Sensitivity of Convection-Permitting Regional Climate Simulations to Changes in Land Cover Input Data: Role of Land Surface Characteristics for Temperature and Climate Extremes - Tölle, Merja H.; Churiulin, Evgenii (Frontiers in Earth Science, 2021)
In climate models, sufficient characterization of climate uncertainties is essential for mitigation and adaptation strategies due to different land cover maps. The spatiotemporal heterogeneity in surface parameters is considered to play a key role in terrestrial surface processes. Here, we quantified the climate uncertainty due to different land cover maps (GlobCover2009, GLC2000, CCI, and ECOCLIMAP) in the COSMO-CLM (v5.0_clm16). We investigated land cover changes due to the retrieval year, number, fractions and distributions of land cover classes by performing convection-permitting simulations driven by ERA5 reanalysis data over Germany from 2002 to 2011. The annual temperature bias of all the simulations compared with observations is larger than the differences between simulations. The land cover class fractional differences are small among the land cover maps. However, some land cover types, such as croplands and urban areas, have greatly changed over the years. These changes can be seen in the temperature differences. Simulations based on the CCI retrieved in 2000 and 2015 revealed no accreditable difference in the climate variables as the land cover changes that occurred between these years are marginal, and thus, the influence is small over Germany. Increasing the land cover types as in ECOCLIMAP leads to higher temperature variability. The largest differences among the simulations occur in maximum temperature and from spring to autumn, which is the main vegetation period. The temperature differences seen among the simulations relate to changes in the leaf area index, plant coverage, roughness length and latent heat fluxes due to differences in land cover types. The vegetation fraction was the main parameter affecting the seasonal evolution of the latent heat fluxes based on linear regression analysis, followed by roughness length and leaf area index. If the same natural vegetation or pasture grid cells changed into urban types in another land cover map, daily maximum temperatures changed accordingly. Similarly, differences in climate extreme indices are strongest for any land cover type change to urban areas. For future development, more attention should be given to land cover classification in complex areas, including more land cover types or single vegetation species and regional representative classification sample selection.