Day 1 for the Integrated Multi-Satellite Retrievals for GPM (IMERG) Data Sets

Tuesday, 16 December 2014: 4:00 PM
George John Huffman, NASA Goddard Space Flight Center, Greenbelt, MD, United States, David T Bolvin, Science Systems and Applications, Inc., Lanham, MD, United States, Daniel Braithwaite, University of California Irvine, Irvine, CA, United States, Kuo-lin Hsu, UC Irvine, Irvine, CA, United States, Robert Joyce, NOAA/NCEP/CPC, Boca Raton, FL, United States, Christopher Kidd, Earth System Science Interdisciplinary Center, COLLEGE PARK, MD, United States, Soroosh Sorooshian, Univ California Irvine, Irvine, CA, United States and Pingping Xie, NOAA/NCEP, College Park, MD, United States
The Integrated Multi-satellitE Retrievals for GPM (IMERG) is designed to compute the best time series of (nearly) global precipitation from "all" precipitation-relevant satellites and global surface precipitation gauge analyses. IMERG was developed to use GPM Core Observatory data as a reference for the international constellation of satellites of opportunity that constitute the GPM virtual constellation. Computationally, IMERG is a unified U.S. algorithm drawing on strengths in the three contributing groups, whose previous work includes:

1) the TRMM Multi-satellite Precipitation Analysis (TMPA);

2) the CPC Morphing algorithm with Kalman Filtering (K-CMORPH); and

3) the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks using a Cloud Classification System (PERSIANN-CCS).

We review the IMERG design, development, testing, and current status. IMERG provides 0.1°x0.1° half-hourly data, and will be run at multiple times, providing successively more accurate estimates: 4 hours, 8 hours, and 2 months after observation time. In Day 1 the spatial extent is 60°N-S, for the period March 2014 to the present. In subsequent reprocessing the data will extend to fully global, covering the period 1998 to the present. Both the set of input data set retrievals and the IMERG system are substantially different than those used in previous U.S. products. The input passive microwave data are all being produced with GPROF2014, which is substantially upgraded compared to previous versions. For the first time, this includes microwave sounders. Accordingly, there is a strong need to carefully check the initial test data sets for performance. IMERG output will be illustrated using pre-operational test data, including the variety of supporting fields, such as the merged-microwave and infrared estimates, and the precipitation type. Finally, we will summarize the expected release of various output products, and the subsequent reprocessing sequence.