Probabilistic and Ensemble Representations of the Uncertainty in an IR/Microwave Satellite Precipitation Product

Abstract While current satellite techniques are theoretically capable of producing precipitation estimates to image pixel resolutions, significant uncertainty is present in such high-resolution products. This uncertainty is frequently difficult to characterize using scalar measures of additive error. This paper describes the development of a methodology to more fully represent the uncertainty in satellite precipitation retrievals. The methodology derives conditional probability distribution functions of rainfall on a pixel-by-pixel basis. This array of distribution functions is then combined with a simple model of the spatiotemporal covariance structure of the uncertainty in the precipitation field to stochastically generate an ensemble precipitation product. Each element of the ensemble represents an equiprobable realization of the precipitation field that is consistent with the original satellite data while containing a random element commensurate with the uncertainty in that field. The technique has be...

[1]  J. Stedinger,et al.  Water resource systems planning and analysis , 1981 .

[2]  Jonathan R. M. Hosking,et al.  MODELLING THE EFFECTS OF SPATIAL VARIABILITY IN RAINFALL ON CATCHMENT RESPONSE. : 1. FORMULATION AND CALIBRATION OF A STOCHASTIC RAINFALL FIELD MODEL , 1996 .

[3]  T. Wigley,et al.  Precipitation predictors for downscaling: observed and general circulation model relationships , 2000 .

[4]  Frank S. Marzano,et al.  Multivariate statistical integration of Satellite infrared and microwave radiometric measurements for rainfall retrieval at the geostationary scale , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[5]  J. Hosking L‐Moments: Analysis and Estimation of Distributions Using Linear Combinations of Order Statistics , 1990 .

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

[7]  W. Woodley,et al.  Rain Estimation from Geosynchronous Satellite Imagery—Visible and Infrared Studies , 1978 .

[8]  Robert F. Adler,et al.  A Satellite Infrared Technique to Estimate Tropical Convective and Stratiform Rainfall , 1988 .

[9]  Patrick L. Odell,et al.  Applied Statistics in Atmospheric Science. Part A: Frequencies and Curve Fitting. , 1979 .

[10]  P. Bauer,et al.  Model Rain and Clouds over Oceans: Comparison with SSM/I Observations , 2003 .

[11]  R. Ababou,et al.  Implementation of the three‐dimensional turning bands random field generator , 1989 .

[12]  S. Sorooshian,et al.  A Microwave Infrared Threshold Technique to Improve the GOES Precipitation Index , 1999 .

[13]  J. Janowiak,et al.  CMORPH: A Method that Produces Global Precipitation Estimates from Passive Microwave and Infrared Data at High Spatial and Temporal Resolution , 2004 .

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

[15]  P. Bauer,et al.  Algorithms for the retrieval of rainfall from passive microwave measurements , 1994 .

[16]  Sharon E. Nicholson,et al.  Validation of TRMM and Other Rainfall Estimates with a High-Density Gauge Dataset for West Africa. Part I: Validation of GPCC Rainfall Product and Pre-TRMM Satellite and Blended Products , 2003 .

[17]  R. A. Scofield,et al.  The role of orographic and parallax corrections on real time high resolution satellite rainfall rate distribution , 2002 .

[18]  Mahmood R. Azimi-Sadjadi,et al.  A study of cloud classification with neural networks using spectral and textural features , 1999, IEEE Trans. Neural Networks.

[19]  T. Bellerby,et al.  A Feature-Based Approach to Satellite Precipitation Monitoring Using Geostationary IR Imagery , 2004 .

[20]  S. Sorooshian,et al.  Parameter estimation of GOES precipitation index at different calibration timescales , 2000 .

[21]  S. Sorooshian,et al.  Evaluation of PERSIANN system satellite-based estimates of tropical rainfall , 2000 .

[22]  J. Filliben The Probability Plot Correlation Coefficient Test for Normality , 1975 .

[23]  Chris Kidd,et al.  Rainfall Estimation from a Combination of TRMM Precipitation Radar and GOES Multispectral Satellite Imagery through the Use of an Artificial Neural Network , 2000 .

[24]  Chong-yu Xu From GCMs to river flow: a review of downscaling methods and hydrologic modelling approaches , 1999 .

[25]  K. Beven,et al.  Similarity and scale in catchment storm response , 1990 .

[26]  R. Wilby,et al.  Statistical downscaling of hydrometeorological variables using general circulation model output , 1998 .

[27]  Erich Franz Stocker,et al.  Analysis of TRMM 3-Hourly Multi-Satellite Precipitation Estimates Computed in Both Real and Post-Real Time , 2002 .

[28]  Paul O'Connell,et al.  Modelling the effects of spatial variability in rainfall on catchment response. 2. Experiments with distributed and lumped models , 1996 .

[29]  Sharon E. Nicholson,et al.  Validation of TRMM and Other Rainfall Estimates with a High-Density Gauge Dataset for West Africa. Part II: Validation of TRMM Rainfall Products , 2003 .

[30]  E. Todini,et al.  Stochastic rainfall interpolation and downscaling , 2001 .

[31]  A. Mantoglou,et al.  The Turning Bands Method for simulation of random fields using line generation by a spectral method , 1982 .

[32]  Chris Kidd,et al.  Satellite Rainfall Estimation Using a Combined Pasive Microwave and Infrared Algorithm. , 2003 .

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

[34]  Roland T. Chin,et al.  Determination of Rainfall Rates from GOES Satellite Images by a Pattern Recognition Technique , 1985 .

[35]  John E. Janowiak,et al.  Sampling-Induced Conditional Biases in Satellite Climate-Scale Rainfall Estimates , 1996 .

[36]  Luca G. Lanza,et al.  A conditional simulation model of intermittent rain fields , 2000 .

[37]  Witold F. Krajewski,et al.  Error Uncertainty Analysis of GPCP Monthly Rainfall Products: A Data-Based Simulation Study , 2003 .

[38]  B. N. Meisner,et al.  The Relationship between Large-Scale Convective Rainfall and Cold Cloud over the Western Hemisphere during 1982-84 , 1987 .

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

[40]  Aristotelis Mantoglou,et al.  Digital simulation of multivariate two- and three-dimensional stochastic processes with a spectral turning bands method , 1987, Mathematical Geology.

[41]  A. Gruber,et al.  GOES Multispectral Rainfall Algorithm (GMSRA) , 2001 .

[42]  M. Todd,et al.  A Combined Satellite Infrared and Passive Microwave Technique for Estimation of Small-Scale Rainfall , 1999 .

[43]  Frank S. Marzano,et al.  A Neural Networks–Based Fusion Technique to Estimate Half-Hourly Rainfall Estimates at 0.1° Resolution from Satellite Passive Microwave and Infrared Data , 2004 .

[44]  Witold F. Krajewski,et al.  Uncertainty Analysis of the TRMM Ground-Validation Radar-Rainfall Products: Application to the TEFLUN-B Field Campaign , 2002 .

[45]  C. Bretherton,et al.  Statistical Precipitation Downscaling over the Northwestern United States Using Numerically Simulated Precipitation as a Predictor , 2003 .