Climate,
Год журнала:
2023,
Номер
11(2), С. 46 - 46
Опубликована: Фев. 13, 2023
Weather
and
climate
extremes
such
as
heat
waves,
droughts
floods
are
projected
to
become
more
frequent
intense
in
several
regions.
There
is
compelling
evidence
indicating
that
changes
its
over
time
influence
the
living
conditions
of
society
surrounding
environment
across
globe.
This
study
applies
max-stable
models
capture
spatio–temporal
with
dependence.
The
objective
was
analyse
risk
drought
caused
by
extremely
high
temperatures
deficient
rainfall.
Hopkin’s
statistic
used
assess
clustering
tendency
before
using
agglomerative
method
hierarchical
cluster
area
into
n=3
temperature
clusters
precipitation
clusters.
For
data,
values
were
0.7317
0.8446,
respectively,
which
shows
both
significantly
clusterable.
Various
process
then
fitted
each
variable,
Schlather
model
covariance
functions
found
be
a
good
fit
on
datasets
compared
Smith
Gaussian
function.
modelling
approach
presented
this
paper
could
useful
hydrologists,
meteorologists
climatologists,
including
decision-makers
agricultural
sector,
enhancing
their
understanding
behaviour
low
these
compound
also
assist
assessing
impact
change.
It
can
seen
from
size,
topography
location
(cluster/region),
provides
important
information
about
strength
extremal
Environmental Research Communications,
Год журнала:
2024,
Номер
6(5), С. 055004 - 055004
Опубликована: Апрель 24, 2024
Abstract
The
prolonged
drought
resulting
from
global
warming
is
considered
an
important
factor
affecting
West
Asia’s
socioeconomic
growth,
with
a
significant
impact
on
the
dynamic
forecasting
of
water
supply
and
forest
ecosystems.
In
such
scenario,
understanding
historical
long-term
changes
crucial
for
accurately
regional
shifts
in
Hindukush
region.
this
study,
517-year
(1506–2022
C.E.)
long
tree-ring
width
chronology
Himalayan
Cedar
(
Cedrus
deodara
D.
Don)
eastern
has
been
developed.
July-September
Standardized
Precipitation-Evapotranspiration
Index
(SPEI)
revealed
positive
relationship
r
=
0.633,
p
<
0.001)
tree
which
leads
to
SPEI
reconstruction
AD
1626
Hindu
Kush
Our
model
explained
40.1%
climate
variance
during
instrumental
period
C.E.
1965
2018.
Fourteen
wet
periods
(≥
3
years)
were
observed
before
period,
specifically
1629–1635,
1638–1658,
1666–1674,
1680–1701,
1715–1724,
1770–1776,
1794–1797,
1802–1810,
1822–1846,
1850–1857,
1872–1881,
1883–1890,
1906–1914,
1921–1937.
Similarly,
twelve
dry
summer
also
past
339
years,
as
1659–1665,
1675–1679,
1702–1714,
1725–1769,
1777–1793,
1798–1801,
1811–1821,
1847–1849,
1858–1871,
1891–1905,
1915–1920,
1938–1963.
Nevertheless,
1663
was
individually
wettest
(with
value
2.13),
while
1754
driest
(−0.99)
year.
spatial
correlation
analysis
its
comparisons
Karakoram-Himalayan
precipitation
reconstructions
have
convincingly
confirmed
reliability
our
reconstruction.
Consequently,
can
effectively
serve
proxy
large-scale
variability
region
northern
Pakistan.
findings
strongly
suggest
considerable
dendrochronological
potential
further
climatological
studies
western
Mountains
System.
Agrarian Bulletin of the,
Год журнала:
2024,
Номер
24(05), С. 605 - 616
Опубликована: Май 27, 2024
Abstract.
Various
climatic
indices
are
used
to
monitor
meteorological
drought,
among
which
the
best
known
standardized
precipitation
index
and
evapotranspiration
(SPEI).
The
purpose
of
research
is
assess
conditions
moisture
content
growing
season
grain
crops
in
agrolandscapes
Novosibirsk
region
on
basis
standardised
index.
Methods.
Methods
big
data
processing,
statistical
analysis
were
study.
scientific
novelty
consists
assessing
humidity
intensity
drought
during
based
climate
evaporation,
as
well
identifying
deviations
average
surface
air
temperature
from
norm
very
dry
extremely
years.
Results.
estimation
agroclimatic
vegetation
period
time
SPEI
example
was
carried
out.
On
changes
value
different
resolution
one
month
a
year
for
1970
2021
region,
years
characterised
by
severe
extreme
identified.
Drought
central
forest-steppe
Priobskiy
agricultural
landscape
uneven
season.
depends
not
only
amount
precipitation,
but
also
deviation
norm.
Advances in Meteorology,
Год журнала:
2024,
Номер
2024(1)
Опубликована: Янв. 1, 2024
Drought
is
a
recurring
natural
hazard
impacting
agriculture,
water
resources,
and
various
socioeconomic
sectors.
This
study
evaluated
the
performances
of
multiple
meteorological
hydrological
drought
index
estimation
methods
in
Tekeze
River
basin,
northwestern
Ethiopia.
Monthly
rainfall
temperature
data
from
15
stations
with
varying
record
lengths
(28–59
years)
streamflow
nine
functional
(1991–2018)
were
used
to
compute
hydrometeorological
indices.
Standardized
precipitation
(SPI),
standardized
evapotranspiration
(SPEI),
reconnaissance
(RDI),
anomaly
(RAI),
decile
(DI),
(SDI)
calculated
using
DrinC
software,
R
programming,
empirical
formulas
at
1,
3,
6,
12‐month
timescales.
Results
analysis
revealed
basin‐wide
prevalence
mild
drought,
SPI
indicating
severity
negative
values
over
longer
The
RDI
analyses
showed
lower
but
also
decreased
its
frequency
DI
calculation
basin
station
averages
indicated
48.4%,
10.7%,
8.0%
incidence
rates
for
severe,
moderate,
droughts,
respectively.
RAI
had
generally
positive
compared
SPI.
SPEI‐1
classified
almost
all
as
experiencing
drought.
Conversely,
SDI6
6‐month
timescale
diverse
impacts,
sustained
severe
(SDI6
<
−2.0)
three
consecutive
years
(2004–2006).
Spearman’s
rank
correlation
coefficients
indices
positive,
showing
particularly
strong
statistically
significant
correlations
other
provides
valuable
insights
policymakers,
researchers,
resource
managers
aiding
development
effective
mitigation
preparedness
strategies.
Climate,
Год журнала:
2023,
Номер
11(2), С. 46 - 46
Опубликована: Фев. 13, 2023
Weather
and
climate
extremes
such
as
heat
waves,
droughts
floods
are
projected
to
become
more
frequent
intense
in
several
regions.
There
is
compelling
evidence
indicating
that
changes
its
over
time
influence
the
living
conditions
of
society
surrounding
environment
across
globe.
This
study
applies
max-stable
models
capture
spatio–temporal
with
dependence.
The
objective
was
analyse
risk
drought
caused
by
extremely
high
temperatures
deficient
rainfall.
Hopkin’s
statistic
used
assess
clustering
tendency
before
using
agglomerative
method
hierarchical
cluster
area
into
n=3
temperature
clusters
precipitation
clusters.
For
data,
values
were
0.7317
0.8446,
respectively,
which
shows
both
significantly
clusterable.
Various
process
then
fitted
each
variable,
Schlather
model
covariance
functions
found
be
a
good
fit
on
datasets
compared
Smith
Gaussian
function.
modelling
approach
presented
this
paper
could
useful
hydrologists,
meteorologists
climatologists,
including
decision-makers
agricultural
sector,
enhancing
their
understanding
behaviour
low
these
compound
also
assist
assessing
impact
change.
It
can
seen
from
size,
topography
location
(cluster/region),
provides
important
information
about
strength
extremal
