Statistical Modelling in Climate Science

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F16%3A00462914" target="_blank" >RIV/67985807:_____/16:00462914 - isvavai.cz</a>
Alternative codes found
RIV/00216208:11320/16:10335131
Result on the web
<a href="http://ceur-ws.org/Vol-1649/102.pdf" target="_blank" >http://ceur-ws.org/Vol-1649/102.pdf</a>
DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Statistical Modelling in Climate Science
Original language description
When it comes to modelling in atmospheric and climate science, the two main types of models are taken into account - dynamical and statistical models. The former ones have a physical basis: they utilize discretized differential equations with a set of conditions (boundary conditions + present state as an initial condition) and model the system’s state by integrating the equations forward in time. Models of this type are currently used e.g. as a numerical weather prediction models. The statistical models are considerably different: they are not based on physical mechanisms underlying the dynamics of the modelled system, but rather derived from the analysis of past weather patterns. An example of such a statistical model based on the idea of linear inverse modelling, is examined for modelling the El Nino - Southern Oscillation phenomenon with a focus on modelling cross-scale interactions in the temporal sense. Various noise parameterizations and the possibility of using a multi-variable model is discussed among other characteristics of the statistical model. The prospect of using statistical models with low complexity as a surrogate model for statistical testing of null hypotheses is also discussed.
Czech name
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Czech description
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Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings ITAT 2016: Information Technologies - Applications and Theory
ISBN
978-1-5370-1674-0
ISSN
1613-0073
e-ISSN
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Number of pages
8
Pages from-to
102-109
Publisher name
Technical University & CreateSpace Independent Publishing Platform
Place of publication
Aachen & Charleston
Event location
Tatranské Matliare
Event date
Sep 15, 2016
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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