It is a well-known fact that during scorching summer days, cities tend to be hotter than forests. To beat the heat, people often escape the concrete jungle and seek solace in the cooling environment of the forest, where temperatures are pleasantly mild. These disparities in temperature are influenced by the distinct characteristics of the land surface (e.g. surface roughness, albedo, emissivity), as well as the properties of the soil (e.g. permeability, thermal conductivity, etc). The variety in land cover plays a critical role in shaping the processes that regulate near-surface temperature. Moreover, strong contrasts in land surface characteristics within a limited area can generate significant surface temperature gradients, which, in turn, have the potential to trigger vertical convective processes and precipitation. The representation of such local scale processes at the land surface is fundamental in climate models, which rely on resolving physical equations that represent the dynamics and thermodynamics of the atmosphere at continuously increasing horizontal resolution. Precise input data is essential for these high resolution models, and the land cover map is one of the most critical, as land surface processes are typically modeled based on land cover and soil texture types that share common physical properties. In regional climate models, these physical properties are carefully tabulated for each land use type. The values are typically defined globally, but should be tailored to the specific target region since generic land cover types (such as crops) may exhibit significant variations from one region to another. In this work, we will delve into the details of how a regional climate model characterizes land surface physical properties and we will evaluate the observable ones against observational products. In particular, we will assess the homogeneity of the land use types across Europe and propose potential improvements to the parameter tables to better align with the observations.
Keywords: Climate Modeling, Land use, Land surface processes, Satellite data, Parameter tuning