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Forcing Single-Column Models Using High-Resolution Model Simulations.

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PubMed
Summary
This summary is machine-generated.

A new method uses high-resolution weather simulations to create realistic inputs for single-column models (SCMs). This approach enhances parameterization development and process studies by providing accurate atmospheric proxies.

Keywords:
Indian Ocean/warm poolNERC Cascade projectforcing datageostrophic windshigh‐resolution modelingsingle‐column model

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Area of Science:

  • Atmospheric Science
  • Climate Modeling
  • Computational Meteorology

Background:

  • Single-column models (SCMs) require realistic initial profiles, forcing fields, and boundary conditions for accurate parameterization development and process studies.
  • The increasing scale and number of high-resolution convection-permitting simulations necessitate improved methods for deriving these SCM inputs.

Purpose of the Study:

  • To propose and implement a novel technique for deriving realistic SCM input profiles from high-resolution atmospheric simulations.
  • To evaluate the effectiveness of this technique using data from the UK Met Office's Unified Model and the European Centre for Medium-Range Weather Forecasts' Integrated Forecasting System (IFS) SCM.

Main Methods:

  • Coarse-graining high-resolution (4 km) convection-permitting simulation data to match SCM resolution.
  • Utilizing these coarse-grained data as a proxy for the true atmosphere to drive the IFS SCM.
  • Comparing SCM performance driven by coarse-grained data versus operational analysis data.

Main Results:

  • SCM simulations driven by coarse-grained data closely tracked the global model, demonstrating consistency between derived forcing fields and true dynamical forcing.
  • Selecting SCM forcing profiles from large domains yielded robust statistics and allowed testing across diverse boundary conditions.
  • The proposed method showed comparable or improved results when compared to using operational analysis data.

Conclusions:

  • The proposed technique effectively derives realistic forcing profiles for SCMs from high-resolution simulations.
  • This method offers a valuable tool for parameterization development and process studies, enhancing consistency with global models.
  • Understanding biases in high-resolution data is crucial, and this approach can be combined with observational data for further refinement.