Climate
models
typically
provide
air
temperature
estimates
at
lower
resolutions,
lacking
the
necessary
details
for
urban
climate
studies.
These
require
significant
computational
resources
and
time
to
estimate
temperatures
higher
resolution,
which
are
not
easily
accessible
city
scale.
In
contrast,
data-driven
approaches
offer
accuracy
speed
in
downscaling.
this
study,
a
framework
downscaling
derived
from
such
as
UrbClim
was
developed.
The
proposed
utilized
morphological
features
extracted
LiDAR
data.
To
extract
features,
first
three-dimensional
building
model
created
using
data
deep
learning
models.
Then,
these
were
integrated
with
meteorological
parameters
wind,
humidity,
etc.,
downscale
machine
algorithms.
results
demonstrated
that
developed
effectively
Deep
algorithms
played
crucial
role
generating
extracting
aforementioned
features.
Also,
evaluation
of
various
indicated
LightGBM
had
best
performance
an
RMSE
0.352°K
MAE
0.215°K.
Furthermore,
examination
final
maps
showed
successfully
estimated
enabling
identification
local
patterns
street
level.
source
codes
corresponding
research
paper
available
on
GitHub
via
https://github.com/FatemehCh97/Air-Temperature-Downscaling
Scientific Reports,
Год журнала:
2025,
Номер
15(1)
Опубликована: Янв. 15, 2025
Land
use
and
land
cover
changes
(LULCC)
alter
local
surface
attributes,
thereby
modifying
energy
balance
material
exchanges,
ultimately
impacting
meteorological
parameters
air
quality.
The
North
China
Plain
(NCP)
has
undergone
rapid
urbanization
in
recent
decades,
leading
to
dramatic
cover.
This
study
utilizes
the
2020
data
obtained
from
MODIS
satellite
replace
default
2001
Weather
Research
Forecasting-Community
Multiscale
Air
Quality
(WRF-CMAQ)
model.
It
simulates
analyzes
direct
impact
of
LULCC
on
indirect
ozone
(O3)
concentration
through
physical
chemical
processes
during
July
summer.
Six
rapidly
urbanizing
cities
were
selected
represent
Plain.
results
show
that
significantly
increased
sensible
heat
flux
2-m
temperature
areas
throughout
diurnal
cycle,
with
more
pronounced
effects
daytime,
ranging
6.49
23.46
W/m2
0.20–0.59
°C,
respectively.
10-m
wind
speed
decreased
at
night
day,
−
0.43
0.27
m/s
0.16
0.15
day.
planetary
boundary
layer
height
generally
increased,
a
larger
rise
23.63
84.74
m.
Simultaneously,
O3
concentrations
both
daytime
nighttime.
increase
ranged
2.89
9.82
μg/m3,
while
nighttime
1.76
7.77
μg/m3.
enhanced
as
well
vertical
transport,
an
O3.
At
same
time,
it
reduced
horizontal
transport
dry
deposition
processes.
These
are
related
variations.
was
not
limited
but
extended
top
(approximately
1500
m).
Below
500
m,
concentrations,
concentrations.
Additionally,
induced
by
showed
above
surface,
whereas
process
had
smaller
surface.
reveals
significant
urban
expansion
regional
optimizes
model's
simulation
quality
provides
new
insights
into
understanding
conditions
Drones,
Год журнала:
2023,
Номер
7(11), С. 645 - 645
Опубликована: Окт. 24, 2023
The
accurate
and
detailed
measurement
of
the
vertical
temperature,
humidity,
pressure,
wind
profiles
atmosphere
is
pivotal
for
high-resolution
numerical
weather
prediction,
determination
atmospheric
stability,
as
well
investigation
small-scale
phenomena
such
urban
heat
islands.
Traditional
approaches,
balloons,
have
been
indispensable
but
are
constrained
by
cost,
environmental
impact,
data
sparsity.
In
this
article,
we
investigate
uncrewed
aerial
systems
(UASs)
an
innovative
platform
in
situ
probing.
By
comparing
from
a
drone-mounted
semiconductor
temperature
sensor
(TMP117)
with
traditional
radiosonde
measurements,
spotlight
UAS-collected
data’s
accuracy
system
suitability
surface
layer
measurement.
Our
research
encountered
challenges
linked
inherent
delays
achieving
ambient
readings.
However,
applying
specific
processing
techniques,
including
smoothing
methodologies
like
Savitzky–Golay
filter,
iterative
smoothing,
time
shift,
Newton’s
law
cooling,
improved
consistency.
28
flights
were
examined
certain
patterns
between
different
sensors
observed.
Temperature
differentials
assessed
over
range
100
m.
article
highlights
notable
achievement
0.16
±
0.014
°C
95%
confidence
when
cooling
comparison
to
RS41’s
data.
findings
demonstrate
potential
UASs
capturing
profiles.
This
work
posits
that
UASs,
further
refinements,
could
revolutionize
collection.
