Abstract
AbstractThe predictability of the Unified Forecast System (UFS) Coupled Model Prototype 2 developed by the National Centers for Environmental Prediction is assessed for the boreal summer over the continental United States (CONUS). The retrospective forecasts of low-level horizontal wind, precipitation and 2-m temperature for 2011–17 are examined to determine the predictability at subseasonal time scale. Using a data-adaptive method, the leading modes of variability are obtained and identified to be related to El Niño–Southern Oscillation (ENSO), intraseasonal oscillation (ISO), and warming trend. In a new approach, the sources of enhanced predictability are identified by examining the forecast errors and correlations in the weekly averages of the leading modes of variability. During the boreal summer, the ISO followed by the trend in UFS are found to provide better predictability in weeks 1–4 compared to the ENSO mode and the total anomaly. The western CONUS seems to have better predictability on weekly time scale in all three modes.
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