Keywords:Tropical Cyclone, Extreme rainfall, extreme event attribution
The rainfall extremes and strong winds associated with tropical cyclones lead to significant damages and lost to where they make landfalling. Upward trend in term of financial lost was indicated for the past few decades from the report of major reinsurance firms. Whether the past anthropogenic warming played a significant role in such extreme event and their changes remained very controversial. On one hand, people argue it’s nearly impossible to attribute an individual extreme event to global warming. On the other hand, the increase of heavy rainfall is consistent with the expected effects of climate change on tropical cyclone. To diagnose possible anthropogenic contributions to the odds of heavy rainfall associated with tropical cyclone, we adapt an existing event attribution framework of modeling a ‘world that was’ and comparing it to a modeled ‘world that might have been’ for that same time but for the absence of historical anthropogenic drivers of climate. One limitation for applying such approach to high-impact weather system is that it will require models capable of capturing the essential processes lead to the studied extremes. Using a cloud system resolving model that can properly simulate the complicated interactions between tropical cyclone, large-scale background, topography, we first perform the ensemble ‘world that was’ simulations forced by the high resolution ECMWF YOTC analysis. We then re-simulate with the adjusted ‘world that might have been conditions’ by removing the regional atmospheric and oceanic forcing due to human influences estimated from the CMIP5 model ensemble mean conditions between all forcing and natural forcing only historical runs. Thus our findings are highly conditional on the driving analysis and adjustments therein, but the setup allows us to elucidate possible contribution of anthropogenic forcing to changes in the likelihood of heavy rainfall associated tropical cyclone. With only less than half of degree anthropogenic warming over the study area, we found that this forcing very likely (9 out of 10 cases) increase the risk of heavy rainfall event (grid rainfall greater than 33 mm per hour) by at least 16%. The role of dynamical processes that leads to precipitation extreme increases beyond the moisture content increase will be further analyzed and discussed.