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.
Highlights
This study further shows that tropical cyclone (TC) fractional contribution to extreme rainfall increases with largest rainfall events, with approximately 66–100% of annual maximum in excess of 100 mm over Western Australia associated with TCs at over one third of the locations
This study further shows that TC fractional contribution to extreme rainfall increases with the largest rainfall events; approximately 66–100% of annual maximum in excess of 100 mm over Western Australia associated with TCs at over one third of the locations
We have examined the probabilities of occurrence of extreme rainfall activity associated with cases of recent severe TC events that have caused substantial impacts in different Island nations (Fig. 19)
Summary
Tropical cyclones (TCs) play a prominent role in driving or contributing to extreme rainfall in different parts of the world (e.g., Lau et al 2008; Knight and Davis 2009; Wang et al 2009; Jiang and Zipser 2010; Chen et al 2013; Villarini and Denniston 2015; Khouakhi et al 2017), and can cause devastating impacts through extensive flooding (e.g., Woodruff et al 2013; Callaghan and Power 2014; Villarini et al 2014; Power and Callaghan 2016; Aryal et al 2019; Paerl et al 2019) and landslides (e.g., Antinao and Farfán 2013; Cogan et al 2018). TCs (and weak depressions) are frequently spawned within the SPCZ and can play a significant role in redirecting and transporting large amounts of moisture from the moisture-laden SPCZ to the islands that lie along TC trajectories This mechanism of moisture transport for the SWP (i.e., from an already established background moisture convection) is similar to what is documented, for example, for the East Asia monsoon region where TCs can provide intense rainfall over the south China coast and Taiwan, or to higher latitude regions of the Korean Peninsula and Japan that often lie along TC trajectories (Guo et al 2017). Recent studies (e.g., McGree et al 2014, 2019) have examined the variability and trends in observed total and extreme rainfall over SWP Island countries They concluded that generally there had been little change in annual and seasonal total and extreme rainfall in the western tropical Pacific in the long-term over the historical record, but there had been significant interannual and decadal variability.
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