5,723
Views
0
CrossRef citations to date
0
Altmetric
Research Article

On the configuration of a regional Arctic Numerical Weather Prediction system to maximize predictive capacity

, &
Pages 1-18 | Received 03 Mar 2021, Accepted 26 Aug 2021, Published online: 13 Sep 2021
 

Abstract

Limitations to operational weather forecasts exist in terms of availability of computer (and human) resources combined with operational deadlines. For operational weather services it is therefore important to utilize their resources to maximize the predictive capability. This study shows how forecast quality in a state-of-the-art high-resolution regional Arctic Numerical Weather Prediction (NWP) system changes with varying configuration choices; (1) Ensemble Prediction System (EPS), (2) higher spatial resolution, (3) atmospheric initialization by assimilation of observations, (4) surface initialization by assimilation of observations and by (5) changing the regional domain and location. Results from such inter-comparisons are useful guidance for (Arctic) weather forecast systems, and can together with information on e.g. user-needs and post-processing capabilities be used to maximize the operational predictive capacity. All configuration choices have a significant impact on the forecast quality of near-surface parameters, but the impact varies with parameter, region, weather type, lead time and part of the forecast evaluated (e.g. average errors or rare events). Higher spatial resolution and EPS are expensive, but are still promising to further improve state-of-the-art regional Arctic high-resolution NWP systems. In particular when forecasting rare events regional EPS shows huge benefits. Assimilation of observations in the initialization process of the regional NWP system has also a positive impact on forecast quality. Finally, although less pronounced, the choice of the domain size and location also has a significant impact and should therefore be chosen carefully.

Additional information

Funding

The work described in this paper has received funding from the European Union’s Horizon 2020 Research and Innovation programme through Grant Agreement 727862 APPLICATE, and the Norwegian Research Council Project 280573 ‘Advanced models and weather prediction in the Arctic: enhanced capacity from observations and polar process representations (ALERTNESS)’.