The Skill of Statistically Forecasting the Early Monsoon Onset in the Southwestern United States at a Subseasonal to Seasonal Time Scale

Ryan Dennis, Christopher L. Castro, and Ben McMahan

Department of Hydrology and Atmospheric Sciences

The University of Arizona

Forecasts at the subseasonal to seasonal timescales have been recognized by the scientific community as having significant socioeconomic value. However, although these forecasts are skillful at forecasting warm season atmopsheric teleconnection patterns, they are less skillful at forecasting warm season precipitation, which puts in question their practicality. In this study, the observed 500-hPa atmospheric circulation anomalies in the Northern Hemisphere are related to the dominant patterns of the observed two-month standard precipitation index (SPI) in the continental United States during the early warm season (June and July) from 1979-2011. An empirical orthogonal function analysis and canonical correlation analysis are then applied to determine the dominant coupled modes between the observed teleconnection patterns and SPI with a focus on the southwestern United States. Next, the same procedure is performed on five ensemble members of the CFSv2 reforecast data at a week four to five forecast period from 1999-2010 to determine the dominant coupled modes between the modeled geopotential height anomalies and SPI. These modeled coupled modes are then correlated with the observed coupled modes to determine the statistically significant pattern correlations and whether the CFSv2 reforecast data has any skill in forecasting the early monsoon onset four to five weeks out.