Toward enhancement of prediction skills of multimodel ensemble seasonal prediction: A climate filter concept

Abstract

Using the APEC Climate Center (APCC) operational multimodel ensemble (MME) hindcasts of precipitation and temperature at 850 hPa for boreal winters for the period 1981-2003, along with those of the individual models as well as corresponding observed and reanalyzed data, we propose the use of a "climate" filter to diagnose and improve the prediction skills. The "filter" is based on the observed strong association between the El Niño-Southern Oscillation (ENSO)-associated Walker circulation and the tropical Pacific rainfall. The reproducibility of this relationship is utilized to evaluate the fidelity of the models. It is found that the retrospective forecast skill of a newer type of MME that contains only the "more skillful" models is superior to that of the all-inclusive operational MME. The difference of the prediction skills between the "more skillful" and "less skillful" MMEs varies with the region and is significant in subtropics such as East Asia, while most of the models perform well in tropics adjacent to the Pacific. Our pilot forecast with the proposed MME for two boreal winter seasons indicates that the method generally works better than the all-inclusive MME in many of the target regions. Copyright 2011 by the American Geophysical Union.