Anette Ganske

Anette Ganske


Research Focus & Metrics

Academic Career Length

33Years (1994-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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31 March 2022 in Data Science Journal
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Journal Article
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GPGe Peng
Ge Peng
CLCarlo Lacagnina
Carlo Lacagnina
RDRobert R. Downs
Robert R. Downs
AGAnette Ganske
Anette Ganske
HRHampapuram Ramapriyan
Hampapuram Ramapriyan
DMDavid F. Moroni
David F. Moroni

4 July 2018 in Ocean Dynamics
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Journal Article
Closed access
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AGAnette Ganske
Anette Ganske
NFNatacha Fery
Natacha Fery
LGLidia Gaslikova
Lidia Gaslikova
IGIris Grabemann
Iris Grabemann
RWRalf Weisse
Ralf Weisse
BTBirger Tinz
Birger Tinz

5 September 2016 in Meteorologische Zeitschrift
Verified
Journal Article
Open access
MGMarie Gerber
Marie Gerber
AGAnette Ganske
Anette Ganske
SMSylvin Müller-Navarra
Sylvin Müller-Navarra
GRGudrun Rosenhagen
Gudrun Rosenhagen

26 April 2013 in Ocean Dynamics
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Journal Article
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SDSönke Dangendorf
Sönke Dangendorf
CMChristoph Mudersbach
Christoph Mudersbach
JJJürgen Jensen
Jürgen Jensen
AGAnette Ganske
Anette Ganske
HHHartmut Heinrich
Hartmut Heinrich

5 September 2016 in Meteorologische Zeitschrift
Verified
Journal Article
Open access
AGAnette Ganske
Anette Ganske
BTBirger Tinz
Birger Tinz
GRGudrun Rosenhagen
Gudrun Rosenhagen
HHHartmut Heinrich
Hartmut Heinrich

30 June 2015 in Natural Hazards and Earth System Sciences
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Journal Article
Open access
DBD. J. Befort
D. J. Befort
MFM. Fischer
M. Fischer
GLG. C. Leckebusch
G. C. Leckebusch
UUUwe Ulbrich
Uwe Ulbrich
AGAnette Ganske
Anette Ganske
HHH. Heinrich
H. Heinrich
A new procedure for the identification of storm surge situations for the German Bight is developed and applied to reanalysis and global climate model data. This method is based on the empirical approach for estimating storm surge heights using information about wind speed and wind direction. Here, we hypothesize that storm surge events are caused by high wind speeds from north-westerly direction in combination with a large-scale wind storm event affecting the North Sea region. The method is calibrated for ERA-40 data, using the data from the storm surge atlas for Cuxhaven. It is shown that using information of both wind speed and direction as well as large-scale wind storm events improves the identification of storm surge events. To estimate possible future changes of potential storm surge events, we apply the new identification approach to an ensemble of three transient climate change simulations performed with the ECHAM5/MPIOM model under A1B greenhouse gas scenario forcing. We find an increase in the total number of potential storm surge events of about 12 % [(2001–2100)–(1901–2000)], mainly based on changes of moderate events. Yearly numbers of storm surge relevant events show high interannual and decadal variability and only one of three simulations shows a statistical significant increase in the yearly number of potential storm surge events between 1900 and 2100. However, no changes in the maximum intensity and duration of all potential events is determined. Extreme value statistic analysis confirms no frequency change of the most severe events.