Assessing evapotranspiration dynamics across central Europe in the context of land-atmosphere drivers

Abstract. Evapotranspiration (ET) is an important variable for analysing ecosystems, biophysical processes, and drought-related changes in the soil-plant-atmosphere system. In this study, we evaluated freely available ET products from satellite remote sensing (i.e., MODIS, SEVIRI, and GLEAM) as well as modelling and reanalysis (i.e., ERA5-land and GLDAS-2) together with in-situ observations at eight Integrated Carbon Observation System (ICOS) stations across central Europe between 2017 and 2020. The land cover at the selected ICOS stations ranged from deciduous broad-leaved, evergreen needle-leaved, and mixed forests to agriculture. Trends in ET were analysed together with soil moisture (SM) and water vapor pressure deficit (VPD) during four years including a severe summer drought in 2018, but contrasting wet conditions in 2017. The analyses revealed the increased atmospheric aridity and decreased water supply for plant transpiration under drought conditions, showing that ET was generally lower and VPD higher in 2018 compared to 2017. Across the study period, results indicate that during moisture limited drought years, ET is strongly decreasing due to decreasing SM and increasing VPD. However, during normal or rather wet years, when SM is not limited, ET is mainly controlled by VPD, and hence, the atmospheric demand.

The comparison of the different ET products based on time series, statistics, and extended triple collocation (ETC) shows in general a good agreement with ETC correlations between 0.39 and 0.99 as well as root-mean-square errors lower than 1.07 mm/day. The greatest deviations are found at the agricultural-managed sites Selhausen (Germany) and Bilos (France), with the former also showing the highest potential dependencies (error cross-correlation) between the ET products. Our results indicate that ET products differ most at stations with spatio-temporal varying land cover conditions (varying crops over growing periods and between seasons). This complex heterogeneity complicates the estimation of ET, while ET products agree at evergreen needle-leaved stations with less temporal changes throughout the year and between years. The ET products from SEVIRI, ERA5-land, and GLEAM performed best when compared to ICOS observations with either lowest errors or highest correlations.