This study aims to understand the role of near-surface temperatures in predicting US climatic extremes using the North American Multi-Model Ensemble (NMME) system. Here, the forecasting skill was measured by… Click to show full abstract
This study aims to understand the role of near-surface temperatures in predicting US climatic extremes using the North American Multi-Model Ensemble (NMME) system. Here, the forecasting skill was measured by anomaly correlation coefficient (ACC) between the observed and forecasted precipitation (PREC)/2-meter air temperature (T2m) anomalies over the contiguous United States (CONUS) during 1982–2012. The strength of the T2m–PREC coupling was measured by ACC between observed PREC and T2m or forecasted PREC and T2m over the CONUS. We also assessed the NMME forecasting skill for the summers of 2004 (spatial anomaly correlation between PREC and T2m: 0.05), 2011 (−0.65), and 2012 (−0.60) when the T2m–PREC coupling was weaker or stronger than the 1982–2012 climatology (ACC: −0.34). We found that most of the NMME models show the bias of stronger T2m–PREC coupling than the observed coupling over 1982–2012, indicating that they failed to reproduce the interannual variability of T2m–PREC coupling. Some NMME models with skillful prediction for T2m show the skillful prediction of the precipitation anomalies and US droughts in 2011 and 2012 via strong T2m–PREC coupling despite the fact that the forecasting skill is year-dependent and model-dependent. Most of the NMME models show the limited seasonal forecasting skill of the PREC surplus from active Atlantic tropical cyclones in the summer of 2004 and thus fail to reproduce weak T2m–PREC coupling. Lastly, we explored how the role of sea surface temperatures in predicting T2m and PREC. The findings of this study suggest a need for the selective use of the current NMME seasonal forecasts for US droughts and pluvials.
               
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