Experimental prediction of severe droughts on seasonal time scales with GFDL High-Resolution Atmosphere Model

Regional heat waves and drought have major economic and societal impacts on regional and even global scales. For example, during and following the 2010-2011 La Nina period, severe droughts have been reported in many places around the world including China, the southern US, and the east Africa, causing severe hardship in China and famine in east Africa. In this study, we investigate the feasibility and predictability of severe drought events, 3 months in advance with the 25-km resolution Geophysical Fluid Dynamics Laboratory High-Resolution Atmosphere Model (HiRAM), which is built as a seamless weather-climate model, capable of long-term climate simulations as well as skillful seasonal predictions (e.g., Chen and Lin 2011, GRL). We adopted a similar methodology and the same model (HiRAM) as in Chen and Lin (2011), which is used successfully for seasonal hurricane predictions. A series of initialized 3-month forecasts starting from Mar/Jun/Sep/Dec 1 are performed each year (5 members each) during the past decade (2001-2011). We will then evaluate the predictability of the severe drought events during this period by comparing model predictions vs. available observations. To evaluate the predictive skill, in this preliminary report, we will focus on the anomalies of precipitation, sea-level-pressure, 500-mb height, and surface temperature. These anomalies will be computed as the individual model prediction minus the mean climatology obtained by an independent AMIP-type “simulation” using observed SSTs (rather than using predictive SSTs in the forecasts) from the same model.