Abstract

Abstract. Clouds play an important role in the climate system by reducing the amount of shortwave radiation reaching the surface and the amount of longwave radiation escaping to space. Accurate simulation of clouds in computer models remains elusive, however, pointing to a lack of understanding of the connection between large-scale dynamics and cloud properties. This study uses a k-means clustering algorithm to group 21 years of satellite cloud data over midlatitude oceans into seven clusters, and demonstrates that the cloud clusters are associated with distinct large-scale dynamical conditions. Three clusters correspond to low-level cloud regimes with different cloud fraction and cumuliform or stratiform characteristics, but all occur under large-scale descent and a relatively dry free troposphere. Three clusters correspond to vertically extensive cloud regimes with tops in the middle or upper troposphere, and they differ according to the strength of large-scale ascent and enhancement of tropospheric temperature and humidity. The final cluster is associated with a lower troposphere that is dry and an upper troposphere that is moist and experiencing weak ascent and horizontal moist advection. Since the present balance of reflection of shortwave and absorption of longwave radiation by clouds could change as the atmosphere warms from increasing anthropogenic greenhouse gases, we must also better understand how increasing temperature modifies cloud and radiative properties. We therefore undertake an observational analysis of how midlatitude oceanic clouds change with temperature when dynamical processes are held constant (i.e., partial derivative with respect to temperature). For each of the seven cloud regimes, we examine the difference in cloud and radiative properties between warm and cold subsets. To avoid misinterpreting a cloud response to large-scale dynamical forcing as a cloud response to temperature, we require horizontal and vertical temperature advection in the warm and cold subsets to have near-median values in three layers of the troposphere. Across all of the seven clusters, we find that cloud fraction is smaller and cloud optical thickness is mostly larger for the warm subset. Cloud-top pressure is higher for the three low-level cloud regimes and lower for the cirrus regime. The net upwelling radiation flux at the top of the atmosphere is larger for the warm subset in every cluster except cirrus, and larger when averaged over all clusters. This implies that the direct response of midlatitude oceanic clouds to increasing temperature acts as a negative feedback on the climate system. Note that the cloud response to atmospheric dynamical changes produced by global warming, which we do not consider in this study, may differ, and the total cloud feedback may be positive.

Highlights

  • Clouds play an integral role in the climate system by reflecting solar radiation back to space and restricting the emission of terrestrial radiation to space, thereby substantially influencing the Earth’s temperature

  • Across all of the seven clusters, we find that cloud fraction is smaller and cloud optical thickness is mostly larger for the warm subset

  • Assuming that variations in cloud fraction, cloud emissivity, and cloud-top pressure are uncorrelated within each cluster, we can sum their individual contributions to longwave cloud radiative forcing (LWCRF) to obtain an approximation of the total LWCRF change associated with the difference between the warm and cold subsets

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Summary

Introduction

Clouds play an integral role in the climate system by reflecting solar radiation back to space and restricting the emission of terrestrial radiation to space, thereby substantially influencing the Earth’s temperature. A large influence over midlatitude ocean cloudiness (Lau and Crane, 1995; Norris and Klein, 2000; Weaver and Ramanathan, 1997), and Fig. 17 shows that vertical profiles of vertical velocity anomalies are almost exactly the same for warm and cold subsets This result gives us confidence that our restriction of temperature advection to near-median values successfully eliminated differences in the large-scale dynamical forcing of clouds in the warm and cold subsets of each cluster. Assuming that variations in cloud fraction, cloud emissivity, and cloud-top pressure are uncorrelated within each cluster, we can sum their individual contributions to LWCRF to obtain an approximation of the total LWCRF change associated with the difference between the warm and cold subsets These are listed, and indicate that the Cirrus cluster (+1.0 Wm−2 K−1) has the largest positive change in LWCRF for increasing temperature, corresponding to a warming effect on the climate system. When averaged over all clusters, weighting by frequency of cluster occurrence, the net radiative difference between warm and cold subsets is −0.5 Wm−2 K−1; this is not a statistically significant change

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