Temporally
compounding
atmospheric
river
(AR)
events
cause
severe
flooding
and
damage
in
California.
However,
the
contribution
of
temporal
to
AR-induced
loss
has
yet
be
systematically
quantified.
We
show
that
strongest
ARs
are
more
likely
part
sequences,
which
periods
elevated
hydrologic
hazard
associated
with
temporally
clustered
ARs.
Sequences
increase
likelihood
flood-related
impacts
by
8.3%
on
AR
days
5.4%
non-AR
days,
across
two
independent
datasets,
we
find
within
sequences
have
over
three
times
higher
expected
losses
compared
outside
sequences.
Expected
also
when
preceding
is
intensity,
time
since
shorter,
an
second
or
later
event
a
sequence.
conclude
critical
source
information
for
predicting
AR's
potential
consequences.
Royal Society Open Science,
Год журнала:
2023,
Номер
10(6)
Опубликована: Июнь 1, 2023
Animals
use
climate-related
environmental
cues
to
fine-tune
breeding
timing
and
investment
match
peak
food
availability.
In
birds,
spring
temperature
is
a
commonly
documented
cue
used
initiate
breeding,
but
with
global
climate
change,
organisms
are
experiencing
both
directional
changes
in
ambient
temperatures
extreme
year-to-year
precipitation
fluctuations.
Montane
environments
exhibit
complex
patterns
where
change
along
elevational
gradients,
exacerbated
annual
variation
has
resulted
swings
between
heavy
snow
drought.
We
10
years
of
data
investigate
how
climatic
conditions
associated
differences
phenology
reproductive
performance
resident
mountain
chickadees
(Poecile
gambeli)
at
two
elevations
the
northern
Sierra
Nevada
mountains,
USA.
Variation
was
not
across
our
system.
Greater
accumulation
later
initiation
high,
low,
elevation.
Brood
size
reduced
under
drought,
only
low
Our
suggest
relationships
avian
reproduction
point
autumn
as
important
for
performance,
likely
via
its
effect
on
abundance
invertebrates.
Geoscientific model development,
Год журнала:
2024,
Номер
17(9), С. 3687 - 3731
Опубликована: Май 8, 2024
Abstract.
The
spatial
heterogeneity
related
to
complex
topography
in
California
demands
high-resolution
(<
5
km)
modeling,
but
global
convection-permitting
climate
models
are
computationally
too
expensive
run
multi-decadal
simulations.
We
developed
a
3.25
km
modeling
framework
by
leveraging
regional
mesh
refinement
(CARRM)
using
the
U.S.
Department
of
Energy
(DOE)'s
Simple
Cloud-Resolving
E3SM
Atmosphere
Model
(SCREAM)
version
0.
Four
5-year
time
periods
(2015–2020,
2029–2034,
2044–2049,
and
2094–2099)
were
simulated
nudging
CARRM
outside
1°
coupled
simulation
E3SMv1
under
Shared
Socioeconomic
Pathways
(SSP)5-8.5
future
scenario.
grid
spacing
adds
considerable
value
prediction
changes,
including
more
realistic
high
temperatures
Central
Valley
much
improved
distributions
precipitation
snowpack
Sierra
Nevada
coastal
stratocumulus.
Under
SSP5-8.5
scenario,
predicts
widespread
warming
6–10
°C
over
most
California,
38
%
increase
statewide
average
30
d
winter–spring
precipitation,
near-complete
loss
alpine
snowpack,
sharp
reduction
shortwave
cloud
radiative
forcing
associated
with
marine
stratocumulus
end
21st
century.
note
climatological
wet
bias
for
discuss
possible
reasons.
conclude
that
SCREAM
RRM
is
technically
feasible
scientifically
valid
tool
simulations
regions
interest,
providing
an
excellent
bridge
Water Resources Research,
Год журнала:
2023,
Номер
59(8)
Опубликована: Авг. 1, 2023
Abstract
The
High‐Resolution
Model
Intercomparison
Project
(HighResMIP)
experiments
from
the
Coupled
Phase
6
represent
a
broad
effort
to
improve
resolution,
and
performance
of
climate
models.
HighResMIP
suite
provides
high
spatial
resolution
(i.e.,
25‐
50‐km)
forcings
that
have
been
shown
representation
processes.
However,
little
is
known
about
their
suitability
for
hydrologic
applications.
We
use
outputs
simulate
annual
maximum
discharge
with
Hillslope‐Link
(HLM)
at
∼1,000
river
communities
across
Iowa.
First,
we
assess
whether
runoff
models
can
be
directly
routed
through
network
model
in
HLM
estimate
discharge.
Runoff‐based
simulations
capture
empirical
distribution
flood
peaks
five
10
models/members
assessed.
Next,
force
precipitation,
temperature,
potential
evapotranspiration
peaks,
finding
all
produce
distributions
similar
our
reference.
significant
biases
exist
model/member
as
correct
response
being
generated
wrong
reason.
To
community‐level
assessment,
nine
statistical
approaches
bias‐correct
downscale
precipitation
4‐km
resolution.
bias‐correction
downscaling
performs
well
models/members.
Furthermore,
do
not
find
changes
magnitude
peak
projections
Iowa
based
on
forced
outputs,
or
runoff,
while
there
are
indications
variability
projected
increase
state.
Temporally
compounding
atmospheric
river
(AR)
events
cause
severe
flooding
and
damage
in
California.
However,
the
contribution
of
temporal
to
AR-induced
loss
has
yet
be
systematically
quantified.
We
show
that
strongest
ARs
are
more
likely
part
sequences,
which
periods
elevated
hydrologic
hazard
associated
with
temporally
clustered
ARs.
Sequences
increase
likelihood
flood-related
impacts
by
8.3%
on
AR
days
5.4%
non-AR
days,
across
two
independent
datasets,
we
find
within
sequences
have
over
three
times
higher
expected
losses
compared
outside
sequences.
Expected
also
when
preceding
is
intensity,
time
since
shorter,
an
second
or
later
event
a
sequence.
conclude
critical
source
information
for
predicting
AR's
potential
consequences.
