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RAS Earth ScienceИзвестия Российской академии наук. Физика атмосферы и океана Izvestiya, Atmospheric and Oceanic Physics

  • ISSN (Print) 0002-3515
  • ISSN (Online) 3034-6487

ASSESSMENT OF STATISTICAL CHARACTERISTICS OF CLOUD LIQUID WATER PATH OVER LAND SURFACE AND WATER BODIES IN THE BALTIC SEA REGION AND THE NORTHWEST RUSSIA BASED ON SEVIRI SATELLITE INSTRUMENT DATA

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PII
S3034648725050109-1
DOI
10.7868/S3034648725050109
Publication type
Article
Status
Published
Authors
V.S. Kostsov
  • Affiliation: Saint Petersburg State University
D.V. Ionov
  • Affiliation: Saint Petersburg State University
A.B. Andryukova
  • Affiliation: Saint Petersburg State University
Volume/ Edition
Volume 61 / Issue number 5
Pages
661-682
Abstract
The results of remote sensing of cloud liquid water path (LWP) by the SEVIRI satellite instrument in the Baltic Sea region and northwestern Russia in 2011–2017 are analyzed. For a detailed study, characteristic geographic points in the water areas of large water bodies and on land were selected. Based on special criteria, the LWP measurement data were selected into several separate arrays, which made it possible to study both the so-called «intrinsic» properties of clouds and the properties of the cloudy/cloudless atmosphere as a whole. The main conclusions of the work were obtained for non-precipitating clouds with LWP not exceeding the threshold value of 0.4 kg · m. Precipitating clouds were classified as having LWP of more than 0.4 kg · m and were considered separately. The statistical distributions of cloud liquid water path, as well as its interannual and seasonal variability, were analyzed. The analysis of the seasonal variation is limited to the period from February to October due to the lack of SEVIRI measurements in autumn/winter when the solar zenith angle is large. For all the considered data arrays, the obtained main statistical characteristics are presented in tabular form, which can be used for solving problems of cloud modeling, weather forecasting and climate change, as well as for composing statistical models of the cloudy atmosphere applied for training of regression and neural network algorithms for derivation of the cloud LWP from remote measurements.
Keywords
водозапас облаков тропосфера межгодовая и сезонная изменчивость параметров облачности дистанционное зондирование метеорологические спутники прибор SEVIRI
Date of publication
09.04.2025
Year of publication
2025
Number of purchasers
0
Views
12

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