Abstract.
Despite
significant
advancements
in
improving
the
dataset
for
biomass
burning
(BB)
emissions
over
past
few
decades,
uncertainties
persist
BB
aerosol
emissions,
impeding
accurate
assessment
of
simulated
optical
properties
(AOPs)
and
direct
radiative
forcing
(DRF)
during
wildfire
events
global
regional
models.
This
study
assessed
AOPs
(including
depth
(AOD),
absorption
(AAOD),
extinction
coefficients
(AEC))
DRF
using
eight
independent
emission
inventories
applied
to
WRF-Chem
model
period
(March
2019)
Peninsular
Southeast
Asia
(PSEA),
where
were
Global
Fire
Emissions
Database
version
4.1s
(GFED),
INventory
from
NCAR
1.5
(FINN1.5),
Inventory
2.5
MOS
(MODIS
fire
detections,
FINN2.5
MOS),
MOSVIS
(MODIS+VIIRS
MOSVIS),
Assimilation
System
1.2s
(GFAS),
Energetics
Research
1.0
(FEER),
Quick
Dataset
release
1
(QFED),
Integrated
Monitoring
Modelling
Wildland
FIRES
Project
2.0
(IS4FIRES),
respectively.
The
results
show
that
PSEA
region,
organic
carbon
(OC)
differ
by
a
factor
about
9
(0.295–2.533
Tg/M),
with
1.09
±
0.83
Tg/M
coefficient
variation
(CV)
76
%.
High-concentration
OC
occurred
primarily
savanna
agricultural
fires.
GFED
GFAS
are
significantly
lower
than
other
inventories.
VISMOS
approximately
twice
as
high
those
FINN1.5.
Sensitivity
analysis
AOD
different
datasets
indicated
FINN
scenarios
(v1.5
2.5)
overestimate
compared
observation
(VIIRS),
while
underestimate
(HAOD,
AOD>1)
regions
range
97–110°
E,
15–22.5°
N.
Among
schemes,
IS4FIRES
FINN1.5
performed
better
terms
simulation
consistency
bias
HAOD
region
when
AERONET
sites.
AAOD
was
satellite
observations
(TROPOMI)
data,
it
found
schemes
did
not
perform
well
AOD.
overestimation
2.5),
FEER,
largest
MOSVIS.
representing
at
sites
within
region.
always
best
correlation
observations.
AEC
all
trends
consistent
CALIPSO
vertical
direction
(0.5
km
4
km),
demonstrating
efficacy
smoke
plume
rise
used
simulate
heights.
However,
overestimated
AEC,
underestimated
it.
In
aerosols
exhibited
daytime
shortwave
-32.60±24.50
W/m2
surface,
positive
(1.70±1.40
W/m2)
atmosphere,
negative
(-30.89±23.6
top
atmosphere.
Based
on
analysis,
recommended
accurately
assessing
impact
air
quality
climate
Atmospheric Research,
Год журнала:
2024,
Номер
308, С. 107515 - 107515
Опубликована: Июнь 5, 2024
Atmospheric
aerosols
play
a
pivotal
role
in
shaping
our
environment,
impacting
climate,
human
health,
and
ecosystems.
Characterizing
the
influence
of
on
ecosystems,
especially
mountain
environments,
is
challenging
task
due
to
their
complex-orography
scarcity
aerosol
ground
stations.
Satellite-based
data
can
improve
knowledge
over
such
areas.
Thus,
we
have
analyzed
Aerosol
Optical
Depth
(AOD)
product
from
MODerate
resolution
Imaging
Spectrometer
(MODIS)
sensor
produced
by
inversion
algorithm
MultiAngle
Implementation
Correction
(MAIAC)
last
two
decades
for
period
2001–2022
with
spatial
1
×
km.
Our
study
focuses
Sierra
Nevada
Mountain
region
National
Park
Southeastern
Spain.
As
first
step,
validated
AOD
MODIS+MAIAC
against
three
AERONET
stations
at
different
altitudes
(680
m,
1800
2500
m
above
sea
level
(a.s.l.)).
showed
good
agreement
ground-based
observations,
R
values
ranging
0.75
0.82,
RMSE
0.047
0.066
having
80%
samples
within
expected
error
(EE)
product.
The
able
characterize
fine-scale
features
area
hence
evaluate
spatio-temporal
distribution
mountainous
region.
We
generated
most
extended
dataset
region,
spanning
past
decades.
deepened
into
seasonal
patterns
2001
2022,
unveiling
elevated
near
valleys
urban
In
general,
decrease
increasing
altitude
exception
snow-covered
areas
high
(>2800
a.s.l.),
which
might
affect
retrieval
provide
bias
higher-reflecting
surfaces
pixel
removal.
For
time,
relationship
loading
ecosystem
type
has
been
assessed
protected
environment
Natural
Park.
Monthly
trends
across
types
altitudinal
ranges
are
detail
addition,
Generalized
Linear
Models
(GLM)
applied
reveal
significant
correlations
between
ecosystems
AOD,
irrespective
altitude,
latitude
or
longitude.
Based
interannual
variation
decades,
500
elevation
ranges.
ecosystem's
maintained
1200–1700
1700–2200
a.s.l.,
demonstrates
that
land-type
an
impact
Furthermore,
it
observed
forest-like
tend
present
lower
compared
bare-soil
low-growth
vegetation
closer
Granada
city
generalized
higher
western
part
mountain,
regardless
ecosystem,
showing
proximity
sites
potential
environment.
Remote Sensing,
Год журнала:
2024,
Номер
16(17), С. 3304 - 3304
Опубликована: Сен. 5, 2024
Reanalysis
and
satellite
retrieval
are
two
primary
approaches
for
obtaining
large-scale
long-term
Aerosol
Optical
Depth
(AOD)
datasets.
This
study
evaluates
compares
the
accuracy,
stability,
error
characteristics
of
MERRA-2,
MODIS
combined
Dark
Target
Deep
Blue
(DT&DB),
VIIRS
DB
AOD
products
globally
regionally.
The
results
indicate
that
MERRA-2
exhibits
highest
accuracy
with
an
expected
(EE,
±0.05
±
20%)
83.24%
mean
absolute
(MAE)
0.056,
maintaining
a
stability
0.010
per
decade.
However,
since
ceased
assimilating
observations
other
than
in
2014,
its
decreased
by
approximately
5.6%
EE
metric
after
2014.
(DB)
product,
79.43%
0.016
decade,
is
slightly
less
accurate
stable
compared
to
AOD.
DT&DB
demonstrates
76.75%
0.011
Regionally,
performs
acceptably
most
areas,
especially
low-aerosol-loading
regions,
>
86%
~0.02
excels
high-aerosol-loading
such
as
Indian
subcontinent,
69.14%
0.049
performance
falls
between
across
regions.
Overall,
each
product
meets
metrics
globally,
but
users
need
select
appropriate
analysis
based
on
validation
different
Remote Sensing,
Год журнала:
2022,
Номер
14(11), С. 2544 - 2544
Опубликована: Май 26, 2022
Three
parallel
Visible/Infrared
Imager
Radiometer
Suite
(VIIRS)
aerosol
products
(SOAR,
NOAA,
and
AERDT)
provided
data
since
2012.
It
is
necessary
to
study
the
performances
advantages
of
different
products.
This
aims
analyze
accuracy
error
these
over
ocean
compare
them
with
each
other.
The
results
show
that
three
VIIRS
retrievals
(including
total
optical
depth
(AOD),
fine
mode
fraction,
Ångström
exponent
(AE),
AOD
(AODF))
correlate
well
AErosol
RObotic
NETwork
(AERONET)
(e.g.,
correlation
>0.895
for
>0.825
AE),
which
are
comparable
newest
moderate-resolution
imaging
spectro-radiometer
(MODIS)
retrievals.
Overall,
SOAR
quality
filtering
have
best
validation
all
parameters.
Therefore,
it
more
recommended
use.
differences
in
annual
spatial
patterns
small
(bias
<
0.016),
but
their
AE
evidently
>
0.315),
indicating
large
uncertainty
AE.
Error
analysis
shows
scattering
angle
wind
speed
affect
retrieval.
Application
non-spherical
dust
model
may
reduce
dependence
retrieval
bias
on
angle.
this
provides
support
usage
possible
algorithm
improvements.
Abstract.
Despite
significant
advancements
in
improving
the
dataset
for
biomass
burning
(BB)
emissions
over
past
few
decades,
uncertainties
persist
BB
aerosol
emissions,
impeding
accurate
assessment
of
simulated
optical
properties
(AOPs)
and
direct
radiative
forcing
(DRF)
during
wildfire
events
global
regional
models.
This
study
assessed
AOPs
(including
depth
(AOD),
absorption
(AAOD),
extinction
coefficients
(AEC))
DRF
using
eight
independent
emission
inventories
applied
to
WRF-Chem
model
period
(March
2019)
Peninsular
Southeast
Asia
(PSEA),
where
were
Global
Fire
Emissions
Database
version
4.1s
(GFED),
INventory
from
NCAR
1.5
(FINN1.5),
Inventory
2.5
MOS
(MODIS
fire
detections,
FINN2.5
MOS),
MOSVIS
(MODIS+VIIRS
MOSVIS),
Assimilation
System
1.2s
(GFAS),
Energetics
Research
1.0
(FEER),
Quick
Dataset
release
1
(QFED),
Integrated
Monitoring
Modelling
Wildland
FIRES
Project
2.0
(IS4FIRES),
respectively.
The
results
show
that
PSEA
region,
organic
carbon
(OC)
differ
by
a
factor
about
9
(0.295–2.533
Tg/M),
with
1.09
±
0.83
Tg/M
coefficient
variation
(CV)
76
%.
High-concentration
OC
occurred
primarily
savanna
agricultural
fires.
GFED
GFAS
are
significantly
lower
than
other
inventories.
VISMOS
approximately
twice
as
high
those
FINN1.5.
Sensitivity
analysis
AOD
different
datasets
indicated
FINN
scenarios
(v1.5
2.5)
overestimate
compared
observation
(VIIRS),
while
underestimate
(HAOD,
AOD>1)
regions
range
97–110°
E,
15–22.5°
N.
Among
schemes,
IS4FIRES
FINN1.5
performed
better
terms
simulation
consistency
bias
HAOD
region
when
AERONET
sites.
AAOD
was
satellite
observations
(TROPOMI)
data,
it
found
schemes
did
not
perform
well
AOD.
overestimation
2.5),
FEER,
largest
MOSVIS.
representing
at
sites
within
region.
always
best
correlation
observations.
AEC
all
trends
consistent
CALIPSO
vertical
direction
(0.5
km
4
km),
demonstrating
efficacy
smoke
plume
rise
used
simulate
heights.
However,
overestimated
AEC,
underestimated
it.
In
aerosols
exhibited
daytime
shortwave
-32.60±24.50
W/m2
surface,
positive
(1.70±1.40
W/m2)
atmosphere,
negative
(-30.89±23.6
top
atmosphere.
Based
on
analysis,
recommended
accurately
assessing
impact
air
quality
climate
