The Met Office winter testbed 2020/2021: Experimenting with an on‐demand 300‐m ensemble in a real‐time environment

Autor: C. L. Bain, M. Bush, J. C. Buxmann, P. Davies, A. Finnenkoetter, D. L. A. Flack, K. Hanley, R. W. Jones, H. W. Lean, H. Lewis, A. McCabe, J. C. Petch, A. Porson, C. Sanchez, E. K. Stone, D. Walters, S. Webster, S. Willington
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Meteorological Applications, Vol 29, Iss 5, Pp n/a-n/a (2022)
Druh dokumentu: article
ISSN: 1469-8080
1350-4827
DOI: 10.1002/met.2096
Popis: Abstract The Met Office held a testbed over winter 2020/2021 where a new numerical weather prediction (NWP) sub‐km ensemble was set up on‐demand in response to interesting weather phenomena in the United Kingdom. The domain for the model was chosen in real time by a community of Met Office Research Scientists and Operational Meteorologists and over a 4‐month period the ensemble was triggered for nine events. The purpose of the testbed was to investigate whether a real‐time weather regime‐based enhancement in NWP capability was feasible, to understand what benefits a testbed environment might give, and to explore the practicalities of running such an event. Case studies from the testbed demonstrated that forecast ensembles at 2.2 km and 300 m grid spacing were able to capture observed winter weather, with greater spatial detail apparent, especially over complex orography, in the 300‐m model. Ensemble spread appeared less influenced by resolution, potentially due to the size of the domains tested or the weather regimes of the case studies. The testbed also showcased underutilized observations and additional radiosonde ascents were conducted. All the testbed meetings were conducted virtually due to COVID‐19 restrictions, and decisions were made about when to trigger the event using an online message board. The winter 2020/2021 testbed provides ideas for how on‐demand weather‐dependent testbeds might be conducted in the future. However, several recommendations are made that would enhance testbed benefits further, including more dedicated resource, stronger technology and data visualization and greater participation from both academia and weather information users.
Databáze: Directory of Open Access Journals
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