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 Older versions will no longer be available and have been superseded by Version 07.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 |
|---|---|---|---|
| Land-Locked Convection as a Barrier to MJO Propagation Across the | Savarin, A., Chen, S. S. | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain, Total Surface Precipitation Rate | |
| Modified flood potential index (MFPI) for flood monitoring in terrestrial water storage depletion basin using GRACE estimates | Jiang, Wei, Ji, Xuan, Li, Yungang, Luo, Xian, Yang, Luyi, Ming, Wenting, Liu, Chang, Yan, Siyi, Yang, Chuanjian, Sun, Cezong | 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, Precipitation, Precipitation Amount, Gravity Anomalies, Gravity | |
| The Diurnal Cycle of East Pacific Convection, Moisture, and CYGNSS Wind Speed and Fluxes | Riley Dellaripa, Emily M., Maloney, Eric D., DeMott, Charlotte A. | Wind Direction, Wind Speed, Heat Flux, Sea Surface Temperature, Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain, Total Surface Precipitation Rate | |
| The Diurnal Cycle of Rainfall and Deep Convective Clouds Around Sumatra | LopezBravo, Clemente, Vincent, Claire L., Huang, Yi, Lane, Todd P. | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| The impacts of assimilating Aeolus horizontal line-of-sight winds on numerical predictions of Hurricane Ida (2021) and a mesoscale convective system over ... | Feng, Chengfeng, Pu, Zhaoxia | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Temporal Gap-Filling of 12-Hourly SMAP Soil Moisture Over the CONUS | Zhang, Runze, Kim, Seokhyeon, Kim, Hyunglok, Fang, Bin, Sharma, Ashish, Lakshmi, Venkataraman | Surface Pressure, Longwave Radiation, Shortwave Radiation, Surface Temperature, Evaporation, Humidity, Convection, Surface Winds, Rain, Land Surface Temperature, Precipitation, Precipitation Amount, Precipitation Rate, Snow | |
| Temporal Dynamics of the Hydropower Water Reservoirs of the | Vieira Valadao, Larissa, Fonseca, Iara Resende da, Cicerelli, Rejane Ennes, Almeida, Tati de, Garnier, Jeremie, Sano, Edson Eyji | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| SPEI and multi-threshold run theory based drought analysis using | Ma, Qian, Li, Yi, Liu, Fenggui, Feng, Hao, Biswas, Asim, Zhang, Qiang | Precipitation, Rain, Precipitation Amount, Precipitation Rate, Snow, Total Surface Precipitation Rate | |
| Stratocumulus adjustments to aerosol perturbations disentangled with a causal approach | Fons, Emilie, Runge, Jakob, Neubauer, David, Lohmann, Ulrike | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Spatial patterns of shallow landslides induced by the 19 September 2017 | Salinas-Jasso, Jorge A., Montalvo-Arrieta, Juan C., Velasco-Tapia, Fernando | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Spatial Variation in the Synoptic Structure of Convective Systems over the Great Plains | Verevkin, Iaroslav, Folkins, Ian | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Spatio-Temporal Variations in Sediment Delivery as a Response to Rapid | Wright, Lachlan J. M., Scholz, Christopher A. | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Seasonal sea breeze variation analysis based on multi-year near-surface | Junnaedhi, I Dewa Gede Agung, Inagaki, Atsushi, Ferdiansyah, Muhammad Rezza, Kanda, Manabu | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Response of xylem formation of Larix sibirica to climate change along the southern Altai Mountains, Central Asia | Wang, Wenjin, Huang, Jian-Guo, Jiang, Shaowei, Yu, Biyun, Zhou, Peng, Zhang, Yaling | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Remote Sensing-Based Estimates of Changes in Stored Groundwater at Local Scales: Case Study for Two Groundwater Subbasins in California's Central ... | Ahamed, Aakash, Knight, Rosemary, Alam, Sarfaraz, Morphew, Michael, Susskind, Tea | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Representing the Subgrid Surface Heterogeneity of Precipitation in a | Arnold, Nathan P., Koster, Randal D., Trayanov, Atanas L. | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Resilience assessment of a highwayrailway complementary network under rainstorms | Chen, Jinqu, Liang, Cheng, Liu, Jie, Du, Bo, Yin, Yong, Peng, Qiyuan | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Review on spatial downscaling of satellite derived precipitation | Kofidou, Maria, Stathopoulos, Stavros, Gemitzi, Alexandra | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain, Total Surface Precipitation Rate, Droplet Size, Radar Reflectivity | |
| Revisiting the Relationship Between Tropical Cyclone Rapid | Shi, Donglei, Chen, Guanghua, Xie, Xinru | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Simulation Analyses on a Downburst Event That Caused a Severe Tower | Li, Danyu, Liu, Jinghua, Liu, Bin, Fan, Wenqi, Yang, Dongwen, Xiao, Xue | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| 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 | |
| Twenty years of net photosynthesis, climatic and anthropic factors from biomes of Bahia State, Brazil | Benfica, Nayanne Silva, Gomes, Andrea da Silva, Zanchi, Fabricio Berton | Photosynthesis, Primary Production, Vegetation Productivity, Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| We Need a Better Way to Share Earth Observations | Liu, Zhong, Wen, Yixin, Mantas, Vasco, Meyer, David | Precipitation, Rain, Precipitation Amount, Precipitation Rate, Snow | |
| Verification of a global weather forecasting system for decision-making in farming over Africa | Kartsios, Stergios, Pytharoulis, Ioannis, Karacostas, Theodore, Pavlidis, Vasileios, Katragkou, Eleni | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain | |
| Utilizing Satellite Data to Establish Rainfall | Zeri, Sarah Jabbar, Hamed, Mohammed Magdy, Wang, Xiaojun, Shahid, Shamsuddin | Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain |