Abstract
In this study, the climatologies of three different satellite cloud products, all based on passive sensors (CERES Edition 4.1 [EBAF4.1 and SYN4.1] and ISCCP–H), were evaluated against the CALIPSO-GOCCP (GOCCP) data, which are based on active sensors and, hence, were treated as the reference. Based on monthly averaged data (ocean + land), the passive sensors underestimated the total cloud cover (TCC) at lower (TCC < 50%), but, overall, they correlated well with the GOCCP data (r = 0.97). Over land, the passive sensors underestimated the TCC, with a mean difference (MD) of −2.6%, followed by the EBAF4.1 and ISCCP-H data with a MD of −2.0%. Over the ocean, the CERES-based products overestimated the TCC, but the SYN4.1 agreed better with the GOCCP data. The ISCCP-H data on average underestimated the TCC both over oceanic and continental regions. The annual mean TCC distribution over the globe revealed that the passive sensors generally underestimated the TCC over continental dry regions in northern Africa and southeastern South America as compared to the GOCCP, particularly over the summer hemisphere. The CERES datasets overestimated the TCC over the Pacific Islands between the Indian and eastern Pacific Oceans, particularly during the winter hemisphere. The ISCCP-H data also underestimated the TCC, particularly over the southern hemisphere near 60° S where the other datasets showed a significantly enhanced TCC. The ISCCP data also showed less TCC when compared against the GOCCP data over the tropical regions, particularly over the southern Pacific and Atlantic Oceans near the equator and also over the polar regions where the satellite retrieval using the passive sensors was generally much more challenging. The calculated global mean root meant square deviation value for the ISCCP-H data was 6%, a factor of 2 higher than the CERES datasets. Based on these results, overall, the EBAF4.1 agreed better with the GOCCP data.
Highlights
Clouds cover a large portion of the Earth’s atmosphere at any given time and play a significant role in the weather and climate systems of the Earth by regulating its radiative balance and hydrological cycle
There are, some examples of localized studies that compared the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) and some other datasets based on passive satellite sensors against ground based measurements [17,18], and the results showed that the active sensors provide better results as compared to the passive sensors
The two Clouds and the Earth’s Radiant Energy System (CERES) products EBAF4.1 and SYN4.1 were compared in the plot (d)
Summary
Clouds cover a large portion of the Earth’s atmosphere at any given time and play a significant role in the weather and climate systems of the Earth by regulating its radiative balance and hydrological cycle. Based on numerous International Plan on Climate Change (IPCC) reports and modeling studies [1,2,3], the current general circulation models (GCMs) suffer from significant uncertainties in predicting the future climate. One of the main sources of these uncertainties is believed to be related to the representation of clouds [3,4,5,6,7]. As the temperature increases because of global warming, GCMs predict that the cloud cover will change because of radiative feedback mechanisms [8].
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