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Quantifying the effects of horizontal grid length and parameterised convection on the degree of convective organisation using a metric of the potential for convective interaction

White, B. A., Buchanan, A. M., Birch, C. E., Stier, P. and Pearson, K. J. (2018) Quantifying the effects of horizontal grid length and parameterised convection on the degree of convective organisation using a metric of the potential for convective interaction. Journal of the Atmospheric Sciences, 75 (2). pp. 425-450. ISSN 1520-0469

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To link to this item DOI: 10.1175/JAS-D-16-0307.1

Abstract/Summary

The organisation of deep convection and its misrepresentation in many global models is the focus of much current interest. We present a new method for quantifying convective organisation based on the identification of convective objects and subsequent derivation of object numbers, areas and separation distances to describe the degree of convective organisation. These parameters are combined into a ‘convection organisation potential’ based on the physical principle of an interaction potential between pairs of convective objects. We apply this technique to simulated and observed fields of outgoing longwave radiation (OLR) over the West African monsoon region using data from Met Office Unified Model simulations and satellite observations made by the Geostationary Earth Radiation Budget instrument (GERB). We evaluate our method by using it to quantify differences between models with different horizontal grid lengths and representations of convection. Distributions of OLR, precipitation and organisation parameters, the diurnal cycle of convection, and relationships between the meteorology in different states of organisation are compared. Switching from a configuration with parameterised convection to one which allows the model to resolve convective processes at the model gridscale is the leading order factor improving some aspects of model performance, while increased model resolution is the dominant factor for others. However, no single model configuration performs best compared to observations, indicating underlying deficiencies in both model scaling and process understanding.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:73004
Publisher:American Meteorological Society
Publisher Statement:Permission to place a copy of this work on this server has been provided by the AMS. The AMS does not guarantee that the copy provided here is an accurate copy of the published work.

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