A study of SST-forced variability and potential predictability of seasonal mean fields using the JMA global model

Abstract

An ensemble climate simulation experiment has been conducted using the Japan Meteorological Agency (JMA) global model to study the SST-forced atmospheric variability and potential predictability of seasonal mean fields. The ensemble consists of three model integrations each for the same 34-year period. The three integrations use the same observed SST for the period 1955-1988 but start from different atmospheric initial states. The variance ratios of the SST-forced variability to the total variability of the seasonal mean fields are computed. The ratios are considered to represent "potential predictability" (possible maximum predictability when SST is perfectly predicted). The variance ratios of pressure fields are generally high (50-90 %) in the tropics but low (less than 30 %) in the extratropics, suggesting that the potential predictability of the seasonal mean fields is high in the tropics but low in the extratropics. The variance ratios of precipitation take a wide range of values within the tropics from 74 % for N.E. Brazil rainfall to 31 % for Indian summer monsoon rainfall, indicating large regional differences in the potential predictability of seasonal mean rainfall within the tropics. The variance ratio of globally-averaged global mean land surface air temperature is high (66 %) but the ratio is low (less than 30 %) for the seasonal mean local surface air temperature over most land area. This suggests that the potential predictability of local land surface air temperature is low.