83rd Annual

Monday, 10 February 2003
Real-time multi-satellite precipitation estimation and assimilation
Mohan L. Nirala, NASA/GSFC, Greenbelt, MD; and P. Houser
Poster PDF (537.5 kB)

Global Land-surface Data Assimilation Scheme (GLDAS) integrates a wide variety of observation and modeling initiatives, and linked with NOAA and NASA land surface research programs. The objectives of this research are to develop high-resolution global precipitation using Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), Special Sensor Microwave/ Imager (SSM/I), Global Precipitation Measurement (GPM) Microwave Imager (GMI) data for GLDAS and to blend remote sensing observations of precipitation using data assimilation technique. The primary goal of this research is to study rainfall estimation improvements while GPM is making substantial improvements in precipitation observations, specifically in terms of measurement accuracy, sampling frequency, Earth coverage, and spatial resolution. This paper addresses questions related to the transition from current to future global precipitation observations as denoted by the TRMM and GPM eras, respectively. 3-hour and 6-hour average rain rate derived from microwave instruments provides valuable pattern information, which is useful to improve global analysis. Active and passive microwave precipitation data used in this study can significantly improve the quality of global datasets for climate analysis and forecasting applications. 3-hourly estimates using geo-IR calibration and merging techniques are susceptible to significant uncertainties. In general, geo-IR calibration and merging techniques possess bias and precision uncertainties for 3-hour estimates exceeding 20 percent and 50 percent, respectively, with little room to improve because there are no meaningful physics tools to exploit in making the estimates.

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