Abstract
Natural hazards such as coastal and river floods, tornadoes, droughts,
heatwaves, wildfires, and landslides cause significant economic losses
(e.g., agriculture and property damage) and notable counts of
fatalities. While natural hazards are often considered to be caused by a
single climatic driver (e.g., coastal flood from storm surge only), they
can be associated with the combined occurrence of multiple drivers
(e.g., coastal flood driven by storm surge and precipitation). Defining
whether the climatic drivers (e.g., precipitation, temperature, or wind)
are extreme enough to turn the hazards into disasters is crucial for
estimating disaster risks. To date, extreme events are often defined
using the block maxima or peaks over threshold methods ignoring the
effects of the built environment and socio-economic conditions. However,
a hazard with the same magnitude can cause very different impacts in
regions with varying built environments and socio-economic conditions.
Additionally, when multiple climatic drivers are involved, traditional
methods of defining extreme events (block maxima and peaks over
threshold) are challenging to apply. In this research, we employ an
impact-based approach and define critical thresholds of climatic drivers
for 12 different hazards, across the US southeast coast. We use the
SHELDUS database (CEMHS, 2020) to identify historical hazard events that
caused socio-economic losses (property and crop damage) and identify
corresponding magnitudes of climatic drivers from historical in-situ
observations and reanalysis datasets from 1979 to 2019. We then identify
thresholds of climatic drivers for impact events where only one or
multiple drivers were involved. These impact-based thresholds can be
used, for example, to backfill loss databases (where impact information
was not available) and to project potential impacts into the future
using projections of the different climatic drivers.