A method for evaluating the convective initiation products of geostationary meteorological satellites based on Doppler weather radar

Abstract

The present invention discloses a method for evaluating the convective initiation products of geostationary meteorological satellites based on Doppler weather radar, which relates to the technical field of evaluating the convective initiation products of meteorological satellites, and solves the problems that the existing methods do not consider the splitting and merging of cloud clusters, and cannot retrieve and calculate the satellite cloud drift wind in case of few clouds or no clouds, thus unable to evaluate the convective initiation products. The present invention extracts convective initiation events from three-dimensional weather radar data as the ground truth to evaluate the convective initiation products of geostationary meteorological satellites, including the following steps: taking the reflectivity value ≥ 35 dBz as the standard to identify the convective initiation events in multi-Doppler weather radar; taking the radar convective initiation as the ground truth, adopting the neighborhood method for the convective initiation region to calculate the hit rate, false alarm rate, TS test index and time lead of satellite convective initiation, and objectively evaluating the convective initiation products of geostationary satellites from the perspectives of space and time, so as to be better applied to the early warning of severe convective weather.

Description

Technical Field

[0001] The present invention relates to the technical field of evaluation of geostationary satellite convective initiation products, and specifically provides a method for evaluating geostationary satellite convective initiation products based on Doppler radar. Background Technique

[0002] Severe convective weather is a local catastrophic weather with strong suddenness and great destructive power, which is likely to cause mass casualties and is one of the most important forecasting contents in weather forecasting operations. Timely monitoring and accurate forecasting of severe convective weather can reduce the huge losses caused by it. Convective initiation is the sign of the start of severe convective weather, and accurately detecting convective initiation is the key to improving the early warning level of local severe convective weather. Due to the wide coverage and high spatio-temporal resolution of satellite data, convective initiation can be detected earlier than radar, significantly improving the early warning timeliness and helping to enhance the forecasting accuracy and timeliness of convective initiation;

[0003] At present, the inspection and evaluation of geostationary satellite convective initiation products are mainly subjective, lacking an objective and comprehensive evaluation method and unable to meet the actual application requirements;

[0004] Due to the suddenness and rapid change of convective initiation and the discontinuity of satellite data, the existing evaluation of convective initiation products mainly stays in subjective inspection, lacking a feasible, recognized and easy-to-operate objective method. Currently, for several cases, radar data is used to obtain the actual situation of convective initiation, and then the possible area where convective initiation may occur is deduced according to the direction of the cloud-derived wind retrieved by the satellite. If there is a satellite convective initiation product in this area, it is judged as correct;

[0005] This method does not consider the splitting and merging of cloud clusters, and when there is little or no cloud, the satellite cloud-derived wind cannot be retrieved and calculated, lacking data, so that the convective initiation products cannot be evaluated; therefore, it does not meet the existing requirements, and for this reason, we propose a method for evaluating geostationary satellite convective initiation products based on Doppler radar. Summary of the Invention

[0006] The purpose of the present invention is to provide a method for evaluating geostationary satellite convective initiation products based on Doppler radar to solve the problem in the above background technique that the existing method does not consider the splitting and merging of cloud clusters, and when there is little or no cloud, the satellite cloud-derived wind cannot be retrieved and calculated, lacking data, so that the convective initiation products cannot be evaluated.

[0007] To achieve the above purpose, the present invention provides the following technical solution: A method for evaluating geostationary satellite convective initiation products based on Doppler radar, including the following steps:

[0008] Step A: Identify cumulus clouds in Doppler radar data: Obtain the radar composite reflectivity data with high spatio-temporal resolution after network quality control from the weather radar mosaic system, and then identify and mark the cumulus cloud areas from the radar composite reflectivity data. The cumulus cloud areas are convective areas;

[0009] Step B: Identify radar convective initiation events using the area overlap method: The grid points corresponding to the convective areas marked in the preprocessed radar reflectivity data are formed into an eight-connected region as a research object. Based on the object-oriented idea, a convective area is used as a sample;

[0010] Step C: Preprocess satellite convective initiation products: Use Python to extract convective initiation product data, perform geometric position correction and data quality control, and finally generate binary data to construct a satellite convective initiation dataset;

[0011] Step D: Use the neighborhood method and based on the object-oriented region idea, calculate the correct forecasts, false alarms, and missed alarms of satellite convective initiation events;

[0012] Step E: Calculate the verification index and time lead of convective initiation: Based on the satellite convective initiation products and radar convective initiation events, with the radar convective initiation as the ground truth, use the neighborhood method for the convective initiation region to calculate the probability of detection (POD), false alarm rate (FAR), verification index, and time lead (TS) of satellite convective initiation. The formulas are as follows:

[0013]

[0014] Where Hit is the number of convective initiation regions correctly predicted by the satellite, False is the number of convective initiation regions falsely alarmed by the satellite, and Failure is the number of convective initiation regions missed by the satellite.

[0015] Preferably, identifying and marking the cumulus cloud areas in the radar composite reflectivity data includes the following steps:

[0016] S1: Interpolate: Use the average value method to interpolate the radar composite reflectivity data into longitude and latitude grid data with a resolution of 0.04°×0.04°;

[0017] S2: Perform 0 / 1 conversion: Take 35 dBz as the discrimination threshold for convective intensity. The area with a reflectivity value ≥ 35 dBz is the convective area, which is replaced with the value 1, and the area with a reflectivity value < 35 dBz is non-cumulus cloud, which is converted to the value 0;

[0018] S3: Perform data quality control to avoid the interference of isolated noise strong echoes. Before identifying convective initiation, filter out the cumulus cloud areas with small areas and eliminate the identified cumulus cloud areas with ≤ 3 pixels.

[0019] Preferably, identifying radar convection incipient events using the area overlap method comprises the following steps:

[0020] E1: Read the radar reflectivity data of the current time and the previous time, and use the neighborhood method to identify the convection areas of the two time periods, that is, the area with a mark value of 1, which is composed of convection grid points connected in eight directions;

[0021] E2: Use the area overlap method to track the cloud clusters, remove the convective events that are generated by the translation or development of the cloud clusters at the previous moment, and only extract the convective events generated at the current moment, which is the convective initiation, and set it as a radar convective initiation live sample;

[0022] E3: Constructing radar convection primary database:

[0023] Z_RADA_C_BABJ_YYYYMMDDHHmmss_P_DOR_ACHN_CREF_YYYYMMDD_HHmmss.da t is a dat format file for data naming, which provides a real-time data set for the subsequent evaluation of satellite convection primary products.

[0024] Preferably, the data naming format is:

[0025] YYYYMMDDhhmmss: product generation time, year, month, day, hour, minute, and second, all in universal time;

[0026] ACHN: area code, the national area is ACHN;

[0027] CREF: abbreviation of radar product type, CREF is radar combination reflectivity;

[0028] YYYYMMDD_hhmmss: data observation time, year, month, day, hour, minute, second;

[0029] dat: file extension.

[0030] Preferably, the geometric position correction comprises the following steps:

[0031] N1: According to the row and column number and longitude and latitude lookup table, if the longitude and latitude data of FY-4B is not integrated into the L1 data set, it is necessary to download the original longitude and latitude file from the website of the National Satellite Meteorological Center;

[0032] N2: For different latitude and longitude files corresponding to different resolutions, the latitude and longitude file corresponding to a resolution of 0.04°×0.04° is FY4B-_DISK_1050E_GEO_NOM_LUT_20240227000000_4000M_V0001.raw, with a grid size of 2748×2748. This file is a two-dimensional image file with geographical location coordinate information, corresponding one-to-one with the pixels of the corrected image;

[0033] N3: First, fill the data file in N2 row by row from north to south or column by column from west to east. Each data stores the corresponding latitude and longitude. Each pixel can find the corresponding latitude and longitude information according to its row number and column number in the image, realizing precise positioning.

[0034] Preferably, the data quality control specifically involves eliminating convective initiation events with ≤3 pixels.

[0035] Preferably, calculating the correct forecasts, false alarms, and missed alarms of satellite convective initiation events includes the following steps:

[0036] M1: Adopt the proximity principle to match the time resolutions of the two. Based on the satellite convective initiation product, use the convective initiation established from radar data as the ground truth, and compare it with the radar convective initiation products at each hour within the previous and subsequent 2 hours to calculate the time lead of the satellite convective initiation product;

[0037] M2: Based on the idea of targeting, regard a convective initiation area as a sample to determine correct forecasts, missed alarms, and false alarms. The false alarm results are finally generated;

[0038] M3: Determine the time lead of the satellite convective initiation: within the forecast period, the time difference between the correct forecast of the satellite convective initiation and the initial satellite convective initiation is the forecast time lead, and subsequent hours do not need to be examined.

[0039] Preferably, the method for determining correct forecasts, missed alarms, and false alarms is as follows: When the satellite convective initiation area overlaps or has less than 30 adjacent grid points with the radar convective initiation area, it is considered a correct forecast; when the satellite convective initiation area and the radar convective initiation area are not adjacent at all times, it is considered a missed alarm; when the satellite convective initiation area and all radar convective initiation areas are not adjacent at all hours within the time period, it is considered a false alarm.

[0040] Compared with the prior art, the beneficial effects of the present invention are:

[0041] The present invention first extracts convective initiation events from three-dimensional weather radar data as the actual situation, and then uses the area overlap method and the neighborhood method to objectively evaluate the convective initiation products of geostationary satellites from the perspectives of time and space by calculating indexes such as the correct rate, false alarm rate, and missed alarm rate, so as to better apply them to the early warning of severe convective weather;

[0042] Using the convective initiation of Doppler radar data with higher resolution as the actual situation, the data quality is high, the continuity is strong, and it is not affected by cloudy or cloudless weather; based on the idea of targeting the target area, the area overlap method and the neighborhood method are used to calculate the correct, false alarm, and missed alarm numbers of satellite convective initiation, and then the verification index and time lead are obtained, and a set of objective and feasible evaluation methods for satellite convective initiation products are proposed. The invention of this evaluation method provides a reference for improving the accuracy of satellite convective initiation products, has a certain supporting role, and also provides a reference for its actual severe convective weather forecasting business. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 It is a schematic flow chart of the evaluation method for the convective initiation product of the present invention;

[0044] Figure 2 It is a schematic diagram showing the parameter distribution in the verification formula of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0045] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments.

[0046] Please refer to Figure 1 and Figure 2 A kind of embodiment provided by the present invention: A method for evaluating the convective initiation products of geostationary satellites based on Doppler radar, comprising the following steps:

[0047] Step A: Identify cumulus clouds in the Doppler radar data: Obtain the radar composite reflectivity data with high spatio-temporal resolution after network quality control from the weather radar mosaic system;

[0048] The weather radar mosaic system is the new generation weather radar mosaic system V3.0, and obtain the radar composite reflectivity data with high spatio-temporal resolution after network quality control:

[0049] The format is bin format, with dimensions of 4200×6200, latitude range from 12.2 - 54.2°N, longitude range from 73 - 135°E, and spatial resolution of 1KM. The product file format is: file header + data block. In the file header, the file label (file fixed identifier, file format version code, file byte count), product description (puzzle product number, coordinate type, product code, product description, starting position of product data, product data byte count), data time (data clock, observation time year, month, day, etc.), and data area information (south, west, north, east boundaries of the data area, etc.) are defined;

[0050] Then, identify and mark the cumulus areas from the radar composite reflectivity data. The cumulus areas are convective areas. First, perform interpolation: Use the average value method to interpolate the radar composite reflectivity data into longitude and latitude grid data with a resolution of 0.04°×0.04°. Then, perform 0 / 1 conversion: Use 35dBz as the discrimination threshold for convective intensity. Areas with a reflectivity value ≥ 35dBz are convective areas and are replaced with the value 1, and areas with a reflectivity value < 35dBz are non - cumulus clouds and are converted to the value 0. Finally, perform data quality control to avoid the interference of isolated noise strong echoes. Before identifying the onset of convection, filter out the cumulus areas with a small area, and eliminate the identified cumulus areas with ≤ 3 pixels;

[0051] Step B: Use the area overlap method to identify the radar convective onset events: First, read the radar reflectivity data of the current time step and the previous time step, and use the neighborhood method to identify the convective areas of the two time steps respectively, that is, the areas marked with the value 1 and composed of convective grid points that are spatially connected in eight directions;

[0052] Then, use the area overlap method to track the cloud clusters, eliminate the convective events that are translated or developed from the cloud clusters at the previous moment, and only extract the convective events generated at the current moment, which is the onset of convection, and set it as a radar convective onset actual situation sample;

[0053] Construct a radar convective onset database:

[0054] Z_RADA_C_BABJ_YYYYMMDDHHmmss_P_DOR_ACHN_CREF_YYYYMMDD_HHmmss.dat is a dat - format file for data naming, and the data naming form is:

[0055] YYYYMMDDhhmmss: Product generation time, year, month, day, hour, minute, and second, all in Coordinated Universal Time;

[0056] ACHN: Region number, the whole country region is ACHN;

[0057] CREF: Abbreviation of radar product type, CREF is radar composite reflectivity;

[0058] YYYYMMDD_hhmmss: Observation time of data, year-month-day_hour-minute-second;

[0059] dat: File extension;

[0060] Provide a real-time data set for subsequent evaluation of satellite convective initiation products.

[0061] The grid points corresponding to the convective regions marked in the preprocessed radar reflectivity data are formed into an eight-connected region as a research object. Based on the idea of object orientation, a convective region is used as a sample;

[0062] Step C: Preprocessing of satellite convective initiation products:

[0063] Evaluate the convective initiation products of the Fengyun-4B geostationary satellite (FY-4B). The FY-4B satellite is the first weather forecasting business satellite of the Fengyun-4 series of China's new generation of geostationary meteorological satellites. It was successfully launched on April 11, 2022, and is fixed at the geostationary orbit position over the equator at 133° east longitude. It was transferred to the trial operation of weather forecasting on June 1 and began to provide observation data and application services for global users. From February 1 to March 5, 2024, it drifted from 133° east longitude to 105° east longitude, replacing the Fengyun-4A satellite to achieve the replacement of the main business position observation system. Since March 5, it has resumed business services at 105° east longitude.

[0064] The geostationary orbit radiation imager of the FY-4B satellite has added a water vapor detection channel and adjusted the spectra of some channels, improving the refined observation level. The design scheme of the geostationary orbit interferometric infrared detector has been optimized, and the spatial resolution has been further improved, and it can provide more accurate hyperspectral atmospheric radiation and temperature and humidity profile products; A new rapid imager has been added, with the ability to rapidly image with a spatial resolution of up to 250 meters in the regional range, and the monitoring of typhoons, heavy rains and mesoscale severe weather is more continuous, flexible and refined.

[0065] The time resolution of the FY-4B convective initiation product is 15 min, and the spatial resolution is 0.04°×0.04°. It is a secondary product developed using the threshold method and obtained after quality inspection, geolocation, and radiometric calibration processing. The observable longitude range of the full disk is 23.82 - 186.18, and the latitude range is -80.883S - 80.883N, and it is stored in HDF format. The convective initiation product is data in the nominal projection mode of the full disk, with a dimension of 2748×2748, and the valid data are 0 and 1, where 1 represents convective initiation.

[0066] Use python to extract the convective initiation product data, perform geometric position correction and data quality control, and finally generate binary data to construct a satellite convective initiation data set;

[0067] Geometric position correction is based on the row and column numbers and the longitude and latitude lookup table. If the longitude and latitude data of FY-4B satellite are not integrated into the L1 dataset, the original format longitude and latitude file needs to be downloaded from the website of the National Satellite Meteorological Center. For different resolutions, there are corresponding longitude and latitude files. The longitude and latitude file corresponding to the resolution of 0.04°×0.04° is FY4B-_DISK_1050E_GEO_NOM_LUT_20240227000000_4000M_V0001.raw, with a grid size of 2748×2748. This file is a two-dimensional image file with geographical position coordinate information, corresponding one-to-one with the pixels of the corrected image. Then, the data file in N2 is filled in row by row from north to south or column by column from west to east. Each data stores the corresponding latitude and longitude; each pixel finds the corresponding longitude and latitude information according to the row number and column number in the image, realizing precise positioning.

[0068] Data quality control: Eliminate the convective initiation events with ≤3 pixels.

[0069] Step D: Using the neighborhood method and based on the idea of targeting the target area, calculate the correct forecasts, false alarms, and missed alarms of satellite convective initiation events;

[0070] Due to the different temporal and spatial resolutions of satellite and radar observations, the two sets of product data have been processed into the same longitude and latitude spatial resolution of 0.04°×0.04°. The proximity principle is used to match their temporal resolutions as shown in the following table:

[0071] Observation time of FY4 satellite in China region (minutes) 00 15 30 45 Radar observation time (minutes) 00 12 30 42

[0072] Based on the satellite convective initiation product, using the convective initiation established from radar data as the ground truth, compare and verify it with the radar convective initiation products at each hour within 2 hours before and after, and calculate the time lead of the satellite convective initiation product;

[0073] Based on the idea of targeting, taking a convective initiation area as a sample, judge the correct forecasts, missed alarms, and false alarms. When the satellite convective initiation area overlaps or has less than 30 adjacent grid points with the radar convective initiation area, it is considered a correct forecast; when the satellite convective initiation area and the radar convective initiation area are not adjacent at all times, it is considered a missed alarm; when the satellite convective initiation area and all radar convective initiation areas are not adjacent at all hours within the time period, it is considered a false alarm, and the false alarm result is finally generated;

[0074] Determine the time lead of the satellite convective initiation: Within the forecast period, the time difference between the correct forecast of the satellite convective initiation and the initial satellite convective initiation is the forecast time lead, and subsequent hours do not need to be verified;

[0075] Step E: Calculate the detection index and time lead for the initial onset of convection: Based on the satellite initial onset of convection products and radar initial onset of convection events, with the radar initial onset of convection as the ground truth, the neighborhood method for the initial onset of convection region is adopted to calculate the probability of detection (POD), false alarm rate (FAR), detection index and time lead (TS) of the satellite initial onset of convection. The formulas are as follows:

[0076]

[0077] Where Hit is the number of regions of the initial onset of convection correctly predicted by the satellite, False is the number of regions of the initial onset of convection falsely reported by the satellite, and Failure is the number of regions of the initial onset of convection missed by the satellite.

[0078] For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and the present invention can be implemented in other specific forms without departing from the spirit or basic characteristics of the present invention. Therefore, in any aspect, the embodiments should be regarded as exemplary and non-limiting. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, all changes falling within the meaning and scope of the equivalent elements of the claims are intended to be embraced within the present invention. Any reference signs in the claims should not be construed as limiting the claimed invention.

Claims

1. A method for evaluating the initial convective products of geostationary satellites based on Doppler radar, characterized in that, The steps include: Step A: Identify cumulus clouds in Doppler radar data: Obtain high-temporal and spatial resolution radar composite reflectivity data after network quality control from the weather radar mosaic system, and then identify and mark cumulus cloud areas from the radar composite reflectivity data. Cumulus cloud areas are convective areas. Step B: Identify radar convection primary events using the area overlap method: The grid points corresponding to the marked convection areas in the preprocessed radar reflectivity data are used as an eight-connected area as a research object. Based on the target-oriented idea, a convection area is used as a sample; Step C: Preprocessing of satellite convective primary products: Use Python to extract convective primary product data, perform geometric position correction, data quality control, and finally generate binary data to construct a satellite convective primary data set; Step D: Using the neighborhood method, based on the idea of ​​oriented to the target area, calculate the correct forecast, false alarm, and missed alarm events of the satellite convective primary events; Step E: Calculate the verification index and time advance of convection initiation: Based on satellite convection initiation products and radar convection initiation events, take radar convection initiation as the actual situation, and use the neighborhood method facing the convection initiation area to calculate the satellite convection initiation hit rate POD, false alarm rate FAR, verification index and time advance TS. The formula is as follows: Hit is the number of convective initiation areas correctly predicted by the satellite, False is the number of convective initiation areas falsely reported by the satellite, and Failure is the number of convective initiation areas missed by the satellite.

2. The method for evaluating the convective initiation product of a geostationary satellite based on Doppler radar according to claim 1, wherein: Identifying and marking cumulus cloud areas in radar composite reflectivity data includes the following steps: S1: interpolation: using the average method to interpolate the radar combined reflectivity data into longitude and latitude grid data with a resolution of 0.04°×0.04°; S2: Perform 0 / 1 conversion: 35 dBz is used as the discrimination threshold of convective intensity. The area with reflectivity value ≥ 35 dBz is the convective area and is replaced by the value 1. The area with reflectivity value < 35 dBz is non-cumulus and is converted to the value 0. S3: Perform data quality control to avoid interference from isolated noise and strong echoes. Before identifying the incipient convection, filter out cumulus areas with smaller areas and remove identified cumulus areas with ≤3 pixels.

3. The method for evaluating the convective initiation product of a geostationary satellite based on a Doppler radar according to claim 2, characterized in that: The identification of radar convective incipient events using the area overlap method includes the following steps: E1: Read the radar reflectivity data of the current time and the previous time, and use the neighborhood method to identify the convection areas of the two time periods, that is, the area with a mark value of 1, which is composed of convection grid points connected in eight directions; E2: Use the area overlap method to track the cloud clusters, remove the convective events that are generated by the translation or development of the cloud clusters at the previous moment, and only extract the convective events generated at the current moment, which is the convective initiation, and set it as a radar convective initiation live sample; E3: Constructing radar convection primary database: Z_RADA_C_BABJ_YYYYMMDDHHmmss_P_DOR_ACHN_CREF_YYYYMMDD_HHmmss.dat is a dat format file for data naming, which provides a real-time data set for the subsequent evaluation of satellite convection primary products.

4. The evaluation method of the convective initiation product of a geostationary satellite based on a Doppler radar according to claim 3, characterized in that: The data naming format is: YYYYMMDDhhmmss: product generation time, year, month, day, hour, minute, and second, all in universal time; ACHN: area code, the national area is ACHN; CREF: abbreviation of radar product type, CREF is radar combination reflectivity; YYYYMMDD_hhmmss: data observation time, year, month, day, hour, minute, second; dat: file extension.

5. The evaluation method of the convective initiation product of a geostationary satellite based on a Doppler radar according to claim 4, characterized in that: The geometric position correction includes the following steps: N1: According to the row and column number and longitude and latitude lookup table, if the longitude and latitude data of FY-4B is not integrated into the L1 data set, it is necessary to download the original longitude and latitude file from the website of the National Satellite Meteorological Center; N2: For different resolutions corresponding to different longitude and latitude files, the longitude and latitude file corresponding to the 0.04°×0.04° resolution is FY4B-_DISK_1050E_GEO_NOM_LUT_20240227000000_4000M_V0001.raw, with a grid size of 2748×2748. This file is a two-dimensional image file with geographic location coordinate information, which corresponds one-to-one to the pixels of the corrected image. N3: The data file in N2 is first filled in from north to south by row or from west to east. Each data stores the corresponding latitude and longitude; each pixel finds the corresponding longitude and latitude information according to the row number and column number in the image to achieve precise positioning.

6. The evaluation method of the convective initiation product of a geostationary satellite based on Doppler radar according to claim 1, characterized in that: The data quality control specifically includes eliminating convective incipient events with ≤3 pixels.

7. A method for evaluating the initial convection products of geostationary satellites based on Doppler radar according to claim 1, characterized in that: The calculation of the correct forecast, false forecast, and missed forecast of satellite convective initiation events includes the following steps: M1: The time resolution of the two is matched by the proximity principle. Based on the satellite convective primary product, the convective primary established by using radar data is taken as the actual situation, and compared with the radar convective primary product of each time before and after 2 hours, and the time advance of the satellite convective primary product is calculated; M2: Based on the goal-oriented idea, a convection initiation area is taken as a sample to determine the correct forecast, missed forecast and false alarm, and the false alarm result is finally generated; M3: Determine the advance time of satellite convection initiation: within the forecast period, the time difference between the correct forecast of satellite convection initiation and the initial satellite convection initiation is the forecast time advance, and the subsequent times do not need to be checked.

8. A method for evaluating the initial convective products of geostationary satellites based on Doppler radar according to claim 7, characterized in that: The method for determining correct forecasts, missed forecasts and false alarms is as follows: when the satellite convection initiation area overlaps with the radar convection initiation area or the number of adjacent grid points is less than 30, it is considered a correct forecast; when the satellite convection initiation area is not adjacent to the radar convection initiation area at all times, it is considered a missed forecast; when the satellite convection initiation area is not adjacent to all radar convection initiation areas at all times within the time period, it is considered a false forecast.

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