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Compute absorption of one gas: The CKDMIP "Idealized" dataset is used to construct a look-up table for each gas (major and minor): for a given input temperature, pressure and concentration, the look-up table provides the absorption coefficient of that gas at all N g points. The absorption coefficient in a g point is computed by averaging the spectral absorption coefficients contributing to that g point such that the transmittance of the layer to diffuse radiation is preserved. For all gases except water vapourH2O, the absorption coefficient is assumed to be proportional to concentration (i.e. the look-up table provides the molar absorption coefficient from temperature and pressure, which is then multiplied by the mole fraction of the gas to obtain the absorption coefficient). The look-up table for water vapour allows H2O allows a nonlinear dependence of absorption on concentration. Composite gases represent those whose concentrations are fixed or depend only on pressure, i.e. O2+N2 in CKD models for climate and CO2+CH4+N2O+O2+N2+CFC11+CFC12 for NWP; in this case the look-up table is a function of temperature and pressure with no dependence on concentration.
Compute combined absorption of multiple gases: Gas optics models produced by ecCKD assume that the total optical depth of a layer in one g point is the sum of the contributions from individual gases (each computed from a look-up table). However, the "out of the box" performance using absorptions from the previous step is poor. Therefore, an optimization step is performed in which the coefficients of the look-up tables are adjusted such that the resulting fluxes best agree (in a least squares sense) with reference fluxes from the 50-profile CKDMIP Evaluation-1 dataset (the 50 profiles sampling wide variations in temperature, water vapour H2O and ozoneO3). Typically in optimizing the coefficients for a CKD gas optics model to be used for climate modelling, this is done in several steps. Firstly, the look-up table coefficients for water vapourH2O, ozone O3 and carbon dioxide are CO2 are optimized using line-by-line flux calculations in which CO2 is varied (CKDMIP scenarios 5-9), but with present-day concentrations of the other well-mixed greenhouse gases. Subsequent steps then optimize the coefficients of CH4 and N2O, each time training with LBL calculations varying only these gases. These optimization steps ensure that when more than one gas is important in a particular spectral range, the coefficients are chosen such that the fluxes are as accurate as they can be over the range of concentrations used in the training. This does, however, mean that an ecCKD-generated gas-optics model is not independent of the Evaluation-1 dataset, so should be evaluated with the independent Evaluation-2 dataset.
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