In Extremis : Disruptive Events and Trends in Climate and Hydrology - neues Buch

EAN (ISBN-13): 9783642148637
ISBN (ISBN-10): 3642148638
Erscheinungsjahr: 2010
Herausgeber: Springer-Verlag
400 Seiten
Sprache: eng/Englisch

Buch in der Datenbank seit 2011-09-16T08:44:53+02:00 (Vienna)
Detailseite zuletzt geändert am 2023-12-07T16:27:52+01:00 (Vienna)
ISBN/EAN: 3642148638

ISBN - alternative Schreibweisen:
3-642-14863-8, 978-3-642-14863-7
Alternative Schreibweisen und verwandte Suchbegriffe:
Autor des Buches: jürgen kropp, hans joachim schell, schellnhuber, sure hans, krop, hans much, hans will, gesellschaft ulk, deutsche pharmakologische gesellschaft
Titel des Buches: events

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Daten vom Verlag:

Autor/in: Jürgen Kropp; Hans-Joachim Schellnhuber
Titel: In Extremis - Disruptive Events and Trends in Climate and Hydrology
Verlag: Springer; Springer Berlin
320 Seiten
Erscheinungsjahr: 2010-11-03
Berlin; Heidelberg; DE
Gedruckt / Hergestellt in Deutschland.
Sprache: Englisch
149,79 € (DE)
154,00 € (AT)
177,00 CHF (CH)
Available
XV, 320 p.

EA; E107; eBook; Nonbooks, PBS / Geowissenschaften/Geografie; Ozeanographie (Meereskunde), Meere und Ozeane; Verstehen; Bootstrapping; Correlations; Extreme value assessment; Instationarity; Trend analysis; climate change impacts; hydrogeology; B; Oceanography; Climate Change/Climate Change Impacts; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Environmental Physics; Atmospheric Sciences; Hydrogeology; Ocean Sciences; Climate Sciences; Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Environmental Physics; Atmospheric Science; Geology; Earth and Environmental Science; Meteorologie und Klimatologie (Klimaforschung); Wahrscheinlichkeitsrechnung und Statistik; Umwelt; Angewandte Physik; Geologie und die Lithosphäre; BB

The book addresses a weakness of current methodologies used in extreme value assessment, i.e. the assumption of stationarity, which is not given in reality. With respect to this issue a lot of new developed technologies are presented, i.e. influence of trends vs. internal correlations, quantitative uncertainty assessments, etc. The book not only focuses on artificial time series data, but has a close link to empirical measurements, in order to make the suggested methodologies applicable for practitioners in water management and meteorology.