Radar-rainfall estimation algorithms of Hydro-NEXRAD

Hydro-NEXRAD is a prototype software system that provides hydrology and water resource communities with ready access to the vast data archives of the U.S. weather radar network known as NEXRAD (Next Generation Weather Radar). This paper describes radar-rainfall estimation algorithms and their modular components used in the Hydro-NEXRAD system to generate rainfall products to be delivered to users. A variety of customized modules implemented in Hydro-NEXRAD perform radar-reflectivity data processing, produce radar-rainfall maps with user-requested space and time resolution, and combine multiple radar data for basins covered by multiple radars. System users can select rainfall estimation algorithms that range from simple (‘Quick Look’) to complex and computing-intensive (‘Hi-Fi’). The ‘Pseudo NWS PPS’ option allows close comparison with the algorithm used operationally by the US National Weather Service. The ‘Custom’ algorithm enables expert users to specify values for many of the parameters in the algorithm modules according to their experience and expectations. The Hydro-NEXRAD system, with its rainfall-estimation algorithms, can be used by both novice and expert users who need rainfall estimates as references or as input to their hydrologic modelling and forecasting applications

[1]  J. Marshall,et al.  THE DISTRIBUTION OF RAINDROPS WITH SIZE , 1948 .

[2]  A. Bemis,et al.  A QUANTITATIVE STUDY OF THE “BRIGHT BAND” IN RADAR PRECIPITATION ECHOES , 1950 .

[3]  Louis J. Battan,et al.  Radar Observation of the Atmosphere , 1973 .

[4]  I. Zawadzki.  The quantitative interpretation of weather radar measurements , 1982 .

[5]  D. Zrnic,et al.  Doppler Radar and Weather Observations , 1984 .

[6]  P. M. Austin,et al.  Relation between Measured Radar Reflectivity and Surface Rainfall , 1987 .

[7]  Witold F. Krajewski,et al.  Cokriging radar‐rainfall and rain gage data , 1987 .

[8]  F. P. Kapinos,et al.  Hydrologic unit maps , 1987 .

[9]  Guy Delrieu,et al.  Rain Measurement by Raingage-Radar Combination: A Geostatistical Approach , 1988 .

[10]  David B. Wolff,et al.  General Probability-matched Relations between Radar Reflectivity and Rain Rate , 1993 .

[11]  Frédéric Fabry,et al.  High resolution rainfall measurements by radar for very small basins: the sampling problem reexamined , 1994 .

[12]  Witold F. Krajewski,et al.  Statistical Detection of Anomalous Propagation in Radar Reflectivity Patterns , 1994 .

[13]  M. Kitchen,et al.  Real-time correction of weather radar data for the effects of bright band, range and orographic growth in widespread precipitation , 1994 .

[14]  D. Rosenfeld,et al.  The Window Probability Matching Method for Rainfall Measurements with Radar , 1994 .

[15]  Robert L. Lee,et al.  The Application of RadarGauge Comparisons to Operational Precipitation Profile Corrections , 1995 .

[16]  Hervé Andrieu,et al.  Identification of Vertical Profiles of Radar Reflectivity for Hydrological Applications Using an Inverse Method. Part II: Formulation. , 1995 .

[17]  Frédéric Fabry,et al.  Long-Term Radar Observations of the Melting Layer of Precipitation and Their Interpretation , 1995 .

[18]  Dong-Jun Seo,et al.  An Intercomparison Study of NEXRAD Precipitation Estimates , 1996 .

[19]  W. Krajewski,et al.  A Comparison of Methods for Calculation of Radar-Rainfall Hourly Accumulations , 1996 .

[20]  Witold F. Krajewski,et al.  Efficient storage of weather radar data , 1997 .

[21]  Witold F. Krajewski,et al.  Efficient Storage of Weather Radar Data , 1997, Softw. Pract. Exp..

[22]  E. Anagnostou,et al.  Radar Rainfall Estimation for Ground Validation Studies of the Tropical Rainfall Measuring Mission , 1997 .

[23]  Dong-Jun Seo,et al.  The WSR-88D rainfall algorithm , 1998 .

[24]  Dong-Jun Seo,et al.  Real-time estimation of rainfall fields using radar rainfall and rain gage data , 1998 .

[25]  H. Andrieu,et al.  Identification of Vertical Profiles of Reflectivity from Volume Scan Radar Data , 1999 .

[26]  D. Maidment,et al.  Coordinate Transformations for Using NEXRAD Data in GIS-Based Hydrologic Modeling , 1999 .

[27]  Witold F. Krajewski,et al.  An Efficient Methodology for Detection of Anomalous Propagation Echoes in Radar Reflectivity Data Using Neural Networks , 2000 .

[28]  Jay P. Breidenbach,et al.  Real-time adjustment of range-dependent biases in WSR-88D rainfall estimates due to nonuniform vertical profile of reflectivity , 2000 .

[29]  W. Krajewski,et al.  Large-Sample Evaluation of Two Methods to Correct Range-Dependent Error for WSR-88D Rainfall Estimates , 2001 .

[30]  Cathy Kessinger.  The Radar Echo Classifier for the WSR-88D , 2001 .

[31]  Ezio Todini,et al.  A Bayesian technique for conditioning radar precipitation estimates to rain-gauge measurements , 2001 .

[32]  Emmanouil N. Anagnostou,et al.  The Use of TRMM Precipitation Radar Observations in Determining Ground Radar Calibration Biases , 2001 .

[33]  C. Kessinger,et al.  Mitigating Ground Clutter Contamination in the WSR-88 D , 2002 .

[34]  Matthias Steiner,et al.  Use of Three-Dimensional Reflectivity Structure for Automated Detection and Removal of Nonprecipitating Echoes in Radar Data , 2002 .

[35]  Witold F. Krajewski,et al.  Radar hydrology: rainfall estimation. , 2002 .

[36]  J. Gourley,et al.  Automated Detection of the Bright Band Using WSR-88D Data , 2003 .

[37]  Jian Zhang,et al.  Four-Dimensional Dynamic Radar Mosaic , 2004 .

[38]  Ashish Sharma,et al.  Application of Scaling in Radar Reflectivity for Correcting Range-Dependent Bias in Climatological Radar Rainfall Estimates , 2004 .

[39]  Bong-Chul Seo,et al.  Towards Better Utilization of NEXRAD Data in Hydrology: An Overview of Hydro-NEXRAD , 2005 .

[40]  Jian Zhang,et al.  Constructing Three-Dimensional Multiple-Radar Reflectivity Mosaics: Examples of Convective Storms and Stratiform Rain Echoes , 2005 .

[41]  Jian Zhang,et al.  The National Mosaic and multisensor QPE (NMQ) Project - Status and plans for a community testbed for high-resolution multisensor quantitative precipitation estimation (QPE) over the United States , 2005 .

[42]  Marc Berenguer,et al.  A Fuzzy Logic Technique for Identifying Nonprecipitating Echoes in Radar Scans , 2006 .

[43]  Gyu Won Lee,et al.  Identification and Removal of Ground Echoes and Anomalous Propagation Using the Characteristics of Radar Echoes , 2006 .

[44]  Arthur Witt,et al.  A Real-Time, Three-Dimensional, Rapidly Updating, Heterogeneous Radar Merger Technique for Reflectivity, Velocity, and Derived Products , 2006 .

[45]  J. McGinley,et al.  Improving QPE and Very Short Term QPF: An Initiative for a Community-Wide Integrated Approach , 2007 .

[46]  K. Droegemeier,et al.  PROJECT CRAFT A Real-Time Delivery System for Nexrad Level II Data Via The Internet , 2007 .

[47]  G. Villarini,et al.  Product-Error-Driven Uncertainty Model for Probabilistic Quantitative Precipitation Estimation with NEXRAD Data , 2007 .

[48]  Travis M. Smith,et al.  An Automated Technique to Quality Control Radar Reflectivity Data , 2007 .

[49]  Jian Zhang,et al.  Brightband Identification Based on Vertical Profiles of Reflectivity from the WSR-88D , 2008 .

[50]  J. Jaime Gómez-Hernández,et al.  A non-parametric automatic blending methodology to estimate rainfall fields from rain gauge and radar data , 2009 .

[51]  W. Krajewski,et al.  Scale Dependence of Radar Rainfall Uncertainty: Initial Evaluation of NEXRAD’s New Super-Resolution Data for Hydrologic Applications , 2010 .

[52]  G. Villarini,et al.  Sensitivity Studies of the Models of Radar-Rainfall Uncertainties , 2010 .

[53]  Witold F. Krajewski,et al.  Hydro-NEXRAD: Metadata computation and use , 2011 .