Whitaker, J. S., and K. M. Weickmann, 2001: Subseasonal variations of tropical convection and week two prediction of wintertime western North American rainfall. J. Climate, 14, 3279-3288.


ABSTRACT

A statistical prediction model for weekly rainfall during winter over western North America is developed that uses tropical outgoing longwave radiation (OLR) anomalies as a predictor. The effects of El Niño-Southern Oscillation (ENSO) are linearly removed from the OLR to isolate the predictive utility of subseasonal variations in tropical convection. A single canonical correlation (CCA) mode accounts for most of the predictable signal. The rank correlation between this mode and observed rainfall anomalies over southern California is 0.2 for a 2-week lag, which is comparable to correlation between a weekly ENSO index and weekly rainfall in this region. This corresponds to a doubling of the risk of extreme rainfall in southern California when the projection of tropical OLR on the leading CCA mode two weeks prior is extremely large, as compared with times when it is extremely small. "Extreme" is defined as being in the upper or lower quintile of the probability distribution.

The leading CCA mode represents suppressed convection in the equatorial Indian Ocean and enhanced convection just south of the equator east of the date line. OLR regressed on the time series of this mode shows an eastward progression of the suppressed region to just south of the Philippines at the time of maximum California rainfall enhancement. The region of enhanced convection east of the date line remains quasi stationary. Associated with this tropical OLR evolution is the development of upper-tropospheric westerly wind anomalies near 30°N in the eastern Pacific. Synoptic-scale weather systems are steered farther east toward California by these enhanced westerlies.

Because most operational weather prediction models do not accurately simulate subseasonal variations in tropical convection, statistical prediction models such as the one presented here may prove useful in augmenting numerical predictions. An analysis of 4 yr of operational week-2 ensemble predictions indicates that the level of skill provided by the statistical model is comparable to that of the operational ensemble mean. Given that by week 2 the operational forecast model has lost its ability to represent convectively coupled circulation associated with the subseasonal tropical convective variability, the statistical model provides essentially independent information for the forecaster.