The GPM Combined Algorithm

AbstractIn this paper, the operational Global Precipitation Measurement (GPM) mission combined radar–radiometer algorithm is thoroughly described. The operational combined algorithm is designed to reduce uncertainties in GPM Core Observatory precipitation estimates by effectively integrating complementary information from the GPM Dual-Frequency Precipitation Radar (DPR) and the GPM Microwave Imager (GMI) into an optimal, physically consistent precipitation product. Although similar in many respects to previously developed combined algorithms, the GPM combined algorithm has several unique features that are specifically designed to meet the GPM objectives of deriving, based on GPM Core Observatory information, accurate and physically consistent precipitation estimates from multiple spaceborne instruments, and ancillary environmental data from reanalyses. The algorithm features an optimal estimation framework based on a statistical formulation of the Gauss–Newton method, a parameterization for the nonuniform...

[1]  C. Schumacher,et al.  Modeled and Observed Variations in Storm Divergence and Stratiform Rain Production in Southeastern Texas , 2012 .

[2]  Derek J. Posselt,et al.  CLOUDSAT: Adding a new dimension to a classical view of extratropical cyclones , 2008 .

[3]  David T. Bolvin,et al.  Improving the global precipitation record: GPCP Version 2.1 , 2009 .

[4]  Eric A. Smith,et al.  Bayesian estimation of precipitating cloud parameters from combined measurements of spaceborne microwave radiometer and radar , 1999, IEEE Trans. Geosci. Remote. Sens..

[5]  Jeffrey A. Jones,et al.  Use of the Surface Reference Technique for Path Attenuation Estimates from the TRMM Precipitation Radar , 2000 .

[6]  R. W. Numrich,et al.  A New Parallel Version of the DDSCAT Code for Electromagnetic Scattering from Big Targets , 2013 .

[7]  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 .

[8]  Ziad S. Haddad,et al.  The TRMM 'Day-1' Radar/Radiometer Combined Rain-Profiling Algorithm , 1997 .

[9]  A. Reynolds,et al.  History matching time-lapse seismic data using the ensemble Kalman filter with multiple data assimilations , 2012, Computational Geosciences.

[10]  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.

[11]  S. Durden,et al.  Impact of non-uniform beam filling on spaceborne cloud and precipitation radar retrieval algorithms , 2012, Asia-Pacific Environmental Remote Sensing.

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

[13]  V. N. Bringi,et al.  Estimation of Spatial Correlation of Drop Size Distribution Parameters and Rain Rate Using NASA's S-Band Polarimetric Radar and 2D Video Disdrometer Network: Two Case Studies from MC3E , 2015 .

[14]  Jimy Dudhia,et al.  Development of a next-generation regional weather research and forecast model. , 2001 .

[15]  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.

[16]  Peter Bauer,et al.  Correction of Three-Dimensional Effects for Passive Microwave Remote Sensing of Convective Clouds , 1998 .

[17]  Christian D. Kummerow,et al.  Combined Radar and Radiometer Analysis of Precipitation Profiles for a Parametric Retrieval Algorithm , 2005 .

[18]  G. Evensen.  Data Assimilation: The Ensemble Kalman Filter , 2006 .

[19]  Clemens Simmer,et al.  Evaluation of Radar Multiple-Scattering Effects from a GPM Perspective. Part II: Model Results , 2006 .

[20]  C. Kummerow,et al.  Combined Use of the Radar and Radiometer of TRMM to Estimate the Influence of Drop Size Distribution on Rain Retrievals , 2000 .

[21]  Robin J. Hogan,et al.  A Variational Scheme for Retrieving Rainfall Rate and Hail Reflectivity Fraction from Polarization Radar , 2007 .

[22]  Toshio Iguchi,et al.  Rain Type Classification Algorithm , 2007 .

[23]  Ali Tokay,et al.  An Experimental Study of Small-Scale Variability of Raindrop Size Distribution , 2010 .

[24]  Jeffrey A. Jones,et al.  An Initial Assessment of the Surface Reference Technique Applied to Data from the Dual-Frequency Precipitation Radar (DPR) on the GPM Satellite , 2015 .

[25]  Jeffrey L. Anderson.  Localization and Sampling Error Correction in Ensemble Kalman Filter Data Assimilation , 2012 .

[26]  Christian D. Kummerow,et al.  Global Precipitation Measurement , 2008 .

[27]  Nobuhiro Takahashi,et al.  Estimation of Path-Integrated Attenuation and Its Nonuniformity From TRMM/PR Range Profile Data , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[28]  L. Dagum,et al.  OpenMP: an industry standard API for shared-memory programming , 1998 .

[29]  Francisco J. Tapiador,et al.  An experiment to measure the spatial variability of rain drop size distribution using sixteen laser disdrometers , 2010 .

[30]  Emmanouil N. Anagnostou,et al.  Use of passive microwave observations in a radar rainfall-profiling algorithm , 2001 .

[31]  Toshio Iguchi,et al.  Uncertainties in the Rain Profiling Algorithm for the TRMM Precipitation Radar(1. Precipitation Radar (PR), Precipitation Measurements from Space) , 2009 .

[32]  S. Joseph Munchak,et al.  A Modular Optimal Estimation Method for Combined Radar–Radiometer Precipitation Profiling , 2011 .

[33]  W. Olson,et al.  The microwave properties of simulated melting precipitation particles: sensitivity to initial melting. , 2016, Atmospheric measurement techniques.

[34]  Tuomo Kauranne.  An Introduction to Parallel Processing in Meteorology , 1990 .

[35]  William S. Olson,et al.  Precipitating Snow Retrievals from Combined Airborne Cloud Radar and Millimeter-Wave Radiometer Observations , 2008 .

[36]  David A. Patterson,et al.  Computer architecture (2nd ed.): a quantitative approach , 1996 .

[37]  A. Waldvogel,et al.  Criteria for the Detection of Hail Cells , 1979 .

[38]  Simone Tanelli,et al.  A Robust Dual-Frequency Radar Profiling Algorithm , 2011 .

[39]  Thomas Meissner,et al.  The Emissivity of the Ocean Surface Between 6 and 90 GHz Over a Large Range of Wind Speeds and Earth Incidence Angles , 2012, IEEE Transactions on Geoscience and Remote Sensing.

[40]  F. Joseph Turk,et al.  Measuring Precipitation from Space: EURAINSAT and the Future , 2007 .

[41]  Liang Liao,et al.  On modeling air/spaceborne Radar returns in the melting layer , 2005, IEEE Transactions on Geoscience and Remote Sensing.

[42]  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 .

[43]  Alessandro Battaglia,et al.  Fast Lidar and Radar Multiple-Scattering Models. Part II: Wide-Angle Scattering Using the Time-Dependent Two-Stream Approximation , 2008 .

[44]  E. Anagnostou,et al.  Retrieval of Precipitation Profiles from Multiresolution, Multifrequency, Active and Passive Microwave Observations , 2004 .

[45]  P. Bauer,et al.  Tropical Rainfall Measuring Mission microwave imaging capabilities for the observation of rain clouds , 1998 .

[46]  Robert A. Black,et al.  The Concept of “Normalized” Distribution to Describe Raindrop Spectra: A Tool for Cloud Physics and Cloud Remote Sensing , 2001 .

[47]  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 .

[48]  Filipe Aires,et al.  A Tool to Estimate Land‐Surface Emissivities at Microwave frequencies (TELSEM) for use in numerical weather prediction , 2011 .

[49]  P. Bauer,et al.  A Melting Layer Model for Passive/Active Microwave Remote Sensing Applications, Part 2: Simulation of Trmm Observations , 2013 .

[50]  David A. Patterson,et al.  Computer Architecture: A Quantitative Approach , 1969 .

[51]  Steven Platnick,et al.  Planning, implementation, and first results of the Tropical Composition, Cloud and Climate Coupling Experiment (TC4) , 2010 .

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

[53]  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.

[54]  R. Meneghini,et al.  Modified Hitschfeld-Bordan Equations for Attenuation-Corrected Radar Rain Reflectivity: Application to Nonuniform Beamfilling at Off-Nadir Incidence , 2013 .

[55]  C. Kummerow,et al.  The Tropical Rainfall Measuring Mission (TRMM) Sensor Package , 1998 .

[56]  Clemens Simmer,et al.  Evaluation of Radar Multiple-Scattering Effects from a GPM Perspective. Part I: Model Description and Validation , 2006 .

[57]  K. Okamoto,et al.  Rain profiling algorithm for the TRMM precipitation radar , 1997, IGARSS'97. 1997 IEEE International Geoscience and Remote Sensing Symposium Proceedings. Remote Sensing - A Scientific Vision for Sustainable Development.

[58]  Jungang Miao,et al.  Sensitivity of microwave brightness temperatures to hydrometeors in a tropical deep convective cloud system at 89–190 GHz , 2005 .

[59]  Christian D. Kummerow,et al.  On the accuracy of the Eddington approximation for radiative transfer in the microwave frequencies , 1993 .

[60]  P. Rosenkranz.  Water vapor microwave continuum absorption: A comparison of measurements and models , 1998 .

[61]  Ralf Bennartz,et al.  Utilizing Spaceborne Radars to Retrieve Dry Snowfall , 2009 .

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