Despite
major
advances
in
numerical
weather
prediction,
few
resources
exist
to
forecast
wildland
fire
danger
conditions
support
operational
management
decisions
and
community
early-warning
systems.
Here
we
present
the
development
evaluation
of
a
spatial
index
that
can
be
used
assess
historical
events,
extreme
danger,
communicate
those
both
firefighters
public.
It
uses
two
United
States
National
Fire
Danger
Rating
System
indices
are
related
intensity
spread
potential.
These
normalized,
combined,
categorized
based
on
39-yr
climatology
(1979–2017)
produce
single,
categorical
metric
called
Severe
Index
(SFDI)
has
five
classes;
Low,
Moderate,
High,
Very
Severe.
We
evaluate
SFDI
against
number
newly
reported
wildfires
total
area
burned
from
agency
reports
(1992–2017)
as
well
daily
remotely
sensed
numbers
active
pixels
radiative
power
for
large
fires
(2003–2016)
Moderate-Resolution
Imaging
Spectroradiometer
(MODIS)
across
conterminous
States.
show
adequately
captures
geographic
seasonal
variations
activity
intensity,
where
58%
eventual
by
records,
75.2%
all
MODIS
pixels,
81.2%
occurred
when
was
either
High
or
(above
90th
percentile).
further
is
strong
predictor
firefighter
fatalities,
97
129
(75.2%)
burnover
deaths
1979
2017
Finally,
an
system
short-term,
predictions
forecasts
76.2%
satellite
detections
during
first
48
h
following
ignition
nine
high-profile
case
study
2018
under
conditions.
The
studies
indicate
events
caused
tremendous
damage
loss
life
could
mapped
ahead
time,
which
would
allow
managers
vulnerable
communities
additional
time
prepare
potentially
dangerous
Ultimately,
this
simple
provide
critical
decision
information
fire-prone
form
basis
improve
situational
awareness
save
lives.
Earth s Future,
Год журнала:
2019,
Номер
7(8), С. 892 - 910
Опубликована: Июль 15, 2019
Abstract
Recent
fire
seasons
have
fueled
intense
speculation
regarding
the
effect
of
anthropogenic
climate
change
on
wildfire
in
western
North
America
and
especially
California.
During
1972–2018,
California
experienced
a
fivefold
increase
annual
burned
area,
mainly
due
to
more
than
an
eightfold
summer
forest‐fire
extent.
Increased
area
very
likely
occurred
increased
atmospheric
aridity
caused
by
warming.
Since
early
1970s,
warm‐season
days
warmed
approximately
1.4
°C
as
part
centennial
warming
trend,
significantly
increasing
vapor
pressure
deficit
(VPD).
These
trends
are
consistent
with
simulated
models.
The
response
VPD
is
exponential,
meaning
that
has
grown
increasingly
impactful.
Robust
interannual
relationships
between
strongly
suggest
nearly
all
during
1972–2018
was
driven
VPD.
Climate
effects
were
less
evident
nonforested
lands.
In
fall,
wind
events
delayed
onset
winter
precipitation
dominant
promoters
wildfire.
While
these
variables
did
not
much
over
past
century,
background
consequent
fuel
drying
enhancing
potential
for
large
fall
wildfires.
Among
many
processes
important
California's
diverse
regimes,
warming‐driven
clearest
link
activity
date.
Bulletin of the American Meteorological Society,
Год журнала:
2019,
Номер
100(9), С. Si - S306
Опубликована: Сен. 1, 2019
Abstract
Editor’s
note:
For
easy
download
the
posted
pdf
of
State
Climate
for
2019
is
a
low-resolution
file.
A
high-resolution
copy
report
available
by
clicking
here
.
Please
be
patient
as
it
may
take
few
minutes
file
to
download.
Since
the
beginning
of
twenty-first
century
California,
USA,
has
experienced
a
substantial
increase
in
frequency
large
wildfires,
often
with
extreme
impacts
on
people
and
property.
Due
to
size
state,
it
is
not
surprising
that
factors
driving
these
changes
differ
across
this
region.
Although
there
are
always
multiple
wildfire
behavior,
we
believe
helpful
model
for
understanding
fires
state
frame
discussion
terms
bottom-up
vs.
top-down
controls
fire
behavior;
is,
clearly
dominated
by
anomalously
high
fuel
loads
from
those
wind
events.
Of
course,
distinction
somewhat
artificial
all
controlled
involving
fuels,
winds,
topography.
However,
recognizable
as
fuel-dominated
wind-dominated
provide
interesting
case
studies
behind
two
extremes.
These
types
greatly
their
(1)
geographical
distribution
(2)
past
history,
(3)
prominent
sources
ignition,
(4)
seasonal
timing,
(5)
resources
most
at
risk,
(6)
requirement
different
management
responses.
Science,
Год журнала:
2023,
Номер
379(6631), С. 457 - 461
Опубликована: Фев. 2, 2023
Extreme
wildfires
threaten
human
lives,
air
quality,
and
ecosystems.
Meteorology
plays
a
vital
role
in
wildfire
behaviors,
the
links
between
climate
have
been
widely
studied.
However,
it
is
not
fully
clear
how
fire-weather
feedback
affects
short-term
variability,
which
undermines
our
ability
to
mitigate
fire
disasters.
Here,
we
show
primacy
of
synoptic-scale
driving
extreme
fires
Mediterranean
monsoon
regimes
West
Coast
United
States
Southeastern
Asia.
We
found
that
radiative
effects
smoke
aerosols
can
modify
near-surface
wind,
dryness,
rainfall
thus
worsen
pollution
by
enhancing
emissions
weakening
dispersion.
The
intricate
interactions
among
wildfires,
smoke,
weather
form
positive
loop
substantially
increases
exposure.
Structure
loss
is
an
acute,
costly
impact
of
the
wildfire
crisis
in
western
conterminous
United
States
("West"),
motivating
need
to
understand
recent
trends
and
causes.
We
document
a
246%
rise
West-wide
structure
from
wildfires
between
1999-2009
2010-2020,
driven
strongly
by
events
2017,
2018,
2020.
Increased
was
not
due
increased
area
burned
alone.
Wildfires
became
significantly
more
destructive,
with
160%
higher
structure-loss
rate
(loss/kha
burned)
over
past
decade.
primarily
unplanned
human-related
ignitions
(e.g.
backyard
burning,
power
lines,
etc.),
which
accounted
for
76%
all
resulted
10
times
structures
destroyed
per
unit
compared
lightning-ignited
fires.
Annual
well
explained
ignitions,
while
decadal
state-level
abundance
flammable
vegetation.
Both
predictors
decades
likely
interacted
fuel
aridity
drive
trends.
While
states
are
diverse
patterns
trends,
nearly
experienced
burning
and/or
rates,
particularly
California,
Washington,
Oregon.
Our
findings
highlight
how
fire
regimes-characteristics
space
time-are
fundamentally
social-ecological
phenomena.
By
resolving
diversity
Western
regimes,
our
work
informs
regionally
appropriate
mitigation
adaptation
strategies.
With
millions
high
risk,
reducing
rethinking
we
build
critical
preventing
future
disasters.
International Journal of Wildland Fire,
Год журнала:
2024,
Номер
33(3)
Опубликована: Март 18, 2024
Background
Fire
danger
rating
systems
are
used
daily
across
Australia
to
support
fire
management
operations
and
communications
the
general
public
regarding
potential
danger.
Aims
In
this
paper,
we
introduce
Australian
Danger
Rating
System
(AFDRS),
providing
a
short
historical
account
of
in
as
well
requirements
for
an
improved
forecast
system.
Methods
The
AFDRS
combines
nationally
consistent,
spatially
explicit
fuel
information
with
weather
advanced
behaviour
models
knowledge
produce
locally
relevant
ratings
potential.
Key
results
A
well-defined
framework
is
essential
categorising
defining
based
on
operational
response,
impact
observable
characteristics
incidents.
modular,
supporting
continuous
incremental
improvements
allowing
upgrades
components
response
new
science.
Conclusions
provides
method
estimate
best
available
models,
leading
potentially
significant
way
calculated,
interpreted.
Implications
was
implemented
2022,
most
change
forecasting
more
than
50
years.
Abstract
Effective
wildfire
prevention
includes
actions
to
deliberately
target
different
causes.
However,
the
cause
of
an
increasing
number
wildfires
is
unknown,
hindering
targeted
efforts.
We
developed
a
machine
learning
model
ignition
across
western
United
States
on
basis
physical,
biological,
social,
and
management
attributes
associated
with
wildfires.
Trained
from
1992
2020
12
known
causes,
overall
accuracy
our
exceeded
70%
when
applied
out‐of‐sample
test
data.
Our
more
accurately
separated
ignited
by
natural
versus
human
causes
(93%
accuracy),
discriminated
among
11
classes
human‐ignited
55%
accuracy.
attributed
greatest
percentage
150,247
for
which
source
was
unknown
equipment
vehicle
use
(21%),
lightning
(20%),
arson
incendiarism
(18%).