The Spatial Scale of Model Errors and Assimilated Retrievals in a Terrestrial Water Storage Assimilation System

A twin experiment was conducted assimilating synthetic retrievals of basin-scale terrestrial water storage (TWS) in the Mackenzie River basin located in northwestern Canada. The synthetic “truth” was generated using the NASA Catchment land surface model (Catchment) forced by meteorological fields from the Modern-Era Retrospective Reanalysis for Applications (MERRA). Synthetic retrievals of TWS were computed from the truth and then corrupted with a prescribed amount of error. Designed errors in the modeling system (relative to the truth) were introduced via application of meteorological forcing fields from the Global Land Data Assimilation System (GLDAS). A total of 16 experiments were conducted over a 9-year study period. Each experiment used a different combination of (i) horizontal model error correlation length (used for the perturbation of model forcing and prognostic variables) and (ii) spatial scale of the assimilated TWS retrievals. In general, assimilation of the finest scale TWS retrievals yielded the best agreement relative to the truth even though the finest scale retrievals contained the greatest amount of error. Greater improvement in TWS and snow water equivalent, in general, was witnessed as the horizontal model error correlation length increased. The same, however, could not be said for the subsurface state estimates nor for the evaporative and runoff fluxes. As the scale of the assimilated TWS retrieval decreased, more mass was effectively transferred from snow water equivalent into the subsurface thereby dampening the hydrologic runoff response in the study area. As the horizontal model error correlation length scale increased, the magnitude of the analysis increments increased (i.e., temporal variability increased) but the temporally-averaged analysis increment over the course of the 9-year study period remained unchanged. In general, TWS retrievals should be assimilated at the smallest spatial scale that may be sufficiently resolved while the specification of horizontal error correlation length scale is of secondary importance. These findings have implications for land data assimilation systems that extract information from satellite-based TWS retrievals such as the Gravity Recovery and Climate Experiment (GRACE) for the purpose of improving regional- and continental-scale freshwater resource characterization.