HR: 11:00h
AN: H32C-03    [Abstracts]
TI: Predictability of U.S. Winter Precipitation: Role of ENSO state in Developing Multimodel Combinations
AU: * Arumugam, S
EM: sankar_arumugam@ncsu.edu
AF: Department of Civil and Environmental Engineering, 2501 Stinson Drive, North Carolina State University, Raleigh, NC 27695-7908, United States
AU: Devineni, N
EM: ndevine@ncsu.edu
AF: Department of Civil and Environmental Engineering, 2501 Stinson Drive, North Carolina State University, Raleigh, NC 27695-7908, United States
AB: Recent research shows that operational climate forecasts obtained by combining different General Circulation Models (GCMs) have improved predictability in comparison to the predictability that could be obtained from a single GCM. In this study, we evaluate the skill of three GCMs in predicting the U.S. winter (December-February) precipitation conditioned on the state of El Nino-Southern Oscillation (ENSO). Using Nino3.4 as the conditioning variable, we show that the skill of GCMs in predicting the U.S winter precipitation is significant only when ENSO conditions exist. Under neutral ENSO conditions, predictability of three GCMs is statistically insignificant. Hence, we propose an algorithm for combining precipitation from multiple GCMs that considers the state of ENSO in developing multimodel ensembles of winter precipitation over the U.S. The approach basically identifies similar conditions or analogue years from the current state of Nino3.4 and then evaluates the average skill of the candidate GCMs during those conditions by computing the average Rank Probability Score (RPS). Multimodel ensembles of precipitation are then developed by drawing ensembles from each model in such a way that the model with low average RPS constitutes higher number of ensembles in the multimodel ensembles. The performance of multimodel ensembles is compared with individual model ensembles in predicting winter precipitation using various performance measures such as Rank Probability Skill Score (RPSS) and reliability plots.
DE: 1833 Hydroclimatology
DE: 1846 Model calibration (3333)
DE: 3305 Climate change and variability (1616, 1635, 3309, 4215, 4513)
DE: 3354 Precipitation (1854)
SC: Hydrology [H]
MN: 2007 Fall Meeting