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Statements

Subject Item
n2:RIV%2F00216208%3A11320%2F14%3A10292089%21RIV15-MSM-11320___
rdf:type
skos:Concept n16:Vysledek
rdfs:seeAlso
http://www.springer.com/gp/book/9783319074009
dcterms:description
Initial errors in weather prediction grow in time. As errors become larger, their growth slows down and then stops at an asymptotic value. Time of reaching this value represents the limit of predictability. Other time limits that measure the error growth are doubling time τd, and times when the forecast error reaches 95%, 71%, 50%, and 25% of the limit of predictability. This paper studies asymptotic value and time limits in a low-dimensional atmospheric model for five initial errors, using ensemble prediction method as well as error approximation by quadratic and logarithmic hypothesis. We show that quadratic hypothesis approximates the model data better for almost all initial errors and time lengths. We also demonstrate that both hypotheses can be further improved to achieve even better match of the asymptotic value and time limits with the model. Initial errors in weather prediction grow in time. As errors become larger, their growth slows down and then stops at an asymptotic value. Time of reaching this value represents the limit of predictability. Other time limits that measure the error growth are doubling time τd, and times when the forecast error reaches 95%, 71%, 50%, and 25% of the limit of predictability. This paper studies asymptotic value and time limits in a low-dimensional atmospheric model for five initial errors, using ensemble prediction method as well as error approximation by quadratic and logarithmic hypothesis. We show that quadratic hypothesis approximates the model data better for almost all initial errors and time lengths. We also demonstrate that both hypotheses can be further improved to achieve even better match of the asymptotic value and time limits with the model.
dcterms:title
Estimations of Initial Errors Growth in Weather Prediction by Low-dimensional Atmospheric Model Estimations of Initial Errors Growth in Weather Prediction by Low-dimensional Atmospheric Model
skos:prefLabel
Estimations of Initial Errors Growth in Weather Prediction by Low-dimensional Atmospheric Model Estimations of Initial Errors Growth in Weather Prediction by Low-dimensional Atmospheric Model
skos:notation
RIV/00216208:11320/14:10292089!RIV15-MSM-11320___
n3:aktivita
n13:S
n3:aktivity
S
n3:cisloPeriodika
289
n3:dodaniDat
n4:2015
n3:domaciTvurceVysledku
n5:4972570 n5:6222536 n5:6598986
n3:druhVysledku
n15:J
n3:duvernostUdaju
n6:S
n3:entitaPredkladatele
n19:predkladatel
n3:idSjednocenehoVysledku
15090
n3:idVysledku
RIV/00216208:11320/14:10292089
n3:jazykVysledku
n17:eng
n3:klicovaSlova
Model; Atmospheric; Low-dimensional; Prediction; Weather; Growth; Errors; Initial; Estimations
n3:klicoveSlovo
n10:Estimations n10:Prediction n10:Growth n10:Initial n10:Model n10:Weather n10:Errors n10:Low-dimensional n10:Atmospheric
n3:kodStatuVydavatele
CH - Švýcarská konfederace
n3:kontrolniKodProRIV
[CC87F4087B2A]
n3:nazevZdroje
Advances in Intelligent Systems and Computing
n3:obor
n12:IN
n3:pocetDomacichTvurcuVysledku
3
n3:pocetTvurcuVysledku
3
n3:rokUplatneniVysledku
n4:2014
n3:svazekPeriodika
2014
n3:tvurceVysledku
Raidl, Aleš Mikšovský, Jiří Bednář, Hynek
s:issn
2194-5357
s:numberOfPages
10
n7:doi
10.1007/978-3-319-07401-6_2
n14:organizacniJednotka
11320