The Global Precipitation Measurement (GPM) mission's scientific achievements and societal contributions: reviewing four years of advanced rain and snow observations

Precipitation represents a life-critical energy and hydrologic exchange between the Earth's atmosphere and its surface. As such, knowledge of where, when, and how much rain and snow falls is essential for scientific research and societal applications. Building on the 17-year success of the Tropical Rainfall Measurement Mission (TRMM), the Global Precipitation Measurement (GPM) Core Observatory (GPM-CO) is the first U.S. National Aeronautical and Space Administration (NASA) satellite mission specifically designed with sensors to observe the structure and intensities of both rain and falling snow. The GPM-CO has proved to be a worthy successor to TRMM, extending and improving high-quality active and passive microwave observations across all times of day. The GPM-CO launched in early 2014, is a joint mission between NASA and the Japanese Aerospace Exploration Agency (JAXA), with sensors that include the NASA-provided GPM Microwave Imager and the JAXA-provided Dual-frequency Precipitation Radar. These sensors were devised with high accuracy standards enabling them to be used as a reference for inter-calibrating a constellation of partner satellite data. These intercalibrated partner satellite retrievals are used with infrared data to produce merged precipitation estimates at temporal scales of 30 minutes and spatial scales of 0.1° × 0.1°. Precipitation estimates from the GPM-CO and partner constellation satellites, provided in near real time and later reprocessed with all ancillary data, are an indispensable source of precipitation data for operational and scientific users. Advances have been made using GPM data, primarily in improving sensor calibration, retrieval algorithms, and ground validation measurements, and used to further our understanding of the characteristics of liquid and frozen precipitation and the science of water and hydrological cycles for climate/weather forecasting. These advances have extended to societal benefits related to water resources, operational numerical weather prediction, hurricane monitoring, prediction, and disaster response, extremes, and disease.

[1]  T. N. Krishnamurti,et al.  The status of the tropical rainfall measuring mission (TRMM) after two years in orbit , 2000 .

[2]  Chris Kidd,et al.  Validation of the Version 05 Level 2 precipitation products from the GPM Core Observatory and constellation satellite sensors , 2018 .

[3]  Lihua Li,et al.  Airborne Radar Observations of Severe Hailstorms: Implications for Future Spaceborne Radar , 2013 .

[4]  Yudong Tian,et al.  An Error Model for Uncertainty Quantification in High-Time-Resolution Precipitation Products , 2014 .

[5]  Li Li,et al.  A Physically Based Soil Moisture and Microwave Emissivity Data Set for Global Precipitation Measurement (GPM) Applications , 2014, IEEE Transactions on Geoscience and Remote Sensing.

[6]  Fumie A. Furuzawa,et al.  Early Evaluation of Ku- and Ka-Band Sensitivities for the Global Precipitation Measurement (GPM) Dual-Frequency Precipitation Radar (DPR) , 2015 .

[7]  Y. Hong,et al.  The TRMM Multisatellite Precipitation Analysis (TMPA): Quasi-Global, Multiyear, Combined-Sensor Precipitation Estimates at Fine Scales , 2007 .

[8]  Michele M. Rienecker,et al.  Precipitation intensity and variation during MC3E: A numerical modeling study , 2013 .

[9]  Annakaisa von Lerber,et al.  Quantifying the effect of riming on snowfall using ground‐based observations , 2017 .

[10]  V. Chandrasekar,et al.  Salient features of the dual‐frequency, dual‐polarized, Doppler radar for remote sensing of precipitation , 2014 .

[11]  David W. Draper,et al.  On-Orbit Absolute Calibration of the Global Precipitation Measurement Microwave Imager , 2016 .

[12]  Patrick M. Reed,et al.  Internationally coordinated multi-mission planning is now critical to sustain the space-based rainfall observations needed for managing floods globally , 2015 .

[13]  Yang Hong,et al.  Toward a Framework for Systematic Error Modeling of Spaceborne Precipitation Radar with NOAA/NSSL Ground Radar–Based National Mosaic QPE , 2012 .

[14]  Jie Gong,et al.  Microphysical Properties of Frozen Particles Inferred from Global Precipitation Measurement (GPM) Microwave Imager (GMI) Polarimetric Measurements. , 2016, Atmospheric chemistry and physics.

[15]  R. Meneghini,et al.  Uncertainties of GPM DPR Rain Estimates Caused by DSD Parameterizations , 2014 .

[16]  Leo Pio D'Adderio,et al.  A Field Study of Footprint-Scale Variability of Raindrop Size Distribution , 2017 .

[17]  Annakaisa von Lerber,et al.  Validation of GMI Snowfall Observations by Using a Combination of Weather Radar and Surface Measurements , 2017 .

[18]  Yudong Tian,et al.  Performance of IMERG as a Function of Spatiotemporal Scale. , 2017, Journal of hydrometeorology.

[19]  Geological Insights from Malaysia Airlines Flight MH370 Search , 2017 .

[20]  Filipe Aires,et al.  Quantifying Uncertainties in Land-Surface Microwave Emissivity Retrievals , 2014, IEEE Transactions on Geoscience and Remote Sensing.

[21]  S. Joseph Munchak,et al.  Detection Thresholds of Falling Snow From Satellite-Borne Active and Passive Sensors , 2012, IEEE Transactions on Geoscience and Remote Sensing.

[22]  Annakaisa von Lerber,et al.  Ensemble mean density and its connection to other microphysical properties of falling snow as observed in Southern Finland , 2016 .

[23]  F. Joseph Turk,et al.  Precipitation from Space: Advancing Earth System Science , 2013 .

[24]  Jeff W. Brogden,et al.  Multi-Radar Multi-Sensor (MRMS) Quantitative Precipitation Estimation: Initial Operating Capabilities , 2016 .

[25]  Gerald M. Heymsfield,et al.  Using a multiwavelength suite of microwave instruments to investigate the microphysical structure of deep convective cores , 2016, Journal of geophysical research. Atmospheres : JGR.

[26]  David T. Bolvin,et al.  An Updated TRMM Composite Climatology of Tropical Rainfall and Its Validation , 2014 .

[27]  S. Tanelli,et al.  Multiple scattering in observations of the GPM dual‐frequency precipitation radar: Evidence and impact on retrievals , 2015, Journal of geophysical research. Atmospheres : JGR.

[28]  Ziad S. Haddad,et al.  The GPM Combined Algorithm , 2016 .

[29]  T. Painter,et al.  Estimation of Precipitation over the OLYMPEX Domain during Winter 2015/16 , 2017 .

[30]  P. Kollias,et al.  Observed relations between snowfall microphysics and triple‐frequency radar measurements , 2015 .

[31]  Y. Hong,et al.  Impact of sub‐pixel rainfall variability on spaceborne precipitation estimation: evaluating the TRMM 2A25 product , 2015 .

[32]  Simone Tanelli,et al.  Multiple-Scattering-Induced “Ghost Echoes” in GPM DPR Observations of a Tornadic Supercell , 2016 .

[33]  G. Peters,et al.  Rain observations with a vertically looking Micro Rain Radar (MRR) , 2002 .

[34]  Budhendra L. Bhaduri,et al.  High resolution urban feature extraction for global population mapping using high performance computing , 2007, 2007 IEEE International Geoscience and Remote Sensing Symposium.

[35]  Di Wu,et al.  Benefits of a 4th Ice Class in the Simulated Radar Reflectivities of Convective Systems Using a Bulk Microphysics Scheme , 2014 .

[36]  T. Raupach,et al.  Invariance of the Double-Moment Normalized Raindrop Size Distribution through 3D Spatial Displacement in Stratiform Rain , 2017 .

[37]  David A. Newell,et al.  The Global Precipitation Measurement (GPM) Microwave Imager (GMI): Instrument Overview and Early On-Orbit Performance , 2015, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[38]  Jian Zhang,et al.  Evaluation of a Method to Enhance Real-Time, Ground Radar–Based Rainfall Estimates Using Climatological Profiles of Reflectivity from Space , 2016 .

[39]  D. Kirschbaum,et al.  Satellite Precipitation Characterization, Error Modeling, and Error Correction Using Censored Shifted Gamma Distributions. , 2017, Journal of hydrometeorology.

[40]  Dawei Han,et al.  Performance Evaluation of the TRMM Precipitation Estimation Using Ground-Based Radars from the GPM Validation Network , 2012 .

[41]  W. Crow,et al.  Operational Hydrological Forecasting during the IPHEx-IOP Campaign - Meet the Challenge. , 2016, Journal of hydrology.

[42]  G. Huffman,et al.  Real‐time global flood estimation using satellite‐based precipitation and a coupled land surface and routing model , 2014 .

[43]  Y. Hong,et al.  Similarities and differences between three coexisting spaceborne radars in global rainfall and snowfall estimation , 2017 .

[44]  Branislav M. Notaros,et al.  Toward Completing the Raindrop Size Spectrum: Case Studies Involving 2D-Video Disdrometer, Droplet Spectrometer, and Polarimetric Radar Measurements , 2017 .

[45]  Chuntao Liu,et al.  “Warm Rain” in the Tropics: Seasonal and Regional Distributions Based on 9 yr of TRMM Data , 2009 .

[46]  Bart Nijssen,et al.  THE OLYMPIC MOUNTAINS EXPERIMENT (OLYMPEX). , 2017, Bulletin of the American Meteorological Society.

[47]  Ali Tokay,et al.  A Novel Approach to Identify Sources of Errors in IMERG for GPM Ground Validation , 2016 .

[48]  Sujay V. Kumar,et al.  Land information system: An interoperable framework for high resolution land surface modeling , 2006, Environ. Model. Softw..

[49]  F. Pappenberger,et al.  Development of a Global Fire Weather Database , 2015 .

[50]  Chuntao Liu,et al.  Latent heating contribution from precipitation systems with different sizes, depths, and intensities in the tropics , 2015 .

[51]  W. Liu,et al.  Premonsoon Drought in India Observed from Space , 2017 .

[52]  D. Cecil,et al.  Signatures of Hydrometeor Species from Airborne Passive Microwave Data for Frequencies 10–183 GHz , 2015 .

[53]  Milija Zupanski,et al.  Assessing the impact of pre‐GPM microwave precipitation observations in the Goddard WRF ensemble data assimilation system , 2014 .

[54]  Darren McKague,et al.  Assessing Calibration Stability Using the Global Precipitation Measurement (GPM) Microwave Imager (GMI) Noise Diodes , 2015, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[55]  Rachael A. Kroodsma,et al.  Intercalibration of the GPM Microwave Radiometer Constellation , 2016 .

[56]  S. Moore,et al.  Climate predictors of the spatial distribution of human plague cases in the West Nile region of Uganda. , 2012, The American journal of tropical medicine and hygiene.

[57]  Filipe Aires,et al.  Evaluation of modeled microwave land surface emissivities with satellite‐based estimates , 2015 .

[58]  Mathew R. Schwaller,et al.  A Ground Validation Network for the Global Precipitation Measurement Mission , 2011 .

[59]  David A. Marks,et al.  General Application of the Relative Calibration Adjustment (RCA) Technique for Monitoring and Correcting Radar Reflectivity Calibration , 2015 .

[60]  John Kochendorfer,et al.  How Well Are We Measuring Snow: The NOAA/FAA/NCAR Winter Precipitation Test Bed , 2012 .

[61]  R. Colwell,et al.  Assessment of Risk of Cholera in Haiti following Hurricane Matthew. , 2017, The American journal of tropical medicine and hygiene.

[62]  Bertrand Chapron,et al.  Analysis of Dual-Frequency Ocean Backscatter Measurements at Ku- and Ka-Bands Using Near-Nadir Incidence GPM Radar Data , 2016, IEEE Geoscience and Remote Sensing Letters.

[63]  Erin Jones,et al.  NASA’s Remotely Sensed Precipitation: A Reservoir for Applications Users , 2017 .

[64]  Luca Baldini,et al.  Use of the GPM Constellation for Monitoring Heavy Precipitation Events Over the Mediterranean Region , 2016, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[65]  Andrew J. Heymsfield,et al.  Importance of snow to global precipitation , 2015 .

[66]  Robert Cifelli,et al.  WRF Simulations of the 20-22 January 2007 Snow Events over Eastern Canada: Comparison with In-Situ and Satellite Observations , 2010 .

[67]  Edward J. Zipser,et al.  The global distribution of largest, deepest, and most intense precipitation systems , 2015 .

[68]  Mathew R. Schwaller,et al.  Global Precipitation Measurement (GPM) Ground Validation (GV) Prototype in the Korean Peninsula , 2014 .

[69]  K. Trenberth.  Changes in precipitation with climate change , 2011 .

[70]  Incorporating Ice Crystal Scattering Databases in the Simulation of Millimeter-Wavelength Radar Reflectivity , 2011 .

[71]  C. Kummerow,et al.  Performance of the GPM Passive Microwave Retrieval in the Balkan Flood Event of 2014 , 2015 .

[72]  O. Branch,et al.  Impact of Climate Change on Vector-Borne Disease in the Amazon , 2014 .

[73]  Venkat Lakshmi,et al.  A global assessment of the timing of extreme rainfall from TRMM and GPM for improving hydrologic design , 2016 .

[74]  T. Kubota,et al.  GSMaP Passive Microwave Precipitation Retrieval Algorithm : Algorithm Description and Validation(2. Global Satellite Mapping of Precipitation (GSMaP) Project, Precipitation Measurements from Space) , 2009 .

[75]  R. Houze,et al.  Stratiform Precipitation Processes in Cyclones Passing over a Coastal Mountain Range , 2018 .

[76]  Christian D. Kummerow,et al.  The Evolution of the Goddard Profiling Algorithm to a Fully Parametric Scheme , 2015 .

[77]  Benjamin T. Johnson,et al.  The Microwave Radiative Properties of Falling Snow Derived from Nonspherical Ice Particle Models. Part II: Initial Testing Using Radar, Radiometer and In Situ Observations , 2016 .

[78]  Chris Kidd,et al.  Global precipitation measurements for validating climate models , 2017 .

[79]  S. Moore,et al.  A Regional Climatography of West Nile, Uganda, to Support Human Plague Modeling , 2012 .

[80]  Toshio Iguchi,et al.  Intercomparison of Attenuation Correction Methods for the GPM Dual-Frequency Precipitation Radar , 2015 .

[81]  Chris Kidd,et al.  Comparison of Precipitation Derived from the ECMWF Operational Forecast Model and Satellite Precipitation Datasets , 2013 .

[82]  Dalia Kirschbaum,et al.  Role of Earth Observation Data in Disaster Response and Recovery: From Science to Capacity Building , 2016 .

[83]  V. Chandrasekar,et al.  Methodology for Aligning and Comparing Spaceborne Radar and Ground-Based Radar Observations , 2003 .

[84]  Viviana Maggioni,et al.  A Review of Merged High-Resolution Satellite Precipitation Product Accuracy during the Tropical Rainfall Measuring Mission (TRMM) Era , 2016 .

[85]  M. Zupanski,et al.  Impact of Assimilated Precipitation-Sensitive Radiances on the NU-WRF Simulation of the West African Monsoon , 2017 .

[86]  E. O'connor,et al.  The CloudSat mission and the A-train: a new dimension of space-based observations of clouds and precipitation , 2002 .

[87]  Sujay V. Kumar,et al.  Calibration to Improve Forward Model Simulation of Microwave Emissivity at GPM Frequencies Over the U.S. Southern Great Plains , 2015, IEEE Transactions on Geoscience and Remote Sensing.

[88]  Riko Oki,et al.  Current status of GPM/DPR level 1 algorithm development and DPR calibration , 2015, 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).

[89]  Elena Volpi,et al.  Raindrop size distribution: Fitting performance of common theoretical models , 2016 .

[90]  Riko Oki,et al.  Precipitation rates estimated with GPM's Dual-frequency Radar , 2016, 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).

[91]  Riko Oki,et al.  Evaluation of Precipitation Estimates by at-Launch Codes of GPM/DPR Algorithms Using Synthetic Data from TRMM/PR Observations , 2014, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[92]  S. Joseph Munchak,et al.  Evaluation of precipitation detection over various surfaces from passive microwave imagers and sounders , 2013 .

[93]  S. Christopher,et al.  Dual-Polarization Radar Characteristics of an Apartment Fire , 2009 .

[94]  Riko Oki,et al.  THE GLOBAL PRECIPITATION MEASUREMENT (GPM) MISSION FOR SCIENCE AND SOCIETY. , 2017, Bulletin of the American Meteorological Society.

[95]  Riko Oki,et al.  A Statistical Method for Reducing Sidelobe Clutter for the Ku-Band Precipitation Radar on Board the GPM Core Observatory , 2016 .

[96]  B. Colle,et al.  Structure and Evolution of a Warm Frontal Precipitation Band during the GPM Cold Season Precipitation Experiment (GCPEx) , 2015 .

[97]  Dalia Kirschbaum,et al.  A dynamic landslide hazard assessment system for Central America and Hispaniola , 2015 .

[98]  M. Alexander,et al.  Tropical Precipitation Variability and Convectively Coupled Equatorial Waves on Submonthly Time Scales in Reanalyses and TRMM , 2013 .

[99]  Yang Hong,et al.  Precipitation Extremes Estimated by GPCP and TRMM: ENSO Relationships , 2007 .

[100]  K. Lau,et al.  Characteristics of Precipitation, Cloud, and Latent Heating Associated with the Madden-Julian Oscillation , 2010 .

[101]  G. Thompson,et al.  Evaluation of convection‐permitting model simulations of cloud populations associated with the Madden‐Julian Oscillation using data collected during the AMIE/DYNAMO field campaign , 2014 .

[102]  Chuntao Liu,et al.  Global distribution of deep convection reaching tropopause in 1 year GPM observations , 2016 .

[103]  D. Kirschbaum,et al.  Spatial and temporal analysis of a global landslide catalog , 2015 .

[104]  Christian D. Kummerow,et al.  An Observationally Generated A Priori Database for Microwave Rainfall Retrievals , 2011 .

[105]  Darren McKague,et al.  Intercalibrating the GPM constellation using the GPM Microwave Imager (GMI) , 2015, 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).

[106]  Alexander Khain,et al.  WRF-SBM Simulations of Melting-Layer Structure in Mixed-Phase Precipitation Events Observed during LPVEx , 2014 .

[107]  P. Joe,et al.  So, how much of the Earth's surface is covered by rain gauges? , 2014, Bulletin of the American Meteorological Society.

[108]  C. Kummerow,et al.  Precipitation-Top Heights of Heavy Orographic Rainfall in the Asian Monsoon Region , 2016 .

[109]  A. Hou,et al.  The Global Precipitation Measurement Mission , 2014 .

[110]  R. Allan,et al.  A multisatellite climatology of clouds, radiation, and precipitation in southern West Africa and comparison to climate models , 2016 .

[111]  Alejandro N. Flores,et al.  Dynamical Precipitation Downscaling for Hydrologic Applications Using WRF 4D-Var Data Assimilation: Implications for GPM Era , 2015 .

[112]  Andrew J. Newman,et al.  Presenting the Snowflake Video Imager (SVI) , 2009 .

[113]  Benjamin T. Johnson,et al.  Evaluation of the GPM-DPR snowfall detection capability: Comparison with CloudSat-CPR , 2017 .

[114]  Kwo-Sen Kuo,et al.  The Microwave Radiative Properties of Falling Snow Derived from Nonspherical Ice Particle Models. Part I: An Extensive Database of Simulated Pristine Crystals and Aggregate Particles, and Their Scattering Properties , 2016 .

[115]  V. Chandrasekar,et al.  Global Precipitation Measurement Cold Season Precipitation Experiment (GCPEx): For Measurement Sake Let it Snow , 2015 .

[116]  W. Olson,et al.  A Consistent Treatment of Microwave Emissivity and Radar Backscatter for Retrieval of Precipitation over Water Surfaces. , 2016, Journal of atmospheric and oceanic technology.

[117]  Thomas Stanley,et al.  A heuristic approach to global landslide susceptibility mapping , 2017, Natural Hazards.

[118]  B. Zaitchik,et al.  Abundance of water bodies is critical to guide mosquito larval control interventions and predict risk of mosquito-borne diseases , 2013, Parasites & Vectors.

[119]  V. Chandrasekar,et al.  Characterizing falling snow using multifrequency dual‐polarization measurements , 2014 .

[120]  Li Li,et al.  An Evaluation of Microwave Land Surface Emissivities Over the Continental United States to Benefit GPM-Era Precipitation Algorithms , 2013, IEEE Transactions on Geoscience and Remote Sensing.

[121]  Assimilation of GPM Microwave Imager Clear-Sky Radiance in Improving Hurricane Forecasts , 2017 .

[122]  N Bharadwaj,et al.  THE MIDLATITUDE CONTINENTAL CONVECTIVE CLOUDS EXPERIMENT (MC3E). , 2016, Bulletin of the American Meteorological Society.

[123]  V. Chandrasekar,et al.  Describing the Shape of Raindrop Size Distributions Using Uncorrelated Raindrop Mass Spectrum Parameters , 2014 .

[124]  N. Bormann,et al.  The growing impact of satellite observations sensitive to humidity, cloud and precipitation , 2017 .

[125]  Guosheng Liu,et al.  A Parameterization of the Probability of Snow–Rain Transition , 2015 .

[126]  Atsushi Hamada,et al.  Improvements in Detection of Light Precipitation with the Global Precipitation Measurement Dual-Frequency Precipitation Radar (GPM DPR) , 2016 .