Uncertainty Analysis of the TRMM Ground-Validation Radar-Rainfall Products: Application to the TEFLUN-B Field Campaign

Efforts to validate the Tropical Rainfall Measuring Mission (TRMM) space-based rainfall products have encountered many difficulties and challenges. Of particular concern is the quality of the ground-based radar products—the main tool for validation analysis. This issue is addressed by analyzing the uncertainty in the maps of rain rate provided by the ground-validation radar. To look closely at factors that contribute to the uncertain performance of the radar products, this study uses high-quality rainfall observations from several surface sensors deployed during the Texas and Florida Underflights (TEFLUN-B) field experiment in central Florida during the summer of 1998. A statistical analysis of the radar estimates is performed by comparison with a high-density rain gauge cluster. The approach followed in the current analysis accounts for the recognized effect of rainfall’s spatial variability in order to assess its contribution to radar differences from independent reference observations. The study provides uncertainty quantification of the radar estimates based on classification into light and heavy rain types. The methodology and the reported results should help in future studies that use radar-rainfall products to validate the various TRMM products, or in any other relevant hydrological applications.

[1]  Emmanouil N. Anagnostou,et al.  Uncertainty Quantification of Mean-Areal Radar-Rainfall Estimates , 1999 .

[2]  I. Rodríguez‐Iturbe,et al.  Random Functions and Hydrology , 1984 .

[3]  Estimating correlations in multivariate streamflow models , 1981 .

[4]  Witold F. Krajewski,et al.  Sampling Errors of Tipping-Bucket Rain Gauge Measurements , 2001 .

[5]  B. Kedem,et al.  On the lognormality of rain rate. , 1987, Proceedings of the National Academy of Sciences of the United States of America.

[6]  Edwin Kessler,et al.  On correlation, with applications to the radar and raingage measurement of rainfall , 1994 .

[7]  C. Kowalski.  On the Effects of Non‐Normality on the Distribution of the Sample Product‐Moment Correlation Coefficient , 1972 .

[8]  J. E. Glynn,et al.  Numerical Recipes: The Art of Scientific Computing , 1989 .

[9]  J. Theon,et al.  Tropical rainfall measuring mission (TRMM) , 1987 .

[10]  Witold F. Krajewski,et al.  Evaluating NEXRAD Multisensor Precipitation Estimates for Operational Hydrologic Forecasting , 2000 .

[11]  Chris G. Collier,et al.  Precipitation Measurement and Hydrology , 1990 .

[12]  D. Sharon,et al.  The spottiness of rainfall in a desert area , 1972 .

[13]  Warner L. Ecklund,et al.  Classification of Precipitating Clouds in the Tropics Using 915-MHz Wind Profilers , 1995 .

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

[15]  Matthias Steiner,et al.  Climatological Characterization of Three-Dimensional Storm Structure from Operational Radar and Rain Gauge Data , 1995 .

[16]  R. Berndtsson.  On the use of cross-correlation analysis in studies of patterns of rainfall variability , 1987 .

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

[18]  M. Robinson,et al.  Climatological processing and product development for the TRMM ground validation program , 2000 .

[19]  James W. Wilson,et al.  Radar Measurement of Rainfall—A Summary , 1979 .

[20]  W. Krajewski,et al.  On the estimation of radar rainfall error variance , 1999 .

[21]  Anthony R. Olsen,et al.  Comparison of Gage and Radar Methods of Convective Rain Measurement , 1975 .

[22]  Kunio Shimizu,et al.  A Bivariate Mixed Lognormal Distribution with an Analysis of Rainfall Data , 1993 .

[23]  Warner L. Ecklund,et al.  UHF Wind Profilers: A New Tool for Diagnosing Tropical Convective Cloud Systems , 1994 .

[24]  W. Krajewski,et al.  Estimation of Rainfall Interstation Correlation , 2001 .

[25]  David T. Bolvin,et al.  Tropical Rainfall Distributions Determined Using TRMM Combined with Other Satellite and Rain Gauge Information , 2000 .

[26]  F. Huff.  Spatial distribution of rainfall rates , 1970 .

[27]  Chin-Diew Lai,et al.  Robustness of the sample correlation - the bivariate lognormal case , 1999, Adv. Decis. Sci..

[28]  K. Georgakakos,et al.  Observation and Analysis of Midwestern Rain Rates. , 1994 .

[29]  Floyd A. Huff,et al.  Spatial Correlations of Storm, Monthly and Seasonal Precipitation , 1969 .

[30]  Robert A. Houze,et al.  Comparison of Radar Data from the TRMM Satellite and Kwajalein Oceanic Validation Site , 2000 .

[31]  M. Kitchen,et al.  Representativeness errors in comparisons between radar and gauge measurements of rainfall , 1992 .

[32]  Jothiram Vivekanandan,et al.  A Comparison of Radar Reflectivity Estimates of Rainfall from Collocated Radars , 1999 .

[33]  William H. Press,et al.  Numerical recipes in C. The art of scientific computing , 1987 .

[34]  I. Zawadzki,et al.  On Radar-Raingage Comparison , 1975 .

[35]  Michael Robinson,et al.  Evolving Improvements to TRMM Ground Validation Rainfall Estimates , 2000 .

[36]  Jean-Dominique Creutin,et al.  A method for delineating and estimating rainfall fields , 1992 .