2 research outputs found
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Evaluating convection-permitting ensemble forecasts of precipitation over Southeast Asia
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
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The African SWIFT project: growing science capability to bring about a revolution in weather prediction
Africa is poised for a revolution in the quality and relevance of weather predictions, with potential for great benefits in terms of human and economic security. This revolution will be driven by recent international progress in nowcasting, numerical weather prediction, theoretical tropical dynamics and forecast communication, but will depend on suitable scientific investment being made. The commercial sector has recognized this opportunity and new forecast products are being made available to African stakeholders. At this time, it is vital that robust scientific methods are used to develop and evaluate the new generation of forecasts. The GCRF African SWIFT project represents an international effort to advance scientific solutions across the fields of nowcasting, synoptic and short-range severe weather prediction, subseasonal-to-seasonal (S2S) prediction, user engagement and forecast evaluation. This paper describes the opportunities facing African meteorology and the ways in which SWIFT is meeting those opportunities and identifying priority next steps.
Delivery and maintenance of weather forecasting systems exploiting these new solutions requires a trained body of scientists with skills in research and training; modelling and operational prediction; communications and leadership. By supporting partnerships between academia and operational agencies in four African partner countries, the SWIFT project is helping to build capacity and capability in African forecasting science. A highlight of SWIFT is the coordination of three weather-forecasting “Testbeds” – the first of their kind in Africa – which have been used to bring new evaluation tools, research insights, user perspectives and communications pathways into a semi-operational forecasting environment