{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T23:38:40Z","timestamp":1742945920508,"version":"3.40.3"},"publisher-location":"Cham","reference-count":42,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319501260"},{"type":"electronic","value":"9783319501277"}],"license":[{"start":{"date-parts":[[2016,1,1]],"date-time":"2016-01-01T00:00:00Z","timestamp":1451606400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016]]},"DOI":"10.1007\/978-3-319-50127-7_7","type":"book-chapter","created":{"date-parts":[[2016,11,29]],"date-time":"2016-11-29T01:04:06Z","timestamp":1480381446000},"page":"88-100","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Forecasting Monthly Rainfall in the Bowen Basin of Queensland, Australia, Using Neural Networks with Ni\u00f1o Indices"],"prefix":"10.1007","author":[{"given":"John","family":"Abbot","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jennifer","family":"Marohasy","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2016,11,29]]},"reference":[{"key":"7_CR1","unstructured":"Queensland Government Flood Commission of Inquiry, Chap. 13 Mining (2012). http:\/\/www.floodcommission.qld.gov.au\/publications\/final-report"},{"key":"7_CR2","unstructured":"Sharma, V., van de Graaff, S., Loechel, B., Franks, D.: Extractive resource development in a changing climate: learning the lessons from extreme weather events in Queensland, Australia. In: National Climate Change Adaptation Research Facility, Gold Coast, p. 110 (2013)"},{"key":"7_CR3","doi-asserted-by":"publisher","first-page":"3233","DOI":"10.1175\/2009MWR2861.1","volume":"137","author":"JS Risbey","year":"2009","unstructured":"Risbey, J.S., Pook, M.J., Mcintosh, P.C.: On the remote drivers of rain variability in Australia. Mon. Weather Rev. 137, 3233\u20133253 (2009)","journal-title":"Mon. Weather Rev."},{"key":"7_CR4","doi-asserted-by":"publisher","first-page":"L08702","DOI":"10.1029\/2011GL050820","volume":"39","author":"W Cai","year":"2012","unstructured":"Cai, W., van Rensch, P.: The 2011 southeast Queensland extreme summer Rain: a confirmation of a negative Pacific Decadal Oscillation phase? Geophys. Res. Lett. 39, L08702 (2012)","journal-title":"Geophys. Res. Lett."},{"key":"7_CR5","doi-asserted-by":"publisher","first-page":"112","DOI":"10.1071\/AR07061","volume":"59","author":"MR Anwar","year":"2008","unstructured":"Anwar, M.R., Rodriguez, D., Liu, D.L., et al.: Quality and potential utility of ENSO-based forecasts of spring rainfall and wheat yield in south-eastern Australia. Aust. J. Agri. Res. 59, 112\u2013126 (2008)","journal-title":"Aust. J. Agri. Res."},{"key":"7_CR6","doi-asserted-by":"publisher","first-page":"1443","DOI":"10.1175\/2010JAMC2373.1","volume":"49","author":"AJ Clarke","year":"2010","unstructured":"Clarke, A.J., Van Gorder, S., Everingham, Y.: Forecasting long-lead rainfall probability with application to Australia\u2019s Northeastern coast. J. Appl. Meteorol. Climatol. 49, 1443\u20131453 (2010)","journal-title":"J. Appl. Meteorol. Climatol."},{"key":"7_CR7","doi-asserted-by":"publisher","first-page":"307","DOI":"10.1136\/oem.2008.044966","volume":"67","author":"W Hu","year":"2010","unstructured":"Hu, W., Clements, A., Williams, G., et al.: Dengue fever and El Nino\/Southern Oscillation in Queensland, Australia: a time series predictive model. Occup. Environ. Med. 67, 307\u2013311 (2010)","journal-title":"Occup. Environ. Med."},{"key":"7_CR8","doi-asserted-by":"publisher","first-page":"1455","DOI":"10.5194\/hess-17-1455-2013","volume":"17","author":"P Brigode","year":"2013","unstructured":"Brigode, P., Mi\u0107ovi\u0107, Z., Bernardara, P., et al.: Linking ENSO and heavy rainfall events over coastal British Columbia through a weather pattern classification. Hydrol. Earth Syst. Sci. 17, 1455\u20131473 (2013)","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"7_CR9","doi-asserted-by":"publisher","first-page":"2301","DOI":"10.1002\/joc.3400","volume":"32","author":"GJ McCabe","year":"2012","unstructured":"McCabe, G.J., Ault, T.R., Cook, B.I., et al.: Influences of the El Nino Southern Oscillation and the Pacific Decadal Oscillation on the timing of the North American spring. Int. J. Climatol. 32, 2301\u20132310 (2012)","journal-title":"Int. J. Climatol."},{"key":"7_CR10","doi-asserted-by":"publisher","first-page":"2593","DOI":"10.1007\/s00382-011-1151-9","volume":"38","author":"IH Bulic","year":"2012","unstructured":"Bulic, I.H., Kucharski, F.: Delayed ENSO impact on spring precipitation over North Atlantic\/European region. Clim Dynam. 38, 2593\u20132612 (2012)","journal-title":"Clim Dynam."},{"issue":"6","key":"7_CR11","doi-asserted-by":"publisher","first-page":"1743","DOI":"10.1007\/s00376-013-2272-3","volume":"30","author":"K Xu","year":"2013","unstructured":"Xu, K., Zhu, C., He, J.: Two types of El Nino-related Southern Oscillation and their different impacts on global land precipitation. Adv. Atmos. Sci. 30(6), 1743\u20131757 (2013)","journal-title":"Adv. Atmos. Sci."},{"issue":"2","key":"7_CR12","doi-asserted-by":"publisher","first-page":"3348","DOI":"10.1002\/joc.3912","volume":"34","author":"S Diatta","year":"2014","unstructured":"Diatta, S., Fink, A.H.: Statistical relationship between remote climate indices and West African monsoon variability. Int. J. Climatol. 34(2), 3348\u20133367 (2014)","journal-title":"Int. J. Climatol."},{"key":"7_CR13","doi-asserted-by":"publisher","first-page":"351","DOI":"10.3402\/tellusa.v46i4.15485","volume":"46A","author":"MT Latif","year":"1994","unstructured":"Latif, M.T., Stockdale, J., Wolff, J., et al.: Climatology and variability in the ECHO coupled GCM. Tellus 46A, 351\u2013366 (1994)","journal-title":"Tellus"},{"key":"7_CR14","doi-asserted-by":"publisher","first-page":"167","DOI":"10.1007\/BF00208250","volume":"9","author":"M Latif","year":"1994","unstructured":"Latif, M., Barnett, T.P., Cane, M.A., et al.: A review of ENSO prediction studies. Clim. Dynam. 9, 167\u2013179 (1994)","journal-title":"Clim. Dynam."},{"key":"7_CR15","doi-asserted-by":"publisher","first-page":"135","DOI":"10.1007\/s003820050156","volume":"13","author":"FT Tangang","year":"1997","unstructured":"Tangang, F.T., Hsieh, W.W., Tang, B.: Forecasting the equatorial Pacific sea surface temperatures by neural network models. Clim. Dynam. 13, 135\u2013147 (1997)","journal-title":"Clim. Dynam."},{"key":"7_CR16","doi-asserted-by":"publisher","first-page":"219","DOI":"10.1002\/joc.1519","volume":"28","author":"H Halide","year":"2008","unstructured":"Halide, H., Ridd, P.: Complicated ENSO models do not significantly outperform very simple ENSO models. Int. J. Climatol. 28, 219\u2013233 (2008)","journal-title":"Int. J. Climatol."},{"issue":"5","key":"7_CR17","doi-asserted-by":"publisher","first-page":"631","DOI":"10.1175\/BAMS-D-11-00111.1","volume":"93","author":"AG Barnston","year":"2012","unstructured":"Barnston, A.G., Tippett, M.K., L\u2019Heureux, M.L., et al.: Skill of real-time seasonal ENSO model predictions during 2002\u20132011: is our capability increasing? B. Am. Meteorol. Soc. 93(5), 631\u2013651 (2012)","journal-title":"B. Am. Meteorol. Soc."},{"key":"7_CR18","doi-asserted-by":"publisher","first-page":"3625","DOI":"10.1016\/j.jcp.2007.05.014","volume":"227","author":"D Chen","year":"2008","unstructured":"Chen, D., Cane, M.A.: El Nino prediction and predictability. J. Comput. Phys. 227, 3625\u20133640 (2008)","journal-title":"J. Comput. Phys."},{"issue":"2","key":"7_CR19","doi-asserted-by":"publisher","first-page":"359","DOI":"10.1007\/s00376-009-0359-7","volume":"26","author":"F Zheng","year":"2009","unstructured":"Zheng, F., Zhu, J., Wang, H., et al.: Ensemble hindcasts of ENSO events over the past 120 years using a large number of ensembles. Adv. Atmos. Sci. 26(2), 359\u2013372 (2009)","journal-title":"Adv. Atmos. Sci."},{"issue":"5","key":"7_CR20","doi-asserted-by":"publisher","first-page":"566","DOI":"10.1007\/s13351-012-0503-7","volume":"26","author":"Y Peng","year":"2012","unstructured":"Peng, Y., Duan, W., Xiang, J.: Can the uncertainties of Madden\u2013Jullian Oscillation cause a significant \u201cSpring Predictability Barrier\u201d for ENSO events? Acta Meteorol. Sin. 26(5), 566\u2013578 (2012)","journal-title":"Acta Meteorol. Sin."},{"issue":"5","key":"7_CR21","doi-asserted-by":"publisher","first-page":"1003","DOI":"10.1007\/s00376-009-9166-4","volume":"27","author":"W Duan","year":"2010","unstructured":"Duan, W., Zhang, R.: Is model parameter error related to a significant spring predictability barrier for El Nino events? results from a theoretical model. Adv. Atmos. Sci. 27(5), 1003\u20131013 (2010)","journal-title":"Adv. Atmos. Sci."},{"key":"7_CR22","doi-asserted-by":"publisher","first-page":"221","DOI":"10.5194\/npg-20-221-2013","volume":"20","author":"W Kramer","year":"2013","unstructured":"Kramer, W., Dijkstra, H.A.: Optimal localized observations for advancing beyond the ENSO predictability barrier. Nonlin. Processes Geophys. 20, 221\u2013230 (2013)","journal-title":"Nonlin. Processes Geophys."},{"issue":"6","key":"7_CR23","doi-asserted-by":"publisher","first-page":"1093","DOI":"10.1007\/s00343-012-1271-z","volume":"30","author":"L Yan","year":"2012","unstructured":"Yan, L., Yu, Y.: The spring prediction barrier in ENSO hindcast experiments using the FGOALS-g model. Chinese J. Oceanology Limnol. 30(6), 1093\u20131104 (2012)","journal-title":"Chinese J. Oceanology Limnol."},{"key":"7_CR24","doi-asserted-by":"publisher","first-page":"1280","DOI":"10.1002\/joc.3513","volume":"33","author":"W Duan","year":"2013","unstructured":"Duan, W., Wei, C.: The \u2018spring predictability barrier\u2019 for ENSO predictions and its possible mechanism: results from a fully coupled model. Int. J. Climatol. 33, 1280\u20131292 (2013)","journal-title":"Int. J. Climatol."},{"issue":"3","key":"7_CR25","doi-asserted-by":"publisher","first-page":"166","DOI":"10.1016\/j.atmosres.2013.11.002","volume":"128","author":"J Abbot","year":"2014","unstructured":"Abbot, J., Marohasy, J.: Input selection and optimization for monthly rainfall forecasting in Queensland, Australia, using artificial neural networks. Atmos. Res. 128(3), 166\u2013178 (2014)","journal-title":"Atmos. Res."},{"issue":"4","key":"7_CR26","doi-asserted-by":"publisher","first-page":"717","DOI":"10.1007\/s00376-012-1259-9","volume":"29","author":"J Abbot","year":"2012","unstructured":"Abbot, J., Marohasy, J.: Application of artificial neural networks to rainfall forecasting in Queensland. Australia. Adv. Atmos. Sci. 29(4), 717\u2013730 (2012)","journal-title":"Australia. Adv. Atmos. Sci."},{"key":"7_CR27","first-page":"1743","volume":"172","author":"J Abbot","year":"2013","unstructured":"Abbot, J., Marohasy, J.: The application of artificial intelligence for monthly rainfall forecasting in the Brisbane Catchment, Queensland, Australia. WIT Trans. Ecol. Environ. 172, 1743\u20133541 (2013)","journal-title":"WIT Trans. Ecol. Environ."},{"key":"7_CR28","first-page":"1743","volume":"171","author":"J Abbot","year":"2013","unstructured":"Abbot, J., Marohasy, J.: The potential benefits of using artificial intelligence for monthly rainfall forecasting for the Bowen Basin, Queensland, Australia. WIT Trans. Ecol. Environ. 171, 1743\u20133541 (2013)","journal-title":"WIT Trans. Ecol. Environ."},{"key":"7_CR29","doi-asserted-by":"crossref","unstructured":"ASCE Task Committee on Application of Artificial Neural Networks in Hydrology: Artificial neural networks in hydrology. I preliminary concepts. J. Hydrol. Eng. 5, 115\u2013123 (2000)","DOI":"10.1061\/(ASCE)1084-0699(2000)5:2(115)"},{"issue":"6","key":"7_CR30","doi-asserted-by":"publisher","first-page":"L06712","DOI":"10.1029\/2005GL025052","volume":"33","author":"DC Verdon","year":"2006","unstructured":"Verdon, D.C., Franks, S.W.: Long-term behavior of ENSO: Interactions with the PDO over the past 400 years inferred from paleoclimate records. Geophys. Res. Lett. 33(6), L06712 (2006)","journal-title":"Geophys. Res. Lett."},{"key":"7_CR31","doi-asserted-by":"publisher","first-page":"319","DOI":"10.1007\/s003820050284","volume":"15","author":"S Power","year":"1999","unstructured":"Power, S., Casey, T., Folland, C., et al.: Interdecadal modulation of the impact of ENSO on Australia. Clim. Dynam. 15, 319\u2013324 (1999)","journal-title":"Clim. Dynam."},{"key":"7_CR32","doi-asserted-by":"publisher","first-page":"168","DOI":"10.1038\/ngeo760","volume":"3","author":"T Izumo","year":"2010","unstructured":"Izumo, T., Vialard, J., Lengaigne, M., et al.: Influence of the state of the Indian Ocean Dipole on the following year\u2019s El Ni\u00f1o. Nat. Geosci. 3, 168\u2013172 (2010)","journal-title":"Nat. Geosci."},{"key":"7_CR33","doi-asserted-by":"publisher","first-page":"1585","DOI":"10.1007\/s00477-013-0695-0","volume":"27","author":"P Singh","year":"2013","unstructured":"Singh, P., Borah, B.: Indian summer monsoon rainfall prediction using artificial neural network. Stoch. Environ. Res. Risk. Assess. 27, 1585\u20131599 (2013)","journal-title":"Stoch. Environ. Res. Risk. Assess."},{"issue":"1","key":"7_CR34","doi-asserted-by":"publisher","first-page":"260","DOI":"10.2478\/s11600-011-0044-y","volume":"60","author":"N Acharya","year":"2012","unstructured":"Acharya, N., Chattopadhyay, S., Kulkarni, M.A., et al.: A neurocomputing approach to predict monsoon rainfall in monthly scale using SST anomaly as a predictor. Acta Geophys. 60(1), 260\u2013279 (2012)","journal-title":"Acta Geophys."},{"issue":"1","key":"7_CR35","first-page":"57","volume":"4","author":"S Saigal","year":"2012","unstructured":"Saigal, S., Mehrotra, D.: Performance comparison of time series data using predictive data mining techniques. Adv. Inf. Mining. 4(1), 57\u201366 (2012)","journal-title":"Adv. Inf. Mining."},{"key":"7_CR36","doi-asserted-by":"publisher","first-page":"79","DOI":"10.3354\/cr030079","volume":"30","author":"CJ Willmott","year":"2005","unstructured":"Willmott, C.J., Matsuura, K.: Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance. Clim. Res. 30, 79\u201382 (2005)","journal-title":"Clim. Res."},{"key":"7_CR37","doi-asserted-by":"publisher","first-page":"343","DOI":"10.1002\/joc.3426","volume":"33","author":"J Zhu","year":"2013","unstructured":"Zhu, J., Zhou, G.Q., Zhang, R.H., et al.: Improving ENSO prediction in a hybrid coupled model with an embedded entrainment temperature parameterisation. Int. J. Climatol. 33, 343\u2013355 (2013)","journal-title":"Int. J. Climatol."},{"key":"7_CR38","doi-asserted-by":"publisher","first-page":"877","DOI":"10.1002\/qj.49711850705","volume":"118","author":"PJ Webster","year":"1992","unstructured":"Webster, P.J., Yang, S.: Monsoon and ENSO: selectively interactive systems. Quart. J. Roy. Meteor. Soc. 118, 877\u2013926 (1992)","journal-title":"Quart. J. Roy. Meteor. Soc."},{"key":"7_CR39","first-page":"945","volume":"122","author":"KM Lau","year":"1996","unstructured":"Lau, K.M., Yang, S.: The Asian monsoon and predictability of the tropical ocean-atmosphere system. Quart. J. Roy. Meteor. Soc. 122, 945\u2013957 (1996)","journal-title":"Quart. J. Roy. Meteor. Soc."},{"key":"7_CR40","doi-asserted-by":"publisher","first-page":"1480","DOI":"10.1029\/2003GL016872","volume":"30","author":"MJ McPhaden","year":"2003","unstructured":"McPhaden, M.J.: Tropical Pacific Ocean heat content variations and ENSO persistence barriers. Geophys. Res. Lett. 30, 1480 (2003)","journal-title":"Geophys. Res. Lett."},{"key":"7_CR41","doi-asserted-by":"publisher","first-page":"108","DOI":"10.1016\/j.gloplacha.2010.01.021","volume":"72","author":"F Zheng","year":"2010","unstructured":"Zheng, F., Zhu, J.: Spring predictability barrier of ENSO events from the perspective of an ensemble prediction system. Global Planet. Change 72, 108\u2013117 (2010)","journal-title":"Global Planet. Change"},{"key":"7_CR42","doi-asserted-by":"publisher","first-page":"145","DOI":"10.1016\/j.neunet.2006.01.004","volume":"19","author":"A Wu","year":"2006","unstructured":"Wu, A., Hsieh, W.W., Tang, B.: Neural network forecasts of the tropical Pacific sea surface temperatures. Neural Netw. 19, 145\u2013154 (2006)","journal-title":"Neural Netw."}],"container-title":["Lecture Notes in Computer Science","AI 2016: Advances in Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-50127-7_7","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,6]],"date-time":"2023-11-06T19:04:21Z","timestamp":1699297461000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-50127-7_7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016]]},"ISBN":["9783319501260","9783319501277"],"references-count":42,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-50127-7_7","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2016]]},"assertion":[{"value":"29 November 2016","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"AI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Australasian Joint Conference on Artificial Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Hobart, TAS","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Australia","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2016","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 December 2016","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 December 2016","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ausai2016","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ai2016.net\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}