Environmental Research Climate,
Год журнала:
2024,
Номер
3(4), С. 045016 - 045016
Опубликована: Сен. 26, 2024
Abstract
Computing
the
return
times
of
extreme
events
and
assessing
impact
climate
change
on
such
is
fundamental
to
event
attribution
studies.
However,
rarity
in
observational
record
makes
this
task
a
challenging
one,
even
more
so
for
‘record-shattering’
that
have
not
been
previously
observed
at
all.
While
models
could
be
used
simulate
extremely
rare
events,
an
approach
entails
huge
computational
cost:
gathering
robust
statistics
with
time
centuries
would
require
few
thousand
years
simulation.
In
study,
we
use
innovative
tool,
algorithm,
allows
us
sample
numerous
much
lower
cost
than
direct
simulations.
We
employ
algorithm
heatwave
seasons,
corresponding
large
anomalies
seasonal
average
temperature,
hotspot
South
Asia
using
global
model
Plasim.
show
estimates
levels
greater
precision
traditional
statistical
fits.
It
also
enables
computation
various
composite
statistics,
whose
accuracy
demonstrated
through
comparison
very
long
control
run.
particular,
our
results
reveal
seasons
are
associated
anticyclonic
anomaly
embedded
within
large-scale
hemispheric
quasi-stationary
wave-pattern.
Additionally,
accurately
represents
intensity-duration-frequency
sub-seasonal
heatwaves,
offering
insights
into
both
aspects
seasons.
This
studies
better
constrain
changes
event’s
probability
intensity
warming,
particularly
spanning
or
millennia.
Journal of Ecology,
Год журнала:
2025,
Номер
unknown
Опубликована: Янв. 2, 2025
Abstract
Plant
invasions
pose
a
major
threat
to
terrestrial
biodiversity,
and
microplastic
pollution
in
soil
could
exacerbate
this
problem.
Seed
germination,
crucial
stage
for
plants,
can
be
affected
by
microplastics
through
both
physical
interference
of
plastic
particles
chemical
leaching
from
additives.
We
conducted
greenhouse
experiment
using
native
invasive
plant
species
European
grasslands,
evaluated
individual
combined
effects
additives
on
germination
parameters.
found
that
primarily
seed
as
agents,
while
these
exerted
comparatively
lesser
impact.
Particles
negatively
all
species.
Germination
velocity,
synchrony
total
decreased
~30%,
~11%
~11%,
respectively,
soils
containing
compared
those
without.
Certain
were
For
Achillea
millefolium
Dactylis
glomerata
,
velocity
~26%
~7%,
~21%
with
than
without
them.
Plastic
may
have
blocked
pores
inhibited
hypocotyl
radicle
growth,
toxic
compounds
disrupted
key
processes.
By
contrast,
generally
did
not
affect
species,
suggesting
the
negative
experienced
natives,
whether
or
chemical,
counteracted
resulting
novel
conditions
created
microplastics,
which
include
amelioration
properties
such
increased
porosity
aeration,
potential
positive
plant–soil
feedbacks.
Invasive
profit
windows
variable
resource
availability,
germination.
Synthesis
.
promote
invasion
affecting
having
neutral
The
delayed
natives
due
poses
threat,
leading
competitive
disadvantages,
reduced
reproductive
success
vulnerability
Microplastic
appears
favour
over
during
early
stages
highlighting
effect
ecosystems
more
severe
previously
thought.
Abstract
Recent
decades
have
seen
substantial
variations
in
the
physicochemical
characteristics
of
atmospheric
aerosols
with
expected
continued
changes
future.
While
sustained
global
emission
controls
yielded
significant
environmental
benefits,
associated
climate
penalty
from
complex
radiative
effects
has
induced
additional
warming,
raising
public
concern.
Our
study
reveals
that
increased
coarse
particles
enhance
fine
particle
coagulation,
contributing
to
higher
levels
and
a
reduction
peak
size,
thereby
scattering
more
solar
radiation
mitigating
warming
reduced
Europe.
From
1999
2021,
offset
24.6%
(26.3%)
cooling
effect
at
top
(ground)
atmosphere
reductions.
findings
highlight
but
role
aerosol
size
influencing
budget,
offering
potential
relief
for
concerns
bolstering
emissions
efforts,
important
European
implications
amid
ongoing
anthropogenic
cuts.
Environmental Research Climate,
Год журнала:
2024,
Номер
3(3), С. 035005 - 035005
Опубликована: Май 29, 2024
Abstract
Summertime
heatwaves
are
extreme
events
with
a
large
societal
impact.
Intensity,
duration
and
spatial
extent,
all
heatwave
properties
projected
to
increase
in
warming
world,
implying
that
summers
qualified
as
the
past
will
become
increasingly
normal.
In
this
paper
we
quantify
how
changes
play
out
for
July
2019
European
shattered
temperature
records
throughout
Western
Europe.
We
combine
storyline
approach
ensemble
Pseudo
Global
Warming
(PGW)
high-resolution
dynamical
downscaling.
The
downscaling
is
done
regional
climate
model
(RACMO2,
12
km
resolution)
convection-permitting
(HCLIM-AROME,
2.5
resolution).
Under
PGW
maximum
during
rises
1.5
times
faster
than
global
mean,
even
at
moderate
levels
impact
tangible.
Moreover,
there
no
sign
off
higher
levels,
+4K
above
present-day
temperatures
could
reach
50
∘
C.
During
cities
islands
of
heat
where
daily
maxima
night-time
minima
up
5
C
rural
areas
show
ultra-high
resolution
HCLIM-AROME
simulations
150
m
resolution.
Atmospheric Science Letters,
Год журнала:
2024,
Номер
25(10)
Опубликована: Авг. 14, 2024
Abstract
In
July
2021,
a
cut‐off
low‐pressure
system
brought
extreme
precipitation
to
Western
Europe.
Record
daily
rainfall
totals
led
flooding
that
caused
loss
of
life
and
substantial
damage
infrastructure.
Climate
change
can
amplify
extremes
via
thermodynamic
processes,
but
the
role
dynamical
changes
is
uncertain.
We
assess
how
dynamics
involved
in
this
particular
event
are
changing
using
flow
analogues.
Using
past
present
periods
reanalyses
large
ensemble
climate
model
data
present‐day
2°C
warmer
climate,
we
find
best
analogues
become
more
similar
observed
over
Europe
2021.
This
may
imply
rain
events
will
occur
frequently
future.
Moreover,
magnitude
analogue
lows
has
deepened,
associated
air
masses
contain
precipitable
water.
Simulations
future
show
could
lead
intense
further
east
than
current
due
shift
pattern.
Such
unprecedented
have
consequences
for
society,
need
mitigate
adapt
reduce
impacts.
Journal of Geophysical Research Atmospheres,
Год журнала:
2024,
Номер
129(22)
Опубликована: Ноя. 22, 2024
Abstract
Lightning
is
a
major
source
of
wildfire
ignition
in
the
western
United
States
(WUS).
We
build
and
train
convolutional
neural
networks
(CNNs)
to
predict
occurrence
cloud‐to‐ground
(CG)
lightning
across
WUS
during
June–September
from
spatial
patterns
seven
large‐scale
meteorological
variables
reanalysis
(1995–2022).
Individually
trained
CNN
models
at
each
1°
×
grid
cell
(
n
=
285
CNNs)
show
high
skill
predicting
CG
days
(median
AUC
0.8)
perform
best
parts
interior
Southwest
where
summertime
most
common.
Further,
interannual
correlation
between
observed
predicted
r
0.87),
demonstrating
that
locally
CNNs
realistically
capture
year‐to‐year
variation
activity
WUS.
then
use
layer‐wise
relevance
propagation
(LRP)
investigate
predictor
successful
prediction
cell.
Using
maximum
LRP
values,
our
results
two
thermodynamic
variables—ratio
surface
moist
static
energy
free‐tropospheric
saturation
energy,
700–500
hPa
lapse
rate—are
relevant
predictors
for
93%–96%
depending
on
variant
used.
As
not
directly
simulated
by
global
climate
models,
these
could
be
used
parameterize
assess
changes
future
with
projected
change.
Understanding
risk
consequently
lightning‐caused
inform
fire
management,
planning,
disaster
preparedness.
Abstract
Climatic
extreme
events
are
important
because
they
can
strongly
impact
humans,
infrastructure,
and
biodiversity
will
be
affected
by
a
changing
climate.
Surface
Solar
Radiation
(SSR)
is
the
primary
energy
source
for
solar
photovoltaics
(PV),
which
indispensable
in
future
zero‐emissions
systems.
Despite
their
pivotal
role,
SSR
remain
under‐documented.
We
provide
starting
point
analysis
focusing
on
caused
internal
variability
alone
therefore
building
baseline
research.
analyze
using
daily‐mean
data
from
pre‐industrial
control
simulations
(piControl)
of
Coupled
Model
Intercomparison
Project—Phase
6.
investigate
role
PV
generation
Global
Energy
Estimator
with
intent
strengthening
system's
resilience.
Our
results
show
pronounced
asymmetry
between
consecutive
days
extremely
high
low
radiation
over
land,
former
occurring
more
frequently
than
latter.
Moreover,
our
call
detailed
modeling
that
includes
panel
geometry.
Simple
models
based
linear
representations
prove
insufficient
due
to
seasonal
variations
strong
non‐linear
dependency
extremes.
demonstrate
how
climate
model
leveraged
understand
persistent
extremes
relevant