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Statements

Subject Item
n2:RIV%2F00216208%3A11320%2F14%3A10292083%21RIV15-MSM-11320___
rdf:type
n5:Vysledek skos:Concept
rdfs:seeAlso
http://link.springer.com/article/10.1007/s11633-014-0788-3
dcterms:description
The growth of small errors in weather prediction is exponential on average. As an error becomes larger, its growth slows down and then stops with the magnitude of the error saturating at about the average distance between two states chosen randomly. This paper studies the error growth in a low-dimensional atmospheric model before, during and after the initial exponential divergence occurs. We test cubic, quartic and logarithmic hypotheses by ensemble prediction method. Furthermore, the quadratic hypothesis suggested by Lorenz in 1969 is compared with the ensemble prediction method. The study shows that a small error growth is best modeled by the quadratic hypothesis. After the error exceeds about a half of the average value of variables, logarithmic approximation becomes superior. It is also shown that the time length of the exponential growth in the model data is a function of the size of small initial error and the largest Lyapunov exponent. We conclude that the size of the error at the least upper bound (supremum) of time length is equal to 1 and it is invariant to these variables. Predictability, as a time interval, where the model error is growing, is for small initial error, the sum of the least upper bound of time interval of exponential growth and predictability for the size of initial error equal to 1. The growth of small errors in weather prediction is exponential on average. As an error becomes larger, its growth slows down and then stops with the magnitude of the error saturating at about the average distance between two states chosen randomly. This paper studies the error growth in a low-dimensional atmospheric model before, during and after the initial exponential divergence occurs. We test cubic, quartic and logarithmic hypotheses by ensemble prediction method. Furthermore, the quadratic hypothesis suggested by Lorenz in 1969 is compared with the ensemble prediction method. The study shows that a small error growth is best modeled by the quadratic hypothesis. After the error exceeds about a half of the average value of variables, logarithmic approximation becomes superior. It is also shown that the time length of the exponential growth in the model data is a function of the size of small initial error and the largest Lyapunov exponent. We conclude that the size of the error at the least upper bound (supremum) of time length is equal to 1 and it is invariant to these variables. Predictability, as a time interval, where the model error is growing, is for small initial error, the sum of the least upper bound of time interval of exponential growth and predictability for the size of initial error equal to 1.
dcterms:title
Initial Error Growth and Predictability of Chaotic Low-dimensional Atmospheric Model Initial Error Growth and Predictability of Chaotic Low-dimensional Atmospheric Model
skos:prefLabel
Initial Error Growth and Predictability of Chaotic Low-dimensional Atmospheric Model Initial Error Growth and Predictability of Chaotic Low-dimensional Atmospheric Model
skos:notation
RIV/00216208:11320/14:10292083!RIV15-MSM-11320___
n3:aktivita
n14:S n14:Z
n3:aktivity
S, Z(MSM0021620860)
n3:cisloPeriodika
3
n3:dodaniDat
n19:2015
n3:domaciTvurceVysledku
n4:6222536 n4:4972570 n4:6598986
n3:druhVysledku
n9:J
n3:duvernostUdaju
n18:S
n3:entitaPredkladatele
n7:predkladatel
n3:idSjednocenehoVysledku
21864
n3:idVysledku
RIV/00216208:11320/14:10292083
n3:jazykVysledku
n10:eng
n3:klicovaSlova
Model; Atmospheric; Low-dimensional; Chaotic; Predictability; Growth; Error; Initial
n3:klicoveSlovo
n6:Error n6:Atmospheric n6:Initial n6:Low-dimensional n6:Growth n6:Model n6:Predictability n6:Chaotic
n3:kodStatuVydavatele
DE - Spolková republika Německo
n3:kontrolniKodProRIV
[05E12912AAA0]
n3:nazevZdroje
International Journal of Automation and Computing
n3:obor
n13:IN
n3:pocetDomacichTvurcuVysledku
3
n3:pocetTvurcuVysledku
3
n3:rokUplatneniVysledku
n19:2014
n3:svazekPeriodika
11
n3:tvurceVysledku
Bednář, Hynek Mikšovský, Jiří Raidl, Aleš
n3:zamer
n15:MSM0021620860
s:issn
1476-8186
s:numberOfPages
9
n17:doi
10.1007/s11633-014-0788-3
n8:organizacniJednotka
11320