Atlantic and Pacific sea surface temperatures and corn yields in the southeastern USA: lagged relationships and forecast model development

作者：Martinez Christopher J^*; Jones James W

来源：International Journal of Climatology, 2011, 31(4): 592-604.

DOI：10.1002/joc.2082

• crop yield forecast
• sea surface temperature
• singular value decomposition analysis
• principal component analysis

Sea surface temperatures (SSTs) can provide valuable predictive information for regional climate and agricultural yields in many parts of the world. This study was conducted to identify relationships between Atlantic and Pacific SSTs and corn yields in Alabama, Florida, and Georgia and to use these relationships to develop forecasts that can be used at lead times prior to spring planting. The relationships between seasonal SSTs and detrended county corn yields were analysed using singular value decomposition (SVD) analysis and confirmed using principal component analysis (PCA). Using a Monte Carlo approach, field-significant results were found with SSTs in the July-September (JAS(-1)) and October-December (OND(-1)) seasons in the previous year and with the January-March (JFM) season of the current. A significant portion of the variability of SSTs with corn yield residuals was connected with anomalous heating and cooling associated with the El Nino Southern Oscillation (ENSO). Based on the results found by SVD analysis and confirmed by PCA, indices of spatially averaged SSTs in regions of the North Pacific and Atlantic Oceans were derived. Using these indices along with the Nino3.4 index to represent tropical Pacific SSTs, cross-validated multiple linear regression models were developed to predict corn yield residuals using index values in the JAS(-1) and OND(-1) seasons. Using the cross-validated models 91.5 and 98.4% of forecasted county corn yield residuals showed predictive skill (based on tercile hit scores) with seasonal index values in the JAS(-1) and OND(-1) seasons, respectively. The results of the models indicate that the indices of SSTs show significant predictability with corn yield residuals at lead times up to 4-7 months prior to spring planting and are a significant improvement over the use of an index of ENSO alone.

• 出版日期2011-3