Errors in cloud detection over the arctic using a satellite imager and implications for observing feedback mechanisms

Abstract

Arctic sea ice extent has decreased dramatically over the last 30 years, and this trend is expected to continue through the twenty-first century. Changes in sea ice extent impact cloud cover, which in turn influences the surface energy budget. Understanding cloud feedback mechanisms requires an accurate determination of cloud cover over the polar regions, which must be obtained from satellite-based measurements. The accuracy of cloud detection using observations from space varies with surface type, complicating any assessment of climate trends aswell as the understanding of ice-albedo and cloud-radiative feedbackmechanisms. To explore the implications of this dependence on measurement capability, cloud amounts from the Moderate Resolution Imaging Spectroradiometer (MODIS) are compared with those from the CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder (CALIPSO) satellites in both daytime and nighttime during the time period from July 2006 to December 2008. MODIS is an imager that makes observations in the solar and infrared spectrum. The active sensors of CloudSat and CALIPSO, a radar and lidar, respectively, provide vertical cloud structures along a narrow curtain. Results clearly indicate that MODIS cloud mask products perform better over open water than over ice. Regional changes in cloud amount from CloudSat/CALIPSO and MODIS are categorized as a function of independent measurements of sea ice concentration (SIC) from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E). As SIC increases from 10% to 90%, the mean cloud amounts from MODIS and CloudSat-CALIPSO both decrease; water that is more open is associated with increased cloud amount. However, this dependency on SIC is much stronger for MODIS than for CloudSat-CALIPSO, and is likely due to a low bias in MODIS cloud amount. The implications of this on the surface radiative energy budget using historical satellite measurements are discussed. The quantified ice-water difference in MODIS cloud detection can be used to adjust estimated trends in cloud amount in the presence of changing sea ice cover from an independent dataset. It was found that cloud amount trends in the Arctic might be in error by up to 2.7% per decade. The impact of these errors on the surface net cloud radiative effect ("forcing") of the Arctic can be significant, as high as 8.5%. © 2010 American Meteorological Society.