A method and device for minute-level low-altitude three-dimensional wind forecasting based on WRF-CALMET

Through the WRF-CALMET system, the WRF model is driven by GFS and Guangdong 3 km forecast data, and combined with terrain elevation and land use data, a multi-process CALMET model is adopted to achieve minute-level low-altitude three-dimensional wind forecasts, solving the problem of low-altitude flight safety threats in existing technologies and improving the accuracy and timeliness of forecasts.

CN120447106BActive Publication Date: 2025-10-14GUANGZHOU GUANGDONG-HONG KONG-MACAO GREATER BAY AREA METEOROLOGICAL INTELLIGENT EQUIP RES CENT
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Patent Information

Application Number
CN202510402119.X
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-04-01
Publication Date
2025-10-14
Estimated Expiration
2045-04-01

AI Technical Summary

Technical Problem

Existing technologies make it difficult to achieve refined low-altitude three-dimensional wind forecasts with a resolution of hundreds of meters. Traditional meteorological data downscaling tools lack minute-level data downscaling capabilities and have slow calculation speeds, threatening low-altitude flight safety.

Method used

The WRF-CALMET system is used to drive the WRF model through GFS global forecast data and Guangdong 3,000-meter forecast data. Combined with terrain elevation and land use data, the CALMET model is run in multiple processes to achieve minute-level low-altitude three-dimensional wind forecasts.

Benefits of technology

It improves the accuracy and timeliness of low-altitude three-dimensional wind forecasts, meets the refined needs of low-altitude flight, and enhances the safety assurance capability of low-altitude flight.

✦ Generated by Eureka AI based on patent content.

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Abstract

The application discloses a kind of minute level low altitude three-dimensional wind forecasting method and device based on WRF-CALMET, including according to GFS global forecast data and Guangdong 3km forecast data, the initial field file and boundary condition file of WRF mode are obtained;According to the initial field file and boundary condition file, the first input file of CALMET mode is obtained by forecasting through WRF mode;According to topographic elevation data and land use data, the second input file of CALMET mode is obtained;According to the first input file and the second input file of CALMET mode, the minute level low altitude three-dimensional wind forecasting result is obtained by running CALMET mode in multiple processes;Wherein, the time length of the minute level low altitude three-dimensional wind forecasting result is 6 hours, and the output time interval is 6 minutes, and the spatial resolution is 100 meters.Compared with prior art, the application can improve the accuracy and timeliness of fine low altitude three-dimensional wind forecasting.
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Description

Technical Field

[0001] The present invention relates to the field of low-altitude economics, and in particular to a minute-level low-altitude three-dimensional wind forecasting method and device based on WRF-CALMET. Background Art

[0002] Low-altitude airspace lies within the atmospheric boundary layer, a layer of air in direct contact with the Earth's surface. Influenced by surface features and topographical differences, coupled with solar radiation, meteorological elements within the boundary layer exhibit significant distribution gradients and diurnal variations, exhibiting a high degree of spatial heterogeneity. Specifically, the low-altitude atmosphere is influenced by both dynamic and thermal factors. Topographical features such as mountains and buildings, as well as local thermal inhomogeneities, can trigger small-scale thermal circulations, while convective systems can cause dramatic disturbances in near-surface airflow. These factors, combined, can significantly alter low-altitude wind fields, posing a potential threat to low-altitude flight safety.

[0003] During low-altitude flight activities, drones are particularly sensitive to meteorological conditions such as strong winds, wind shear, and severe convective weather. Sudden changes in wind direction and speed can cause aircraft to deviate from their planned routes or pose other safety hazards. Low-altitude wind shear and microbursts are recognized by the international aviation and meteorological communities as key factors affecting flight safety. Since the concept of low-altitude economy was proposed, forecasting low-altitude wind fields at the 100-meter level has become a key concern and a challenge for meteorological departments. Although large-scale weather forecast products are currently available, the low quality of meteorological element data required to construct small and medium-scale weather forecast products means that traditional meteorological data downscaling tools lack minute-level data downscaling capabilities and have slow computational speeds. As a result, refined low-altitude three-dimensional wind forecast products with 100-meter resolution remain insufficient. Accurately forecasting low-altitude wind fields and other meteorological elements at the 100-meter level has become a technical bottleneck that meteorological departments urgently need to address.

[0004] Therefore, conducting research on refined three-dimensional wind technology tailored to the needs of low-altitude flight is not only an important technical support for improving low-altitude flight meteorological support capabilities, but also a key measure to promote the sustainable development of the low-altitude economic industry. The establishment of this system will provide a solid technical foundation for improving the meteorological service support system for low-altitude flight routes, while also safeguarding the healthy development of the low-altitude economic industry. Summary of the Invention

[0005] The present invention provides a minute-level low-altitude three-dimensional wind forecast method and device based on WRF-CALMET, which can improve the accuracy and timeliness of refined low-altitude three-dimensional wind forecast.

[0006] In a first aspect, an embodiment of the present invention provides a minute-level low-altitude three-dimensional wind forecast method based on WRF-CALMET, comprising:

[0007] Based on the GFS global forecast data and Guangdong 3 km forecast data, the initial field file and boundary condition file of the WRF model are obtained;

[0008] Based on the initial field file and the boundary condition file, a forecast is performed using the WRF model to obtain a first input file of the CALMET model; wherein the WRF model has a simulation time of 6 hours, an output time interval of 6 minutes, and a spatial resolution of 1 km;

[0009] Obtaining a second input file of the CALMET model based on the terrain elevation data and the land use data; wherein the spatial resolution of the terrain elevation data and the land use data is 100 meters;

[0010] According to the first input file and the second input file of the CALMET model, the CALMET model is run in multiple processes to obtain a minute-level low-altitude three-dimensional wind forecast result; wherein, the duration of the minute-level low-altitude three-dimensional wind forecast result is 6 hours, the output time interval is 6 minutes, and the spatial resolution is 100 meters.

[0011] The embodiment of the present invention uses GFS global forecast data and Guangdong 3 km forecast data to drive the WRF model, making the output data of the WRF model more accurate; the first input file of the CALMET model is obtained through the WRF model, providing a minute-level meteorological initial data basis for the subsequent downscaling of the three-dimensional wind forecast results; the second input file of the CALMET model is obtained through terrain elevation data and land use data, and a geographic static data basis is provided for the subsequent downscaling of the three-dimensional wind forecast results; the CALMET model is run through multiple processes to obtain minute-level low-altitude three-dimensional wind forecast results, which can achieve efficient and refined low-altitude three-dimensional wind forecasts. Compared with the prior art, the present application can improve the accuracy and timeliness of refined low-altitude three-dimensional wind forecasts.

[0012] Furthermore, the initial field file and boundary condition file of the WRF model are obtained based on the GFS global forecast data and the Guangdong 3 km forecast data, specifically:

[0013] According to the soil temperature data and soil moisture data in the GFS global forecast data, the soil data decoding file is obtained;

[0014] Obtain an atmospheric data decoding file based on Guangdong 3 km forecast data; wherein the Guangdong 3 km forecast data includes upper air temperature, geopotential height, meridional wind, zonal wind, relative humidity, 2-meter temperature, 2-meter relative humidity, 10-meter meridional wind, and 10-meter zonal wind data;

[0015] The soil data decoding file and the atmospheric data decoding file are combined and interpolated to obtain an initial field file and a boundary condition file.

[0016] The embodiment of the present invention obtains soil data decoding files and atmospheric data decoding files through GFS global forecast data and Guangdong 3 km forecast data, and provides initial field files and boundary condition files for the WRF model.

[0017] Furthermore, the forecasting is performed by the WRF model based on the initial field file and the boundary condition file to obtain the first input file of the CALMET model, including using a two-layer nested scheme for forecasting:

[0018] The first layer is the Guangdong Province area, with a spatial resolution of 3 kilometers;

[0019] The second layer is the Guangzhou area with a spatial resolution of 1 km; the output data of the second layer is used as the output data of the WRF model.

[0020] The embodiment of the present invention uses a two-layer nested scheme for forecasting, which can capture multi-scale meteorological characteristics.

[0021] Furthermore, the forecast is performed using the WRF model based on the initial field file and the boundary condition file to obtain the first input file of the CALMET model, including parameterization scheme selection:

[0022] The boundary layer parameterization scheme adopts the MYJ scheme;

[0023] The microphysical parameterization scheme adopts the Lin scheme;

[0024] The BMJ scheme is used for the cumulus convection parameterization scheme;

[0025] The longwave radiation parameterization scheme adopts the RRTM scheme;

[0026] The shortwave radiation parameterization scheme adopts the Dudhia scheme.

[0027] The embodiment of the present invention makes the forecast results of the WRF model more accurate by selecting a parameterization scheme.

[0028] Furthermore, the method of performing forecasting by the WRF model based on the initial field file and the boundary condition file to obtain the first input file of the CALMET model further includes:

[0029] According to the output data of the WRF model, a CALWRF code is run to obtain a first input file of the CALMET model; wherein the CALWRF code includes a time calculation function code in seconds and an output code in seconds.

[0030] The embodiment of the present invention modifies the CALWRF data output version and data output format, so that CALWRF can output minute-level WRF mode output data.

[0031] Furthermore, the second input file of the CALMET model is obtained based on the terrain elevation data and land use data, specifically:

[0032] The Copernicus 30-meter resolution terrain elevation data was processed by TERREL to obtain 100-meter resolution terrain elevation data;

[0033] According to the ESA 10-meter resolution land use data, the 100-meter resolution land use data was obtained by processing it through CTGPROC;

[0034] The terrain elevation data and land use data are merged through MAKEGEO to obtain the second input file of the CALMET model.

[0035] In the embodiment of the present invention, a second input file of the CALMET model is obtained through terrain elevation data and land use data, and a three-dimensional wind forecast result is subsequently downscaled to provide a geographic static data basis.

[0036] Furthermore, according to the first input file and the second input file of the CALMET model, the CALMET model is run in multiple processes to obtain a minute-level low-altitude three-dimensional wind forecast result, specifically:

[0037] The Guangzhou area is divided into multiple sub-areas; each sub-area corresponds to a CALMET model;

[0038] Calculate all CALMET modes in parallel to obtain all CALMET mode output data;

[0039] Based on the CALMET model output data, minute-level low-altitude three-dimensional wind forecast results are obtained.

[0040] The embodiment of the present invention improves the efficiency of minute-level low-altitude three-dimensional wind forecast by running the CALMET mode in multiple processes.

[0041] Furthermore, all CALMET modes are operated in parallel to obtain all CALMET mode output data, specifically:

[0042] Reading the first input file and the second input file of the CALMET model through the minute-level output data reading code of the CALMET model;

[0043] The first input file and the second input file of the CALMET model are processed by the CALMET model running body to obtain CALMET model output data.

[0044] The embodiment of the application improves the code of the CALMET mode, so that the CALMET mode can process minute-level input data.

[0045] Further, the minute-level low-altitude three-dimensional wind prediction result is obtained according to the CALMET mode output data, and specifically comprises the following steps:

[0046] The CALMET mode output data is decoded to obtain the minute-level low-altitude three-dimensional wind prediction result of all regions.

[0047] The minute-level low-altitude three-dimensional wind prediction result of all regions is spatially networked to obtain the minute-level low-altitude three-dimensional wind prediction result of the whole region.

[0048] The embodiment of the application decodes and assembles the minute-level low-altitude three-dimensional wind prediction result of all regions to obtain the minute-level low-altitude three-dimensional wind prediction result of the whole region.

[0049] In a second aspect, the embodiment of the application provides a minute-level low-altitude three-dimensional wind prediction device based on WRF-CALMET, comprising a first data processing module, a WRF mode prediction module, a second data processing module and a CALMET mode prediction module.

[0050] The first data processing module is configured to obtain an initial field file and a boundary condition file of the WRF mode according to GFS global prediction data and Guangdong 3km prediction data.

[0051] The WRF mode prediction module is configured to perform prediction through the WRF mode according to the initial field file and the boundary condition file to obtain a first input file of the CALMET mode, wherein the simulation time length of the WRF mode is 6 hours, the output time interval is 6 minutes, and the spatial resolution is 1km.

[0052] The second data processing module is configured to obtain a second input file of the CALMET mode according to terrain elevation data and land use data, wherein the spatial resolution of the terrain elevation data and the land use data is 100m.

[0053] The CALMET mode prediction module is configured to run the CALMET mode in multiple processes according to the first input file and the second input file of the CALMET mode to obtain a minute-level low-altitude three-dimensional wind prediction result, wherein the time length of the minute-level low-altitude three-dimensional wind prediction result is 6 hours, the output time interval is 6 minutes, and the spatial resolution is 100m.

[0054] The embodiment of the present invention uses the GFS global forecast data and Guangdong 3-kilometer forecast data to drive the WRF model through a first data processing module, so that the output data of the WRF model is more accurate; the first input file of the CALMET model is obtained through the WRF model forecast module, providing a minute-level meteorological initial data basis for subsequent downscaling of three-dimensional wind forecast results; the second input file of the CALMET model is obtained by processing terrain elevation data and land use data through a second data processing module, and providing a geographic static data basis for subsequent downscaling of three-dimensional wind forecast results; the CALMET model is run through multiple processes of the CALMET model forecast module to obtain a minute-level low-altitude three-dimensional wind forecast result, which can achieve efficient and refined low-altitude three-dimensional wind forecast. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 A schematic diagram of a flow chart of a minute-level low-altitude three-dimensional wind forecast method based on WRF-CALMET provided in an embodiment of the present invention;

[0056] Figure 2 A schematic diagram of the process of a minute-level low-altitude three-dimensional wind forecast product based on WRF-CALMET provided in an embodiment of the present invention;

[0057] Figure 3 A schematic diagram of the structure of a minute-level low-altitude three-dimensional wind forecasting device based on WRF-CALMET provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0058] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0059] Example 1

[0060] Please refer to Figure 1 , a minute-level low-altitude three-dimensional wind forecast method based on WRF-CALMET provided in an embodiment of the present invention includes steps S101 to S104, which are described in detail as follows:

[0061] Step S101: Obtain the initial field file and boundary condition file of the WRF model based on the GFS global forecast data and the Guangdong 3 km forecast data.

[0062] In this step, the initial field file and boundary condition file of the WRF model are obtained based on the GFS global forecast data and the Guangdong 3 km forecast data, specifically:

[0063] According to soil temperature data and soil humidity data in GFS global forecast data, obtain a soil data decoding file; optionally, the GFS global forecast data (Global Forecast System meteorological forecast data run by the U.S. National Environmental Prediction Center) is 72 hours of forecast data, with a time interval of 3 hours, and is updated every 6 hours;

[0064] According to Guangdong 3 km forecast data, obtain an atmospheric data decoding file; wherein, the Guangdong 3 km forecast data contains high-altitude temperature, potential height, meridional wind, zonal wind, relative humidity, 2-meter temperature, 2-meter relative humidity, 10-meter meridional wind and 10-meter zonal wind data; optionally, the Guangdong 3 km forecast data (3 km resolution forecast data of the Pan-Pearl River Delta / South China Sea region produced in real time by the Guangzhou Tropical Meteorology Institute) is 30 hours of forecast data, with a time interval of 1 hour, and is updated every 1 hour;

[0065] Merge and interpolate the soil data decoding file and the atmospheric data decoding file to obtain an initial field file and a boundary condition file.

[0066] Illustratively, the soil data, atmospheric data and geographic static data in the WPS of the WRF model are processed (the WRF model is provided by the official website), including: writing a namelist file to set the calculation area, nested grid and geographic static data path; processing geographic static data; writing a GFS soil information Vtable to decode GFS global forecast data; writing a Guangdong 3 km data decoding Vtable to decode Guangdong 3 km data; processing atmospheric data and interpolating and merging to obtain met_em data; processing the met_em data into an initial field file and a boundary condition file of the WRF model.

[0067] This embodiment obtains a soil data decoding file and an atmospheric data decoding file through GFS global forecast data and Guangdong 3 km forecast data, and provides an initial field file and a boundary condition file for the WRF model.

[0068] Step S102, according to the initial field file and the boundary condition file, the WRF model is used to make a prediction to obtain a first input file of the CALMET model; wherein, the simulation time length of the WRF model is 6 hours, the output time interval is 6 minutes, and the spatial resolution is 1 km.

[0069] In this step, according to the initial field file and the boundary condition file, the WRF model is used to make a prediction to obtain a first input file of the CALMET model, including using a two-layer nested scheme to make a prediction:

[0070] The first layer is the Guangdong Province area, with a spatial resolution of 3 kilometers;

[0071] The second layer is the Guangzhou area with a spatial resolution of 1 km; the output data of the second layer is used as the output data of the WRF model.

[0072] This embodiment uses a two-layer nested solution for forecasting, which can capture multi-scale meteorological characteristics.

[0073] In this step, the WRF model is used to forecast based on the initial field file and the boundary condition file to obtain the first input file of the CALMET model, including the parameterization scheme selection:

[0074] The boundary layer parameterization scheme adopts the MYJ scheme;

[0075] The microphysical parameterization scheme adopts the Lin scheme;

[0076] The BMJ scheme is used for the cumulus convection parameterization scheme;

[0077] The longwave radiation parameterization scheme adopts the RRTM scheme;

[0078] The shortwave radiation parameterization scheme adopts the Dudhia scheme.

[0079] Optionally, a sensitivity experiment is conducted on the parameterization schemes of the WRF model to obtain the final parameterization scheme combination. All parameterization schemes are shown in Table 1.

[0080] Table 1 - WRF model parameterization scheme

[0081]

[0082] This embodiment makes the forecast results of the WRF model more accurate by selecting a parameterization scheme.

[0083] In this step, the forecast is performed using the WRF model based on the initial field file and the boundary condition file to obtain the first input file of the CALMET model, which also includes:

[0084] According to the output data of the WRF model, a CALWRF code is run to obtain a first input file of the CALMET model; wherein the CALWRF code includes a time calculation function code in seconds and an output code in seconds.

[0085] This embodiment modifies the CALWRF data output version and data output format so that CALWRF can output minute-level WRF mode output data.

[0086] Step S103, obtaining a second input file of the CALMET model according to the terrain elevation data and the land use data; wherein, the terrain elevation data and the land use data have a spatial resolution of 100 meters.

[0087] In this step, the second input file of the CALMET model is obtained according to the terrain elevation data and the land use data, specifically:

[0088] According to the 30-meter resolution terrain elevation data of Copernicus, the terrain elevation data with a resolution of 100 meters is obtained by processing the terrain elevation data through the TERREL (terrain elevation data preprocessing module).

[0089] According to the 10-meter resolution land use data of the European Space Agency, the land use data with a resolution of 100 meters is obtained by processing the land use data through the CTGPROC (land use data preprocessing module); optionally, the CTGPROC calculates roughness, surface albedo, Bowen ratio, soil heat flux, anthropogenic heat flux, and leaf area index and other parameters to obtain the land use data with a resolution of 100 meters according to different land use types.

[0090] The terrain elevation data and the land use data are merged by MAKEGEO to obtain the second input file of the CALMET model.

[0091] Illustratively, the terrain elevation data file terrain.dat is generated by TERREL; the land use data file lu.dat is generated by CTGPROC; the terrain elevation data file terrain.dat and the land use data file lu.dat are merged by MAKEGEO to obtain the geographic static data file geo.dat that can be recognized by the CALMET model.

[0092] This embodiment obtains the second input file of the CALMET model through the terrain elevation data and the land use data, and provides a geographic static data basis for subsequent three-dimensional wind forecast result downscaling.

[0093] Step S104, running the CALMET model in multiple processes according to the first input file and the second input file of the CALMET model to obtain a minute-level low-altitude three-dimensional wind forecast result; wherein, the minute-level low-altitude three-dimensional wind forecast result has a time length of 6 hours, an output time interval of 6 minutes, and a spatial resolution of 100 meters.

[0094] In this step, the CALMET model is run in multiple processes according to the first input file and the second input file of the CALMET model to obtain a minute-level low-altitude three-dimensional wind forecast result, specifically:

[0095] The Guangzhou region is divided into multiple sub-regions; wherein, one sub-region corresponds to one CALMET model;

[0096] All the CALMET models are operated in parallel to obtain all the CALMET model output data;

[0097] According to the CALMET model output data, a minute-level low-altitude three-dimensional wind prediction result is obtained.

[0098] Optionally, each CALMET model reduces the mesoscale three-dimensional wind field to a small-scale three-dimensional wind field by considering the interaction between the near-surface layer wind and the underlying surface (topographic dynamics, slope flow, topographic blocking effect, while using vertical velocity adjustment and three-dimensional divergence minimization to adjust the wind direction and wind speed), specifically:

[0099] Topographic dynamic effect: mainly considering the forcing effect of terrain on air mass velocity, mainly calculating the vertical wind speed affected by terrain through the horizontal wind of the region and the terrain slope, and assuming that the vertical velocity satisfies a decreasing function (the decreasing function is related to atmospheric stability);

[0100] Slope flow: the slope flow is calculated by using MAHRT's formula for shooting flows, and the slope flow is a buoyancy-driven flow, and is balanced with the surrounding weak flow, surface drag and carrying effect at the top of the slope flow layer; terrain slope, distance to the top of the slope peak and local sensible heat flux are used for parameterization calculation; the calculated slope flow (thermal inhomogeneity) is added to the background field wind;

[0101] Topographic blocking effect: the topographic blocking effect refers to the thermodynamic blocking effect of terrain on the wind field, which is calculated by the local Froude number, if the calculated value of the grid point is less than the critical Froude number, and the wind has an uphill wind amount, the wind direction is adjusted to be tangent to the terrain, and the wind speed remains unchanged; if it exceeds the critical Froude number, no adjustment is needed;

[0102] Three-dimensional divergence minimization: using the continuity equation, divergence minimization constraint, adjusting three-dimensional wind direction and wind speed.

[0103] The embodiment improves the efficiency of minute-level low-altitude three-dimensional wind prediction by running the CALMET model in multiple processes.

[0104] Further, the parallel operation of all the CALMET models obtains all the CALMET model output data, specifically:

[0105] The minute-level output data reading code of the CALMET model is used to read the first input file and the second input file of the CALMET model;

[0106] The first input file and the second input file of the CALMET model are processed by the CALMET model running body to obtain CALMET model output data.

[0107] Optionally, the CALMET mode can solve the problem of the initial CALMET mode reporting time limit by modifying the initial calculation time setting (the calculation time set in the initial CALMET mode must be before sunset, and the starting calculation time is 0-5 hours to ensure that the initial mixing layer height is 0). The initial mixing layer height is proposed to adopt the following empirical formula:

[0108]

[0109] Where H is the initial mixing layer height; TT d is the dew point difference; P is the Pasquier stability level; Z is the height; U z is the average wind speed observed at height Z; z0 is the ground roughness; f is the geostrophic parameter.

[0110] This embodiment transforms the code of the CALMET model so that the CALMET model can process minute-level input data.

[0111] Furthermore, the CALMET model output data is used to obtain minute-level low-altitude three-dimensional wind forecast results, specifically:

[0112] Decoding the CALMET model output data to obtain minute-level low-level three-dimensional wind forecast results for all regions;

[0113] The minute-level low-altitude three-dimensional wind forecast results for all the areas are spatially networked to obtain the minute-level low-altitude three-dimensional wind forecast results for the entire area.

[0114] This embodiment obtains the minute-level low-altitude three-dimensional wind forecast results for the entire area by decoding and piecing together the minute-level low-altitude three-dimensional wind forecast results for all areas.

[0115] For example, please refer to Figure 2 , a minute-level low-altitude three-dimensional wind forecast product based on WRF-CALMET provided in an embodiment of the present invention, comprising:

[0116] The WRF model is driven by GFS global forecast data and Guangdong 3 km forecast data, and the wrfout data with an output time interval of 6 minutes and a spatial resolution of 1 km is obtained;

[0117] According to the wrfout data, write the ca lwrf.i np file and run the ca lwrf.exe file to obtain the first input file of the CALMET model;

[0118] The Copernicus 30-meter resolution terrain elevation data was processed by TERREL, the ESA 10-meter resolution land use data was processed by CTGPROC, and the terrain elevation data and land use data were merged by MAKEGEO to obtain the second input file of the CALMET model;

[0119] A modified CALMET model was used for spatial downscaling. During the downscaling process, the Guangzhou area was divided into 35 sub-regions. Then, a CALMET model was called for each sub-region to perform calculations, obtaining minute-level low-altitude three-dimensional wind forecast data with a resolution of 100 meters.

[0120] Use Python to decode the 100-meter resolution minute-level low-altitude three-dimensional wind forecast data, and spatially network all sub-areas to obtain the minute-level low-altitude three-dimensional wind forecast product for the entire area; wherein, the forecast duration of the minute-level low-altitude three-dimensional wind forecast product is 6 hours, the temporal resolution is 6 minutes, the spatial resolution is 100 meters, the number of vertical layers is 21, and the heights above the ground are 20 meters, 50 meters, 70 meters, 100 meters, 150 meters, 200 meters, 250 meters, 300 meters, 350 meters, 400 meters, 450 meters, 500 meters, 600 meters, 700 meters, 800 meters, 900 meters, 1000 meters, 1500 meters, 2000 meters, 2500 meters and 3000 meters.

[0121] This embodiment uses GFS global forecast data and Guangdong 3 km forecast data to drive the WRF model, making the output data of the WRF model more accurate; the first input file of the CALMET model is obtained through the WRF model, providing a minute-level meteorological initial data basis for the subsequent downscaling of the three-dimensional wind forecast results; the second input file of the CALMET model is obtained through terrain elevation data and land use data, providing a geographic static data basis for the subsequent downscaling of the three-dimensional wind forecast results; the CALMET model is run through multiple processes to obtain minute-level low-altitude three-dimensional wind forecast results, which can achieve efficient and refined low-altitude three-dimensional wind forecasts. Compared with the prior art, this application can improve the accuracy and timeliness of refined low-altitude three-dimensional wind forecasts.

[0122] Example 2

[0123] Please refer to Figure 3 , a minute-level low-altitude three-dimensional wind forecasting device based on WRF-CALMET provided in an embodiment of the present invention includes a first data processing module 301, a WRF model forecasting module 302, a second data processing module 303, and a CALMET model forecasting module 304, which are described in detail as follows:

[0124] The first data processing module 301 is used to obtain the initial field file and boundary condition file of the WRF model based on the GFS global forecast data and the Guangdong 3 km forecast data;

[0125] The WRF model forecast module 302 is used to forecast using the WRF model based on the initial field file and the boundary condition file to obtain a first input file for the CALMET model; wherein the WRF model has a simulation duration of 6 hours, an output time interval of 6 minutes, and a spatial resolution of 1 km;

[0126] The second data processing module 303 is used to obtain a second input file of the CALMET model based on the terrain elevation data and the land use data; wherein the spatial resolution of the terrain elevation data and the land use data is 100 meters;

[0127] The CALMET model forecast module 304 is used to run the CALMET model in multiple processes according to the first input file and the second input file of the CALMET model to obtain a minute-level low-altitude three-dimensional wind forecast result; wherein the minute-level low-altitude three-dimensional wind forecast result has a duration of 6 hours, an output time interval of 6 minutes, and a spatial resolution of 100 meters.

[0128] In this embodiment, the first data processing module 301 includes a soil data submodule, an air data submodule, and a first data merging submodule, specifically:

[0129] The soil data submodule is used to obtain a soil data decoding file based on the soil temperature data and soil moisture data in the GFS global forecast data;

[0130] The atmospheric data submodule is used to obtain an atmospheric data decoding file based on Guangdong 3 km forecast data; wherein the Guangdong 3 km forecast data includes high-altitude temperature, geopotential height, meridional wind, zonal wind, relative humidity, 2-meter temperature, 2-meter relative humidity, 10-meter meridional wind, and 10-meter zonal wind data;

[0131] The first data merging submodule is used to merge and interpolate the soil data decoding file and the atmospheric data decoding file to obtain an initial field file and a boundary condition file.

[0132] This embodiment obtains soil data decoding files and atmospheric data decoding files through GFS global forecast data and Guangdong 3 km forecast data, and provides initial field files and boundary condition files for the WRF model.

[0133] In this embodiment, the WRF model forecast module 302 includes nested scheme submodules, specifically:

[0134] The first layer is the Guangdong Province area, with a spatial resolution of 3 kilometers;

[0135] The second layer is the Guangzhou area with a spatial resolution of 1 km; the output data of the second layer is used as the output data of the WRF model.

[0136] This embodiment uses a two-layer nested solution for forecasting, which can capture multi-scale meteorological characteristics.

[0137] In this embodiment, the WRF model forecast module 302 includes a parameterized scheme submodule, specifically:

[0138] The boundary layer parameterization scheme adopts the MYJ scheme;

[0139] The microphysical parameterization scheme adopts the Lin scheme;

[0140] The BMJ scheme is used for the cumulus convection parameterization scheme;

[0141] The longwave radiation parameterization scheme adopts the RRTM scheme;

[0142] The shortwave radiation parameterization scheme adopts the Dudhia scheme.

[0143] This embodiment makes the forecast results of the WRF model more accurate by selecting a parameterization scheme.

[0144] In this embodiment, the WRF model forecast module 302 further includes a data conversion submodule, specifically:

[0145] The data conversion submodule is used to run the CALWRF code according to the output data of the WRF model to obtain the first input file of the CALMET model; wherein the CALWRF code includes a time calculation function code in seconds and an output code in seconds.

[0146] This embodiment modifies the CALWRF data output version and data output format so that CALWRF can output minute-level WRF mode output data.

[0147] In this embodiment, the second data processing module 303 further includes a terrain elevation data submodule, a land use data submodule, and a second data merging submodule, specifically:

[0148] The terrain elevation data submodule is used to process the Copernicus 30-meter resolution terrain elevation data through TERREL to obtain 100-meter resolution terrain elevation data;

[0149] The land use data submodule is configured to process the land use data of the European Space Agency (ESA) with a 10-meter resolution by using CTGPROC to obtain land use data with a 100-meter resolution.

[0150] The second data merging submodule is configured to merge the terrain elevation data and the land use data by using MAKEGEO to obtain a second input file of the CALMET model.

[0151] The terrain elevation data and the land use data are used to obtain the second input file of the CALMET model, and geographic static data is provided for subsequent three-dimensional wind forecast result downscaling.

[0152] In this embodiment, the CALMET model prediction module 304 includes a region division submodule, a model operation submodule, and a result output submodule, and specifically includes:

[0153] The region division submodule is configured to divide the region of Guangzhou into a plurality of sub-regions, and one sub-region corresponds to one CALMET model.

[0154] The model operation submodule is configured to operate all the CALMET models in parallel to obtain all the CALMET model output data.

[0155] The result output submodule is configured to obtain the minute-level low-altitude three-dimensional wind forecast result according to the CALMET model output data.

[0156] This embodiment improves the efficiency of the minute-level low-altitude three-dimensional wind forecast by running the CALMET model in multiple processes.

[0157] In this embodiment, the model operation submodule includes a data reading unit and a model operation unit, and specifically includes:

[0158] The data reading unit is configured to read the first input file and the second input file of the CALMET model by using a minute-level output data reading code of the CALMET model.

[0159] The model operation unit is configured to process the first input file and the second input file of the CALMET model by using a CALMET model running main body to obtain the CALMET model output data.

[0160] This embodiment modifies the code of the CALMET model so that the CALMET model can process minute-level input data.

[0161] In this embodiment, the result output submodule includes a data decoding unit and a result splicing unit, and specifically includes:

[0162] The data decoding unit is configured to decode the CALMET mode output data to obtain the minute-level low-altitude three-dimensional wind prediction result of all regions.

[0163] The result splicing unit is configured to spatially network the minute-level low-altitude three-dimensional wind prediction result of all regions to obtain the minute-level low-altitude three-dimensional wind prediction result of the whole region.

[0164] The embodiment obtains the minute-level low-altitude three-dimensional wind prediction result of the whole region by decoding and splicing the minute-level low-altitude three-dimensional wind prediction result of all regions.

[0165] The device described above can implement the method of the method embodiment described above. The optional items in the method embodiment described above are also applicable to the embodiment, and will not be described in detail here. The remaining content of the embodiment of the present application can refer to the content of the method embodiment described above, and will not be described in detail in the embodiment.

[0166] The embodiment drives the WRF mode by using the GFS global prediction data and the Guangdong 3-kilometer prediction data through the first data processing module, so that the output data of the WRF mode is more accurate; the first input file of the CALMET mode is obtained through the WRF mode prediction module, which provides the basis of the initial meteorological data of the minute level for subsequent three-dimensional wind prediction result downscaling; the second input file of the CALMET mode is obtained by processing the terrain elevation data and the land use data through the second data processing module, which provides the basis of the geographical static data for subsequent three-dimensional wind prediction result downscaling; the minute-level low-altitude three-dimensional wind prediction result is obtained by running the CALMET mode through the CALMET mode prediction module, which can realize efficient and refined low-altitude three-dimensional wind prediction. Compared with the prior art, the present application can improve the accuracy and timeliness of refined low-altitude three-dimensional wind prediction.

[0167] The specific embodiments described above further illustrate the purpose, technical solutions and beneficial effects of the present application. It should be understood that the above description is only a specific embodiment of the present application and is not intended to limit the protection scope of the present application. It should be particularly pointed out that any modification, equivalent replacement, improvement, etc. made by those skilled in the art within the spirit and principles of the present application should be included in the protection scope of the present application.

Claims

1. A minute-level low-altitude three-dimensional wind forecast method based on WRF-CALMET, characterized by: include: Based on the GFS global forecast data and Guangdong 3 km forecast data, the initial field file and boundary condition file of the WRF model are obtained; Based on the initial field file and the boundary condition file, a forecast is performed using the WRF model to obtain a first input file of the CALMET model; wherein the WRF model has a simulation time of 6 hours, an output time interval of 6 minutes, and a spatial resolution of 1 km; Obtaining a second input file of the CALMET model based on the terrain elevation data and the land use data; wherein the spatial resolution of the terrain elevation data and the land use data is 100 meters; According to the first input file and the second input file of the CALMET model, the CALMET model is run in multiple processes to obtain a minute-level low-altitude three-dimensional wind forecast result; wherein, the duration of the minute-level low-altitude three-dimensional wind forecast result is 6 hours, the output time interval is 6 minutes, and the spatial resolution is 100 meters.

2. A WRF-CALMET-based minute-level low-altitude three-dimensional wind forecast method according to claim 1, characterized in that: According to the GFS global forecast data and Guangdong 3 km forecast data, the initial field file and boundary condition file of the WRF model are obtained, specifically: According to the soil temperature data and soil moisture data in the GFS global forecast data, the soil data decoding file is obtained; Obtain an atmospheric data decoding file based on Guangdong 3 km forecast data; wherein the Guangdong 3 km forecast data includes upper air temperature, geopotential height, meridional wind, zonal wind, relative humidity, 2-meter temperature, 2-meter relative humidity, 10-meter meridional wind, and 10-meter zonal wind data; The soil data decoding file and the atmospheric data decoding file are merged and interpolated to obtain an initial field file and a boundary condition file.

3. A WRF-CALMET-based minute-level low-altitude three-dimensional wind forecast method according to claim 1, characterized in that: The method comprises: performing forecasting by using the WRF model according to the initial field file and the boundary condition file to obtain the first input file of the CALMET model, including using a two-layer nested scheme for forecasting: The first layer is the Guangdong Province area, with a spatial resolution of 3 kilometers; The second layer is the Guangzhou area with a spatial resolution of 1 km; the output data of the second layer is used as the output data of the WRF model.

4. A WRF-CALMET-based minute-level low-altitude three-dimensional wind forecast method according to claim 3, characterized in that: The WRF model is used to forecast based on the initial field file and the boundary condition file to obtain the first input file of the CALMET model, including parameterization scheme selection: The boundary layer parameterization scheme adopts the MYJ scheme; The microphysical parameterization scheme adopts the Lin scheme; The cumulus convection parameterization scheme adopts the BMJ scheme; The longwave radiation parameterization scheme adopts the RRTM scheme; The shortwave radiation parameterization scheme adopts the Dudhia scheme.

5. A WRF-CALMET-based minute-level low-altitude three-dimensional wind forecast method according to claim 3, characterized in that: The method further comprises: performing forecasting by the WRF model according to the initial field file and the boundary condition file to obtain a first input file of the CALMET model; According to the output data of the WRF model, a CALWRF code is run to obtain a first input file of the CALMET model; wherein the CALWRF code includes a time calculation function code in seconds and an output code in seconds.

6. A method for forecasting low-altitude three-dimensional wind at the minute level based on WRF-CALMET according to claim 1, characterized in that: The second input file of the CALMET model is obtained based on the terrain elevation data and land use data, specifically: The Copernicus 30-meter resolution terrain elevation data was processed by TERREL to obtain 100-meter resolution terrain elevation data; According to the ESA 10-meter resolution land use data, the 100-meter resolution land use data was obtained by processing it through CTGPROC; The terrain elevation data and land use data are merged through MAKEGEO to obtain the second input file of the CALMET model.

7. A WRF-CALMET-based minute-level low-altitude three-dimensional wind forecast method according to claim 1, characterized in that: According to the first input file and the second input file of the CALMET model, the CALMET model is run in multiple processes to obtain the minute-level low-altitude three-dimensional wind forecast result, specifically: The Guangzhou area is divided into multiple sub-areas; each sub-area corresponds to a CALMET model; Calculate all CALMET modes in parallel to obtain all CALMET mode output data; Based on the CALMET model output data, minute-level low-altitude three-dimensional wind forecast results are obtained.

8. A WRF-CALMET-based minute-level low-altitude three-dimensional wind forecast method according to claim 7, characterized in that: The parallel operation of all CALMET modes obtains all CALMET mode output data, specifically: Reading the first input file and the second input file of the CALMET model through the minute-level output data reading code of the CALMET model; The first input file and the second input file of the CALMET model are processed by the CALMET model running body to obtain CALMET model output data.

9. A WRF-CALMET-based minute-level low-altitude three-dimensional wind forecast method according to claim 7, characterized in that: The CALMET model output data is used to obtain minute-level low-altitude three-dimensional wind forecast results, specifically: Decoding the CALMET model output data to obtain minute-level low-level three-dimensional wind forecast results for all regions; The minute-level low-altitude three-dimensional wind forecast results for all the areas are spatially networked to obtain the minute-level low-altitude three-dimensional wind forecast results for the entire area.

10. A minute-level low-altitude three-dimensional wind forecasting device based on WRF-CALMET, characterized in that: include: The first data processing module, the WRF model forecast module, the second data processing module and the CALMET model forecast module: The first data processing module is used to obtain the initial field file and boundary condition file of the WRF model based on the GFS global forecast data and the Guangdong 3 km forecast data; The WRF model forecast module is used to forecast using the WRF model based on the initial field file and the boundary condition file to obtain a first input file for the CALMET model; wherein the WRF model has a simulation duration of 6 hours, an output time interval of 6 minutes, and a spatial resolution of 1 km; The second data processing module is used to obtain a second input file of the CALMET model based on the terrain elevation data and the land use data; wherein the spatial resolution of the terrain elevation data and the land use data is 100 meters; The CALMET model forecast module is used to run the CALMET model in multiple processes according to the first input file and the second input file of the CALMET model to obtain a minute-level low-altitude three-dimensional wind forecast result; wherein the minute-level low-altitude three-dimensional wind forecast result has a duration of 6 hours, an output time interval of 6 minutes, and a spatial resolution of 100 meters.

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