Data assimilation experiment of precipitable water vapor observed by a hyper-dense GNSS receiver network using a nested NHM-LETKF system

• 資料種別: 記事
• タイトル: Data assimilation experiment of precipitable water vapor observed by a hyper-dense GNSS receiver network using a nested NHM-LETKF system
• 著者・編者: Masanori Oigawa; Toshitaka Tsuda; Hiromu Seko
• 出版事項: 日本 : Springer Nature
• 出版年月日等: 2018-05-04
• 出版年（W3CDTF）: 2018-05-04
• タイトル（掲載誌）: EPS : Earth, Planets and Space
• 巻号年月日等（掲載誌）: 70(74)
• 掲載巻: 70(74)
• ISSN（掲載誌）: 1880-5981
• ISSN-L（掲載誌）: 1343-8832
• 本文の言語コード: eng
• DOI: 10.1186/s40623-018-0851-3; https://doi.org/10.1186/s40623-018-0851-3
• 国立国会図書館永続的識別子: info:ndljp/pid/11125842; https://dl.ndl.go.jp/pid/11125842
• コレクション（共通）: 障害者向け資料
• コレクション（障害者向け資料：レベル1）: テキストデータ
• コレクション（個別）: 国立国会図書館デジタルコレクション > 電子書籍・電子雑誌 > その他; https://dl.ndl.go.jp/collections/B00035
• 収集根拠: オンライン資料収集制度
• 受理日（W3CDTF）: 2018-08-10T20:26:03+09:00
• 保存日（W3CDTF）: 2018-08-10
• 記録形式（IMT）: application/pdf
• オンライン閲覧公開範囲: 国立国会図書館内限定公開
• デジタル化資料送信: 図書館・個人送信対象外
• 遠隔複写可否（NDL）: 可
• 掲載誌（URI）: https://earth-planets-space.springeropen.com/articles
• 掲載誌（国立国会図書館永続的識別子）: info:ndljp/pid/11067456; https://dl.ndl.go.jp/pid/11067456
• 連携機関・データベース: 国立国会図書館 : 国立国会図書館デジタルコレクション; https://dl.ndl.go.jp

• 要約等: We studied the assimilation of high-resolution precipitable water vapor (PWV) data derived from a hyper-dense global navigation satellite system network around Uji city, Kyoto, Japan, which had a mean inter-station distance of about 1.7 km. We focused on a heavy rainfall event that occurred on August 13–14, 2012, around Uji city. We employed a local ensemble transform Kalman filter as the data assimilation method. The inhomogeneity of the observed PWV increased on a scale of less than 10 km in advance of the actual rainfall detected by the rain gauge. Zenith wet delay data observed by the Uji network showed that the characteristic length scale of water vapor distribution during the rainfall ranged from 1.9 to 3.5 km. It is suggested that the assimilation of PWV data with high horizontal resolution (a few km) improves the forecast accuracy. We conducted the assimilation experiment of high-resolution PWV data, using both small horizontal localization radii and a conventional horizontal localization radius. We repeated the sensitivity experiment, changing the mean horizontal spacing of the PWV data from 1.7 to 8.0 km. When the horizontal spacing of assimilated PWV data was decreased from 8.0 to 3.5 km, the accuracy of the simulated hourly rainfall amount worsened in the experiment that used the conventional localization radius for the assimilation of PWV. In contrast, the accuracy of hourly rainfall amounts improved when we applied small horizontal localization radii. In the experiment that used the small horizontal localization radii, the accuracy of the hourly rainfall amount was most improved when the horizontal resolution of the assimilated PWV data was 3.5 km. The optimum spatial resolution of PWV data was related to the characteristic length scale of water vapor variability.
• DOI: 10.1186/s40623-018-0851-3; https://doi.org/10.1186/s40623-018-0851-3
• オンライン閲覧公開範囲: インターネット公開
• 著作権情報: © The Author(s) 2018. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
• 関連情報（URI）: http://hdl.handle.net/2433/234641; http://id.ndl.go.jp/digimeta/11125842; https://dl.ndl.go.jp/pid/11125842; http://link.springer.com/content/pdf/10.1186/s40623-018-0851-3.pdf; http://link.springer.com/article/10.1186/s40623-018-0851-3/fulltext.html
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• 連携機関・データベース: 国立情報学研究所 : CiNii Research; https://cir.nii.ac.jp/
• 提供元機関・データベース: 学術機関リポジトリデータベース; https://irdb.nii.ac.jp; 雑誌記事索引データベース; https://ndlsearch.ndl.go.jp; Crossref; https://www.crossref.org; CiNii Articles; 科学研究費助成事業データベース; https://kaken.nii.ac.jp/ja
• 書誌ID（NDLBibID）: 11125842; http://id.ndl.go.jp/bib/11125842
• NII論文ID: 120006528345