Abstract:
Soil moisture is an important component of the terrestrial water cycle and a key land surface variable in the global weather and climate system. Global estimates of surface soil moisture can be inferred from satellite-based low frequency passive microwave observations, such as collected by, for example, the current the Soil Moisture Ocean Salinity (SMOS) mission and the Soil Moisture Active Passive (SMAP) mission. However, the utility of spaceborne radiometry is constrained by the limited vertical penetration depth, the coarse spatial resolution, the indirect connection to relevant land surface variables and the intermittent nature of the measurements. The assimilation of passive microwave measurements into land surface models has potential to add value to these satellite data by (i) increasing the effective vertical penetration depth though propagation of surface information to the root-zone, (ii) increasing the spatial resolution through dynamic downscaling, (iii) increasing the spatial and temporal coverage by interpolation and extrapolation to unobserved times and locations and (iv) providing enhanced and consistent estimates of various land surface state and flux estimates. The talk will discuss the assimilation of global SMOS and SMAP (separately) brightness temperature observations into the Goddard Earth Observing System version 5 (GEOS-5) Catchment land surface model. Special attention will be devoted to the operational SMAP level 4 soil moisture (L4_SM) product, a data assimilation product specifically aimed at providing globally consistent root-zone soil moisture and other geophysical land surface variables.