Spatial‐temporal rainfall simulation using generalized linear models

We consider the problem of simulating sequences of daily rainfall at a network of sites in such a way as to reproduce a variety of properties realistically over a range of spatial scales. The properties of interest will vary between applications but typically will include some measures of “extreme” rainfall in addition to means, variances, proportions of wet days, and autocorrelation structure. Our approach is to fit a generalized linear model (GLM) to rain gauge data and, with appropriate incorporation of intersite dependence structure, to use the GLM to generate simulated sequences. We illustrate the methodology using a data set from southern England and show that the GLM is able to reproduce many properties at spatial scales ranging from a single site to 2000 km2 (the limit of the available data).

[1]  V. Isham,et al.  Changes in extreme wind speeds in NW Europe simulated by generalized linear models , 2006 .

[2]  Richard E. Chandler,et al.  On the use of generalized linear models for interpreting climate variability , 2005 .

[3]  Valerie Isham,et al.  Simulation and downscaling models for potential evaporation , 2003 .

[4]  The Wilson–Hilferty transformation is locally saddlepoint , 2003 .

[5]  R. Chandler,et al.  Analysis of rainfall variability using generalized linear models: A case study from the west of Ireland , 2002 .

[6]  V. Isham,et al.  An Analysis of Daily Maximum Wind Speed in Northwestern Europe Using Generalized Linear Models , 2002 .

[7]  M. Parlange,et al.  Statistics of extremes in hydrology , 2002 .

[8]  H. Wheater Progress in and prospects for fluvial flood modelling , 2002, Philosophical Transactions of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[9]  A. Bárdossy,et al.  Multivariate stochastic downscaling model for generating daily precipitation series based on atmospheric circulation , 2002 .

[10]  Re Chandler,et al.  GLIMCLIM: Generalized linear modelling for daily climate time series (software and user guide) , 2002 .

[11]  Theo Brandsma,et al.  Multisite simulation of daily precipitation and temperature in the Rhine Basin by nearest‐neighbor resampling , 2001 .

[12]  R. Washington,et al.  United Kingdom and Ireland precipitation variability and the North Atlantic sea‐level pressure field , 2001 .

[13]  David M. Zucker,et al.  Modelling and generating correlated binary variables , 2001 .

[14]  Demetris Koutsoyiannis,et al.  Generation of spatially consistent rainfall data , 2000 .

[15]  James P. Hughes,et al.  A spatiotemporal model for downscaling precipitation occurrence and amounts , 1999 .

[16]  D. Wilks,et al.  The weather generation game: a review of stochastic weather models , 1999 .

[17]  D. Wilks Multisite generalization of a daily stochastic precipitation generation model , 1998 .

[18]  A. D. Lunn,et al.  A note on generating correlated binary variables , 1998 .

[19]  P. Jones,et al.  Extension to the North Atlantic oscillation using early instrumental pressure observations from Gibraltar and south‐west Iceland , 1997 .

[20]  C. Klüppelberg,et al.  Modelling Extremal Events , 1997 .

[21]  Nanny Wermuth,et al.  Multivariate Dependencies: Models, Analysis and Interpretation , 1996 .

[22]  Peter Guttorp,et al.  A Nonhomogeneous Hidden Markov Model for Precipitation , 1996 .

[23]  J. Hurrell Decadal Trends in the North Atlantic Oscillation: Regional Temperatures and Precipitation , 1995, Science.

[24]  [Inference Based on Estimating Functions in the Presence of Nuisance Parameters]: Comment , 1995 .

[25]  PAUL EMBRECHTS,et al.  Modelling of extremal events in insurance and finance , 1994, Math. Methods Oper. Res..

[26]  A. Bárdossy,et al.  SPACE-TIME MODEL FOR DAILY RAINFALL USING ATMOSPHERIC CIRCULATION PATTERNS , 1992 .

[27]  J. H. Schuenemeyer,et al.  Generalized Linear Models (2nd ed.) , 1992 .

[28]  M. Piedmonte,et al.  A Method for Generating High-Dimensional Multivariate Binary Variates , 1991 .

[29]  Annette J. Dobson,et al.  An introduction to generalized linear models , 1991 .

[30]  P. McCullagh,et al.  Generalized Linear Models, 2nd Edn. , 1990 .

[31]  Brian Everitt,et al.  Principles of Multivariate Analysis , 2001 .

[32]  A. Barnston,et al.  Classification, seasonality and persistence of low-frequency atmospheric circulation patterns , 1987 .

[33]  Richard Coe,et al.  A Model Fitting Analysis of Daily Rainfall Data , 1984 .

[34]  Roger Stern,et al.  Fitting Models to Daily Rainfall Data , 1982 .

[35]  D. A. Williams,et al.  Extra‐Binomial Variation in Logistic Linear Models , 1982 .

[36]  R. Beverton,et al.  Institute of Hydrology , 1972, Nature.