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 Older versions will no longer be available and have been superseded by Version 07.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.
Precipitation phase is a diagnostic variable computed using analyses of surface temperature, humidity, and pressure.
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Publications Citing This Dataset
| Title | Year Sort ascending | Author | Topic |
|---|---|---|---|
| Assessing the risk posed by flash floods to the transportation network in southwestern China | He, Yufeng, Xiong, Junnan, Cheng, Weiming, Yang, Jiawei, He, Wen, Yong, Zhiwei, Duan, Yu, Liu, Jun, Yang, Gang, Wang, Nan | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Assessment of SMAP and SMOS soil moisture products using triple | Hu, Fengmin, Wei, Zushuai, Yang, Xining, Xie, Wenjun, Li, Yuanxi, Cui, Changlu, Yang, Beibei, Tao, Chongxin, Zhang, Wen, Meng, Lingkui | Land Use/Land Cover Classification, Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Cloud water path, precipitation amount, and precipitation efficiency derived from multiple datasets on the Qilian Mountains, Northeastern Tibetan Plateau | Qi, Peng, Guo, Xueliang, Chang, Yi, Tang, Jie, Li, Siyuan | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain, Total Surface Precipitation Rate | |
| Mapping Susceptibility With Open-Source Tools: A New Plugin for QGIS | Titti, Giacomo, Sarretta, Alessandro, Lombardo, Luigi, Crema, Stefano, Pasuto, Alessandro, Borgatti, Lisa | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Lightning forecasting in Bangladesh based on the lightning potential index and the electric potential | Rabbani, Khan Md Golam, Islam, Md Jafrul, Fierro, Alexandre O., Mansell, Edward R., Paul, Pappu | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Mapped coral mortality and refugia in an archipelago-scale marine heat wave | Asner, Gregory P., Vaughn, Nicholas R., Martin, Roberta E., Foo, Shawna A., Heckler, Joseph, Neilson, Brian J., Gove, Jamison M. | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Intercomparison of multiple high-resolution precipitation products over | Du, Yi, Wang, Dagang, Zhu, Jinxin, Lin, Zequn, Zhong, Yixuan | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Large loss and rapid recovery of vegetation cover and aboveground | Qin, Yuanwei, Xiao, Xiangming, Wigneron, Jean-Pierre, Ciais, Philippe, Canadell, Josep G., Brandt, Martin, Li, Xiaojun, Fan, Lei, Wu, Xiaocui, Tang, Hao, Dubayah, Ralph, Doughty, Russell, Crowell, Sean, Zheng, Bo, Moore, Berrien | Leaf Characteristics, Photosynthetically Active Radiation, Leaf Area Index (LAI), Fraction Of Absorbed Photosynthetically Active Radiation (fapar), Land Surface Temperature, Emissivity, Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| 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 | |
| Integrating Hydrological Connectivity in a Process-Response Framework | Singh, Manudeo, Sinha, Rajiv | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Interannual and intra-annual cycles of satellite-derived chlorophyll-a | Moradi, Masoud | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Increasing model vertical resolution may not necessarily lead to improved atmospheric predictability | Moon, Sungju, Baik, Jong-Jin, Song, Hyo-Jong, Han, Ji-Young | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Improving the Wind Power Density Forecast in the Middle- and | Ma, Hui, Cao, Xin, Ma, Xiaolei, Su, Haijing, Jing, Yanwei, Zhu, Kunshuang | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Improving the prediction of monsoon depressions by assimilating ASCAT soil moisture in NCUM-R modeling system | Lodh, Abhishek, Routray, Ashish, Dutta, Devajyoti, George, John P., Mitra, Ashis K. | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Impact of lithium mining on climate change in the Atacama Desert, South America | Chakraborty, R., Srinivas, B., Chakraborty, A. | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Impact of data assimilation on a calibrated WRF model for the prediction | Baki, Harish, Balaji, C., Srinivasan, Balaji | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Impact of transported dust aerosols on precipitation over the Nepal Himalayas using convection-permitting WRF-Chem simulation | Adhikari, Pramod, Mejia, John F. | Dust/Ash/Smoke, Carbonaceous Aerosols, Organic Particles, Sulfate Particles, Sulfur Oxides, Sulfur Compounds, Sulfate, Sulfur Dioxide, Sulfur Oxides, Dimethyl Sulfide, Aerosol Particle Properties, Particulate Matter, Aerosols, Surface Pressure, Pressure Thickness, Relative Humidity, Sea Salt, Black Carbon, Air Mass/Density, Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Enhancement of Satellite Precipitation Estimations with Bias Correction | Soo, Eugene Zhen Xiang, Wan Jaafar, Wan Zurina, Lai, Sai Hin, Othman, Faridah, Elshafie, Ahmed | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Elucidating the impacts of COVID-19 lockdown on air quality and ozone chemical characteristics in India | Roozitalab, Behrooz, Carmichael, Gregory R., Guttikunda, Sarath K., Abdi-Oskouei, Maryam | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Direct and indirect effects and feedbacks of biomass burning aerosols over Mainland Southeast Asia and South China in springtime | Li, Jiawei, Han, Zhiwei, Surapipith, Vanisa, Fan, Wenxuan, Thongboonchoo, Narisara, Wu, Jian, Li, Jie, Tao, Jun, Wu, Yunfei, Macatangay, Ronald, Bran, Sherin Hassan, Yu, Entao, Zhang, Anzhi, Liang, Lin, Zhang, Renjian | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Dynamic Relationship Study between the Observed Seismicity and | Nath, Biswajit, Singh, Ramesh P., Gahalaut, Vineet K., Singh, Ajay P. | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Could road constructions be more hazardous than an earthquake in terms | Tanyas, Hakan, Gorum, Tolga, Kirschbaum, Dalia, Lombardo, Luigi | RADAR IMAGERY, Terrain Elevation, Topographical Relief Maps, Digital Elevation/Terrain Model (DEM), Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Dynamic downscaling ensemble forecast of an extreme rainstorm event in South China by COSMO EPS | Ji, Luying, Zhi, Xiefei, Schalge, Bernd, Stephan, Klaus, Wu, Zhifang, Wu, Chong, Simmer, Clemens, Zhu, Shoupeng | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Evaluating performance of 20 global and quasi-global precipitation | Degefu, Mekonnen Adnew, Bewket, Woldeamlak, Amha, Yosef | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain, Total Surface Precipitation Rate | |
| Comparison of flow simulations with sub-daily and daily GPM IMERG products over a transboundary Chenab River catchment | Ahmed, Ehtesham, Al Janabi, Firas, Yang, Wenyu, Ali, Akhtar, Saddique, Naeem, Krebs, Peter | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain |