Submitted to: American Meteorological Society Proceedings
Publication Type: Abstract Only
Publication Acceptance Date: September 16, 2003
Publication Date: September 16, 2003
Citation: GARBRECHT, J.D., SCHNEIDER, J.M., ZHANG, X.J. DOWNSCALING NOAA'S SEASONAL CLIMATE FORECASTS TO PREDICT HYDROLOGIC RESPONSE. AVAILABLE FROM: http://ams.confex.com/ams/84annual/18hydro/abstracts/68223.htm AMERICAN METEOROLOGICAL SOCIETY PROCEEDINGS . Interpretive Summary: Abstract Only.
Technical Abstract: The impact of NOAA's seasonal climate forecasts on water resources must be assessed to establish the utility of the forecast for water resources decision making. To this end, the probabilistic characteristics of a seasonal climate forecast must be translated into a corresponding probabilistic hydrologic response. This can be achieved by modeling the hydrologic system for the range of forecasted conditions. A method to adjust the precipitation parameters of daily weather generators to reflect NOAA's forecasted seasonal precipitation conditions is the object of this paper. For illustration purposes the experimental stochastic weather generator SYNTOR is used. The drivers of SYNTOR are probability measures of occurrence of precipitation on any given day and distribution parameters of daily precipitation amount. To adjust the precipitation parameters for SYNTOR, NOAA's 3-month overlapping forecast departures are first transformed into non-overlapping monthly values. Thereafter, the observed relationship between monthly precipitation amount, number of rainy days and transitional probabilities at the location of interest is used to partition the forecasted precipitation departure into a forecasted departure for daily precipitation amount, number of rainy days, and sequence of rainy days. Once the number and sequence of rainy days are generated, the forecasted change in precipitation amount is imposed by adjusting the generated daily precipitation by the percent change in forecasted daily precipitation amount. This forecasted daily weather can then be used to establish the hydrologic response to the forecast.