Arctic clouds and surface radiation: a critical comparison of satellite retrievals and the ERA-Interim reanalysis

• Main Authors: Zygmuntowska, Marta, Mauritsen, Thorsten, Quaas, Johannes, Kaleschke, Lars
• Other Authors: May-Planck-Institut für Meteorologie, 2Nansen Environmental and Remote Sensing Center, Universität Leipzig, Universität Hamburg, Copernicus Publications
• Format: Article in Journal/Newspaper
• Language: English
• Published: 2015
• Subjects: info:eu-repo/classification/ddc/551; ddc:551; Klima; Atmosphäre; Wolken; climate; atmosphere; clouds; Arctic
• Online Access: https://nbn-resolving.org/urn:nbn:de:bsz:15-qucosa-185357; https://ul.qucosa.de/id/qucosa%3A13793; https://ul.qucosa.de/api/qucosa%3A13793/attachment/ATT-0/

Clouds regulate the Earth’s radiation budget, both by reflecting part of the incoming sunlight leading to cooling and by absorbing and emitting infrared radiation which tends to have a warming effect. Globally averaged, at the top of the atmosphere the cloud radiative effect is to cool the climate, while at the Arctic surface, clouds are thought to be warming. Here we compare a passive instrument, the AVHRR-based retrieval from CM-SAF, with recently launched active instruments onboard CloudSat and CALIPSO and the widely used ERA-Interim reanalysis. We find that in particular in winter months the three data sets differ significantly. While passive satellite instruments have serious difficulties, detecting only half the cloudiness of the modeled clouds in the reanalysis, the active instruments are in between. In summer, the two satellite products agree having monthly means of 70–80 percent, but the reanalysis are approximately ten percent higher. The monthly mean long- and shortwave components of the surface cloud radiative effect obtained from the ERAInterim reanalysis are about twice that calculated on the basis of CloudSat’s radar-only retrievals, while ground based measurements from SHEBA are in between. We discuss these differences in terms of instrument-, retrieval- and reanalysis characteristics, which differ substantially between the analyzed datasets.