fuse response, automatically stopping transport and initiating a dissipation procedure when radar echoes increase or exponentially rise. The cold / warm channels are vertically physically isolated, and their descent is staggered in time or space.

[0175] It should be noted that not all strong winds have identifiable precursor clouds. Systemic strong winds, such as northerly winds following cold fronts and persistent strong winds on the periphery of extratropical cyclones, are directly driven by large-scale pressure gradient forces. Their formation process does not depend on cloud organization, and therefore, no precursor clouds are identifiable. For strong wind types with identifiable precursor clouds, such as thunderstorm winds, squall lines, and strong winds on the periphery of typhoons, the system prioritizes intervention using precursor clouds to mitigate the winds at their source.

[0176] 6. Artificial Shading Cloud Application Module 109

[0177] The artificial shading cloud application module 109 achieves long-term maintenance through a three-pronged technology of "soft wall constraint - dynamic water replenishment - particle size control," such as... Figure 18As shown. Soft wall constraint reduces the horizontal diffusion rate of clouds by 60-80%. Dynamic water replenishment continuously extracts water vapor from oceans, lakes, industrial cooling towers, and agricultural irrigation areas for atomization replenishment. Particle size control keeps cloud droplets within 0.5-5μm and suppresses collisions and coalescence by like charges, reducing the self-consumption rate by 70-90%.

[0178] The collaborative deployment mode supports differentiated selection of daytime and nighttime precipitation strategies. The daytime precipitation strategy is suitable for emergency cooling in extreme heat, with shading clouds and precipitation working simultaneously; the nighttime precipitation strategy is suitable for water resource replenishment needs, with shading clouds reducing heat accumulation during the day and precipitation starting at night.

[0179] A year-round operational workflow has been established for polar ice cap protection. Threat monitoring covers surface melt pool area, ice shelf shear stress, ice flow velocity, and albedo. Priority protection areas are identified based on vulnerability maps. Cloud deployment utilizes polar stabilization stratification in conjunction with locally sourced sea salt. Soft walls are reinforced or temporary cloud formations are stored during cyclone passage. Seasonal strategies cover the entire polar day cycle.

[0180] The steady growth of polar ice caps may require a two-pronged approach: "shading to control energy expenditure" and "increasing snowfall." For example... Figure 19 As shown, sunshade clouds reduce solar radiation absorption and slow down the melting rate by increasing the albedo of the ice surface, but they cannot directly increase the mass of the ice sheet. The system of this invention attempts to achieve material accumulation in key polar regions through planned artificial snowfall, forming a synergistic protection with sunshade clouds.

[0181] The initial relatively high-growth phase (0-20 years): During the periods of polar day regression and polar night, water vapor is preferentially obtained from nearby polar seas using the principle of source location regulation. This water vapor is then generated through standardized relay unit 20 to produce snowfall cloud clusters, resulting in relatively high-intensity snowfall in key areas such as near the ice shelf grounding line and ice flow acceleration zones. Shading clouds continue to exert their effect during the polar day, significantly reducing ablation. The overall goal is to shift the polar ice sheet from a net deficit to a net growth.

[0182] Later, gradually stabilizing phase (over 20 years): As the global climate regulation system gradually takes effect and the polar ice cap mass recovers to a certain level, snowfall intensity will gradually decrease, shifting to a stable protection mode primarily maintained by sunshade clouds and supplemented by low-intensity snowfall. This "high at the beginning, low at the end" strategy is an experimental phased approach, and its actual effectiveness requires long-term observation and verification.

[0183] 7. Extreme Weather Early Intervention Module 105

[0184] This module uses cloud-based intervention as the primary strategy, embryonic period rescue as a backup plan, and joint prevention and control to address multiple types of complications.

[0185] CAPE (Convective Available Potential Energy) is one of the core indicators for identifying prelude clouds. CAPE represents the work done by positive buoyancy as an air mass rises in the free troposphere, and is a physical quantity that measures atmospheric instability energy. The higher the CAPE value, the stronger the convective potential: below 1000 J / kg generally indicates weak instability, 1000-2500 J / kg indicates moderate instability, 2500-4000 J / kg indicates strong instability, and above 4000 J / kg indicates extreme instability. In this system, a sudden increase in CAPE is a precursor to extreme weather and also represents the main form of energy required for prelude cloud intervention.

[0186] 7.1 Classification Prelude Cloud Recognition

[0187]

[0188] The prelude cloud classification is shown in the table above, and also combined with Figure 20 When the P_extreme index jumps above the threshold within 30 minutes, an automatic warning is triggered. It should be objectively noted that prelude cloud identification has a certain "false alarm rate"—not all clouds identified as preludes will eventually develop into extreme weather. In real meteorological operations, identifying typhoon preludes (tropical disturbances) is a global challenge; hundreds of tropical disturbances are generated annually, but only about 10-20% ultimately develop into typhoons. The system of this invention minimizes the false alarm rate through multi-source data fusion, multi-member ensemble forecasting, and real-time verification mechanisms, and performs counterfactual analysis before each intervention to avoid unnecessary intervention in cloud clusters that will not develop naturally.

[0189] 7.2 Safe Conditioning and Transportation After Prelude Cloud Capture

[0190] Upon capture, the system immediately performs "de-energization" pretreatment on the prelude cloud passing through the pipeline within the standardized relay unit 20. This involves the L6 condensation nucleus dispersal unit to micro-disseminate condensation nuclei to consume supercooled water droplets, and the L7 charge control unit to neutralize charge separation, thereby reducing its explosive potential. The pretreated prelude cloud exits from the upper section of the pipeline and is confined within a physically isolated "safe container" formed by the soft walls of the relay airspace for further conditioning and transport. The transport path automatically avoids areas with high convective effective potential energy and existing strong convection areas. Arranging the prelude cloud pretreatment within a closed pipeline inside the base unit has significant safety implications: the pipeline provides a controllable environment, and even if an unexpected energy release occurs due to abnormal cloud conditions during pretreatment, it is confined within the pipeline structure and will not mix with the outside atmosphere to trigger a chain reaction. The risk of triggering extreme weather is significantly reduced when the low-energy cloud, after being "de-energized," re-enters the relay airspace for temporary storage and transport. This safety-first logic of "processing within the pipeline first, then temporarily storing in the airspace" is the core design principle of the cloud intervention process in the prelude to the system of this invention.

[0191] 7.3 Prelude Cloud Intervention (Main Strategy)

[0192] The reason why prelude cloud intervention can potentially alter the evolution of large-scale weather systems with minimal energy consumption is based on the nonlinear nature of atmospheric systems. When a system is in a "critical state" (i.e., the prelude cloud stage, before energy has significantly accumulated), a small disturbance can be amplified through a positive feedback mechanism, thus affecting the system's final evolution path. However, it should be noted that "sensitive" does not equal "controllable"—the butterfly effect tells us that a small disturbance may trigger a hurricane or nothing at all. The reliability of prelude cloud intervention needs to be gradually confirmed through more theoretical research and practical verification.

[0193] Taking a pre-storm cloud as an example: the consumption of supercooled water promotes the premature crystallization of supercooled water droplets by seeding silver iodide nuclei within the cloud. A vapor pressure difference exists between the ice crystals and the supercooled water droplets (the saturated vapor pressure at the ice surface is lower than that at the water surface), causing water vapor to transfer from the supercooled water droplets to the ice crystals (the Bergeron process). The ice crystals grow while the water droplets evaporate. This process consumes the cloud's unstable energy (CAPE), and simultaneously, a large number of small ice crystals replace a few large water droplets, altering the spectral distribution of precipitation particles—from "a few large particles rapidly settling to produce heavy rain" to "a large number of small particles slowly settling to produce mild precipitation."

[0194] Taking thunderstorm prelude clouds as an example: charge neutralization, by releasing ions with opposite initial charges within the cloud, suppresses the charge separation process. Charge separation is the root cause of strong electric fields and lightning within thunderstorm clouds, and a key mechanism driving the eruption of downdrafts. Neutralizing charge separation means cutting off the "trigger switch" for the concentrated eruption of downdrafts. Competitive seeding, by disseminating a large number of hygroscopic nuclei at the squall line leading edge, induces the dispersed development of multiple small convection centers, avoiding the formation of a single strong downdraft.

[0195] Quantitatively speaking, the total system energy in the prelude cloud stage is comparable to that in the mature stage (both are 10). 14 -10 15 (On the order of joules), but its "organization level" is far below that of the mature stage—the cape of the prelude cloud is not yet concentrated, the vertical wind shear is not yet organized, and the convective core has not yet formed. At this stage, intervention only needs to change the way energy is released (from concentrated bursts to dispersed, gentle releases), rather than counteracting the total energy itself, such as... Figure 21 As shown. Based on the critical state theory of atmospheric nonlinear systems, the energy consumption of intervention in the prelude cloud stage can be reduced by several orders of magnitude compared with the mature stage intervention, but the actual effect of this energy consumption advantage still needs to be verified through phased experiments.

[0196] Intervention schemes for various types of storms can be as follows: Strong typhoons: competitive convective seeding + sea surface cooling + enhanced wind shear. Storms: supercooled water consumption + pre-release of precipitation. Blizzards: ice crystal concentration regulation + temperature stratification control + phase transition. Hail and thunderstorms: competitive seeding + charge neutralization. After intervention, the cloud clusters undergo a three-stage process to achieve stable precipitation of the predetermined intensity, and residual winds are further reduced through a multi-base array coordinated wind-generating mode.

[0197] 7.4 Joint Prevention and Control Strategies for Multiple Types of Extreme Weather

[0198] When a wide range of extreme weather events, including heavy rainfall, thunderstorms, and strong winds, occur simultaneously across the country, the system activates a joint prevention and control mode. This mode follows a five-step approach: "unified scanning, hierarchical sorting, categorized intervention, residual energy dissipation, and stable release." Figure 25 As shown.

[0199] Step 1: Encrypted Scanning of the Space-Based Sensing Layer for Comprehensive Identification of Precursor Clouds. The space-based sensing layer satellite constellation switches its observation frequency from regular to encrypted mode, focusing on scanning the convective initiation regions ahead of systems such as fronts, shear lines, and low-level vortices. When the P_extreme index of a certain region jumps by more than 40 percentage points within 30 minutes, it is automatically marked as a candidate for a precursor cloud. The quantum-classical hybrid decision-making center 104 completes threat assessment and intervention plan generation for all candidate precursor clouds within 30 minutes.

[0200] Step 2: Prioritize risks and allocate control resources. Based on the development probability of each candidate cloud site, the population density of the affected area, the distribution of critical infrastructure, and the risk of geological disasters, a unified priority ranking is established.

[0201] Step 3: Differentiated Intervention Based on Cloud Type. Activate the corresponding intervention plan based on the type of each prelude cloud. For concurrent prelude clouds, first suppress downdrafts, then consume supercooled water, and finally control cloud droplet size.

[0202] Step 4: Residual strong winds are dissipated by the array. If residual strong winds persist after the intervention of the prelude cloud, the multi-base array collaborative wind generation mode is activated to dissipate energy.

[0203] Step 5: Cloud Cluster Conditioning and Stable Precipitation Release. The cloud clusters that have degenerated into stratiform clouds after intervention are temporarily stored in the relay airspace and released after being regulated through a three-stage process.

[0204] It is important to note that when multiple systems occur concurrently, the cumulative effect of local interventions can produce unexpected large-scale impacts through the same synoptic-scale system. Although these local systems are spatially separate, they compete with and are interconnected in terms of energy sources and water vapor supply. If the system intervenes in the foreshadowing clouds over North China (consuming supercooled water, triggering pre-release of precipitation), these operations may alter the water vapor transport pattern of the entire frontal system, thereby unexpectedly enhancing convection development in the Yangtze-Huaihe River Basin. When the system is jointly controlling the weather, it not only considers intervention schemes for individual foreshadowing clouds but also assesses the cumulative effect of multiple intervention operations on the same weather system through teleconnection monitoring units and ensemble forecast models. When the assessment finds that it may lead to "over-intervention," the system automatically adjusts the intervention priority or reduces the scale of intervention.

[0205] 7.5 Prevention and control mechanisms to prevent conflicts with native cloud clusters during the prelude cloud transformation process

[0206] During the transformation and transport of prelude clouds, the adjusted cloud clusters may intersect with existing primary cloud clusters at high altitudes, triggering a "butterfly effect." The system attempts to prevent such risks through a four-layer prevention and control mechanism, such as... Figure 22 and Figure 27 As shown.

[0207] Layer 1: Pre-transport compatibility assessment and route planning. Utilizing space-based sensing and ground-based radar, the location, temperature, phase, thickness, water content, and CAPE value of all native clouds along the transport route are scanned, covering a 50-kilometer buffer zone on both sides of the transport route. A compatibility score is assigned to each potentially intersecting native cloud. When the temperature difference exceeds 15°C, or the supercooled water content of the native cloud exceeds 1.5 g / m³, or the CAPE exceeds 2000 J / kg, it is automatically marked as a danger zone, and the transport route is immediately changed or transport is suspended.

[0208] The second layer: Safety container constraint and real-time monitoring during transport. The conditioned prelude cloud is constrained within a "safety container" formed by a soft wall in the relay airspace. The soft wall forms a density barrier through a temperature gradient field, ensuring that the air inside the cloud is essentially unmixed with the external atmosphere. A cluster of micro-units deployed within the container continuously monitors the cloud's microphysical parameters and issues immediate warnings upon detecting anomalies.

[0209] The third layer: Proactive intervention when convergence is unavoidable. If, due to rapid changes in the weather system, unavoidable native clouds appear in the transport path, the system pre-treats the native clouds before their arrival—spreading hygroscopic condensation nuclei to expand the cloud droplet spectrum, consuming supercooled water droplets, and reducing their reactivity. Simultaneously, the transporting clouds undergo secondary conditioning, adjusting their temperature through heat exchange units to reduce the temperature difference with the native clouds to a safe range. Micro-unit clusters are pre-deployed in the convergence zone for charge management, neutralizing any potential charge separation.

[0210] Fourth layer: Circuit breaking and emergency response after anomalies occur. If an abnormal signal is detected after the convergence (sharp increase in radar echo, rapid increase in extreme weather development index), the system will automatically trigger the circuit breaker: immediately stop sending new cloud clusters to the convergence area, the partial dissipation procedure has been initiated, the light wind and gust subsystem is activated to guide the convergence area in a safe direction, and at the same time call for human monitoring intervention.

[0211] 7.6 Embryo-stage salvage (backup plan)

[0212] The remediation window is divided into three levels: early remediation (within 6 hours after the window closes, energy consumption is 5-10 times higher, success rate is 70-90%), mid-term remediation (6-24 hours, energy consumption is 50-200 times higher), and late remediation (more than 1,000 times higher). After the window closes completely, the focus shifts to monitoring and early warning, as well as ground protection. Data feedback optimizes the early warning algorithm, forming a closed loop.

[0213] 8. The principle of progressive capability development and phased implementation roadmap

[0214] The various capabilities of the system of this invention follow a progressive relationship from simple to complex and from local to global, as detailed in the table below. Figure 16 As shown.

[0215]

[0216] 9. Climate Engineering Risk Management Module 106

[0217] The system incorporates a quantitative risk assessment matrix, covering intervention measures such as polar cold resource allocation, precipitation scheduling, shading deployment, thermal balance regulation, local wind generation, remote cloud transport, prelude cloud intervention, source-level regulation operations, and joint prevention and control. Cross-regional fairness assessment quantifies intervention differences through a regional climate regulation benefit-loss index, automatically compensating or triggering circuit breakers when thresholds are exceeded. Counterfactual simulations are performed before each major intervention.

[0218] The teleconnection monitoring system integrates diagnostic modules such as the Rossby wavelet, the Pacific-North American teleconnection pattern (PNA), and the North Atlantic Oscillation (NAO), assessing long-range impacts through ensemble forecasts of 20-50 members. Cumulative effect early warning tracks cumulative intensity using the Global Intervention Activity Index (GIAI), triggering quota restrictions and reserving a recovery period when warning levels are exceeded, while simultaneously running a "no-intervention" digital twin control model. Ensemble forecast probabilistic decisions are executed only when the probability of a favorable outcome is significantly higher than that of an unfavorable outcome. Ecological cascade protection follows the principles of minimum intervention and seasonal windows.

[0219] The proportional relationship between the system's intervention scale and natural processes is the core basis for assessing the global impact. Under full operational conditions, the system's annual water volume is approximately 1 billion tons, while the global annual natural evaporation is approximately 50 trillion tons. The system's intervention volume accounts for only one millionth of the natural cycle. The latent heat release involved in the system is approximately 10... 16 The energy levels are on the order of joules per year, while the Earth's atmosphere receives approximately 5 × 10⁻⁶ kilojoules per year from the sun. 24 Joules. The system's intervention energy accounts for only one ten-billionth of natural energy. More importantly, the system's operation does not "create" or "destroy" energy and water vapor out of thin air, but rather makes minute temporal and spatial adjustments to the water cycle and energy conversion processes that already exist in nature. Prelude cloud intervention alters the energy release pattern of extreme weather systems with extremely small disturbances before their formation; source location regulation utilizes natural temperature differences and the chimney effect to transport heat; and the water vapor replenished by shading clouds ultimately returns to the surface as precipitation. The entire system attempts to follow the design philosophy of "using minimal force to achieve maximum effect"—utilizing the nonlinear sensitivity of the atmospheric system in a critical state to achieve significant regulatory effects with minimal guiding intervention.

[0220] 10. Diverse application scenarios

[0221] The system covers six major areas: urban management (cooling down high-temperature heat waves, dispersing high concentrations of particulate matter in the air, and ensuring weather conditions for major events), agricultural disaster prevention (frost prevention, protection against hot and dry winds, and assisting in pollination), water resource management (reservoir rain enhancement, cross-basin water vapor dispatch, and glacier replenishment), ecological protection (wetland water replenishment, forest fire prevention, and emergency response to coral bleaching), emergency response (dispersion of toxic gases and emergency response to cooling water), and energy management (power peak shaving and maintenance of solar power plants).

[0222] 11. Economic Feasibility

[0223] The total deployment cost of the system is approximately US$250-330 billion, and it consists of the following components:

[0224] Research and development expenses (Phase 1, approximately US$300-500 billion): This includes verification prototype units (3-5 units), deployment of space-based sensing satellite constellations, research and development of quantum-classical hybrid decision-making centers, construction of intelligent micro-unit cluster verification networks, initial construction of ground bases, and tackling of key technologies. This phase does not involve large-scale production; the cost of the prototype units is far higher than the cost of mass production and is included in research and development expenses rather than equipment manufacturing costs.

[0225] Equipment manufacturing costs (Phase II-IV, approximately $170-200 billion): Production deployment officially begins from Phase II. The manufacturing cost per unit decreases significantly with mass production scale: Phase II (small batch production, approximately 50 units) costs approximately $500 million per unit; Phase III (medium scale, approximately 300 units) reduces to approximately $300 million; and Phase IV (large-scale mass production, approximately 650 units) further reduces to approximately $150 million. Based on a final scale of 1000 units, the weighted average cost is approximately $200-250 million per unit.

[0226] Deployment, installation, and ground base construction (approximately US$500-800 billion): This includes the transportation deployment of 80-120 relay chains globally, installation of ground anchoring systems, comprehensive construction and maintenance of ground bases, workshops, charging arrays, and other supporting facilities.

[0227] Annual operating costs are approximately US$8-12 billion (including energy replenishment, micro-unit replenishment, ground base maintenance, and personnel expenses). Global direct economic losses from meteorological disasters amount to approximately US$500 billion annually. The system, by reducing disaster intensity by 40-60%, increasing agricultural production, increasing water resources, and saving energy, generates an average annual total benefit of approximately US$250-400 billion. The static investment payback period is approximately 1-1.5 years. The system construction period is approximately 15 years, implemented in three phases. Initial revenue can be generated through localized trials during the construction phase. The above cost and benefit estimates are based on current understanding; actual figures may be adjusted due to technological advancements, price fluctuations, and actual operational experience.

[0228] 12. Multi-layered fault-tolerant and foolproof design

[0229] The system features: unit-level fault tolerance (automatic load transfer in case of failure, with backup backup); chain-level fault tolerance (task routing to adjacent redundant chains); degraded operation mode (switching between classical supercomputing and ground-based radar when quantum or space-based systems are unavailable); fail-safe design (temporary storage of cloud or air mass for natural dissipation in case of global power failure, with micro-units automatically returning to base when low on power); and data integrity assurance (multi-node redundant backup). Ground base resupply capabilities are coordinated with the system's fault tolerance mechanism: when an aerospace AI base needs to return to the ground for resupply due to insufficient energy or depleted supplies, its air missions are temporarily taken over by adjacent or backup units; after resupply, it re-takes off to restore control coverage of the area. Ground bases can also mutually allocate resources and energy, forming a globally distributed logistics network. (See [link to relevant documentation]). Figure 17 .

[0230] The system incorporates multiple security safeguards to prevent the misuse of technology. All intervention operations operate within the final decision-making authority framework of the human oversight layer; AI only has the right to execute and propose, but not the final decision-making power for major matters. The system's core control protocol adheres to the principles of transparency and auditability under the international climate governance framework, and the initiation of any large-scale intervention operation requires a rigorous authorization process. Key intervention decisions must be reviewed by a multidisciplinary expert group composed of multiple countries; no single country or entity has the authority to unilaterally initiate large-scale climate control operations. The system's human-computer interaction records are fully traceable, ensuring that any intervention behavior can be reviewed and held accountable afterward.

[0231] To clearly demonstrate the technical features of this invention, specific examples from real-world scenarios will be provided below. It should be noted that the specific numerical values ​​and effects involved in the following examples are results obtained through simulation calculations and counterfactual inferences based on mature physical models (including atmospheric thermodynamics, cloud microphysics, fluid mechanics, atmospheric teleconnection theory, etc.) and digital twin Earth models. These are not intended to claim protection for specific numerical values, but rather to illustrate the possible technical effects of the present invention. Those skilled in the art should understand that in actual deployment, the parameters and effects will vary depending on specific environmental conditions and equipment configurations. The technical solution of this invention is based on well-verified fundamental physical principles, and its feasibility is established on the basis of mature scientific theories.

[0232] Example 1: Construction and Deployment of Standardized Relay Units

[0233] The mobile AI base, designed to create a lifting body configuration, is approximately 300 meters in diameter and 60 meters thick at its center. The main structure utilizes carbon fiber reinforced composite materials and a titanium alloy frame, with approximately 50,000 square meters of thin-film photovoltaic components on the upper surface, providing a peak power of approximately 25MW. An internal buoyancy adjustment chamber provides approximately 1500 tons of static buoyancy. Seven processing levels (L1-L7) are arranged in a ring along the central through-channel. The macroscopic telescopic pipes are nested in five stages, reaching a total height of approximately 1010 meters when fully extended, and retracting to restore the smooth lifting body shape. The ground anchoring system consists of four heavy-duty tractors, with tethered balloons used for rope delivery. Units are deployed at different altitudes along the meridian to form vertical relay chains, requiring approximately 80-120 main relay chains globally, with denser deployment in key climate zones, ultimately aiming for approximately 1000 units deployed globally.

[0234] The base is designed for a continuous stratospheric stay of 5-10 years, during which its total service life can be extended by returning to a ground base for regular maintenance, refueling, and component replacement. The ground base is equipped with nuclear fuel replacement facilities, photovoltaic panel cleaning equipment, an energy storage system testing platform, a storage and resupply system for consumable materials such as condensation nuclei and coolants, and a large-scale charging array for the intelligent micro-unit cluster. Upon return, the telescopic pipes are fully retracted, and the base glides down in a high lift-to-drag ratio configuration. After refueling and maintenance at the ground base, it is relaunched using its own power or auxiliary propulsion system. During the return from the space-based base, the intelligent micro-unit cluster can undergo mass deep charging and comprehensive status testing at the ground base.

[0235] Example 2: Single-site near-ground air generation – closed loop of suction-based air generation, outlet cool air, and guide head.

[0236] The base moves to a position approximately 150 meters above the edge of the rice paddies and hovers there. The telescopic pipe extends downwards, with a converging outlet. Utilizing the approximately 4-6°C temperature difference between the ground surface and the top of the pipe, and the resulting air pressure difference, a chimney effect is created, naturally drawing in air at a velocity of 3-5 m / s—the suction itself generates wind. The drawn-in hot air, around 35°C, rises and is adiabatically cooled, accelerating to 12-20 m / s via a Venturi stream. The outlet air temperature drops to approximately 30-32°C, and the wind-cooling effect lowers the perceived temperature to approximately 21-23°C, creating a comfortable cool breeze.

[0237] An adjustable-angle guide head is installed at the duct outlet to direct high-speed airflow directly to the ground at an inclined angle. After impacting the ground, the airflow diffuses horizontally in all directions as a light breeze of 2-5 m / s. Part of the diffused airflow is then drawn back into the duct bottom due to the chimney effect, forming a local closed-loop cycle of "suction-acceleration-guidance-diffusion-re-suction". The guide head is merely a geometric extension and does not add any additional energy consumption. When large-scale open ventilation is required, the guide head can be retracted or adjusted to a horizontal direction. In intermittent pulsed mode, daily operation for 8 hours consumes approximately 12 MWh, about 18% of that of traditional fans, reducing rice canopy humidity by 15-25% and disease incidence by approximately 40%.

[0238] Example 3: Multi-site array collaborative wind generation – a typical application of large-scale light wind production

[0239] A certain plain agricultural area requires large-scale ventilation and cooling during summer afternoons, covering an area of ​​approximately 300 square kilometers. The maximum coverage of a single-site ventilation model is limited and cannot meet the needs of the entire area. The decision-making center activates a multi-site array coordinated ventilation model.

[0240] Three standardized relay units are arranged in an equilateral triangle array, approximately 8 kilometers apart. Each unit's telescopic duct extends downwards, with adjustable-angle guide heads at the duct outlets to direct high-speed airflow towards the ground. The duct outlets at each base employ a horizontal diffusion configuration to ensure uniform coverage of the light winds generated at each base along the array direction. After being released from the bases, the micro-unit cluster ascends to the airspace near the outlet of the upper telescopic section, forming a soft wall to guide the airflow diffusion direction.

[0241] Through continuous operation, the three-base coordinated operation expanded the coverage area of ​​the light wind to approximately 300 square kilometers, maintaining a ground wind speed of 2-5 m / s (equivalent to a level 2-3 light wind), effectively reducing the temperature and humidity of the crop canopy. The total energy consumption of the multi-base array coordinated wind generation mode is approximately 2.5-3 times that of the single-base mode, and far lower than the energy consumption of traditional wind turbine arrays with the same coverage area.

[0242] This example demonstrates the significant advantages of multi-site collaborative wind generation in expanding coverage.

[0243] Example 4: Urban heat island nighttime gusts disperse high concentrations of particulate matter in the air

[0244] During winter nights, the temperature inversion layer remains stable, resulting in heavy PM2.5 pollution. The base is deployed in the upwind relay airspace to temporarily store a cold air mass of approximately 10°C, releasing it intermittently at a rate of about 200 tons per minute. The descending and diverging cold air generates gusts of 3-5 m / s. After 4 hours, the temperature inversion layer is disturbed, and projections indicate that PM2.5 levels could decrease by approximately 35%.

[0245] Example 5: Local warm and humid air mass in-situ precipitation and cooling – a typical application of source-level regulation.

[0246] In a southern city, the afternoon temperature reached 38°C with a relative humidity of 65%. System assessment confirmed that all conditions for the first priority of source-level regulation were met. The decision-making center directly activated the source-level regulation mode without any remote transmission. A base-based aircraft hovered approximately 500 meters above the city's core area, utilizing the urban heat island effect to create a strong chimney effect, drawing in warm, moist air masses that rose and condensed. The cloud clusters were conditioned by L1+L2 processes to a particle size of 5-20 μm and released from the mid-cloud region. The precipitation, at a moderate intensity, lasted for about 2 hours, reducing the city's temperature from 38°C to about 31°C, with a perceived temperature decrease of about 8°C. The entire process consumed only about 8 MWh of active energy, while simultaneously purifying the air and replenishing the green areas with water.

[0247] Example 6: Synergistic Cooling Effect of Daytime Shading and Daytime Rainfall in Extreme Summer Heat

[0248] An inland city was forecast to reach an afternoon temperature of 42°C, with a perceived temperature potentially exceeding 50°C. Human oversight approved a daytime coordinated cooling plan. At 10:00 AM, two standardized relay units deployed a sunshade cloud layer in the central cloud region, covering approximately 200 square kilometers of the city's core area. The sunshade cloud layer employed a three-in-one persistent maintenance technology; satellite radiometer measurements showed a reduction of approximately 35% in shortwave solar radiation reaching the ground, significantly slowing the rate of ground warming. At 2:00 PM, with the near-surface temperature still at 38°C, three base stations activated the local warm and humid air mass daytime precipitation mode. The warm and humid air mass was drawn in and condensed, and the cloud mass was released after being conditioned by moderate rain particles. The precipitation, at a moderate intensity, lasted for approximately 1.5 hours. The synergistic effect of rainwater evaporation absorbing heat and the sunshade cloud layer reflecting cooling reduced the city's temperature from 38°C to 30°C, with a perceived temperature decrease of approximately 15°C. The entire coordinated operation successfully avoided secondary disasters such as heatstroke and power overload that could have been caused by extreme heat.

[0249] Example 7: Customized Rainfall Timing Based on Popular Preferences – Daytime Rainfall in Tourist Areas

[0250] A famous tourist city experiences high daytime temperatures in summer, impacting tourists' outdoor experiences. Simultaneously, the region boasts unique nighttime cultural activities and a vibrant night market economy; nighttime rainfall can disrupt tourist travel and business operations. The local government submitted a preference setting of "daytime rainfall to lower temperatures, and clear skies at night." The decision-making center, after review, confirmed that this preference did not contradict the overall goal of "favorable weather" and incorporated it into the control strategy. The system activates a daytime rainfall mode from 2 PM to 4 PM daily, utilizing the chimney effect to draw in warm, moist air masses and trigger precipitation. Rainfall intensity is controlled at light to moderate levels of 3-5 mm / h, lasting 1-2 hours. Following the rainfall, the air is fresh and temperatures drop significantly, providing a comfortable outdoor environment for tourists, while clear skies at night ensure that night markets and nighttime cultural activities remain unaffected. Furthermore, the rainfall replenishes the city's green spaces and landscaping water supply.

[0251] Example 8: Guiding the Descending of Cold Air from Nearby Mountains – A Typical Application of Proximity Transport

[0252] An inland basin city is experiencing a heatwave, with no usable warm, moist cloud cover. The system assessment prioritizes the second-highest temperature: approximately 5°C at the summit of a nearby mountain. A base is deployed to the airspace above the mountain ridge, utilizing a relay airspace soft wall to guide the cold mountain air down the terrain slowly. The soft wall precisely controls the descent rate to prevent the formation of downbursts or foehn effects. Simulations indicate that the city's temperature could drop by approximately 3-5°C.

[0253] Example 9: Precise three-stage control of heavy, medium, and light rain

[0254] The three areas are expected to receive heavy, moderate, and light rain, respectively. Cloud clusters were uniformly captured and distributed to different relay airspaces. Area A used only L1 arrays with large nuclei to release concentrated rainfall from high cloud areas at night; Area B used L1+L2 arrays with organic nuclei to release staggered rainfall from mid-cloud areas; Area C used a full range of arrays with fine particulate nuclei to release rainfall from low cloud areas in the early morning. The simulation shows that the three areas will simultaneously receive the expected rainfall intensity.

[0255] Example 10: Emergency Shading Protection for Melt Ponds in Greenland Ice Sheet

[0256] The melting pool area has been expanded to 150% of the climatological baseline value, and a 45-day contingency plan has been approved. Three bases have been deployed in the open sea, using locally sourced sea salt to atomize into ultrafine salt spray aerosols to form marine stratocumulus clouds. A rotating system will maintain 24-hour sunshade, with tethered balloons and solar power providing self-sufficiency. Soft walls will be reinforced in advance when cyclones pass. Simulations show a reduction of approximately 38 W / m² in the radiative flux across the ice surface. 2 The area of ​​the melting pool was reduced by about 45% compared to the control area.

[0257] Example 10 Appendix: Artificial Snowfall Growth in Polar Ice Sheets – High-Growth Strategy in the Early Stage

[0258] In the region near the grounding line of the West Antarctic ice shelf, the system initiates a high-intensity snowfall growth mode during the period of polar day regression. Three standardized relay units are deployed in the offshore area of ​​the target region, using the soft wall of the relay airspace to guide water vapor evaporated from the Southern Ocean to be transported over the ice sheet. The water vapor naturally cools and condenses in the polar low-temperature environment, and is kept below freezing temperature by the L5 heat exchange unit. The L6 unit seedes silver iodide nuclei to form ice crystals, and the L7 unit charges and regulates to accelerate the collision and growth of ice crystals.

[0259] The snowfall cloud clusters were controlled through a three-stage process: snow crystal size was preset to small to medium (to facilitate uniform coverage and compaction), release height was set in the mid-cloud region, and the timing was chosen at night (to further reduce melt loss). After approximately 60 days of continuous operation, simulations showed an increase in snow depth in the target area of ​​about 0.5 to 1 meter. Combined with the continued effect of sunshade clouds during the polar day, the annual net increase in ice cover in this region significantly improved.

[0260] The main energy consumption for artificial snowmaking in polar regions is water vapor collection and transport, and maintaining sub-freezing temperatures through L5 refrigeration. Thanks to the naturally low temperatures of the polar environment, the energy consumption for water vapor cooling and condensation is relatively low; the main active energy consumption is concentrated in guiding micro-unit clusters and seeding condensation nuclei at L6. Projections show that the energy consumption for annual snowfall increase operations is approximately 5-10% of that of traditional artificial snowmaking for the same amount of snowfall.

[0261] This embodiment verifies the technical feasibility of the synergistic strategy of "shading to conserve energy and snowfall to generate revenue".

[0262] Example 11: Intervention of Prelude Clouds to a Strong Typhoon – Transforming into Low-Grade Gentle Winds and Stable Precipitation

[0263] The space-based sensing layer identified the tropical disturbance as a typhoon precursor cloud approximately 5 days in advance. Immediately after capture, the precursor cloud, passing through the pipeline, underwent de-energization preprocessing within the base unit. The preprocessed precursor cloud was confined within a soft-walled safety container in the relay airspace, and its transport path avoided high CAPE areas. Three bases implemented convective competitive seeding, sea surface shading for cooling, and wind shear enhancement, respectively. 72-hour post-intervention simulations showed that the disturbance failed to develop into a typhoon, with maximum sustained winds controlled at tropical depression levels, and remnant clouds producing steady moderate rain.

[0264] Example 12: Intervention of Prelude Clouds to Storms – Transforming Heavy Rain into Steady Precipitation

[0265] In a coastal region, a mesoscale convective complex was initially formed, resulting in a sharp increase in CAPE (Capacity for Emerging Objects). After capture, de-energization pretreatment was performed, followed by seeding with silver iodide to consume supercooled water droplets, triggering early precipitation release. Following intervention, the cloud clusters degenerated from strong convective clouds to stratiform clouds, and after moderate rain conditioning, settled as steady precipitation.

[0266] Example 13: Intervention of Prelude Clouds to Thunderstorms and Gale-Strong Winds – Transforming Thunderstorms and Gale-Strong Winds into Gentle Brees

[0267] An arc-shaped cloud line at the leading edge of a squall line in a certain area was identified as a precursor cloud to thunderstorms and strong winds. During the precursor cloud stage, catalysts were seeded and charge was regulated to suppress the concentrated bursts of descending airflow. After intervention, a multi-base array coordinated wind-generating mode was used to dissipate residual wind energy, and simulations showed that the surface wind speed dropped below the preset level.

[0268] Example 14: Remedial Measures for the Stormy Embryonic Period After Missing the Window

[0269] Due to initial geographical limitations, the cloud cluster missed its prelude cloud window and has now entered the mid-to-late embryonic stage. Three bases respectively implemented supercooled water consumption, peripheral convection competition, and path guidance. Simulations show that the cloud cluster degenerates into stratiform cloud precipitation, with energy consumption approximately 80 times that of the optimal window.

[0270] Example 15: Early-stage hail prevention using prelude clouds

[0271] Early in its development, the cumulus cloud was identified as a prelude to hail. After de-energization pretreatment, approximately 200 micro-units were seeded with a catalyst at an extremely low rate to neutralize the charge. The simulation showed that it produced mild, moderate rain rather than hail, with energy consumption only about one-thousandth that of hail suppression in the mature stage.

[0272] Example 16: Heating Regulated by Warm Air Source Location in Inversion Layer during Winter

[0273] In a northern city, the near-surface temperature drops to -15°C at night during winter. A significant temperature inversion layer exists at an altitude of approximately 300 meters, with a temperature of about 3°C. A base is deployed to guide the localized, slow descent of warm air from the inversion layer. Soft walls are used to precisely control the range and rate of descent, ensuring the stability of the inversion layer is not disrupted. Simulations indicate that the near-surface temperature in the city's core area could rise by approximately 2-4°C.

[0274] Example 17: Security Management of Remote Cloud Transmission Process

[0275] When planning the long-distance transport of a cold cloud mass, compatibility assessments revealed the presence of warm stratocumulus clouds rich in supercooled water droplets in the middle of the path. The transporting cloud mass was temporarily lifted to avoid it at a safe vertical distance. The cold air mass was transported in the lower stratosphere, while the warm air mass was transported in the middle and lower troposphere, maintaining vertical isolation between the two. No contact occurred throughout the entire journey, and precipitation was successfully triggered after the cloud mass passed safely.

[0276] Example 18: Joint Prevention and Control of Precursor Clouds for Widespread Heavy Rainfall and Thunderstorms Across the Country

[0277] One summer, a cold air mass moved southward and converged with warm, humid air currents along a line from North China to the Yangtze River Delta. The space-based sensing layer simultaneously identified 15 candidate points for prelude clouds. The decision-making center implemented joint prevention and control measures using a five-step approach: first, dense scanning for comprehensive identification; second, prioritizing by risk; third, differentiated intervention based on risk type; fourth, residual wind array energy dissipation; and fifth, cloud cluster regulation and stable precipitation release. The simulation showed that the North China urban agglomeration transitioned from heavy rain and gale-force winds (level 8) to moderate rain and light winds (level 3); the Jianghuai agricultural region transitioned from heavy rain and hail to light rain without hail; the Jiangnan mountainous area transitioned from heavy rain and gale-force thunderstorms (level 9) to moderate rain and gentle winds (level 4); and the Huanghuai Plain transitioned from squall line storms and torrential rain to light rain and light winds (level 3). The total energy consumption of the joint intervention was only one-thousandth to one-hundredth of the energy consumption of a mature response. During the joint prevention and control process, the teleconnection monitoring unit simultaneously assessed the cumulative impact of multiple intervention operations on the frontal system, and no "over-involvement" effect was found.

[0278] Example 19: A Case Study on Preventing Conflicts with Native Cloud Clusters During Prelude Cloud Conversion

[0279] The system will transport the adjusted pre-storm clouds (temperature around -15°C) from North China to the middle reaches of the Yangtze River, such as... Figure 27 As shown. A native warm stratocumulus cloud (temperature approximately 8°C, supercooled water 1.8 g / m³, CAPE approximately 2200 J / kg) was detected in the middle of the path, and the compatibility score entered the danger zone. The decision center chose to temporarily elevate the conditioning cloud cluster approximately 2 kilometers over the native cloud cluster, confining it within a safe container throughout the process. Simultaneously, alternative solutions were generated, including pre-processing of the native cloud cluster and secondary conditioning of the transport cloud cluster. Ultimately, the conditioning cloud cluster safely avoided the native cloud cluster, the melting condition was not triggered, and it released steadily with moderate rain intensity.

[0280] Example 20: Economic Simulation of Large-Scale System Deployment

[0281] Based on a final deployment of 1,000 units, the total investment is estimated at approximately US$250-330 billion (US$30-50 billion for R&D + US$170-200 billion for equipment manufacturing + US$50-80 billion for deployment, installation, and ground bases). Annual operating costs are estimated at US$8-12 billion. Global direct economic losses from meteorological disasters amount to approximately US$500 billion annually. The system, through disaster reduction benefits, increased agricultural production, increased water resources, and energy savings, will generate an average annual total benefit of approximately US$250-400 billion. The projection shows a static investment payback period of approximately 1-1.5 years, with a life-cycle internal rate of return far exceeding benchmark levels. The above estimates are based on current understanding; actual costs may deviate due to technological breakthroughs or price fluctuations.

[0282] [Industrial Applicability]

[0283] This invention provides a global climate coordinated regulation system based on a multi-level relay network. Its technical solution is a systematic integration and innovation based on existing principles of physics, atmospheric science, and artificial intelligence. Core principles such as the chimney effect, the Venturi effect, thermodynamic adiabatic processes, cloud microphysical collision and growth mechanisms, artificial weather modification catalysis theory, and atmospheric teleconnection theory are all mature theories verified through long-term scientific research and engineering practice. The system of this invention attempts to provide a more comprehensive technical solution based on these mature theories, rather than re-assuming the fundamental principles.

[0284] The system's design prioritizes energy efficiency based on "natural forces, structural gains, and source location," aiming to keep active energy consumption at a low level. The hierarchical design of the prelude cloud intervention strategy and the embryonic stage remedial backup plan, the five-step joint prevention and control method, the four-layer prevention and control mechanism, the "stay-return-replenishment-maintenance-redeployment" operation and maintenance closed loop, the serialized and modular design of micro-unit clusters, and the "shading and energy saving + snowfall energy generation" polar protection collaborative strategy are all innovative explorations of this invention.

[0285] It should be objectively pointed out that the technical solution of this invention is still in the theoretical demonstration and digital twin simulation stage, and its actual engineering effects are being verified in stages. The inherent limitations of the high complexity and predictability of the climate system mean that any climate intervention technology is subject to uncertainty. The system of this invention has fully recognized these inherent limitations in its design—including but not limited to the possibility of a certain misjudgment rate in prelude cloud identification, the possibility of large-scale intervention having long-range effects through teleconnection, and the possibility of cumulative effects from local intervention when multiple systems are operating concurrently. Based on a clear understanding of these uncertainties, the system incorporates a multi-layered risk management mechanism and a phased, gradual deployment roadmap to ensure that these uncertainties are systematically recognized, tested, and controlled in practice, rather than being deployed on a global scale in one step. The system also incorporates multiple security safeguards to prevent the abuse of technology, ensuring that any large-scale regulation operation is carried out within a strict international supervision and authorization framework.

[0286] Theoretically, this system can be applied to exploratory research in multiple fields such as urban cooling, agricultural disaster prevention, water resource allocation, ecological protection, emergency response, and energy peak shaving. However, its practical application effects and impacts require rigorous phased verification and evaluation. This invention provides a systematic technical approach worthy of further research and verification to address major challenges such as frequent extreme weather events, uneven water resource distribution, urban heat island effect, and polar ice cap protection under the background of global climate change.

[0287] The ultimate vision of this invention is to explore, through responsible technological innovation and with full respect for the laws of nature and the common interests of humankind, the possibility of building our planet into a beautiful home where humanity and nature coexist harmoniously, with favorable weather and abundant life and hope.

[0288] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A global climate co-regulation system based on a multi-stage relay network, characterized in that, include: The global thermal balance regulation module is used to maintain a dynamic thermal balance between at least one target area and the polar region, with the stability of the polar ice cap as a hard constraint. The global thermal balance regulation module follows a three-tiered energy efficiency optimization principle: prioritizing source location regulation, followed by nearby transport, and with long-distance transport as a backup. The multi-level cloud cluster control network module comprises multiple standardized relay units distributed along vertical height, used to capture, vertically transport, temporarily store and condition, and release cloud clusters. This module achieves pre-programmed control of precipitation intensity within predetermined levels and active switching of precipitation phases between rain and snow through a three-stage process of particle size preset, height adjustment, and time-period control, by combining and controlling cloud temperature, condensation nucleus type, and release height. Each standardized relay unit integrates an aerospace AI mobile base and a macroscopic telescopic pipe into a single independent force-bearing structure. The aerospace AI mobile base adopts a lifting body configuration, possessing a high lift-to-drag ratio and rotational symmetry. Flexible transmission between each standardized relay unit is achieved through a relay airspace, without rigid mechanical connections. The light breeze / gust generation subsystem, relying on the standardized relay units, utilizes natural physical processes as the driving force to support a multi-level relay network remote wind generation mode, a near-ground local wind generation mode using a single standardized relay unit, and a multi-base array collaborative wind generation mode. The near-ground local wind generation mode utilizes the natural temperature and pressure differences between the ground and upper atmosphere to create a chimney effect that draws in airflow. This airflow is accelerated by a passive aerodynamic acceleration structure at the outlet of the macroscopic telescopic pipe. The outlet airflow is then guided to the ground via an adjustable guide structure to form a localized closed-loop circulation or diffused airflow, generating a cool breeze due to the wind-cooling effect. The multi-base array collaborative wind generation mode uses multiple standardized relay units arranged in an array. Each standardized relay unit works in conjunction with a soft wall in the airspace to jointly generate a wide-coverage light breeze or gust. The quantum-classical hybrid decision-making center, based on a digital twin Earth model, aims to maximize the global livability index and coordinate the control of various modules. The livability index is composed of multiple sub-indices, including winter comfort, summer comfort, precipitation temperature, and humidity. The Extreme Weather Early Intervention Module is used to identify the cloud structure of typhoons, rainstorms, blizzards, hail, and thunderstorms in the early cloud stage before the energy of extreme weather systems has accumulated significantly. It attempts to identify the cloud structure of typhoons, rainstorms, blizzards, hail, and thunderstorms in advance through a classification-based cloud identification standard. The early cloud intervention strategy is used as the main strategy to try to transform extreme weather events into winds and stable precipitation below the preset level. The embryonic stage remedial intervention is used as a backup plan after missing the early cloud window. It also has the ability to jointly prevent and control multiple types of extreme weather concurrently. It works in conjunction with the climate engineering risk management module to form an early prevention and control system covering the entire chain of "early cloud identification - early cloud intervention - embryonic stage remedial intervention - circuit breaker protection". The climate engineering risk management module has a built-in quantitative risk assessment matrix, an upper-air environmental disturbance assessment unit, a teleconnection monitoring unit, a cumulative effect early warning unit, and a cross-regional fairness assessment algorithm. It is used to conduct multi-dimensional risk assessments before, during, and after intervention. When the negative climate impact caused by global regulation in any region exceeds a preset threshold, it triggers circuit breaker or compensatory regulation. The human supervision interface module is used to receive decision instructions from the human supervision layer and automatically switch the system's operating mode according to preset human intervention trigger conditions.

2. The system of claim 1, wherein, The global heat balance regulation module adopts a sequential transfer mechanism, with heat being transferred step by step along the horizontal latitudinal gradient; and different paths are used for the long-distance horizontal transport of cold and hot air masses, wherein: cold air masses take the lower stratosphere as the main channel, and hot air masses take the middle and lower troposphere as the main channel. The complete transport path of the cold air mass is as follows: after being collected from the polar regions, it is vertically lifted to the lower stratosphere, where it is horizontally transported using the low turbulence environment and the constraints of the relay airspace. During short-distance transport, the settling rate is controlled by the soft walls of the relay airspace, allowing the air mass to naturally settle to the target area. During medium- and long-distance transport, a "transport-sinking-conditioning-lifting" cyclic relay mode is adopted, with dynamic cooling and conditioning by the relay airspace along the way, and relay lifting when the air mass approaches the preset minimum allowable height. Finally, it is temporarily stored and released in the relay airspace in the low cloud region. The complete transport path of the hot air mass is as follows: after being collected from the hot zone, it rises to the lower troposphere using the chimney effect. After being heated and conditioned by the relay airspace, it is transported horizontally in this layer. During the transport process, the buoyancy ascent rate is controlled by the bidirectional regulation capability of the soft wall of the relay airspace, and a maximum allowable height is set as a hard constraint. After arriving near the target cold zone, precipitation is triggered at an appropriate height, transferring heat to the ground. The cold air mass transport channel and the hot air mass transport channel are physically isolated in the vertical direction. When there is a cooling demand, the global thermal balance regulation module evaluates and implements the response according to the priority of source location regulation, nearby delivery, and long-distance delivery; when there is a heating demand, it also evaluates and implements the response according to the priority of source location regulation, nearby short-distance delivery, and long-distance delivery. The global thermal balance regulation module also includes a local warm and humid air mass precipitation and cooling mode.

3. The system of claim 1, wherein, The natural physical processes utilized by the light wind and gust generation subsystem include the chimney effect, passive aerodynamic acceleration effect, and gravity-thermal driving effect. The chimney effect refers to the natural temperature and pressure difference between the ground and the upper atmosphere driving the air around the bottom opening of the macroscopic telescopic pipe to flow centripetally, forming a centripetal wind. At the same time, the hot air inside the pipe cools due to adiabatic expansion during its ascent and is passively accelerated through the outlet contraction configuration before being ejected. The gravity-thermal driving effect includes the sinking and diverging of cold air masses and the rising and drawing in of warm air masses. The active energy consumption of the gravity-thermal driving effect is zero. In the multi-base array collaborative wind-generating mode, multiple standardized relay units are arranged in an array, and each standardized relay unit works in conjunction with the airspace soft wall to jointly generate light winds or gusts with a wide coverage area. In the near-ground local wind-generating mode of a single set of standardized relay units, the system's active energy consumption is only used to maintain the base's flight attitude and micro-unit guidance and adjustment, and the wind-generating power itself is provided by natural physical processes.

4. The system of claim 1, wherein, The aerospace AI mobile base adopts a lifting body configuration, with a high lift-to-drag ratio and rotational symmetry aerodynamic shape. It is equipped with a central through-channel to accommodate the macroscopic telescopic pipe, and has a built-in ducted propulsion system and integrated buoyancy adjustment structure to achieve long-term residence in the stratosphere, or return to the ground base for maintenance, repair, energy replenishment and material resupply before redeployment. The macroscopic telescopic pipe adopts a multi-level nested telescopic structure, forming a vertically penetrating airflow channel in the extended state, and can be completely stored inside the aerospace AI mobile base in the contracted state; the macroscopic telescopic pipe adopts a honeycomb composite structure; and a quick-connect and quick-disconnect interface structure is provided at the bottom.

5. The system of claim 4, wherein, The aerospace AI mobile base is equipped with a cloud processing and control system, including at least one of an aerodynamic atomization unit, a heat exchange unit, a condensation nucleus dissemination unit, and a charge control unit; the aerodynamic atomization unit is driven by the air pressure difference generated by the chimney effect to achieve cloud droplet size control without additional power consumption. The type of condensation nuclei sown by the condensation nucleus dispersing unit can be adapted and selected according to the target precipitation phase. The three-stage process includes: particle size preset stage, heavy rain activates eddy current pre-crushing unit, moderate rain activates eddy current pre-crushing and passive atomization combination, light rain activates all crushing units, and charge regulation suppresses collisions to achieve drizzle or only humidification without precipitation. During the height adjustment phase, heavy rain is released from high cloud areas, moderate rain from mid cloud areas, and light rain from low cloud areas; during the time period control phase, the timing of release is controlled by relay airspace temporary storage, which realizes daytime rain avoidance, nighttime water replenishment, staggered release, emergency response, and differentiated scheduling based on public preferences.

6. The system according to claim 1, characterized in that, The quantum-classical hybrid decision-making hub adopts a multi-level computing architecture, including a quantum heuristic layer, a quantum acceleration layer, a classical supercomputing layer, and a hybrid interface layer. The quantum heuristic layer is used to deploy tensor network algorithms to simulate quantum parallel exploration and scan global atmospheric data around the clock. The quantum acceleration layer is used to deploy quantum optimization algorithms to improve the search efficiency of high-dimensional parameter spaces. The classical supercomputing layer is used to run high-resolution atmospheric circulation models and integrate intelligent micro-unit sensing data for four-dimensional variational assimilation. The hybrid interface layer is used to realize real-time task scheduling and data collaboration between computing units at all levels.

7. The system according to claim 1, characterized in that, The livability index is composed of three sub-indices: winter comfort, summer comfort, and precipitation temperature. The quantum-classical hybrid decision center aims to maximize the global livability index under the premise of stable growth of the polar ice cap and dynamically generates control strategies. The system adopts the principle of relative optimization, allowing different regions to maintain preset differences in temperature preference and precipitation period preference on their own climate baseline.

8. The system according to claim 1, characterized in that, The multi-level cloud cluster control network module also includes an intelligent micro-unit cluster, which is carried and deployed to the operational area by the aerospace AI mobile base and is fully recovered after the task is completed. The intelligent micro-unit cluster adopts a swarm rotation working mode, returning to the aerospace AI mobile base or ground base for rapid charging and status detection after a single task is completed, while a backup batch is launched to take over. The working mode of the intelligent micro-unit cluster includes at least one of cloud generation, cloud guidance, shading cloud generation and maintenance, prelude cloud identification, prelude cloud intervention, embryonic stage remediation, ecological monitoring, and relay airspace soft wall maintenance. The intelligent micro-unit cluster adopts a serialized and modular design, and is divided into several special models: the sensing type is equipped with a micro-sensor array for pre-cloud identification and ecological monitoring; the dispersing type is equipped with a replaceable catalyst loading chamber for precise dispersing of condensation nuclei; and the soft-wall type is equipped with pulse heating or cooling elements for maintaining intermittent temperature gradients at the edge of the airspace. The guiding type is equipped with directional heating and vector thrusters for guiding cloud paths; the water replenishment type is equipped with water vapor collection and atomization devices for dynamic water replenishment of shading clouds. The communication relay type is equipped with a laser communication terminal for cross-spatial data transmission; each model of the intelligent micro-unit cluster adopts a unified communication protocol, positioning interface and charging specifications, and can be flexibly combined and deployed according to task requirements.

9. The system according to claim 8, characterized in that, In the relay airspace soft wall maintenance mode, the intelligent micro-unit cluster generates a temperature gradient field at the edge of the relay airspace through intermittent pulsed local heating or cooling. It uses the density stratification and buoyancy effect of the atmosphere itself to constrain the diffusion of cloud or air mass, and generates lifting force through bottom heating to counteract the downward gravitational trend of cold air mass and the kinetic energy of the downward divergent wind of cold air mass, or generates downforce through top cooling to counteract the upward buoyancy trend of hot air mass. For long-cycle missions, the intelligent micro-unit cluster is deployed in the form of tethered balloons or aerostats and is directly powered by the base.

10. The system according to claim 1, characterized in that, The ultra-early intervention module for extreme weather includes a prelude cloud identification unit, a prelude cloud intervention unit, a joint prevention and control unit, and an embryonic period remediation unit; The categorized prelude cloud identification unit integrates multi-source data and establishes differentiated prelude cloud identification standards for strong typhoons, rainstorms, blizzards, hail, and thunderstorms. It attempts to identify prelude clouds in advance when energy has not yet accumulated significantly. Since prelude cloud identification has a certain false alarm rate, the system reduces the risk of false alarm by integrating multi-source data and ensemble forecasting, and performs counterfactual analysis before intervention to avoid unnecessary intervention in cloud clusters that cannot develop naturally. The prelude cloud intervention unit, as the main strategy, first performs de-energization preprocessing on the prelude cloud passing through the macroscopic telescopic pipe within the standardized relay unit after identifying the prelude cloud. Then, the preprocessed prelude cloud is confined within a safe container formed by the soft wall of the relay airspace for transportation and conditioning. Subsequently, the corresponding intervention plan is activated: for strong typhoons, convective competitive seeding combined with sea surface cooling and wind shear enhancement is implemented; for storms, supercooled water consumption and precipitation pre-release are implemented; for blizzards, ice crystal concentration regulation and temperature stratification control are implemented; for hail and thunderstorms, competitive seeding and charge neutralization are implemented. After intervention, the cloud cluster is regulated through a three-stage process to achieve stable precipitation, and residual wind is further reduced through a multi-base array collaborative wind-generating mode. The joint prevention and control unit is used to deal with multiple types of extreme weather concurrent scenarios. It identifies all candidate points of foreshadowing clouds through encrypted scanning of the space-based sensing layer, sorts them according to risk priority, and mobilizes multiple relay chains to coordinate and execute type-specific interventions, residual wind energy dissipation, and precipitation regulation. During the joint prevention and control process, the cumulative impact of multiple intervention operations on the same weather system is assessed simultaneously to prevent the systemic risk of "paying attention to one thing but neglecting another". The embryonic stage rescue unit serves as a backup plan. It is activated when the prelude cloud intervention window is missed for any reason, and performs graded rescue based on the delay time. When the rescue window is completely closed, it switches to monitoring, early warning, and ground protection mode.

11. The system according to claim 1, characterized in that, It also includes an artificial shading cloud application module, which adopts a three-in-one persistent maintenance technology of soft wall constraint, dynamic water replenishment and particle size control. Specifically, it constrains cloud boundary diffusion by relaying the temperature gradient field at the edge of the airspace; it continuously extracts water vapor from the ocean or land surface water for atomization replenishment; it suppresses collision and sedimentation by applying the same charge to cloud droplets; it supports a coordinated deployment mode of shading cloud reflection cooling and local warm and humid air mass precipitation cooling, and has established an all-season operation process for polar ice sheet protection. The protection of the polar ice cap adopts a synergistic strategy of "shading and reducing heat loss + increasing snowfall." Specifically, during the polar day, the shading cloud layer reduces the absorption of solar radiation and slows down the melting rate. Artificial snowfall strives to achieve material accumulation during the polar day's decline and the polar night, following a trial strategy of "high at the beginning and low at the end," which involves relatively high intensity snowfall growth in the early stage and gradually reducing intensity in the later stage.

12. The system according to claim 1, characterized in that, The multi-level cloud cluster control network module also includes a cloud cluster remote transport safety management unit, which is used to prevent extreme weather triggered by the convergence with the primary cloud layer at high altitude during the remote transport of cloud clusters, and to prevent cold and warm air masses from converging due to gravity sinking or buoyancy rising in their respective transport channels and deviating from the safe altitude layer. The safety management unit adopts a four-layer protection system, namely: prediction and avoidance, active intervention, enhanced monitoring and early warning, and circuit breaking and emergency response. The cold air mass transport channel and the warm air mass transport channel are physically isolated in the vertical direction.

13. The system according to claim 1, characterized in that, The climate engineering risk management module includes a cross-regional equity assessment unit, a teleconnection monitoring unit, and a cumulative effect early warning unit. The cross-regional equity assessment unit has a built-in regional climate regulation benefit-loss index, which automatically activates compensatory regulation or a circuit breaker mechanism when negative climate impacts exceed a preset threshold. The teleconnection monitoring unit automatically reduces or suspends source area interventions when abnormal signals appear in teleconnection sensitive areas. The cumulative effect early warning unit tracks the cumulative intensity of interventions through a global intervention activity index.

14. The system according to claim 1, characterized in that, The human supervision interface module has a built-in three-level decision-making authority system, namely: the AI ​​autonomous decision-making layer is responsible for routine operations; the AI ​​suggestion and human confirmation layer is responsible for major matters; and the human special decision-making layer is responsible for extreme matters. The human intervention triggering mechanism includes at least one of the following: abnormal monitoring of polar ice caps, continuous decline in regional livability index, unexpected disturbance in non-target areas, large-scale loss of connection of intelligent micro-unit clusters, circuit breaker triggered by cloud cluster transportation process, abnormal signals in remote sensing sensitive areas, and cumulative effect index exceeding the warning level. The system also includes a habitable zone dynamic evolution unit and a global carbon cycle collaborative management module; The system follows a phased and incremental deployment approach and a capability progression principle, attempting to achieve economic feasibility through phased and incremental investment and large-scale cost reduction. The system incorporates multi-layered fault tolerance and mistake-proofing designs, and includes multiple security safeguards to prevent the misuse of technology. These safeguards include: all intervention operations are conducted within the final decision-making authority framework of the human oversight layer; the system's core control protocol adheres to the principles of transparency and auditability under the international climate governance framework; and key intervention decisions are subject to review by a multidisciplinary expert group composed of multiple countries.

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