Method and system for forecasting, diagnosing and evaluating tropical cyclone precipitation

Abstract

The invention provides a tropical cyclone precipitation forecast diagnosis evaluation method and system, and the method comprises the steps: sequentially eliminating the position, magnitude and structural errors of a forecast precipitation field step by step, and calculating the improvement amount of an evaluation index after each correction, errors specifically include path-related spatial deviation, mode systematicness deviation, magnitude deviation related to tropical cyclone strength, radial distribution deviation related to a mode precipitation radial structure and azimuth angle deviation related to precipitation asymmetry of tropical cyclone precipitation forecast. According to the method, the tropical cyclone rainfall forecast error is decomposed into errors associated with the tropical cyclone path, the rainfall level, the rainfall radial distribution and the rainfall asymmetric structure forecast, so that the source of the tropical cyclone rainfall forecast error is better explained; the error contribution after each step of correction can well reflect the contribution degree of the error source related to the attribute of the tropical cyclone or the environmental field to the total precipitation error, and correction reference is provided for real-time tropical cyclone precipitation forecast.

Description

Technical Field

[0001] This invention relates to the field of meteorological research technology, and in particular to a method and system for forecasting, diagnosing and evaluating tropical cyclone precipitation. Background Technology

[0002] Quantitative precipitation forecasting for tropical cyclones is crucial for ensuring the safety of life and property and for the effective use of water resources. Currently, quantitative precipitation forecasting for tropical cyclones mainly relies on numerical models. Objectively assessing the forecasting capabilities of these models and clearly diagnosing the sources of error in model forecasts are of great significance for the use and improvement of model forecasts.

[0003] For the verification of quantitative precipitation forecasts for tropical cyclones, operational methods generally use point-to-point ThreatScore (TS) scoring, or object-based CRA (Contiguous Rain Area) or MODE (Mode-based Object Diagnostic Assessment) methods. However, these methods, in their initial design, do not consider the correlation between tropical cyclone precipitation distribution and attributes such as the location and intensity of the tropical cyclone, resulting in unclear physical meaning and certain limitations.

[0004] Therefore, it is necessary to design a tropical cyclone precipitation forecast diagnosis and assessment method that can decompose and diagnose tropical cyclone precipitation forecast errors, link precipitation forecast errors with forecast errors of the tropical cyclone's own attributes, and thus better explain the sources of precipitation forecast errors. Summary of the Invention

[0005] To address the problems existing in the prior art, this invention provides a method and system for the diagnostic assessment of tropical cyclone precipitation forecasts. This method can calculate the contributions of tropical cyclone track forecast errors, systematic biases in model precipitation intensity, radial precipitation structure errors, and asymmetric precipitation structure errors to the total precipitation forecast error. This method provides richer diagnostic information for tropical cyclone precipitation forecast assessment, which is helpful for forecasters interpreting forecasts and for model developers improving their models.

[0006] This invention provides a method for the diagnosis and assessment of tropical cyclone precipitation forecasts, comprising:

[0007] Based on the observed tropical cyclone path with radius R, the observed precipitation fields were analyzed respectively. Precipitation field predicted by numerical model After cropping, the observed precipitation field is obtained. and forecast precipitation field ;

[0008] Based on the offset between the tropical cyclone center predicted by the numerical model and the observed tropical cyclone center, the predicted precipitation field is analyzed. The forecast precipitation field is shifted, and precipitation is extracted from the shifted forecast precipitation field with the observed tropical cyclone center as the center and R as the radius, to obtain the path bias-removed forecast precipitation correction field. ;

[0009] Adjusting the Precipitation Forecast Field Based on Quantile Mapping Method The rainfall magnitude caused the forecast precipitation correction field Adjusted precipitation magnitude distribution and observed precipitation field The precipitation magnitude distribution is consistent, resulting in a revised precipitation field after removing model magnitude biases. ;

[0010] Observed precipitation field in polar coordinate system and Forecasted Precipitation Correction Field Radial precipitation profiles are obtained by azimuth averaging. The ratio of the two radial precipitation profiles is used to correct the forecast precipitation field. Adjustments were made to obtain the revised precipitation forecast field. Interpolate it back to the original latitude and longitude grid coordinates to obtain the radially distributed adjusted forecast correction field. ;

[0011] Calculate the observed precipitation field in polar coordinates respectively and Forecasted Precipitation Correction Field The azimuth 1-wave asymmetric component, and the offset angle between the azimuth angles where the maximum values ​​of the azimuth 1-wave asymmetric components of the two components are located in each radial direction, are used to correct the forecast precipitation field. Rotate to obtain the forecast precipitation correction field. Interpolate it back to the original latitude and longitude grid coordinates to obtain the forecast precipitation correction field with azimuth asymmetric structure adjustment. ;

[0012] Calculate and predict precipitation fields And the revised precipitation forecast field after each revision , , and The evaluation indicators are used to determine the contribution of factors associated with each correction to the precipitation forecast error based on the changes in the evaluation indicators after each correction.

[0013] According to the present invention, a method for diagnostic evaluation of tropical cyclone precipitation forecasts is provided, which corrects the forecast precipitation field based on the ratio of the radial precipitation distribution profiles of two objects. Adjustments were made to obtain the revised precipitation forecast field. ,include:

[0014] Calculate the observed precipitation field in polar coordinates Radial precipitation distribution profile and forecast precipitation correction field The ratio between radial precipitation profiles;

[0015] Correction field for predicted precipitation in polar coordinates Multiplying by the ratio yields the forecast precipitation correction field. .

[0016] According to the present invention, a method for the diagnostic evaluation of tropical cyclone precipitation forecasting is provided, which is based on the observed precipitation field in polar coordinate system. and Forecasted Precipitation Correction Field Before obtaining the radial precipitation distribution profile by azimuth averaging, the following steps are also included:

[0017] Observing precipitation fields and Forecasted Precipitation Correction Field Interpolate to a polar coordinate system with the observed tropical cyclone center as the origin and R as the radius, where R is 500 km or is set according to the observed precipitation distribution range.

[0018] According to the tropical cyclone precipitation forecast diagnosis and evaluation method provided by the present invention, the radial resolution of the polar coordinate system is the same as the precipitation field grid at the origin, and gradually becomes thicker radially outward.

[0019] According to the present invention, a method for diagnostic evaluation of tropical cyclone precipitation forecasting is provided, which calculates the forecast precipitation field. And the revised precipitation forecast field after each revision , , and The evaluation indicators are used to determine the contribution of factors associated with each correction to the precipitation forecast error, based on the changes in the evaluation indicators after each correction. These factors include:

[0020] Calculate and predict precipitation fields With the observed precipitation field The evaluation metric between them is the SSIM score. ;

[0021] Calculation of Precipitation Correction Field With the observed precipitation field The evaluation metric between them is the SSIM score. ;

[0022] Calculation of Precipitation Correction Field With the observed precipitation field The evaluation metric between them is the SSIM score. ;

[0023] Calculate the precipitation forecast correction field With the observed precipitation field The evaluation metric between them is the SSIM score. ;

[0024] Calculate the precipitation forecast correction field With the observed precipitation field The evaluation metric between them is the SSIM score. ;

[0025] Will As a total error, and The proportion of the difference between the two values ​​in the total error is taken as the contribution value corresponding to the i-th correction, i=1, 2, 3 and 4.

[0026] The method for forecasting, diagnosing, and evaluating tropical cyclone precipitation according to the present invention further includes:

[0027] calculate and The proportion of the difference between the two errors in the total error is taken as the cumulative contribution value corresponding to the first i corrections.

[0028] The method for forecasting, diagnosing, and evaluating tropical cyclone precipitation according to the present invention further includes:

[0029] Subtract 1 The difference is treated as an unexplained residual.

[0030] This invention also provides a tropical cyclone precipitation forecasting and diagnostic assessment system, comprising:

[0031] The initial scoring module is used to score the observed precipitation field based on the observed tropical cyclone path with a radius of R. Precipitation field predicted by numerical model After cropping, the observed precipitation field is obtained. and forecast precipitation field ;

[0032] The first correction module is used to adjust the forecast precipitation field based on the offset between the tropical cyclone center predicted by the numerical model and the observed tropical cyclone center. The forecast precipitation field is shifted, and precipitation is extracted from the shifted forecast precipitation field with the observed tropical cyclone center as the center and R as the radius, to obtain the path bias-removed forecast precipitation correction field. ;

[0033] The second correction module is used to adjust the forecast precipitation correction field based on the quantile mapping method. The rainfall magnitude caused the forecast precipitation correction field Adjusted precipitation magnitude distribution and observed precipitation field The precipitation magnitude distribution is consistent, resulting in a revised precipitation field after removing model magnitude biases. ;

[0034] The third correction module is used to correct the observed precipitation field in polar coordinates. and Forecasted Precipitation Correction Field Radial precipitation profiles are obtained by azimuth averaging. The ratio of the two radial precipitation profiles is used to correct the forecast precipitation field. Adjustments were made to obtain the revised precipitation forecast field. Interpolate it back to the original latitude and longitude grid coordinates to obtain the radially distributed adjusted forecast correction field. ;

[0035] The fourth correction module is used to calculate the observed precipitation field in polar coordinates. and Forecasted Precipitation Correction Field The azimuth 1-wave asymmetric component, and the offset angle between the azimuth angles where the maximum values ​​of the azimuth 1-wave asymmetric components of the two components are located in each radial direction, are used to correct the forecast precipitation field. Rotate to obtain the forecast precipitation correction field. Interpolate it back to the original latitude and longitude grid coordinates to obtain the forecast precipitation correction field with azimuth asymmetric structure adjustment. ;

[0036] The evaluation module is used to calculate the forecast precipitation field. And the revised precipitation forecast field after each revision , , and The evaluation indicators are used to determine the contribution of factors associated with each correction to the precipitation forecast error based on the changes in the evaluation indicators after each correction.

[0037] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the tropical cyclone precipitation forecasting, diagnosis and evaluation method as described above.

[0038] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the tropical cyclone precipitation forecasting, diagnosis and evaluation method as described above.

[0039] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the tropical cyclone precipitation forecasting, diagnosis and evaluation method as described above.

[0040] The tropical cyclone precipitation forecast diagnosis and evaluation method and system provided by this invention decomposes tropical cyclone precipitation forecast errors into errors associated with the forecasts of tropical cyclone tracks, precipitation magnitudes, radial distribution of precipitation, and asymmetric structure of precipitation. This better explains the sources of tropical cyclone precipitation forecast errors and has a clearer physical meaning compared to previous methods. Practical implementation shows that the precipitation field corrected step-by-step by this invention has a high degree of similarity to the observed field. The error contribution calculated after each correction step can well reflect the contribution of error sources related to the tropical cyclone's own properties or environmental fields to the total precipitation error, providing a correction reference for real-time tropical cyclone precipitation forecasts. Attached Figure Description

[0041] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0042] Figure 1 This is a flowchart illustrating the tropical cyclone precipitation forecasting, diagnosis, and assessment method provided by the present invention.

[0043] Figure 2 This is a complete flowchart of the tropical cyclone precipitation forecasting, diagnosis, and evaluation method provided by the present invention;

[0044] Figure 3 This is a schematic diagram of the observation and forecast precipitation fields in each step of the tropical cyclone precipitation forecasting, diagnosis, and evaluation method provided by this invention, where part a is the original observed precipitation field. Part b is the original forecast precipitation field. Part c is the forecast precipitation field before cropping after eliminating path errors, and part d is the cropped observed precipitation field. Part e is the cropped forecast precipitation field. Part f is the forecast precipitation correction field after eliminating path errors. Part g is the precipitation correction field after eliminating the bias in precipitation magnitude. The h-part represents the precipitation correction field after eliminating radial distribution errors. Part i is the precipitation correction field after eliminating precipitation azimuth error. The plus sign indicates the location of the center of a tropical cyclone;

[0045] Figure 4 The observation precipitation field in the tropical cyclone precipitation forecasting, diagnosis, and evaluation method provided by this invention. and Forecasted Precipitation Correction Field A schematic diagram of the established quantile mapping model, applied to precipitation forecasting. The revised curve, with the solid line at the midpoint representing the revised forecast precipitation. With forecast precipitation The mapping relationship is shown, with the solid line representing the standard unbiased line;

[0046] Figure 5 The radial distribution profile of observed and predicted axisymmetric precipitation obtained from the tropical cyclone precipitation forecasting diagnosis and evaluation method provided by this invention. (Solid line) and (Dashed line), and the ratio of the radial distribution profile of the azimuth average of the observed and predicted fields. (Dotted-line) diagram;

[0047] Figure 6 This is a schematic diagram of correcting asymmetric precipitation errors in polar coordinates in the tropical cyclone precipitation forecasting diagnosis and evaluation method provided by this invention, where part a is the asymmetric component field of the observed azimuth angle 1-wave. Part b is the predicted azimuth angle 1-wave asymmetric component field. Part c is the forecast azimuth 1-wave asymmetric component field after correcting for asymmetric precipitation errors, and part d is the observed precipitation field. Part e is the forecast precipitation correction field. Part f is the precipitation forecast field that corrects for asymmetric precipitation errors. ;

[0048] Figure 7 This is a schematic diagram of the structure of the tropical cyclone precipitation forecasting, diagnosis and evaluation system provided by the present invention. Detailed Implementation

[0049] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0050] The following is combined Figure 1 and Figure 2 This invention describes a method for the diagnostic assessment of tropical cyclone precipitation forecasting, comprising:

[0051] Step 101: Based on the observed tropical cyclone path with radius R, analyze the observed precipitation field... Precipitation field predicted by numerical model After cropping, the observed precipitation field is obtained. and forecast precipitation field ;

[0052] This embodiment evaluates and diagnoses errors in tropical cyclone precipitation forecasts for a specific time period. A cumulative precipitation duration of 1 hour or 3 hours is preferred. If the user requires results for a longer time period, they can first process the 3-hour data and then overlay it onto the desired timeframe.

[0053] First, tropical cyclone data for a specific time period is acquired, including numerical model forecasts, cumulative precipitation observations, and the tropical cyclone positions at the start and end of that period. The observed cumulative precipitation data is interpolated to the same grid as the forecasts. The GFDL vortex tracking algorithm is used to obtain the model-predicted tropical cyclone paths, and the average observed and predicted tropical cyclone positions for that time period are calculated.

[0054] Observed and forecasted precipitation data were cropped separately based on the observed tropical cyclone path. The observed precipitation field... and forecast precipitation field Precipitation was extracted using the observed tropical cyclone location as the center and R as the radius, resulting in the observed precipitation field. and forecast precipitation field .

[0055] The specific method for extracting precipitation fields is as follows: if the distance between a grid point and the center of a tropical cyclone does not exceed the radius R, then the precipitation at that grid point is retained; otherwise, it is set as a missing value.

[0056] Preferably, the location of the tropical cyclone can be obtained from the best track data of tropical cyclones IBTRASC (International BestTrack Archive for Climate Stewardship), and the gridded precipitation data can be obtained from the Global Precipitation Measurement (GPM) program, with R being 500 km or set according to the observed precipitation distribution range.

[0057] Step 102: Based on the offset between the tropical cyclone center predicted by the numerical model and the observed tropical cyclone center, adjust the predicted precipitation field. The forecast precipitation field is shifted, and precipitation is extracted from the shifted forecast precipitation field with the observed tropical cyclone center as the center and R as the radius, to obtain the path bias-removed forecast precipitation correction field. ;

[0058] The specific method for shifting the forecast precipitation field is as follows: calculate the offset of the forecast tropical cyclone center relative to the observed tropical cyclone center, spatially shift the latitude and longitude of the forecast precipitation field grid according to the offset, and interpolate the shifted precipitation field to the original grid to ensure the consistency of the verification grid.

[0059] Step 103: Adjust the forecast precipitation correction field based on the quantile mapping method The rainfall magnitude caused the forecast precipitation correction field Adjusted precipitation magnitude distribution and observed precipitation field The precipitation magnitude distribution is consistent, resulting in a revised precipitation field after removing model magnitude biases. ;

[0060] Based on the quantile mapping method, the precipitation correction field is... The precipitation magnitude was adjusted to match the observed magnitude distribution to obtain the precipitation correction field after removing model magnitude bias. The quantile mapping method was used to eliminate the magnitude bias of tropical cyclone precipitation and the improvement of the assessment index after magnitude bias correction was calculated.

[0061] Step 104, observe the precipitation field in polar coordinates. and Forecasted Precipitation Correction Field Radial precipitation profiles are obtained by azimuth averaging. The ratio of the two radial precipitation profiles is used to correct the forecast precipitation field. Adjustments were made to obtain the revised precipitation forecast field. Interpolate it back to the original latitude and longitude grid coordinates to obtain the radially distributed adjusted forecast correction field. ;

[0062] The forecast will be corrected. and observation field A polar coordinate system is established with the observed tropical cyclone center as the origin. The radial resolution of this polar coordinate system is set to be the same as the grid spacing of the forecast field at the origin, and gradually transitions to a coarse resolution along the radial direction outwards, thus obtaining the forecast correction field in the polar coordinate system. and observation field Preferably, the polar coordinate azimuth resolution is set to 2.5 degrees.

[0063] Step 105: Calculate the observed precipitation field in polar coordinates. and Forecasted Precipitation Correction Field The azimuth 1-wave asymmetric component, and the offset angle between the azimuth angles where the maximum values ​​of the azimuth 1-wave asymmetric components of the two components are located in each radial direction, are used to correct the forecast precipitation field. Rotate to obtain the forecast precipitation correction field. Interpolate it back to the original latitude and longitude grid coordinates to obtain the forecast precipitation correction field with azimuth asymmetric structure adjustment. ;

[0064] The observed precipitation field in polar coordinates was transformed using Fourier transform. And the revised forecast Transforming to the frequency space, retaining the 1-wave component, and then transforming back to the time domain through an inverse transform, we obtain the azimuth 1-wave asymmetric component field of the observed and predicted fields in polar coordinates. and .

[0065] Find the azimuth position of the maximum value of the asymmetric component of wave 1 in each radial direction. and Calculate the error between the azimuth angle of the observed maximum value and the azimuth angle of the predicted maximum value for each radial direction. .

[0066] Prediction field According to azimuth error Rotating along each radial direction yields the precipitation forecast field corrected for azimuth distribution. By interpolating the coordinates back to the original latitude and longitude grid, a precipitation field corrected for the asymmetric distribution error of precipitation was obtained. .

[0067] Step 106, Calculate the predicted precipitation field And the revised precipitation forecast field after each revision , , and The evaluation indicators are used to determine the contribution of factors associated with each correction to the precipitation forecast error based on the changes in the evaluation indicators after each correction.

[0068] This embodiment eliminates location, magnitude, and structural errors step by step and calculates the improvement of evaluation indicators. Specifically, it includes spatial deviations related to the path of tropical cyclone precipitation forecasts, systematic deviations related to the model, magnitude deviations related to the intensity of tropical cyclones, radial distribution deviations related to the radial structure of model precipitation, and azimuth deviations related to precipitation asymmetry.

[0069] This embodiment eliminates the location, magnitude, and structure errors of the forecast precipitation field step by step, and calculates the improvement of the evaluation index before and after each correction. This yields the contributions of tropical cyclone track forecast error, systematic bias of model precipitation intensity, radial precipitation structure forecast error, and asymmetric precipitation structure forecast error to the total precipitation forecast error. Compared with commonly used CRA or MODE verification methods, this approach is more targeted and interpretable in the verification and evaluation of tropical cyclone precipitation forecasts, with clearer physical meaning. It is helpful for forecasters to interpret forecasts and for model developers to improve models, and can provide strong support for real-time error analysis and correction of tropical cyclone precipitation forecasts.

[0070] Based on the above embodiments, this embodiment corrects the forecast precipitation field according to the ratio of the radial precipitation distribution profiles of the two. Adjustments were made to obtain the revised precipitation forecast field. ,include:

[0071] Calculate the observed precipitation field Radial precipitation distribution profile and forecast precipitation correction field The ratio between radial precipitation profiles;

[0072] Correction field for predicted precipitation in polar coordinates Multiplying by the ratio yields the forecast precipitation correction field. .

[0073] Observation field in polar coordinate system And the revised forecast The azimuth-averaged precipitation was calculated separately to obtain the radial distribution profiles of the observed and forecasted axisymmetric precipitation. and Calculate the ratio of the radial distribution profile of the observed and predicted azimuth averages. .

[0074] Multiplying the forecast correction field in polar coordinates by the distribution profile ratio yields the forecast correction field that corrects the azimuth-mean radial precipitation distribution deviation. The forecast will be revised. Interpolate back to the original latitude and longitude grid coordinates to obtain the forecast correction field. .

[0075] Based on the above embodiments, this embodiment focuses on the observed precipitation field in polar coordinates. and Forecasted Precipitation Correction Field Before obtaining the radial precipitation distribution profile by azimuth averaging, the following steps are also included:

[0076] Observing precipitation fields and Forecasted Precipitation Correction Field Interpolate to a polar coordinate system with the observed tropical cyclone center as the origin and R as the radius.

[0077] Based on the above embodiments, the radial resolution of the polar coordinate system in this embodiment is the same as the grid spacing at the origin and at the precipitation field, and gradually becomes thicker radially outward.

[0078] When constructing the polar coordinates of precipitation, a gradually coarsening radial resolution setting is adopted to make the construction of wave 1 asymmetric components and azimuth rotation process more robust.

[0079] Based on the above embodiments, this embodiment calculates the forecast precipitation field. And the evaluation indices of the revised precipitation forecast field after each revision. Based on the changes in the evaluation indices after each revision, the contribution values ​​of the factors associated with each revision to the precipitation forecast error are obtained, including:

[0080] Calculate and predict precipitation fields With the observed precipitation field The evaluation metric between them is the SSIM score. ;

[0081] Calculate the precipitation forecast correction field With the observed precipitation field The evaluation metric between them is the SSIM score. ;

[0082] Calculate the precipitation forecast correction field With the observed precipitation field The evaluation metric between them is the SSIM score. ;

[0083] Calculate the precipitation forecast correction field With the observed precipitation field The evaluation metric between them is the SSIM score. ;

[0084] Calculate the precipitation forecast correction field With the observed precipitation field The evaluation metric between them is the SSIM score. ;

[0085] Will and The difference between them is taken as the total explained error. and The proportion of the difference between the two values ​​in the total explained error is taken as the contribution value corresponding to the i-th correction, i=1, 2, 3 and 4.

[0086] Log-numerical model precipitation forecast field and each step of the correction process , , and In sequence with the observation field Calculate the evaluation metric SSIM. , where i takes the values ​​i = 1, 2, 3 and 4.

[0087] calculate This is considered as the overall error.

[0088] The contribution of the SSIM score improvement from the previous correction to the overall error in each step is calculated and used as the contribution of the forecast bias or error expressed by that correction step to the precipitation forecast error. , where i takes the values ​​i = 1, 2, 3 and 4.

[0089] Based on the above embodiments, this embodiment also includes:

[0090] calculate and The proportion of the difference between the two errors in the total error is taken as the cumulative contribution value corresponding to the first i corrections.

[0091] Calculate the cumulative contribution of each correction step relative to the numerical model precipitation forecast: , where i takes the values ​​i = 1, 2, 3 and 4.

[0092] Based on the above embodiments, this embodiment also includes:

[0093] Subtract 1 The difference is treated as an unexplained residual.

[0094] Calculate unexplained residuals .

[0095] For example, consider the 3-hour cumulative precipitation of a super typhoon from 05:00 to 08:00 (UTC) on July 28, 2023. Numerical model forecast data can be obtained from a weather forecasting center, and tropical cyclone location data can be obtained from the optimal tropical cyclone track data IBTRASC, with a time resolution of 3 hours. Tropical cyclone cumulative precipitation data can be obtained from the Global Precipitation Measurement (GPM) project, with a time resolution of 30 minutes. After downloading, the precipitation for the corresponding time period is summed to obtain the 3-hour cumulative precipitation.

[0096] Using data from numerical models of 500 hPa geopotential height, 700 hPa and 850 hPa wind fields, sea level pressure and 10 m wind field, the GFDL vortex tracking algorithm was used to calculate the forecast location and intensity of the tropical cyclone center at 05:00 and 08:00 on the 28th, as shown in Table 1.

[0097] Table 1

[0098]

[0099] The average position of the observed tropical cyclone at 05:00 and 08:00 is used as the center of the observed cumulative precipitation for that period, and the average position of the predicted tropical cyclone at 05:00 and 08:00 is used as the center of the predicted cumulative precipitation for that period. The observed cumulative precipitation is interpolated to the forecast grid using nearest neighbor interpolation for evaluation, such as... Figure 3 As shown in part a of the diagram.

[0100] Calculate the error of the predicted tropical cyclone center relative to the observation center, and divide the predicted precipitation grid field ( Figure 3 The latitude and longitude of part b) are subtracted from the error to obtain the shifted latitude and longitude, which are then interpolated back to the original grid latitude and longitude to complete the spatial translation of the forecast precipitation field. This corrects the precipitation forecast error caused by the tropical cyclone track error. The result is as follows: Figure 3 As shown in part c.

[0101] The observed, forecast, and track error-corrected forecast fields are interpolated into a polar coordinate system centered on the observed tropical cyclone with a radius of 5 latitudes (the radial resolution of the polar coordinate system is set to the model grid resolution at the origin, gradually becoming coarser outwards, and can be set to 4 times the origin at the edge; the azimuth resolution can be set to 2.5°).

[0102] The observed, forecast, and longitude error-corrected forecast fields in the polar coordinate system are re-interpolated back to the model's latitude and longitude grid, such as... Figure 3 The d and f parts in the data are used to obtain the observed precipitation field for verification. Precipitation forecast And the predicted precipitation correction field after path error correction The SSIM scores for the numerical model forecast and the observed field after longitude path error correction are calculated separately in the latitude and longitude grid, and denoted as follows: and See rating Figure 3 The numerical values ​​indicated in the headings of sections e and f.

[0103] The quantile mapping method was used to correct the previously revised forecast precipitation field. Towards Figure 3 Observed precipitation in part d Adjustments are made to obtain the quantile-mapped precipitation correction field for each grid cell. ,like Figure 3 The g part. The predicted precipitation field obtained by the quantile mapping method. and correcting the precipitation field The mapping relationship is as follows Figure 4 Similarly, calculate the adjusted forecast field and the observed SSIM score, denoted as... The scoring results are shown below. Figure 3 The numerical value indicated in the title of section g.

[0104] Calculate observed precipitation in polar coordinates ( Figure 3 (part d in the previous step) and the revised forecast precipitation field after the previous step. ( Figure 3 The azimuth average of the g-part in the image is used to obtain the radial distribution profile of axisymmetric precipitation in the observed and corrected field. and The ratio of the observed profile to the corrected field profile is calculated as the radial distribution correction coefficient. ,like Figure 5 .

[0105] The revised precipitation forecast field after path correction and quantile mapping ( Figure 3The g part in the equation is multiplied by the corresponding radial distribution correction factor in each radial direction. The forecast correction field was obtained, which corrected the deviation of the azimuth mean radial precipitation distribution. The forecast will be revised. Interpolating back to the original latitude and longitude grid coordinates yields the revised forecast precipitation field after adjustment for axisymmetric radial distribution. ,like Figure 3 For the h part, the adjusted forecast field and the observed SSIM score are also calculated, denoted as The scoring results are shown below. Figure 3 The value indicated in the heading of the h section.

[0106] The observed precipitation and the previously corrected forecast precipitation fields in polar coordinates are transformed to the frequency domain using a real Fourier transform. All wavenumber components except the 1-wave component are removed. Then, an inverse real Fourier transform is performed to transform them back to the time domain in polar coordinates, resulting in the 1-wave asymmetric component fields of the observed and numerical model correction fields. and ,like Figure 6 Parts a and b are shown in the figure.

[0107] Calculate the azimuth maximum index in each radial direction for the observed and numerical model correction field's one-wave asymmetric component field in polar coordinates. Subtract the azimuth maximum index of the numerical model correction field from the observed azimuth maximum index to obtain the azimuth error characterized by grid offset. .

[0108] The numerical model correction field and its one-wave component in polar coordinates are adjusted in each radial direction according to the corresponding azimuth error. Rotation yields the revised precipitation field after removing the first-wave asymmetric structure error and its first-wave component, as follows: Figure 6 The f and c parts are shown in the diagram. To verify that the center of the asymmetric component of wave 1 has been adjusted to match the observation, the SSIM scores of the adjusted forecast and observation fields are calculated and denoted as... The scoring results are shown below. Figure 3 The numerical values ​​indicated in the heading of section i. Figure 6 The d and e parts in the figure are the observation fields. And the revised forecast .

[0109] Through the above multi-step correction, the numerical model precipitation forecast bias can be significantly eliminated, and the SSIM score after each correction is obtained, including the original precipitation score SSIM0, the tropical cyclone track removal forecast error score SSIM1, the superimposed removal of the systematic bias of precipitation intensity in the model SSIM2, the superimposed removal of the axisymmetric radial precipitation structure forecast error score SSIM3, and the superimposed removal of the asymmetric precipitation structure forecast error SSIM4.

[0110] The following formula is used to characterize the overall precipitation forecast error and the relative contributions of the four types of errors and biases to the overall precipitation forecast error:

[0111] a) Overall precipitation forecast error:

[0112] b) Errors in tropical cyclone track forecasting:

[0113] c) Systematic bias in model precipitation intensity:

[0114] d) Forecast error of axisymmetric radial precipitation structure:

[0115] e) Forecast error of wave 1 asymmetric precipitation structure:

[0116] f) Error residual: .

[0117] The tropical cyclone precipitation forecasting diagnosis and evaluation system provided by the present invention is described below. The tropical cyclone precipitation forecasting diagnosis and evaluation system described below can be referred to in correspondence with the tropical cyclone precipitation forecasting diagnosis and evaluation method described above.

[0118] like Figure 7 The system includes an initial scoring module 701, a first correction module 702, a second correction module 703, a third correction module 704, a fourth correction module 705, and an evaluation module 706, wherein:

[0119] The initial scoring module 701 is used to score the observed precipitation field based on the observed tropical cyclone path with a radius of R. Precipitation field predicted by numerical model After cropping, the observed precipitation field is obtained. and forecast precipitation field ;

[0120] The first correction module 702 is used to adjust the forecast precipitation field based on the offset between the tropical cyclone center predicted by the numerical model and the observed tropical cyclone center. The forecast precipitation field is shifted, and precipitation is extracted from the shifted forecast precipitation field with the observed tropical cyclone center as the center and R as the radius, to obtain the path bias-removed forecast precipitation correction field. ;

[0121] The second correction module 703 is used to adjust the forecast precipitation correction field based on the quantile mapping method. The rainfall magnitude caused the forecast precipitation correction field Adjusted precipitation magnitude distribution and observed precipitation field The precipitation magnitude distribution is consistent, resulting in a revised precipitation field after removing model magnitude biases. ;

[0122] The third correction module 704 is used to correct the observed precipitation field in polar coordinates. and Forecasted Precipitation Correction Field Radial precipitation profiles are obtained by azimuth averaging. The ratio of the two radial precipitation profiles is used to correct the forecast precipitation field. Adjustments were made to obtain the revised precipitation forecast field. Interpolate it back to the original latitude and longitude grid coordinates to obtain the radially distributed adjusted forecast correction field. ;

[0123] The fourth correction module 705 is used to calculate the observed precipitation field in polar coordinates. and Forecasted Precipitation Correction Field The azimuth 1-wave asymmetric component, and the offset angle between the azimuth angles where the maximum values ​​of the azimuth 1-wave asymmetric components of the two components are located in each radial direction, are used to correct the forecast precipitation field. Rotate to obtain the forecast precipitation correction field. Interpolate it back to the original latitude and longitude grid coordinates to obtain the forecast precipitation correction field with azimuth asymmetric structure adjustment. ;

[0124] Evaluation module 706 is used to calculate the forecast precipitation field. And the revised precipitation forecast field after each revision , , and The evaluation indicators are used to determine the contribution of factors associated with each correction to the precipitation forecast error based on the changes in the evaluation indicators after each correction.

[0125] This embodiment eliminates the location, magnitude, and structure errors of the forecast precipitation field step by step, and calculates the improvement of the evaluation index before and after each correction. This yields the contributions of tropical cyclone track forecast error, systematic bias of model precipitation intensity, radial precipitation structure forecast error, and asymmetric precipitation structure forecast error to the total precipitation forecast error. Compared with commonly used CRA or MODE verification methods, this approach is more targeted and interpretable in the verification and evaluation of tropical cyclone precipitation forecasts, with clearer physical meaning. It is helpful for forecasters to interpret forecasts and for model developers to improve models, and can provide strong support for real-time error analysis and correction of tropical cyclone precipitation forecasts.

[0126] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for diagnostic assessment of tropical cyclone precipitation forecasting, characterized in that, include: Based on the observed tropical cyclone path with radius R, the observed precipitation fields were analyzed respectively. Precipitation field predicted by numerical model After cropping, the observed precipitation field is obtained. and forecast precipitation field ; Based on the offset between the tropical cyclone center predicted by the numerical model and the observed tropical cyclone center, the predicted precipitation field is analyzed. The forecast precipitation field is shifted, and precipitation is extracted from the shifted forecast precipitation field with the observed tropical cyclone center as the center and R as the radius, to obtain the path bias-removed forecast precipitation correction field. ; Adjusting the Precipitation Forecast Field Based on Quantile Mapping Method The rainfall level caused the forecast precipitation correction field to... Adjusted precipitation magnitude distribution and observed precipitation field The precipitation magnitude distribution is consistent, resulting in a revised precipitation field after removing model magnitude biases. ; Observed precipitation field in polar coordinate system and Forecasted Precipitation Correction Field Radial precipitation profiles are obtained by azimuth averaging. The ratio of the two radial precipitation profiles is used to correct the forecast precipitation field. Adjustments were made to obtain the revised precipitation forecast field. Interpolate it back to the original latitude and longitude grid coordinates to obtain the radially distributed adjusted forecast correction field. ; Calculate the observed precipitation field in polar coordinates respectively and Forecasted Precipitation Correction Field The azimuth 1-wave asymmetric component, and the offset angle between the azimuth angles where the maximum values ​​of the azimuth 1-wave asymmetric components of the two components are located in each radial direction, are used to correct the forecast precipitation field. Rotate to obtain the forecast precipitation correction field. Interpolate it back to the original latitude and longitude grid coordinates to obtain the forecast precipitation correction field with azimuth asymmetric structure adjustment. ; Calculate and predict precipitation fields And the revised precipitation forecast field after each revision , , and The evaluation indicators are used to determine the contribution of factors associated with each correction to the precipitation forecast error based on the changes in the evaluation indicators after each correction.

2. The method for forecasting, diagnosing, and evaluating tropical cyclone precipitation according to claim 1, characterized in that, The predicted precipitation field is corrected based on the ratio of the radial precipitation distribution profiles of the two. Adjustments were made to obtain the revised precipitation forecast field. ,include: Calculate the observed precipitation field Radial precipitation distribution profile and forecast precipitation correction field The ratio between radial precipitation profiles; Correction field for predicted precipitation in polar coordinates Multiplying by the ratio yields the forecast precipitation correction field. .

3. The method for forecasting, diagnosing, and evaluating tropical cyclone precipitation according to claim 1, characterized in that, Observation of precipitation field in polar coordinate system and Forecasted Precipitation Correction Field Before obtaining the radial precipitation distribution profile by azimuth averaging, the following steps are also included: Observing precipitation fields and Forecasted Precipitation Correction Field Interpolate to a polar coordinate system with the observed tropical cyclone center as the origin.

4. The method for forecasting, diagnosing, and evaluating tropical cyclone precipitation according to claim 1, characterized in that, The radial resolution of the polar coordinate system is the same as the precipitation field grid at the origin, and gradually becomes thicker radially outward.

5. The method for forecasting, diagnosing, and evaluating tropical cyclone precipitation according to any one of claims 1-4, characterized in that, Calculate and predict precipitation fields And the revised precipitation forecast field after each revision , , and The evaluation indicators are used to determine the contribution of factors associated with each correction to the precipitation forecast error, based on the changes in the evaluation indicators after each correction. These factors include: Calculate and predict precipitation fields With the observed precipitation field The evaluation metric between them is the SSIM score. ; Calculate the precipitation forecast correction field With the observed precipitation field The evaluation metric between them is the SSIM score. ; Calculate the precipitation forecast correction field With the observed precipitation field The evaluation metric between them is the SSIM score. ; Calculate the precipitation forecast correction field With the observed precipitation field The evaluation metric between them is the SSIM score. ; Calculate the precipitation forecast correction field With the observed precipitation field The evaluation metric between them is the SSIM score. ; Will As a total error, and The proportion of the difference between the two values ​​in the total error is taken as the contribution value corresponding to the i-th correction, i=1, 2, 3 and 4.

6. The method for forecasting, diagnosing, and evaluating tropical cyclone precipitation according to claim 5, characterized in that, Also includes: calculate and The proportion of the difference between the two errors in the total error is taken as the cumulative contribution value corresponding to the first i corrections.

7. The method for forecasting, diagnosing, and evaluating tropical cyclone precipitation according to claim 5, characterized in that, Also includes: Subtract 1 The difference is treated as an unexplained residual.

8. A tropical cyclone precipitation forecasting, diagnostic, and assessment system, characterized in that, include: The initial scoring module is used to score the observed precipitation field based on the observed tropical cyclone path with a radius of R. Precipitation field predicted by numerical model After cropping, the observed precipitation field is obtained. and forecast precipitation field ; The first correction module is used to adjust the forecast precipitation field based on the offset between the tropical cyclone center predicted by the numerical model and the observed tropical cyclone center. The forecast precipitation field is shifted, and precipitation is extracted from the shifted forecast precipitation field with the observed tropical cyclone center as the center and R as the radius, to obtain the path bias-removed forecast precipitation correction field. ; The second correction module is used to adjust the forecast precipitation correction field based on the quantile mapping method. The rainfall level caused the forecast precipitation correction field to... Adjusted precipitation magnitude distribution and observed precipitation field The precipitation magnitude distribution is consistent, resulting in a revised precipitation field after removing model magnitude biases. ; The third correction module is used to correct the observed precipitation field in polar coordinates. and Forecasted Precipitation Correction Field Radial precipitation profiles are obtained by azimuth averaging. The ratio of the two radial precipitation profiles is used to correct the forecast precipitation field. Adjustments were made to obtain the revised precipitation forecast field. Interpolate it back to the original latitude and longitude grid coordinates to obtain the radially distributed adjusted forecast correction field. ; The fourth correction module is used to calculate the observed precipitation field in polar coordinates. and Forecasted Precipitation Correction Field The azimuth 1-wave asymmetric component, and the offset angle between the azimuth angles where the maximum values ​​of the azimuth 1-wave asymmetric components of the two components are located in each radial direction, are used to correct the forecast precipitation field. Rotate to obtain the forecast precipitation correction field. Interpolate it back to the original latitude and longitude grid coordinates to obtain the forecast precipitation correction field with azimuth asymmetric structure adjustment. ; The evaluation module is used to calculate the forecast precipitation field. And the revised precipitation forecast field after each revision , , and The evaluation indicators are used to determine the contribution of factors associated with each correction to the precipitation forecast error based on the changes in the evaluation indicators after each correction.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the tropical cyclone precipitation forecasting diagnostic assessment method as described in any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the tropical cyclone precipitation forecasting diagnostic assessment method as described in any one of claims 1 to 7.

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