Significant influences of global mean temperature and ENSO on extreme
rainfall over Southeast Asia
Marcelino Villafuerte II and Jun Matsumoto
Tokyo Metropolitan University, Tokyo, Japan (marcelino-villafuerte@ed.tmu.ac.jp)
Along with the increasing concerns on the consequences of global warming, and the accumulating records of
disaster related to heavy rainfall events in Southeast Asia, this study investigates whether a direct link can be
detected between the rising global mean temperature, as well as the El Niño–Southern Oscillation (ENSO), and
extreme rainfall over the region. The maximum likelihood modeling that allows incorporating covariates on the
location parameter of the generalized extreme value (GEV) distribution is employed. The GEV model is fitted
to annual and seasonal rainfall extremes, which were taken from a high-resolution gauge-based gridded daily
precipitation data covering a span of 57 years (1951–2007). Nonstationarities in extreme rainfall are detected
over the central parts of Indochina Peninsula, eastern coasts of central Vietnam, northwest of the Sumatra Island,
inland portions of Borneo Island, and on the northeastern and southwestern coasts of the Philippines. These
nonstationarities in extreme rainfall are directly linked to near-surface global mean temperature and ENSO. In
particular, the study reveals that a kelvin increase in global mean temperature anomaly can lead to an increase of
30% to even greater than 45% in annual maximum 1-day rainfall, which were observed pronouncedly over central
Vietnam, southern coast of Myanmar, northwestern sections of Thailand, northwestern tip of Sumatra, central
portions of Malaysia, and the Visayas island in central Philippines. Furthermore, a pronounced ENSO influence
manifested on the seasonal maximum 1-day rainfall; a northward progression of 10%–15% drier condition over
Southeast Asia as the El Niño develops from summer to winter is revealed. It is important therefore, to consider
the results obtained here for water resources management as well as for adaptation planning to minimize the
potential adverse impact of global warming, particularly on extreme rainfall and its associated flood risk over the
region.
Acknowledgment