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

Rocío Baró,Paolo Tuccella,Pedro Jiménez-Guerrero,Laura Palacios-Peña,Stefano Galmarini,Gabriele Curci,Dominik Brunner,Martin Stengel,Lucy Neal,Renate Forkel,Martijn Schaap,Nicholas Savage,Hugo Denier Van Der Gon

doi:10.5194/acp-18-15183-2018

Abstract

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.

Highlights

Atmospheric aerosols vary in time and space, influence the Earth’s radiation budget, and can lead to variations in cloud microphysics, which impact cloud radiative properties and climate
3 Results This section describes the behaviour of the studied variables (CF, ice water path (IWP), liquid water path (LWP), cloud optical depth (COD)) for the bias, temporal correlation, and spatial variability
They were obtained by calculating the corresponding statistics of the monthly mean series at each grid point of all the land grid points of the domain for each season as follows: January–February–March (JFM); April– May–June (AMJ); July–August–September (JAS); October– November–December (OND)

Summary

Introduction

Atmospheric aerosols vary in time and space, influence the Earth’s radiation budget, and can lead to variations in cloud microphysics, which impact cloud radiative properties and climate. The modification of cloud microphysical properties is expected to have an impact on the cloud evolution, in terms of a cloud’s ability to generate large enough droplets to initiate precipitation This effect is traditionally called the second aerosol indirect effect, but since the AR5, these indirect effects are called aerosol–cloud interactions (ACIs). Those interactions are more uncertain due to the complexity of the microphysical processes (Boucher and Lohmann, 1995; Schwartz et al, 2002; Lohmann and Feichter, 2005)

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Conclusion