Impact of soil texture in coupled regional climate model on land-atmosphere interactionsImpact of soil texture in coupled regional climate model on land-atmosphere interactionsLazić et al.

Like the oceans, which store heat and create a “memory” in the climate system, the land also accumulates water, which also contributes to climate persistence. One of the considerable sources of uncertainty in regional climate models, which are crucial climate impact and adaptation support tools, is related to soil texture datasets and its soil parameters. Soil properties, defined by parameters in soil datasets, influence surface water and energy cycles and hence play a role in land-atmosphere exchanges. In this study, the main goal was to inspect uncertainty of the simulated mean and extreme climate to changes in prescribed soil texture datasets. We performed climate simulations over Europe with a particular focus on the Pannonian Basin during the summer season with a fully coupled regional climate model EBU-POM using two different soil maps: the STATSGO/FAO global hybrid map and the Zobler soil texture map generalized from the FAO Soil Map of the World, which has a lower spatial resolution. The simulations showed that regions with lower latent heat (corresponding to a lower evaporative fraction) coincide with areas that have a higher 2-m temperature (above + 0.4 °C) and drier soils (with a soil moisture content of less than − 60 mm). Also, differences in soil moisture content, primarily driven by changes in soil texture, largely coincide with differences in parameters such as the wilting point and soil water diffusivity which highlight the importance of these parameters in shaping surface fluxes. Furthermore, these experiments illustrate the important role of soil parameters in the dynamics of the summer climate, as they affect the coupling strength and consequently influence climate and its extremes. Results suggest that the choice of soil parameters/soil texture datasets has considerable consequences, especially on climate extremes, as biases and coupling strength can be more pronounced.