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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Volume 8, issue 3
Geosci. Model Dev., 8, 501–531, 2015
https://doi.org/10.5194/gmd-8-501-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
Geosci. Model Dev., 8, 501–531, 2015
https://doi.org/10.5194/gmd-8-501-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Development and technical paper 09 Mar 2015

Development and technical paper | 09 Mar 2015

Development and basic evaluation of a prognostic aerosol scheme (v1) in the CNRM Climate Model CNRM-CM6

M. Michou, P. Nabat, and D. Saint-Martin M. Michou et al.
  • CNRM-GAME, Météo-France, Centre National de Recherches Météorologiques, UMR3589, 42 avenue G. Coriolis, 31057 Toulouse CEDEX 1, France

Abstract. We have implemented a prognostic aerosol scheme (v1) in CNRM-CM6, the climate model of CNRM-GAME and CERFACS, based upon the GEMS/MACC aerosol module of the ECMWF operational forecast model. This scheme describes the physical evolution of the five main types of aerosols, namely black carbon, organic matter, sulfate, desert dust and sea salt. In this work, we describe the characteristics of our implementation, for instance, taking into consideration a different dust scheme or boosting biomass burning emissions by a factor of 2, as well as the evaluation performed on simulation output. The simulations consist of time slice simulations for 2004 conditions and transient runs over the 1993–2012 period, and are either free-running or nudged towards the ERA-Interim Reanalysis. Evaluation data sets include several satellite instrument AOD (aerosol optical depth) products (i.e., MODIS Aqua classic and Deep-Blue products, MISR and CALIOP products), as well as ground-based AERONET data and the derived AERONET climatology, MAC-v1. The uncertainty of aerosol-type seasonal AOD due to model internal variability is low over large parts of the globe, and the characteristics of a nudged simulation reflect those of a free-running simulation. In contrast, the impact of the new dust scheme is large, with modelled dust AODs from simulations with the new dust scheme close to observations. Overall patterns and seasonal cycles of the total AOD are well depicted with, however, a systematic low bias over oceans. The comparison to the fractional MAC-v1 AOD climatology shows disagreements mostly over continents, while that to AERONET sites outlines the capability of the model to reproduce monthly climatologies under very diverse dominant aerosol types. Here again, underestimation of the total AOD appears in several cases, sometimes linked to insufficient efficiency of the aerosol transport away from the aerosol sources. Analysis of monthly time series at 166 AERONET sites shows, in general, correlation coefficients higher than 0.5 and lower model variance than observed. A large interannual variability can also be seen in the CALIOP vertical profiles over certain regions of the world. Overall, this prognostic aerosol scheme appears promising for aerosol-climate studies. There is room, however, for implementing more complex parameterisations in relation to aerosols.

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