Seattle
Nisqually Earthquake 2001
M6.8
Mount St. Helens Eruption 1980
Portland
Helena
Minneapolis
Pierre
Boston
Storm of the Century 1993
New York
Chicago
Oakland Fire 1991
Salt Lake City
San Francisco
Earthquake 1906
M7.8
Philadelphia
Omaha
Washington, D.C.
San Francisco
New England Hurricane 1938
Las Vegas
Northridge Earthquake 1994
M6.7
Los Angeles
Phoenix Hailstorm 2010
Joplin Tornado 2011
Wichita
EF5
Virginia Beach
M6.6-8.1
Super Outbreak 1974
30 Tornadoes F4-F5
Nashville
Bridge Creek–Moore Tornado 1999
Memphis
F5
Phoenix
Category 3
1811-1812
St. Louis New Madrid
Earthquakes
Charleston Earthquake 1886
Moore Tornado 2013
EF5
Atlanta
Cedar Fire 2003
Dallas
M7.3
Charleston
Southeast U.S.
Tornadoes 2011
Wallow Fire 2011
358 Tornadoes
EF5 Max
New Orleans
Hurricane Andrew 1992
Category 5
Tampa
Miami
Galveston Hurricane 1900
Category 4
Honolulu
Hurricane Katrina 2005
Category 4
Great Miami Hurricane 1926
Category 4
Hurricane Iniki 1992
Category 4
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LOW
LOW
WINTER STORM
HIGH
LOW
HIGH
LOW
HIGH
VOLCAN O
HIGH
WIL DF IR E
HIGH
HU RRIC ANE
EARTH QUAK E
HIGH
TO RNADO/H AIL
Anchorage
LOW
LOW
CATASTROPHIC RISK IN THE UNITED STATES
Regional Risk
On average, the U.S. property and casualty industry pays approximately
$20 billion in catastrophe-related claims per year. RMS catastrophe
models synthesize the latest science, data, and engineering knowledge,
along with 25 years of catastrophe risk research, to analyze the
likelihood that a disaster will cause damage at a location, and how
severe that damage could be.
The Regional Perspective
This map illustrates the regional risk from the most damaging natural
hazards in the United States: earthquake (ground shaking and fire),
hurricane (wind and flood), severe convective storm (tornado and hail),
winter storm (snow, ice, and wind), wildfire, and volcano. All map data is
derived from RMS catastrophe models and loss assessments.
The different colors highlight the dominant natural hazard driving risk
across different regions of the United States. Within each region, risk is
expressed on a scale from low to high. The map includes some of the
nation’s most significant catastrophes to provide an additional historical
perspective.
Risk vs. Hazard
Simply defined, a hazard is a source of potential damage or harm, while
risk is the probability that a hazard will cause damage or harm.
Hurricane winds are a hazard, while the probability of those winds
damaging a property is a risk.
Hazard maps and risk maps look similar, but tell different stories. A
typical hazard map indicates the probability that a peril will strike a
location, and how severe that peril’s effects could be. RMS risk maps
illustrate the probability that a hazard will cause property damage at a
location, and how that damage translates into loss.
Quantifying Catastrophe Risk
RMS catastrophe models quantify risk using the "pure premium," which
is an estimate of the annual insurance premium needed to cover losses
from the modeled perils over time. The pure premium estimate evens
out the influence of year-on-year extremes and allows a direct
comparison of the potential damage and loss from a range of perils.
For example, over time, the cumulative losses at one location from
frequent, lower-severity events such as hailstorms may be similar to—or
even exceed—the loss at another location from a higher-severity but less
frequent event, like a hurricane.
Also, regions that have experienced a recent catastrophe are typically
better prepared for future, similar events, as they tend to enforce stricter
building codes and construction practices than areas that have not
experienced such an event. Such mitigating strategies help to lessen a
catastrophe’s impact, sometimes causing risk to be lower than in regions
populated with more vulnerable homes.
To establish a common baseline for comparative risk assessment, the
pure premium estimate is normalized to a constant unit of property
exposure—a uniform building with an insured value of $1,000. The
resulting “loss cost,” represented as a dollar amount per $1,000, allows
for direct comparisons of risk severity.
By removing the influence of property value or population density on
loss results, the loss cost reveals a region’s risk from the peril in
question. The loss from a hurricane in Miami, Florida will be much
greater than that of a hurricane in a small town nearby, but their relative
risk will be similar.
Regions that experience frequent, damaging perils have a higher relative
loss cost than regions where severe events are rare. For example, the
loss cost for earthquake risk in San Francisco is approximately $3 to $5
per $1,000 of property exposure. Along the Louisiana coast, the
hurricane risk loss cost is much higher, at about $20 to $25 per $1,000
of property exposure.
Interpreting the Risk
The apparently negligible losses in some areas of the country do not
necessarily imply an absence of risk. Rare, extreme catastrophes are “tail
risk” events that can cause significant loss anywhere within the United
States. A large earthquake in New York is a possible but improbable
scenario that would be devastating.
Note that the map represents the natural hazards that RMS models, and
does not include, for example, precipitation-induced flooding. However,
RMS does model hurricane-induced storm surge flooding, which drives
the majority of flood risk in the United States.
About RMS
RMS models and software help insurers, financial markets,
corporations, and public agencies evaluate and manage
catastrophe risks throughout the world.
We lead an industry that we helped to pioneer—catastrophe risk
modeling—and are the innovators of the RMS(one)® platform,
which is transforming the world's understanding and
quantification of risk through open, real-time exposure and risk
management.
More than 400 insurers, reinsurers, trading companies, and other
financial institutions trust RMS models and SaaS solutions to
better understand and manage the risks of natural and
human-made catastrophes, including hurricanes, earthquakes,
floods, terrorism, and pandemics.
We think about the unthinkable, enabling the management of
even the most extreme events. Our scientific and objective
measurement of risk facilitates the efficient flow of capital
needed to insure, manage, and ultimately mitigate these risks to
reduce the consequences of disasters, promoting resilient
societies and a sustainable global economy.