The development and operational use of an integrated Numerical Weather Prediction System in the National Center of Meteorology of the Kingdom of Saudi Arabia
Platon Patlakas, Christos Stathopoulos, Christina Kalogeri, Vassilios Vervatis, John Karagiorgos, Ioannis Chaniotis, Andreas Kallos, Ayman S. Ghulam, Mohammed A. Al-omary, Ioannis Papageorgiou, Dimitrios Diamantis, Zaphiris Christidis, John Snook, Sarantis Sofianos, George Kallos
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引用次数: 0
Abstract
Abstract The weather and climate greatly affect socioeconomic activities on multiple temporal and spatial scales. From a climate perspective, atmospheric and ocean characteristics have determined the life, evolution, and prosperity of humans and other species in different areas of the world. On smaller scales, the atmospheric and sea conditions affect various sectors such as civil protection, food security, communications, transportation, and insurance. It becomes evident that weather and ocean forecasting is high-value information highlighting the need for state-of-the-art forecasting systems to be adopted. This importance has been acknowledged by the authorities of Saudi Arabia entrusting the National Center for Meteorology (NCM) to provide high-quality weather and climate analytics. This led to the development of a numerical weather prediction (NWP) system. The new system includes weather, wave, and ocean circulation components and has been operational since 2020 enhancing the national capabilities in NWP. Within this article, a description of the system and its performance is discussed alongside future goals.
期刊介绍:
Weather and Forecasting (WAF) (ISSN: 0882-8156; eISSN: 1520-0434) publishes research that is relevant to operational forecasting. This includes papers on significant weather events, forecasting techniques, forecast verification, model parameterizations, data assimilation, model ensembles, statistical postprocessing techniques, the transfer of research results to the forecasting community, and the societal use and value of forecasts. The scope of WAF includes research relevant to forecast lead times ranging from short-term “nowcasts” through seasonal time scales out to approximately two years.