WEKO3
アイテム
{"_buckets": {"deposit": "94d00999-8c7d-451b-9606-8247108cae28"}, "_deposit": {"created_by": 26, "id": "16900", "owners": [26], "pid": {"revision_id": 0, "type": "depid", "value": "16900"}, "status": "published"}, "_oai": {"id": "oai:nipr.repo.nii.ac.jp:00016900", "sets": ["2087"]}, "author_link": ["74100", "74099", "74101", "74098"], "item_10001_biblio_info_7": {"attribute_name": "書誌情報", "attribute_value_mlt": [{"bibliographicIssueDates": {"bibliographicIssueDate": "2022-03", "bibliographicIssueDateType": "Issued"}, "bibliographicPageStart": "100743", "bibliographicVolumeNumber": "31", "bibliographic_titles": [{}, {"bibliographic_title": "Polar Science", "bibliographic_titleLang": "en"}]}]}, "item_10001_description_5": {"attribute_name": "抄録", "attribute_value_mlt": [{"subitem_description": "Sea-ice extent (SIE) satellite data has been stored and studied over the past four decades. Antarctica’s SIE has recently attained both its maximum (2014) and its minimum (2017) values, which raised questions regarding how SIE variability is evolving. Here we discuss a new approach to improve our understanding of SIE variability for the 1982–1993 and 2006–2017 periods. Using a probability density function and examining the mean and standard deviation of SIE distributions as a function of seasonality. Results show that the whole Southern Ocean presented both mean and standard deviation growth in all seasons. The largest SIE distribution difference for Southern Ocean between 1982–1993 and 2006–2017 periods was observed in July, August and September (JAS), during which all individual Sea sectors presented growth of the SIE mean. Not only different Sea sectors showed different variations, but the SIE data distributions from the same Sea sector yielded different changes with differing seasons. January, February and March (JFM) together with April, May and June were the seasons with the largest SIE decadal variability for Weddell, Indian, Amundsen and West Pacific Sea Sectors, while the Ross Sea showed greater SIE variability during JAS and October November, December. This methodology showed consistent results with the traditional SIE trend calculation and introduced a new quantification index for evaluating the differences between two distributions not necessarily connected in time.", "subitem_description_type": "Abstract"}]}, "item_10001_relation_14": {"attribute_name": "DOI", "attribute_value_mlt": [{"subitem_relation_name": [{"subitem_relation_name_text": "10.1016/j.polar.2021.100743"}], "subitem_relation_type_id": {"subitem_relation_type_id_text": "https://doi.org/10.1016/j.polar.2021.100743", "subitem_relation_type_select": "DOI"}}]}, "item_10001_source_id_9": {"attribute_name": "ISSN", "attribute_value_mlt": [{"subitem_source_identifier": "18739652", "subitem_source_identifier_type": "ISSN"}]}, "item_access_right": {"attribute_name": "アクセス権", "attribute_value_mlt": [{"subitem_access_right": "metadata only access", "subitem_access_right_uri": "http://purl.org/coar/access_right/c_14cb"}]}, "item_creator": {"attribute_name": "著者", "attribute_type": "creator", "attribute_value_mlt": [{"creatorNames": [{"creatorName": "Gorenstein, Iuri", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "74098", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "Wainer, Ilana", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "74099", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "Mata, Mauricio M.", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "74100", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "Tonelli, Marcos", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "74101", "nameIdentifierScheme": "WEKO"}]}]}, "item_keyword": {"attribute_name": "キーワード", "attribute_value_mlt": [{"subitem_subject": "Antarctic sea ice extent", "subitem_subject_language": "en", "subitem_subject_scheme": "Other"}, {"subitem_subject": "Probability density function", "subitem_subject_language": "en", "subitem_subject_scheme": "Other"}, {"subitem_subject": "SIE variability", "subitem_subject_language": "en", "subitem_subject_scheme": "Other"}]}, "item_language": {"attribute_name": "言語", "attribute_value_mlt": [{"subitem_language": "eng"}]}, "item_resource_type": {"attribute_name": "資源タイプ", "attribute_value_mlt": [{"resourcetype": "journal article", "resourceuri": "http://purl.org/coar/resource_type/c_6501"}]}, "item_title": "Revisiting Antarctic sea-ice decadal variability since 1980", "item_titles": {"attribute_name": "タイトル", "attribute_value_mlt": [{"subitem_title": "Revisiting Antarctic sea-ice decadal variability since 1980"}, {"subitem_title": "Revisiting Antarctic sea-ice decadal variability since 1980", "subitem_title_language": "en"}]}, "item_type_id": "10001", "owner": "26", "path": ["2087"], "permalink_uri": "https://nipr.repo.nii.ac.jp/records/16900", "pubdate": {"attribute_name": "公開日", "attribute_value": "2022-05-26"}, "publish_date": "2022-05-26", "publish_status": "0", "recid": "16900", "relation": {}, "relation_version_is_last": true, "title": ["Revisiting Antarctic sea-ice decadal variability since 1980"], "weko_shared_id": -1}
Revisiting Antarctic sea-ice decadal variability since 1980
https://nipr.repo.nii.ac.jp/records/16900
https://nipr.repo.nii.ac.jp/records/1690040951048-aa6f-4834-a37e-5824157496c9
Item type | 学術雑誌論文 / Journal Article(1) | |||||
---|---|---|---|---|---|---|
公開日 | 2022-05-26 | |||||
タイトル | ||||||
タイトル | Revisiting Antarctic sea-ice decadal variability since 1980 | |||||
タイトル | ||||||
言語 | en | |||||
タイトル | Revisiting Antarctic sea-ice decadal variability since 1980 | |||||
言語 | ||||||
言語 | eng | |||||
キーワード | ||||||
言語 | en | |||||
主題Scheme | Other | |||||
主題 | Antarctic sea ice extent | |||||
キーワード | ||||||
言語 | en | |||||
主題Scheme | Other | |||||
主題 | Probability density function | |||||
キーワード | ||||||
言語 | en | |||||
主題Scheme | Other | |||||
主題 | SIE variability | |||||
資源タイプ | ||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
資源タイプ | journal article | |||||
アクセス権 | ||||||
アクセス権 | metadata only access | |||||
アクセス権URI | http://purl.org/coar/access_right/c_14cb | |||||
著者 |
Gorenstein, Iuri
× Gorenstein, Iuri× Wainer, Ilana× Mata, Mauricio M.× Tonelli, Marcos |
|||||
抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | Sea-ice extent (SIE) satellite data has been stored and studied over the past four decades. Antarctica’s SIE has recently attained both its maximum (2014) and its minimum (2017) values, which raised questions regarding how SIE variability is evolving. Here we discuss a new approach to improve our understanding of SIE variability for the 1982–1993 and 2006–2017 periods. Using a probability density function and examining the mean and standard deviation of SIE distributions as a function of seasonality. Results show that the whole Southern Ocean presented both mean and standard deviation growth in all seasons. The largest SIE distribution difference for Southern Ocean between 1982–1993 and 2006–2017 periods was observed in July, August and September (JAS), during which all individual Sea sectors presented growth of the SIE mean. Not only different Sea sectors showed different variations, but the SIE data distributions from the same Sea sector yielded different changes with differing seasons. January, February and March (JFM) together with April, May and June were the seasons with the largest SIE decadal variability for Weddell, Indian, Amundsen and West Pacific Sea Sectors, while the Ross Sea showed greater SIE variability during JAS and October November, December. This methodology showed consistent results with the traditional SIE trend calculation and introduced a new quantification index for evaluating the differences between two distributions not necessarily connected in time. | |||||
書誌情報 |
en : Polar Science 巻 31, p. 100743, 発行日 2022-03 |
|||||
ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 18739652 | |||||
DOI | ||||||
識別子タイプ | DOI | |||||
関連識別子 | https://doi.org/10.1016/j.polar.2021.100743 | |||||
関連名称 | 10.1016/j.polar.2021.100743 |