Abstract:
Terrestrial water storage (mostly encompassing soil moisture, groundwater and snow) is a key climatic variable, which is relevant both for short-term and seasonal forecasting, as well as for long-term climate modeling. Despite its importance, it is not routinely measured and observations of its individual components are scarce. A possible approach for deriving estimates of this quantity is the use of water-balance computations based on the following three variables: moisture flux convergence, changes in atmospheric moisture content, and river runoff. This methodology was shown to give reliable results for various river basins of the northern mid-latitudes and to compare well with available ground observations. Here we compare estimates derived with this approach with offline simulations performed with the NASA Catchment Land Surface Model (hereafter Catchment model). These results are used to assess the potential gain in using water-balance estimates of terrestrial water-storage variations in a data assimilation framework.