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Quantifying the circulation induced by convective clouds in kilometer-scale simulations.

Annika Oertel1,2, Sebastian Schemm1

  • 1Institute for Atmospheric and Climate Science ETH Zürich Zürich Switzerland.

Quarterly Journal of the Royal Meteorological Society. Royal Meteorological Society (Great Britain)
|July 5, 2021
PubMed
Summary
This summary is machine-generated.

A new method quantifies how convective clouds interact with atmospheric circulation. This reveals clouds move slower than their surroundings, impacting precipitation distribution and improving weather model accuracy.

Keywords:
cloud‐circulation interactiondiabatic–adiabatic couplingfar‐ and near‐field cloud‐induced circulationhigh‐resolution modeling

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Area of Science:

  • Atmospheric Science
  • Meteorology
  • Climate Modeling

Background:

  • Complex interactions between large-scale atmospheric circulation and parameterized cloud processes cause errors in weather and climate models.
  • Understanding these interactions is crucial for improving prediction accuracy.

Purpose of the Study:

  • To develop and apply a novel method for quantifying the circulation induced by cloud systems.
  • To analyze the impact of convective clouds on atmospheric flow and their self-propagation speed.

Main Methods:

  • A new method reconstructs cloud-induced flow using vorticity and divergence estimates without needing a background flow definition.
  • Applied to high-resolution (12- and 2-km) simulations of convective clouds within an extratropical cyclone.

Main Results:

  • Cloud-induced circulation opposes the upper-level jet, reaching speeds up to 10 m/s, consistent across different resolutions.
  • Embedded convection creates a negative wind speed anomaly near the jet, explained by the cloud-induced circulation.
  • Convective clouds were found to propagate slower than their environment due to this induced flow.

Conclusions:

  • The developed method effectively quantifies cloud-induced circulation and its impact on atmospheric flow.
  • Cloud-induced flow counteracts advection, leading to slower cloud propagation and potentially altered precipitation patterns.
  • This approach enables comparisons of cloud effects across different model resolutions and parameterizations.