Earth Systems and Environment,
Journal Year:
2022,
Volume and Issue:
7(1), P. 99 - 130
Published: Dec. 19, 2022
Extreme
temperature
and
precipitation
events
are
the
primary
triggers
of
hazards,
such
as
heat
waves,
droughts,
floods,
landslides,
with
localized
impacts.
In
this
sense,
finer
grids
Earth
System
models
(ESMs)
could
play
an
essential
role
in
better
estimating
extreme
climate
events.
The
performance
High
Resolution
Model
Intercomparison
Project
(HighResMIP)
is
evaluated
using
Expert
Team
on
Climate
Change
Detection
Indices
(ETCCDI)
over
1981-2014
period
future
changes
(2021-2050)
under
Shared
Socioeconomic
Pathway
SSP5-8.5,
ten
regions
Latin
America
Caribbean.
impact
increasing
horizontal
resolution
variability
a
regional
scale
first
compared
against
reference
gridded
datasets,
including
reanalysis,
satellite,
merging
products.
We
used
three
different
groups
based
model's
grid
(sg):
(i)
low
(0.8°
≤
sg
1.87°),
(ii)
intermediate
(0.5°
0.7°),
(iii)
high
(0.23°
≥
0.35°).
Our
analysis
indicates
that
there
was
no
clear
evidence
to
support
posit
improves
model
performance.
ECMWF-IFS
family
appears
be
plausible
choice
represent
extremes,
followed
by
ensemble
mean
HighResMIP
their
resolution.
For
climate,
projections
indicate
consensus
extremes
increase
across
most
regions.
Despite
uncertainties
presented
study,
have
been
will
continue
important
tool
for
assessing
risk
face
events.The
online
version
contains
supplementary
material
available
at
10.1007/s41748-022-00337-7.
Natural Hazards,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Aug. 20, 2024
Extreme
precipitation
events
usually
lead
to
economic,
agricultural,
and
social
losses
globally.
The
bias
of
different
global
circulation
models
(GCMs)
is
a
major
challenge
in
the
projection
extreme
climate
regions.
Revealing
Coupled
Model
Intercomparison
Project
(CMIP)
GCMs
helpful
for
providing
reference
predicting
understanding
performance
CMIP
Phase
6
(CMIP6)
GCMs.
Eight
indices
were
used
describe
based
on
daily
data
retrieved
from
Global
Precipitation
Climatology
(GPCP)
19
CMIP6
Six
evaluation
metrics
adopted
assess
ability
CMIP6-determined
precipitation.
results
showed
that
half
overestimated
Sahara,
Arabian
Peninsula,
Central
Asia,
underestimated
northern
North
America
Asia.
In
general,
multimodel
ensemble
(MME)
achieved
greater
simulating
than
did
individual
considered
was
relatively
small
tropical
regions,
especially
equatorial
future,
will
increase,
under
high
emission
scenarios
(i.e.,
SSP5-8.5).
notably
increase
cold
polar
Our
could
improve
simulations,
they
are
very
important
reliable
future
predictions.
Climate,
Journal Year:
2024,
Volume and Issue:
12(3), P. 43 - 43
Published: March 13, 2024
Various
indices
of
climate
variability
and
extremes
are
extensively
employed
to
characterize
potential
effects
change.
Particularly,
the
semiarid
region
Brazil
is
influenced
by
adverse
these
changes,
especially
in
terms
precipitation.
In
this
context,
main
objective
present
study
was
regional
trends
extreme
precipitation
(SAB),
using
daily
data
from
IMERG
V06
product,
spanning
period
1
January
2001
31
December
2020.
Twelve
were
considered,
which
estimated
annually,
their
spatial
temporal
subsequently
analyzed
nonparametric
Mann–Kendall
test
Sen’s
slope.
The
analysis
revealed
that
peripheral
areas
SAB,
northwest
south
regions,
exhibited
higher
intensity
frequency
events
compared
central
portion
area.
However,
a
negative
trend
event
noted
north,
while
positive
identified
south.
showed
predominance
across
most
region,
with
an
increase
consecutive
dry
days
particularly
throughout
western
SAB.
average
total
index
above
1000
mm
north
whereas
averages
predominantly
below
600
mm,
rainfall
values
ranging
between
6
10
mm/day.
Over
span
20
years,
underwent
40
certain
localities.
A
observed
indices,
indicating
reduction
future
decades,
variations
some
indices.
years
towards
end
likely
contributed
majority
Such
directly
impact
weather
important
for
highlighting
considering
impacts
changes
Brazil.
Based
on
obtained
results,
we
advocate
implementation
public
policies
address
challenges,
such
as
incorporating
adaptations
water
resource
management,
sustainable
agricultural
practices,
planning
urban
rural
areas.
International Journal of Climatology,
Journal Year:
2024,
Volume and Issue:
44(12), P. 4495 - 4514
Published: Aug. 15, 2024
Abstract
Climate
change
is
expected
to
cause
important
changes
in
precipitation
patterns
Iran
until
the
end
of
21st
century.
This
study
aims
at
evaluating
projections
climate
over
by
using
five
model
outputs
(including
ACCESS‐ESM1‐5,
BCC‐CSM2‐MR,
CanESM5,
CMCC‐ESM2
and
MRI‐ESM2‐0)
Coupled
Model
Intercomparison
Project
phase
6
(CMIP6),
performing
bias‐correction
a
novel
combination
quantile
mapping
(QM)
random
forest
(RF)
between
years
2015
2100
under
three
shared
socioeconomics
pathways
(SSP2‐4.5,
SSP3‐7.0
SSP5‐8.5).
First,
was
performed
on
ERA5‐Land
reanalysis
data
as
reference
period
(1990–2020)
QM
method,
then
corrected
considered
measured
data.
Based
historical
simulations
(1990–2014),
future
(2015–2100)
were
also
bias‐corrected
utilizing
method.
Next,
accuracy
method
validated
comparing
with
for
overlapping
2020.
comparison
revealed
persistent
biases;
hence,
QM‐RF
applied
rectify
result,
highest
RMSE
both
SSP2‐4.5
amounting
331.74
201.84
mm·year
−1
,
respectively.
Particularly,
exclusive
use
displayed
substantial
errors
projecting
annual
based
SSP5‐8.5,
notably
case
ACCESS‐ESM1‐5
(RMSE
=
431.39
),
while
reduced
after
(197.75
).
Obviously,
significant
enhancement
results
observed
upon
implementing
139.30
)
151.43
showcasing
approximately
reduction
values
192.43
50.41
Although
each
output
evaluated
individually,
multi‐model
ensemble
(MME)
created
project
pattern
Iran.
By
considering
that
lower
correcting
outputs,
we
used
technique
create
MME.
SSP2‐4.5,
MME
highlight
imminent
reductions
(>10%)
across
large
regions
Iran,
conversely
increases
ranging
from
10%
20%
southern
areas
SSP3‐7.0.
Moreover,
projected
dramatic
declines
especially
impacting
central,
eastern,
northwest
Notably,
most
pronounced
possibly
decline
are
arid
(central
plateau)
eastern
SSP5‐8.5.
Discover Environment,
Journal Year:
2023,
Volume and Issue:
1(1)
Published: Aug. 31, 2023
Abstract
The
Accuracy
of
model
simulations
is
critical
for
climate
change
and
its
socio-economic
impact.
This
study
evaluated23
Global
models
participating
in
the
Coupled
Model
Intercomparison
Project
phase
6
(CMIP6).
main
objective
was
to
identify
top
10
best
performance
capturing
patterns
rainfall
1981–2014
period
over
Intergovernmental
Authority
on
Development
(IGAD)
region
Eastern
Africa.
total
rainfall,
annual
cycle,
continuous,
categorical
Volumatic
statistical
metrics,
scatter
plots,
Cumulative
Distribution
Function
(CDF),
colored
code
portrait
were
used
assess
.
Results
indicate
that
most
CMIP6
generally
capture
characteristics
observed
climatology
pattern
bimodal
unimodal
regimes.
majority
Arid
Semi-Arid
Lands
(ASALs)
Kenya,
Somalia,
Ethiopia,
Sudan
scored
lowest
skills,
highest
bias,
over-estimated
lower
skills
June–September
(JJAS)
compared
March–May
(MAM)
October-December
(OND).
Quantitatively,
a
high
percent
bias
exceeding
80%
ASALs,
correlation
coefficient
ranging
between
0.6
0.7
across
Ethiopia’s
highlands,
5–40
as
Root
Mean
Squared
Error
region.
In
addition,
21
out
23
parts
ACCESS-ESM1-5
MIROC6
are
opposed
CNRM-CM6-1HR
under-estimated
RMSE
values.
regional
sub-national
analysis
showed
it
inconclusive
select
best-performed
based
individual
metrics
analysis.
Out
models,
INM-CM5-0,
HadGEM3-GC31-MM,
CMCC-CM2-HR4,
IPSL-CM6A-LR,
KACE-1-0-G,
EC-Earth3,
NorESM2-MM,
GFDL-ESM4,
TaiESM1,
KIOST-ESM
IGAD
These
findings
highlight
importance
selecting
mapping
present
future
hotspots
extreme
events
