Comparing methods to estimate cloud cover over the Baikal Natural Territory in December 2020.

Author:

Podlesny Stepan1,Devyatova Elena2,Saunkin Andrey3,Vasilyev Roman1

Affiliation:

1. Institute of Solar Terrestrial Physics SB RAS

2. Institut solnechno-zemnoy fiziki SO RAN

3. Institute of Solar-Terrestrial Physics SB RAS

Abstract

The paper addresses the issue of how much cloud cover data obtained using satellite and model-interpolation techniques are suitable for monitoring the transparency of the atmosphere and determining conditions for airglow observations at a local geophysical observatory. For this purpose, we compared the temporal dynamics of cloud cover from ECMWF’s ERA5 reanalysis and NOAA satellites with the night atmosphere transparency according to a digital camera. We considered the dynamics of the addressed parameters at the Geophysical Observatory of the Institute of Solar-Terrestrial Physics, located in the Baikal Natural Territory near the village of Tory (Republic of Buryatia, Russia), during December 2020. The comparative analysis showed a generally good agreement between cloud cover data from ECMWF’s ERA5 climate reanalysis and those observed with the camera. Disadvantages are the lack of information on rapid variations in cloud cover in the reanalysis and positive and negative delays in the dynamics of cloud fields that last about two hours. Due to irregular satellite data, large time gaps between passes and difficulties in estimating cloud cover at night, we could not come to reliable conclusions concerning the applicability of satellite data.

Publisher

Infra-M Academic Publishing House

Subject

General Medicine

Reference20 articles.

1. Дарчия Ш.П. Об астрономическом климате СССР. М.: Наука, 1985. 175 с., Ahlgrimm M., Forbes R. Improving the representation of low clouds and drizzle in the ECMWF model based on ARM observations from the Azores. Monthly Weather Review. 2014, vol. 142, iss. 2, pp. 668–685. DOI: 10.1175/MWR-D-13-00153.1.

2. Загайнова Ю.С., Караваев Ю.С. Оценка состояния облачности по 8-балльной шкале методом гистограмм по изображениям в видимом диапазоне, получаемым с камеры полного неба. Солнечно-земная физика. 2013. Вып. 23. С. 120–128., Darchia Sh.P. Ob astronomicheskom climate SSSR [On the astronomical climate of the USSR]. Moscow, Nauka Publ., 1985, 175 p. (In Russian).

3. Здор С.Е., Колинько В.И. Датчик ночной облачности. Патент RU 2436133 C2. 2011., Forbes R.M., Ahlgrimm M. On the representation of high-latitude boundary-layer mixed-phase cloud in the ECMWF global model. Monthly Weather Review. 2014, vol. 142, iss. 9, pp. 3425–3445. DOI: 10.1175/MWR-D-13-00325.1.

4. Казаковцев А.Ф., Колинько В.И. Способ оценки облачности ночной атмосферы и датчик ночной облачности для его осуществления. Патент RU 2678950 C1. 2019., Forbes R.M., Tompkins A.M. An improved representation of cloud and precipitation. ECMWF Newsletter. 2011, vol. 129, pp. 13–18. DOI: 10.21957/nfgulzhe.

5. Кокарев Д.В., Галилейский В.П., Морозов А.М., Елизаров А.И. Устройство наблюдения оптического состояния неба в пределах видимой полусферы. Патент RU 191582 U1. 2019., Forbes R.M., Tompkins A.M., Untch A. A new prognostic bulk microphysics scheme for the IFS. ECMWF Technical Memorandum No. 649. 2011, 28 p. DOI: 10.21957/bf6vjvxk.

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Russian Studies on Clouds and Precipitation in 2019–2022;Известия Российской академии наук. Физика атмосферы и океана;2023-12-01

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