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Statistics of Black Sea Extreme Storms. / Lopatoukhin, L.; Boukhanovsky, A.; Chernysheva, E.

Proc. 10th Intern. Conf. Mediterranean Coastal Environment. MEDCOAST 09. November 2009. Sochu, Russia.. 2009. p. 701-710.

Research output: Chapter in Book/Report/Conference proceeding › Article in an anthology › Research

Harvard

Lopatoukhin, L, Boukhanovsky, A & Chernysheva, E 2009, Statistics of Black Sea Extreme Storms. in Proc. 10th Intern. Conf. Mediterranean Coastal Environment. MEDCOAST 09. November 2009. Sochu, Russia.. pp. 701-710.

APA

Lopatoukhin, L., Boukhanovsky, A., & Chernysheva, E. (2009). Statistics of Black Sea Extreme Storms. In Proc. 10th Intern. Conf. Mediterranean Coastal Environment. MEDCOAST 09. November 2009. Sochu, Russia. (pp. 701-710)

Vancouver

Lopatoukhin L, Boukhanovsky A, Chernysheva E. Statistics of Black Sea Extreme Storms. In Proc. 10th Intern. Conf. Mediterranean Coastal Environment. MEDCOAST 09. November 2009. Sochu, Russia.. 2009. p. 701-710

Author

Lopatoukhin, L. ; Boukhanovsky, A. ; Chernysheva, E. / Statistics of Black Sea Extreme Storms. Proc. 10th Intern. Conf. Mediterranean Coastal Environment. MEDCOAST 09. November 2009. Sochu, Russia.. 2009. pp. 701-710

BibTeX

@inbook{89765d1992df44798daed0d1dd0c4460,
title = "Statistics of Black Sea Extreme Storms",
abstract = "November 2007 storm in the Black sea provoke a lot of shipwrecks. It is shown, that this storm is not unique (in contrast to some official statements). Historical analogy to this storm is famous storm of November 1854, when fleets of England, France and Turkey near Sevastopol had been annihilated. These events were one of the acts to investigate statistics of Black sea storms. Model SWAN is used for continuous 40-years hindcasting of wave fields. Classification of strong (hs>5m) storms is made. A storm presented as spatial pulse moving over a sea. The parameters of this pulse are specified. Four classes (types) of storm are selected. Return period (5, 10 and 100 years) for each class is estimated.",
author = "L. Lopatoukhin and A. Boukhanovsky and E. Chernysheva",
year = "2009",
language = "не определен",
isbn = "978-605-88990-0-1 978-605-88990-2-5",
pages = "701--710",
booktitle = "Proc. 10th Intern. Conf. Mediterranean Coastal Environment. MEDCOAST 09. November 2009. Sochu, Russia.",

}

RIS

TY - CHAP

T1 - Statistics of Black Sea Extreme Storms

AU - Lopatoukhin, L.

AU - Boukhanovsky, A.

AU - Chernysheva, E.

PY - 2009

Y1 - 2009

N2 - November 2007 storm in the Black sea provoke a lot of shipwrecks. It is shown, that this storm is not unique (in contrast to some official statements). Historical analogy to this storm is famous storm of November 1854, when fleets of England, France and Turkey near Sevastopol had been annihilated. These events were one of the acts to investigate statistics of Black sea storms. Model SWAN is used for continuous 40-years hindcasting of wave fields. Classification of strong (hs>5m) storms is made. A storm presented as spatial pulse moving over a sea. The parameters of this pulse are specified. Four classes (types) of storm are selected. Return period (5, 10 and 100 years) for each class is estimated.

AB - November 2007 storm in the Black sea provoke a lot of shipwrecks. It is shown, that this storm is not unique (in contrast to some official statements). Historical analogy to this storm is famous storm of November 1854, when fleets of England, France and Turkey near Sevastopol had been annihilated. These events were one of the acts to investigate statistics of Black sea storms. Model SWAN is used for continuous 40-years hindcasting of wave fields. Classification of strong (hs>5m) storms is made. A storm presented as spatial pulse moving over a sea. The parameters of this pulse are specified. Four classes (types) of storm are selected. Return period (5, 10 and 100 years) for each class is estimated.

M3 - статья в сборнике

SN - 978-605-88990-0-1 978-605-88990-2-5

SP - 701

EP - 710

BT - Proc. 10th Intern. Conf. Mediterranean Coastal Environment. MEDCOAST 09. November 2009. Sochu, Russia.

ER -

ID: 4504547