Tropical Rainfall Measuring Mission - 3 hours Level 3 product
Important update:this dataset is now superseded by GPM-IMERG.
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 at NCI
Directory structure is:
Available formats are hdf and netcdf4
3B42.<YYYYMMDD>.<HH>.<version>.HDF for example: 3B42.19980203.21.7.HDF
The files are in HDF4-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.
We are currently downloading the same version in netcdf format.
Each year has been concatenated in one file with the exclusion of the current year
which would be in the <year> subdirectory.