Articles | Volume 13, issue 12
https://doi.org/10.5194/gmd-13-6501-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-13-6501-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Evaluating and improving the treatment of gases in radiation schemes: the Correlated K-Distribution Model Intercomparison Project (CKDMIP)
European Centre for Medium-range Weather Forecasts, Reading, UK
Marco Matricardi
European Centre for Medium-range Weather Forecasts, Reading, UK
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19 citations as recorded by crossref.
- Exploring Pathways to More Accurate Machine Learning Emulation of Atmospheric Radiative Transfer P. Ukkonen 10.1029/2021MS002875
- Modeling Atmospheric Lines by the Exoplanet Community (MALBEC) Version 1.0: A CUISINES Radiative Transfer Intercomparison Project G. Villanueva et al. 10.3847/PSJ/ad2681
- What are the optimum discrete angles to use in thermal‐infrared radiative transfer calculations? R. Hogan 10.1002/qj.4598
- Present-day methane shortwave absorption mutes surface warming relative to preindustrial conditions R. Allen et al. 10.5194/acp-24-11207-2024
- How Moisture Shapes Low‐Level Radiative Cooling in Subsidence Regimes B. Fildier et al. 10.1029/2023AV000880
- A Tool for Generating Fast k‐Distribution Gas‐Optics Models for Weather and Climate Applications R. Hogan & M. Matricardi 10.1029/2022MS003033
- Surface warming and wetting due to methane’s long-wave radiative effects muted by short-wave absorption R. Allen et al. 10.1038/s41561-023-01144-z
- The k-bin tool: Fast and flexible k-distribution algorithms written in Python N. Madenach et al. 10.1016/j.jqsrt.2024.109213
- The ICON Single-Column Mode I. Bašták Ďurán et al. 10.3390/atmos12070906
- Sparse, Empirically Optimized Quadrature for Broadband Spectral Integration P. Czarnecki et al. 10.1029/2023MS003819
- Assessment of the spectral misalignment effect (SMILE) on EarthCARE's Multi-Spectral Imager aerosol and cloud property retrievals N. Docter et al. 10.5194/amt-17-2507-2024
- Advances in Atmospheric Radiation: Theories, Models, and Their Applications. Part I: Atmospheric Gas Absorption and Particle Scattering H. Zhang et al. 10.1007/s13351-024-3091-4
- Optimized Alternate Mapping Correlated K‐Distribution Method for Atmospheric Longwave Radiative Transfer Y. Cai et al. 10.1029/2022MS003419
- 含云大气单次散射参量极大相关k分布优选算法 张. Zhang Yin et al. 10.3788/AOS222030
- Implementation of a machine-learned gas optics parameterization in the ECMWF Integrated Forecasting System: RRTMGP-NN 2.0 P. Ukkonen & R. Hogan 10.5194/gmd-16-3241-2023
- Integrated efficient radiative transfer model named Dayu for simulating the imager measurements in cloudy atmospheres W. Li et al. 10.1364/OE.482762
- Copula-based synthetic data augmentation for machine-learning emulators D. Meyer et al. 10.5194/gmd-14-5205-2021
- Aerosol optical depth retrieval from the EarthCARE Multi-Spectral Imager: the M-AOT product N. Docter et al. 10.5194/amt-16-3437-2023
- Machine Learning Emulation of 3D Cloud Radiative Effects D. Meyer et al. 10.1029/2021MS002550
1 citations as recorded by crossref.
Latest update: 08 Dec 2024
Short summary
A key component of computer models used to predict weather and climate is the radiation scheme, which calculates how solar and infrared radiation heats and cools the atmosphere and surface, including the important role of greenhouse gases. This paper describes the experimental protocol and large datasets for a new project, CKDMIP, to evaluate and improve the accuracy of the treatment of atmospheric gases in the radiation schemes used worldwide, as well as their computational speed.
A key component of computer models used to predict weather and climate is the radiation scheme,...