Abstract
In the present study, the spatiotemporal and vertical distributions of ice cloud properties and their association with meteorological variables are analyzed for the period 2007–2016 using the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) and Modern Era Retrospective-Analysis for Research (MERRA-2) reanalysis observations. The distribution of ice cloud fraction (ICF) with its peak does not overlap with that of the ice water content (IWC) peak during daytime and nighttime due to the sampling bias. Moreover, the vertical distributions of mean IWC exhibited a vaguely “sharp thorn” at an altitude of ~4 km in all seasons at the location of about ±40°, which can be caused by the artifacts. Furthermore, it is noted that different ice cloud optical depth (ICOD) presents significant changes observed in their diurnal variations in the heights of peaks. The maximum diurnal difference of ice cloud properties occurs in the tropical regions of the North Hemisphere (NH) during summer. We also investigated the relation between ICOD and the meteorological variables and found that the ICOD values are dependent on the meteorological parameters.
Highlights
Ice clouds are one of the key regulators of global surface temperature
The peak is below the tropical tropopause, and decreasing in altitude steadily towards both the South Hemisphere (SH) and North Hemisphere (NH) polar regions, which can be related to the general circulation height (i.e., Hadley, Ferrel, and Polar cell)
We conducted a statistical analysis of climatology of global ice clouds properties, including ice cloud fraction (ICF), ice water content (IWC), and ice cloud optical depth (ICOD) with six sub-categories based on the 10-year (2007–2016) measurements from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) lidar observed at 532 nm
Summary
Ice clouds are one of the key regulators of global surface temperature. They have implications for the Earth’s radiative balance, hydrological cycle, atmospheric circulation, and climate change owing to their widespread occurrence and long duration [1,2]. Owing to insufficient knowledge of ice cloud microphysical properties and the complexity of remote-sensing methods, large discrepancies still occur in the scientific understanding of their climatology [6,7]. The related studies argued that the climatology of ice clouds obtained from global cloud models (GCMs) presents a relatively large difference in spatiotemporal distribution, compared with that retrieved from satellite measurements [11,12]
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