Geoscientific model development,
Journal Year:
2025,
Volume and Issue:
18(2), P. 211 - 237
Published: Jan. 20, 2025
Abstract.
Decadal-scale
oceanographic,
environmental,
and
ecological
changes
have
been
reported
in
the
Salish
Sea,
an
ecologically
productive
inland
sea
northeast
Pacific
that
supports
economies
cultures
of
millions
people.
However,
there
are
substantial
data
gaps
related
to
physical
water
properties
make
it
difficult
evaluate
trends
pathways
effects
between
ocean
productivity
marine
ecosystems.
With
aim
addressing
these
gaps,
we
present
Hindcast
Sea
(HOTSSea)
v1,
a
3D
oceanographic
model
developed
using
Nucleus
for
European
Modelling
Ocean
(NEMO)
engine,
with
temporal
coverage
from
1980–2018.
We
used
experimental
approach
incrementally
assess
sensitivity
atmospheric
reanalysis
products
boundary
forcings
horizontal
discretisation
grid
(∼
1.5
km).
Biases
inherited
were
quantified,
simple
temperature
bias
correction
factor
applied
at
one
was
found
substantially
improve
skill.
Evaluation
salinity
indicates
performance
is
best
Strait
Georgia.
Relatively
large
biases
occur
near-surface
waters,
especially
subdomains
topography
narrower
than
grid's
resolution.
demonstrated
simulates
anomalies
secular
warming
trend
over
entire
column
general
agreement
observations.
HOTSSea
v1
provided
first
look
spatially
temporally
heterogenous
throughout
northern
central
part
domain
where
observations
sparse.
Overall,
despite
relatively
coarse
discretisation,
performs
well
representing
spatial–temporal
scales
needed
support
research
decadal-scale
climate
on
ecosystems,
fish,
fisheries.
conclude
by
underscoring
need
further
extend
hindcast
capture
regime
shift
occurred
1970s.
Abstract
Approximately
10
years
ago,
convection‐permitting
regional
climate
models
(CPRCMs)
emerged
as
a
promising
computationally
affordable
tool
to
produce
fine
resolution
(1–4
km)
decadal‐long
simulations
with
explicitly
resolved
deep
convection.
This
explicit
representation
is
expected
reduce
projection
uncertainty
related
convection
parameterizations
found
in
most
models.
A
recent
surge
CPRCM
decadal
over
larger
domains,
sometimes
covering
continents,
has
led
important
insights
into
advantages
and
limitations.
Furthermore,
new
observational
gridded
datasets
spatial
temporal
(~1
km;
~1
h)
resolutions
have
leveraged
additional
knowledge
through
evaluations
of
the
added
value
CPRCMs.
With
an
improved
coordination
frame
ongoing
international
initiatives,
production
ensembles
provide
more
robust
projections
better
identification
their
associated
uncertainties.
review
paper
presents
overview
methodology
latest
research
on
current
future
climates.
Impact
studies
that
are
already
taking
advantage
these
highlighted.
ends
by
proposing
next
steps
could
be
accomplished
continue
exploiting
full
potential
article
categorized
under:
Climate
Models
Modeling
>
Earth
System
Scientific Data,
Journal Year:
2021,
Volume and Issue:
8(1)
Published: Nov. 4, 2021
Dynamical
downscaling
is
an
important
approach
to
obtaining
fine-scale
weather
and
climate
information.
However,
dynamical
simulations
are
often
degraded
by
biases
in
the
large-scale
forcing
itself.
We
constructed
a
bias-corrected
global
dataset
based
on
18
models
from
Coupled
Model
Intercomparison
Project
Phase
6
(CMIP6)
European
Centre
for
Medium-Range
Weather
Forecasts
Reanalysis
5
(ERA5)
dataset.
The
data
have
ERA5-based
mean
interannual
variance,
but
with
non-linear
trend
ensemble
of
CMIP6
models.
spans
historical
time
period
1979–2014
future
scenarios
(SSP245
SSP585)
2015–2100
horizontal
grid
spacing
(1.25°
×
1.25°)
at
six-hourly
intervals.
Our
evaluation
suggests
that
better
quality
than
individual
terms
climatological
mean,
variance
extreme
events.
This
will
be
useful
projections
Earth's
climate,
atmospheric
environment,
hydrology,
agriculture,
wind
power,
etc.
Machine-accessible
metadata
file
describing
reported
data:
https://doi.org/10.6084/m9.figshare.16802326
Journal of Hydrologic Engineering,
Journal Year:
2021,
Volume and Issue:
26(10)
Published: Aug. 3, 2021
One
of
the
most
important
impacts
a
future
warmer
climate
is
projected
increase
in
frequency
and
intensity
extreme
rainfall
events.
This
increasing
trend
seen
both
observational
record
model
projections.
However,
thorough
review
recent
scientific
literature
paints
complex
picture
which
intensification
extremes
depends
on
multitude
factors.
While
some
indices
follow
Clausius-Clapeyron
relationship
scaling
an
∼7%
per
1°C
warming,
there
substantial
evidence
that
this
frequency,
with
longer
return
period
events
seeing
larger
increases,
leading
to
super
cases.
The
now
well
documented
at
daily
scale
but
less
clear
subdaily
scale.
In
years,
simulations
finer
spatial
temporal
resolution,
including
convection-permitting
models,
have
provided
more
reliable
projections
rainfall.
Recent
analyses
indicate
may
also
as
function
duration,
such
shorter-duration,
will
likely
see
largest
increases
climate.
has
broad
implications
design
use
intensity–duration–frequency
(IDF)
curves,
for
overall
magnitude
steepening
can
be
predicted.
paper
presents
overview
measures
been
adopted
by
various
governing
bodies
adapt
IDF
curves
changing
Current
vary
from
multiplying
historical
simple
constant
percentage
modulating
correction
factors
based
periods
them
temperature
increases.
All
these
current
fail
recognize
possible
and,
perhaps
importantly,
toward
shorter-duration
significantly
impact
stormwater
runoff
cities
small
rural
catchments.
discusses
remaining
gaps
offers
technical
recommendations
practitioners
how
improve
resilience.
Geoscientific model development,
Journal Year:
2023,
Volume and Issue:
16(3), P. 907 - 926
Published: Feb. 6, 2023
Abstract.
The
term
“pseudo-global
warming”
(PGW)
refers
to
a
simulation
strategy
in
regional
climate
modeling.
consists
of
directly
imposing
large-scale
changes
the
system
on
control
(usually
representing
current
conditions)
by
modifying
boundary
conditions.
This
differs
from
traditional
dynamic
downscaling
technique
where
output
global
model
(GCM)
is
used
drive
models
(RCMs).
PGW
are
usually
derived
transient
simulation.
approach
offers
several
benefits,
such
as
lowering
computational
requirements,
flexibility
design,
and
avoiding
biases
models.
However,
implementing
non-trivial,
care
must
be
taken
not
deteriorate
physics
when
To
simplify
preparation
simulations,
we
present
detailed
description
methodology
provide
companion
software
PGW4ERA5
facilitating
simulations.
In
describing
methodology,
particular
attention
devoted
adjustment
pressure
geopotential
fields.
Such
an
required
ensuring
consistency
between
thermodynamical
(temperature
humidity)
one
hand
dynamical
other
hand.
It
demonstrated
that
this
important
extratropics
highly
essential
tropical
subtropical
regions.
We
show
projections
simulations
prepared
using
presented
closely
comparable
for
most
climatological
variables.
Water,
Journal Year:
2022,
Volume and Issue:
14(10), P. 1590 - 1590
Published: May 16, 2022
This
paper
proposes
a
method
to
infer
the
future
change
in
wind-wave
climate
using
reanalysis
wind
corrected
statistically
match
data
from
regional
model
(RCM).
The
is
applied
sea
surface
speed
of
ERA5
European
Centre
for
Medium-Range
Weather
Forecasts.
correction
determined
quantile
mapping
between
and
RCM
at
any
given
point
geographical
space.
issues
that
need
be
addressed
better
understand
apply
are
discussed.
Corrected
fields
eventually
used
force
spectral
wave
numerical
simulate
significant
height.
strategy
implemented
over
Adriatic
Sea
(a
semi-enclosed
basin
Mediterranean
Sea)
includes
present-day
period
(1981–2010)
near-future
(2021–2050)
under
two
IPCC
RCP4.5
RCP8.5
concentration
scenarios.
Evaluation
against
observations
waves
gives
confidence
reliability
proposed
approach.
Results
confirm
evolution
toward
an
overall
decrease
storm
severity
basin,
especially
its
northern
area.
It
expected
methodology
may
other
reanalyses,
RCMs
(including
multi-model
ensembles),
or
seas
with
similar
characteristics.
npj Climate and Atmospheric Science,
Journal Year:
2024,
Volume and Issue:
7(1)
Published: June 13, 2024
Abstract
As
our
planet
is
entering
into
the
“global
boiling”
era,
understanding
regional
climate
change
becomes
imperative.
Effective
downscaling
methods
that
provide
localized
insights
are
crucial
for
this
target.
Traditional
approaches,
including
computationally-demanding
dynamical
models
or
statistical
frameworks,
often
susceptible
to
influence
of
uncertainty.
Here,
we
address
these
limitations
by
introducing
a
diffusion
probabilistic
model
(DPDM)
meteorological
field.
This
can
efficiently
transform
data
from
1°
0.1°
resolution.
Compared
with
deterministic
schemes,
it
not
only
has
more
accurate
local
details,
but
also
generate
large
number
ensemble
members
based
on
probability
distribution
sampling
evaluate
uncertainty
downscaling.
Additionally,
apply
180-year
dataset
monthly
surface
variables
in
East
Asia,
offering
detailed
perspective
scale
over
past
centuries.
Weather and Climate Extremes,
Journal Year:
2021,
Volume and Issue:
32, P. 100328 - 100328
Published: May 7, 2021
The
Loess
Plateau
in
China
is
one
of
the
most
erosive
regions
world,
especially
under
warming
climate
conditions,
which
are
aggravating
evapotranspiration
and
water
scarcity.
Thus,
there
a
need
to
better
understand
historical
future
change
patterns
Plateau,
global
models
(GCMs)
key
tool
achieve
this.
Because
mismatch
spatial
resolution
between
GCMs
requirements
regional
applications,
Statistical
Downscaling
Model
(SDSM)
combination
with
two
bias-correction
methods
was
employed
for
first
time
downscale
modeled
values
from
Phase
5
Coupled
Intercomparison
Project
daily
maximum
temperature
(TMAX),
mean
(TMEAN),
minimum
(TMIN)
over
Plateau.
After
evaluation
model
capability,
bias-corrected
downscaled
temperatures
forced
by
GCM
outputs
period
2010–2099
were
then
projected.
results
show
that
SDSM
cumulative
density
function
matching
technique
produced
more
accurate
estimates
than
integration
delta
correction,
reduced
root
square
errors
(and
associated
standard
deviations)
59.2%
(88.6%),
45.3%
(78.8%),
48.8%
(43.4%)
TMAX,
TMEAN,
TMIN,
respectively.
projected
will
increase
entire
plateau
relative
1961–1990
period,
greatest
changes
northern
eastern
regions.
Another
finding
can
reduce
uncertainties
projection
obtain
reliable
projections.
Energy Conversion and Management X,
Journal Year:
2024,
Volume and Issue:
23, P. 100660 - 100660
Published: July 1, 2024
Wind
energy
plays
a
pivotal
role
in
the
ongoing
effort
to
reduce
carbon
emissions
sector.
With
increasing
evidence
of
climate
change,
there
is
growing
concern
regarding
planning
and
operation
wind
resources.
Accurate
forecasts
are
essential
understand
frequency
distribution
speed
data
given
area
and,
consequently,
estimate
production.
This
paper
aims
analyze
resources
under
assess
their
potential,
create
zoning
maps
for
production
island
Ireland.
For
this
objective,
from
31
general
circulation
models
(GCMs)
two
change
scenarios
were
utilized
both
hindcast
forecast
periods
1981–2010
2021–2050,
respectively.
The
GCM
outputs
first
bias-corrected
then
post-processed
using
various
(non–)parametric
statistical
distributions
3
Copula
families.
results
indicate
an
expected
decrease
average
region
up
∼
21
%
by
2050,
contingent
on
consideration
target
point.
Ultimately,
study
concludes
presenting
power
density
specifically
region,
offering
valuable
insights
sustainable
planning.