Warm cloud graded sowing catalysis system based on four-dimensional multi-source meteorological data assimilation numerical weather mode

Abstract

The invention discloses a warm cloud graded sowing catalysis system based on a four-dimensional multi-source meteorological data assimilation numerical weather mode. The system comprises a four-dimensional data assimilation coupling module, an emission source generation and reading module, an aerosol initial and boundary condition generation module, a sand dust and sea salt coupling module, a vertical mixing coupling module, an aerosol dry sedimentation module, an aerosol grading setting module, an aerosol grading sowing module and a catalytic effect calculation module. The WRF-SBM mode is transformed and optimized based on the WRF-FDDA framework, a perfect warm cloud graded sowing catalysis system is constructed, simulation of different warm cloud catalyst sowing processes and evaluation and analysis of the catalysis effect are achieved, and scientific basis and technical support are provided for optimization of warm cloud catalysis operation.

Description

Technical Field

[0001] The present invention relates to a warm cloud tiered seeding catalytic system, and in particular to a warm cloud tiered seeding catalytic system based on a four-dimensional multi-source meteorological data assimilation numerical weather model. Background Art

[0002] Against the backdrop of global climate change and water scarcity, weather modification technology has become a key measure for preventing and mitigating meteorological disasters and improving water resource utilization. Especially in tropical, subtropical, and mid-latitude regions, warm clouds, due to their widespread distribution and significant precipitation processes, play an important role in local water resource balance and climate regulation. Warm cloud processes focus on small and medium-sized scales and differ significantly from convective processes at traditional numerical weather scales. The development of warm clouds is highly dependent on environmental conditions at a distance, such as near-surface water vapor supply, aerosol concentration distribution, and topography. It emphasizes the interaction between the aloft environment and weather processes, making it extremely challenging to accurately simulate and capture subtle changes in warm cloud formation, development, and precipitation. This also places higher demands on the accuracy of cloud water resource simulation and forecasting.

[0003] Traditional numerical weather models typically use a bulk scheme to account for cloud microphysics, treating hydrometeors of varying sizes as a mixed entity and describing them with a small number of parameters. While this approach is simple to implement, it struggles to accurately capture the specific population variations of hydrometeors of varying sizes and their crucial impact on precipitation formation. In this context, binned cloud microphysics schemes (bin schemes) are particularly important because they can more accurately describe variations in cloud droplet spectra. By classifying cloud droplets by size, bin schemes more realistically simulate cloud droplet evolution, contributing to a more precise understanding of the complex interactions between aerosols, clouds, and precipitation.

[0004] Existing spatial and temporal distributions of natural environmental aerosols are mostly based on assumptions and lack an accurate depiction of the dynamic changes of aerosols in the real atmosphere. As the main source of cloud condensation nuclei (CCN), the spectral distribution and concentration distribution of aerosols directly affect the macroscopic and microscopic properties of clouds. For example, aerosols from different sources have different chemical compositions and particle size distributions. Under the same meteorological conditions, the activation characteristics of CCNs can vary significantly, leading to significant differences in cloud droplet number concentrations, cloud droplet spectrum widths, and cloud development and evolution processes. However, the spatial and temporal distributions of aerosols assumed in existing graded microphysics schemes cannot truly reflect these differences, resulting in large errors in both the simulation of natural clouds and the expression of warm cloud catalysis processes. This makes it difficult to accurately assess the actual effect of warm cloud catalysts, severely restricting the accuracy and effectiveness of weather modification operations. Summary of the Invention

[0005] Purpose of the invention: The purpose of the present invention is to provide a warm cloud tiered seeding catalytic system based on four-dimensional multi-source meteorological data assimilation numerical weather model to improve the accuracy of warm cloud process simulation, deepen the understanding of aerosol-cloud-precipitation interaction, and realize the simulation of different warm cloud catalyst seeding processes and the evaluation and analysis of catalytic effects.

[0006] Technical solution: The warm cloud grading spreading catalytic system of the present invention comprises: The four-dimensional data assimilation coupling module is used to fuse multi-source observation data through four-dimensional data assimilation technology to obtain the initial state information of warm clouds; Emission source generation and reading module, used to convert the emission source inventory into a gridded pollutant emission inventory for the target study area to form atmospheric aerosols; The aerosol initial and boundary condition generation module is used to generate the aerosol initial and boundary conditions in the target study area within a given time and convert them into the CCN number concentration required for the binned microphysical process; The dust and sea salt coupling module is used to calculate the emission of dust and sea salt aerosols and integrate them into the overall simulation; A vertical mixing coupling module is used to calculate the temporal variation of species mixing ratios due to vertical mixing and dry deposition; Aerosol dry deposition module, used to simulate the gravitational deposition process of aerosol particles at different levels; The aerosol classification setting module is used to divide the aerosol into different grades to simulate the behavior of aerosols with different particle sizes; Aerosol graded spreading module, used to simulate the spreading process of aerosols in different grades; The catalytic effect calculation module is used to calculate the catalytic effect of the catalytic process involving aerosols.

[0007] Preferably, the multi-source observation data in the four-dimensional data assimilation coupling module include ALL WTO / GTS standard stations, wind automatic weather stations, wind profiler radars, satellite observations, weather radars, microwave radiometers, flight weather reports, and meteorological observation data; the initial state information of warm clouds includes the macroscopic structure, microphysical properties, and aerosol distribution of the clouds.

[0008] Preferably, the emission source generation and reading module calculates the aerosol concentration release value of each grid point through density conversion, emission calculation and time accumulation function to form atmospheric aerosol.

[0009] Preferably, the aerosol initial and boundary condition generation module obtains the online prediction result of CCN number concentration through emission source input, atmospheric chemical process, transmission diffusion, vertical mixing, and dry deposition process, and further simulates.

[0010] Preferably, the sand, dust and sea salt coupling module includes the GOCART overall sand and dust solution, the GOCART 5-speed sand and dust coupling solution, the GOCART overall sea salt solution and the GOCART 4-speed sea salt solution; The GOCART dust program calculates dust aerosol emissions and is equivalent to PM 2.5 and PM 10 The part is further refined into 43 or 33 aerosol grades, and the overall spectrum distribution is defined by the aerosol grade setting module; The GOCART 5-speed dust coupling scheme calculates the vertical dust flux in five particle size segments and the corresponding aerosol emissions; The GOCART overall sea salt scheme calculates sea salt aerosol emissions based on a parameterized method of sea salt aerosol source function based on a semi-empirical formula; The GOCART 4-grade sea salt solution obtains a sea salt source function parameterization method suitable for submicron and submicron particles based on a semi-empirical formula to calculate the number particle size distribution of sea salt aerosols, and further refines the 4-grade sea salt aerosols into 43 or 33 grades of aerosols.

[0011] Preferably, the vertical mixing coupling module is used to calculate the temporal variation of species mixing ratios due to vertical mixing and dry deposition using a diffusion equation, which is as follows: ; in, is the species mixing ratio, t is time, z is the vertical coordinate, D is the diffusion coefficient, and Vd is the dry deposition velocity.

[0012] Preferably, the aerosol dry deposition module applies Stoke's law to calculate the settling velocity of aerosol CCN particles larger than 1 μm, and the formula is as follows: ; in, is the sedimentation velocity, r is the radius of the particle, is the density of the particle, is the density of air, g is the acceleration due to gravity, is the dynamic viscosity of air.

[0013] Preferably, the aerosol classification setting module divides the aerosol into an aerosol nucleus mode, an accumulation mode and a coarse mode according to the aerodynamic diameter.

[0014] Preferably, the aerosol graded spreading module includes: taking into account the influence of its different chemical components, adding 8 levels of warm cloud catalyst aerosol, adjusting the three properties of molar molecular mass MAERO, aerosol density RHO and ion number IONS according to the chemical composition of the catalyst, and adjusting the particle size of the catalyst according to the spectral distribution.

[0015] Preferably, the catalytic effect calculation module includes: simulating atmospheric environmental aerosols and warm cloud processes using natural and artificial aerosol spectra as a control test; adding aerosols with catalyst spectra for spreading as a spreading test, and comparing the two tests with and without spreading to obtain the warm cloud catalytic effect.

[0016] Beneficial effects: Compared with the prior art, the present invention has the following significant advantages: 1. Based on the WRF-SBM binned microphysics scheme, we improve emission sources, CCN initial and boundary conditions, and aerosol transport and diffusion processes. We construct a warm cloud binned seeding catalytic system based on a four-dimensional multi-source meteorological data assimilation numerical weather model (abbreviated as WRF-FDDA-CABIN or WRF-CABIN). This system supports flexible data source strategies for setting CCN initial and boundary conditions. In the replacement mode, high-precision data generated by global atmospheric chemistry models (such as WACCM and CHEM-CAM) are used as initial and boundary conditions, replacing the original initialization method to obtain more realistic aerosol distribution information. In the overlay mode, when global atmospheric chemistry numerical model data is lacking, the system will use the model's original initialization function to calculate aerosol initial and boundary conditions. It then combines regional observation data or a simplified emission inventory to make supplementary corrections to ensure that the simulation process can continue smoothly. 2. By coupling WRF-FDDA technology with data from multiple meteorological observation platforms and combining it with four-dimensional data assimilation techniques, the initial atmospheric state can be finely calibrated in both time and space. This can effectively improve the simulation accuracy of cloud water resources and provide more accurate initial field conditions for the warm cloud catalysis process. Furthermore, WRF-CABIN, with its large eddy simulation capability, can conduct high-resolution simulations of processes such as warm cloud catalyst seeding and aerosol-cloud interactions at small scales (such as in local mountainous areas and urban heat islands). This can capture key features such as turbulent motion and changes in cloud microphysical structure that are difficult to interpret with traditional models, thereby providing a scientific basis for optimizing warm cloud catalysis strategies and evaluating the effectiveness of weather modification. 3. By integrating natural aerosols, anthropogenic aerosols, and warm cloud catalyst seeding sources, an 8-level warm cloud catalyst aerosol classification system has been added to the existing 43 or 33 levels of aerosol / CCN. Based on the catalyst's chemical composition, its molar molecular weight, aerosol density, and ion count are precisely adjusted, and the particle size is adapted according to the spectral distribution, thereby refining the characterization of CCN with different chemical compositions. The dry deposition process of CCN at different levels is introduced, combined with sub-grid vertical mixing to simulate turbulence effects, and improve the aerosol transmission and diffusion mechanism. Aerosol activation is calculated using a microphysical solution, abandoning the chemical process to reduce resource consumption. At the same time, it also provides customized functions such as catalyst seeding and specified spectral distribution. 4. Through flexible initial and boundary condition settings, high-precision data assimilation, and high-resolution simulation capabilities, meteorological fields are generated online through WRF, multi-level aerosol / CCN and newly added catalyst levels are integrated, and a graded microphysics scheme of ambient aerosols is considered through SBM (fast, full, and liquid). This enables simulation of aerosol-cloud interactions and human shadow operations, improves the authenticity of warm cloud catalysis and cloud microphysical process descriptions, and supports weather modification research. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 Schematic diagram of the system structure of the present invention; Figure 2 Schematic diagram of the binned microphysics scheme considering ambient aerosols in the present invention; Figure 3 This is a schematic diagram of the mixing ratio profile of aerosol concentration and water vapor after 24 hours of integration of a single column test of the present invention; wherein, Figure 3 (a) is a schematic diagram of the vertical mixing ratio profile. Figure 3 (b) is a schematic diagram of closing the vertical mixing ratio profile. Figure 3 (c) is a schematic diagram of the water vapor profile; Figure 4 This is a schematic diagram of the time series of ground aerosol concentration and water vapor mixing ratio integrated from 0 to 24 hours in the single column test of the present invention; Figure 5 Schematic diagram of the horizontal and cross-sectional concentration distribution of aerosol when the vertical mixing switch is turned on and off according to the present invention; Figure 6 Schematic diagram of the change of aerosol vertical profile over time in the present invention. DETAILED DESCRIPTION

[0018] The technical solution of the present invention will be further described below with reference to the accompanying drawings.

[0019] The Weather Research and Forecasting (WRF) model is a next-generation mesoscale numerical weather prediction system designed to meet the needs of atmospheric research and operational forecasting. WRF provides the foundational framework and meteorological simulation capabilities for CABIN. Widely used globally and boasting a large user base and research foundation, WRF offers a wealth of experience, data, and model component references for CABIN's technical development. WRF's dynamical core and physical process parameterization scheme provide the underlying support for CABIN's simulation of complex processes such as aerosols, clouds, and precipitation.

[0020] WRF-FDDA is a four-dimensional data assimilation (FDDA) technique based on the WRF model. By integrating multi-source observational data (such as satellite, radar, and ground-based observations) with the WRF model, the model's initial fields are continuously adjusted in both temporal and spatial dimensions, enabling the model to more accurately reflect the actual atmospheric state and improve the accuracy of numerical weather forecasts. CABIN technology focuses on a catalytic scheme for the tiered seeding of warm clouds, which requires precise initial field conditions to accurately simulate aerosol distribution, cloud microphysical processes, and the seeding and catalytic effects of catalysts. WRF-FDDA provides WRF-CABIN with more realistic initial atmospheric conditions, including information on aerosol concentrations and macro- and microscopic cloud characteristics. This compensates for the shortcomings of WRF-CABIN's initial field construction and is crucial for improving its simulation accuracy.

[0021] This invention utilizes WRF and WRF-FDDA as its foundational framework. CABIN technology complements WRF-FDDA and represents a modification of WRF itself. Its operation requires the same operating conditions as WRF or WRF-FDDA. In summary, CABIN technology is deeply coupled with WRF and WRF-FDDA, hence the designations WRF-CABIN, WRF-FDDA-CABIN, or the binned microphysics scheme that considers ambient aerosols.

[0022] like Figure 1-Figure 2 As shown in the figure, the warm cloud bin-by-bin spreading catalytic system based on the four-dimensional multi-source meteorological data assimilation numerical weather model, namely WRF-FDDA-CABIN, consists of nine modules: four-dimensional data assimilation coupling module, emission source generation and reading module, aerosol initial and boundary condition generation module, dust and sea salt coupling module, vertical mixing coupling module, aerosol dry deposition module, aerosol bin setting module, aerosol bin spreading module and catalytic effect calculation module.

[0023] The specific functions of each module are as follows: The four-dimensional data assimilation coupling module is used to integrate atmospheric observation data from different times and dimensions to obtain the initial state information of warm clouds, optimize the initial simulation field, and improve simulation accuracy. The details are as follows: The accuracy of numerical weather forecasts is highly dependent on a precise description of the initial state of the atmosphere. Four-dimensional data assimilation technology can fully integrate multi-source observational data, more accurately depicting the initial state of the atmosphere in both temporal and spatial dimensions, providing high-quality initial conditions for numerical weather models and significantly improving the accuracy and reliability of numerical simulation results. For the simulation of warm cloud processes focused on small and medium-scales, four-dimensional data assimilation technology can effectively integrate multi-source observational data such as satellite remote sensing, radar detection, and ground-based observations to obtain information on the initial state of warm clouds at a refined temporal and spatial resolution, including the cloud's macroscopic structure, microphysical properties, and aerosol distribution. This solves the challenge of accurately simulating cloud water resources and lays the foundation for subsequent simulations of warm cloud catalysis processes.

[0024] The 4D Data Assimilation Coupled Module couples the 4D Data Assimilation technique (WRF-FDDA) to the basic functionality of WRF-CABIN. This coupler enables the calculation of aerosol-cloud interactions, aerosol-diffusion, aerosol-dynamical transmission, and binned catalytic effects within a more accurate cloud water resource and meteorological condition forecast. Furthermore, a separate assimilation and catalytic scheme is employed to separate the assimilation and catalytic phases in terms of time integration, preventing assimilation effects from overriding catalytic effects.

[0025] The emission source generation and reading module is used to process aerosol emission source data and provide various aerosol emission inputs for simulation, as follows: In atmospheric chemistry models, primary aerosols and gases are primarily generated through releases, and emission sources describe the rate, temporal, and spatial distribution of these releases. Therefore, using appropriate emission source data is a crucial prerequisite for a reasonable simulation of aerosols or CCN. WRF-SBM does not employ an emission source scheme; instead, it simply sets initial values ​​and fixed boundary conditions to idealize the aerosol concentration within the simulation domain. Commonly used bulk microphysics schemes typically do not consider the mixing and transport of CCN in three dimensions, thereby simplifying the computational process. In contrast, WRF-SBM divides aerosol concentration into 33 or 43 steps, and integrates and calculates transport, diffusion, and activation processes at each integration step using an online computational approach. This is highly beneficial for a detailed description of the aerosol-cloud-rainfall microphysical processes. Therefore, using an overly idealized aerosol distribution in WRF-SBM can significantly waste these online computations, potentially resulting in suboptimal or even inferior simulation results to those achieved with bulk schemes. Therefore, to address this type of problem, the emission source generation and reading module of WRF-CABIN transplanted and adjusted the emission source reading function in WRF-CHEM atmospheric chemistry, and is compatible with the Multi-resolution Emission Inventory for China (MEIC) and the EDGAR (Emissions Database for Global Atmospheric Research) global atmospheric emission database, etc., to realize the calculation of the "emission source-aerosol emission process" applicable to WRF-SBM.

[0026] Through interpolation, concentration conversion, vertical stratification and other algorithms, the original MEIC emission source list is converted into a gridded pollutant emission list (mainly for aerosols) in the target study area. Then, through density conversion, emission calculation and time accumulation function, the aerosol concentration release value of each grid point in the model is calculated, and finally atmospheric aerosols such as PM 2.5 , PM 10 The mass concentration of chemical substances such as PM 2.5 and PM 10 The aerosol concentration of chemical substances such as pollutants will provide basic data for the calculation of aerosol number concentration at 43 or 33 levels.

[0027] The aerosol initial and boundary condition generation module is used to set the aerosol state parameters at the simulation start time and at the region boundary, such as concentration and particle size, as follows: For online CCN forecasting, in addition to emission sources, initial and boundary conditions are crucial. Initial values ​​define the initial CCN concentration distribution, while boundary conditions provide information on external inputs to the target area. After a series of processes, including emission source input, atmospheric chemistry, transport and diffusion, vertical mixing, and dry deposition, online CCN concentration forecasts are obtained, which are then further simulated using microphysics schemes.

[0028] In the WRF-SBM scheme, the initial CCN concentration values ​​and boundary conditions are preset concentrations, not real-world online CCN simulations. Consequently, the simulation results are overly idealized, lacking regional distribution characteristics, incapable of accounting for new particle formation and chemical evolution, lacking diurnal and seasonal variations, and idealizing vertical and horizontal concentration distributions. The WRF-CABIN technology, through external input embedding, processes the simulation results of two global atmospheric chemistry models, generating aerosol initial and boundary conditions for a given timeframe in the target region. These are then converted into the 43- and 33-bin CCN number concentrations required for binned microphysical processes. Accessible global atmospheric chemistry models include CHEM-CAM and WACCM.

[0029] The sand and sea salt coupling module is used to consider the generation and transport of sand and dust (terrestrial) and sea salt (marine) aerosols and integrate them into the overall simulation. The details are as follows: The GOCART overall dust solution mainly adjusts and couples the bulk dust module in aerosol-aware thompson to calculate dust aerosol emissions. The dust particle emissions are calculated based on different parameters (such as soil moisture, wind speed, soil type, etc.) and added to the e_pm_dust array.

[0030] First, based on the density and diameter of the dust particles, the mass of the dust particles (dustmas) is calculated, and based on the mass of the dust particles, wind speed and some constants, the threshold wind speed (u_ts0) of the dust particles is calculated. Next, based on the value of soil moisture (gwet), it is determined whether the soil is dry enough to produce dust particle emissions. If the soil is dry enough, the threshold wind speed (u_ts) is adjusted according to the soil moisture. Then, based on the erosivity (erodin) of the dust particles, wind speed and some constants, the emission area (srce) of the dust particles is calculated. Finally, based on the emission area, wind speed and some constants of the dust particles, the emission of dust particles (dsrc) is calculated. This calculation process takes into account factors such as the density, diameter, wind speed, soil moisture and erosivity of the dust particles to determine the emission of dust particles. Then the equivalent of PM 2.5 and PM 10The part is further refined into 43 or 33 aerosol bins, and the overall spectrum distribution is defined by the aerosol bin setting module.

[0031] The GOCART 5-level dust coupling scheme, GOCART (Goddard Chemistry Aerosol Radiation and Transport), is based on 10 m wind speed and soil moisture. It calculates vertical dust flux in five particle size segments: 0-1, 1-1.8, 1.8-3, 3-6, and 6-10 μm. The vertical dust flux calculation formula for dust particles is as follows: ; Where G represents the vertical dust flux and C is a constant of 0.8 μg·s -2 ·m 5 , S is the wind erosion index, which represents the influence of potential dust source distribution on surface characteristics such as ice and snow coverage and vegetation rate, is the mass ratio of dust in each particle size range, except for 0~1μm particle size which is 0.1, all other particle sizes are 0.25, is the horizontal wind speed at 10m above the ground, is the critical friction speed, which is affected by the size of dust particles and soil moisture.

[0032] In WRF-CABIN, the GOCART bulk scheme can calculate and generate dust particle emissions. The dust particle emissions are calculated based on different parameters (such as soil moisture, wind speed, soil type, etc.), added to the e_pm_dust array, and the corresponding aerosol emissions are calculated. The dust spectrum distribution is refined by the aerosol bin setting module.

[0033] The GOCART overall sea salt scheme is based on the parameterization method of the sea salt aerosol source function of the semi-empirical formula of the existing technology (Monahan, EC, Spiel, DE,&Davidson, KL (1986). A model of marine aerosol generation via whitecapsand wave disruption. In Oceanic whitecaps (pp. 167-174). Springer, Dordrecht.) and the existing technology (Gong, SL (2003). A parameterization of sea-saltaerosol source function for sub-and super-micron particles. Globalbiogeochemical cycles, 17(4).). It mainly considers the submicron and supermicron particles formed by wave breaking and whitecaps. The overall spectrum distribution is defined by the aerosol bin setting module. When waves on the ocean surface break, small water droplets are generated. These water droplets contain salt particles in the seawater. At the same time, wind power will also carry salt particles in the seawater into the air. These salt particles are suspended in the atmosphere in the form of water droplets or aerosols, and then dispersed and spread with the movement of the atmosphere.

[0034] The GOCART 4-step sea salt scheme is based on a semi-empirical formula from existing technology (Monahan, EC, Spiel, DE, & Davidson, KL (1986). A model of marine aerosol generation via whitecapsand wave disruption. In Oceanic whitecaps (pp. 167-174). Springer, Dordrecht.). It develops a sea salt source function parameterization method suitable for submicron and submicron particles, extending the applicability of the Monahan formula to the particle size range of 0.05μm while maintaining good simulation results for sea salt aerosols with a radius greater than 0.2μm. This is of great significance for accurately predicting the number particle size distribution of sea salt aerosols and assessing their indirect impact on climate, especially when submicron particles may play a major role in aerosol-cloud interactions.

[0035] The dust and sea salt coupling module couples GOCART's four-level sea salt scheme, and then further refines the four-level sea salt aerosol into 43 or 33 levels of aerosol. The spectral distribution refinement rules are defined by the aerosol classification setting module.

[0036] The vertical mixing coupling module is used to characterize the mixing and diffusion of aerosols in the vertical direction (at different altitudes) and reflect the changes in their vertical distribution, as follows: The catalyst's transport and mixing processes are crucial to the effectiveness of the shadow operation, determining whether the spread catalyst can be properly transported and diffused to the target location in three-dimensional space. The transport process primarily relies on grid-scale atmospheric flow calculations, which are implemented within the WRF dynamics framework. The sub-grid mixing of the catalyst requires consideration of atmospheric boundary layer processes.

[0037] Vertical mixing of species within the atmospheric boundary layer is driven by eddies ranging in diameter from 100 to 3000 meters, which determine the atmospheric state within the boundary layer (Roland B. Stull). However, most mainstream NWP scales fail to resolve this turbulence. In the WRF model, the primary responsibility of the boundary layer parameterization scheme is to parameterize turbulent exchange processes at the subgrid scale and describe them at the grid scale. The various boundary layer schemes in standard WRF only parameterize vertical mixing of specified atmospheric scalar fields (such as T and Q) and do not address additional introduced variables such as aerosols and chemical gases. In the current version of WRF-Chem, the turbulent diffusion coefficient is diagnosed by a subset of boundary layer parameterization schemes, including YSU, MYJ, MYNN2, BL, QNSE, and UW. Vertical mixing of chemical species is handled in a separate subroutine using a first-order closure scheme. Therefore, in WRF-Chem, the diffusion of chemical species is affected only by the local mixing processes in the boundary layer scheme, while meteorological variables are affected by the combined effects of local mixing, nonlocal mixing, and entrainment processes depending on the selected boundary layer scheme.

[0038] An independent local subgrid vertical mixing scheme in WRF-CHEM is coupled with the WRF-CABIN scheme. This scheme uses a diffusion equation to calculate the temporal variation of species mixing ratios due to vertical mixing and dry deposition. The general form of the diffusion equation can be expressed as: ; in, is the species mixing ratio, t is time, z is the vertical coordinate, D is the diffusion coefficient, and Vd is the dry deposition velocity. The diffusion coefficient and dry deposition velocity are given by the input parameters kt_turb and vd. The diffusion equation is discretized into a tridiagonal matrix by calculating the coefficients a_coeff and b_coeff. The discretized diffusion equation is then solved to obtain the temporal variation of the species mixing ratio.

[0039] This solution can independently handle the vertical mixing process of aerosol subgrids at 33 or 43 bins, adapting to various boundary layer schemes and operating efficiency far superior to high-resolution LES. The vertical mixing switch in the module only affects the aerosol diffusion process.

[0040] The Aerosol Dry Deposition module is used to simulate the dry deposition of aerosols to the surface due to gravity, turbulence, and other factors. It is related to the removal of aerosols. The details are as follows: Gravitational dry deposition refers to the slow sinking of aerosol particles to the ground due to their large mass under the influence of gravity. The settling rate of a particle is related to factors such as its size, density, and air viscosity. Large aerosol particles settle to the ground faster due to gravity, while small particles settle more slowly. Gravitational deposition primarily uses Stoke's law to calculate the settling rate of aerosol CCN particles larger than 1 μm: ; in, is the sedimentation velocity (unit: m / s), r is the radius of the particle (unit: m), is the density of the particle (in kg / m 3 ), is the density of air (in kg / m 3 ), g is the acceleration due to gravity, about 9.81m / s 2 , is the dynamic viscosity of air.

[0041] Generally speaking, only aerosol particles with a size greater than 1 micron need to consider the gravity sedimentation process, especially PM 10 and PM 2.5 For particles smaller than 1 micron, gravitational settling is weak, and they primarily travel through the atmosphere via other mechanisms (such as diffusion and convection). Gravitational settling is even more pronounced for particles larger than 10 microns. If dry gravitational settling occurs, large, spreading aerosols lose the ability to fall.

[0042] The aerosol classification module is used to classify aerosols into different classes (categories) based on properties such as particle size, and to simulate the behavior of aerosols of different particle sizes in a refined manner. The details are as follows: Atmospheric aerosols can be divided into the Aegon nucleation mode (0.001-0.1 μm), the accumulation mode (0.1-1 μm), and the coarse mode (>1 μm) based on their aerodynamic diameter. From a physical perspective, the Aegon nucleation mode arises from gas-particle conversion, the accumulation mode arises from collisions and heterogeneous condensation, and the coarse mode is primarily generated by mechanical processes. Aerosol particles that act as condensation nuclei for water vapor to condense into cloud particles are called cloud condensation nuclei (CCNs) and are typically smaller than 1 μm. Generally speaking, aerosols of different particle sizes have different effects on cloud droplet nucleation and growth. Accurately describing the aerosol size distribution helps better simulate cloud microphysical processes. Therefore, considering aerosol size bins in binned cloud models is essential.

[0043] The aerosol spreading module is used to simulate the spreading of different aerosol levels (such as the spreading operation in weather modification) as follows: Essentially, warm cloud catalyst seeding and aerosol emission sources inject atmospheric chemicals into the model's three-dimensional space and allow them to follow atmospheric motion. Based on the atmospheric state, their transport, diffusion, and deposition processes are calculated. This module develops a scheme suitable for graded aerosol seeding, based on the silver iodide seeding technology used in cold cloud catalysis. This module not only retains the multiple injection methods of all silver iodide seeding technologies, but also adds an aerosol grading function, allowing injected aerosols of a certain mass concentration to be parsed into 43 or 33 grades of CCN concentration based on atmospheric conditions and a custom aerosol spectrum distribution. Using point, line, and surface source seeding modules, different seeding schemes such as aircraft, rockets, anti-aircraft guns, and ground-based smoke stoves can be implemented.

[0044] Namelist injection: Edit the namelist file during WRF runtime to set the seeding location, seeding time, and seeding rate (mass concentration / area / time) to inject a specified aerosol type. This technique requires no data preparation or processing and is flexible and adaptable. Up to six point sources and one volume source can be configured. The volume source can be adjusted to point, line, or area sources using x, y, and z range settings. Only fixed emission sources are considered. It is suitable for a small number of ground point sources and catalytic seeding tests.

[0045] Gridded Source Injection: Similar to source injection in WRF-CHEM, gridded source injection uses a special data channel to read specific emissions from a 3D NC source data file at a fixed time point. This technique is suitable for large, fixed sources and for mobile sources with long-term fluctuations, such as those that move more than once an hour.

[0046] External sequence file injection. Among the two injection methods above, namelist injection can only describe fixed point sources, while the injection time interval of grid emission sources is limited and cannot describe rapid changes in a short time (such as minutes or seconds). Therefore, both are not suitable for fast movement or instantaneous seeding processes.

[0047] Therefore, through a special file channel and the addition of an external sequence file injection method, the time, location, altitude, and distribution rate of a point source can be described with a maximum integration step time interval. This solution can set up multiple point sources for distribution at fixed times, compensating for the limitation of only six point sources in the namelist emission source. It can also describe aircraft distribution, instantaneous fixed point source distribution, and distribution methods such as antiaircraft artillery and rockets by using rapidly changing time and location information.

[0048] In addition to the aforementioned WRF-CABIN technology's ability to account for the nucleation of natural and anthropogenic aerosol particles in SBM binned cloud microphysics, a binned seeding scheme enables numerical simulation of warm cloud seeding and catalysis. However, this process presents certain challenges: the binned seeding aerosols are fixed and homogeneous with CCN (e.g., sodium chloride or ammonium sulfate), which cannot meet the current requirements for evaluating new warm cloud catalysts, which require consideration of the impact of their varying chemical composition. Therefore, this technical solution incorporates eight additional bins of warm cloud catalyst aerosols into WRF-CABIN. Three properties—molar molecular weight (MAERO), aerosol density (RHO), and number of ions (IONS)—can be adjusted based on the catalyst's chemical composition, while the catalyst particle size can be adjusted based on its spectral distribution.

[0049] The catalytic effect calculation module is used to calculate the effect of catalytic processes involving aerosols (such as the catalysis of cloud precipitation, etc.), as follows: Previous research has demonstrated that different CCN concentrations and particle size distributions can be set within a binned cloud microphysics scheme to simulate aerosol-cloud-precipitation processes in various scenarios. A warm cloud catalysis scheme was designed based on the custom aerosol profile technology within WRF-CABIN and the simulation of warm cloud catalyst seeding. The specific catalysis scheme involves first simulating atmospheric aerosols and warm cloud processes using natural and anthropogenic aerosol profiles as a control experiment. Next, a catalyst-profile aerosol is seeded as a seeding experiment. The two experiments, with and without seeding, are compared to determine the warm cloud catalysis effect.

[0050] In terms of spatial distribution, PM in anthropogenic CABIN 2.5 The emission sources are mainly on land and ocean waterways, which can better reflect the spatial distribution of aerosol CCN released by human activities. This is a huge improvement to WRF-SBM.

[0051] like Figure 3 As shown, the mixing ratio profiles of aerosol concentration and water vapor after 24 hours of integration of the single-column test are displayed. In order to reflect the importance of vertical mixing and diffusion of aerosols, an ideal single-column test of chemical-free aerosol diffusion (WRF_SCM) is carried out, and an emission source that continuously emits aerosol catalyst is placed on the ground.

[0052] like Figure 4 The figure shows the time series of ground aerosol concentration and water vapor mixing ratio for a single-column experiment from 0 to 24 hours. These results show that if vertical mixing is disabled, aerosols accumulate at the ground level, causing ground concentrations to continue to rise. However, with vertical mixing enabled, aerosols diffuse vertically, resulting in a diurnal variation in ground concentrations. The aerosol profile and diurnal variation are similar to those of water vapor, making them more reasonable.

[0053] A ground-seeding point source was placed in the test area to investigate the effects of vertical mixing on aerosols in the real atmosphere during ground-seeding diffusion. Comparison revealed that vertical mixing allows the seeded aerosol to disperse vertically at a reasonable altitude, especially during daytime. If vertical mixing is disabled, silver iodide will have difficulty leaving the seeding layer and will be transported more horizontally, which is crucial for ground-seeding smoke stoves. Because ground seeding is a bottom-up diffusion and transport process, if the boundary layer is well-developed and turbulent activity within the mixing layer is appropriate, ground-seeded pollutants will be carried higher by turbulent activity, making them more likely to reach critical seeding areas.

[0054] like Figure 5 As shown in Figure 2, the horizontal and vertical (profile) concentration distributions of aerosols in the test case are shown when the vertical mixing switch is turned on and off; Figure 6 As shown, the vertical profile of aerosols changes with time, and the horizontal axis is the time series (15-minute intervals). When the model resolution is not enough to resolve the turbulence scale, the vertical mixing scheme can reflect the sub-grid mixing process of the catalyst in the vertical direction under the action of turbulent mixing. In addition, the present invention is faster, more effective, and more stable than high-resolution large eddy simulation, and therefore has more business conditions. On the other hand, in addition to spreading aerosols, natural / artificial aerosols also require vertical mixing to reflect the impact of boundary layer turbulent transport on the distribution of ground pollutants. If vertical mixing is not turned on, ground pollutants will continue to accumulate, causing the aerosol concentration near the pollution source to continue to accumulate, resulting in unrealistic high values. Therefore, vertical mixing plays a very important role in the online simulation of CCN and the diffusion of warm cloud catalysts.

[0055] By comparing the distribution of initial concentrations of SBM FAST and CABIN, it can be seen that WRF-CABIN can adopt more realistic initial and boundary conditions compared to WRF-SBM.

[0056] All of the aforementioned spreading technologies have been upgraded with a tiered option. Users can customize their own aerosol profile. This module allows for bin-by-bin spreading of 33 or 43 bins of aerosol CCN. The specific amount (number concentration) of each bin is calculated from the aerosol profile and the total amount of aerosol catalyst spread.

[0057] A warm cloud catalysis experiment was conducted to simulate a convective process over Fujian Province on November 11, 2023. First, a control experiment was conducted, specifying the spectrum type p1 for both natural and anthropogenic sources. Then, a seeding experiment was conducted, specifying the spectrum type p101 for both natural and anthropogenic sources, seeding the catalyst in the 10th layer of the model. Thirty minutes after seeding began, the changes in qrain and cloud_rain for both experiments (seeding experiment minus the control experiment) were analyzed. Analysis of the warm cloud catalysis effect revealed a broadening of the cloud raindrop particle size spectrum and an increase in QRAIN within the convective cloud region. This demonstrates CABIN's ability to simulate warm cloud seeding catalysis processes and can provide a fundamental tool for simulating and evaluating warm cloud catalysis effects in the weather modification industry, thereby generating economic value.

Claims

1. A warm cloud tiered seeding catalytic system based on four-dimensional multi-source meteorological data assimilation numerical weather model, characterized by: include: The four-dimensional data assimilation coupling module is used to fuse multi-source observation data through four-dimensional data assimilation technology to obtain the initial state information of warm clouds; Emission source generation and reading module, used to convert the emission source inventory into a gridded pollutant emission inventory for the target study area to form atmospheric aerosols; The aerosol initial and boundary condition generation module is used to generate the aerosol initial and boundary conditions in the target study area within a given time and convert them into the CCN number concentration required for the binned microphysical process; The dust and sea salt coupling module is used to calculate the emission of dust and sea salt aerosols and integrate them into the overall simulation; A vertical mixing coupling module is used to calculate the temporal variation of species mixing ratios due to vertical mixing and dry deposition; Aerosol dry deposition module, used to simulate the gravitational deposition process of aerosol particles at different levels; The aerosol classification setting module is used to divide the aerosol into different grades to simulate the behavior of aerosols with different particle sizes; Aerosol graded spreading module, used to simulate the spreading process of aerosols in different grades; The catalytic effect calculation module is used to calculate the catalytic effect of the catalytic process involving aerosols.

2. The warm cloud grading catalytic system according to claim 1 is characterized in that: The multi-source observation data in the four-dimensional data assimilation coupling module include all WTO / GTS standard stations, automatic weather stations, wind profiler radars, satellite observations, weather radars, microwave radiometers, flight weather reports, and meteorological observation data; the initial state information of warm clouds includes the cloud's macroscopic structure, microphysical properties, and aerosol distribution.

3. The warm cloud grading spreading catalytic system according to claim 1 is characterized in that: The emission source generation and reading module calculates the aerosol concentration release value of each grid point through density conversion, emission calculation and time accumulation function to form atmospheric aerosol.

4. The warm cloud grading spreading catalytic system according to claim 1, characterized in that: The aerosol initial and boundary condition generation module obtains the online prediction result of CCN number concentration through emission source input, atmospheric chemical process, transmission diffusion, vertical mixing, and dry deposition process, and further simulates.

5. The warm cloud grading spreading catalytic system according to claim 1, characterized in that: The sand, dust and sea salt coupling module includes the GOCART overall sand and dust scheme, the GOCART 5-speed sand and dust coupling scheme, the GOCART overall sea salt scheme and the GOCART 4-speed sea salt scheme; The GOCART dust program calculates dust aerosol emissions and is equivalent to PM 2.5 and PM 10 The part is further refined into 43 or 33 aerosol grades, and the overall spectrum distribution is defined by the aerosol grade setting module; The GOCART 5-speed dust coupling scheme calculates the vertical dust flux in five particle size segments and the corresponding aerosol emissions; The GOCART overall sea salt scheme calculates sea salt aerosol emissions based on a parameterized method of sea salt aerosol source function based on a semi-empirical formula; The GOCART 4-grade sea salt solution obtains a sea salt source function parameterization method suitable for submicron and submicron particles based on a semi-empirical formula to calculate the number particle size distribution of sea salt aerosols, and further refines the 4-grade sea salt aerosols into 43 or 33 grades of aerosols.

6. The warm cloud grading spreading catalytic system according to claim 1, characterized in that: The vertical mixing coupling module is used to calculate the temporal variation of species mixing ratios due to vertical mixing and dry deposition using the diffusion equation, which is as follows: ； in, is the species mixing ratio, t is time, z is the vertical coordinate, D is the diffusion coefficient, and Vd is the dry deposition velocity.

7. The warm cloud grading spreading catalytic system according to claim 1, characterized in that: The Stoke's law is applied in the aerosol dry deposition module to calculate the settling velocity of aerosol CCN particles larger than 1 μm. The formula is as follows: ； in, is the sedimentation velocity, r is the radius of the particle, is the density of the particle, is the density of air, g is the acceleration due to gravity, is the dynamic viscosity of air.

8. The warm cloud grading spreading catalytic system according to claim 1, characterized in that: The aerosol classification setting module divides the aerosol into an aerosol core mode, an accumulation mode and a coarse mode according to the aerodynamic diameter.

9. The warm cloud grading spreading catalytic system according to claim 1, characterized in that: The aerosol grading spreading module includes: considering the influence of its different chemical components, adding 8 levels of warm cloud catalyst aerosol, adjusting the three properties of molar molecular weight MAERO, aerosol density RHO and ion number IONS according to the chemical composition of the catalyst, and adjusting the particle size of the catalyst according to the spectral distribution.

10. The warm cloud grading spreading catalytic system according to claim 1, characterized in that: The catalytic effect calculation module includes: simulating atmospheric environmental aerosols and warm cloud processes using natural and artificial aerosol spectra as a control experiment; adding aerosols with catalyst spectra for seeding as a seeding experiment, and comparing the two experiments with and without seeding to obtain the warm cloud catalytic effect.

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