VALIDACE LORENZOVA 05 NÍZKO-DIMENZIONÁLNÍHO CHAOTICKÉHO MODELU PRO SIMULACI PREDIKTABILITY POČASÍ

Kód výsledku v 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>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

čeština

Název v původním jazyce

VALIDACE LORENZOVA 05 NÍZKO-DIMENZIONÁLNÍHO CHAOTICKÉHO MODELU PRO SIMULACI PREDIKTABILITY POČASÍ

Popis výsledku v původním jazyce

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&apos;s (2005) chaotic model to simulate predictability curve of the ECMWF model by quadratic hypothesis. Similar predictability curves are found for the Lorenz&apos;s model with N = 120 variables and the ECMWF model from 1990s, for the Lorenz&apos;s model with numbers of variables between N = 120 and N = 240 and the ECMWF model from around 2000 and for the Lorenz&apos;s model with N = 240 variables and the ECMWF model from around 2010. Usability and challenges of quadratic hypothesis are also discussed.

Název v anglickém jazyce

Lorenz's 05 low-dimensional chaotic model validity in simulating weather predictability

Popis výsledku anglicky

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&apos;s (2005) chaotic model to simulate predictability curve of the ECMWF model by quadratic hypothesis. Similar predictability curves are found for the Lorenz&apos;s model with N = 120 variables and the ECMWF model from 1990s, for the Lorenz&apos;s model with numbers of variables between N = 120 and N = 240 and the ECMWF model from around 2000 and for the Lorenz&apos;s model with N = 240 variables and the ECMWF model from around 2010. Usability and challenges of quadratic hypothesis are also discussed.

Druh

J_ost - Ostatní články v recenzovaných periodicích

CEP obor

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OECD FORD obor

10509 - Meteorology and atmospheric sciences

Projekt

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Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Meteorologické zprávy (Meteorological Bulletin.)

ISSN

0026-1173

e-ISSN

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Svazek periodika

71

Číslo periodika v rámci svazku

5

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

6

Strana od-do

138-143

Kód UT WoS článku

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EID výsledku v databázi Scopus

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