87th AMS Annual Meeting

Monday, 15 January 2007
Regional atmospheric circulation and surface temperatures predicting cotton yields in the southeastern USA
Exhibit Hall C (Henry B. Gonzalez Convention Center)
Guillermo A. Baigorria, University of Florida, Gainesville, FL; and J. W. Hansen, N. Ward, J. W. Jones, and J. J. O'Brien
In the Southeastern USA, climate during summertime and cotton yields show little or no association with ENSO phase. To improve prediction of cotton yields at a long lead-time in the region, we identify regional atmospheric variables that are related to historic summer rainfall and cotton yields, and evaluate the use of predictions of those variables from a global circulation model (GCM) for forecasting cotton yields. We analyzed de-trended cotton yields (1970-2004) from 48 counties in Alabama and Georgia, monthly rainfall from 53 weather stations, monthly estimates of 850 and 200 hPa winds at and surface temperatures over the SE-USA region from reanalysis data, and monthly predictions of the same variables from the ECHAM 4.5 GCM. Meridional wind fields and surface temperature around SE-USA were correlated with cotton yield and with rainfall, especially during April and July, over most of the region, and explained up to 52% of the inter-annual variability of observed yields. The tendency for cotton yields to be lower during years with atmospheric circulation patterns that favor higher humidity and rainfall is consistent with increased incidence of disease during flowering and harvest periods under wet conditions. Cross-validated yield predictions based on ECHAM hindcasts of wind and temperature fields forced by observed SSTs showed significant skill (55% and 60% hit skills based on terciles and averages respectively). Mean square errors of yield predictions varied from 3 to 10% over all locations and from 0 to 15% over all years. There is potential to increase the skill of cotton yield forecasts using variables that are forecast by numerical climate models.

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