Comparing Temporal Dynamics of Soil Moisture from Remote Sensing, Modeling, and Field Observations across Europe

Abstract

This study evaluates temporal variability and algorithm differences in soil moisture estimates over Europe using the European Center for Medium-range Weather Forecasts (ECMWF) operational analysis and the passive Soil Moisture Active Passive (SMAP) soil moisture product. While models and satellite retrievals have improved in capturing the timing of soil moisture dynamics, absolute accuracy and temporal variability magnitudes still diverge. This study compares the representation of short-term and seasonal variability of soil moisture in absolute and normalized terms over two different hydrometeorological growing periods (2021 and 2022). Both datasets exhibit intermediate to high temporal correlations with in situ measurements at selected stations (median Pearson correlation coefficients of all stations range between 0.65 and 0.79), confirming previous studies. However, they overestimate the magnitude of absolute soil moisture variability at most stations (median interquartile range of all stations at 0.085 (0.10) m3m−3 for ECMWF and 0.072 (0.079) m3m−3 for SMAP opposed to 0.063 (0.072) m3m−3 for in situ in 2021 (2022)) due to an overestimation of short-term fluctuations, especially at dry stations in southern France and Eastern Europe. The soil wetness index is underestimated, particularly within SMAP estimates. The performance of both is sensitive to hydrometeorological conditions, with the 2022 European drought causing strong seasonal and weak short-term fluctuations. This is easier to capture than conditions with pronounced short-term and weaker seasonal fluctuations, as in 2021. Overall, SMAP and ECMWF time series show considerable coincident timing, whereas the magnitude of temporal variability and accuracy depend on site-specific characteristics and the pre-processing of the data.