The Surface Longwave Cloud Radiative Effect from Space Lidar Observations

Clouds exert important effects on Earth's surface energy balance through their effects on longwave (LW) and shortwave (SW) radiation. Indeed, clouds radiatively warm the surface in the LW domain by emitting LW radiation back to the ground. The surface LW cloud radiative effect (CRE) quantifies this warming effect. To study the impact of clouds on the interanual natural climate variability, we need to observe them on a long time scale over all kinds of surfaces. The CALIPSO space lidar provides these observations by sampling the atmosphere along its track over all kinds of surfaces for over than 14 years (2006-2020).

In this work, we propose new estimates of the surface LW CRE from space-based lidar observations only. Indeed, we show from 1D atmospheric column radiative transfer calculations, that surface LW CRE at sea level linearly decreases with the cloud altitude. Thus, these computations allow to establish simple relationships between the surface LW CRE, and five cloud properties observed by the CALIPSO space lidar: the opaque cloud cover and altitude, the thin cloud cover, altitude, and emissivity. Over the 2008–2011, CALIPSO-based retrieval (27.7 W m^-2) is 1.2 W m^-2 larger than the one derived from combined space radar, lidar, and radiometer observations. Over the 2008–2018 period, the global mean CALIPSO-based retrieval (27.5 W m^-2) is 0.1 W m^-2 larger than the one derived from CERES space radiometer. Our estimates show that globally, opaque clouds warm the surface by 23.3 W m^-2 and thin clouds contribute only by 4.2 W m^-2. At high latitudes North and South over oceans, the largest surface LW opaque CRE occurs in fall (40.4 W m^-2, 31.6 W m^-2) due to the formation of additional opaque low clouds after sea ice melting over a warmer ocean.

To quantify the cloud property that drives the temporal variations of the surface LW CRE, the surface LW CRE needs to be related by simple relationships to a finite number of cloud properties such as cloud opacity, cloud altitude and cloud cover. This study allows a decomposition and attribution approach of the surface LW CRE variations and shows that they are driven by the variations occurring in the opaque cloud properties. Moreover, opaque cloud cover drives over than 73% of global surface LW CRE interannual variations.