Abstract

AbstractThe performance of the Met Office Global Seasonal Forecast System (GloSea5-GC2) for tropical cyclone (TC) frequency for the western North Pacific (WNP) in July–October is evaluated, using 23 years of ensemble forecasts (1993–2015). Compared to observations, GloSea5 overpredicts the climatological TC frequency in the eastern WNP and underpredicts it in the western and northern WNP. These biases are associated with an El Niño–type bias in TC-related environmental conditions (e.g., low-level convergence and steering flow), which encourages too many TCs to form throughout the tropical Pacific and slows TC propagation speed. For interannual TC frequency variability, GloSea5 overestimates the observed negative TC–ENSO teleconnection in the western and northern WNP, associated with an eastward shift in the ENSO teleconnection to environmental conditions. Consequently, GloSea5 fails to predict interannual TC variability in the northeast WNP (south of Japan); performance is higher in the southwest WNP (e.g., the South China Sea) where the sign of the TC–ENSO teleconnection is correct. This study suggests the need to reduce biases in environmental conditions and associated ENSO teleconnections in GloSea5 to improve the TC prediction performance in the NWP.

Highlights

  • As one of most destructive weather phenomena, tropical cyclones (TCs) can have tremendous impacts over land, associated with strong winds, heavy rainfall, and storm surges

  • Because the same TC identification scheme is applied to ERA-Interim and GloSea5, and because ERA-Interim and GloSea5 have similar horizontal resolutions, validating GloSea5 against ERA-Interim is fairer than validating GloSea5 against International Best Track Archive for Climate Stewardship (IBTrACS) from the perspective of model development

  • Met Office GloSea5-GC2 global seasonal forecast system for predicting western North Pacific (WNP) TC frequency in JASO (July–October), from ensemble forecasts initialized in June, May, and April

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Summary

Introduction

As one of most destructive weather phenomena, tropical cyclones (TCs) can have tremendous impacts over land, associated with strong winds, heavy rainfall, and storm surges. We evaluate the ability of GloSea5-GC2 to predict the climatology and variability of regional WNP TC frequency, including the effects of forecast lead time and ensemble size.

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