4.6 Article

Seasonal forecasting of tropical storms using the Met Office GloSea5 seasonal forecast system

Journal

QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY
Volume 141, Issue 691, Pages 2206-2219

Publisher

WILEY-BLACKWELL
DOI: 10.1002/qj.2516

Keywords

seasonal forecasting; ensembles; tropical storms; landfall

Funding

  1. Joint DECC and Defra Integrated Climate Programme, DECC/Defra [GA01101]
  2. EU [FP7-308378]
  3. Natural Environment Research Council [jwcrp01003] Funding Source: researchfish
  4. NERC [jwcrp01003] Funding Source: UKRI

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The variability and predictability of tropical storm activity in the Met Office fully coupled atmosphere-ocean Global Seasonal Forecast System 5 (GloSea5) is assessed. GloSea5 is a high-resolution seasonal forecast system with an atmospheric horizontal grid of 0.83 degrees longitude x 0.55 degrees latitude (approximate to 53 km at 55 degrees N) and 0.25 degrees in the global ocean. The performance of the system is assessed in terms of its ability to retrospectively predict the observed tropical storm climatology and its response to the El Nino-Southern Oscillation (ENSO). Results are compared to the predecessor system GloSea4 (approximate to 120 km atmospheric horizontal resolution) and observational analyses over the common period of the operational hindcast for both systems: 1996-2009. A supplementary assessment of GloSea5 for the period 1992-2013 is then performed to evaluate skill of tropical storm predictions in the Northern Hemisphere as well as landfall frequency along two regions, the US coast and the Caribbean, over a longer period. GloSea5 is able to reproduce key tropical storm characteristics, such as their geographical distribution, seasonal cycle and interannual variability, as well as spatial changes in storm track density with ENSO. GloSea5 shows statistically significant skill for predictions of tropical storm numbers and accumulated cyclone energy (ACE) index in the North Atlantic, western Pacific, Australian region and South Pacific. Statistically significant skill is also found for predictions of landfall frequency along the Caribbean coastline. Skill is similar using either the direct counting of landfalling storms in the model, or by inferring landfall rates from the Atlantic basin-wide storm count. We find no skill for predictions of landfall along the US coast. Results suggest the potential for operational seasonal tropical storm forecasts throughout the Tropics.

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