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Description

TMPA (3B42) dataset have been discontinued as of Dec. 31, 2019, and users are strongly encouraged to shift to the successor IMERG dataset (doi: 10.5067/GPM/IMERG/3B-HH/06).

This dataset was the output from the TMPA (TRMM Multi-satellite Precipitation Analysis) Algorithm. It 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 granule temporal coverage is 3 hours.

Product Summary

Platforms
TMPA
Instruments
NOT APPLICABLE
Projects
TRMM
Spatial Extent

N: 50 S: -50 E: 180 W: -180

Spatial Resolution
0.25 Decimal Degrees x 0.25 Decimal Degrees
Location
TROPICS
Coordinate System
CARTESIAN
Granule Spatial Representation
CARTESIAN
Temporal Extent
1997-12-31 to 2019-12-31
Data Partner
Goddard Earth Sciences Data and Information Services Center (formerly Goddard DAAC), Terrestrial Information Systems Laboratory, Earth Sciences Division, Science and Exploration Directorate, Goddard Space Flight Center, NASA (NASA/GSFC/SED/ESD/TISL/GESDI
Concept ID
C1281704371-GES_DISC
Data State
COMPLETE
Number of Files/Granules
64280
Processing Level
3
Published
Updated
Science Keywords
Total Surface Precipitation Rate

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.

Copy Citation

Precipitation Processing System (PPS) at Goddard Space Flight Center. (2018). TRMM (TMPA) Rainfall Estimate L3 3 hour 0.25 degree x 0.25 degree V7 [Data set]. NASA Goddard Earth Sciences Data and Information Services Center. https://doi.org/10.5067/TRMM/TMPA/3H/7 Date Accessed: 2026-06-08

Documents

Publications Citing This Dataset

Filters
Title Year Author Topic
A Dual-TransUNet Deep Learning Framework for Multi-Source Precipitation Merging and Improving Seasonal and Extreme Estimates Ye, Yuchen, Qi, Zixuan, Li, Shixuan, Qi, Wei, Cai, Yanpeng, Yuan, Chaoxia Total Surface Precipitation Rate
A Comprehensive review of global precipitation Products: Availability and application for flood inundation mapping Nikam, Vikrant, Patil, Mangal, Wandre, Sarika, Nikam, Bhaskar, Nandgude, Sachin, Ghatge, Jayant Total Surface Precipitation Rate
A hybrid machine learning model for flood prediction with recursive feature elimination informed by training performance Gong, Liying, Woo, Wai Lok, Wu, Yue Ivan, Zheng, Xiujuan RADAR IMAGERY, Terrain Elevation, Topographical Relief Maps, Digital Elevation/Terrain Model (DEM), Land Use/Land Cover Classification, Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain, Total Surface Precipitation Rate
Are urban impacts on heavy rainfall amplified in mountainous regions? Urdiales-Flores, Diego, Koukoula, Marika, Prein, Andreas F, Jan de Vries, Andries, Mariethoz, Gregoire, Bendix, Jorg, Dominguez, Francina, Celleri, Rolando, Peleg, Nadav Total Surface Precipitation Rate
Artificial neural network-based forecasting of SPI for extreme event analysis in the Upper Sao Francisco sub-basin Santos, Celso Augusto Guimaraes, de Medeiros Miranda, Vanessa Negreiros, Brasil Neto, Reginaldo Moura, de Farias, Camilo Allyson Simoes, da Silva, Richarde Marques Total Surface Precipitation Rate
Biased Aerosol Wet Deposition CAM5 Simulations: A Result of Misrepresented Convective-Stratiform Precipitation Partitioning When Benchmarked Against SPCAM Xia, Wenwen, He, Yujun, Wang, Bin Total Surface Precipitation Rate
Clustering-based evaluation of satellite rain-fall products: A novel perspective Giarno, G, Sunusi, Nurtiti, Didiharyoni, D, Rais, Achmad, Muflihah, M, Pranoto, Bono, Rachmawardani, Agustina, Hariyanto, H, Syamsudin, Muhammad, Utomo, Bagus, Slamet, Irwan, Amri, Sayful Total Surface Precipitation Rate
Integrated Spatio-Hydrological Modeling for Hydro-Power Management in North East India Kurbah, Shanbor, Barman, Diganta, Arjun, B. M., Das, Ranjit Total Surface Precipitation Rate, Cloud Liquid Water/Ice, Precipitation Amount, Precipitation Rate
Mean biases dominate CMIP6 model deficiencies in simulating heavy rainfall during monsoon intraseasonal oscillation Shi, Qingjian, Qin, Jianhuang, Li, Baosheng Total Surface Precipitation Rate
Limitations of satellite precipitation products in capturing extreme precipitation events: An object-based evaluation over China Gu, Hongji, Shen, Dingtao, Chen, Jinming, Zhang, Chunxiao, Xiao, Shuting, Yu, Fei Total Surface Precipitation Rate
Low level jet controlled dynamical and thermodynamical regimes of the diurnal cycle of rainfall over the western ghats Utkarsh, Verma, Pokhrel, Samir, Sahoo, Patita Kalyana, Choudhury, B Abida, Yashas, Shivamurthy, Chaudhari, Hemantkumar S, Konwar, Mahen, Saha, Subodh K Total Surface Precipitation Rate
Integrating CHIRPS rainfall and FJ Mock model for inflow estimation and water availability analysis in reservoir Febrianti, D T, Bisri, M, Sisinggih, D, Aina, C Total Surface Precipitation Rate
Iron isotope insights into equatorial Pacific biogeochemistry Camin, Capucine, Labatut, Marie, Pradoux, Catherine, Murray, James W., Lacan, Francois Total Surface Precipitation Rate
Improvement of Google Earth Engine-Based Multi-satellite Rainfall Estimation using Rain Gauge Data in South Sulawesi Ismail, Prayoga, Jatmiko, Retnadi Heru, Farda, Nur Mohammad, Munandar, Muhammad Arif Total Surface Precipitation Rate, Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain
Improving thermodynamic nudging in the E3SM Atmosphere Model version 2 (EAMv2): strategy and hindcast skills on weather systems Zhang, Shixuan, Leung, L. Ruby, Harrop, Bryce E., Bora, Aniruddha, Karniadakis, George, Shukla, Khemraj, Zhang, Kai Total Surface Precipitation Rate
Comparative Assessment of IMD and CHIRPS Rainfall Products over Southern Peninsular India: A Multi-Scale Validation Study (2001-2020) Tanakanti, Vijaya Markandeya, Bharghavi, Kandula, Lokeswara Reddy, Thotli, Krishna Reddy, Krishnareddigari Total Surface Precipitation Rate
Evaluating and enhancing the performance of satellite precipitation products by considering uncertainty in rain gauge observations Wei, Tai, Zhong, Xian-Ci, Gao, Yang Total Surface Precipitation Rate
Decadal precipitation variability and atmospheric brown cloud effects: a multi-platform assessment over the Indian subcontinent Jangid, Manish, Dass, Avinash 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 1.0), PARTICULATE MATTER (PM 10), Atmospheric Radiation, Longwave Radiation, Shortwave Radiation, Radiative Flux, Radiative Forcing, Surface Radiative Properties, Albedo, Emissivity, Cloud Properties, Cloud Fraction, Cloud Optical Depth/Thickness, Skin Temperature, Skin Temperature, Sea Surface Skin Temperature
Does vertical wind shear increase tropical cyclone rain? Lau, King Heng, Toumi, Ralf Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain, Total Surface Precipitation Rate
Enhancing Satellite Precipitation Product Accuracy for Hydrological and Environmental Analysis in Semi-Arid Urban Regions Heir, A. Vaezi, Salehi, E., Zand, A. Daryabeigi, Bidhendi, G. Nabi Total Surface Precipitation Rate
GIS-integrated 2D HEC-RAS modeling approach for assessing dam-break floods and their socio-economic consequences in urban arid environment Khan, Mohd Yawar Ali, ElKashouty, Mohamed, Refadah, Samyah Salem Total Surface Precipitation Rate
Extreme rainfall, flooding and malaria in the Sahara: outbreak analysis in Kidal, Mali 2024 Dolo, A. M., Cissoko, M., Teme, A., Keita, K., Sanogo, M., Traore, C. A. T., Magassa, M., Kone, A., Roy, F. A., Sagara, I., Gaudart, J. Total Surface Precipitation Rate
Event-Based Verification of IMERG Precipitation Estimates over Complex Terrain in the Southern Appalachian Mountains Major, Dylan, Prat, Olivier P., Nelson, Brian R., Miller, Douglas K., Petkovic, Veljko, Arulraj, Malarvizhi, Ferraro, Ralph Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain, Total Surface Precipitation Rate
Extreme Hydrological Events and Land Cover Impacts on Water Resources in Haiti: Remote Sensing and Modeling Tools Can Improve Adaptation Planning Joseph, Jeldane, Chatterjee, Suranjana, Molnar, Joseph J., ODonnell, Frances Total Surface Precipitation Rate, Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain
Evaluation of long-term multiple satellite precipitation products under different climatic regions over Taiwan Sathianarayanan, Manikandan, Hsu, Pai-Hui Total Surface Precipitation Rate
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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 Description Units Data Type Fill Value Valid Range Scale Factor Offset
Grid/HQprecipitation Grid/HQprecipitation mm/hr float32 -9999.900390625 N/A N/A N/A
Grid/IRprecipitation Grid/IRprecipitation mm/hr float32 N/A N/A N/A N/A
Grid/precipitation Grid/precipitation mm/hr float32 N/A N/A N/A N/A
Grid/relativeError Grid/relativeError mm/hr float32 N/A N/A N/A N/A
Grid/satObservationTime Grid/satObservationTime minutes int8 N/A N/A N/A N/A
Grid/satPrecipitationSource Grid/satPrecipitationSource N/A int16 N/A N/A N/A N/A
nlat nlat degrees_north float32 N/A N/A N/A N/A
nlon nlon degrees_east float32 N/A N/A N/A N/A
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