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.
Current status
- Longwave datasets are available, shortwave coming soon
- Comments are welcome on the protocol design before it is finalized
- Potential participants are welcome to email Robin Hogan outlining what submissions they envisage being able to provde
The longwave absorption spectrum of the nine gases considered in CKDMIP.
Documentation
More information on the design of the experimental protocol is here:
- Hogan and Matricardi: draft GMD protocol paper, 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-0.7.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:
- Evaluation-1 - 50 realistic profiles for training and evaluation: ckdmip_evaluation1_concentrations.nc
- Evaluation-2 - 50 further realistic profiles for independent evaluation (not yet available)
- MMM - profiles of median, minimum and maximum temperature, H2O and O3: ckdmip_mmm_concentrations.nc
- Idealized - idealistic profiles of temperature, pressure and humidity: ckdmip_idealized_concentrations.nc
The absorption spectra used to generate reference radiation calculations were produced at ECMWF by Marco Matricardi using the LBLRTM line-by-line model.
- ftp://dissemination.ecmwf.int: The location of the absorption spectra and associated CKDMIP datasets (username ckdmip, password on request from Robin Hogan, r.j.hogan@ecmwf.int)
As described in section 4 of the technical guide, participants are requested to provide files containing the output from their CKD model in the form of the optical depth and Planck function for each 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:
- ecrad-rrtmg_evaluation1_lw_climate_narrow-n140_optical-depth_present.nc: Gas optical depth in the 140 g-points of the RRTMG gas-optics model in its implementation in the ecRad radiation scheme
- ecrad-rrtmg_evaluation1_lw_climate_narrow-n140_fluxes_present.nc: Broadband and spectral upwelling and downwelling fluxes computed from the RRTMG gas optical depths
- ckdmip_evaluation1_lw_fluxes_present.h5: The corresponding reference line-by-line fluxes
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:
- ecrad-rrtm_lw_climate_narrow-n140_spectral-definition.nc: Note that this particular file is 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).