Online coupled meteorology–chemistry models permit the description of the aerosol–radiation (ARI) and aerosol–cloud interactions (ACIs). The aim of this work is to assess the representation of several cloud properties in regional-scale coupled models when simulating the climate–chemistry–cloud–radiation system. The evaluated simulations are performed under the umbrella of the Air Quality Model Evaluation International Initiative (AQMEII) Phase 2 and include ARI+ACI interactions. Model simulations are evaluated against observational data from the European Space Agency (ESA) Cloud_cci project. The results show an underestimation (overestimation) of cloud fraction (CF) over land (sea) areas by the models. Lower bias values are found in the ensemble mean. Cloud optical depth (COD) and cloud ice water path (IWP) are generally underestimated over the whole European domain. The cloud liquid water path (LWP) is broadly overestimated. The temporal correlation suggests a generally positive correlation between models and satellite observations. Finally, CF gives the best spatial variability representation, whereas COD, IWP, and LWP show less capacity. The differences found can be attributed to differences in the microphysics schemes used; for instance, the number of ice hydrometeors and the prognostic/diagnostic treatment of the LWP are relevant.

Evaluating cloud properties in an ensemble of regional online coupled models against satellite observations

Gabriele Curci;Paolo Tuccella;
2018-01-01

Abstract

Online coupled meteorology–chemistry models permit the description of the aerosol–radiation (ARI) and aerosol–cloud interactions (ACIs). The aim of this work is to assess the representation of several cloud properties in regional-scale coupled models when simulating the climate–chemistry–cloud–radiation system. The evaluated simulations are performed under the umbrella of the Air Quality Model Evaluation International Initiative (AQMEII) Phase 2 and include ARI+ACI interactions. Model simulations are evaluated against observational data from the European Space Agency (ESA) Cloud_cci project. The results show an underestimation (overestimation) of cloud fraction (CF) over land (sea) areas by the models. Lower bias values are found in the ensemble mean. Cloud optical depth (COD) and cloud ice water path (IWP) are generally underestimated over the whole European domain. The cloud liquid water path (LWP) is broadly overestimated. The temporal correlation suggests a generally positive correlation between models and satellite observations. Finally, CF gives the best spatial variability representation, whereas COD, IWP, and LWP show less capacity. The differences found can be attributed to differences in the microphysics schemes used; for instance, the number of ice hydrometeors and the prognostic/diagnostic treatment of the LWP are relevant.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11697/127926
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