Climate Services,
Год журнала:
2024,
Номер
34, С. 100458 - 100458
Опубликована: Апрель 1, 2024
Soy
is
the
most
important
agricultural
commodity
in
Argentina,
with
relevance
public
revenues
and
international
reserves
accumulation.
However,
a
proper
impact
evaluation
of
future
losses
context
climate
change
has
not
yet
been
developed.
Therefore,
aim
this
paper
to
provide
estimates
for
macroeconomic
adaptation
policies.
By
means
multiple
partial
regression,
relation
between
total
country
soybean
yields
different
combinations
28
territorial
weather
stations
was
estimated
period
2001–2021.
With
optimal
model,
output
projected
using
rainfall
temperature
data
from
150
models
4
scenarios
Copernicus
database
during
2022–2042.
Results
show
strong
statistical
relationship
levels
maximum
yields,
explaining
on
average
91.2%
yield
variation.
The
projections
showed
that
general
four
at
3.8%
higher
than
current
levels,
30%
lower
70%
values
production.
Variability
analysis
an
increase
frequency
intensity
extreme
negative
events
aggregate
past:
relative
loss
3.6%
production
(USD
million
$13,000)
compared
2.3%
historical
$7,492).
main
application
estimation
macro-fiscal
long-term
budgetary
fiscal
planning,
parsimonious
approach
open-access
allows
permanent
actualization.
Earth Systems and Environment,
Год журнала:
2022,
Номер
7(1), С. 99 - 130
Опубликована: Дек. 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.
npj Climate and Atmospheric Science,
Год журнала:
2023,
Номер
6(1)
Опубликована: Июль 20, 2023
Abstract
Runoff
from
glacierised
Andean
river
basins
is
essential
for
sustaining
the
livelihoods
of
millions
people.
By
running
a
high-resolution
climate
model
over
two
most
regions
Peru
we
unravel
past
climatic
trends
in
precipitation
and
temperature.
Future
changes
are
determined
an
ensemble
statistically
downscaled
global
models.
Projections
under
high
emissions
scenario
suggest
substantial
increases
temperature
3.6
°C
4.1
regions,
accompanied
by
12%
increase
late
21st
century.
Crucially,
significant
extremes
(around
75%
total
on
very
wet
days)
occur
together
with
intensification
meteorological
droughts
caused
increased
evapotranspiration.
Despite
higher
precipitation,
glacier
mass
losses
enhanced
both
highest
emission
stabilization
scenarios.
Our
modelling
provides
new
projection
combined
contrasting
risks,
region
already
experiencing
rapid
environmental
change.
Water Resources Research,
Год журнала:
2023,
Номер
59(8)
Опубликована: Авг. 1, 2023
Abstract
Investigating
modifications
in
the
hydrological
cycle
is
essential
to
understand
impacts
of
climate
change
on
ecosystems.
This
study
assesses
velocity
water
over
land
at
global
scale,
whereas
previous
studies
have
mostly
focused
changes
atmospheric
cycle.
The
acceleration
quantified
by
a
decrease
average
residence
time
(RT)
first
meter
soil.
soil
RT
shown
be
sensitive
texture
and
seasonality
hydroclimatic
variables.
Despite
substantial
local
variability,
most
RTs
are
range
50–300
days.
mean
declined
rate
−2.30
−0.36
days
decade
−1
(−1.6
1.0
nine
models)
from
2001
2020
as
measured
reanalysis
CMIP6
simulations
for
historical
scenario,
respectively,
which
corresponds
−6.8
−1.1
°C
when
expressed
per
degree
warming
land.
projected
continue
−1.35
(−3.4
0.0
or
−2.2
during
period
2015–2100
under
extreme
emission
scenario:
SSP
585.
Changes
precipitation
dominantly
drive
terrestrial
compared
evapotranspiration.
Rising
temperatures
increasing
carbon
dioxide
opposite
effects
speed
with
compensatory
roles
keeping
relatively
unchanged
absence
PR
trends.
Climate Services,
Год журнала:
2024,
Номер
34, С. 100458 - 100458
Опубликована: Апрель 1, 2024
Soy
is
the
most
important
agricultural
commodity
in
Argentina,
with
relevance
public
revenues
and
international
reserves
accumulation.
However,
a
proper
impact
evaluation
of
future
losses
context
climate
change
has
not
yet
been
developed.
Therefore,
aim
this
paper
to
provide
estimates
for
macroeconomic
adaptation
policies.
By
means
multiple
partial
regression,
relation
between
total
country
soybean
yields
different
combinations
28
territorial
weather
stations
was
estimated
period
2001–2021.
With
optimal
model,
output
projected
using
rainfall
temperature
data
from
150
models
4
scenarios
Copernicus
database
during
2022–2042.
Results
show
strong
statistical
relationship
levels
maximum
yields,
explaining
on
average
91.2%
yield
variation.
The
projections
showed
that
general
four
at
3.8%
higher
than
current
levels,
30%
lower
70%
values
production.
Variability
analysis
an
increase
frequency
intensity
extreme
negative
events
aggregate
past:
relative
loss
3.6%
production
(USD
million
$13,000)
compared
2.3%
historical
$7,492).
main
application
estimation
macro-fiscal
long-term
budgetary
fiscal
planning,
parsimonious
approach
open-access
allows
permanent
actualization.
