Abstract

Abstract. According to climate model simulations, the changing altitude of middle and high clouds is the dominant contributor to the positive global mean longwave cloud feedback. Nevertheless, the mechanisms of this longwave cloud altitude feedback and its magnitude have not yet been verified by observations. Accurate, stable, and long-term observations of a metric-characterizing cloud vertical distribution that are related to the longwave cloud radiative effect are needed to achieve a better understanding of the mechanism of longwave cloud altitude feedback. This study shows that the direct measurement of the altitude of atmospheric lidar opacity is a good candidate for the necessary observational metric. The opacity altitude is the level at which a spaceborne lidar beam is fully attenuated when probing an opaque cloud. By combining this altitude with the direct lidar measurement of the cloud-top altitude, we derive the effective radiative temperature of opaque clouds which linearly drives (as we will show) the outgoing longwave radiation. We find that, for an opaque cloud, a cloud temperature change of 1 K modifies its cloud radiative effect by 2 W m−2. Similarly, the longwave cloud radiative effect of optically thin clouds can be derived from their top and base altitudes and an estimate of their emissivity. We show with radiative transfer simulations that these relationships hold true at single atmospheric column scale, on the scale of the Clouds and the Earth's Radiant Energy System (CERES) instantaneous footprint, and at monthly mean 2° × 2° scale. Opaque clouds cover 35 % of the ice-free ocean and contribute to 73 % of the global mean cloud radiative effect. Thin-cloud coverage is 36 % and contributes 27 % of the global mean cloud radiative effect. The link between outgoing longwave radiation and the altitude at which a spaceborne lidar beam is fully attenuated provides a simple formulation of the cloud radiative effect in the longwave domain and so helps us to understand the longwave cloud altitude feedback mechanism.

Highlights

  • Cloud feedbacks remain the main source of uncertainty in predictions of climate sensitivity (e.g., Dufresne and Bony, 2008; Vial et al, 2013; Webb et al, 2013; Caldwell et al, 2016)

  • We summarize the vertical profiles of clouds observed by active sensors using three specific cloud levels that drive the LW cloud radiative effect (CRE) at the TOA and that can be accurately observed by spaceborne lidar: cloud-top altitude, cloud-base altitude, and the altitude of opacity, at which the lidar signal becomes fully attenuated within an opaque cloud

  • Such simple models exist in the SW domain but not in the LW domain, because LW fluxes are sensitive to the cloud vertical distribution, making the definition of such a simple model more challenging

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Summary

Introduction

Cloud feedbacks remain the main source of uncertainty in predictions of climate sensitivity (e.g., Dufresne and Bony, 2008; Vial et al, 2013; Webb et al, 2013; Caldwell et al, 2016). It is useful to identify the fundamental variables driving the climate radiative response and to decompose the overall radiative response as the sum of the individual responses due to changes in each of these variables. This classical feedback analysis has been frequently applied to outputs from numerical cli-. The shortwave (SW) cloud feedback is primarily driven by changes in cloud cover and cloud optical depth, whereas the longwave (LW) cloud feedback is driven by changes in cloud cover, cloud optical depth, and cloud vertical distribution (e.g., Klein and Jakob, 1999; Zelinka et al, 2012b, 2013, 2016)

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