Representing clouds in climate models is a challenging problem. It is particularly difficult to represent deep convective clouds and, historically, deep convective parameterization is separate from the representation of other cloud types. Here we use a single-column cloud model to simulate three deep convective cases, and two shallow cloud cases. The results look reasonable, demonstrating that it may be possible to use one parameterization within a climate model for all cloud types.

The model reproduces the temporal variability of NO2, O3, PM10, PM2.5 better at rural than urban background stations. The fractional biases show that the model performs slightly better at RB sites than at UB sites for NO2, O3 and PM10. At UB sites, CHIMERE reproduces PM2.5 better than PM10. This is primarily the result of an underestimation of coarse particulate matter (PM) associated with uncertainties on SOA chemistry and their precursor emissions, dust and sea salt.

A new Geoengineering Model Intercomparison Project (GeoMIP) experiment “G4 specified stratospheric aerosols” (G4SSA) is proposed to investigate the impact of stratospheric aerosol geoengineering on atmosphere, chemistry, dynamics, climate, and the environment. In contrast to the earlier G4 GeoMIP experiment, which requires an emission of sulfur dioxide (SO2) into the model, a prescribed aerosol forcing file is provided to the community, to be consistently applied to future model experiments.

The paper deals with the comparison of the common periodization methods used to obtain spectral fields of limited-area models for numerical weather prediction. The focus is on the impact the methods have on the spectra of the fields. The results show that detrending and DCT have little impact on the spectra, as does the Boyd method for extension zone. For the ALADIN and HIRLAM methods, the impact depends on the width of the extension zone - the wider the zone, the larger impact on the spectra.

The implementation and application of the Integrated Source Apportionment Method (ISAM) for O3 and its precursors for the Community Multiscale Air Quality (CMAQ) model are described. CMAQ-ISAM is a hybrid of source apportionment and source sensitivity in that O3 production is attributed to precursor sources based on the O3 formation regime. CMAQ-ISAM offers a source attribution tool for the purposes of quantifying and understanding sources and impacts of regional air pollution.