Evaluation of CERES and CloudSat Surface Radiative Fluxes Over Macquarie Island, the Southern Ocean

• Published in: Earth and Space Science
• Main Authors: Laura M. Hinkelman, Roger Marchand
• Format: Article in Journal/Newspaper
• Language: English
• Published: American Geophysical Union (AGU) 2020
• Subjects: surface radiative fluxes; Southern Ocean; Macquarie Island; MICRE; Astronomy; QB1-991; Geology; QE1-996.5
• Online Access: https://doi.org/10.1029/2020EA001224; https://doaj.org/article/d60bc87dce004545bba51283f2d74189

Abstract Many studies involving surface radiative fluxes rely on surface fluxes retrieved by the Clouds and the Earth's Radiant Energy System (CERES) project or derived from spaceborne cloud radar and lidar observations (CloudSat‐CALIPSO). In particular, most climate models that participated in the Coupled Model Intercomparison Project Phase 5 (CMIP5) were found to have too little shortwave (SW) radiation being reflected back to space and excessive SW radiation reaching the surface over the Southern Ocean—an error with significant consequences for predicting both regional and global climate. There have been few evaluations of CERES or CloudSat retrievals over the Southern Ocean. In this article, CERES and CloudSat retrieved surface SW and longwave (LW) downwelling fluxes are evaluated using surface observations collected over the Southern Ocean during the Macquarie Island Cloud and Radiation Experiment (MICRE). Overall, biases (CERES—surface observations) in the CERES‐surface fluxes are found to be slightly larger over Macquarie Island than most other regions, approximately +10 W m−2 for the SW and −10 W m−2 for the LW in the annual mean, but with significant seasonal and diurnal variations. If the Macquarie observations are representative of the larger SO, these results imply that CMIP5 model errors in SW surface fluxes are (if anything) somewhat larger than previous evaluation studies suggest. The bias in LW surface flux shows a marked increase at night, which explains most of the total LW bias. The nighttime bias is due to poor representation of cloud base associated with low clouds.