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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/gmd-2018-221
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-2018-221
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Model evaluation paper 29 Nov 2018

Model evaluation paper | 29 Nov 2018

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Geoscientific Model Development (GMD).

A statistical and process oriented evaluation of cloud radiative effects in high resolution global models

Manu Anna Thomas1, Abhay Devasthale1, Torben Koenigk1, Klaus Wyser1, Malcolm Roberts2, Christopher Roberts3, and Katja Lohmann4 Manu Anna Thomas et al.
  • 1Swedish Meteorological and Hydrological Institute, Folkborgsvägen 17, 60176 Norrköping, Sweden
  • 2Met Office Hadley Centre, FitzRoy Rd, Exeter, Devon EX1 3PB, United Kingdom
  • 3European Centre for Medium-Range Weather Forecasts | ECMWF, Shinfield Park, Reading RG2 9AX, United Kingdom
  • 4Max Planck Institute for Meteorology, Bundesstr. 53, D-20146 Hamburg, Germany

Abstract. This study evaluates the impact of atmospheric horizontal resolution on the representation of cloud radiative effects (CREs) in an ensemble of global climate model simulations following the protocols of the High Resolution Model Intercomparison Project (HighResMIP). We compare results from four European modelling centres, each of which provides data from "standard" and "high" resolution model configurations. Simulated radiative fluxes are compared with observation-based estimates derived from the Clouds and Earth's Radiant Energy System (CERES) dataset. Model CRE biases are evaluated using both conventional statistics (e.g. time and spatial averages) and after conditioning on the phase of two modes of internal climate variability, namely the El Niño and Southern Oscillation (ENSO) and the North Atlantic Oscillation (NAO). Simulated top-of-atmosphere (TOA) and surface CREs show large biases over the polar regions, particularly over regions where seasonal sea-ice variability is strongest. Increasing atmospheric resolution does not significantly improve these biases. The spatial structure of the cloud radiative response to ENSO and NAO variability is simulated reasonably well by all model configurations considered in this study. However, it is difficult to identify a systematic impact of atmospheric resolution on the associated CRE errors. Mean absolute CRE errors conditioned on ENSO phase are relatively large (5–10W/m2) and show differences between models. We suggest this is a consequence of differences in the parameterization of SW radiative transfer and the treatment of cloud optical properties rather than a result of differences in resolution. In contrast, mean absolute CRE errors conditioned on NAO phase are generally smaller (0–2W/m2) and more similar across models. Although the regional details of CRE biases show some sensitivity to atmospheric resolution within a particular model, it is difficult to identify patterns that hold across all models. This apparent insensitivity to increased atmospheric horizontal resolution indicates that physical parameterizations play a dominant role in determining the behaviour of cloud-radiation feedbacks. However, we note that these results are obtained from atmosphere-only simulations and the impact of changes in atmospheric resolution may be different in the presence of coupled climate feedbacks.

Manu Anna Thomas et al.
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Short summary
Cloud processes occur at scales ranging from few micrometers to hundreds of kilometers. Their representation in global climate models and its fidelity are thus sensitive to the choice of spatial resolution. Here, cloud radiative effects simulated by models are evaluated using satellite dataset, with focus on investigating the sensitivity to the spatial resolution. The evaluations are carried out using two approaches: the traditional statistical comparisons and the process oriented evaluation.
Cloud processes occur at scales ranging from few micrometers to hundreds of kilometers. Their...
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