HR: 16:00h
AN: A44A-03    [Abstracts]
TI: Storm track predictability on seasonal to decadal scales
AU: * Compo, G P
EM: compo@colorado.edu
AF: NOAA-CIRES Climate Diagnostics Center, 325 Broadway R/CDC1, Boulder, CO 80305 United States
AU: Sardeshmukh, P D
EM: prashant.d.sardeshmukh@noaa.gov
AF: NOAA-CIRES Climate Diagnostics Center, 325 Broadway R/CDC1, Boulder, CO 80305 United States
AB: This talk is concerned with estimating the predictable variation of extratropical daily weather statistics ("storm tracks") associated with global sea surface temperature (SST) changes on interannual to interdecadal scales, and its magnitude relative to the unpredictable noise. The SST-forced stormtrack signal in each northern winter in 1950-2004 is estimated as the mean stormtrack anomaly in an ensemble of atmospheric general circulation model (AGCM) integrations for that winter with prescribed observed SSTs. Since the stormtrack signals cannot be derived directly from the archived monthly AGCM output, they are diagnosed from the SST-forced winter-mean 200 mb height signals using an empirical linear stormtrack model (STM). For two particular winters, the El Nino of JFM 1987 and the La Nina of JFM 1989, the stormtrack signals and noise are estimated directly, and more accurately, from additional large ensembles of AGCM integrations. The linear STM is remarkably successful at capturing the AGCM's stormtrack signal in these two winters, and is thus also suitable for estimating the signal in other winters. Our principal conclusion is that a predictable SST-forced stormtrack signal exists in many winters, but its strength and pattern can change substantially from winter to winter. The pattern correlation of the SST-forced and observed stormtrack anomalies is high enough in the Pacific-North American sector to be of practical use. In the Euro-Atlantic region, we find much lower correlations, which we argue arise from substantial AGCM error in representing the regional response to tropical SST forcing, rather than intrinsically low stormtrack predictability.
DE: 1610 Atmosphere (0315, 0325)
SC: Atmospheric Sciences [A]
MN: 2005 Joint Assembly