Long-term cloud cover trends over the U.S. from ground-based data and satellite products
Hyelim Yoo, Melissa Free, and Bomin Sun
Clouds play a critically important role in regulating the Earth radiative energy budget and the hydrologic cycle. Especially, cloud cover influences surface solar radiation as well as cloud feedbacks, so it is important to advance our knowledge of long-term cloud cover trends with observations. This study compares the long-term cloud cover time series over the U.S. from different satellite products using a homogeneity-adjusted dataset with 54 National Weather Service (NWS) and 101 military stations. Significant effort has been given to characterizing long-term trends in cloud cover time series and correlations between the U.S mean total cloud cover retrieved from satellites and weather station data. ISCCP (International Satellite Cloud Climatology Project), PATMOS-x (Pathfinder Atmospheres Extended) and CLARA-A1 (CM SAF cLoud Albedo and RAdiation), and the recently developed PATMOS-x diurnally corrected dataset are used in this study. Most of the satellite products show good agreement with the station data for inter-annual and anomaly variability. Correlations between satellite products and station data are statistically significant for ISCCP and PATMOS-x but not for CLARA-A1, and all datasets have negative trends in total cloud cover. We find that the PATMOS-x diurnally corrected product has the best match to the station data in terms of correlation and cloud cover trends for the time period of 1984-2007.