Land use and soil texture effects on WRFv4.3

In meteorological models, land use and soil texture play a key role in determining surface variables, as they intervene in the exchange of energy, moisture and momentum between the land and the air. In recent years, new data have been made public at higher resolutions, whether they are based on satellite, surveys or machine learning.In this work we want to study the impact of using updated datasets of land use and soil textures in the WRF model (v4.3) with the Noah-MP surface parameterization, which operationally runs at Meteorological Service of Catalonia (SMC).For the land use, we combine two sources, the Europe CORINE land cover (2018) at 100m resolution, and, with 1m resolution, one from the cartographic and geological institute of Catalonia (ICGC), an organization carrying out actions related to the awareness, survey and information about the soil and subsoil.For soil texture, we use SOILGRIDS, a system for global digital soil mapping that makes use of global soil profile information and covariate data to model the spatial distribution of soil properties, which includes some additional variables such as silt, density and gravel. These let us analyze the impact of three different pedotransfer functions: Saxton Rawls (2006), Wsten(1999), Weynants (2009) that transform the variables given by the soil texture to the ones needed by the model.The results of the different initializations are verified against our surface station network for the spring 2023 to quantify their impact. Our results compared to the operational version show an improvement on wind and temperature, with a wider thermal range.BibliographyJimnez-Esteve B, et al: Land use and topography influence in a complex terrain area: a high resolution mesoscale modelling study over the Eastern Pyrenees using the WRF model. Atmos Res, 202, (2018):4962 Pedruzzi R. et al: Update of land use/land cover and soil texture for Brazil: Impact on WRF modeling results over So Paulo, Atmospheric Environment, 268, (2022)Poggio, L., et al: SoilGrids 2.0: producing soil information for the globe with quantified spatial uncertainty, SOIL, 7,(2021), 217240Saxton K.E. et al: Estimating generalized soil-water characteristics from texture, Soil Sci. Soc. Am. J., 50 (1986), pp. 1031-1036Weynants M. et al: Revisiting Vereecken pedotransfer functions: introducing a closed-form hydraulic model, Vadose Zone J., 8 (2009), pp. 86-95Wsten J.H.M. et al: Development and use of a database of hydraulic properties of European soils, Geoderma, 90 (1999), pp. 169-185