Abstract:
The NASA Goddard Earth Observing System (GEOS) is a modeling and data assimilation framework for generating global Earth system data products, including weather analysis and forecast data, climate reanalysis datasets such as the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), and land-only datasets such as the NASA Soil Moisture Active Passive (SMAP) mission Level-4 Soil Moisture (L4_SM) data assimilation product. To reduce the impact of errors in the model parameters and parameterizations on the simulated soil moisture and snow mass, MERRA-2 ingests precipitation observations, and L4_SM additionally assimilates SMAP brightness temperatures observations. The beneficial impact of these precipitation and soil moisture observations on the quality of the simulated land surface water cycle variables has been documented in the literature.

Recently, we expanded the GEOS framework with the assimilation of (i) soil moisture retrievals from the Advanced Scatterometer (ASCAT) and (ii) observations of snow cover area fraction (SCF) from the Moderate Resolution Imaging Spectroradiometer (MODIS).

The assimilation of MODIS SCF observations in a land-only version of the system reduced errors in snow mass and snow depth by up to ~10% when validated against in situ measurements from the Snow Telemetry (SNOTEL), Canadian historical Snow Water Equivalent dataset (CanSWE), and Global Historical Climatology Network - Daily (GHCN-Daily) networks. Additionally, the SCF assimilation improved the surface albedo.

The assimilation of ASCAT soil moisture retrievals reduced errors in soil moisture only when the land surface was forced with simulated precipitation (as in the GEOS weather analysis and forecasts). When precipitation observations are used to force the land surface (as in MERRA-2 and L4_SM), the impact of the ASCAT soil moisture retrieval assimilation becomes neutral.

Finally, assimilating ASCAT soil moisture retrievals and SMAP brightness temperature observations in a joint soil moisture analysis often yields ASCAT-based analysis increments that are followed by SMAP-based analysis increments of the opposite sign, and vice versa. That is, the soil moisture analysis increments based on the two types of observations conflict with each other. As a result, the assimilation estimates from the joint analysis of ASCAT and SMAP observations exhibits lower skill than when only SMAP observations are assimilated.

This presentation provides an update on the aforementioned developments.