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pro vyhledávání: '"Hasegawa, Kiyoharu"'
Autor:
Hasegawa, Kiyoharu, Kanae, Shinjiro
Precipitation season forecasting is an important indicator for stabilizing water resources for all social activities, including economic, agricultural, and industrial activities. In recent years, in addition to forecasts based on general circulation
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=jairo_______::1af0a99bea3cf20414cde1bdac838b98
http://t2r2.star.titech.ac.jp/cgi-bin/publicationinfo.cgi?q_publication_content_number=CTT100895590
http://t2r2.star.titech.ac.jp/cgi-bin/publicationinfo.cgi?q_publication_content_number=CTT100895590
Autor:
Hasegawa, Kiyoharu, Kanae, Shinjiro
Thanks to their remarkable development, numerical models have shown high prediction accuracy in short-term rainfall forecasting. On the other hand, in regions where rainfall is closely related to complex meteorological phenomena such as monsoon inclu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=jairo_______::d9a50e1700f702f2a2981a8c7298e80a
http://t2r2.star.titech.ac.jp/cgi-bin/publicationinfo.cgi?q_publication_content_number=CTT100882421
http://t2r2.star.titech.ac.jp/cgi-bin/publicationinfo.cgi?q_publication_content_number=CTT100882421
Autor:
Hasegawa, Kiyoharu, Kanae, Shinjiro
Publikováno v:
土木学会論文集B1（水工学）. 77(Issue 2)
2週間以上の降雨予測は気候モデルの精度が急激に低くなることが知られており，深層学習モデルの適用が期待されている．本研究はタイ，チャオプラヤー川流域を対象に5~10月までの雨
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=jairo_______::723e9e0836c1d85f7d17fbb11b3ce98b
http://t2r2.star.titech.ac.jp/cgi-bin/publicationinfo.cgi?q_publication_content_number=CTT100880439
http://t2r2.star.titech.ac.jp/cgi-bin/publicationinfo.cgi?q_publication_content_number=CTT100880439
Autor:
Hasegawa, Kiyoharu, Kanae, Shinjiro
Subseasonal to seasonal (S2S) prediction still remains as a challenge task even today. S2S prediction refers to a lead time ranging from one to several months, which is known to result in rapidly decreasing forecast accuracy. Deep learning (DL), one
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=jairo_______::03e89543fee4b98427225f1d7cd072ba
http://t2r2.star.titech.ac.jp/cgi-bin/publicationinfo.cgi?q_publication_content_number=CTT100880471
http://t2r2.star.titech.ac.jp/cgi-bin/publicationinfo.cgi?q_publication_content_number=CTT100880471
Autor:
Hasegawa, Kiyoharu, Kanae, Shinjiro
Publikováno v:
土木学会論文集B1（水工学）. 75(2):1195-1200
本研究は，タイ王国における数か月先の降水量予測を試みた研究である．数か月先の降雨量は，大気・陸面・海洋での環境場が複雑な関係により左右されると考えられている．これらの
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=jairo_______::a4910996f7c76d53ae49dc443e62347b
http://t2r2.star.titech.ac.jp/cgi-bin/publicationinfo.cgi?q_publication_content_number=CTT100845486
http://t2r2.star.titech.ac.jp/cgi-bin/publicationinfo.cgi?q_publication_content_number=CTT100845486
Autor:
Hasegawa, Kiyoharu, Kanae, Shinjiro
Subseasonal to seasonal prediction(S2S予測)は未だ水文気象予測に残された難問の1つである． S2S予測とは1か月から数か月にわたるリードタイムを指し，予測精度が急激に低くなることが知られて
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=jairo_______::14f167a71b4528364921fa3c9260fbd1
http://t2r2.star.titech.ac.jp/cgi-bin/publicationinfo.cgi?q_publication_content_number=CTT100880472
http://t2r2.star.titech.ac.jp/cgi-bin/publicationinfo.cgi?q_publication_content_number=CTT100880472
Autor:
Hasegawa, Kiyoharu, Kanae, Shinjiro
This research focuses on the seasonal prediction of precipitation in Thailand. Thailand faces difficulty of dam operation because of its climate and geography characteristics. Here, seasonal prediction of precipitation is effective for accurate dam o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=jairo_______::56397c702ea6fef8d3cf5bee1add8b7a
http://t2r2.star.titech.ac.jp/cgi-bin/publicationinfo.cgi?q_publication_content_number=CTT100811178
http://t2r2.star.titech.ac.jp/cgi-bin/publicationinfo.cgi?q_publication_content_number=CTT100811178
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