Skip to main content

Description

Version 07B is the current version of the IMERG data sets. Older versions will no longer be available and have been superseded by Version 07.

The Integrated Multi-satellitE Retrievals for GPM (IMERG) is the unified U.S. algorithm that provides the multi-satellite precipitation product for the U.S. GPM team.

The precipitation estimates from the various precipitation-relevant satellite passive microwave (PMW) sensors comprising the GPM constellation are computed using the 2021 version of the Goddard Profiling Algorithm (GPROF2021), then gridded, intercalibrated to the GPM Combined Ku Radar-Radiometer Algorithm (CORRA) product, and merged into half-hourly 0.1°x0.1° (roughly 10x10 km) fields. Note that CORRA is adjusted to the monthly Global Precipitation Climatology Project (GPCP) Satellite-Gauge (SG) product over high-latitude ocean to correct known biases.

The half-hourly intercalibrated merged PMW estimates are then input to both a Morphing-Kalman Filter (KF) Lagrangian time interpolation scheme based on work by the Climate Prediction Center (CPC) and the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) Dynamic Infrared–Rain Rate (PDIR) re-calibration scheme. In parallel, CPC assembles the zenith-angle-corrected, intercalibrated merged geo-IR fields and forwards them to PPS for input to the PERSIANN-CCS algorithm (supported by an asynchronous re-calibration cycle) which are then input to the KF morphing (quasi-Lagrangian time interpolation) scheme.

The KF morphing (supported by an asynchronous KF weights updating cycle) uses the PMW and IR estimates to create half-hourly estimates. Motion vectors for the morphing are computed by maximizing the pattern correlation of successive hours within each of the precipitation (PRECTOT), total precipitable liquid water (TQL), and vertically integrated vapor (TQV) data fields provided by the Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) and Goddard Earth Observing System model Version 5 (GEOS-5) Forward Processing (FP) for the post-real-time (Final) Run and the near-real-time (Early and Late) Runs, respectively. The vectors from PRECTOT are chosen if available, else from TQL, if available, else from TQV. The KF uses the morphed data as the “forecast” and the IR estimates as the “observations”, with weighting that depends on the time interval(s) away from the microwave overpass time. The IR becomes important after about ±90 minutes away from the overpass time. Variable averaging in the KF is accounted for in a routine (Scheme for Histogram Adjustment with Ranked Precipitation Estimates in the Neighborhood, or SHARPEN) that compares the local histogram of KF morphed precipitation to the local histogram of forward- and backward-morphed microwave data and the IR.

The IMERG system is run twice in near-real time:

"Early" multi-satellite product ~4 hr after observation time using only forward morphing and
"Late" multi-satellite product ~14 hr after observation time, using both forward and backward morphing
and once after the monthly gauge analysis is received:

"Final", satellite-gauge product ~4 months after the observation month, using both forward and backward morphing and including monthly gauge analyses.

In V07, the near-real-time Early and Late half-hourly estimates have a monthly climatological concluding calibration based on averaging the concluding calibrations computed in the Final, while in the post-real-time Final Run the multi-satellite half-hourly estimates are adjusted so that they sum to the Final Run monthly satellite-gauge combination. In all cases the output contains multiple fields that provide information on the input data, selected intermediate fields, and estimation quality. In general, the complete calibrated precipitation, precipitation, is the data field of choice for most users.

Briefly describing the Final Run, the input precipitation estimates computed from the various satellite passive microwave sensors are intercalibrated to the CORRA product (because it is presumed to be the best snapshot TRMM/GPM estimate after adjustment to the monthly GPCP SG), then "forward/backward morphed" and combined with microwave precipitation-calibrated geo-IR fields, and adjusted with seasonal GPCP SG surface precipitation data to provide half-hourly and monthly precipitation estimates on a 0.1°x0.1° (roughly 10x10 km) grid over the globe. Precipitation phase is a diagnostic variable computed using analyses of surface temperature, humidity, and pressure. The current period of record is June 2000 to the present (delayed by about 4 months).

Product Summary

Platforms
IMERG
Instruments
NOT APPLICABLE
Spatial Extent

N: 90 S: -90 E: 180 W: -180

Location
GLOBAL ,
GLOBAL LAND ,
GLOBAL OCEAN
Coordinate System
CARTESIAN
Granule Spatial Representation
CARTESIAN
Temporal Extent
1998-01-01 to Present
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
C2723754847-GES_DISC
Data State
ACTIVE
Number of Files/Granules
486480
Processing Level
3
Published
Updated
Science Keywords
Precipitation ,
Precipitation Amount ,
Precipitation Rate ,
Snow ,
Rain

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 NASA GSFC. (2023). GPM IMERG Final Precipitation L3 Half Hourly 0.1 degree x 0.1 degree V07 [Data set]. NASA Goddard Earth Sciences Data and Information Services Center. https://doi.org/10.5067/GPM/IMERG/3B-HH/07 Date Accessed: 2026-05-03

Documents

SHOWING 1 OF 1

Publications Citing This Dataset

Filters
Title Year Author Topic
25-years study (20002024) of extreme precipitation following heatwaves in the Middle East: Regional patterns, trends, and atmospheric drivers Ghasemifar, Elham, Planche, Celine, Baray, Jean-Luc, Almazroui, Mansour, Rashid, Irfan Ur, Moradi, Sakine, Topuz, Muhammet Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain
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
Insuring Peace: Index-Based Livestock Insurance, Droughts, and Conflict Gehring, Kai, Schaudt, Paul Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain
Influences of Desert Afforestation on Boundary Layer Convergence Lines and Related Convection and Convective Precipitation Over Desert-oasis Border Wang, Xuelei, Meng, Zhiyong, Yu, Yan, Liu, Hongjun, Yi, Nana Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain
Impacts of cold surges on the synoptic changes of the western North Pacific anticyclone in winter Liu, Qian, Huang, Ling, Bai, Lanqiang, Chen, Guixing Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain
Does vertical wind shear increase tropical cyclone rain? Lau, King Heng, Toumi, Ralf Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain
Development of CAS-ESM_MMF: improving East Asian summer precipitation simulation with a Multiscale Modeling Framework Lin, Guangxing, Liao, Wei, Lin, Zhaohui, Zhang, He, Kou, Wenbin, Guo, Xiaojie, Xie, Zhenghui, Yang, Qiu, Wu, Chenglai, Zhang, Minghua Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain
Dynamics and thermodynamics of extreme rainfall event over different subregions of Himachal Pradesh during 810 July, 2023 Ancy, P., Babu, C. A., Varikoden, Hamza Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain
Evaluating the carbon benefits and economic efficiency of photovoltaic-green roof systems in China: A nationwide application analysis Yan, Qi, Yu, Jiao, Dong, Nannan Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain, Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI)
Evaluation of Atmospheric Models Over Mountainous Regions Using a Yang, Heng, Chen, Shuanglong, Bian, Qingyun, Zheng, Hui Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain
East Asian Meiyu variability reflected in precipitation oxygen isotopes via western Pacific subtropical high Li, Rong, Cai, Zhongyin, Yu, Xinyi, Wang, Cheng, Tian, Lide Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain
Evaluation of Precipitation Observations Across Ecuador IzaWong, Angela, Moldovan, Gabriel, Bouallegue, Zied Ben, Hemingway, Rebecca, Chantry, Matthew, Lavers, David A. Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain
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
High-resolution regional climate modeling over Myanmar using WRF: Historical validation and future projections under different shared socioeconomic pathways Messmer, Martina, Gonzalez-Roji, Santos J., Nay Chi, Mo Aung, Leonard, Sonia Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain
Hemispheric Synoptic Patterns Control Rainfall and Long-Range Aerosol Machado, Luiz A. T., Gan, Manoel A., Barbosa, Henrique M. J., Holanda, Bruna A., Pozzer, Andrea, Poschl, Ulrich, Pohlker, Christopher Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain, Aerosol Optical Depth/Thickness
How armed conflict shapes environmental trends in Yemen? Al-Yaari, Amen, Govind, Ajit Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain
Performance Evaluation of a Distributed Hydrological Model Using Satellite Data over the Lake Kastoria Catchment, Greece Papadimos, Dimitris, Papamichail, Dimitris Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain
Recent oceanic performance of GPM multisatellite precipitation estimates Wang, Yiding, Yong, Bin, Qi, Weiqing, Wen, Yixin Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain
A Synoptic-Scale Anticyclone Bridging Typhoon In-Fa (2021) and the Liu, Jiayi, Tao, Li, Wang, Yuqing Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain
Case study of aircraft icing in-cloud measurements and explicit Luo, Liping, Xue, Ming, Xu, Xin, Deng, Lin, Li, Junxia, Zhang, Rong Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain
Assessment of Groundwater Potential in North-Central Palawan using Remote Sensing and Geophysical Analysis of Fractured Basement Aquifers Cuevas, Joshua Godwin, Cari, John Esteban E., Principe, Jeark A., Tamondong, Ayin M., Dimalanta, Carla B., Armada, Leo T. Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain
Controls on lag time in Philippine catchments identified using rainfallrunoff modelling and a generalized additive model (GAM) Tolentino, Pamela Louise M., Hurst, Martin D., Williams, Richard D., Hoey, Trevor B., Boothroyd, Richard J. Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain
Operational Flood Forecasting System in Denmark Integrating Groundwater and Surface-water Liu, Jun, Koch, Julian, Stisen, Simon, Troldborg, Lars, Schneider, Raphael Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain
Revealing mechanism of phreatic eruptions derived by satellite-and Saepuloh, Asep, Ramadhan, Saiyidinal Futhra, Riawan, Edi, Abdillah, Muhammad Rais, Gumilar, Irwan, Ramdhan, Agus Mochamad, Purnamasari, Heruningtyas Desi, Ghiffari, Fattah, Sibarani, Axel Widjanarko, Tambunan, Ricky Nelson, da Costa, Janice Clementine, Nugraha, Dwina, Basuki, Ahmad, Kristianto Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain
Response of tropical cyclones to global warming: Super Typhoon Usagi in the Western Pacific Ocean Sun, Qi, Arnault, Joel, Holst, Christopher, Laux, Patrick, Kunstmann, Harald Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain
Surface Soil Moisture Drydown over the Tibetan Plateau from SMAP: Dong, Shiyu, Zhu, Zhongli, Zhang, Jinsong, Liu, Ziqi, Wu, Qingxia Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain
Tropical Cyclone Intensity Sensitivity to Sea Surface Temperature and Mixed Layer Depth Wellmeyer, Evan David, Ricchi, Antonio, Ferretti, Rossella Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain
Tropical cyclone rainfall extends inland Deng, E, Xiang, Qian, Ouyang, De-Hui, Chan, Kelvin T. F., He, Dengxin, Lin, Ning, Chan, Johnny C. L., Tu, Shifei, Chan, Pak-Wai, Liu, Zhizhao, Li, Guo-Zhi, Zhou, Shang-Qi, Dong, Yue, Ni, Yi-Qing Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain
A Diagnosis of Oceanic Precipitation in IMERG-GMI Watters, Daniel C., Huffman, George J., Gatlin, Patrick N., Kirstetter, Pierre-Emmanuel, Bolvin, David T., Joyce, Robert, Nelkin, Eric J., Tan, Jackson, Wolff, David B. Atmospheric Water Vapor, Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain
20 Years of MCSs simulations over South America using a convection-permitting model Rehbein, Amanda, Prein, Andreas F., Ambrizzi, Tercio, Ikeda, Kyoko, Liu, Changhai, Rasmussen, Roy M. Precipitation, Brightness Temperature, Precipitation Amount, Precipitation Rate, Snow, Rain
A climatology and lifecycle characteristics of atmospheric fronts and their associated precipitation Landy, John, Reed, Kevin A., Rhoades, Alan M., Ullrich, Paul A. Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain
A dataset of tracked mesoscale precipitation systems in the tropics Russell, James, Rajagopal, Manikandan, Veals, Peter, Skok, Gregor, Zipser, Edward, TinocoMorales, Michell Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain
A Framework to Attribute Tropical Multiscale Precipitation Extremes to Carenso, M., Fildier, B., Roca, R., Fiolleau, T. Precipitation, Brightness Temperature, Precipitation Amount, Precipitation Rate, Snow, Rain
A global dataset of remote sensing-based soil critical point and permanent wilting point Xu, Yawei, He, Qing, Lu, Hui, Yang, Kun, Entekhabi, Dara, Short Gianotti, Daniel J. Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain, Land Use/Land Cover Classification
A onedimensional variational precipitation retrieval algorithm considering cloud types for western North Pacific tropical cyclones using FengYun3E microwave ... Xu, Jintao, Ma, Ziqiang, Hu, Hao, Li, Xiaoqing, Fang, Xiang Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain
Interferometric Radar Satellite and In-Situ Well Time-Series Reveal Kakar, N., Metzger, S., Schone, T., Motagh, M., Waizy, H., Nasrat, N. A., Lazecky, M., Amelung, F., Bookhagen, B. Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain
Interplay of freezethaw cycles and avalanche impact on glacial landslidedebris flow geohazard chain in the southeastern Tibetan Plateau Huang, Taosheng, Wang, Tengfei, Zhang, Limin, Peng, Dalei, Shen, Ping Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain
Investigating Mechanisms Driving Differences in the Characteristics of Hsu, WeiChing, Kooperman, Gabriel J., Hannah, Walter M. Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain
Intensifying tropical cyclones in the Arabian Sea replenish depleting aquifers Saleh, Hassan, Sultan, Mohamed, Yan, Eugene, Save, Himanshu, Elhaddad, Hesham, Karimi, Hadi, Abdelmohsen, Karem, Emil, Mustafa K., Qamshouai, Sara Al Terrestrial Water Storage, Ground Water, Glacier Mass Balance/Ice Sheet Mass Balance, Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain
Making earth observations model-friendly: An interoperable tool enabling Wang, Linji, Rajib, Adnan, Merwade, Venkatesh Leaf Characteristics, Photosynthetically Active Radiation, Leaf Area Index (LAI), Fraction Of Absorbed Photosynthetically Active Radiation (fapar), Evapotranspiration, Latent Heat Flux, Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain
Mapping the spatio-temporal distribution of burned areas in the Amazon Abid, Mohamed, Gonzalez, Jonatan A., de Rivera, Oscar Rodriguez, Moraga, Paula Fire Ecology, Biomass Burning, Wildfires, Fire Occurrence, Land Use/Land Cover Classification, Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain, Surface Pressure, Heat Flux, Longwave Radiation, Shortwave Radiation, Air Temperature, Specific Humidity, Evapotranspiration, Wind Speed, Soil Moisture/Water Content, Soil Temperature, Land Surface Temperature, Snow Cover, Snow Depth, Snow Water Equivalent, Runoff, Burned Area, Emissivity
Moisture sources and dynamics over the Southeast Tibetan Plateau reflected in dual water vapor isotopes Cai, Zhongyin, Li, Rong, Wang, Cheng, Mao, Qiukai, Tian, Lide Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain
Mesoscale Convective Systems in Northeast China From Satellite Products Yu, Hongyong, Prein, Andreas F., Qi, Dan, Wang, Kaicun Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain, Brightness Temperature
Mesoscale Convective Systems over Ecuador: Climatology, Trends and Robaina, Leandro, Campozano, Lenin, Villacis, Marcos, Rehbein, Amanda Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain
Mesoscale Convective Systems over South America: Representation in Kilometer-Scale Met Office Unified Model Climate Simulations Gilmour, Harriet, Chadwick, Robin, Catto, Jennifer L., Halladay, Kate, Hart, Neil C. G., Rehbein, Amanda Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain
Mesoscale Convective Systems over South Asia: Unraveling climatology, land-ocean differences and environmental drivers Paul, Debjit, Dubey, Sarvesh, Cui, Wenjun Precipitation, Brightness Temperature, Precipitation Amount, Precipitation Rate, Snow, Rain
Mesoscale Convective Systems Tracking Method Intercomparison (MCSMIP): Feng, Zhe, Prein, Andreas F., Kukulies, Julia, Fiolleau, Thomas, Jones, William K., Maybee, Ben, Moon, Zachary L., Nunez Ocasio, Kelly M., Dong, Wenhao, Molina, Maria J., Albright, Mary Grace, Rajagopal, Manikandan, Robledo, Vanessa, Song, Jinyan, Song, Fengfei, Leung, L. Ruby, Varble, Adam C., Klein, Cornelia, Roca, Remy, Feng, Ran, Mejia, John F. Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain, Atmospheric Water Vapor, RADAR, Brightness Temperature
Muted Amazon Rainfall Response to Deforestation in a Global Yoon, Arim, Hohenegger, Cathy Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain
Near-Surface Temperature Warming Modulated by Rain Layers at the Edge of a Warm Eddy Hsu, Je-Yuan, Chang, Ming-Huei, Yang, Yiing Jang, Jan, Sen Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain
Multiscale Processes Modulating the Duration of Extremely Persistent Heavy Rainfall: A Comparative Study of Two Winter Events Liu, Haisheng, Huang, Xiaogang, Fei, Jianfang, Cheng, Xiaoping, Li, Xuhang, Zeng, Can, Zhang, Chi, Wu, Zhiyan, Yang, Wei Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain
You're viewing 50 of 741

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/Intermediate/IRinfluence Grid/Intermediate/IRinfluence N/A int16 -9999 N/A N/A N/A
Grid/Intermediate/IRprecipitation Grid/Intermediate/IRprecipitation mm/hr float32 -9999.900390625 N/A N/A N/A
Grid/Intermediate/MWobservationTime Grid/Intermediate/MWobservationTime minutes int16 -9999 N/A N/A N/A
Grid/Intermediate/MWprecipitation Grid/Intermediate/MWprecipitation mm/hr float32 -9999.900390625 N/A N/A N/A
Grid/Intermediate/MWprecipSource Grid/Intermediate/MWprecipSource N/A int16 -9999 N/A N/A N/A
Grid/Intermediate/precipitationUncal Grid/Intermediate/precipitationUncal mm/hr float32 -9999.900390625 N/A N/A N/A
Grid/lat Grid/lat degrees_north float32 N/A N/A N/A N/A
Grid/lat_bnds Grid/lat_bnds degrees_north float32 N/A N/A N/A N/A
Grid/lon Grid/lon degrees_east float32 N/A N/A N/A N/A
Grid/lon_bnds Grid/lon_bnds degrees_east float32 N/A N/A N/A N/A
Grid/precipitation Grid/precipitation mm/hr float32 -9999.900390625 N/A N/A N/A
Grid/precipitationQualityIndex Grid/precipitationQualityIndex N/A float32 -9999.900390625 N/A N/A N/A
Grid/probabilityLiquidPrecipitation Grid/probabilityLiquidPrecipitation percent int16 -9999 N/A N/A N/A
Grid/randomError Grid/randomError mm/hr float32 -9999.900390625 N/A N/A N/A
Grid/time Grid/time seconds since 1980-01-06 00:00:00 UTC int32 N/A N/A N/A N/A
Grid/time_bnds Grid/time_bnds seconds since 1980-01-06 00:00:00 UTC int32 N/A N/A N/A N/A
You're viewing 16 of 16