Abstract
Abstract. Arctic clouds exhibit a robust annual cycle with maximum cloudiness in fall and minimum cloudiness in winter. These variations affect energy flows in the Arctic with a large influence on the surface radiative fluxes. Contemporary climate models struggle to reproduce the observed Arctic cloud amount annual cycle and significantly disagree with each other. The goal of this analysis is to quantify the cloud-influencing factors that contribute to winter–summer cloud amount differences, as these seasons are primarily responsible for the model discrepancies with observations. We find that differences in the total cloud amount annual cycle are primarily caused by differences in low, rather than high, clouds; the largest differences occur between the surface and 950 hPa. Grouping models based on their seasonal cycles of cloud amount and stratifying cloud amount by cloud-influencing factors, we find that model groups disagree most under strong lower tropospheric stability, weak to moderate mid-tropospheric subsidence, and cold lower tropospheric air temperatures. Intergroup differences in low cloud amount are found to be a function of lower tropospheric thermodynamic characteristics. Further, we find that models with a larger low cloud amount in winter have a larger ice condensate fraction, whereas models with a larger low cloud amount in summer have a smaller ice condensate fraction. Stratifying model output by the specifics of the cloud microphysical scheme reveals that models treating cloud ice and liquid condensate as separate prognostic variables simulate a larger ice condensate fraction than those that treat total cloud condensate as a prognostic variable and use a temperature-dependent phase partitioning. Thus, the cloud microphysical parameterization is the primary cause of inter-model differences in the Arctic cloud annual cycle, providing further evidence of the important role that cloud ice microphysical processes play in the evolution and modeling of the Arctic climate system.
Highlights
Arctic clouds, arguably one of the most poorly understood aspects of the Arctic climate system, strongly modulate radiative energy fluxes at the surface, through the atmosphere, and to the top of the atmosphere (Cesana et al, 2012; Curry et al, 1996; Kay et al, 2008; Kay and L’Ecuyer, 2013; Shupe and Intrieri, 2004)
Climate models participating in the Coupled Model Intercomparison Project 5 (CMIP5) (Taylor et al, 2011) simulate Arctic clouds that are Published by Copernicus Publications on behalf of the European Geosciences Union
What do our results argue about the drivers of the Arctic cloud annual cycle? The climate model results argue that the Arctic cloud annual cycle is most strongly driven by the seasonality of cloud microphysics, the cloud phase and temperature relationship
Summary
Arguably one of the most poorly understood aspects of the Arctic climate system, strongly modulate radiative energy fluxes at the surface, through the atmosphere, and to the top of the atmosphere (Cesana et al, 2012; Curry et al, 1996; Kay et al, 2008; Kay and L’Ecuyer, 2013; Shupe and Intrieri, 2004). Representing clouds in climate models is necessary to realistically simulate the evolution of the Arctic surface energy budget. Contemporary climate models, strongly disagree with observations of the seasonality of Arctic cloud radiative effects. Climate models possess significant biases in the seasonality of the surface cloud radiative effect (Boeke and Taylor, 2016; Karlsson and Svensson, 2013, 2011). Climate models participating in the Coupled Model Intercomparison Project 5 (CMIP5) (Taylor et al, 2011) simulate Arctic clouds that are Published by Copernicus Publications on behalf of the European Geosciences Union
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