N: 60 S: -60 E: 180 W: -180
Description
TMPA (3B42RT) dataset have been discontinued as of Dec. 31, 2019, and users are strongly encouraged to shift to the successor IMERG datasets (doi: 10.5067/GPM/IMERG/3B-HH-E/06, 10.5067/GPM/IMERG/3B-HH-L/06).
These data were output from the TRMM Multi-satellite Precipitation Analysis (TMPA), the Near Real-Time (RT) processing stream. The latency was about seven hours from the observation time, although processing issues may delay or prevent this schedule. Users should be mindful that the price for the short latency of these data is the reduced quality as compared to the research quality product.
Each file is a snapshot considered to represent the three-hour period centered on the "nominal" file time. So, e.g., 00 UTC nominally represents the period from 2230 UTC of the previous day to 0130 UTC of the current day. Estimates outside the band 50 degree N-S are considered highly experimental.
GES DISC initially receives these data from the Precipitation Processing System (PPS) in binary format. However, before archiving, the data are scaled to real numbers, and re-arranged to a standard grid so that the first grid cell is at 180W, 60S. Thus formatted, data are stored into CF-1.6 compliant netCDF-4 files and archived. This format is machine-independent, self-explanatory, provides extremely efficient seamless compression, and gives various options for previewing the data without downloading it.
Apart from these technical differences, all other science content details remain the same, and users are strongly encouraged to read the provider's documentation that is linked to from here.
Product Summary
Citation
Citation is critically important for dataset documentation and discovery. This dataset is openly shared, without restriction, in accordance with the EOSDIS Data Use and Citation Guidance.
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Documents
READ-ME
GENERAL DOCUMENTATION
| Title | Year Sort ascending | Author | Topic |
|---|---|---|---|
| Mass deposition of microbes from wildfire smoke to the sea surface | Yue, Siyao, Cheng, Yafang, Zheng, Lishan, Lai, Senchao, Wang, Shan, Song, Tianli, Li, Linjie, Li, Ping, Zhu, Jialei, Li, Meng, Wei, Lianfang, Ma, Chaoqun, Jin, Rui, Zhang, Yingyi, Sun, Yele, Wang, Zifa, Kawamura, Kimitaka, Liu, CongQiang, Su, Hang, Andreae, Meinrat O., Fu, Pingqing | Total Surface Precipitation Rate | |
| An extraordinary chlorophyll-a enhancement event jointly induced by two | Zheng, Hui, Zhang, Wen-Zhou | Total Surface Precipitation Rate | |
| Sensitivity of precipitation in the highlands and lowlands of Peru to physics parameterization options in WRFV3. 8.1 | Gonzalez-Roji, Santos J., Messmer, Martina, Raible, Christoph C., Stocker, Thomas F. | Total Surface Precipitation Rate, Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Sensitivity of precipitation and temperature over the Mount Kenya area to physics parameterization options in a high-resolution model simulation performed ... | Messmer, Martina, Gonzalez-Roji, Santos J., Raible, Christoph C., Stocker, Thomas F. | Total Surface Precipitation Rate, Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Atmospheric measurements in the context of protection and conservation of cultural heritage objects | Rosu, Adrian, Constantin, Daniel-Eduard, Arseni, Maxim, Timofti, Mihaela | Atmospheric Ozone, Total Surface Precipitation Rate, Aerosols, Aerosol Extinction, Aerosol Optical Depth/Thickness, Angstrom Exponent, Aerosol Particle Properties, Carbonaceous Aerosols, Dust/Ash/Smoke, Organic Particles, Sulfate Particles, Sulfur Oxides, Sulfur Compounds, Sulfate, Sulfur Dioxide, Sulfur Oxides, Particulate Matter, Dimethyl Sulfide, Black Carbon, Sea Salt, PARTICULATE MATTER (PM 2.5), PARTICULATE MATTER (PM 10), PARTICULATE MATTER (PM 1.0), Nitrogen Dioxide, Ultraviolet Radiation | |
| Dependence of tropical cyclone damage on maximum wind speed and socioeconomic factors | Ye, Mengqi, Wu, Jidong, Liu, Wenhui, He, Xin, Wang, Cailin | Total Surface Precipitation Rate | |
| Which rainfall score is more informative about the performance in river discharge simulation? A comprehensive assessment on 1318 basins over Europe | Camici, Stefania, Massari, Christian, Ciabatta, Luca, Marchesini, Ivan, Brocca, Luca | Total Surface Precipitation Rate | |
| A susceptibility-based rainfall threshold approach for landslide occurrence | Monsieurs, Elise, Dewitte, Olivier, Demoulin, Alain | Total Surface Precipitation Rate | |
| Causes and triggers of deep-seated hillslope instability in the tropicsInsights from a 60-year record of Ikoma landslide (DR Congo) | Dille, Antoine, Kervyn, Francois, Mugaruka Bibentyo, Toussaint, Delvaux, Damien, Ganza, Gloire Bamulezi, Ilombe Mawe, Guy, Kalikone Buzera, Christian, Safari Nakito, Evelyne, Moeyersons, Jan, Monsieurs, Elise, Nzolang, Charles, Smets, Benoit, Kervyn, Matthieu, Dewitte, Olivier | Total Surface Precipitation Rate | |
| Historical and future changes in asset value and GDP in areas exposed to tropical cyclones in China | Ye, Mengqi, Wu, Jidong, Wang, Cailin, He, Xin | Total Surface Precipitation Rate |
Variables
The table below lists the variables contained within a single granule for this dataset. Variables often contain observed or derived geophysical measurements collected from a variety of sources, including remote sensing instruments on satellite and airborne platforms, field campaigns, in situ measurements, and model outputs. The terms variable, parameter, scientific data set, layer, and band have been used across NASA’s Earth science disciplines; however, variable is the designated nomenclature in NASA’s Common Metadata Repository (CMR). Variable metadata attributes such as Name, Description, Units, Data Type, Fill Value, Valid Range, and Scale Factor allow users to efficiently process and analyze the data. The full range of attributes may not be applicable to all variables. Additional information on variable attributes is typically available in the data, user guide, and/or other product documentation.
For questions on a specific variable, please use the Earthdata Forum.
| Name Sort descending | Description | Units | Data Type | Fill Value | Valid Range | Scale Factor | Offset |
|---|---|---|---|---|---|---|---|
| lat | lat | degrees_north | float32 | N/A | N/A | N/A | N/A |
| lon | lon | degrees_east | float32 | N/A | N/A | N/A | N/A |
| precipitation | precipitation | mm/hr | float32 | -99999 | N/A | N/A | N/A |
| precipitation_error | precipitation_error | mm/hr | float32 | -99999 | N/A | N/A | N/A |
| source | source | Index Value | int16 | N/A | N/A | N/A | N/A |
| uncal_precipitation | uncal_precipitation | mm/hr | float32 | -99999 | N/A | N/A | N/A |