Line-by-line coefficients for an analytical solution of spectrally resolved outgoing longwave radiation

<p>Following <strong>Feng et al., 2023</strong> , the change in spectrally-resolved outgoing longwave radiance <span class="math-tex">\(R\)</span>&nbsp;is:</p> <p><span class="math-tex">\(\pi \frac{R_{\text{trop}}}{R} [B(rT_e) - B(T_e)]\)</span></p> <p>In this equation, B(T_e) refers to Planck Function at temperature T_e, <span class="math-tex">\(R_{trop}\)</span>&nbsp;is the radiance contributed by troposphere, and&nbsp;<span class="math-tex">\(r\)</span>&nbsp;is an emission temperature shift ratio, computed using <strong>Eq. 10</strong> of <strong>Feng et al., 2023 </strong>with line-by-line regression coefficients <span class="math-tex">\(k\)</span>&nbsp;contained in&nbsp;the netCDF file &#39;lbl_regression_coeff.nc&#39; for each major greenhouse gas.&nbsp;This set of coefficients is derived using an open-source line-by-line radiation code&nbsp;PyLBL (<a href="https://pylbl-1.readthedocs.io/en/latest/">https://pylbl-1.readthedocs.io</a>) following the Appendix of&nbsp;Feng et al., 2023 via Eq. B2, B4, and B6.</p> <p>An example matlab script is included&nbsp;to compute the&nbsp;emission temperature shift ratio based on the line-by-line coefficients and to further predict the spectrally-resolved feedback parameter based on Feng et al., 2023.</p>