Abstract.
The
wet-bulb
temperature
(WBT;
TW)
comprehensively
characterizes
the
and
humidity
of
thermal
environment
is
a
relevant
variable
to
describe
energy
regulation
human
body.
daily
maximum
class="inline-formula">TW
can
be
effectively
used
in
monitoring
humid
heat
waves
their
effects
on
health.
Because
meteorological
stations
differ
temporal
resolution
are
susceptible
non-climatic
influences,
it
difficult
provide
complete
homogeneous
long-term
series.
In
this
study,
based
sub-daily
station-based
HadISD
(Met
Office
Hadley
Centre
Integrated
Surface
Database)
dataset
integrating
NCEP-DOE
reanalysis
dataset,
series
1834
that
have
passed
quality
control
were
homogenized
reconstructed
using
method
Climatol.
These
form
new
global
(GSDM-WBT)
from
1981
2020.
Compared
with
other
reanalysis-based
datasets
class="inline-formula">TW,
average
bias
was
class="inline-formula">â0.48
0.34ââC,
respectively.
GSDM-WBT
handles
many
missing
values
possible
inhomogeneities,
also
avoids
underestimation
calculated
data.
support
research
or
regional
extreme
events
waves.
available
at
https://doi.org/10.5281/zenodo.7014332
(Dong
et
al.,
2022).
Environmental Modelling & Software,
Journal Year:
2023,
Volume and Issue:
163, P. 105663 - 105663
Published: March 7, 2023
Applying
extreme
temperature
events
for
future
conditions
is
not
straightforward
infrastructure
resilience
analyses.
This
work
introduces
a
stochastic
model
that
fills
this
gap.
The
uses
at
least
50
years
of
daily
records,
climate
normals
with
10%–90%
confidence
intervals,
and
shifts/offsets
increased
frequency
intensity
heat
wave
events.
Intensity
are
shifted
based
on
surface
anomaly
from
1850–1900
32
models
CMIP6.
A
case
study
Worcester,
Massachusetts
passed
85%
cases
using
the
two-sided
Kolmogorov–Smirnov
p-value
test
95%
both
duration.
Future
shifts
several
scenarios
to
2020,
2040,
2060,
2080
had
acceptable
errors
between
10-
50-year
event
thresholds
largest
error
being
2.67°C.
likely
be
flexible
enough
other
patterns
weather
such
as
precipitation
hurricanes.
Climate Services,
Journal Year:
2024,
Volume and Issue:
34, P. 100448 - 100448
Published: Feb. 16, 2024
With
global
climate
change,
temperatures
in
Switzerland
are
projected
to
rise
the
coming
decades,
according
national
scenarios
CH2018.
Associated
with
mean
temperature
increase,
heatwaves
expected
become
longer,
more
frequent,
and
intense.
The
changing
will
affect
indoor
as
well
heating
cooling
needs.
In
building
design,
these
climatic
changes
have
be
planned
for
today
order
ensure
a
comfortable
future.
collaboration
practitioners,
reference
data
set
future
is
created
that
specifically
targets
designers
engineers.
consists
of
hourly
weather
one-year
length
based
on
Swiss
change
These
years
representative
two
time
periods
future:
one
around
2030
2060.
Climate
uncertainty
considered
by
using
emission
(RCP2.6
RCP8.5).
Reference
provided
not
only
typical
year
(called
Design
Year,
or
DRY)
but
also
an
above-average
warm
summer.
available
at
sites
45
measurement
stations
across
Switzerland,
including
four
inside
major
cities
take
urban
heat
island
effect
into
account.
generated
applied
model
provide
application
example.
results
point
out
needs
substantially
which
why
adaptation
design
vital.
