A long-term analysis of thundersnow events over the Marmara Region, Turkey

Veli Yavuz (), Anthony R. Lupo, Neil I. Fox and Ali Deniz
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Veli Yavuz: Istanbul Technical University
Anthony R. Lupo: University of Missouri
Neil I. Fox: University of Missouri
Ali Deniz: Istanbul Technical University

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2022, vol. 114, issue 1, No 15, 367-387

Abstract: Abstract This study aimed to reveal the temporal statistics, formation mechanisms, suitable land/sea surface (LS/SS) and upper-level atmospheric conditions, and predictability of thundersnow (TSSN) events that occurred between 2000 and 2021 in the Marmara Region with atmospheric stability indexes. Aviation reports from 11 airports were analyzed throughout the period, and no TSSN events were found at four airports. A total of 19 TSSN events were identified, and six events were found in 2015, when the sea-effect snow (SES) mechanisms were observed four times. The majority of TSSN events were of very short duration (0–1 h), and no significant trend was observed in terms of intraday distribution. SES mechanism was observed in 17 of the 19 TSSN events, and the dominance of northern flows was detected at all airports and at the sub-inversion upstream levels. In terms of air-sea interaction, suitable temperature differences between the SS and 850/700 hPa (17 °C and 27 °C on average), and the transfer of heat-moisture fluxes from the SS to the upper-atmosphere were possible in almost all TSSN events. In this way, meteorological parameters were sufficient for the formation and strengthening of the convective layer. In addition, the presence of directional wind shear and the observation of inversion layers restricting convective movements at higher levels instead of near the surface ensured that the moisture requirement, lifting mechanism, and unstable atmospheric conditions required for the formation of TS were provided. The CAPE values were very low for winter TSs. Total Total Index and TQ Index produced the most appropriate results for TSSN prediction.

Keywords: Thundersnow; Sea-effect snow; Snow bands; TSSN; Stability index; Marmara region (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s11069-022-05393-w

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