The potential use of operational radar network data to evaluate the representation of convective storms in NWP models

Stein, T. H. M. ORCID: https://orcid.org/0000-0002-9215-5397, Scovell, R. W., Hanley, K., Lean, H. W. and Marsden, N. H. (2020) The potential use of operational radar network data to evaluate the representation of convective storms in NWP models. Quarterly Journal of the Royal Meteorological Society, 146 (730). pp. 2315-2331. ISSN 0035-9009 doi: 10.1002/qj.3793

Abstract/Summary

Operational forecasting centres increasingly rely on convection-permitting NWP simulations to assist in their forecasting of convective events. The evaluation of upgrades in the underlying NWP modeling system normally happens through routine verification using traditional metrics on two-dimensional fields, such as gridded rainfall data. Object- and process-based evaluation can identify specific physical mechanisms for model improvement, but such evaluation procedures normally require targeted and expensive field campaigns. Here, we explore the potential use of the UK operational radar network observations and its derived 3D composite product for evaluating the representation of convective storms in the Met Office Unified Model. A comparison of the 1 km x 1 km x 0.5 km 3D radar composites against observations made with the research-grade radar at Chilbolton in the southern UK indicates that the 3D radar composite data can reliably be used to evaluate the morphology of convective storms. The 3D radar composite data are subsequently used to evaluate the development of convective storms in the Met Office Unified Model. Such analysis was heretofore unavailable due to a lack of high-frequency three-dimensional radar data. The operational nature of the UK radar data makes these 3D composites a valuable resource for future studies of the initiation, growth, development, and organisation of convective storms over the UK.

Item Type	Article
URI	https://reading-pure-test.eprints-hosting.org/id/eprint/89643
Identification Number/DOI	10.1002/qj.3793
Refereed	Yes
Divisions	Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology Central Services
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