N: 50 S: -50 E: 180 W: -180
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
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
Publications Citing This Dataset
| Title | Year Sort ascending | Author | Topic |
|---|---|---|---|
| Does vertical wind shear increase tropical cyclone rain? | Lau, King Heng, Toumi, Ralf | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain, Total Surface Precipitation Rate | |
| Multiday precipitation extremes are projected to become less likely in southern Pakistan | Dollan, Ishrat J., Maggioni, Viviana, Araujo, Diogo, Bhuiyan, Soelem Aafnan, Nair, Anju Vijayan, Nikolopoulos, Efthymios I. | Air Temperature, Precipitation Amount, Atmospheric Water Vapor, Precipitation, 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 | |
| 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 | |
| The impact of Aeolus observations on wind and rainfall predictions | Borne, Maurus, Knippertz, Peter, Rennie, Michael, Weissmann, Martin | Total Surface Precipitation Rate | |
| Understanding Climate Dynamics in Three Cities of Uttarakhand at Different Altitudes Using GEE and Nonparametric Methods | Dhir, Hazel, Sablania, Saraansh, Bisaria, Jigyasa | 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 | |
| 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 | |
| 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 | |
| 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 | |
| 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 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 | |
| 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 | |
| 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 | |
| Comparison and evolution of satellite-based precipitation product for flood-prone Kunhar River basin, KPK, Pakistan | Shazaib shakeel, Dr.Mustajab Ali, Usman Ali, Hamid Mumtaz, Toseeq Tahir, Amman Abbas | 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 | |
| Evaluation of long-term multiple satellite precipitation products under different climatic regions over Taiwan | Sathianarayanan, Manikandan, Hsu, Pai-Hui | 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 | |
| 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 | |
| Prior weight dilution in Bayesian model averaging for groundwater | Hu, Haoxin, Zeng, Xiankui, Wu, Jichun, Wang, Dong | Snow Cover, 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 | |
| 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 | |
| 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 | |
| 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 |
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 |
|---|---|---|---|---|---|---|---|
| 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 |