Download the paper:

Note: Full text may not be available for papers that have not yet been published.


Crow, W. T., F. Chen, R. H. Reichle, and Q. Liu:
"L band microwave remote sensing and land data assimilation improve the representation of prestorm soil moisture conditions for hydrologic forecasting"
Geophysical Research Letters, 44, 5495-5503, doi:10.1002/2017GL073642, 2017.

Abstract:
Recent advances in remote sensing and land data assimilation purport to improve the quality of antecedent soil moisture information available for operational hydrologic forecasting. We objectively validate this claim by calculating the strength of the relationship between storm-scale runoff ratio (i.e., total streamflow divided by total rainfall accumulation in depth units) and prestorm surface soil moisture estimates from a range of surface soil moisture data products. Results demonstrate that both satellite-based, L band microwave radiometry and the application of land data assimilation techniques have significantly improved the utility of surface soil moisture data sets for forecasting streamflow response to future rainfall events.


Home

NASA-GSFC / GMAO / Rolf Reichle