"negative learning" where the scientific belief and technical evidence turns out to be
incorrect.
There is perhaps a grand-challenge problem inherent in this discussion. Much of
this work focuses on how natural systems respond to climate and climate change.
However, this is not strictly a one-way process, as the response of natural systems to
climate change (potentially resulting from human intervention) will have a feedback to
the climate system. Such responses are being incorporated in some crude way in
climate models, but there is much work to be done in this area.
Research Challenge for the Mathematical Sciences: Find new methods for
quantifying and visualizing uncertainty in ensembles of climate models; develop
scalable, spatial, and spatial-temporal models of extreme climate events and adaptation
of natural systems to climate drivers; explore how changes in human systems affect the
climate systems; develop new tools for studying spatial and spatial-temporal processes
and the underlying issues of data fusion and data assimilation.
Example 2: Preparing for and Responding to Rare Extreme Events
Increasing frequency of extreme events such as floods, hurricanes, wildfires, or
heat waves is predicted as an outcome of climate change. Reacting to such events
stresses human beings and the infrastructure designed to protect them; preparing for
them and responding to them so as to minimize impact on humans leads to challenging
mathematical problems. For example, extreme heat events overtax energy and water
needs of cities, eventually compromising infrastructure and safety of homes, offices, and
public facilities. Increased incidence of heat stroke, dehydration, cardiac stress and
respiratory distress are commonly resulting health problems. These can be especially
serious among elderly or juvenile populations. Under severe enough conditions,
evacuation (transport) to controlled environments can be the best means of ensuring the
continued well-being of the population. However, the determination of optimal placement
of relief centers can be difficult. Facilities must be able to maintain energy and water
supplies and sufficient, hygienically-maintained space for displaced persons. They must
be able to manage incoming supplies of food and potable water despite the heat-related
increase in the dangers of food spoilage. Further, the populations at greatest health risk
from heat events are also those least able to travel long distances, requiring
consideration of spatial demography for the area being served by the facility. Easy
access to healthcare will also be of great importance, whether that should ultimately
include planning for onsite care, or ensuring nearby access to hospitals capable of
handling the increased patient load. Careful planning for the locations chosen for relief
centers may be of critical importance to ensuring minimal health impact during heat
events. The research challenges in this area cut across disciplines, involving spatial
demographic distribution of vulnerable populations, probabilistic mixed integer
programming methods, and other aspects of “location theory”. While location theory is a
classical subject in operations research and discrete mathematics, there are major new
twists that interrelate choice of optimal location to predictions of duration, onset time,
and severity of heat events that will require the engagement of remote sensors and the
expertise of climate change modelers.^1
(^1) This paragraph is taken from the description of the DIMACS Climate and Health Research Initiative.