Arctic Cloud Characteristics as Derived from MODIS, CALIPSO, and CloudSat

Abstract

he Moderate Resolution Imaging Spectroradiometer (MODIS), Cloud?Aerosol Lidar with Orthogonal Polarization (CALIOP), and CloudSat Cloud Profiling Radar (CPR) set of sensors, all in the Afternoon Constellation (A-Train), has been regarded as among the most powerful tools for characterizing the cloud cover. While providing good complementary information, the authors also observed that, at least for the Arctic region, the different sensors provide significantly different statistics about cloud cover characteristics. Data in 2007 and 2010 were analyzed, and the annual averages of cloud cover in the Arctic region were found to be 66.8%, 78.4%, and 63.3% as derived from MODIS, CALIOP, and CPR, respectively. A large disagreement between MODIS and CALIOP over sea ice and Greenland is observed, with a cloud percentage difference of 30.9% and 31.5%, respectively. In the entire Arctic, the average disagreement between MODIS and CALIOP increased from 13.1% during daytime to 26.7% during nighttime. Furthermore, the MODIS cloud mask accuracy has a high seasonal dependence, in that MODIS?CALIOP disagreement is the lowest during summertime at 10.7% and worst during winter at 28.0%. During nighttime the magnitude of the bias is higher because cloud detection is limited to the use of infrared bands. The clouds not detected by MODIS are typically low-level (top height <2 km) and high-level clouds (top height >6 km) and, especially, those that are geometrically thin (<2 km). Geometrically thin clouds (<2 km) accounted for about 95.5% of all clouds that CPR misses. As reported in a similar study, very low and thin clouds (<0.3 km) over sea ice that are detected by MODIS are sometimes not observed by CPR and misclassified by CALIOP.