The AEMET-γSREPS over the Antarctic Peninsula and the impact of kilometric-resolution EPS on logistic activities on the continent

Kilometric-resolution Ensemble Prediction Systems (EPSs) will be the new state-of-the-art forecasting tools for short-range prediction in the following decade. Their value will be even greater in Antarctica due to the increasingly demanding weather forecasts for logistic services. During the 2018–20...

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Bibliographic Details
Published in:Advances in Science and Research
Main Authors: Gonzalez, Sergi, Callado, Alfons, Martínez, Mauricia, Elvira, Benito
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2020
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Online Access:https://doi.org/10.5194/asr-17-209-2020
https://noa.gwlb.de/receive/cop_mods_00054226
https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00053877/asr-17-209-2020.pdf
https://asr.copernicus.org/articles/17/209/2020/asr-17-209-2020.pdf
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Summary:Kilometric-resolution Ensemble Prediction Systems (EPSs) will be the new state-of-the-art forecasting tools for short-range prediction in the following decade. Their value will be even greater in Antarctica due to the increasingly demanding weather forecasts for logistic services. During the 2018–2019 austral summer (1 December–31 March), coinciding with the Southern Hemisphere Special Observation Period of the Year of Polar Prediction (YOPP), the 2.5 km AEMET-γSREPS was operationally integrated over the Antarctic Peninsula. In particular, the Antarctic version of γSREPS comes up with crossing four non-hydrostatic convection-permitting NWP models at 2.5 km with three global NWP driving models as boundary conditions. The γSREPS forecasting system has been validated in comparison with ECMWF EPS. It is concluded that γSREPS has an added value to ECMWF EPS due to both its higher resolution and its multi-boundary conditions and multi-NWP model approach. γSREPS performance has a positive impact on logistic activities at research stations and its design may contribute to polar prediction research.