{"created":"2023-07-25T11:11:05.168812+00:00","id":15464,"links":{},"metadata":{"_buckets":{"deposit":"84eebe4f-7c25-4030-8442-672432dead8a"},"_deposit":{"created_by":25,"id":"15464","owners":[25],"pid":{"revision_id":0,"type":"depid","value":"15464"},"status":"published"},"_oai":{"id":"oai:nipr.repo.nii.ac.jp:00015464","sets":["1259:1267:1927"]},"author_link":["67444","67445","67443"],"item_10001_biblio_info_7":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2018-12","bibliographicIssueDateType":"Issued"},"bibliographicPageEnd":"93","bibliographicPageStart":"83","bibliographicVolumeNumber":"18","bibliographic_titles":[{},{"bibliographic_title":"Polar Science","bibliographic_titleLang":"en"}]}]},"item_10001_description_5":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"The importance of ice shelf in realistic simulation of the ocean sea ice variability is demonstrated in the Southern Ocean region [9 E - 78 E; 58 S - 71 S] covering the Indian Antarctic Stations Maitri [11.7 E; 70.7 S] and Bharati [76.1 E; 69.4 S] during 2002–2012. A coupled ocean sea-ice modeling with ice shelf is carried out for this purpose. It is shown that the inclusion of shelf ice in the coupled model setup leads to better simulation of the sea surface temperature (SST), sea surface salinity (SSS), and sea ice concentration (SIC) of the region. The effect of ice shelf on the sub-surface temperature and salinity is also examined. The model derived surface currents are used to compute the Finite Time Lyapunov Exponent (FTLE) as a measure of spatio-temporal local predictability in the domain of study. The regions of high and low predictability and their seasonal evolution are clearly demonstrated using the FTLE. The chaotic time series analysis of sea ice volume (SIV) around the Maitri and Bharati stations is performed to examine the predictability of SIV. The largest Lyapunov exponent and Correlation dimension are used as the measures of predictability for this purpose. It is found that there exists a low-dimensional chaotic attractor around the Maitri and Bharati with the correlation dimension of 2.95 and 1.9, respectively. The FTLE as well as the largest Lyapunov exponent analysis suggests that the Maitri region is less predictable as compared to the Bharati region. The analysis reveals that the limit of predictability of the SIV around the Maitri and Bharati regions is 22 days and 25 days, respectively.","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.2018.04.003"}],"subitem_relation_type_id":{"subitem_relation_type_id_text":"https://doi.org/10.1016/j.polar.2018.04.003","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":"Kumar, Anurag","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Dwivedi, Suneet","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Pandey, Avinash C.","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"Predictability","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"Indian Antarctic stations","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"Ocean sea ice modeling","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"Shelf ice","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":"Quantifying predictability of sea ice around the Indian Antarctic stations using coupled ocean sea ice model with shelf ice","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Quantifying predictability of sea ice around the Indian Antarctic stations using coupled ocean sea ice model with shelf ice"},{"subitem_title":"Quantifying predictability of sea ice around the Indian Antarctic stations using coupled ocean sea ice model with shelf ice","subitem_title_language":"en"}]},"item_type_id":"10001","owner":"25","path":["1927"],"pubdate":{"attribute_name":"公開日","attribute_value":"2019-04-03"},"publish_date":"2019-04-03","publish_status":"0","recid":"15464","relation_version_is_last":true,"title":["Quantifying predictability of sea ice around the Indian Antarctic stations using coupled ocean sea ice model with shelf ice"],"weko_creator_id":"25","weko_shared_id":-1},"updated":"2023-07-25T13:39:42.040907+00:00"}