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 Older versions will no longer be available and have been superseded by Version 07.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 |
|---|---|---|---|
| Accuracy of satellite precipitation products in data-scarce Inner Tibetan Plateau comprehensively evaluated using a novel ground observation network | Liu, Zhaofei | Total Surface Precipitation Rate, Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| An assessment of L-band surface soil moisture products from SMOS and | Ma, Hongliang, Li, Xiaojun, Zeng, Jiangyuan, Zhang, Xiang, Dong, Jianzhi, Chen, Nengcheng, Fan, Lei, Sadeghi, Morteza, Frappart, Frederic, Liu, Xiangzhuo, Wang, Mengjia, Wang, Huan, Fu, Zheng, Xing, Zanpin, Ciais, Philippe, Wigneron, Jean-Pierre | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| A spatial and temporal analysis of commercialized NTFP production in four administrative regions in Myanmar | Chew, Wei Chuang, Okuda, Toshinori, Mon, Su Myat, Mandal, Mohammad Shamim Hasan, Shigematsu, Chihomi, Shin, Thant, Thant, Aye Mya | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| A reduced latency regional gap-filling method for SMAP using random forest regression | Wang, Xiaoyi, Lu, Haishen, Crow, Wade T., Corzo, Gerald, Zhu, Yonghua, Su, Jianbin, Zheng, Jingyao, Gou, Qiqi | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| A twenty-year dataset of soil moisture and vegetation optical depth from AMSR-E/2 measurements using the multi-channel collaborative algorithm | Hu, Lu, Zhao, Tianjie, Ju, Weimin, Peng, Zhiqing, Shi, Jiancheng, Rodriguez-Fernandez, Nemesio J., Wigneron, Jean-Pierre, Cosh, Michael H., Yang, Kun, Lu, Hui, Yao, Panpan | Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain, Land Use/Land Cover Classification, Vegetation Water Content, Soil Moisture/Water Content, Skin Temperature | |
| A Novel Optimization Strategy of Sidelobe Suppression for Pulse | Hu, Jiaqi, Dong, Xichao, Tian, Weiming, Hu, Cheng, Feng, Kai, Lu, Jun | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Assessing the Impact of Deforestation on Decadal Runoff Estimates in | Khor, Jen Feng, Lim, Steven, Ling, Vania Lois, Ling, Lloyd | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Assessing the soil moisture-precipitation feedback in Australia: CYGNSS observations | Bui, Hien X, Li, Yi-Xian, Sherwood, Steven C, Reid, Kimberley J, Dommenget, Dietmar | Soil Moisture/Water Content, Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Assessing the Water Budget Closure Accuracy of | Luo, Zengliang, Yu, Han, Liu, Huan, Chen, Jie | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain, Total Surface Precipitation Rate, 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 | |
| Boundary-dependent urban impacts on timing, pattern, and magnitude of heavy rainfall in Istanbul | Donmez, Kutay, Donmez, Berkay, Diren-Ustun, Deniz H., Unal, Yurdanur | Land Surface Temperature, Emissivity, Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Atlantic ITCZ variability during the Holocene based on high-resolution speleothem isotope records from northern Venezuela | Medina, N. Melissa M., Cruz, Francisco W., Winter, Amos, Zhang, Haiwei, Ampuero, Angela, Vuille, Mathias, Mayta, Victor C., Campos, Marilia C., Ramirez, Veronica Marcela, Utida, Giselle, Zuniga, Andres Camilo, Cheng, Hai | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| BartlettLewis Model Calibrated with Satellite-Derived Precipitation Data to Estimate Daily Peak 15 Min Rainfall Intensity | Islam, Md. Atiqul, Yu, Bofu, Cartwright, Nick | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Characterizing the 2022 Extreme Drought Event over the Poyang Lake Basin | Liu, Sulan, Wu, Yunlong, Xu, Guodong, Cheng, Siyu, Zhong, Yulong, Zhang, Yi | Surface Pressure, Heat Flux, Longwave Radiation, Shortwave Radiation, Surface Temperature, Humidity, Evapotranspiration, Surface Winds, Rain, Precipitation Rate, Snow, Soil Moisture/Water Content, Soil Temperature, Land Surface Temperature, Snow Water Equivalent, Runoff, Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Precipitation, Precipitation Amount | |
| Characterization of ensemble generation strategies: Application to three illustrative examples of Mediterranean high-impact weather | Hermoso, Alejandro, Homar, Victor, Romero, Romualdo | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Changes of tropical gravity waves and the quasi-biennial oscillation in | Franke, Henning, Preusse, Peter, Giorgetta, Marco | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Assessment of a Dynamic Physically Based Slope Stability Model to | Thomas, Juby, Gupta, Manika, Srivastava, Prashant K., Petropoulos, George P. | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Assessing global parameters of slope stability model using Earth data observations for forecasting rainfallinduced shallow landslides | Thomas, Juby, Gupta, Manika, Prusty, Ganesh | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Climate responsive design for road surface drainage systems: a case study for city of Bengaluru | Kalore, Shubham, Yashas, V, Bagrecha, Aman, Nypunya, J, Sivakumar Babu, G L | RADAR IMAGERY, Terrain Elevation, Topographical Relief Maps, Digital Elevation/Terrain Model (DEM), Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Hydraulic design of granular and geocomposite drainage layers in pavements based on demand-capacity modeling | Kalore, Shubham A., Sivakumar Babu, G.L. | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Identification of the significant parameters in spatial prediction of landslide hazard | Tyagi, Ankit, Tiwari, Reet Kamal, James, Naveen | 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, Precipitation, Precipitation Amount, Precipitation Rate | |
| Learnings from rapid response efforts to remotely detect landslides triggered by the August 2021 Nippes earthquake and Tropical Storm Grace in Haiti | Amatya, Pukar, Scheip, Corey, Deprez, Aline, Malet, Jean-Philippe, Slaughter, Stephen L., Handwerger, Alexander L., Emberson, Robert, Kirschbaum, Dalia, Jean-Baptiste, Julien, Huang, Mong-Han, Clark, Marin K., Zekkos, Dimitrios, Huang, Jhih-Rou, Pacini, Fabrizio, Boissier, Enguerran | Terrain Elevation, RADAR IMAGERY, Topographical Relief Maps, Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| IMERG Precipitation Improves the SMAP Level-4 Soil Moisture Product | Reichle, Rolf H., Liu, Qing, Ardizzone, Joseph V., Crow, Wade T., De Lannoy, Gabrielle J. M., Kimball, John S., Koster, Randal D. | Surface Soil Moisture, Soil Moisture/Water Content, Soil Temperature, Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain, Brightness Temperature | |
| Integrating development inhomogeneity into geological disasters risk assessment framework in mountainous areas: a case study in LushanBaoxing counties, Southwestern China | He, Yufeng, Ding, Mingtao, Zheng, Hao, Gao, Zemin, Huang, Tao, Duan, Yu, Cui, Xingjie, Luo, Siyuan | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Interaction Between Evapotranspiration and Meteorological and Hydrological Factors in Drought Events: A Case Study of The Yangtze River Basin | He, Kaixun, Lu, Hui | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Interannual variation of coastal upwelling around Hainan Island | Zhu, Junying, Zhou, Quanyi, Zhou, Qianqing, Geng, Xinxing, Shi, Jie, Guo, Xinyu, Yu, Yang, Yang, Ziwei, Fan, Renfu | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain |