{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T23:23:57Z","timestamp":1742945037718,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":18,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819964918"},{"type":"electronic","value":"9789819964925"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023]]},"DOI":"10.1007\/978-981-99-6492-5_47","type":"book-chapter","created":{"date-parts":[[2023,10,15]],"date-time":"2023-10-15T18:01:56Z","timestamp":1697392916000},"page":"549-563","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Study on Quantitative Precipitation Estimation and Model\u2019s Transfer Performance by Incorporating Dual Polarization Radar Variables"],"prefix":"10.1007","author":[{"given":"Yanqin","family":"Wen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jun","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhe","family":"Liang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Di","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ping","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,10,16]]},"reference":[{"issue":"3","key":"47_CR1","first-page":"202","volume":"32","author":"X Yu","year":"2013","unstructured":"Yu, X.: Nowcasting thinking and method of flash heavy rain. Torrential Rain Disaster 32(3), 202\u2013209 (2013)","journal-title":"Torrential Rain Disaster"},{"issue":"9","key":"47_CR2","doi-asserted-by":"publisher","first-page":"1048","DOI":"10.1175\/1520-0477(1979)060<1048:RMORS>2.0.CO;2","volume":"60","author":"JW Wilson","year":"1979","unstructured":"Wilson, J.W., Brandes, E.A.: Radar measurement of rainfall-a summary. Bull. Am. Meteor. Soc. 60(9), 1048\u20131060 (1979)","journal-title":"Bull. Am. Meteor. Soc."},{"key":"47_CR3","first-page":"497","volume":"77","author":"L Song","year":"2019","unstructured":"Song, L., Chen, M., Cheng, C., et al.: Characteristics of summer QPE error and a climatological correction method over Beijing-Tianjin-Hebei region. Acta Meteorol. Sin. 77, 497\u2013515 (2019)","journal-title":"Acta Meteorol. Sin."},{"issue":"11","key":"47_CR4","doi-asserted-by":"publisher","first-page":"1601","DOI":"10.1109\/LGRS.2016.2597170","volume":"13","author":"Q Kuang","year":"2016","unstructured":"Kuang, Q., Yang, X., Zhang, W., et al.: Spatiotemporal modeling and implementation for radar-based rainfall estimation. IEEE Geosci. Remote Sens. Lett. 13(11), 1601\u20131605 (2016)","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"issue":"2","key":"47_CR5","doi-asserted-by":"publisher","first-page":"413","DOI":"10.1007\/s13351-020-9036-7","volume":"34","author":"C Zhang","year":"2020","unstructured":"Zhang, C., Wang, H., Zeng, J., et al.: Short-Term dynamic radar quantitative precipitation estimation based on wavelet transform and support vector machine. J. Meteorol. Res. 34(2), 413\u2013426 (2020)","journal-title":"J. Meteorol. Res."},{"issue":"1","key":"47_CR6","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1175\/1520-0450(1976)015<0069:PUORDR>2.0.CO;2","volume":"15","author":"TA Seliga","year":"1976","unstructured":"Seliga, T.A., Bringi, V.N.: Potential use of radar differential reflectivity measurements at orthogonal polarizations for measuring precipitation. J. Appl. Meteorol. 15(1), 69\u201376 (1976)","journal-title":"J. Appl. Meteorol."},{"issue":"11","key":"47_CR7","doi-asserted-by":"publisher","first-page":"1950","DOI":"10.1175\/JAMC-D-11-081.1","volume":"51","author":"E Ruzanski","year":"2012","unstructured":"Ruzanski, E., Chandrasekar, V.: Nowcasting rainfall fields derived from specific differential phase. J. Appl. Meteorol. Climatol. 51(11), 1950\u20131959 (2012)","journal-title":"J. Appl. Meteorol. Climatol."},{"issue":"6","key":"47_CR8","doi-asserted-by":"publisher","first-page":"809","DOI":"10.1175\/BAMS-86-6-809","volume":"86","author":"AV Ryzhkov","year":"2005","unstructured":"Ryzhkov, A.V., Schuur, T.J., Burgess, D.W., et al.: The joint polarization experiment: polarimetric rainfall measurements and hydrometeor classification. Bull. Am. Meteor. Soc. 86(6), 809\u2013824 (2005)","journal-title":"Bull. Am. Meteor. Soc."},{"issue":"5","key":"47_CR9","doi-asserted-by":"publisher","first-page":"633","DOI":"10.1175\/1520-0426(2002)019<0633:AMFETP>2.0.CO;2","volume":"19","author":"VN Bringi","year":"2002","unstructured":"Bringi, V.N., Huang, G.J., Chandrasekar, V., et al.: A methodology for estimating the parameters of a gamma raindrop size distribution model from polarimetric radar data: application to a squall-line event from the TRMM\/Brazil campaign. J. Atmos. Oceanic Tech. 19(5), 633\u2013645 (2002)","journal-title":"J. Atmos. Oceanic Tech."},{"key":"47_CR10","unstructured":"Tan, H., Chandrasekar, V., Chen, H.: A deep neural network model for rainfall estimation using polarimetric WSR-88DP radar observations. In: Agu Fall Meeting, AGU Fall Meeting Abstracts 2016, pp. IN11B-1622 (2016)"},{"key":"47_CR11","unstructured":"Chen, H., Chandrasekar, V., Tan, H., et al: Development of deep learning based data fusion approach for accurate rainfall estimation using ground radar and satellite precipitation products. In: Agu Fall Meeting,\u00a0AGU Fall Meeting Abstracts 2016, pp. H12D\u201303 (2016)"},{"issue":"1","key":"47_CR12","doi-asserted-by":"publisher","first-page":"173","DOI":"10.1186\/s13638-017-0965-5","volume":"2017","author":"H Wang","year":"2017","unstructured":"Wang, H., Ran, Y., Deng, Y., et al.: Study on deep-learning based identification of hydrometeors observed by dual polarization Doppler weather radars. EURASIP J. Wirel. Commun. Netw. 2017(1), 173 (2017)","journal-title":"EURASIP J. Wirel. Commun. Netw."},{"issue":"8","key":"47_CR13","doi-asserted-by":"publisher","first-page":"2017","DOI":"10.1175\/JAMC-D-13-0358.1","volume":"53","author":"VN Mahale","year":"2014","unstructured":"Mahale, V.N., Zhang, G., Xue, M.: Fuzzy logic classification of S-band polarimetric radar echoes to identify three-body scattering and improve data quality. J. Appl. Meteorol. Climatol. 53(8), 2017\u20132033 (2014)","journal-title":"J. Appl. Meteorol. Climatol."},{"key":"47_CR14","volume-title":"The Physics of Clouds","author":"BJ Mason","year":"2010","unstructured":"Mason, B.J.: The Physics of Clouds. Clarendon Press, Oxford (2010)"},{"key":"47_CR15","first-page":"1","volume":"19","author":"C Wang","year":"2022","unstructured":"Wang, C., Wang, P., Wang, P., et al.: A spatiotemporal attention model for severe precipitation estimation. IEEE Geosci. Remote Sens. Lett. 19, 1\u20135 (2022)","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"47_CR16","unstructured":"Vaswani, A., Shazeer, N., Parmar,\u00a0N., et al: Attention is all you need. In: 30th International Proceedings of Neural Information Processing Systems, Long Beach, USA (2017)"},{"key":"47_CR17","unstructured":"Shi, X., Gao, Z., Lausen, L., et al: Deep learning for precipitation nowcasting: a benchmark and a new model. In: 30th International Proceedings of Neural Information Processing Systems, vol. 30. Long Beach, USA (2017)"},{"issue":"16","key":"47_CR18","doi-asserted-by":"publisher","first-page":"3157","DOI":"10.3390\/rs13163157","volume":"13","author":"Y Zhang","year":"2021","unstructured":"Zhang, Y., Bi, S., Liu, L., et al.: Deep learning for polarimetric radar quantitative precipitation estimation during landfalling typhoons in South China. Remote Sens. 13(16), 3157 (2021)","journal-title":"Remote Sens."}],"container-title":["Lecture Notes in Computer Science","Intelligent Robotics and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-99-6492-5_47","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,15]],"date-time":"2023-10-15T18:09:52Z","timestamp":1697393392000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-99-6492-5_47"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9789819964918","9789819964925"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/978-981-99-6492-5_47","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"16 October 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIRA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Robotics and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Hangzhou","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 July 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7 July 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icira2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/icira2023.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Microsoft CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"630","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"431","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"68% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}