Tropical cyclone contribution to extreme rainfall over southwest Pacific Island nations |
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Authors: | Deo Anil Chand Savin S. Ramsay Hamish Holbrook Neil J. McGree Simon Magee Andrew Bell Samuel Titimaea Mulipola Haruhiru Alick Malsale Philip Mulitalo Silipa Daphne Arieta Prakash Bipen Vainikolo Vaiola Koshiba Shirley |
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Affiliation: | 1.School of Engineering, Information Technology and Physical Sciences, Federation University Australia, Mt Helen Campus, Mt Helen, VIC, Australia ;2.CSIRO, Oceans and Atmosphere, Aspendale, VIC, Australia ;3.Institute for Marine and Antarctic Studies and ARC Centre of Excellence for Climate Extremes, University of Tasmania, Hobart, Australia ;4.Australian Bureau of Meteorology, Melbourne, Australia ;5.Centre for Water, Climate and Land, The University of Newcastle, Callaghan, NSW, Australia ;6.Samoa Meteorological Services, Apia, Samoa ;7.Solomon Islands Meteorological Service, Honiara, Solomon Islands ;8.Secretariat of the Pacific Regional Environment Programme, Apia, Samoa ;9.Fiji Meteorological Services, Nadi, Fiji ;10.Tonga Meteorological Services, Nukuʻalofa, Tonga ;11.Palau International Coral Reef Centre, Koror, Palau ; |
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Abstract: | Southwest Pacific nations are among some of the worst impacted and most vulnerable globally in terms of tropical cyclone (TC)-induced flooding and accompanying risks. This study objectively quantifies the fractional contribution of TCs to extreme rainfall (hereafter, TC contributions) in the context of climate variability and change. We show that TC contributions to extreme rainfall are substantially enhanced during active phases of the Madden–Julian Oscillation and by El Niño conditions (particularly over the eastern southwest Pacific region); this enhancement is primarily attributed to increased TC activity during these event periods. There are also indications of increasing intensities of TC-induced extreme rainfall events over the past few decades. A key part of this work involves development of sophisticated Bayesian regression models for individual island nations in order to better understand the synergistic relationships between TC-induced extreme rainfall and combinations of various climatic drivers that modulate the relationship. Such models are found to be very useful for not only assessing probabilities of TC- and non-TC induced extreme rainfall events but also evaluating probabilities of extreme rainfall for cases with different underlying climatic conditions. For example, TC-induced extreme rainfall probability over Samoa can vary from ~ 95 to ~ 75% during a La Niña period, if it coincides with an active or inactive phase of the MJO, and can be reduced to ~ 30% during a combination of El Niño period and inactive phase of the MJO. Several other such cases have been assessed for different island nations, providing information that have potentially important implications for planning and preparing for TC risks in vulnerable Pacific Island nations. |
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