Our hearts go out to those affected by hurricanes Harvey and Irma and by earlier monsoons across South Asia. These events are compelling remind- ers of the important role that science must play in preparing for disasters. But preparation is chal- lenging, as reflected in the many facets of the “sci- ence of preparedness.” Certainly, modeling and
forecasting storms are critical, but so are analyses of how
agencies, communities, and individuals interact to under-
stand and implement preparedness initiatives.
Hurricane tracking has received much recent attention
as Harvey and Irma moved
across the Atlantic. Information about the hurricanes’
movements was combined
with other data through the
use of large-scale computer
models to estimate likely
tracks and other characteristics of these storms. The
physical principles underlying weather are understood
well enough to generate
equations that can extend
initial values into the future, but the equations, the
methods used for solving
them, and available underlying data all have limitations.
Additional empirical parameters are introduced to produce workable models. It is
variations and uncertainties
that allow the development
of several different models
that make distinct predictions about future tracks.
The public has become used to seeing depictions and
comparisons of the results of these different models, al-
lowing individuals to develop an intuitive sense of the
uncertainty associated with these ambitious calculations.
The convergence of the models as storms approach can
allow agencies and communities to act before a storm’s
arrival, particularly if plans have been prepared in ad-
vance that are ready to be triggered. Extending the ac-
curacy of the models as far into the future as possible will
allow more time for the public and government officials
to make and implement decisions that may mitigate dam-
age and help prepare for the immediate aftermaths. The
United States government recently passed the Weather
Research and Forecasting Innovation Act of 2017, which
includes aims to improve longer-range forecasting.
Long-range estimates of the number and expected severity of storms in an upcoming hurricane season are also
challenging because they are driven in part by changes
in Earth’s climate. These estimates depend on empirical
data regarding long-term trends from previous seasons
as well as computational models. Physical principles
suggest that increases in storm intensity is a very likely
consequence of global warming (see www.gfdl.noaa.
gov/global-warming-and-hurricanes). These long-range
predictions may be useful for urban planning and
to prepare, not for a particular event, but rather, for the
likely occurrence of storms
over time in a given location.
The science of prepared-
ness also relates to the de-
velopment and evaluation of
disaster management plans.
Work in this area involves
analysis of previous events
to discern whether responses
were effective in mitigating
potential adverse outcomes
or may have, in some cases,
made them worse. Coordination between different agencies, the timeliness and clarity
of decisions made by officials,
and prior identification and
mobilization of resources
have all been identified as
key factors of management
plans. In addition, progress
has been made in developing computational models that
simulate events such as disease outbreaks, such that the
responses of virtual individuals are modeled in response
to different scenarios. With appropriate development,
such tools may be useful for exploring a wider range of
circumstances and enhancing preparedness without such
a strong dependence on data from previous actual events.
The recent storms have dramatically affected many
people. We must increase attention on refining tools to
improve preparedness, but keep in mind that improved
tools are useful only if appropriate steps are implemented. This will require coordinated efforts between
agencies and the public to develop resources and trust.
Science of preparedness
“…improved tools are useful
only if appropriate steps are
15 SEPTEMBER 2017 • VOL 357 ISSUE 6356 1073 SCIENCE sciencemag.org