Abstract
Risk-based event attribution (EA) science involves probabilistically estimating alterations of the likelihoods of particular weather events, such as heat waves and heavy rainfall, owing to global warming, and has been considered as an effective approach with regard to climate change adaptation. However, risk-based EA for heavy rain events remains challenging because, unlike extreme temperature events, which often have a scale of thousands of kilometres, heavy rainfall occurrences depend on mesoscale rainfall systems and regional geographies that cannot be resolved using general circulation models (GCMs) that are currently employed for risk-based EA. Herein, we use GCM large-ensemble simulations and high-resolution downscaled products with a 20-km non-hydrostatic regional climate model (RCM), whose boundary conditions are obtained from all available GCM ensemble simulations, to show that anthropogenic warming increased the risk of two record-breaking regional heavy rainfall events in 2017 and 2018 over western Japan. The events are examined from the perspective of rainfall statistics simulated by the RCM and from the perspective of background large-scale circulation fields simulated by the GCM. In the 2017 case, precipitous terrain and a static pressure pattern in the synoptic field helped reduce uncertainty in the dynamical components, whereas in the 2018 case, a static pressure pattern in the synoptic field provided favourable conditions for event occurrence through a moisture increase under warmer climate. These findings show that successful risk-based EA for regional extreme rainfall relies on the degree to which uncertainty induced by the dynamic components is reduced by background conditioning.
Highlights
It is widely acknowledged that global warming significantly affects the features of extreme events[1]
The ascending current and instability of the Baiu rainband were enhanced by the upper-level westerly jet and travelling synoptic waves, the mid-level advection of warm and moist air influenced by the South Asian thermal low, and low-level southerly moisture transport associated with an enhanced north Pacific subtropical high (NPSH)[29]
We confirmed whether these rainfall systems and responsible atmospheric circulations in each location are successfully classified npj Climate and Atmospheric Science (2020) 37
Summary
It is widely acknowledged that global warming significantly affects the features of extreme events[1]. For the storyline approach, model boundary conditions are strictly constrained by realistic background atmospheric conditions to ensure the occurrence of the event of interest Through these approaches, a reasonable degree of consensus can be obtained on the attribution of temperature extremes to anthropogenic climate change, e.g. refs. 2018 in Japan using an RCM with realistic initial and boundary conditions based on the reanalysis data and found that the record-breaking precipitation could be attributed to recent rapid warming through comparison between hindcast and detrended experiments. This technique is similar to the ‘pseudo-global warming’ approach and has been extensively used for storyline EA of tropical cyclones (TCs).
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