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https://doi.org/10.5194/acp-2020-635
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-2020-635
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  14 Jul 2020

14 Jul 2020

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This preprint is currently under review for the journal ACP.

The behavior of high-CAPE summer convection in large-domain large-eddy simulations with ICON

Harald Rybka1, Ulrike Burkhardt2, Martin Köhler1, Ioanna Arka2, Luca Bugliaro2, Ulrich Görsdorf3, Ákos Horváth4, Catrin I. Meyer5, Jens Reichardt3, Axel Seifert1, and Johan Strandgren2 Harald Rybka et al.
  • 1German Meteorological Service, Offenbach am Main, Germany
  • 2Deutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
  • 3German Meteorological Service, Lindenberg, Germany
  • 4Universität Hamburg, Germany
  • 5Jülich Supercomputing Centre, Forschungszentrum Jülich, Jülich, Germany

Abstract. Current state of the art regional numerical weather prediction (NWP) models employ kilometre scale horizontal grid resolutions thereby simulating convection within its grey-zone. Increasing resolution leads to resolving the 3D motion field and has been shown to improve the representation of clouds and precipitation. Using a hectometer-scale model in forecasting mode on a large domain therefore offers a chance to study processes that require the simulation of the 3D motion field at small horizontal scales, such as deep summertime moist convection, a notorious problem in NWP.

We use the Icosahedral Nonhydrostatic weather and climate model in large-eddy simulation mode (ICON-LEM) to simulate deep moist convection distinguishing between scattered, large scale dynamically forced and frontal convection. We use different ground and satellite based observational data sets, that supply information on ice water content and path, ice cloud cover and cloud top height on a similar scale as the simulations, in order to evaluate and constrain our model simulations.

We find that the timing and geometric extent of the convectively generated cloud shield agrees well with observations while the life time of the convective anvil was, at least in one case, significantly overestimated. Given the large uncertainties of individual ice water path observations, we use a suite of observations in order to better constrain the simulations. ICON-LEM simulates cloud ice water path that lies in-between the different observational data sets but simulations appear to be biased towards a large frozen water path (all frozen hydrometeors). The bias in frozen water path and the longevity of the anvil are little affected by modifications of parameters within the microphysical scheme. In particular one of our convective days appeared to be very sensitive to the initial and boundary conditions which had a large impact on the convective triggering, but little impact on the high frozen water path and long anvil life time bias. Based on this limited set of sensitivity experiments, the evolution of locally forced convection appears to depend more on the uncertainty of the large-scale dynamical state based on data assimilation than of microphysical parameters.

Overall, we judge ICON-LEM simulations of deep moist convection to be very close to observations regarding timing, geometrical structure and cloud ice water path of the convective anvil, but other frozen hydrometeors, in particular graupel, are likely overestimated. Therefore, ICON-LEM supplies important information for weather forecasting and forms a good basis for parameterization development based on physical processes or machine learning.

Harald Rybka et al.

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Harald Rybka et al.

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High-CAPE summer convection in large-domain large- eddy simulations with ICON – model and observational data sets H. Rybka https://doi.org/10.5281/zenodo.3629457

Harald Rybka et al.

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Latest update: 11 Aug 2020
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Short summary
Current state of the art regional numerical weather prediction models employ kilometre scale horizontal grid resolutions, thereby still parametrizing convection. In this study, we use a high-resolution model to study summertime convection comparing to different ground and satellite based observational data sets. The results suggest a very close agreement to observations regarding timing, geometrical structure and cloud ice water path, supplying information for parametrization development.
Current state of the art regional numerical weather prediction models employ kilometre scale...
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