Statistics of precipitable water vapour, optical thickness and cloud cover within the Northern part of Eurasia

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Abstract

One of the most important tasks in astroclimatic studies of possible locations for the Eurasian Submillimeter Telescopes is estimating statistics of precipitable water vapour, optical thickness and cloud cover. In this paper, the statistics of precipitable water vapour and total cloud cover within Northern part of Eurasia are studied using ERA-5 reanalysis. Optical thickness statistics at a wavelength of 3 mm were obtained using the Liebe model from the ERA-5 reanalysis for the region where the BTA is located. The most favorable astroclimatic zones of Eurasia include Tibet and the Eastern Pamirs, certain regions of the Sayan Mountains, Altai and Mts within Dagestan. Also we verified the ERA-5 reanalysis data using radiosonde data, GNSS measurement data and radiometric measurements for 2021.

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About the authors

V. В. Khaikin

Special Astrophysical Observatory of the Russian Academy of Sciences; Institute of Astronomy, Russian Academy of Sciences

Email: Ashikhovtsev@iszf.irk.ru
Russian Federation, Nizhnij Arkhyz, Zelenchukskiy Region, Karachai-Cherkessian; Moscow

A. Yu. Shikhovtsev

Institute of Solar-Terrestrial Physics, the Siberian Branch of the Russian Academy of Sciences

Author for correspondence.
Email: Ashikhovtsev@iszf.irk.ru
Russian Federation, Irkutsk

A. P. Mironov

Sternberg Astronomical Institute of Moscow State University; Institute of Astronomy, Russian Academy of Sciences

Email: Ashikhovtsev@iszf.irk.ru
Russian Federation, Moscow; Moscow

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Supplementary files

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2. Fig. 1. Map of the location of the GNSS stations used. Commonly accepted station designations: MDVJ — Mendeleevo, LAVH — State Budgetary Institution Mosgorgeotrest, 7 km from Dolgoprudny, CAOD — radiosonde station in Dolgoprudny, CNG1 — Center of Geodesy and Cartography, 7 km from Dolgoprudny.

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3. Fig. 2. Changes in PWV [mm] in January 2021, estimated based on Era-5 reanalysis data in Mendeleev (PWV ERA-5Mnd), GNSS station measurements (PWV GNSMDVJ, PWV GNSLAVH, PWV GNSCNG1), RVP in Mendeleev (PWV WVRMnd) and radiosonde data in Dolgoprudny (PWV RSDp). The blue dotted line shows changes in precipitation levels based on measurements at the Tushino station.

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4. Fig. 3. Scatterplot of Pearson correlation coefficients for precipitable water vapor for 2021. The figure shows PWV [mm] values ​​determined from different data. The diagonal shows histograms describing the distributions of time-consistent Pearson correlation coefficients between PWV values. MDVJ — Mendeleevo, LAVH — State Budgetary Institution Mosgorgeotrest, CAOD — Dolgoprudny radiosonde station, CNG1 — Center for Geodesy and Cartography, ERAM and ERAD — reanalysis grid nodes closest to Mendeleevo and Dolgoprudny.

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5. Fig. 4. Spatial distribution of precipitated water vapor PWV [mm] at night in northern Eurasia for altitudes above 2500 m, averaged from December to February for the period 2013–2022.

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6. Fig. 5. Spatial distribution of the proportion of total cloudiness at night in northern Eurasia for altitudes above 2500 m, averaged from December to February for the period 2013–2022.

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7. Fig. 6. The probability function of the recurrence of hourly values ​​of the optical thickness for a wavelength of 3 mm, estimated from the ERA-5 reanalysis data, for the location of the Large Azimuth Telescope. The black line corresponds to the cumulative probability of recurrence, the blue line to the kernel estimate of the distribution density.

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8. Fig. 7. The probability function of the recurrence of optical thickness values ​​for a radiation wavelength of 3 mm, obtained from radiometric measurements, adapted from the work of Bubnov [34], for the location of the Large Azimuth Telescope. The black line corresponds to the accumulated probability of recurrence, the blue line to the nuclear estimate of the distribution density.

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