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Evaluating convection-permitting ensemble forecasts of precipitation over Southeast Asia

Ferrett, S. ORCID: https://orcid.org/0000-0003-4726-847X, Frame, T. H. A., Methven, J., Holloway, C. E. ORCID: https://orcid.org/0000-0001-9903-8989, Webster, S., Stein, T. H.M. ORCID: https://orcid.org/0000-0002-9215-5397 and Cafaro, C. ORCID: https://orcid.org/0000-0001-8063-4887 (2021) Evaluating convection-permitting ensemble forecasts of precipitation over Southeast Asia. Weather and Forecasting. ISSN 0882-8156 (In Press)

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To link to this item DOI: 10.1175/WAF-D-20-0216.1

Abstract/Summary

Forecasting rainfall in the tropics is a major challenge for numerical weather prediction. Convection-permitting (CP) models are intended to enable forecasts of high-impact weather events. Development and operation of these models in the tropics has only just been realised. This study describes and evaluates a suite of recently developed Met Office Unified Model CP ensemble forecasts over three domains in Southeast Asia, covering Malaysia, Indonesia and the Philippines. Fractions Skill Score is used to assess the spatial scale-dependence of skill in forecasts of precipitation during October 2018 - March 2019. CP forecasts are skilful for 3-hour precipitation accumulations at spatial scales greater than 200 km in all domains during the first day of forecasts. Skill decreases with lead time but varies depending on time of day over Malaysia and Indonesia, due to the importance of the diurnal cycle in driving rainfall in those regions. Skill is largest during daytime when precipitation is over land and is constrained by orography. Comparison of CP ensembles using 2.2, 4.5 and 8.8 km grid spacing and an 8.8km ensemble with parameterised convection reveals that varying resolution has much less effect on ensemble skill and spread than the representation of convection. The parameterised ensemble is less skilful than CP ensembles over Malaysia and Indonesia and more skilful over the Philippines; however, the parameterised ensemble has large drops in skill and spread related to deficiencies in its diurnal cycle representation. All ensembles are under-spread indicating that future model development should focus on this issue.

Item Type:Article
Refereed:Yes
Divisions:Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:96819
Publisher:American Meteorological Society

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