Variability of multilayer cloud structure over Western and Eastern Siberia in summer and winter in 2006-2023 based on CALIPSO data
A.V. Skorokhodov, K.V. Kuryanovich
V.E. Zuev Institute of Atmospheric Optics of Siberian Branch of the Russian Academy of Science, Tomsk, Russia
Keywords: time series, Western Siberia, Eastern Siberia, long-term trend, cloud classification, multilayer cloud cover, satellite data
Abstract
One of the indicators of ongoing climate change is the evolution of cloud regimes, both in individual regions and globally. Within this framework, the long-term variability in the structure of multilayered clouds with an optical thickness of less than 15 over Western and Eastern Siberia during the summer and winter seasons from 2006 to 2023 in daytime conditions is estimated based on CALIOP lidar data (CALIPSO satellite). Multilayering refers to the presence of clouds in several levels at the same time located under each other with gaps between them. The applied methodology is based on the use of cloud classification results from daily CALIOP lidar measurements, calculation of seasonal recurrence values for each combination of cloud types in multilayer structure, deriving time series, determining trends, and evaluating their parameters. It was found that the fractions of clouds with different numbers of layers over both regions did not significantly change during the period under study. In Western Siberia, the proportion of double-layer clouds is 68% in summer and 71% in winter, while in Eastern Siberia, 71 and 75%, respectively. The fraction of three-layer clouds reaches 27% in summer and 25% in winter in Western Siberia and 26% and 23% in Eastern Siberia. The fractions of four- and five-layer clouds do not exceed 5% in both regions together and are almost the same in the two seasons. The most frequent combinations in the multilayer clouds over Western and Eastern Siberia were determined. Estimates of linear trends in the fraction of the most frequent variations in multilayer clouds over the period under study are presented. The results can contribute to improving the accuracy of climate models and radiative transfer estimates.
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