Lorenz's 05 low-dimensional chaotic model validity in simulating weather predictability
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F18%3A10390957" target="_blank" >RIV/00216208:11320/18:10390957 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
čeština
Original language name
VALIDACE LORENZOVA 05 NÍZKO-DIMENZIONÁLNÍHO CHAOTICKÉHO MODELU PRO SIMULACI PREDIKTABILITY POČASÍ
Original language description
Predictability curves show average growth rate of initial and model error of meteorological quantities predicted by numerical weather models. A curve displays limits of predictability and average error of prediction for a chosen day. The curves are calculated to show effects to predictability of different parameterizations, different resolutions, numbers of ensemble members, initial conditions etc. Low-dimensional atmospheric models are used to carry out predictability studies that would be too expensive to perform using numerical weather prediction models. This article tests the ability of the Lorenz's (2005) chaotic model to simulate predictability curve of the ECMWF model by quadratic hypothesis. Similar predictability curves are found for the Lorenz's model with N = 120 variables and the ECMWF model from 1990s, for the Lorenz's model with numbers of variables between N = 120 and N = 240 and the ECMWF model from around 2000 and for the Lorenz's model with N = 240 variables and the ECMWF model from around 2010. Usability and challenges of quadratic hypothesis are also discussed.
Czech name
VALIDACE LORENZOVA 05 NÍZKO-DIMENZIONÁLNÍHO CHAOTICKÉHO MODELU PRO SIMULACI PREDIKTABILITY POČASÍ
Czech description
Predictability curves show average growth rate of initial and model error of meteorological quantities predicted by numerical weather models. A curve displays limits of predictability and average error of prediction for a chosen day. The curves are calculated to show effects to predictability of different parameterizations, different resolutions, numbers of ensemble members, initial conditions etc. Low-dimensional atmospheric models are used to carry out predictability studies that would be too expensive to perform using numerical weather prediction models. This article tests the ability of the Lorenz's (2005) chaotic model to simulate predictability curve of the ECMWF model by quadratic hypothesis. Similar predictability curves are found for the Lorenz's model with N = 120 variables and the ECMWF model from 1990s, for the Lorenz's model with numbers of variables between N = 120 and N = 240 and the ECMWF model from around 2000 and for the Lorenz's model with N = 240 variables and the ECMWF model from around 2010. Usability and challenges of quadratic hypothesis are also discussed.
Classification
Type
J<sub>ost</sub> - Miscellaneous article in a specialist periodical
CEP classification
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OECD FORD branch
10509 - Meteorology and atmospheric sciences
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Meteorologické zprávy (Meteorological Bulletin.)
ISSN
0026-1173
e-ISSN
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Volume of the periodical
71
Issue of the periodical within the volume
5
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
6
Pages from-to
138-143
UT code for WoS article
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EID of the result in the Scopus database
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