Jump to: 188045257 ecCKD | 188045257ARTDECO-PyKdis | 188045257 RRTMG | 188045257 RRTMGP | 188045257 KBIN | PSLACKD | SOCRATES | CMA
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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Other relevant information...
ecCKD
Reference: Hogan and Matricardi (JAMES 2022), building on ideas from Hogan (JAS 2010), although there have been several improvements since then such as extension to the shortwave.
Implementation details: ecCKD consists of a number of C++ programs called from shell scripts. Permission has been requested to release it to others under the Apache 2.0 open source license, although some tidying would be needed.
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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). 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 | 10 | 3 |
0.05 < T ≤ 0.5 | 20 | 5 |
0.5 < T ≤ 0.8 | 15 | 5 |
0.8 < T ≤ 0.9 | 10 | 5 |
0.9 < T ≤ 0.99 | 5 | 5 |
0.99 < T ≤ 0.999 | 3 | 2 |
0.999 < T ≤ 1.0 | 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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Significant hand-tuning of k’s was done in many bands to increase the code’s accuracy. This is described further by Pincus et al. (2019).
PSLACKD
Implementation details: Fortran, C and IDL
Selecting band boundaries: There is no restriction on band width, except that the maximum band width is limited by the line-by-line code outputs that are used to generate k-distributions.
Reordering spectrum: Reordering is done separately at each pressure level. However, in order to select the same number of g points, determination of the number of g points is done using all pressure levels.
Choosing number of g points: It is automated using a common threshold of transmission for all pressure and temperature, and water vapor concentrations.
Partitioning g space for one gas: Gaussian quadrature is used for the shortwave and longwave.
Partitioning g space for multiple gases: We can handle both random overlap and separating major and minor gases. The submitted files used fixed minor gas concentrations. The concentration of minor gases is fixed in line-by-line computations to generate inputs. Two separate concentrations of the major gas are used so that the absorption cross section is computed by interpolation.
Computing absorption of one gas: Absorption cross sections are averaged in logarithmic space for pressure and concentration, linear for temperature.
Computing combined absorption of multiple gases: Minor gas absorption is included in line-by-line computations. The k-table is built with additional dimension of minor gas concentrations to allow the variation of the minor gas concentration.
Computing Planck function for each longwave g point: The Planck function is first computed for the band and then partitioned amongst the g points.
Computing incoming solar radiation for each shortwave g point: The solar constant for the band is weighted by the gaussian weight. The Coddington Insolation Spectrum is used.
SOCRATES
Reference(s): There is no definitive paper; the code was initially written by Mark Ringer and John Edwards for the simulation of satellite channel radiances (Ringer et al., 2003: http://dx.doi.org/10.1256/qj.02.61), but it was subsequently heavily modified by James Manners for use in the Met Office Global Atmosphere configurations (e.g. Walters et al., 2019: https://gmd.copernicus.org/articles/12/1909/2019/), and with David Amundsen for use in Exoplanet configurations (Amundsen et al., 2014: http://dx.doi.org/10.1051/0004-6361/201323169).
Implementation details: Fortran 2003, 3-clause BSD licence. Free to use/develop.
Selecting band boundaries: Band boundaries are chosen principally to minimize the number of major gases in each band (ideally one). Also, the surface, clouds, aerosols, Rayleigh scattering and the Planck emission all use band-average properties.
Line-by-line model: Line-by-line absorption coefficients are generated internally using HITRAN line-lists or cross-sections as input. It is also possible to use absorption data in an input netCDF file that has been generated externally by, for example, LBLRTM or ExoCross.
Reordering spectrum: An optimal mapping is done using the reordering of effective absorption coefficients from the top-of-atmosphere down to an optical depth of one. This is used for the g-space partitioning and calculation of weights. A new reordering is then done separately for each pressure and temperature in the look-up table to calculate the actual k-terms used for each g-point at a given pressure and temperature (P/T).
Choosing number of g points: Can be specified manually or automated to arrive at the number of g-points that will bring the error in transmission below a given tolerance for each gas and band separately.
Partitioning g space for one gas: g-space is partitioned using the effective absorption coefficients (see ‘re-ordering spectrum’ above). The points are determined to give an equal spacing in the log of the absorption, with extra consideration given to the first point (least absorption) where an assumption is made for the range that can be taken as ‘grey’. Points are combined if there are no data within a given interval. Optionally, this partitioning can be preceded by splitting the absorption coefficients into three groups according to whether their absorption peaks at the top-of-atmosphere, mid-atmosphere or surface (with groups being automatically combined where absorption is very weak). This is a way of overcoming the inaccuracies due to the 'correlated' assumption in the correlated k-distribution method.
Partitioning g space for multiple gases: Not done. Gas k-terms are kept separate in the configuration, but the ‘optimal mapping’ is saved to the spectral file for potential use within the radiative transfer solver for the method of ‘exact-major overlap’.
Computing absorption of one gas: The k-term for a given g partition at a given P/T is found by determining the absorption that would give the smallest error in transmission for a range of path-lengths up to a maximum path-length supplied. Pressure/temperature dependence of absorption is handled in a look-up table. The concentration dependence of the water vapour continuum and collision-induced absorption are handled separately (two methods are available, each assuming only a dependence on concentration and temperature, not pressure).
Computing combined absorption of multiple gases: . Gas overlap is assumed to be random for the method of Equivalent Extinction (see Edwards, 1996: http://dx.doi.org/10.1175/1520-0469(1996)053%3C1921:ECOIFA%3E2.0.CO;2, or more concisely Amundsen et al., 2017: http://dx.doi.org/10.1051/0004-6361/201629322, section 3.3, which also covers the shortwave treatment). A reference method of ‘Exact-major overlap’ is also available that considers the spectral overlap with the major gas exactly using the ‘optimal mapping’ for each gas.
Computing Planck function for each longwave g point: Planck function is computed for the band and applied according to the g-point weights.
Computing incoming solar radiation for each shortwave g point: g-point weights are calculated using a solar spectral weighting (the exact spectrum used depends on configuration – the GA7 configuration uses NRLSSI data meaned over the period 2000-2011). The solar flux per band and the g-point weights can be varied at runtime according to a varying solar spectrum.
CMA
Reference(s): Zhang et al., 2003: An optimal approach to overlapping bands with correlated k distribution method and its application to radiative calculations, J. Geophys. Res., 108(D20), 4641, doi:10.1029/2002JD003358; Zhang et al., 2005: A Comparison Between the Two Line-by-Line Integration Algorithms[J]. Chinese Journal of Atmospheric Sciences, 2005, 29(4): 581-593. doi:10.3878/j.issn.1006-9895.2005.04.09; Zhang et al., 2006: The effects of the choice of the k-interval number on radiative calculations, doi:10.1016/j.jqsrt.2005.05.090.
Implementation details: Coded in Fortran.
Selecting band boundaries: We have different narrow band schemes for various research purpose to balance the accuracy and speed of radiative transfer computations. In general, the number of major gases and the variation in the Planck function in each band are taken into consideration.
Line-by-line model: All the absorption coefficients are calculated by LBLRTM v12.8; They are put into LBLZS2000 (Zhang et al., 2005) radiative transfer model to calculate fluxes and cooling rates in our calculation.
Reordering spectrum: We have a unique mapping from wavenumber to g space. Reordering for the major gas in each band is done at a reference pressure and temperature level, while the absorption coefficients of other levels and other gases are following the reference reordering. See Zhang et al. (2003) for details.
Choosing number of g points: We have an automated procedure to choose g points for every band. See Zhang et al. (2006).
Partitioning g space for one gas: The partitioning of g space is optimized on the basis of Gaussian Quadrature in order to satisfy the accuracy conditions. We make following changes on each Gaussian Quadrature point:
PN(IG)=2*WGT(IG)*XG(IG)
PNUJ(IG)=XG(IG)**2
where XG(IG) and WGT(IG) are the initial abscissa and Gaussian weight respectively, PNUJ(IG) and PN(IG) are the abscissa and Gaussian weight we used.
Partitioning g space for multiple gases: The partitioning of g space is the same for every gas.
Computing absorption of one gas: The absorption coefficients computed from LBLRTM v12.8 are first reordered, and then the effective absorption coefficients are obtained by the above Gaussian Quadrature, i.e., they are averaged with about 100 absorption coefficients at each g point. These effective absorption coefficients are given as a look-up table in 22 pressure and 3 temperature, independent of concentration.
Computing combined absorption of multiple gases: We have three methods for overlapping band based on completely correlated, completely uncorrelated, and partly correlated, which depend on each band. See Zhang et al. (2003).
Computing Planck function for each longwave g point: The Planck function is first computed for the band mean and then partitioned amongst the g points.
Computing incoming solar radiation for each shortwave g point: The band-mean of incoming solar radiation is computed for every shortwave band, and the value for each g point is obtained by Gaussian weights. The solar spectrum is from ‘mean-ssi_nrl2.nc’ in the CKDMIP software.