Estimate of atmospheric predictability and development of prediction model using ensemble forecast assimilation in nonlinear dynamical system

application/pdf In this study, a limit of predictability for the atmosphere is estimated based on analog weather maps in the historical data, and a new type of ensemble forecast assimilation technique is developed in order to improve the forecast skill in the nonlinear dynamical system. The limit of...

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Main Authors: 野原, 大輔, 34814, Nohara, Daisuke, 34812
Language:Japanese
Published: 2004
Subjects:
Online Access:http://hdl.handle.net/2241/6842
https://tsukuba.repo.nii.ac.jp/record/8370/files/B2021.pdf
https://tsukuba.repo.nii.ac.jp/record/8370/files/1.pdf
id fttsukubauniv:oai:tsukuba.repo.nii.ac.jp:00008370
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spelling fttsukubauniv:oai:tsukuba.repo.nii.ac.jp:00008370 2023-05-15T17:35:15+02:00 Estimate of atmospheric predictability and development of prediction model using ensemble forecast assimilation in nonlinear dynamical system 野原, 大輔 34814 Nohara, Daisuke 34812 2004 application/pdf http://hdl.handle.net/2241/6842 https://tsukuba.repo.nii.ac.jp/record/8370/files/B2021.pdf https://tsukuba.repo.nii.ac.jp/record/8370/files/1.pdf jpn jpn http://hdl.handle.net/2241/6842 https://tsukuba.repo.nii.ac.jp/record/8370/files/B2021.pdf https://tsukuba.repo.nii.ac.jp/record/8370/files/1.pdf 2004 fttsukubauniv 2022-09-17T00:47:09Z application/pdf In this study, a limit of predictability for the atmosphere is estimated based on analog weather maps in the historical data, and a new type of ensemble forecast assimilation technique is developed in order to improve the forecast skill in the nonlinear dynamical system. The limit of the predictability (denoted as P) is defined as the time taken for the initial difference (E0) of the analog pair to reach the climate noise level which is defined by one standard deviation from the long term mean of the fluctuation in the observed atmosphere. Although a total of 185,547,600 pairs of the weather maps are searched, there are no good analog pairs to investigate the difference growth rate for a sufficiently small E0 of the analog pairs. For this reason, the behavior of E0 is explained by a quadratic error growth model. Regressing the quadratic error growth model to the scattergram between P and E0, it is estimated that P would extend 2.88 days when E0 is reduced to 1[?]e for sufficiently small E0. The limit of predictability P varies depending on variable by the atmospheric boundary condition such as El Ni~no, La Ni~na, Pacific/North American (PNA), and North Atlantic Oscillation (NAO). In the case of PNA+ and NAO-, the differences of the analog pairs grow slower than the average showing the e-folding time of 3.17 and 3.07 days, respectively. Conversely, in the case of La Ni~na and PNA-, the differences grow faster than the average showing the e-folding time of 2.72 and 2.69 days, respectively. These results are also verified by hindcast datasets. ・・・ Thesis (Ph. D. in Science)--University of Tsukuba, (B), no. 2021, 2004.3.25 Includes bibliographical references thesis Other/Unknown Material North Atlantic North Atlantic oscillation University of Tsukuba Repository (Tulips-R) Pacific
institution Open Polar
collection University of Tsukuba Repository (Tulips-R)
op_collection_id fttsukubauniv
language Japanese
description application/pdf In this study, a limit of predictability for the atmosphere is estimated based on analog weather maps in the historical data, and a new type of ensemble forecast assimilation technique is developed in order to improve the forecast skill in the nonlinear dynamical system. The limit of the predictability (denoted as P) is defined as the time taken for the initial difference (E0) of the analog pair to reach the climate noise level which is defined by one standard deviation from the long term mean of the fluctuation in the observed atmosphere. Although a total of 185,547,600 pairs of the weather maps are searched, there are no good analog pairs to investigate the difference growth rate for a sufficiently small E0 of the analog pairs. For this reason, the behavior of E0 is explained by a quadratic error growth model. Regressing the quadratic error growth model to the scattergram between P and E0, it is estimated that P would extend 2.88 days when E0 is reduced to 1[?]e for sufficiently small E0. The limit of predictability P varies depending on variable by the atmospheric boundary condition such as El Ni~no, La Ni~na, Pacific/North American (PNA), and North Atlantic Oscillation (NAO). In the case of PNA+ and NAO-, the differences of the analog pairs grow slower than the average showing the e-folding time of 3.17 and 3.07 days, respectively. Conversely, in the case of La Ni~na and PNA-, the differences grow faster than the average showing the e-folding time of 2.72 and 2.69 days, respectively. These results are also verified by hindcast datasets. ・・・ Thesis (Ph. D. in Science)--University of Tsukuba, (B), no. 2021, 2004.3.25 Includes bibliographical references thesis
author 野原, 大輔
34814
Nohara, Daisuke
34812
spellingShingle 野原, 大輔
34814
Nohara, Daisuke
34812
Estimate of atmospheric predictability and development of prediction model using ensemble forecast assimilation in nonlinear dynamical system
author_facet 野原, 大輔
34814
Nohara, Daisuke
34812
author_sort 野原, 大輔
title Estimate of atmospheric predictability and development of prediction model using ensemble forecast assimilation in nonlinear dynamical system
title_short Estimate of atmospheric predictability and development of prediction model using ensemble forecast assimilation in nonlinear dynamical system
title_full Estimate of atmospheric predictability and development of prediction model using ensemble forecast assimilation in nonlinear dynamical system
title_fullStr Estimate of atmospheric predictability and development of prediction model using ensemble forecast assimilation in nonlinear dynamical system
title_full_unstemmed Estimate of atmospheric predictability and development of prediction model using ensemble forecast assimilation in nonlinear dynamical system
title_sort estimate of atmospheric predictability and development of prediction model using ensemble forecast assimilation in nonlinear dynamical system
publishDate 2004
url http://hdl.handle.net/2241/6842
https://tsukuba.repo.nii.ac.jp/record/8370/files/B2021.pdf
https://tsukuba.repo.nii.ac.jp/record/8370/files/1.pdf
geographic Pacific
geographic_facet Pacific
genre North Atlantic
North Atlantic oscillation
genre_facet North Atlantic
North Atlantic oscillation
op_relation http://hdl.handle.net/2241/6842
https://tsukuba.repo.nii.ac.jp/record/8370/files/B2021.pdf
https://tsukuba.repo.nii.ac.jp/record/8370/files/1.pdf
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