A method, device and equipment for generating a typhoon event set based on climate change

Abstract

The present application relates to the technical field of typhoon disaster risk assessment, and discloses a typhoon event set generation method, device, equipment and medium based on climate change, which comprises the following steps: obtaining historical tropical cyclone path data set corresponding to the current climate scenario, and generating a first random event set and an alternative random event set based on the same; generating a first landing typhoon proportion table according to the sea area level and landing level of each landing typhoon event in the first random event set; obtaining a sea area typhoon annual average number change table of a future period under a preset climate scenario; determining the number of typhoon events added and reduced in the first random event set based on the first landing typhoon proportion table and the sea area typhoon annual average number change table, processing the typhoon events in the first random event set, and obtaining a target random event set. The present application determines the number of typhoon events added and reduced in the random event set by the number of typhoon events in the sea area of the future period, so that the finally determined typhoon events can reflect the typhoon risk under the future scenario.

Description

Technical Field

[0001] This invention relates to the field of typhoon disaster prediction technology, specifically to a method, apparatus, equipment, and medium for generating typhoon event sets based on climate change. Background Technology

[0002] Climate change is one of the greatest challenges facing humanity's future, with its impact on the economy constantly increasing. The international community has begun to study incorporating climate risk into the financial risk management framework. The frequent occurrence of extreme weather events under climate change poses substantial physical and transformation risks to financial institutions' investment portfolios. To effectively address the risks posed by climate to financial institutions, climate risk management is necessary, and climate risk stress testing is an important tool and approach for climate risk management.

[0003] Physical risk is essentially extreme weather risk, with typhoons being a significant hazard. To achieve good testing results when stress-testing typhoon-related climate risks, catastrophic models are often used to quantify the risk. However, using catastrophic models requires a set of typhoon events as input. Current technologies often generate typhoon event sets by perturbing historical typhoon events. This method of generating event sets is often limited by historical data and cannot fully reflect future changes in typhoon risk. Summary of the Invention

[0004] In view of this, the present invention provides a method, apparatus, device and medium for generating typhoon event sets based on climate change, in order to solve the problem that existing typhoon event sets cannot reflect the physical risks of typhoons under future scenarios.

[0005] In a first aspect, the present invention provides a method for generating typhoon event sets based on climate change, the method comprising:

[0006] Obtain a dataset of historical tropical cyclone tracks corresponding to the current climate scenario;

[0007] Based on the historical tropical cyclone path dataset, a first random event set and a candidate random event set are generated using a preset typhoon event generation model.

[0008] Determine the landfall typhoon events in the first random event set and the corresponding sea area level and landfall level for each landfall typhoon event. Based on the number of typhoon events under different sea area levels and landfall levels, generate a table of proportions of the first landfall typhoons.

[0009] Obtain a table showing the annual average number of typhoons in the sea area under a preset climate scenario for future periods;

[0010] Based on the first landfall typhoon proportion table and the annual average number of typhoons in the sea area table, the increase or decrease in the number of typhoon events under different sea area levels and landfall levels in the first random event set is determined.

[0011] Based on the increase or decrease in the number of typhoon events under different sea area levels and landfall levels in the first random event set and the candidate random event set, the typhoon events in the first random event set are processed to obtain the target random event set.

[0012] This method generates a first random event set and a candidate random event set using historical tropical cyclone track datasets. Based on the sea area and landfall level of the landfall typhoons in the first random event set, a landfall typhoon proportion table is generated. Then, combined with a table of the annual average number of typhoons in the sea area under a preset climate scenario, the increase or decrease in the number of typhoon events at different levels in the first random event set is determined. This allows for the processing of typhoon events in the first random event set to obtain a target random event set. The final typhoon event set can take into account the changes in the number of typhoons under future scenarios, resulting in better testing performance when conducting typhoon risk stress tests based on this typhoon event set.

[0013] In one optional implementation, the set of random events includes: typhoon events corresponding to multiple random years;

[0014] The determination of the increase or decrease in the number of typhoon events under different sea area levels and landfall levels in the first random event set, based on the first landfall typhoon proportion table and the annual average number of typhoons in the sea area table, includes:

[0015] Based on the first landfall typhoon proportion table and the annual average number of typhoons in the sea area table, the annual average number of typhoon events under different sea area levels and landfall levels is determined.

[0016] The increase or decrease in the number of typhoon events under different sea area levels and landfall levels is determined based on the average annual number of typhoon events under different sea area levels and landfall levels and the number of random years corresponding to the first random event set.

[0017] In this implementation, the annual average number of typhoon events under different sea area levels and landfall levels in the first random event set is determined by using the first landfall typhoon proportion table and the annual average number of typhoons in the sea area table. Combined with the total number of random years in the first random event set, the increase or decrease in the number of typhoon events under each level can be obtained. This allows for a more accurate determination of the increase or decrease in the number of typhoon events in the first random event set based on the changes in the number of typhoons in the future, so as to facilitate subsequent adjustments to the typhoon events in the first random event set.

[0018] In one optional implementation, the processing of typhoon events in the first random event set based on the increase or decrease in the number of typhoon events under different sea area and landfall levels in the first random event set and the candidate random event set includes:

[0019] Determine the increase or decrease in the number of typhoon events under each sea area level and landfall level;

[0020] If the increase or decrease in the number of typhoon events is negative, multiple random samples are taken from the typhoon events of the corresponding sea area level and landfall level in the first random event set according to the increase or decrease, and each collected typhoon event is deleted.

[0021] If the increase or decrease in the number of typhoon events is positive, multiple random samples are taken from the typhoon events of the corresponding sea area level and landfall level in the candidate random event set according to the increase or decrease, and the collected typhoon events are added to the first random event set.

[0022] This implementation method, by randomly sampling and deleting typhoon events in the first random event set and randomly sampling and adding typhoon events from the candidate random event set to the first random event set according to the positive or negative sign of the number of typhoon events corresponding to each sea area level and landfall level, can ensure that the typhoon events in the first random event set conform to the typhoon number changes in a specific period under future scenarios, and provide a scientific, objective and relatively stable risk quantification basis for subsequent typhoon risk stress tests.

[0023] In one optional implementation, the set of random events further includes: weights corresponding to each typhoon event;

[0024] The step of performing multiple random samplings based on the increase or decrease in quantity includes:

[0025] For each random sample, normalization calculation is performed based on the weight of the current typhoon event under the corresponding sea area level and landfall level to obtain the normalized weight range;

[0026] By setting a random number seed and a random number generator to determine the sampling random number, and based on the sampling random number and the normalized weight interval, the typhoon event corresponding to this random sampling is determined.

[0027] In this embodiment, the sampling random number is determined by setting a random number seed and a random number generator, thereby ensuring the reproducibility and randomness of random sampling.

[0028] In one optional implementation, the first set of random events includes: typhoon events corresponding to multiple random years;

[0029] Adding the collected typhoon events to the first random event set includes:

[0030] Based on the Poisson distribution, determine the increase in each random year in the first random event set under the corresponding sea area level and landing level;

[0031] Based on the increase corresponding to each random year, typhoon events collected from the candidate random event set will be added to the corresponding random year in the first random event set.

[0032] In this implementation, after collecting typhoon events from the candidate random event set, the number of typhoons to be added in each random year is determined by the Poisson distribution. This allows the typhoon events collected from the candidate random event set to be added to the corresponding random year, so that the typhoon events added to the first random event set conform to the typhoon distribution under real conditions.

[0033] In an optional implementation, after obtaining the target set of random events, the method further includes:

[0034] The target random event set is compared with the first random event set, and the change rate of typhoon events corresponding to each landfall level is statistically analyzed.

[0035] Based on the preset change parameters and the change rate of typhoon events corresponding to each landfall level, determine whether the target random event set is qualified.

[0036] In this embodiment, the rate of change of typhoon events at each level is determined by comparing the final determined target random event set with the first random event set, and then compared with the preset change parameters to ensure that the final determined target random event set conforms to the actual situation.

[0037] In one optional implementation, the table of annual average number of typhoons in the sea area includes: the annual average number of typhoon events under each sea area level;

[0038] The determination of the annual average number of typhoon events under different sea area and landfall levels, based on the first landfall typhoon proportion table and the annual average number of typhoons in the sea area table, includes:

[0039] Determine the proportion of typhoon events of different landfall levels under each sea area level in the first typhoon landfall proportion table;

[0040] Based on the proportion of typhoon events of different landfall levels under each sea area level and the annual average number of such events corresponding to each sea area level, the annual average number of such events of different landfall levels under each sea area level is determined.

[0041] In this implementation method, by combining the proportional relationship between typhoon events of different landfall levels under each sea area level in the first landfall typhoon proportion table with the annual average number of changes corresponding to each sea area level in the annual average number of typhoon events change table, the annual average number of changes corresponding to each sea area level can be accurately obtained.

[0042] Secondly, the present invention provides a typhoon event set generation device based on climate change, the device comprising:

[0043] The historical data acquisition module is used to acquire a dataset of historical tropical cyclone paths corresponding to the current climate scenario;

[0044] The random event generation module is used to generate a first random event set and a candidate random event set based on the historical tropical cyclone path dataset and a preset typhoon event generation model.

[0045] The typhoon landfall determination module is used to determine the landfall typhoon events in the first random event set and the corresponding sea area level and landfall level for each landfall typhoon event, and to generate the first landfall typhoon proportion table based on the number of typhoon events under different sea area levels and landfall levels.

[0046] The quantity change acquisition module is used to obtain a table of the annual average number of typhoons in the sea area for future periods under a preset climate scenario;

[0047] The increase / decrease quantity determination module is used to determine the increase / decrease quantity of typhoon events under different sea area levels and landfall levels in the first random event set based on the first landfall typhoon ratio table and the annual average number of typhoons in the sea area table.

[0048] The random event set processing module is used to process the typhoon events in the first random event set based on the increase or decrease in the number of typhoon events under different sea area levels and landfall levels in the first random event set and the candidate random event set, so as to obtain the target random event set.

[0049] Thirdly, the present invention provides a computer device, including: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the computer instructions to perform the climate change-based typhoon event set generation method described in the first aspect or any corresponding embodiment thereof.

[0050] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the climate change-based typhoon event set generation method of the first aspect or any corresponding embodiment thereof. Attached Figure Description

[0051] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0052] Figure 1 This is a flowchart illustrating a method for generating typhoon event sets based on climate change according to an embodiment of the present invention.

[0053] Figure 2 This is a flowchart illustrating another method for generating typhoon event sets based on climate change according to an embodiment of the present invention;

[0054] Figure 3 This is an example diagram comparing the number of event sets under different typhoon intensities across the country according to an embodiment of the present invention;

[0055] Figure 4 This is an example diagram comparing the average annual number of typhoon events of preset typhoon level or above in different provinces according to an embodiment of the present invention.

[0056] Figure 5 This is a structural block diagram of an apparatus for generating typhoon event sets based on climate change, according to an embodiment of the present invention.

[0057] Figure 6 This is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. Detailed Implementation

[0058] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, 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, 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.

[0059] Climate change is one of the greatest challenges facing humanity's future, with its impact on the economy constantly increasing. The international community has begun to study incorporating climate risk into the financial risk management framework. The frequent occurrence of extreme weather events under climate change poses substantial physical and transformation risks to financial institutions' investment portfolios. To effectively address the risks posed by climate to financial institutions, climate risk management is necessary, and climate risk stress testing is an important tool and approach for climate risk management.

[0060] Physical risk is essentially extreme weather risk, and typhoons are an important type of disaster. When stress testing climate risks such as typhoons, it is necessary to prepare a certain set of typhoon events for risk stress testing. In the existing technology, the generation of typhoon event sets is often achieved by perturbing historical typhoon events. Such event sets are often limited by historical data and cannot fully reflect the changes in typhoon risk under future scenarios.

[0061] To address this, this invention provides a method for generating typhoon event sets based on climate change. It generates a first random event set and a candidate random event set using a historical tropical cyclone path dataset. Based on the sea area and landfall level corresponding to the landfall typhoons in the first random event set, a typhoon proportion table is generated. This, combined with a table showing the annual average number of typhoons in the sea area under a preset climate scenario, determines the increase or decrease in the number of typhoon events at different levels within the first random event set. This allows for the processing of typhoon events in the first random event set to obtain a target random event set. The final typhoon event set can account for changes in the number of typhoons under future scenarios, resulting in better testing performance when conducting typhoon risk stress tests based on this typhoon event set.

[0062] According to an embodiment of the present invention, a method for generating typhoon event sets based on climate change is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0063] This embodiment provides a method for generating typhoon event sets based on climate change, which can be used for the aforementioned typhoon event set generation. Figure 1 This is a flowchart of a method for generating typhoon event sets based on climate change according to an embodiment of the present invention, such as... Figure 1 As shown, the process includes the following steps:

[0064] Step S101: Obtain the historical tropical cyclone path dataset corresponding to the current climate scenario.

[0065] The term "typhoon" usually refers to a tropical cyclone. However, in professional fields, tropical cyclones are classified into different types based on their wind force, namely tropical depression, tropical storm, severe tropical storm, typhoon, severe typhoon, and super typhoon. Furthermore, different countries and organizations have different classifications and names for tropical cyclones. In the method provided in this application, for ease of understanding and consistent terminology, tropical cyclones of various wind force levels are uniformly referred to as typhoon events. That is, in this embodiment of the method, typhoon events refer to tropical cyclones of various wind force levels, and will be uniformly referred to as typhoons thereafter. Historical tropical cyclone path data can be obtained from relevant meteorological agencies. For example, the historical tropical cyclone path dataset corresponding to the current climate scenario can be the CMA best path dataset from the China Meteorological Administration, which can be obtained from relevant climate websites. The best path dataset provides the position and intensity of tropical cyclones in the Northwest Pacific Ocean every 6 hours since 1949. To make the generated typhoon events more consistent with the current climate scenario, and considering the accuracy of earlier historical records, the best path dataset from 1980 to the present year can be used for subsequent modeling.

[0066] Step S102: Based on the historical tropical cyclone path dataset, generate a first random event set and a candidate random event set using a preset typhoon event generation model.

[0067] After obtaining historical tropical cyclone track datasets, random event sets can be generated based on existing typhoon event generation models. Specifically, a statistical dynamics-based typhoon random event set simulation method can be used to generate random event sets. In this method, for each generated typhoon event, a typhoon formation point model, a movement track model, an intensity model, and a dissipation model are included. These four models can generate typhoon information covering the entire cycle from formation to dissipation. The methods for generating typhoon events described above can be understood through relevant research and will not be elaborated upon here.

[0068] According to this method, a first random event set and a candidate random event set can be generated. The first random event set may include typhoon events corresponding to each of 10,000 random years, i.e., a 10,000-year event set. The candidate event set may include typhoon events corresponding to each of 40,000 random years, i.e., a 40,000-year event set.

[0069] Each random year can be understood as a typhoon event generation model generating possible typhoon events within a year based on the tropical cyclone path dataset corresponding to the current climate scenario. Considering the relatively low probability of typhoon formation, typically 10,000 random years are generated at a time, with each random year's typhoon event representing a possible typhoon event within the current climate scenario. The 40,000-year event set can be understood as obtaining the 40,000-year event set by repeating the 10,000-year event set generation process four times in the above manner.

[0070] Step S103: Determine the landfall typhoon events in the first random event set and the corresponding sea area level and landfall level for each landfall typhoon event, and generate the first landfall typhoon proportion table based on the number of typhoon events under different sea area levels and landfall levels.

[0071] The first set of generated random events can include the specific wind force level for each typhoon event, specifically including a marine area level and a landfall level. The marine area level refers to the maximum wind force level of the typhoon throughout its entire life cycle, while the landfall level refers to the wind force level at the time of landfall. Since typhoons originate from the ocean and different typhoons have different paths, all typhoons making landfall will have a marine area level, but not all marine typhoons will make landfall.

[0072] For the typhoon events in the generated first random event set and candidate random event set, not all typhoon events made landfall. Therefore, by combining coastline information data and the movement paths of each typhoon event in the first random event set, the landfalling typhoons in the first random event set can be determined. Information such as the event ID, landfall location (i.e., the province and latitude / longitude of landfall), typhoon speed at landfall, and landfall time of these landfalling typhoons can be collected to generate landfalling typhoon information tables for the first random event set and candidate random event set respectively. The landfall time can be understood as the specific landfall time within the random year corresponding to the typhoon time. Specifically, in addition to the information mentioned above, the landfalling typhoon information table can also include information such as the maximum wind speed and force level during the lifecycle and the landfall wind force level.

[0073] Specifically, the time ID of a typhoon event can be uniquely composed of the year, month, day of the typhoon's occurrence, and the typhoon number for that year. Furthermore, the year, month, day, and number of each event ID can be reverse-engineered.

[0074] After obtaining the typhoon landfall information table, we can determine the proportion of typhoon events of different landfall levels in typhoon events under each sea area level, and obtain the first landfall typhoon proportion table. An example first landfall typhoon proportion table is shown in Table 1:

[0075] Table 1

[0076]

[0077]

[0078] As shown in Table 1 above, this table illustrates the proportion of typhoon events of each landfall level within different sea area categories. Taking sea area level 2 as an example, the information in the table indicates that within the first random event set, 27.58% of typhoon events in sea area level 2 made landfall. Among these, typhoon events of landfall level 1 accounted for 20.37% of all typhoon events in sea area level 2, and so on. Other landfall levels of typhoon events will not be discussed further here.

[0079] Step S104: Obtain the table of annual average number of typhoons in the sea area for future periods under the preset climate scenario.

[0080] The preset climate scenario can be understood as the climate situation under a certain gas emission scenario. It can be represented by a scientific combination of shared socio-economic pathways (SSPs) and typical concentration pathways (RCPs), namely SSP-RCP. RCPs are a series of comprehensive concentration and emission scenarios, which are used as input parameters for climate change prediction models under the influence of human activities in the 21st century. They describe the emissions of greenhouse gases, reactive gases, and aerosols, as well as the concentration of atmospheric components, when there are changes in future population, socio-economic, scientific and technological, energy consumption, and land use. The preset climate scenario mentioned in step S104 can be understood as the different climate scenarios corresponding to different emission scenarios. When generating the event set, the information under the required climate scenario can be selected according to the actual situation, that is, the change in the average annual number of typhoons in the sea area in the future under the preset climate scenario.

[0081] Specifically, RCPs include a high-emission scenario (8.5W×m). -2 RCP8.5), a medium-emission scenario (6.0 W × m). -2 (RCP6.0) and a low-emission scenario (2.6W × m -2 (RCP2.6). Among them, RCP8.5 causes the largest temperature rise, followed by RCP6.0, RCP4.5, and RCP2.6 has the smallest impact on global warming. An important difference among the four different scenario models is the difference in future land use planning.

[0082] By using relevant scientific research data and expert experience, we can determine how the annual number of typhoons in a future period will change compared to the annual number of typhoons under the current climate scenario, under the climate conditions corresponding to a certain emission scenario of SSP-RCP. This will allow us to obtain a table showing the changes in the annual number of typhoons in the sea area under the preset climate scenario.

[0083] For example, taking a specific RCP emission scenario, assuming the current year is 2024 and the future period refers to 2024 to 2030, expert experience can be used to predict the number of typhoon events of different sea areas and levels during this period under a given RCP emission scenario, thus obtaining the average annual number of typhoons in the future period. It is important to note that the specific paths of typhoons are difficult to determine through expert experience, therefore the exact number of typhoons making landfall cannot be predicted. However, the number of typhoons of different sea areas and levels can be inferred based on specific climate conditions and relevant research, thus allowing us to obtain the number of typhoons of different sea areas and levels in the future period.

[0084] In addition, by combining the historical tropical cyclone path dataset corresponding to the current climate scenario mentioned in step S101 above, taking 1980-2024 as an example, the number of typhoon events of different sea areas and levels during this period is counted, so as to obtain the annual average number of typhoons corresponding to this historical period.

[0085] By comparing the average annual number of typhoons in the future period with the average annual number of typhoons in the historical period corresponding to the current climate scenario, a table showing the annual average number of typhoons in the sea area is obtained. For example, Table 2 shows the annual average number of typhoons in the sea area:

[0086] Table 2

[0087] Sea area level Number of changes per year 2 -0.848 3 -0.537 4 -0.452 5 -0.283 6 -0.176 7 -0.112 8 -0.018 9 -0.034 10 -0.002 … … 16 0.109 17 0.054 18 0.042

[0088] As shown above, we can obtain the changes in the average annual number of typhoons in different sea areas under the preset climate scenario compared to the average annual number of typhoons under the current climate scenario.

[0089] Step S105: Based on the table of proportions of the first landfall typhoons and the table of annual average number of typhoons in the sea area, determine the increase or decrease in the number of typhoon events under different sea area levels and landfall levels in the first random event set.

[0090] The first typhoon landfall proportion table includes the percentage of typhoon events at each landfall level across various sea areas. After determining the annual average number of typhoon events per sea area, and combining this with the annual average number of typhoon events per sea area level in the annual average number of typhoon events per sea area table, the annual average number of typhoon events per sea area level and landfall level can be obtained. Simultaneously, based on the specific number of random years comprising the first random event set, the increase or decrease in the number of typhoon events at each sea area level and landfall level within the first random event set can be determined.

[0091] Step S106: Based on the increase or decrease in the number of typhoon events under different sea area levels and landfall levels in the first random event set and the alternative random event set, process the typhoon events in the first random event set to obtain the target random event set.

[0092] After determining the number of typhoons to be added or removed under different sea area levels and landfall levels in the first random event set, for some typhoon events under sea area levels and landfall levels that need to be reduced, they can be directly deleted randomly from the first random event set; for some typhoon events under sea area levels and landfall levels that need to be added, they need to be randomly selected from the candidate random event set and added to the first random event set. Finally, after adding and deleting from the first random event set, the target random event set can be obtained.

[0093] The typhoon event set generation method based on climate change provided in this embodiment generates a first random event set and a candidate random event set using a historical tropical cyclone path dataset. Based on the sea area and landfall level corresponding to the landfall typhoons in the first random event set, a landfall typhoon proportion table is generated. This table, combined with a table showing the annual average number of typhoons in the sea area under a preset climate scenario, determines the increase or decrease in the number of typhoon events at different levels within the first random event set. This process is then used to process the typhoon events in the first random event set to obtain a target random event set. The final typhoon event set can account for changes in the number of typhoons under future scenarios, resulting in better testing performance when conducting typhoon risk stress tests based on this typhoon event set.

[0094] According to an embodiment of the present invention, another embodiment of a typhoon event set generation method based on climate change is provided, which can be used for the above-described typhoon event set generation. Figure 2 This is a flowchart of another method for generating typhoon event sets based on climate change according to an embodiment of the present invention, such as... Figure 2 As shown, the process includes the following steps:

[0095] Step S201: Obtain the historical tropical cyclone track dataset corresponding to the current climate scenario. For detailed implementation details, refer to [link to implementation details]. Figure 1 Step S101 of the illustrated embodiment will not be described again here.

[0096] Step S202: Based on the historical tropical cyclone path dataset, generate a first random event set and a candidate random event set using a preset typhoon event generation model.

[0097] Specifically, in step S202, the set of random events includes typhoon events corresponding to multiple random years.

[0098] This can be understood as follows: when generating a random event set using a preset typhoon event generation model, typhoon events for multiple random years corresponding to the current climate scenario are generated. These typhoon events corresponding to multiple random years together constitute the first random event set. Similarly, the generation method for the candidate random event set is the same, which will not be elaborated here. For details, please refer to [link to relevant documentation]. Figure 1 Step S202 of the illustrated embodiment will not be described again here.

[0099] Step S203: Determine the landfall typhoon events in the first random event set and the corresponding sea area level and landfall level for each landfall typhoon event. Based on the number of typhoon events under different sea area levels and landfall levels, generate a first landfall typhoon proportion table. For detailed implementation methods, refer to [link to implementation details]. Figure 1 Step S103 of the illustrated embodiment will not be described again here.

[0100] Step S204: Obtain the table of annual average number of typhoons in the sea area for future periods under the preset climate scenario.

[0101] Specifically, in step S204, the table of annual average number of typhoons in the sea area includes: the annual average number of typhoon events under each sea area level.

[0102] This can be understood as the annual average number of typhoons in a sea area representing the change in the average number of typhoon events per year for different sea areas under a given climate scenario, based on a certain gas emission intensity, compared to historical periods under the current climate scenario. For details, please refer to [reference needed]. Figure 1 Table 2 of the illustrated embodiment.

[0103] Step S205: Based on the table of proportion of first landfall typhoons and the table of annual average number of typhoons in the sea area, determine the increase or decrease in the number of typhoon events under different sea area levels and landfall levels in the first random event set.

[0104] Specifically, step S205 includes:

[0105] Step S205-1: Based on the table of proportions of first landfall typhoons and the table of annual average number of typhoons in different sea areas, determine the annual average number of typhoon events under different sea area levels and landfall levels.

[0106] After determining the table of annual average number of typhoons in a sea area, it can be combined with the table of proportions of first landfall typhoons obtained above to determine the annual average number of typhoon events corresponding to different sea area levels and landfall levels. For example, determine the annual average number of typhoon events corresponding to sea area level 2 and landfall level 1, and the annual average number of typhoon events corresponding to sea area level 2 and landfall level 2, etc.

[0107] Specifically, in step S205-1, based on the table of proportions of first landfall typhoons and the table of annual average number of typhoons in different sea areas, the annual average number of typhoon events under different sea area and landfall levels is determined, including:

[0108] Determine the proportion of typhoon events of different landfall levels under each sea area level in the first landfall typhoon proportion table;

[0109] Based on the proportion of typhoon events of different landfall levels under each sea area level and the annual average number of events corresponding to each sea area level, the annual average number of events of different landfall levels under each sea area level is determined.

[0110] Based on the above Figure 1 Taking Tables 1 and 2 in the illustrated embodiment as examples, and taking sea area level 2 as an example, in Table 2, the corresponding annual average number of events is -0.848. In Table 1, the proportion of typhoon events at sea area level 2 and landfall level 1 relative to all typhoon events at sea area level 2 is 20.37%, and the proportion of typhoon events at sea area level 2 and landfall level 2 is 7.31%. The annual average number of events corresponding to sea area level 2 and landfall level 1 is 20.37% × (-0.848) = -0.1726. Similarly, the annual average number of events corresponding to different sea area levels and landfall levels can be determined. For example, it can be shown in Table 3.

[0111] Table 3

[0112]

[0113]

[0114] Step S205-2: Determine the increase or decrease in the number of typhoon events under different sea area levels and landfall levels based on the annual average number of typhoon events under different sea area levels and landfall levels and the number of random years corresponding to the first random event set.

[0115] After determining the average annual variation in the number of typhoon events under different sea area and landfall levels, and combining this with the number of random years in the first random event set, the increase or decrease in the number of typhoon events under different sea area and landfall levels can be obtained, for example, as described above. Figure 1As shown in step S102 of the illustrated embodiment, the generated first random event set can be a ten-thousand-year event set. Therefore, the increase or decrease in the number of typhoons under each sea area level and landfall level in this first random event set is the corresponding annual average change multiplied by ten thousand. For example, in the first random event set, the increase or decrease in the number of typhoon events corresponding to sea area level 1 and landfall level 1 is -0.1726 × 10000 = -1726, meaning that 1726 typhoon events of sea area level 1 and landfall level 1 need to be reduced from the first random event set.

[0116] Step S206: Based on the increase or decrease in the number of typhoon events under different sea area levels and landfall levels in the first random event set and the alternative random event set, process the typhoon events in the first random event set to obtain the target random event set.

[0117] Specifically, in step S206, based on the increase or decrease in the number of typhoon events under different sea area levels and landfall levels in the first random event set and the candidate random event set, the typhoon events in the first random event set are processed, including:

[0118] Step S206-1: Determine the increase or decrease in the number of typhoon events under each sea area level and landfall level.

[0119] In step S205 above, the number of typhoon events corresponding to different sea area levels and landfall levels is determined. Before processing the first random dataset, it is necessary to first determine the number of typhoon events corresponding to each sea area level and landfall level. Taking Table 3 above as an example, the number of typhoon events corresponding to sea area level 2 and landfall level 1 is -0.1726×10000, or -1726.

[0120] Step S206-2: If the increase or decrease in the number of typhoon events is negative, perform multiple random samplings based on the increase or decrease in the typhoon events corresponding to the sea area level and landfall level in the first random event set, and delete the typhoon events collected each time.

[0121] This can be understood as follows: when the increase or decrease in the number of typhoon events corresponding to a certain sea area level and landfall level is negative, it indicates that the number of typhoon events at that level has decreased compared to future climate scenarios. Therefore, it is necessary to reduce the number of typhoon events corresponding to that level in the first random event set. Thus, multiple random samplings need to be performed on the typhoon events of the sea area level and landfall level corresponding to the increase or decrease in the first random event set, and the sampled typhoon events need to be deleted. Taking sea area level 2 and landfall level 1 as an example, the corresponding increase or decrease is -1726. Therefore, 1726 samples need to be performed on all typhoon events of sea area level 2 and landfall level 1 in the first random event set, and these typhoon events need to be deleted.

[0122] Step S206-3: If the increase or decrease in the number of typhoon events is positive, perform multiple random samplings based on the increase or decrease in the number of typhoon events corresponding to the sea area level and landfall level in the candidate random event set, and add the collected typhoon events to the first random event set.

[0123] Similarly, referring to the corresponding explanation in step S206-2 above, for sea area levels and landfall levels where the number of typhoon increases or decreases is positive, multiple random samplings need to be performed in the candidate random event set, and the sampled typhoon events are added to the first random event set.

[0124] Specifically, the random event set generated in step S202 above also includes the weights corresponding to each typhoon event.

[0125] This can be understood as follows: in the generated random time set, the initial weight of each typhoon event is 1. However, considering that some scholars in actual climate research have proposed that typhoon paths tend to shift northward, different weights can be assigned to typhoon events at different latitudes and longitudes based on expert experience. For example, typhoon events that make landfall in provinces further north can be assigned a higher weight, so that when sampling typhoon events later, the actual typhoon path shift can be taken into account, and appropriate additions or deletions can be made. It should be noted that whether typhoon paths have shifted northward needs to be determined by combining relevant research and specific expert experience. Some studies believe that northward shift exists, while others believe that it does not. However, under the background of future climate change, the influence of atmospheric structure, sea surface temperature, and other factors will inevitably lead to a shift in typhoon paths compared to historical data. Therefore, the weights of typhoon events at different landfall locations can be set based on actual expert experience, so that the subsequent sampling of typhoon events can be adapted to the path shift.

[0126] The weighting needs to be based on expert experience or relevant scientific basis. The weight of each typhoon can be adjusted according to the landfall location (latitude and longitude / province). This can increase the probability of subsequent sampling of typhoon events in areas of interest, thereby achieving the purpose of typhoon path shift.

[0127] For example, taking tropical cyclones of typhoon (TY) level as an example, under current climate conditions, the average annual number of tropical cyclones of typhoon (TY) level and above making landfall in Hainan is 0.47, in Guangdong it is 0.90, and in Shandong it is 0.02. If the weights are all set to 1, then theoretically, the ratio of the average annual number of landfalls in each province in the perpetual event set after adding or deleting events should remain unchanged at 0.47:0.9:0.02.

[0128] If relevant research indicates that the number of typhoons making landfall in Shandong increases by 100%, the weight of typhoon events making landfall in Shandong can be set to 2. Then, after adding or deleting events, the annual average number of landfalls in each province can be 0.47:0.9:0.04.

[0129] Specifically, in steps S206-2 and S206-3, multiple random samples are performed based on the increase or decrease in quantity, including:

[0130] For each random sample, normalization calculation is performed based on the weight of the current typhoon event under the corresponding sea area level and landfall level to obtain the normalized weight range;

[0131] By setting a random number seed and a random number generator to determine the sampling random number, and based on the sampling random number and the normalized weight range, the typhoon event corresponding to this random sampling is determined.

[0132] This can be understood as follows: when performing each random sampling, the typhoon events corresponding to the sea area level and landfall level in the current first random event set or candidate random event set can be statistically analyzed. Based on the weights of these typhoon events, they can be normalized to generate a weighted interval, with each typhoon event corresponding to a part of the interval.

[0133] Simultaneously, a random number seed and a random number generator are set to generate a sampled random number. Based on which typhoon event interval the sampled random number falls within, the typhoon event corresponding to this random sampling is determined. After each random sampling, normalization is performed again to obtain a new weight interval, and a new random sampling is performed until the sampling is completed for the number of times the corresponding typhoon event increases or decreases. By setting a random number seed and a random number generator, each set of random numbers can be reproduced.

[0134] Specifically, in step S206-3, the collected typhoon events are added to the first random event set, including:

[0135] Based on the Poisson distribution, determine the increase in each random year in the first random event set under the corresponding sea area level and landing level;

[0136] Based on the increase corresponding to each random year, typhoon events collected from the candidate random event set will be added to the corresponding random year in the first random event set.

[0137] This can be understood as follows: since the first random event set consists of typhoon events corresponding to multiple random years, after identifying the typhoon events to be added to the first random event set from the candidate random event set, it is necessary to determine which random years these typhoon events should be added to. Because in practical applications, the distribution of typhoons over historical periods follows a Poisson distribution, the Poisson distribution can be used to determine which years the specific typhoon events to be added should be placed in. Specifically, the average annual increase in the number of typhoons can be used as the Poisson distribution parameter to determine the distribution of the typhoon events to be added.

[0138] For example, the distribution of newly added typhoon events can be shown in Table 4:

[0139] Table 4

[0140]

[0141] In the table, the simulated year refers to a random year in the first set of random events, which are sorted from 1 to 10000, where N... TD N TS N H1 N H2 N H3 N H4 and N H2 This refers to typhoon events of different landfall levels within the first random event set, denoted by POISSON(λ). H1 For example, the corresponding column is N. H1 The specific distribution of typhoon events for each random year in the first random event set needs to be added to the level, where λ H1 This refers to the Poisson distribution parameter, specifically the average annual increase in the number of typhoons under the corresponding typhoon category. For the typhoon events corresponding to sea area category 18 and landfall category 18 in Table 3 above, the Poisson distribution parameter is 0.0004 when determining their corresponding Poisson distribution.

[0142] N TD N TS N H1 N H2 N H3 N H4 and N H5These refer to tropical depressions, tropical storms, Category 1 hurricanes, Category 2 hurricanes, Category 3 hurricanes, Category 4 hurricanes, and Category 5 hurricanes, respectively. This classification standard is based on literature research using the Saffir-Simpson scale. These typhoon level classifications can be understood as typhoon level classifications under broad categories. In the embodiments of this invention, the typhoon level classification standard in the above-mentioned related exemplary examples is based on the above-mentioned intensity level division, and a more detailed level division is made at the wind speed level, corresponding to levels 1-18 respectively.

[0143] This step determines the number of years required to add each subsequent typhoon. For example, adding 10 typhoons per year under a certain category is unreasonable, as it's unreasonable for all 10 typhoons to occur in the same year. It's necessary to determine the actual distribution of their annual probability of occurrence; the parameter of the distribution function is the average number of typhoons added per year. For instance, after sampling, a list of typhoons to be added and removed from the sample can be generated, with output attributes including: event ID, year, day, and hour.

[0144] Step S207: Compare the target random event set with the first random event set, and calculate the rate of change of typhoon events corresponding to each landfall level;

[0145] Based on the preset change parameters and the rate of change of typhoon events corresponding to each landfall level, determine whether the target random event set is qualified.

[0146] This can be understood as comparing the number of typhoon events at various landfall levels in the target random event set and the first random event set, and comparing the rate of change between the two event sets. The rate of change is then compared with the preset parameter range corresponding to each landfall level. If the rate of change is within the preset range, it is considered qualified.

[0147] For example, refer to Figure 3 The figure shown is an example of comparing the number of event sets under different typhoon intensities across the country according to an embodiment of the present invention. Figure 3 The system displays the number of typhoon events at different landfall levels in the first random event set and the target random event set, as well as the rate of change between them. For different landfall levels, a corresponding rate of change range can be set based on expert experience. By judging the relationship between the rate of change corresponding to each landfall level and the preset rate of change range, it is determined whether the processed target random event set is qualified.

[0148] Specifically, one can also statistically analyze the annual average number of landfalling typhoons exceeding a certain landfall level for each province in the first random event set and the target random event set, obtaining the rate of change for each province between the annual average number of landfalling typhoons in the target random event set and the first random event set. For example, [examples would be inserted here]. Figure 4The figure shown is an example of comparing the average annual number of typhoon events of a preset typhoon level or above in different provinces according to an embodiment of the present invention. Figure 4 The system displays the annual average number of typhoons of TY level or above in each province in the first and second random event sets. The rate of change between the two sets is compared with the corresponding rate of change range for each province to determine whether the target random event set is qualified.

[0149] The typhoon event set generation method based on climate change provided in this invention generates a first random event set and a candidate random event set using a historical tropical cyclone path dataset. Based on the sea area and landfall level corresponding to the landfall typhoons in the first random event set, a landfall typhoon proportion table is generated. This table, combined with a table showing the annual average number of typhoons in the sea area under a preset climate scenario, determines the increase or decrease in the number of typhoon events at different levels within the first random event set. This process is then used to process the typhoon events in the first random event set to obtain a target random event set. The final typhoon event set can account for changes in the number of typhoons under future scenarios, resulting in better testing performance when conducting typhoon risk stress tests based on this typhoon event set.

[0150] The existing typhoon event set reflects the typhoon activity characteristics under the current climate scenario. Based on the research on the intensity / frequency of typhoon disasters in different regions under future climate change scenarios, the climate change-based typhoon event set generation method corresponding to the embodiment of this invention is used to perform secondary sampling, which can effectively increase tail risk. By adjusting the statistical characteristics of the event set, a scientific and relatively economical way can be achieved to use a catastrophe model to quantify climate change risk.

[0151] By combining the typhoon event set provided in this invention with a catastrophic model to quantify climate change risks, internal climate change risk management capabilities can be strengthened, integrating climate change into a comprehensive risk management system. Climate change risk appetite and assessment should be established in accordance with regulatory requirements. Improving the internal climate change governance mechanism and ensuring adequate disclosure and reporting are crucial, with the core being the quantification of climate change risks to support decision-making. Systematic design of climate change insurance products can also be undertaken, considering separating climate change products from general catastrophic products to meet regulatory and investment requirements. Developing climate change + credit insurance products can support banking institutions in mitigating risks by developing climate change index-based products, green building insurance, and mitigating agricultural climate change risks. When the time is right, coverage can be expanded to include sea-level rise, extreme cold, and drought.

[0152] Simultaneously, climate change factors can be incorporated into the investment decision-making system. This involves considering the climate change risks (regulatory requirements) of invested products, establishing a climate change and even ESG scoring system, considering transformation risks, and integrating them into strategic asset allocation decisions. For bond assets, the degree of climate risk exposure will affect bond ratings. For equity assets, climate change impacts future corporate earnings, existing asset value, and investment-related risks. All of these factors can affect corporate valuations. Climate risk will affect the valuation of equity assets and the cost of equity capital, leading to significant stock price fluctuations and increased costs of equity capital. Other real estate projects need to consider location, building characteristics, and historical climate conditions to avoid extreme risks.

[0153] This embodiment also provides a typhoon event set generation device based on climate change, which is used to implement the above embodiments and preferred embodiments, and will not be repeated as already described. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0154] This embodiment provides a typhoon event set generation device based on climate change, such as... Figure 5 As shown, it includes:

[0155] The historical data acquisition module 401 is used to acquire the historical tropical cyclone path dataset corresponding to the current climate scenario.

[0156] The random event generation module 402 is used to generate a first random event set and a candidate random event set based on a historical tropical cyclone path dataset and a preset typhoon event generation model.

[0157] The typhoon determination module 403 is used to determine the typhoon events that make landfall in the first random event set and the corresponding sea area level and landfall level for each typhoon event, and to generate a first typhoon proportion table based on the number of typhoon events under different sea area levels and landfall levels.

[0158] The quantity change acquisition module 404 is used to acquire the table of the annual average number of typhoons in the sea area for future periods under a preset climate scenario.

[0159] The module 405 for determining the increase or decrease in the number of typhoon events is used to determine the increase or decrease in the number of typhoon events under different sea area levels and landfall levels in the first random event set, based on the first landfall typhoon proportion table and the annual average number of typhoons in the sea area change table.

[0160] The random event set processing module 406 is used to process typhoon events in the first random event set based on the increase or decrease in the number of typhoon events under different sea area levels and landfall levels and the alternative random event sets, so as to obtain the target random event set.

[0161] In some optional implementations, the random event set includes: typhoon events corresponding to multiple random years; the increase / decrease quantity determination module 405, when determining the increase / decrease quantity of typhoon events under different sea area levels and landfall levels in the first random event set based on the first landfall typhoon proportion table and the annual average number of typhoons in the sea area table, includes:

[0162] Based on the table of the proportion of first landfall typhoons and the table of the annual average number of typhoons in different sea areas, the annual average number of typhoon events was determined for different sea area levels and landfall levels.

[0163] The increase or decrease in the number of typhoon events under different sea area levels and landfall levels is determined based on the annual average number of typhoon events and the number of random years corresponding to the first random event set.

[0164] In some optional implementations, the random event set processing module 406, when processing typhoon events in the first random event set based on the increase or decrease in the number of typhoon events under different sea area levels and landfall levels and alternative random event sets, includes:

[0165] Determine the increase or decrease in the number of typhoon events under each sea area level and landfall level;

[0166] If the increase or decrease in the number of typhoon events is negative, multiple random samples will be taken from the typhoon events of the corresponding sea area level and landfall level in the first random event set, and each collected typhoon event will be deleted.

[0167] If the increase or decrease in the number of typhoon events is positive, multiple random samples are taken from the typhoon events of the corresponding sea area level and landfall level in the candidate random event set according to the increase or decrease, and the collected typhoon events are added to the first random event set.

[0168] In some optional implementations, the set of random events may further include: weights corresponding to each typhoon event;

[0169] The random event set processing module 406, when performing multiple random samplings based on the increase or decrease in quantity, includes:

[0170] For each random sample, normalization calculation is performed based on the weight of the current typhoon event under the corresponding sea area level and landfall level to obtain the normalized weight range;

[0171] By setting a random number seed and a random number generator to determine the sampling random number, and based on the sampling random number and the normalized weight range, the typhoon event corresponding to this random sampling is determined.

[0172] In some optional implementations, the random event set processing module 406, when adding the collected typhoon events to the first random event set, includes:

[0173] Based on the Poisson distribution, determine the increase in each random year in the first random event set under the corresponding sea area level and landing level;

[0174] Based on the increase corresponding to each random year, typhoon events collected from the candidate random event set will be added to the corresponding random year in the first random event set.

[0175] In some optional implementations, after obtaining the target random event set, the random event set processing module 406 is further used to compare the target random event set with the first random event set and to count the rate of change of typhoon events corresponding to each landfall level.

[0176] Based on the preset change parameters and the rate of change of typhoon events corresponding to each landfall level, determine whether the target random event set is qualified.

[0177] In some optional implementations, the table of annual average number of typhoons in the sea area includes: the annual average number of typhoon events under each sea area level;

[0178] The module 405 for determining the increase or decrease in the number of typhoons, when determining the annual average number of typhoon events under different sea area and landfall levels based on the table of proportions of the first landfall typhoon and the table of annual average number of typhoons in different sea areas, includes:

[0179] Determine the proportion of typhoon events of different landfall levels under each sea area level in the first landfall typhoon proportion table;

[0180] Based on the proportion of typhoon events of different landfall levels under each sea area level and the annual average number of events corresponding to each sea area level, the annual average number of events of different landfall levels under each sea area level is determined.

[0181] Further functional descriptions of the above modules and units are the same as those in the corresponding embodiments described above, and will not be repeated here.

[0182] In this embodiment, the typhoon event set generation device based on climate change is presented in the form of functional units. Here, a unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0183] This invention also provides a computer device having the above-described features. Figure 5 The device shown is a climate change-based typhoon event set generation device.

[0184] Please see Figure 6 , Figure 6 This is a schematic diagram of the structure of a computer device provided in an optional embodiment of the present invention, such as... Figure 6 As shown, the computer device includes one or more processors 10, memory 20, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components communicate with each other via different buses and can be mounted on a common motherboard or otherwise installed as needed. The processors can process instructions executed within the computer device, including instructions stored in or on memory to display graphical information of a GUI on external input / output devices (such as display devices coupled to the interfaces). In some alternative implementations, multiple processors and / or multiple buses can be used with multiple memories and multiple memory modules, if desired. Similarly, multiple computer devices can be connected, each providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multiprocessor system). Figure 6 Take a processor 10 as an example.

[0185] Processor 10 may be a central processing unit, a network processor, or a combination thereof. Processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The programmable logic device may be a complex programmable logic device (CAMP), a field-programmable gate array (FPGA), a general-purpose array logic (GDA), or any combination thereof.

[0186] The memory 20 stores instructions executable by at least one processor 10 to cause at least one processor 10 to perform the method shown in the above embodiments.

[0187] The memory 20 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the computer device. Furthermore, the memory 20 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, the memory 20 may optionally include memory remotely located relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0188] The memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk or solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0189] The computer device also includes an input device 30 and an output device 40. The processor 10, memory 20, input device 30, and output device 40 can be connected via a bus or other means. Figure 6 Taking the example of a connection between China and Israel via a bus.

[0190] Input device 30 can receive input numerical or character information, and generate key signal inputs related to user settings and function control of the computer device, such as a touchscreen, keypad, mouse, trackpad, touchpad, joystick, one or more mouse buttons, trackball, joystick, etc. Output device 40 may include display devices, auxiliary lighting devices (e.g., LEDs), and haptic feedback devices (e.g., vibration motors). The aforementioned display devices include, but are not limited to, liquid crystal displays, light-emitting diodes, displays, and plasma displays. In some alternative embodiments, the display device may be a touchscreen.

[0191] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code, which, when accessed and executed by the computer, processor, or hardware, implements the methods shown in the above embodiments.

[0192] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for generating typhoon event sets based on climate change, characterized in that, The method includes: Obtain a dataset of historical tropical cyclone tracks corresponding to the current climate scenario; Based on the historical tropical cyclone path dataset, a first random event set and a candidate random event set are generated using a preset typhoon event generation model. Determine the landfall typhoon events in the first random event set and the corresponding sea area level and landfall level for each landfall typhoon event. Based on the number of typhoon events under different sea area levels and landfall levels, generate a table of proportions of the first landfall typhoons. Obtain a table showing the annual average number of typhoons in the sea area under a preset climate scenario for future periods; Based on the first landfall typhoon proportion table and the annual average number of typhoons in the sea area table, the increase or decrease in the number of typhoon events under different sea area levels and landfall levels in the first random event set is determined. Based on the increase or decrease in the number of typhoon events under different sea area levels and landfall levels in the first random event set and the candidate random event set, the typhoon events in the first random event set are processed to obtain the target random event set.

2. The method of claim 1, wherein, The random event set includes the first random event set and the alternative random event set, and the random event set further includes: typhoon events corresponding to multiple random years; The determination of the increase or decrease in the number of typhoon events under different sea area levels and landfall levels in the first random event set, based on the first landfall typhoon proportion table and the annual average number of typhoons in the sea area table, includes: Based on the first landfall typhoon proportion table and the annual average number of typhoons in the sea area table, the annual average number of typhoon events under different sea area levels and landfall levels is determined. The increase or decrease in the number of typhoon events under different sea area levels and landfall levels is determined based on the average annual number of typhoon events under different sea area levels and landfall levels and the number of random years corresponding to the first random event set.

3. The method of claim 1, wherein, The process of processing typhoon events in the first random event set based on the increase or decrease in the number of typhoon events under different sea area and landfall levels in the first random event set and the candidate random event set includes: Determine the increase or decrease in the number of typhoon events under each sea area level and landfall level; If the increase or decrease in the number of typhoon events is negative, multiple random samples are taken from the typhoon events of the corresponding sea area level and landfall level in the first random event set according to the increase or decrease, and each collected typhoon event is deleted. If the increase or decrease in the number of typhoon events is positive, multiple random samples are taken from the typhoon events of the corresponding sea area level and landfall level in the candidate random event set according to the increase or decrease, and the collected typhoon events are added to the first random event set.

4. The method of claim 3, wherein, The random event set includes the first random event set and the alternative random event set, and the random event set further includes: the weights corresponding to each typhoon event; The step of performing multiple random samplings based on the increase or decrease in quantity includes: For each random sample, normalization calculation is performed based on the weight of the current typhoon event under the corresponding sea area level and landfall level to obtain the normalized weight range; By setting a random number seed and a random number generator to determine the sampling random number, and based on the sampling random number and the normalized weight interval, the typhoon event corresponding to this random sampling is determined.

5. The method of claim 3, wherein, The first set of random events includes: typhoon events corresponding to multiple random years; Adding the collected typhoon events to the first random event set includes: Based on the Poisson distribution, determine the increase in each random year in the first random event set under the corresponding sea area level and landing level; Based on the increase corresponding to each random year, typhoon events collected from the candidate random event set will be added to the corresponding random year in the first random event set.

6. The method of claim 1, wherein, After obtaining the target set of random events, the method further includes: The target random event set is compared with the first random event set, and the change rate of typhoon events corresponding to each landfall level is statistically analyzed. Based on the preset change parameters and the change rate of typhoon events corresponding to each landfall level, determine whether the target random event set is qualified.

7. The method of claim 2, wherein, The table of annual average number of typhoons in the sea area includes: the annual average number of typhoon events under each sea area level; The determination of the annual average number of typhoon events under different sea area and landfall levels, based on the first landfall typhoon proportion table and the annual average number of typhoons in the sea area table, includes: Determine the proportion of typhoon events of different landfall levels under each sea area level in the first typhoon landfall proportion table; Based on the proportion of typhoon events of different landfall levels under each sea area level and the annual average number of such events corresponding to each sea area level, the annual average number of such events of different landfall levels under each sea area level is determined.

8. A device for generating a set of typhoon events based on climate change, characterized by, The device includes: The historical data acquisition module is used to acquire a dataset of historical tropical cyclone paths corresponding to the current climate scenario; The random event generation module is used to generate a first random event set and a candidate random event set based on the historical tropical cyclone path dataset and a preset typhoon event generation model. The typhoon landfall determination module is used to determine the landfall typhoon events in the first random event set and the corresponding sea area level and landfall level for each landfall typhoon event, and to generate the first landfall typhoon proportion table based on the number of typhoon events under different sea area levels and landfall levels. The quantity change acquisition module is used to obtain a table of the annual average number of typhoons in the sea area for future periods under a preset climate scenario; The increase / decrease quantity determination module is used to determine the increase / decrease quantity of typhoon events under different sea area levels and landfall levels in the first random event set based on the first landfall typhoon ratio table and the annual average number of typhoons in the sea area table. The random event set processing module is used to process the typhoon events in the first random event set based on the increase or decrease in the number of typhoon events under different sea area levels and landfall levels in the first random event set and the candidate random event set, so as to obtain the target random event set.

9. A computer device, comprising: include: A memory and a processor are communicatively connected, the memory stores computer instructions, and the processor executes the computer instructions to perform the climate change-based typhoon event set generation method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing a computer to execute the climate change-based typhoon event set generation method according to any one of claims 1 to 7.

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