CN107330583B - Full-path typhoon risk analysis method based on statistical dynamics - Google Patents

Full-path typhoon risk analysis method based on statistical dynamics Download PDF

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CN107330583B
CN107330583B CN201710433578.XA CN201710433578A CN107330583B CN 107330583 B CN107330583 B CN 107330583B CN 201710433578 A CN201710433578 A CN 201710433578A CN 107330583 B CN107330583 B CN 107330583B
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段忠东
陈煜�
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Shenzhen Graduate School Harbin Institute of Technology
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Abstract

The invention provides a full-path typhoon risk analysis method based on statistical dynamics. Firstly, generating annual occurrence number and occurrence position of typhoon by using a generating model, respectively estimating the annual occurrence number of typhoon and the probability density of the generation position of typhoon on the sea by using a one-dimensional nuclear probability density function and a three-dimensional nuclear probability density function, and simulating the annual occurrence number and the generation position of typhoon by using a Monte Carlo method; and secondly, substituting the annual occurrence number and the occurrence position of the simulated typhoon into a mobile model based on statistical dynamics to simulate the position of every 6 hours after the generation of the typhoon, and estimating the intensity of every 6 hours of the typhoon by using an intensity model. The invention has the beneficial effects that: the typhoon generation position simulated by the generation model based on the kernel density probability function is not limited to the historical generation position, and the defect that the samples of the typhoon generation points are too few because the historical generation points are directly used by the empirical full-path model is overcome.

Description

Full-path typhoon risk analysis method based on statistical dynamics
Technical Field
The invention relates to a full-path typhoon risk analysis method, in particular to a full-path typhoon risk analysis method based on statistical dynamics.
Background
The existing typhoon risk analysis model mainly comprises a single-point probability model and an empirical full-path model.
1. The single-point probability model is used for defining a circular area for a research point to determine typhoon samples influencing the research point, determining annual occurrence number parameters of typhoons in the area through Poisson distribution, carrying out probability statistics on characteristics such as the moving speed, the moving direction, the central air pressure difference, the maximum wind speed radius, the minimum distance between a typhoon center and the research point and the like of the typhoon samples in the area, simulating a large number of typhoon samples by utilizing a Monte Carlo method, and combining with the typhoon field model to estimate the typhoon wind speeds of 50-year-first and 100-year-first at the research point.
2. The method comprises the steps of using the whole northwest Pacific ocean historical typhoon as a sample, determining annual generation number parameters of the northwest Pacific ocean typhoon through Poisson distribution, directly using historical generation points as initial points of simulation, conducting regression statistics on the moving speed, moving direction and intensity of the whole path of the typhoon, synthesizing a large number of complete paths of the typhoon by using a Monte Carlo method, screening typhoon samples in a certain range of a research point, and combining with a typhoon wind field model to estimate the typhoon wind speeds of the research point in 50 years and 100 years.
The prior art has the problems and defects that:
1. the single-point probability model is only suitable for typhoon risk analysis of small areas with abundant typhoon samples, and for typhoon risk analysis of large-scale areas (such as a plurality of cities, railways, highways, power grid systems and the like on the coast), the calculation is complex due to the fact that the areas need to be subjected to sectional statistics, and large deviation exists when the single-point probability model is used for researching areas with insufficient typhoon samples. The model cannot be applied to researching typhoon risk analysis under future climate change.
2. The initial generation point of the empirical full-road model simulation is limited, only historical typhoon path information is considered, the model is good in performance in areas with rich typhoon samples, but is inferior in performance in areas with rare historical typhoon records, and cannot be applied to research of typhoon risk analysis under future climate change.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides a full-path typhoon risk analysis method based on statistical dynamics,
first, the annual occurrence number and the occurrence position of typhoon are generated using a generative model. The annual occurrence probability density of the typhoon is estimated by utilizing a one-dimensional kernel probability density function, as shown in formula (1),
Figure BDA0001318029090000021
wherein x represents the annual number of typhoons; x is the number ofiRepresenting the number of typhoons in each year in history; n represents the total years of the historical typhoon records; h represents the optimal bandwidth, and is estimated by adopting a one-dimensional biased cross validation method, wherein the h with the minimum expression (2) is the optimal bandwidth as shown in the expression (2).
Figure BDA0001318029090000022
In the formula,. DELTA.ij＝(xi-xj)/h，xiAnd xjIndicating the number of typhoons in different years in history. The annual number of typhoons is simulated by a Monte Carlo method. The probability density of the position of the typhoon generated on the ocean is estimated by utilizing the three-dimensional nuclear probability density function, as shown in the formula (3),
Figure BDA0001318029090000031
in the formula, x represents a typhoon-generated position vector; x is the number ofiRepresenting the occurrence position vector of each historical typhoon; s represents a standard deviation matrix of the position vector; n represents the historical typhoon occurrence number; sigmaxx、σyy、σzzRespectively representing the variance of each of the three dimensions; w is aiRepresenting the correction weight of each kernel density estimator; gamma ray1、γ2、γ3Respectively representing feature vectors of correlation coefficients among the three dimensions after standardization; lambda [ alpha ]1、λ2、λ3Respectively representing the characteristic values; h isopt1、hopt2、hopt3Respectively, the optimal bandwidth of the three variables. Estimating by adopting a three-dimensional biased cross validation method, as shown in formula (4), so that the minimum of formula (4) is the optimal bandwidth,
Figure BDA0001318029090000032
in the formula,. DELTA.ijk＝(xik-xjk)/hk，xikAnd xjkAnd a k-dimension variable, k being 1, 2, 3, indicating a history generation position. And simulating the generation position of the typhoon by a Monte Carlo method.
Then, the number of annual typhoon occurrences and the occurrence position of the typhoon are substituted into the position of every 6 hours after the generation of the typhoon is simulated in the moving model, the moving speed of the typhoon is shown as (5),
Figure BDA0001318029090000033
in the formula, U and V respectively represent latitudinal and longitudinal moving speeds of typhoon; u shapesteerAnd VsteerRespectively representing the latitudinal and longitudinal guide airflow speeds of the typhoon; u shape300，U400The equal values respectively represent the circumferential average values of the latitudinal speeds of the environmental wind fields of the atmospheric pressure layers of 300 hectopascal, 400 hectopascal and the like on the radius of 5 degrees of the center of the typhoon; v300，V400The mean values of the radial velocities of the environmental wind field of the atmospheric pressure layer such as 300 hectopascal and 400 hectopascal on the radius of 5 degrees of the center of the typhoon are respectively represented; b isxAnd ByRespectively the latitudinal direction drift velocity and the longitudinal direction drift velocity, substituting the moving velocity of the historical typhoon into the equation (5) to calculate the beta drift velocity of the historical typhoon, and taking the historical beta drift average value in the grid where the simulated typhoon is located as the beta drift velocity of the simulated typhoon. And (4) the typhoon moves for 6 hours along the maximum arc of the earth at the simulated moving speed to obtain the position of the typhoon after 6 hours, and the simulation is repeated until the typhoon disappears, so that the simulation of the whole path of the typhoon is completed.
As a further improvement of the invention, the typhoon path is simulated, simultaneously, the intensity of the typhoon every 6 hours is simulated by using the intensity model, when the typhoon is positioned on the sea, the intensity of the second position and the intensity of the third position and the positions after the second position of the typhoon are respectively estimated by adopting the formula (6) and the formula (7),
Figure BDA0001318029090000041
Figure BDA0001318029090000042
in the formula, VmaxIndicating the intensity of the typhoon; a is0，b0Etc. representing intensity regression parameters of each ocean grid; i represents this time; i +1 represents the time after 6 hours; i-1 represents the time 6 hours ago; i represents relative intensity; PI represents the potential intensity of the typhoon; SST denotes the ocean surface temperature at the center of the typhoon. When in typhoonAfter landing, the intensity attenuation of the typhoon on the land is estimated by adopting the formula (8),
Vmax＝Vb+(Vmax0-Vb)exp(-αT) (8)
in the formula, Vmax0The intensity of the moment before the typhoon lands is represented; vbRepresenting the background wind speed of the land grid, α representing a land intensity decay parameter, and T representing a decay time, when the simulated intensity of the typhoon is less than 10.8 m/s, the typhoon is considered to die, and the simulation of the path and the intensity of the typhoon is terminated.
And after synthesizing a large number of typhoon full paths, screening out simulated typhoons entering the typhoon risk analysis position within a range of five hundred kilometers, and interpolating the path position and intensity of the simulated typhoons every 6 hours into the position and intensity of the simulated typhoons every 1 minute. By utilizing the Georgiou gradient wind field, the gradient wind speed generated by each simulated typhoon to the analysis position is calculated, as shown in the formula (9),
Figure BDA0001318029090000051
wherein the content of the first and second substances,
Figure BDA0001318029090000052
Figure BDA0001318029090000053
when typhoon is on the sea
Figure BDA0001318029090000054
When typhoon is on land
Rmax＝exp(c0+c1lnVmax+c2lon+c3lat)
Wherein α represents the clockwise angle between the moving direction of the typhoon and the analysis position, r represents the distance from the center of the typhoon to the analysis position, and VTRepresenting the moving speed of the typhoon; f denotes the Coriolis parameters of the analysis position; b represents a typhoon air pressure distribution parameter; Δ p represents a typhoon center air pressure difference; ρ represents air densityDegree; rmaxRepresenting a typhoon maximum wind speed radius; lon represents the latitude of the analysis location; lat represents the longitude of the analysis location; c. C0，c1Etc. the maximum wind speed radius regression parameters representing the analysis location. Finally, the estimated gradient wind speed is reduced to the wind speed at the height of 10 meters from the ground surface, namely the reduction coefficient is 0.58 when the analysis position is within 50 kilometers of the coast, and the reduction coefficient is 0.53 when the analysis position is outside 50 kilometers of the coast.
And screening out annual maximum wind speed generated by the simulated typhoon to the analysis position and sequencing the annual maximum wind speed from small to large, wherein the 98 th percentile is the wind speed which is encountered in 50 years, and the 99 th percentile is the wind speed which is encountered in 100 years, so that the typhoon risk analysis of the analysis position is completed.
The invention has the beneficial effects that: 1. the typhoon generation position simulated by the generation model based on the kernel density probability function is not limited to the historical generation position, and the defect that the samples of the typhoon generation points are too few because the historical generation points are directly used by the empirical full-path model is overcome;
2. the method distributes the estimated generation probability of the land typhoon back to an estimator of a kernel probability density function, corrects the generation probability of the typhoon at the ocean position, and overcomes the defect that the generation probability of the ocean position near the land is estimated by the traditional model and is lower;
3. the method utilizes the statistical relationship among the movement, the intensity and the environment variables of the historical typhoon to simulate the typhoon path and the intensity of the scarce area of the historical typhoon record, and overcomes the defect that the empirical full-path model cannot simulate the scarce area of the historical typhoon record;
4. the method can simulate a large number of complete typhoon paths, typhoon risk analysis can be carried out on a large range and a plurality of regions by utilizing the complete typhoon paths, and the defect that a single-point model cannot be suitable for typhoon risk analysis of the large range region is overcome.
Drawings
Fig. 1 is a simulation of the tropical cyclone generation locations of 70 years (open circles) and the historical tropical cyclone generation locations of 1945-.
Fig. 2 is a grid distribution diagram of fig. 1.
Fig. 3 is a diagram of a 66-year typhoon path from a stochastic simulation.
Detailed Description
The invention is further described with reference to the following description and embodiments in conjunction with the accompanying drawings.
A full-path typhoon risk analysis method based on statistical dynamics can be subdivided into: and generating a model, a moving model, a strength model and a wind field model.
The annual number of occurrences and the location of occurrence of the typhoon are first generated using a generative model. And (3) estimating the annual occurrence probability density of the typhoon by using a one-dimensional kernel probability density function, wherein the formula is shown as the formula (1).
Figure BDA0001318029090000071
Wherein x represents the annual number of typhoons; x is the number ofiRepresenting the number of typhoons in each year in history; n represents the total years of the historical typhoon records; h denotes the optimum bandwidth. And (3) estimating by adopting a one-dimensional biased cross validation method, wherein the minimum h of the formula (2) is the optimal bandwidth as shown in the formula (2).
Figure BDA0001318029090000072
In the formula,. DELTA.ij＝(xi-xj)/h，xiAnd xjIndicating the number of typhoons in different years in history. The annual number of typhoons is simulated by a Monte Carlo method. And (3) estimating the probability density of the position (longitude, latitude and time) of the typhoon on the ocean by using the three-dimensional kernel probability density function, wherein the probability density is shown as the formula (3).
Figure BDA0001318029090000073
Where x represents a typhoon-generated-position (longitude, latitude, time) vector; x is the number ofiRepresenting the occurrence position vector of each historical typhoon; s represents a standard deviation matrix of the position vector; n represents the historical typhoon occurrence number;σxx，σyy，σzzrespectively representing the variance of each of the three dimensions; w is aiRepresenting the correction weight of each kernel density estimator; gamma ray1，γ2，γ3Respectively representing feature vectors of correlation coefficients among the three dimensions after standardization; lambda [ alpha ]1，λ2，λ3Respectively representing the characteristic values; h isopt1，hopt2，hopt3Respectively, the optimal bandwidth of the three variables. And (4) estimating by adopting a three-dimensional biased cross validation method, wherein the minimum of the formula (4) is the optimal bandwidth as shown in the formula (4).
Figure BDA0001318029090000081
In the formula,. DELTA.ijk＝(xik-xjk)/hk，xikAnd xjkAnd a k-dimension variable, k being 1, 2, 3, indicating a history generation position. And simulating the generation position of the typhoon by a Monte Carlo method. Figure 1 is a comparison of the 70 year tropical cyclone generation location simulated by the present method and the historical generation location of 1945-.
Next, the number of annual typhoon occurrences and the occurrence position of the typhoon are substituted into the movement model to simulate the position every 6 hours after the generation of the typhoon, and the movement speed of the typhoon is shown in (5).
Figure BDA0001318029090000082
In the formula, U and V respectively represent latitudinal and longitudinal moving speeds of typhoon; u shapesteerAnd VsteerRespectively representing the latitudinal and longitudinal guide airflow speeds of the typhoon; u shape300，U400The equal values respectively represent the circumferential average values of the latitudinal speeds of the environmental wind fields of the atmospheric pressure layers of 300 hectopascal, 400 hectopascal and the like on the radius of 5 degrees of the center of the typhoon; v300，V400The mean values of the radial velocities of the environmental wind field of the atmospheric pressure layer such as 300 hectopascal and 400 hectopascal on the radius of 5 degrees of the center of the typhoon are respectively represented; b isxAnd BySubstituting the moving speed of the historical typhoon into the latitudinal and longitudinal beta drift speeds respectivelyAnd (5) reversely calculating the beta drift speed of the historical typhoon, and taking the historical beta drift average value in the grid of the graph 2 where the simulated typhoon is located as the beta drift speed of the simulated typhoon. And (4) the typhoon moves for 6 hours along the maximum arc of the earth at the simulated moving speed to obtain the position of the typhoon after 6 hours, and the simulation is repeated until the typhoon disappears, so that the simulation of the whole path of the typhoon is completed.
The intensity of the typhoon every 6 hours (defined here as the maximum wind speed at a height of 10 meters near the center of the typhoon) was simulated using an intensity model while simulating the path of the typhoon. When the typhoon is located on the sea, the intensity of the second position and the intensity of the third position and the positions behind the second position of the typhoon are respectively estimated by adopting an equation (6) and an equation (7).
Figure BDA0001318029090000091
Figure BDA0001318029090000092
In the formula, VmaxIndicating the intensity of the typhoon; a is0，b0The intensity regression parameters of the ocean grids in FIG. 2 are represented by the same numbers; i represents this time; i +1 represents the time after 6 hours; i-1 represents the time 6 hours ago; i represents relative intensity; PI represents the potential intensity of the typhoon; SST denotes the ocean surface temperature at the center of the typhoon. When a typhoon lands, the intensity attenuation of the typhoon on land is estimated by equation (8).
Vmax＝Vb+(Vmax0-Vb)exp(-αT) (8)
In the formula, Vmax0The intensity of the moment before the typhoon lands is represented; vbRepresenting the background wind speed of each land grid in fig. 2, α representing a land intensity decay parameter, T representing a decay time, when the simulated intensity of the typhoon is less than 10.8 m/s, the typhoon is considered to die, and the simulation of the typhoon path and intensity is terminated, fig. 3 is a randomly simulated 66-year typhoon path.
And after a large number of typhoon full paths are synthesized, screening out the simulated typhoon which enters the typhoon risk analysis position within a range of five hundred kilometers. The path position and intensity every 6 hours for the simulated typhoon are interpolated to a position and intensity every 1 minute. And (4) calculating the gradient wind speed of each simulated typhoon to the analysis position by utilizing the Georgiou gradient wind field, wherein the formula is shown as (9).
Figure BDA0001318029090000093
Wherein the content of the first and second substances,
Figure BDA0001318029090000101
Figure BDA0001318029090000102
when typhoon is on the sea
Figure BDA0001318029090000103
When typhoon is on land
Rmax＝exp(c0+c1lnVmax+c2lon+c3lat)
Wherein α represents the clockwise angle between the moving direction of the typhoon and the analysis position, r represents the distance from the center of the typhoon to the analysis position, and VTRepresenting the moving speed of the typhoon; f denotes the Coriolis parameters of the analysis position; b represents a typhoon air pressure distribution parameter; Δ p represents a typhoon center air pressure difference; ρ represents an air density; rmaxRepresenting a typhoon maximum wind speed radius; lon represents the latitude of the analysis location; lat represents the longitude of the analysis location; c. C0，c1Etc. the maximum wind speed radius regression parameters representing the analysis location. Finally, the estimated gradient wind speed is reduced to the wind speed at the height of 10 meters from the ground surface, namely the reduction coefficient is 0.58 when the analysis position is within 50 kilometers of the coast, and the reduction coefficient is 0.53 when the analysis position is outside 50 kilometers of the coast. Screening out annual maximum wind speed generated by the simulated typhoon to the analysis position and sequencing the annual maximum wind speed from small to large, wherein the 98 th percentile is the wind speed which is encountered in 50 years, and the 99 th percentile is the wind speed which is encountered in 100 years, thereby completing the pairingAnd analyzing the typhoon danger of the position. The statistical dynamics-based full-path typhoon risk analysis method provided by the invention has the following advantages:
1. the typhoon generation position simulated by the generation model based on the kernel density probability function is not limited to the historical generation position, and the defect that the samples of the typhoon generation points are too few because the historical generation points are directly used by the empirical full-path model is overcome.
2. The method distributes the estimated generation probability of the land typhoon back to the estimator of the kernel probability density function, corrects the generation probability of the typhoon at the ocean position, and overcomes the defect that the generation probability of the ocean position near the land is estimated by the traditional model and is lower.
3. The method can simulate the typhoon path and the typhoon intensity of the scarce area of the historical typhoon record by utilizing the statistical relationship among the historical typhoon movement, the intensity and the environment variable, and overcomes the defect that the historical typhoon record scarce area can not be simulated by an empirical full-path model.
4. The method can simulate a large number of complete typhoon paths, typhoon risk analysis can be carried out on a large range and a plurality of regions by utilizing the complete typhoon paths, and the defect that a single-point model cannot be suitable for typhoon risk analysis of the large range region is overcome.
The invention provides a full-path typhoon risk analysis method based on statistical dynamics. 1, the method is applied to typhoon simulation and disaster risk analysis, and has wide application prospects in the aspects of giant disaster insurance and reinsurance, and design and development of giant disaster securities; 2, the method is applied to determining the typhoon level of engineering fortification and has application prospect on disaster defense of design and operation of important engineering; 3, the method is applied to wind-resistant disaster prevention and emergency plan planning of cities, and has application prospect on disaster management and emergency response decisions of government management departments.
The foregoing is a more detailed description of the invention in connection with specific preferred embodiments and it is not intended that the invention be limited to these specific details. For those skilled in the art to which the invention pertains, several simple deductions or substitutions can be made without departing from the spirit of the invention, and all shall be considered as belonging to the protection scope of the invention.

Claims (2)

1. A full-path typhoon risk analysis method based on statistical dynamics is characterized in that:
firstly, generating annual occurrence number and occurrence position of typhoon by using a generating model, estimating annual occurrence number probability density of typhoon by using a one-dimensional kernel probability density function, as shown in formula (1),
Figure FDA0002426666050000011
in the formula (1), x represents the annual number of typhoon; x is the number ofiRepresenting the number of typhoons in each year in history; n represents the total years of the historical typhoon records; h represents the optimal bandwidth, and is estimated by adopting a one-dimensional biased cross validation method, wherein the minimum h of the formula (2) is the optimal bandwidth as shown in the formula (2);
Figure FDA0002426666050000012
in the formula,. DELTA.ij＝(xi-xj)/h，xiAnd xjRepresenting the number of typhoons in different years in history, and simulating the annual occurrence number of the typhoons by a Monte Carlo method; the probability density of the position of the typhoon generated on the ocean is estimated by utilizing the three-dimensional nuclear probability density function, as shown in the formula (3),
Figure FDA0002426666050000013
in the formula (3), x represents a typhoon-generated position vector; x is the number ofiRepresenting the occurrence position vector of each historical typhoon; s represents a standard deviation matrix of the position vector; n represents the historical typhoon occurrence number; sigmaxx、σyy、σzzRespectively representing the variance of each of the three dimensions; w is aiRepresenting the correction weight of each kernel density estimator; gamma ray1、γ2、γ3Respectively of correlation coefficients between three dimensions after normalizationA feature vector; lambda [ alpha ]1、λ2、λ3Respectively representing the characteristic values; h isopt1、hopt2、hopt3Respectively estimating the optimal bandwidths of the three variables by adopting a three-dimensional biased cross validation method, wherein the optimal bandwidth is obtained by minimizing the formula (4) as shown in the formula (4);
Figure FDA0002426666050000021
in the formula,. DELTA.ijk＝(xik-xjk)/hk，xikAnd xjkA k-dimensional variable indicating a history generation position, k being 1, 2, 3; simulating the generation position of the typhoon by a Monte Carlo method;
then substituting the annual occurrence number and occurrence position of the simulated typhoon into the position of every 6 hours after the generation of the simulated typhoon in the moving model, wherein the moving speed of the typhoon is shown as (5);
Figure FDA0002426666050000022
in the formula (5), U and V respectively represent the latitudinal and longitudinal moving speeds of the typhoon; u shapesteerAnd VsteerRespectively representing the latitudinal and longitudinal guide airflow speeds of the typhoon; u shape300，U400The equal values respectively represent the circumferential average values of the latitudinal speeds of the environmental wind fields of the atmospheric pressure layers of 300 hectopascal, 400 hectopascal and the like on the radius of 5 degrees of the center of the typhoon; v300，V400The mean values of the radial velocities of the environmental wind field of the atmospheric pressure layer such as 300 hectopascal and 400 hectopascal on the radius of 5 degrees of the center of the typhoon are respectively represented; b isxAnd BySubstituting the moving speed of the historical typhoon into the equation (5) to obtain the beta drifting speed of the historical typhoon, and taking the historical beta drifting average value in the grid where the simulated typhoon is located as the beta drifting speed of the simulated typhoon; the typhoon moves for 6 hours along the maximum arc of the earth at the simulated moving speed to obtain the position of the typhoon after 6 hours, and the simulation is repeated until the typhoon disappears to finish the simulation of the whole path of the typhoon。
2. The statistical dynamics-based full-path typhoon risk analysis method according to claim 1, characterized in that: simulating the strength of the typhoon every 6 hours by using a strength model while simulating the path of the typhoon, respectively estimating the strength of a second position and the strength of a third position and the subsequent positions of the typhoon by adopting an equation (6) and an equation (7) when the typhoon is positioned on the ocean,
Figure FDA0002426666050000031
Figure FDA0002426666050000032
in formulae (6) and (7), VmaxIndicating the intensity of the typhoon; a is0，b0Etc. representing intensity regression parameters of each ocean grid; i represents this time; i +1 represents the time after 6 hours; i-1 represents the time 6 hours ago; i represents relative intensity; PI represents the potential intensity of the typhoon; SST represents the ocean surface temperature at the center of the typhoon; when the typhoon lands, the intensity attenuation of the typhoon on the land is estimated by adopting the formula (8),
Vmax＝Vb+(Vmax0-Vb)exp(-αT) (8)
in the formula (8), Vmax0The intensity of the moment before the typhoon lands is represented; vbRepresenting the background wind speed of the land grid, α representing land intensity attenuation parameters, T representing attenuation time, when the simulation intensity of the typhoon is less than 10.8 m/s, considering the typhoon to die, and terminating the simulation of the path and intensity of the typhoon;
after a large number of typhoon full paths are synthesized, the simulated typhoons entering the typhoon risk analysis position within a range of five hundred kilometers are screened out, and the path position and the path intensity of the simulated typhoons in every 6 hours are interpolated into the position and the intensity of the simulated typhoons in every 1 minute; by utilizing the Georgiou gradient wind field, the gradient wind speed generated by each simulated typhoon to the analysis position is calculated, as shown in the formula (9),
Figure FDA0002426666050000033
wherein the content of the first and second substances,
Figure FDA0002426666050000041
Figure FDA0002426666050000042
when typhoon is on the sea
Figure FDA0002426666050000043
When typhoon is on land
Rmax＝exp(c0+c1ln Vmax+c2lon+c3lat)
In the formula (9), α represents the clockwise angle between the moving direction of the typhoon and the analysis position, r represents the distance from the center of the typhoon to the analysis position, and VTRepresenting the moving speed of the typhoon; f denotes the Coriolis parameters of the analysis position; b represents a typhoon air pressure distribution parameter; Δ p represents a typhoon center air pressure difference; ρ represents an air density; rmaxRepresenting a typhoon maximum wind speed radius; lon represents the latitude of the analysis location; lat represents the longitude of the analysis location; c. C0，c1The maximum wind speed radius regression parameter representing the analysis position is equal; finally, the estimated gradient wind speed is reduced to the wind speed at the height of 10 meters from the ground surface, namely the reduction coefficient is 0.58 when the analysis position is within 50 kilometers of the coast, and the reduction coefficient is 0.53 when the analysis position is outside 50 kilometers of the coast; and screening out annual maximum wind speed generated by the simulated typhoon to the analysis position and sequencing the annual maximum wind speed from small to large, wherein the 98 th percentile is the wind speed which is encountered in 50 years, and the 99 th percentile is the wind speed which is encountered in 100 years, so that the typhoon risk analysis of the analysis position is completed.
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