|
Activity Number:
|
453
|
|
Type:
|
Contributed
|
|
Date/Time:
|
Wednesday, August 6, 2008 : 2:00 PM to 3:50 PM
|
|
Sponsor:
|
Section on Statistics and the Environment
|
| Abstract - #302162 |
|
Title:
|
Generalized Linear Modeling Approach to Stochastic Weather Generators
|
|
Author(s):
|
Eva M. Furrer*+ and Richard W. Katz
|
|
Companies:
|
National Center for Atmospheric Research and National Center for Atmospheric Research
|
|
Address:
|
1850 Table Mesa Dr, Boulder, CO, 80305,
|
|
Keywords:
|
GLM ; ENSO ; Climate ; Weather ; Precipitation modeling ; Downscaling
|
|
Abstract:
|
Stochastic weather generators are a popular method to produce synthetic sequences of daily weather. We demonstrate how an extension of the Richardson model based on generalized linear models (GLMs) can provide a general modeling framework, allowing for the straightforward incorporation of annual cycles as well as other covariates (e.g. an index of the El Nino-Southern Oscillation (ENSO) phenomenon) into stochastic weather generators (downscaling). We apply the GLM technique to daily time series of weather variables (i.e. precipitation as well as minimum and maximum temperature) at Pergamino, Argentina. Besides annual cycles, the fit is significantly improved by permitting both transition probabilities of the first-order Markov chain for daily precipitation occurrence, as well as the means of both daily minimum and maximum temperature, to depend on the ENSO state.
|
