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.