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United States Department of Agriculture

Agricultural Research Service

Research Project: ENHANCING SATELLITE-BASED PRECIPITATION PRODUCTS USING REMOTELY-SENSED SOIL MOISTURE RETRIEVALS AND DATA ASSIMILATION TECHNIQUE

Location: Hydrology and Remote Sensing Laboratory

2012 Annual Report


1a.Objectives (from AD-416):
This project seeks to develop, test and implement a robust data assimilation system capable of correcting remotely-sensed precipitation inputs via the assimilation of remotely-sensed soil moisture retrievals into a land surface water balance model.


1b.Approach (from AD-416):
This project objective will be addressed in three phases:

1) Starting with a simple existing baseline system - based on a simple linear surface model modern and Kalman filtering – define and construct alternative systems based on more complex data assimilation and/or land surface modeling techniques. Potential data assimilation alternatives include the use of an Ensemble Kalman filter or Particle filtering techniques. Alternative land surface model techniques include the range of complex land surface models currently implemented within the NASA Land Information System.

2) Test the modified system using existing remote sensing datasets and evaluate the degree to which various systems are able to correct satellite-base precipitation to match aggregated rain gauge observations of short-term precipitation accumulations.

3) Prototype the identified system for the eventual availability of NASA Soil Moisture Active/Passive mission soil moisture measurements by running the system using L-band based soil moisture retrievals obtained from the European Space Agency (ESA) Soil Moisture/Ocean Salinity mission.


3.Progress Report:

This agreement seeks to develop, test, and implement a data assimilation system capable of correcting remotely-sensed precipitation inputs via the assimilation of remotely-sensed surface soil moisture retrievals into a land surface water balance model. Work is proceeding according to three primary objectives:

Objective #1: Starting with the baseline system, construct and evaluate alternative precipitation accumulation correction schemes based on more complex data assimilation and/or land surface modeling techniques.

Objective #2: Apply this new system (obtained following Objective.
1)to create a multi-year time series of corrected satellite-based precipitation products using available satellite-based surface soil moisture retrievals.

Objective #3: Prototype the system for its eventual application to the NASA Soil Moisture Active/Passive (SMAP) mission and Global Precipitation Mission (GPM).

All technical objectives are currently on schedule for completion within required time frames. Objective #1 has been completed and published in a peer-reviewed journal which formally defines the Soil Moisture Analysis Rainfall Tool (SMART) algorithm. The research required for Objective #2 is substantially complete. Using AMSR-E soil moisture retrievals, SMART has been applied to the correction of Tropical Rainfall Measuring Mission Multi-Satellite Precipitation Analysis (TMPA) 3B40RT, 3B42RT and 3B42 accumulation products (at a spatial resolution of 1-degree and temporal period of 3-days) from 2002 onwards. In order to complete work on Objective #3, we are currently adapting SMART to simultaneously incorporate both 45-km SMOS (L-band passive) and 25-km (Advanced Scatterometer) ASCAT (C-band active) soil moisture retrievals to correct 0.25 degree TMPA 3B40RT rainfall accumulation estimates. The resulting system will provide an excellent prototype for a GPM/SMAP compliant version of SMART. It will also address the key project objective of integrating Soil Moisture and Ocean Salinity (SMOS) soil moisture retrievals into SMART.


Last Modified: 8/29/2014
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