Convective-scale perturbation growth across the spectrum of convective regimes

Flack, D. L. A., Gray, S. L. ORCID: https://orcid.org/0000-0001-8658-362X, Plant, R. S. ORCID: https://orcid.org/0000-0001-8808-0022, Lean, H. W. and Craig, G. C. (2018) Convective-scale perturbation growth across the spectrum of convective regimes. Monthly Weather Review, 146 (1). pp. 387-405. ISSN 0027-0644 doi: 10.1175/mwr-d-17-0024.1

Abstract/Summary

Convection-permitting ensembles have led to improved forecasts of many atmospheric phenomena. However, to fully utilize these forecasts the dependence of predictability on synoptic conditions needs to be understood. In this study, convective regimes are diagnosed based on a convective timescale which identifies the degree to which convection is in equilibrium with the large-scale forcing. Six convective cases are examined in a convection-permitting ensemble constructed using the Met Office Unified Model. The ensemble members were generated using small-amplitude buoyancy perturbations added into the boundary layer, which can be considered to represent turbulent fluctuations close to the gridscale. Perturbation growth is shown to occur on different scales with an order of magnitude difference between the regimes (O(1 km) for cases closer to non-equilibrium convection and O(10 km) for cases closer to equilibrium convection). This difference reflects the fact that cell locations are essentially random in the equilibrium events after the first 12 h of the forecast, indicating a more rapid upscale perturbation growth compared to the non-equilibrium events. Furthermore, large temporal variability is exhibited in all perturbation growth diagnostics for the nonequilibrium regime. Two boundary condition driven cases are also considered and show similar characteristics to the non-equilibrium cases, implying that caution is needed to interpret the timescale when initiation is not within the domain. Further understanding of perturbation growth within the different regimes could lead to a better understanding of where ensemble design improvements can be made beyond increasing the model resolution and could improve interpretation of forecasts.

Item Type	Article
URI	https://reading-pure-test.eprints-hosting.org/id/eprint/74117
Identification Number/DOI	10.1175/mwr-d-17-0024.1
Refereed	Yes
Divisions	Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology Central Services
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