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\begin{document}

\title{A tool for generating fast k-distribution gas-optics models for weather
and climate applications}



\author[1]{Robin James Hogan}%
\author[1]{Marco Matricardi}%
\affil[1]{ECMWF}%


\vspace{-1em}



  
  \date{May 27, 2024}


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\begin{abstract}
One of the most important components of an atmospheric radiation scheme
is its treatment of gas optical properties, which determines not only
the accuracy of its radiative forcing calculations fundamental to
climate prediction, but also its computational cost. This paper
describes a free software tool `ecCKD' for generating fast gas-optics
models by optimally dividing the spectrum into pseudo-monochromatic
spectral intervals (known as k-terms) according to a user-specified
error tolerance and the range of greenhouse-gas concentrations that
needs to be simulated. The models generated use the correlated
k-distribution method in user-specified bands, but can also generate
accurate `full-spectrum correlated-k' models that operate on the entire
longwave or near-infrared parts of the spectrum. In the near-infrared,
the large spectral variation in cloud absorption is represented by
partitioning the parts of the spectrum where gases are optically thin
into three or more sub-bands, while allowing k-terms for the optically
thicker parts of the spectrum (where clouds and surface reflectance are
less important) to span the entire near-infrared spectrum. Candidate
models using only 16 and 32 k-terms in each of the shortwave and
longwave are evaluated against line-by-line calculations on clear and
cloudy profiles. The 32-term models are able to accurately capture the
radiative forcing of varying greenhouse gases including
CO\textsubscript{2} concentrations spanning a factor of 12, and heating
rates at pressures down to 1 Pa.%
\end{abstract}%



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