Soil Science Society of America

Forecasting cotton yield in the southeastern United States using coupled global circulation models

We developed methods of forecasting cotton (Gossypium hirsutum L. var. hirsutum) yields at a county level 3 mo before harvest for the states of Alabama and Georgia. Cotton yield historical records for 57 counties were obtained from NASS and detrended using a low-pass spectral filter. A Canonical Correlation Analysis regression-based model was annually recalibrated to incorporate the year-by-year accumulating data: (i) April–June (during vegetative growth) observed rainfall for the forecasting year, and (ii) July–September (during reproductive growth) global-scaled 2-m mean temperatures for years before the forecasting year, beginning with 1970. We produced two types of forecasts: short range and medium range. The short-range near-term yield forecast (just before initiating harvest in the region) used gridded assimilated observed 2-m mean temperatures obtained from the NCEP-NCAR CDAS Reanalysis data. The medium-range forecast (3 mo before harvest) used 2-m mean temperature retrospective forecasts from the operational NOAA/NWS/NCEP Climate Forecasts System coupled global circulation model. The short-range, near-term forecast performance was measured by leave-one-out cross-validation and retroactive validation, whereas medium-range forecast performance used the previous two methods plus a proposed coral-reef validation method. The agreement between short-range near-term forecast and actual cotton yield was statistically significant at the 0.05 level in 31 out of 57 counties. For 48% of these 31 counties, the agreements between medium-range forecasts and actual cotton yields were statistically significant at the 0.05 level. The goodness-of-fit index for those 15 counties was 0.51 and the RMSE ranged from 13 to 31% of the annual yield.

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