TRMM-TMPA is a 3 hours Level 3 product from the Tropical Rainfall Measuring Mission (TRMM 3B42) providing a rainfall estimate.
This dataset is the output from the TMPA (TRMM Multi-satellite Precipitation) Algorithm, and provides precipitation estimates in the TRMM regions that have the (nearly-zero) bias of the ”TRMM Combined Instrument” precipitation estimate and the dense sampling of high-quality microwave data with fill-in using microwave-calibrated infrared estimates. The spatial resolution is 0.25ºx0.25º latitude--longitude (on a Cylindrical Equal Distance grid) , covering -180E to 180W and -50S to 50N degrees. Current version is V7 and the dataset is published by Goddard Earth Sciences Data and Information Services Center (GES DISC). A summary for the dataset is available on the GESC DISC website A full technical description of this and other TRMM products can be found in the Real-Time TRMM Multi-Satellite Precipitation Analysis Data Set documentation. From this document: "... *3B42RT* is the official PPS identifier of the HQ+VAR data set. The identifier indicates that it is a level 3 (gridded) product with input from multiple sensors ("B") using non-TRMM data ("40"-series), running in Real Time. The *units of the TMPA-RT estimates* as stored in the data files is 0.01 mm/h for both precipitation and random error. To recover the original floating-point values in mm/h, divide by 100. The precipitation values are based on satellite snapshots. ... The *period of record* for the TMPA-RT is 1 March 2000 through the present. The start is based on the start of the CPC merged 4 Km IR Tb data set. In contrast, the Version 7 TRMM product 3B42 provides after-real-time processing of the TMPA from 1 January 1998 to the delayed present. ..."
TRMM 3B42 on raijin
Directory structure is: /g/data1/ua8/NASA_TRMM/TRMM_L3/TRMM_3B42/<YEAR>/<files> Data format is HDF-EOS and filenames are
3B42.<YYYYMMDD>.<HH>.<version>.HDF for example: 3B42.19980203.21.7.HDF
The files are in HDF-EOS format. To access this dataset using python you need to use the pyhdf module, other hdf modules cannot deal with the HDF-EOS format.
We are using the CRC32 checksum to check the files integrity, the script to download, update and check the files is available in the CMS github:
Usually new files are produced with a 3 months delay from the current date.