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Balancing Accuracy, Efficiency, and Flexibility in Radiation Calculations for Dynamical Models.

Robert Pincus1,2, Eli J Mlawer3, Jennifer S Delamere4

  • 1Cooperative Institute for Environmental Studies University of Colorado Boulder Boulder CO USA.

Journal of Advances in Modeling Earth Systems
|December 24, 2019
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Summary
This summary is machine-generated.

This study introduces a new radiation calculation toolbox, balancing accuracy, efficiency, and flexibility for dynamical models. It enhances atmospheric radiation transfer calculations using advanced spectroscopy and computational objects.

Keywords:
atmospheric modelparameterizationradiation

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Area of Science:

  • Atmospheric Science
  • Computational Physics
  • Climate Modeling

Background:

  • Accurate radiation calculations are crucial for dynamical models.
  • Existing tools face challenges in balancing accuracy, efficiency, and flexibility.
  • Dynamical models require efficient and adaptable radiation transfer computations.

Purpose of the Study:

  • To introduce a new toolbox for radiation calculations in dynamical models.
  • To balance accuracy, efficiency, and flexibility in atmospheric radiation transfer.
  • To provide a flexible and accurate computational framework for radiative transfer.

Main Methods:

  • Implementation of two code bases: Radiative Transfer for Energetics (RTE) and RRTM for General circulation model applications-Parallel (RRTMGP).
  • Utilizing k-distribution for spectral absorption and two-stream, plane-parallel methods for solving the radiative transfer equation.
  • Employing computational objects for flexibility and high-efficiency computational kernels for performance.

Main Results:

  • The toolbox successfully balances accuracy, efficiency, and flexibility.
  • State-of-the-art spectroscopy enhances the accuracy of k-distribution.
  • Computational objects and efficient kernels improve adaptability and performance.

Conclusions:

  • The new toolbox offers a significant advancement in radiation calculations for dynamical models.
  • The implementation provides a flexible, accurate, and efficient solution for atmospheric radiative transfer.
  • Further user engagement is expected for cloud and aerosol mapping.