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Introduction

Most radiation schemes in weather and climate models use the "correlated k-distribution" (CKD) method to treat gas absorption, which approximates the integration over hundreds of thousands of spectral lines by N pseudo-monochromatic radiative transfer calculations, where N is in the range tens to hundreds. In principle, there is a trade-off to make: larger N means more accuracy and a wider range of atmospheric conditions can be simulated, but at greater computational cost. Unfortunately most CKD schemes are a black box: there is no way for the user to adjust N according to their application. The purpose of CKDMIP is to address these issues, and specifically:

  • To use benchmark line-by-line calculations to evaluate the accuracy of existing CKD models for applications spanning short-range weather forecasting to climate modelling, and to explore how accuracy varies with number of g-points in individual CKD schemes.

  • To understand how different choices in way that CKD models are generated affects their accuracy for the same number of g-points.

  • To provide freely available datasets and software to facilitate the development of new gas-optics models, with the ultimate aim of producing a community tool to allow users to generate their own gas-optics models targeted at specific applications.

Potential participants are welcome to email Robin Hogan outlining what submissions they envisage being able to provide. See the results so far from the participating CKD tools and models.

Latest update: 4 June 2020

Earlier updates

  • Evaluation plots are now available for version 0.5 of the longwave ecCKD tool
  • Evaluation plots may be viewed for the ecRad-RRTMG and RTE-RRTMGP CKD models
  • Longwave absorption spectra for water vapour excluding the water vapour continuum have been uploaded to the FTP site
  • Both shortwave and longwave datasets are now available
  • Additional climate scenarios have been added to test the representation of longwave spectral overlap between CO2, CH4 and N2O
  • The longwave radiative transfer calculation can now use up to 8 angles in each hemisphere
  • Software includes conversion from spectral layerwise optical depth to mass- or molar extinction coefficient

The absorption spectrum of the nine gases considered in CKDMIP for concentrations at 100 hPa in the CKDMIP median atmospheric profile. Note that the wavenumber scale changes from linear to logarithmic at 2500 cm-1.

Documentation

More information on the design of the experimental protocol is here:

  • Hogan and Matricardi: protocol paper submitted to GMD (view in GMD discussions), including a description of the broad requirements of participants in section 4.2
  • Technical Guide: describes the CKDMIP datasets and software, and a detailed description of the requirements of participants in section 4

Software

  • ckdmip-0.9.tar.gz: Software package for performing longwave radiative transfer calculations both on line-by-line absorption spectra and CKD files produced by CKDMIP participants

Datasets

Table 3 of Hogan and Matricardi defines four datasets consisting of a number of gas-concentration profiles plotted here:

The absorption spectra used to generate reference radiation calculations were produced at ECMWF by Marco Matricardi using the LBLRTM line-by-line model.

As described in section 4 of the technical guide, participants are requested to provide files containing the output from their CKD model. In the longwave this contains the optical depth and Planck function at g-point of their model, for each concentration scenario. Here is an example of this file, and the fluxes that the CKDMIP software package will produce from it:

In the shortwave, the file should contain the absorption optical depth, Rayleigh optical depth and solar irradiance at each g-point of the model, for example:

Participants are also requested to provide information on any CKD model they generate in terms of which points in the spectrum contribute to each g-point. The format should match the following:

Note that these particular files have been built without any knowledge of where individual g-points are weighted within a band, but this sub-band information will be needed to most accurately assess errors in cloudy profiles in the final phase of the project (section 4.4 of Hogan and Matricardi).

Contact

Any queries not answered in the documentation on this page should be addressed to Robin Hogan (r.j.hogan@ecmwf.int).