Journal of Vegetation Science,
Год журнала:
2024,
Номер
35(4)
Опубликована: Июль 1, 2024
Abstract
Questions
The
alpine
vegetation
of
the
Alps
is
particularly
vulnerable
to
climate
change,
as
temperature
increase
in
this
region
twice
global
average
and
available
area
for
new
colonisations
decreases
with
increasing
elevation.
While
numerous
studies
have
investigated
response
vascular
plants
a
warming
belt,
only
handful
that
cryptogams
European
Alps.
Based
on
21‐year
monitoring
project,
we
assessed
effects
change
along
elevation,
from
treeline
subnival
belt.
Location
Four
GLORIA
summits
Valais
(Switzerland).
Methods
Between
2001
2022,
terricolous
lichens
bryophytes
(from
2008)
were
inventoried
52
1‐m
2
plots
distributed
across
four
summits:
2360
m
a.s.l.
(treeline),
2550
(lower
alpine),
2990
(upper
alpine)
3210
(subnival).
Changes
species
cover
richness
analysed
using
generalised
linear
mixed‐effects
model
(GLMMs).
Results
For
bryophytes,
total
remained
stable
overall.
However,
six
declined
significantly
between
2008
decreased
after
2015.
lichens,
increased
lower
summit,
while
upper
summits.
Conclusions
Bryophytes
probably
suffered
increasingly
dry
conditions,
succession
very
warm
summers
over
last
decades.
Terricolous
taken
advantage
warmer
conditions
their
colonised
they
compete
soil
light,
may
suffer
shrub
tree
encroachment
future
will
be
limited
upwards
by
rarity
developed
soils.
large
topo‐climatic
gradient
(850
m)
length
time
series
suggest
similar
trends
are
likely
more
widespread
Climate Dynamics,
Год журнала:
2022,
Номер
60(1-2), С. 65 - 86
Опубликована: Май 10, 2022
Abstract
A
comprehensive
assessment
of
twenty-first
century
climate
change
in
the
European
Alps
is
presented.
The
analysis
based
on
EURO-CORDEX
regional
model
ensemble
available
at
two
grid
spacings
(12.5
and
50
km)
for
three
different
greenhouse
gas
emission
scenarios
(RCPs
2.6,
4.5
8.5).
core
simulation
has
been
subject
to
a
dedicated
evaluation
exercise
carried
out
frame
CH2018
Climate
Scenarios
Switzerland.
Results
reveal
that
entire
Alpine
region
will
face
warmer
course
all
considered.
Strongest
warming
projected
summer
season,
regions
south
main
ridge
high-end
RCP
8.5
scenario.
Depending
medium
high
elevations
might
experience
an
amplified
warming.
Model
uncertainty
can
be
considerable,
but
major
patterns
are
consistent
across
ensemble.
For
precipitation,
seasonal
shift
precipitation
amounts
from
winter
over
most
parts
domain
projected.
However,
individual
simulations
show
signals
opposite
sign.
Daily
intensity
increase
seasons
sub-domains,
while
wet-day
frequency
decrease
season.
temperature
negatively
correlated
with
change,
i.e.
and/or
strong
mean
typically
stronger
decrease.
By
contrast,
positive
correlation
between
found
winter.
Among
other
indicators,
snow
cover
strongly
affected
by
climatic
changes
widespread
except
very
elevation
settings.
In
general
magnitude
increases
assumed
forcing,
i.e.,
smallest
2.6
largest
being
located
between.
These
results
largely
agree
previous
works
older
generations
RCM
ensembles
but,
due
comparatively
large
size
spatial
resolution,
allow
more
decent
inherent
projection
uncertainties
details
future
change.
Communications Earth & Environment,
Год журнала:
2024,
Номер
5(1)
Опубликована: Апрель 6, 2024
Abstract
In
much
of
western-central
Europe,
summer
temperatures
have
surged
three
times
faster
than
the
global
mean
warming
since
1980,
yet
this
is
not
captured
by
most
climate
model
simulations.
Here
we
disentangle
into
thermodynamic
and
circulation-induced
contributions,
show
that
latter
main
reason
why
numerically
simulated
weaker
observed.
Crucially,
regional
models
from
Coordinated
Regional
Downscaling
Experiment
with
constant
aerosol
forcings
systematically
strongest
discrepancies
observations:
in
these
simulations,
brightening
associated
due
to
reductions
represented.
We
estimate
an
effect
~0.5
°C
over
Europe
for
our
ensemble,
discrepancy
evolving
aerosols
increases
future
projections.
To
better
reap
benefits
high-resolution
it
thus
imperative
represent
relevant
external
responses
across
entire
chain.
Hydrology and earth system sciences,
Год журнала:
2024,
Номер
28(2), С. 375 - 389
Опубликована: Янв. 31, 2024
Abstract.
Extreme
sub-hourly
precipitation,
typically
convective
in
nature,
is
capable
of
triggering
natural
disasters
such
as
floods
and
debris
flows.
A
key
component
climate
change
adaptation
resilience
quantifying
the
likelihood
that
extreme
precipitation
will
exceed
historical
levels
future
scenarios.
Despite
this,
current
approaches
to
estimating
return
are
deemed
insufficient.
The
reason
for
this
can
be
attributed
two
factors:
there
limited
availability
data
from
convection-permitting
models
(capable
simulating
adequately)
statistical
methods
we
use
extrapolate
do
not
capture
physics
governing
global
warming.
We
present
a
novel
physical-based
method
levels.
proposed
model,
named
TEmperature-dependent
Non-Asymptotic
model
eXtreme
(TENAX),
based
on
parsimonious
non-stationary
non-asymptotic
theoretical
framework
incorporates
temperature
covariate
physically
consistent
manner.
first
explain
theory
TENAX
model.
Using
several
stations
Switzerland
case
study,
demonstrate
model's
ability
reproduce
some
observed
properties
precipitation.
then
illustrate
how
utilized
project
changes
warmer
only
projections
temperatures
during
wet
days
foreseen
frequency.
conclude
by
discussing
uncertainties
associated
with
its
limitations,
advantages.
With
one
extremes
at
different
daily
scale
any
location
globally
where
observations
near-surface
air
available.
Abstract
This
paper
presents
the
methodology
for
construction
of
KNMI'23
national
climate
scenarios
Netherlands.
We
have
developed
six
scenarios,
that
cover
a
substantial
part
uncertainty
in
CMIP6
projections
future
change
region.
Different
sources
are
disentangled
as
much
possible,
partly
by
means
storyline
approach.
Uncertainty
emissions
is
covered
making
conditional
on
different
SSP
(SSP1‐2.6,
SSP2‐4.5,
and
SSP5‐8.5).
For
each
scenario
time
horizon
(2050,
2100,
2150),
we
determine
global
warming
level
based
median
constrained
estimates
sensitivity
from
IPCC
AR6.
The
remaining
model
regional
response
at
these
levels
two
storylines,
which
designed
with
focus
annual
seasonal
mean
precipitation
(a
dry‐trending
wet‐trending
variant
SSP).
choice
was
motivated
importance
water
management
to
society.
users
specific
interests
provide
how
account
impact
sensitivity.
Since
GCM
data
do
not
required
spatial
detail
modeling,
reconstruct
responses
resampling
internal
variability
GCM‐RCM
initial‐condition
ensemble.
resulting
form
detailed
plausible
climates
can
be
used
calculations
assessments
stakeholders,
will
inform
policy
sectors
Dutch
Abstract
High‐resolution
climate
change
projections
are
increasingly
necessary
to
inform
policy
and
adaptation
planning.
Downscaling
of
global
models
(GCMs)
is
required
simulate
the
at
spatial
scale
relevant
for
local
impacts.
Here,
we
dynamically
downscaled
15
CMIP6
GCMs
a
10
km
resolution
over
Australia
using
Conformal
Cubic
Atmospheric
model
(CCAM),
creating
largest
ensemble
high‐resolution
Australia.
We
compared
host
simulations
Australian
Gridded
Climate
Data
(AGCD)
observational
data
evaluated
performance
Kling‐Gupta
efficiency
Perkins
skill
score.
improved
seasonal
temperature
precipitation
(10%
43%
respectively),
annual
cycles
(6%
13%
respectively).
also
fraction
dry
days,
reducing
bias
too
many
low‐rain
days.
The
improvements
were
found
in
extremes,
with
enhancements
extreme
minimum
temperatures
all
seasons
varying
from
142%
201%,
52%
Austral
winter
47%
summer.
average
integrated
score
by
16%.
Temperature
biases
reduced
mountainous
coastal
areas.
CCAM
downscaling
outperformed
multiple
scales
regions—continental
Australia,
IPCC
regions
Queensland's
regions—with
added
value
ranging
9%
150%
higher
densely
populated
more
exposed
This
set
will
be
valuable
resource
understanding
future
changes
Journal of Glaciology,
Год журнала:
2023,
Номер
69(277), С. 1365 - 1378
Опубликована: Май 18, 2023
Abstract
Wet-snow
avalanches
are
triggered
by
the
infiltration
of
liquid
water
which
weakens
snowpack.
among
most
destructive
avalanches,
yet
their
release
mechanism
is
not
sufficiently
understood
for
a
process-based
prediction
model.
Therefore,
we
followed
data-driven
approach
and
developed
random
forest
model,
depending
on
slope
aspect,
to
predict
local
wet-snow
avalanche
activity
at
locations
124
automated
weather
stations
distributed
throughout
Swiss
Alps.
The
input
variables
were
snow
data
recorded
over
past
20
years.
target
variable
was
based
manual
observations
same
20-year
period.
To
filter
out
erroneous
reports,
defined
days
with
in
stringent
manner,
selecting
only
extreme
active
or
inactive
days,
reduced
size
dataset
but
increased
reliability
variable.
model
trained
computed
from
simulated
stratigraphy
38
$^\circ$
slopes
facing
4
cardinal
directions.
While
development
validation
done
nowcast
mode,
also
studied
performance
24-hour
forecast
mode
using
numerical
(NWP)
Overall,
good
both
(f1-score
around
0.8).
assess
beyond
definition
compared
predictions
entire
Alps,
raw
8
winters.
We
obtained
Spearman
correlation
coefficient
0.71.
Hence,
our
represents
step
toward
application
support
tools
operational
forecasting.
Ecology and Evolution,
Год журнала:
2024,
Номер
14(2)
Опубликована: Фев. 1, 2024
Global
warming
is
affecting
the
phenological
cycles
of
plants
and
animals,
altering
complex
synchronization
that
has
co-evolved
over
thousands
years
between
interacting
species
trophic
levels.
Here,
we
examined
how
warmer
winter
conditions
affect
timing
budburst
in
six
common
European
trees
hatching
a
generalist
leaf-feeding
insect,
spongy
moth
Climate Services,
Год журнала:
2023,
Номер
30, С. 100373 - 100373
Опубликована: Апрель 1, 2023
The
spatial
visualization
of
current
and
future
climate
conditions
is
one
key
component
for
assessing
related
impacts
risks
in
a
given
territory.
A
suitable
combination
statistical
methods
visualisation
techniques
allows
the
creation
outputs
that
support
interpretation
understanding
as
well
communication
complex
analysis
to
wider
target
audience.
present
paper
describes
adopted
approaches
portray
information
about
change
Germany
until
end
21st
century
meaningful
maps
with
aim
communicate
it
public
decision
makers.
In
particular,
conducted
analyses
focused
on
assessment
regions,
hotspots
analogues.
showing
resulting
patterns
1)
divide
country
seven
clusters,
2)
reveal
different
hotspot
areas
terms
indicators
middle
3)
provide
shifts
German
cities
analogue
regions
Europe.
Results
are
accompanied
recommendations
aids
supporting
correct
use
practical
applications
purposes.
final
map
products
from
these
published
frame
Climate
Impact
Risk
Assessment
2021
were
taken
up
by
national
media
outlets
(print
audio),
education
experts
stakeholders,
benefits
limitations
choices.
Climate Services,
Год журнала:
2024,
Номер
34, С. 100448 - 100448
Опубликована: Фев. 16, 2024
With
global
climate
change,
temperatures
in
Switzerland
are
projected
to
rise
the
coming
decades,
according
national
scenarios
CH2018.
Associated
with
mean
temperature
increase,
heatwaves
expected
become
longer,
more
frequent,
and
intense.
The
changing
will
affect
indoor
as
well
heating
cooling
needs.
In
building
design,
these
climatic
changes
have
be
planned
for
today
order
ensure
a
comfortable
future.
collaboration
practitioners,
reference
data
set
future
is
created
that
specifically
targets
designers
engineers.
consists
of
hourly
weather
one-year
length
based
on
Swiss
change
These
years
representative
two
time
periods
future:
one
around
2030
2060.
Climate
uncertainty
considered
by
using
emission
(RCP2.6
RCP8.5).
Reference
provided
not
only
typical
year
(called
Design
Year,
or
DRY)
but
also
an
above-average
warm
summer.
available
at
sites
45
measurement
stations
across
Switzerland,
including
four
inside
major
cities
take
urban
heat
island
effect
into
account.
generated
applied
model
provide
application
example.
results
point
out
needs
substantially
which
why
adaptation
design
vital.