N: 90 S: -90 E: 180 W: -180
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 Older versions will no longer be available and have been superseded by Version 07.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).
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Publications Citing This Dataset
| Title | Year Sort ascending | Author | Topic |
|---|---|---|---|
| Evaluation of GPM-IMERG Precipitation Product at Multiple Spatial and | Zhou, Zehui, Lu, Dekai, Yong, Bin, Shen, Zhehui, Wu, Hao, Yu, Lei | Precipitation, Rain, Precipitation Amount, Precipitation Rate, Snow, Total Surface Precipitation Rate | |
| Evaluation of Hourly Precipitation Characteristics from a Global | Chen, Tianru, Li, Jian, Zhang, Yi, Chen, Haoming, Li, Puxi, Che, Huizheng | Precipitation, Rain, Precipitation Amount, Precipitation Rate, Snow, Total Surface Precipitation Rate | |
| Evaluation of IMERG for GPM satellite-based precipitation products for extreme precipitation indices over Turkiye | Aksu, Hakan, Taflan, Gaye Yesim, Yaldiz, Sait Genar, Akgul, Mehmet Ali | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain, Total Surface Precipitation Rate | |
| Global and Regional Characteristics of Radially Outward Propagating Tropical Cyclone Diurnal Pulses | Zhang, Xinyan, Ditchek, Sarah D., Corbosiero, Kristen L., Xu, Weixin | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain, Total Surface Precipitation Rate | |
| Evaluating the Hydrological Components Contributions to Terrestrial | Guo, Yi, Xing, Naichen, Gan, Fuping, Yan, Baikun, Bai, Juan | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Evaluation of 12 precipitation products and comparison of 8 multi-model averaging methods for estimating precipitation in the Qilian Mountains, Northwest China | Yang, Yong, Chen, Rensheng, Ding, Yongjian, Qing, Wenwu, Li, Hongyuan, Han, Chuntan, Liu, Zhangwen, Liu, Junfeng | Total Surface Precipitation Rate, Surface Pressure, Heat Flux, Longwave Radiation, Shortwave Radiation, Air Temperature, Specific Humidity, Evapotranspiration, Wind Speed, Rain, Snow, Soil Moisture/Water Content, Soil Temperature, Land Surface Temperature, Snow Cover, Snow Depth, Snow Water Equivalent, Runoff, Surface Temperature, Humidity, Surface Winds, Precipitation Rate, Precipitation, Precipitation Amount | |
| Evaluating satellite precipitation estimates over oceans using passive aquatic listeners | Bytheway, J. L., Thompson, E. J., Yang, J., Chen, H. | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain, Liquid Precipitation, Wind Speed | |
| Evaluating the Representations of Atmospheric Rivers and Their | Ma, Weiming, Chen, Gang, Guan, Bin, Shields, Christine A., Tian, Baijun, Yanez, Emilio | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Evaluation of an early flood warning system in Bamako (Mali): Lessons learned from the flood of May 2019 | Chahinian, Nanee, Alcoba, Matias, Dembele, Ndji dit Jacques, Cazenave, Frederic, Bouvier, Christophe | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Estimating the Impacts of Ungauged Reservoirs Using Publicly Available | Nguyen, Ngoc Thi, Du, Tien Le Thuy, Park, Hyunkyu, Chang, Chi-Hung, Choi, Sunghwa, Chae, Hyosok, Nelson, E. James, Hossain, Faisal, Kim, Donghwan, Lee, Hyongki | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Estimating Monthly River Discharges from GRACE/GRACE-FO Terrestrial | Duvvuri, Bhavya, Beighley, Edward | Emissivity, Land Surface Temperature, Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Effects of the Horizontal Scales of the Cloud-Resolving Model on | Kuo, KuanTing, Wu, ChienMing, Chen, WeiTing | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Enhancing spatial resolution of GRACE-derived groundwater storage anomalies in Urmia catchment using machine learning downscaling methods | Sabzehee, F., Amiri-Simkooei, A.R., Iran-Pour, S., Vishwakarma, B.D., Kerachian, R. | Evapotranspiration, Latent Heat Flux, Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Precipitation, Rain, Precipitation Amount, Precipitation Rate, Snow, Land Surface Temperature, Emissivity, Surface Pressure, Heat Flux, Longwave Radiation, Shortwave Radiation, Air Temperature, Specific Humidity, Wind Speed, Soil Moisture/Water Content, Soil Temperature, Snow Cover, Snow Depth, Snow Water Equivalent, Runoff | |
| Ensemble precipitation estimates based on an assessment of 21 gridded precipitation datasets to improve precipitation estimations across Madagascar | Ollivier, Camille C., Carriere, Simon D., Heath, Thomas, Olioso, Albert, Rabefitia, Zo, Rakoto, Heritiana, Oudin, Ludovic, Satge, Frederic | Heat Flux, Air Temperature, Skin Temperature, Specific Humidity, Water Vapor, Precipitation Rate, Snow/Ice, Evaporation, Latent Heat Flux, Latent Heat Flux, Sensible Heat Flux, Diffusion, Surface Winds, Wind Speed, U/V Wind Components, Wind Stress, Wind Stress, Surface Roughness, Planetary Boundary Layer Height, Ice Fraction, Total Surface Precipitation Rate, Longwave Radiation, Shortwave Radiation, Soil Heat Budget, Soil Heat Budget, Soil Temperature, Soil Temperature, Soil Infiltration, Soil Infiltration, Soil Moisture/Water Content, Surface Soil Moisture, Root Zone Soil Moisture, Soil Moisture/Water Content, Surface Water, Runoff Rate, Average Flow, Average Flow, Precipitation, Snow Depth, Snow Melt, Snow/Ice Temperature, Leaf Area Index (LAI), Leaf Area Index (LAI), Rain, Precipitation Amount, Snow | |
| Evaluation of rainfall thresholds triggering debris flows in western China with gauged-and satellite-based precipitation measurement | Liu, Zhaofei | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Evaluation of WRF simulation of deep convection in the US Southern Great Plains | Pryor, S. C., Letson, F., Shepherd, T., Barthelmie, R. J. | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Geospatial Modeling Based-Multi-Criteria Decision-Making for Flash Flood Susceptibility Zonation in an Arid Area | Shawky, Mohamed, Hassan, Quazi K. | Precipitation, Rain, Precipitation Amount, Precipitation Rate, Snow | |
| Spatio-temporal characteristics and driving factors of flash drought recovery: From the perspective of soil moisture and GPP changes | Wang, Haichen, Zhu, Qian, Wang, Yushi, Zhang, Hao | Precipitation, Rain, Precipitation Amount, Precipitation Rate, Snow | |
| Utilization of Google Earth Engine for Assessment of Daily and Seasonal Variations of TRMM3B43-v7, GPM-v6 and PERSIANN-CDR Data Over the Coastline of ... | Akbari, Abolghasem, Rajabi Jaghargh, Majid, Abu Samah, Azizan, Cox, Jonathan | Total Surface Precipitation Rate, Precipitation, Rain, Precipitation Amount, Precipitation Rate, Snow | |
| Spatial Prediction of Groundwater Withdrawal Potential Using Shallow, Hybrid, and Deep Learning Algorithms in the Toudgha Oasis, Southeast Morocco | Ouali, Lamya, Kabiri, Lahcen, Namous, Mustapha, Hssaisoune, Mohammed, Abdelrahman, Kamal, Fnais, Mohammed S., Kabiri, Hichame, El Hafyani, Mohammed, Oubaassine, Hassane, Arioua, Abdelkrim, Bouchaou, Lhoussaine | Precipitation, Rain, Precipitation Amount, Precipitation Rate, Snow | |
| Quantitative Evaluation of Runoff Simulation and Its Driving Forces Based on Hydrological Model and Multisource Precipitation Fusion | Ma, Zice, Yao, Rui, Sun, Peng, Zhuang, Zhen, Ge, Chenhao, Zou, Yifan, Lv, Yinfeng | Total Surface Precipitation Rate, Precipitation, Rain, Precipitation Amount, Precipitation Rate, Snow | |
| Late Quaternary hydroclimate of the Levant: The leaf wax record from the Dead Sea | Tierney, Jessica E., Torfstein, Adi, Bhattacharya, Tripti | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Investigation of compound drought risk and driving factors in Nepal | Song, Wen, Cao, Shisong, Du, Mingyi, Mo, You, Li, Suju | Crop/Plant Yields, Land Use Classes, Landscape Patterns, Cropland, Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Integrating Hydrological Connectivity in a Process-Response Framework | Singh, Manudeo, Sinha, Rajiv | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| How well are we able to close the water budget at the global scale? | Lehmann, Fanny, Vishwakarma, Bramha Dutt, Bamber, Jonathan | Precipitation, Rain, Precipitation Amount, Precipitation Rate, Snow |