Two sets of bias-corrected regional UK Climate Projections 2018 (UKCP18) of temperature, precipitation and potential evapotranspiration for Great Britain
Earth system science data,
Journal Year:
2025,
Volume and Issue:
17(5), P. 2113 - 2133
Published: May 20, 2025
Abstract.
The
United
Kingdom
Climate
Projections
2018
(UKCP18)
regional
climate
model
(RCM)
12
km
perturbed
physics
ensemble
(UKCP18-RCM-PPE)
is
one
of
the
three
strands
latest
set
UK
national
projections
produced
by
Met
Office.
It
has
been
widely
adopted
in
impact
assessment.
In
this
study,
we
report
biases
raw
UKCP18-RCM
simulations
that
are
significant
and
likely
to
deteriorate
assessments
if
they
not
adjusted.
Two
methods
were
used
bias-correct
UKCP18-RCM:
non-parametric
quantile
mapping
using
empirical
quantiles
a
variant
developed
for
third
phase
Inter-Sectoral
Impact
Model
Intercomparison
Project
(ISIMIP)
designed
preserve
change
signal.
Specifically,
daily
temperature
precipitation
1981
2080
adjusted
members.
Potential
evapotranspiration
was
also
estimated
over
same
period
Penman–Monteith
formulation
then
bias-corrected
latter
method.
Both
successfully
corrected
range
temperature,
precipitation,
potential
metrics
reduced
multi-day
lesser
degree.
An
exploratory
analysis
projected
future
changes
confirms
expectation
wetter,
warmer
winters
hotter,
drier
summers
shows
uneven
different
parts
distributions
both
precipitation.
bias-correction
preserved
signal
almost
equally
well,
as
well
spread
among
changes.
factor
method
benchmark
show
it
fails
capture
variables,
making
inadequate
most
assessments.
By
comparing
differences
between
two
within
members,
uncertainty
stemming
from
parameterization
far
outweighs
introduced
selecting
these
methods.
We
conclude
providing
guidance
on
use
datasets.
datasets
bias-adjusted
with
ISIMIP3BA
publicly
available
following
repositories:
https://doi.org/10.5281/zenodo.6337381
(Reyniers
et
al.,
2022a)
https://doi.org/10.5281/zenodo.6320707
2022b).
datasets,
method,
at
https://doi.org/10.5281/zenodo.8223024
(Zha
2023).
Language: Английский
Correcting biases in regional climate model boundary variables for improved simulation of high-impact compound events
iScience,
Journal Year:
2023,
Volume and Issue:
26(9), P. 107696 - 107696
Published: Aug. 21, 2023
Although
climate
models
have
been
used
to
assess
compound
events,
the
combination
of
multiple
hazards
or
drivers
poses
uncertainties
because
systemic
biases
present.
Here,
we
investigate
multivariate
bias
correction
for
correcting
in
boundaries
that
form
inputs
regional
(RCMs).
This
improves
representation
physical
relationships
among
variables,
essential
accurate
characterization
events.
We
address
four
types
events
result
from
eight
different
hazards.
The
results
show
while
RCM
simulations
presented
here
exhibit
similar
performance
some
event
types,
broadly
compared
no
univariate
correction,
particularly
coincident
high
temperature
and
precipitation.
with
uncorrected
tends
produce
a
negative
return
period
these
suggesting
tendency
over-simulate
respect
observed
Language: Английский
An improved statistical bias correction method for Global Climate Model (GCM) precipitation projection: A case study on the CMCC-CM2-SR5 model projection in China’s Huaihe River Basin
Journal of Hydrology Regional Studies,
Journal Year:
2024,
Volume and Issue:
57, P. 102146 - 102146
Published: Dec. 21, 2024
Language: Английский