A framework for dynamical seasonal prediction of precipitation over the Pacific Islands

  • 5 May 2014
  • Number of views: 5610

Research funded by CPO’s Modeling, Analysis, Prediction, and Projections (MAPP) program was published in the latest issue of the Journal of Climate.

The paper "A Framework for Dynamical Seasonal Prediction of Precipitation over the Pacific Islands," adopted a three-step approach to develop a framework for dynamical seasonal prediction of precipitation over the U.S. Affiliated Pacific Islands (USAPI) .

First, guided by the climatological features of basic variables, the researchers proposed a view that climates of the USAPI are connected by large-scale phenomena involving the warm pool, South Pacific convergence zone, tropical monsoons, and subtropical anticyclone.  Secondly, they evaluated  prediction skill in ensemble hindcasts performed with the Climate Forecast System, version 2 (CFSv2), with the hypothesis that ENSO is the leading candidate for large and persisting precipitation departures. Third, moist static energy budget diagnostics are performed to identify physical processes responsible for precipitation anomalies.

The paper found that at leads of 0–6 months, CFSv2 demonstrates useful skill in predicting Niño-3.4 SST and equatorial Pacific precipitation anomalies. During El Niño, positive precipitation anomalies along the central (eastern) equatorial Pacific are anchored by net radiative flux (Frad) and moist advection (evaporation and Frad). The model’s skill in predicting precipitation anomalies over South Pacific (Hawaiian) islands is highest (lowest). Over the west Pacific islands, the skill is low during the rainy season. During El Niño, skill over the USAPI, in particular predicting dryness persistence at long leads is useful. Suppressed precipitation over the Hawaiian and South Pacific (west Pacific) islands are determined by anomalous dry and cold air advection (reduced evaporation and Frad). These processes are local, but are dictated by circulation anomalies forced by ENSO. Model budget estimates are qualitatively consistent with those obtained from reanalysis, boosting confidence for societal benefits. However, observational constraints, as well as budget residuals, pose limitations.

 To view the full paper, visit: http://apdrc.soest.hawaii.edu

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