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Abstract:
The GRACE satellites provide signals of total terrestrial water storage (TWS) variations over large spatial domains at seasonal to inter-annual time scales. While the GRACE data have been extensively and successfully used to assess spatio-temporal changes in TWS, little effort has been made to quantify the relative contributions of snow pack, soil moisture and other components to the integrated TWS signal across northern latitudes, which is essential to gain a better insight into the underlying hydrological processes. Therefore, this study aims to assess which storage component dominates the spatio-temporal patterns of TWS variations in the humid regions of northern mid-to-high latitudes.
To do so, we constrained a rather parsimonious hydrological model with multiple state-of-the-art Earth observation products including GRACE TWS anomalies, estimates of snow water equivalent, evapotranspiration fluxes, and gridded runoff estimates. The optimized model demonstrates good agreement with observed hydrological patterns, and was used to assess the relative contributions of solid (snow pack) versus liquid (soil moisture, retained water) storage components to total TWS variations. In particular, we analysed whether the same storage component dominates TWS variations at seasonal and inter-annual temporal scales, and whether the dominating component is consistent across small to large spatial scales.
Consistent with previous studies, we show that snow dynamics control seasonal TWS variations across spatial scales in the northern mid-to-high latitudes. In contrast, we find that inter-annual variations of TWS are dominated by liquid water storages, comprising mainly of soil moisture. However, as the spatial domain over which the storages are averaged becomes larger, the relative contribution of snow to inter-annual TWS variations increases. This is due to a stronger spatial coherence of snow anomalies as opposed to spatially more heterogeneous liquid water anomalies that cancel out over large spatial domains.
The findings first highlight the effectiveness of our model-data fusion approach that jointly interprets multiple Earth observation data streams with a simple model. Secondly, they reveal that the determinants of TWS variations in snow-affected northern latitudes are scale dependent. We conclude that inferred driving mechanisms of TWS cannot simply be transferred from one scale to another, which is of particular relevance for understanding the short and long-term variability of water resources.
