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A Correlated K-Distribution (CKD) tool generates CKD gas-optics models in a number of steps, some which may require human intervention. One of the most interesting parts of the CKDMIP project will be to understand how differences in how each step is performed feed through to differences in the accuracy of fluxes and heating rates. The page is an attempt to gather the necessary information about the CKD tools participating in CKDMIP, specifically:
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Choosing number of g points: The number of g points for a given gas depends on its transmission over the band for airmass = 2 computed for a test atmosphere (usually US62).
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There are two different versions, "full" and "reduced" with the numbers of g points as shown in the table below:
Atmosphere transmission | Ng "full" | Ng "reduced" |
0 < T ≤ 0.05 |
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10 | 3 | |
0.05 < T ≤ 0.5 |
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20 | 5 | |
0.5 < T ≤ 0.8 |
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15 | 5 | |
0.8 < T ≤ 0.9 |
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10 | 5 | |
0.9 < T ≤ 0.99 |
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5 | 5 | |
0.99 < T ≤ 0.999 |
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3 | 2 | |
0.999 < T ≤ 1.0 |
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1 | 1 |
Partitioning g space for one gas: For each gas, the partition of g space is obtained by first setting a Gaussian quadrature grid over the log10(k) range for a reference pressure and temperature (most likely corresponding to an altitude where the absorption will be the most important in the atmosphere). This grid is then mapped to the g space and the corresponding g partition is then used for all other pressures and temperatures.
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Computing incoming solar radiation for each shortwave g point: The incoming solar spectral flux is accounted for in computing g as a weighting function of the spectral absorption coefficients.
Other relevant information: Two versions of the CKD tool are considered. One is based on the spectral reordering scheme described above. The second method uses the Rank Transmutation Strategy described by Andre et al. (2018), in which case the power exponential germ with medium resolution mapping functions (1,000 points) is used.
KBIN
Reference: Doppler et al. (2014)
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