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dc.contributor.authorMaria Gehne
dc.contributor.authorBrandon Wolding
dc.contributor.authorJuliana Dias
dc.contributor.authorGeorge N. Kiladis
dc.date.accessioned2023-04-12T18:26:08Z
dc.date.available2023-04-12T18:26:08Z
dc.date.copyright2022/09/01
dc.date.issued2022
dc.identifier.otherWAF-D-21-0204.1.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4289659
dc.description.abstractTropical precipitation and circulation are often coupled and span a vast spectrum of scales from a few to several thousands of kilometers and from hours to weeks. Current operational numerical weather prediction (NWP) models struggle with representing the full range of scales of tropical phenomena. Synoptic to planetary scales are of particular importance because improved skill in the representation of tropical larger-scale features such as convectively coupled equatorial waves (CCEWs) has the potential to reduce forecast error propagation from the tropics to the midlatitudes. Here we introduce diagnostics from a recently developed tropical variability diagnostics toolbox, where we focus on two recent versions of NOAA’s Unified Forecast System (UFS): operational GFSv15 forecasts and experimental GFSv16 forecasts from April to October 2020. The diagnostics include space–time coherence spectra to identify preferred scales of coupling between circulation and precipitation, pattern correlations of Hovmöller diagrams to assess model skill in zonal propagation of precipitating features, CCEW skill assessment, plus a diagnostic aimed at evaluating moisture–convection coupling in the tropics. Results show that the GFSv16 forecasts are slightly more realistic than GFSv15 in their coherence between precipitation and model dynamics at synoptic to planetary scales, with modest improvements in moisture convection coupling. However, this slightly improved performance does not necessarily translate to improvements in traditional precipitation skill scores. The results highlight the utility of these diagnostics in the pursuit of better understanding of NWP model performance in the tropics, while also demonstrating the challenges in translating model advancements into improved skill.
dc.publisherAmerican Meteorological Society
dc.titleDiagnostics of Tropical Variability for Numerical Weather Forecasts
dc.typeJournal Paper
dc.journal.volume37
dc.journal.issue9
dc.journal.titleWeather and Forecasting
dc.identifier.doi10.1175/WAF-D-21-0204.1
dc.journal.fristpage1661
dc.journal.lastpage1680
dc.page1661–1680
dc.treeWeather and Forecasting:;2022:;volume( 037 ):;issue: 009
dc.contenttypeFulltext


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