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Increased computing power has made it possible to run simulations of the Weather Research and Forecasting (WRF) numerical model in high spatial resolution. However, running high-resolution simulations requires a higher-detail mapping of landforms, land use, and land cover. Often, higher-resolution data have limited coverage or availability. This paper presents the feasibility of using CORINE Land Cover (CLC) land use and land cover data and alternative high-resolution global coverage land use/land cover (LULC) data from Copernicus Global Land Service Land Cover Map (CGLS-LC100) V2.0 in high-resolution WRF simulations (100 × 100 m). Global LULC data with a resolution of 100 m are particularly relevant for areas not covered by CLC. This paper presents the method developed by the authors for reclassifying land cover data from CGLS-LC100 to MODIS land use classes with defined parameters in the WRF model and describes the procedure for their implementation into the model. The obtained simulation results of the basic meteorological parameters from the WRF simulation using CLC, CGLS-LC100 and default geographical data from MODIS were compared to observations from 13 meteorological stations in the Warsaw area. The research has indicated noticeable changes in the forecasts of temperature, relative humidity wind speed, and direction after using higher-resolution LULC data. The verification results show a significant difference in weather predictions in terms of CLC and CGLS-LC100 LULC data implementation. Due to the fact that better results were obtained for CLC simulations than for CGLS-LC100, it is suggested that CLC data are first used for simulations in numerical weather prediction models and to use CGLS-LC100 data when the area is outside of CLC coverage. [ABSTRACT FROM AUTHOR]

The Weather Research and Forecasting (WRF) model is commonly associated with meteorological data, but its algorithms may also use geographical data. The objective of this paper is to evaluate the impact of the high resolution CORINE Land Cover (CLC) data and the SRTM topography on the estimation accuracy of the weather model parameters in the WRF microscale simulations (200 × 200 m) for Warsaw. In the presented studies, the authors propose their own method of attaching the CLC data to the WRF microscale modeling for the CLC border areas, where first calculational domains reach beyond areas of CLC coverage. As a part of the research, the adaptation of the proposed method was examined by the assessment of the WRF microscale modeling simulations for Warsaw. The modified IGBP MODIS land use/land cover (LULC) and USGS GMTED2010 terrain elevation geographical data (30 arc seconds) was applied for the WRF simulations as default. As higher resolution geographical data (100 m), the LULC from CORINE Land Cover (CLC) 2018 data, and the SRTM topography were adopted. In this study the forecasts of air temperature and relative humidity at 2 m, and wind (speed and direction) at 10 m above ground level obtained using the WRF model for particular simulations were evaluated against measurements made at the Warsaw airports: Chopin (EPWA) and Babice (EPBC). The research has indicated that for microscale calculation fields there are noticeable changes in the meteorological parameter values when the CLC and the SRTM data are integrated into the WRF model, which in most cases yielded more accurate values of temperature and relative humidity at 2 m. This has also proved the correctness of the proposed methodology of the CLC data adoption. The improvement in the forecasted meteorological parameters is different for the particular locations and depends on the degree of the LULC and topography data change after higher resolution data adoption. [ABSTRACT FROM AUTHOR]