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Boundary-Layer Meteorology

, Volume 169, Issue 3, pp 483–503 | Cite as

Modification of a Parametrization of Shallow Convection in the Grey Zone Using a Mesoscale Model

  • Dávid Lancz
  • Balázs Szintai
  • Rachel Honnert
Research Article
  • 128 Downloads

Abstract

In current operational numerical weather prediction models, the effect of shallow convection is parametrized. The grey zone of shallow convection is found between the horizontal resolutions of mesoscale numerical models (2–3 km) and large-eddy simulations (10–100 m or finer). At these horizontal scales the shallow convection is to some extent explicitly resolved by the model. The shallow-convection parametrization is still needed, but has to be regulated according to the model horizontal resolution. Here the behaviour of the non-hydrostatic mesoscale numerical weather prediction model Application of Research to Operations at Mesoscale is examined in the grey zone and a new scale-adaptive surface closure of its shallow-convection parametrization, dependent on horizontal resolution, is defined based on large-eddy simulation. The new closure is tested on a series of numerical experiments and validated on a 15-day-long real case period. Its impact on the development of deep convection is examined in detail. The idealized simulations show promising results, as the mean profiles of the subgrid and resolved turbulence change in the desired way. Based on the real case tests our modification has a low impact on model performance, but is part of a set of upgrades of the current parametrization that is aimed to treat the shallow convection grey zone.

Keywords

Grey zone Kilometric scale Numerical weather prediction Scale dependency Shallow convection 

Notes

Acknowledgements

This study was prepared at the Hungarian Meteorological Service, financially supported by the RC-LACE consortium. The authors wish to thank André Simon for his help in the case study and Michael Robert Glinton for his language corrections. Detailed and constructive reviews from three anonymous reviewers led to a significant improvement in the text.

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Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  1. 1.Hungarian Meteorological ServiceBudapestHungary
  2. 2.CNRM UMR 3589, Météo-France/CNRS 42Toulouse Cedex 01France

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