{"created":"2022-01-28T07:17:40.146109+00:00","id":2008810,"links":{},"metadata":{"_buckets":{"deposit":"f00828f9-9c5b-4252-b9b5-a52874cf3480"},"_deposit":{"id":"2008810","owners":[1],"pid":{"revision_id":0,"type":"depid","value":"2008810"},"status":"published"},"_oai":{"id":"oai:u-ryukyu.repo.nii.ac.jp:02008810","sets":["1642838163960:1642838338003","1642838403551:1642838406414"]},"author_link":[],"item_1617186331708":{"attribute_name":"Title","attribute_value_mlt":[{"subitem_1551255647225":"Mesoscale Hybrid Data Assimilation System based on JMA Nonhydrostatic Model","subitem_1551255648112":"en"}]},"item_1617186419668":{"attribute_name":"Creator","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Ito, Kosuke","creatorNameLang":"en"}]},{"creatorNames":[{"creatorName":"Kunii, Masaru","creatorNameLang":"en"}]},{"creatorNames":[{"creatorName":"Kawabata, Takuya","creatorNameLang":"en"}]},{"creatorNames":[{"creatorName":"Saito, Kazuo","creatorNameLang":"en"}]},{"creatorNames":[{"creatorName":"Aonashi, Kazumasa","creatorNameLang":"en"}]},{"creatorNames":[{"creatorName":"Le, Duc","creatorNameLang":"en"}]}]},"item_1617186476635":{"attribute_name":"Access Rights","attribute_value_mlt":[{"subitem_1522299639480":"open access","subitem_1600958577026":"http://purl.org/coar/access_right/c_abf2"}]},"item_1617186499011":{"attribute_name":"Rights","attribute_value_mlt":[{"subitem_1522650717957":"ja","subitem_1522651041219":"© 2016 American Meteorological Society"}]},"item_1617186609386":{"attribute_name":"Subject","attribute_value_mlt":[{"subitem_1522299896455":"en","subitem_1522300014469":"Other","subitem_1523261968819":"Circulation/ Dynamics"},{"subitem_1522299896455":"en","subitem_1522300014469":"Other","subitem_1523261968819":"Convective clouds"},{"subitem_1522299896455":"en","subitem_1522300014469":"Other","subitem_1523261968819":"Atm/Ocean Structure/ Phenomena"},{"subitem_1522299896455":"en","subitem_1522300014469":"Other","subitem_1523261968819":"Tropical cyclones"},{"subitem_1522299896455":"en","subitem_1522300014469":"Other","subitem_1523261968819":"Forecasting"},{"subitem_1522299896455":"en","subitem_1522300014469":"Other","subitem_1523261968819":"Numerical weather prediction/forecasting"},{"subitem_1522299896455":"en","subitem_1522300014469":"Other","subitem_1523261968819":"Models and modeling"},{"subitem_1522299896455":"en","subitem_1522300014469":"Other","subitem_1523261968819":"Data assimilation"}]},"item_1617186626617":{"attribute_name":"Description","attribute_value_mlt":[{"subitem_description":"This paper discusses the benefits of using a hybrid ensemble Kalman filter and four-dimensional variational (4D-Var) data assimilation (DA) system rather than a 4D-Var system employing the National Meteorological Center (NMC, now known as NCEP) method (4D-Var-Bnmc) to predict severe weather events. An adjointbased 4D-Var system was employed with a background error covariance matrix B constructed from theNMC method and perturbations in a local ensemble transform Kalman filter system. The DA systems are based on the Japan Meteorological Agency’s nonhydrostatic model. To reduce the sampling noise, three types of implementation (the spatial localization, spectral localization, and neighboring ensemble approaches) were tested. The assimilation of a pseudosingle observation of sea level pressure located at a tropical cyclone (TC) center yielded analysis increments physically consistent with what is expected of a mature TC in the hybrid systems at the beginning of the assimilation window, whereas analogous experiments performed using the 4D-Var-Bnmc system did not. At the end, the structures of the 4D-Var-based increments became similar to one another, while the analysis increment by the 4D-Var-Bnmc system was broad in the horizontal direction. Realistic DA experiments showed that all of the hybrid systems provided initial conditions that yielded more accurate TC track and intensity forecasts than those achievable by the 4D-Var-Bnmc system. The hybrid systems also yielded some statistically significant improvements in forecasting local heavy rainfall events in terms of fraction skill scores when a 160 km 3 160 km window size was used. The overall skills of the hybrid systems were relatively independent of the choice of implementation.","subitem_description_type":"Other"},{"subitem_description":"論文","subitem_description_type":"Other"}]},"item_1617186643794":{"attribute_name":"Publisher","attribute_value_mlt":[{"subitem_1522300295150":"en","subitem_1522300316516":"American Meteorological Society"}]},"item_1617186702042":{"attribute_name":"Language","attribute_value_mlt":[{"subitem_1551255818386":"eng"}]},"item_1617186783814":{"attribute_name":"Identifier","attribute_value_mlt":[{"subitem_identifier_type":"HDL","subitem_identifier_uri":"http://hdl.handle.net/20.500.12000/37528"}]},"item_1617186941041":{"attribute_name":"Source Title","attribute_value_mlt":[{"subitem_1522650068558":"en","subitem_1522650091861":"MONTHLY WEATHER REVIEW"}]},"item_1617187056579":{"attribute_name":"Bibliographic Information","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2016-08-26","bibliographicIssueDateType":"Issued"},"bibliographicPageEnd":"3439","bibliographicPageStart":"3417","bibliographicVolumeNumber":"144"}]},"item_1617258105262":{"attribute_name":"Resource Type","attribute_value_mlt":[{"resourcetype":"journal article","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_1617265215918":{"attribute_name":"Version Type","attribute_value_mlt":[{"subitem_1522305645492":"VoR","subitem_1600292170262":"http://purl.org/coar/version/c_970fb48d4fbd8a85"}]},"item_1617353299429":{"attribute_name":"Relation","attribute_value_mlt":[{"subitem_1522306287251":{"subitem_1522306382014":"DOI","subitem_1522306436033":"https://doi.org/10.1175/MWR-D-16-0014.1"}},{"subitem_1522306287251":{"subitem_1522306382014":"DOI","subitem_1522306436033":"info:doi/10.1175/MWR-D-16-0014.1"}}]},"item_1617605131499":{"attribute_name":"File","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_access","filename":"MONTHLY_WEATHER_REVIEW_Vol144p3417.pdf","mimetype":"application/pdf","url":{"objectType":"fulltext","url":"https://u-ryukyu.repo.nii.ac.jp/record/2008810/files/MONTHLY_WEATHER_REVIEW_Vol144p3417.pdf"},"version_id":"04f06c8b-b632-4b38-a995-50b4827999f2"}]},"item_title":"Mesoscale Hybrid Data Assimilation System based on JMA Nonhydrostatic Model","item_type_id":"15","owner":"1","path":["1642838338003","1642838406414"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2018-01-12"},"publish_date":"2018-01-12","publish_status":"0","recid":"2008810","relation_version_is_last":true,"title":["Mesoscale Hybrid Data Assimilation System based on JMA Nonhydrostatic Model"],"weko_creator_id":"1","weko_shared_id":-1},"updated":"2023-08-03T05:39:43.907767+00:00"}