92nd American Meteorological Society Annual Meeting (January 22-26, 2012)

Tuesday, 24 January 2012: 12:00 AM
Contribution of the Autumn Tibetan Plateau Snow Cover to Seasonal Prediction of North American Winter Temperature
Room 354 (New Orleans Convention Center )
Hai Lin, EC, Dorval, QC, Canada; and Z. Wu

Predicting surface air temperature (Ts) is a major task of North American (NA) winter seasonal prediction. It has been recognized that variations of the NA winter Ts can be associated with El Niņo-Southern Oscillation (ENSO) and the North Atlantic Oscillation (NAO). This study presents observed evidence that variability in snow cover over the Tibetan Plateau (TP) and its adjacent areas in prior autumn (September-November) is significantly correlated with the first principal component (PC1) of the NA winter Ts which features a meridional seesaw pattern over the NA continent. The autumn TP snow cover anomaly can persist into the following winter through a positive feedback between snow cover and the atmosphere. A positive TP snow cover anomaly may induce a negative sea level pressure and geopotential height anomaly over the eastern North Pacific, a positive geopotential height anomaly over Canada, and a negative anomaly over southeast US, a structure very similar to the positive phase of the Pacific-North American (PNA) pattern. This usually favors the occurrence of a warm-North cold-South winter over the NA continent. When a negative snow cover anomaly occurs, the situation tends to be opposite. Since the autumn TP snow cover shows a weak correlation with ENSO, it provides a new predictability source for NA winter Ts.

Based on the above results, an empirical model is constructed to predict PC1 by a combination of autumn TP snow cover and other sea surface temperature anomalies related to ENSO and the NAO. Hindcasts and real forecasts are performed for the 1972-2003 and 2004-2009 periods, respectively. Both show a promising prediction skill. As far as PC1 is concerned, the empirical model hindcast performs better than the ensemble mean of four dynamical models from the Canadian Meteorological Center. Particularly, the real forecast of the empirical model exhibits a better performance in predicting the extreme phases of PC1, i.e., the extremely warm winter over Canada in 2009/2010, should the model include the autumn TP snow cover impacts. Since all these predictors can be readily monitored in real time, this empirical model provides a real time forecast tool for NA winter climate.

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