Introduction
Fires burn across the Amazon region every year, releasing large
amounts of trace gases and aerosols into the atmosphere
e.g.. The majority of these fires are of anthropogenic
origin: for deforestation, preparation of agriculture fields, conversion of
cropland to pasture or road and city expansion . Between
1976 and 2010, deforestation fires destroyed more than 15 % of the
original Amazonian forest . Most of these fires burn in the
so-called arc of deforestation, along the eastern and southern borders of the
Amazon forest, during the dry season (typically from July to November)
. However, significant variability exists, caused by changes
in meteorology, drought and land-management policies
e.g.. Amazon fires can contribute
up to about 15 % of the total global biomass-burning emissions
. These emissions have important implications for air quality,
atmospheric composition, climate and ecosystem health
e.g.. For example, air
pollution from deforestation fires is estimated to cause on average about
3000 premature deaths per year across South America
and may decrease the net primary productivity in the Amazon forest as a
result of increases in surface ozone .
Fires are also an important source of buoyancy locally, which in combination
with other atmospheric properties determines the vertical distribution of
fire emissions in the atmosphere near the fire source (i.e. injection
height). The altitude at which smoke is injected is critical, as it
determines the lifetime of the pollutant, its downwind transport dispersion
pathway and the magnitude of its environmental impact
e.g.. Space-borne
observations have been used to study smoke injection heights across the
world. Using Multi-angle Imaging SpectroRadiometer (MISR) stereo-height
retrievals, smoke plume heights have been assessed across North America
, Indonesia , Australia
, south-eastern Asia and Europe
. For example, , using a 5-year
climatology of smoke fire plumes and smoke clouds observed by MISR across
North America, showed that wildfire smoke can reach altitudes from a few
hundred metres above the ground to about 5 km, and that 5 %–30 % of the
smoke plumes are injected into the free troposphere (FT), depending on the
biome and year. Related work also demonstrated the important effect that fire
radiative power, i.e. a proxy of fire intensity, and atmospheric conditions
have on the initial rise of fire emissions
. reported that
less than 4 % of smoke plumes reach the free troposphere, based on a MISR
8-year climatology from tropical forest and peatland fires over Borneo and
Sumatra and found that the greatest plume heights were recorded during an El
Niño year over Borneo.
Smoke plume heights have also been determined using space-borne lidar
observations from CALIOP , aerosol index from
the TOMS and OMI instruments , and CO observations from TES
and MSL . used a multi-year record of
CALIOP vertical aerosol distributions to study smoke and dust layer heights
over six high-aerosol-loading regions across the globe. Specifically over the
Amazon, they found that on a broad scale, smoke layers are typically located
above boundary layer clouds, at altitudes of 1.6–2.5 km. Consistent with
the smoke altitudes detected by CALIOP, an analysis of injection heights
using CO observations from TES and MLS estimated that about 17 % of fire
plumes over South America reached the free troposphere in 2006
.
Numerous studies have sought to understand the impact of biomass burning in
the Amazon, on local to hemispheric scales. In particular, during the past
decade, several aircraft campaigns have been designed to study the effect of
biomass burning on greenhouse gases, aerosols loading, clouds, regional
weather and/or climate over the Amazon (e.g. BARCA ,
SAMBBA and GoAmazon ). For example,
modelling studies during SAMBBA showed the importance of the vertical
representation of aerosols from biomass burning over the region
, as biomass burning can modify local weather
and regional climate . Based on lidar
observations taken in six research flights during SAMBBA
(16–29 September 2014), reported the presence of two
distinct smoke aerosol layers, a fresh smoke layer extending from the surface
to an altitude of 1–1.5 km, and an elevated and persistent layer of aged
smoke at 4–6 km. During the 2008 dry biomass season, continuous raman lidar
measurements of optical properties taken in Manaus (2.5∘ S,
60∘ W) also detected biomass-burning layers at 3–5 km heights,
although most of the smoke was confined below 2 km . Whilst the
results from these aircraft and in situ lidar observations are significant,
there are no analyses yet that seek to quantify the long-term average
vertical distribution of smoke from fires across the Amazon and to identify
the key factors that control plume rise over this region.
Here we present an 8-year climatology of smoke plume heights over the Amazon,
derived from observations by the MISR and CALIOP instruments on board the
NASA Terra and CALIPSO satellites, respectively. These data are analysed in
combination with measurements of fire radiative power (FRP) from NASA
Moderate Resolution Imaging Spectroradiometer (MODIS) instruments,
assimilated meteorological observations from MERRA-2 and drought condition
indicators from the MODIS drought severity index (DSI). The objectives of
this work are to characterise the magnitude and variability of smoke heights
from biomass burning across the Amazon and to assess the influence of biome
type, fire intensity, local atmospheric conditions and regional drought on
smoke vertical distribution as well as aerosol loading.
Data and methods
We use a combination of remote-sensing data from multiple sources to build a
comprehensive climatology of smoke plume heights and characterise the
vertical distribution of smoke across the Amazon. We provide below a summary
of main datasets and tools used in the analysis and compile their main
features in Table S1 of the Supplement.
MINX overview
The MISR INteractive eXplorer (MINX) software is an
application written in Interactive Data Language (IDL) that is used to
analyse the physical properties of smoke plumes and to study plume dynamics
. MINX can use MODIS thermal anomalies to locate active
fires, and MINX then computes the smoke plume or cloud heights from MISR
stereo imagery. MINX also collects particle property results from the MISR
standard aerosol retrieval algorithm . MODIS and MISR
are both aboard the NASA Terra satellite, which crosses the equator in the
descending node at around 10:30 local time. These instruments allow
temporally and spatially coincident detection of active fires and their
associated smoke plumes .
MODIS has a cross-track swath of 2330 km that provides global coverage every
1 to 2 days. The instrument has 36 spectral channels with wavelengths between
0.4 and 14.2 µm, and detects thermal anomalies at 1 km spatial
resolution (at nadir) under cloud-free conditions. MODIS reports fire radiate
power based on a detection algorithm that uses brightness temperature
differences in the 4 and the 11 µm channels ;
this FRP parameter is used as an indicator of fire location and qualitative
intensity. We use MODIS Collection 6 (Table S1 in the Supplement). We note
that MINX provides FRP values in MW, although they are actually in MW per
1 km pixel, which corresponds to W m-2, except toward the edges of the
swath.
MISR has nine push-broom cameras placed at viewing angles spanning -70.5 to
70.5 relative to nadir in the satellite along-track direction
. The cameras each provide imagery in four spectral bands
(446, 558, 672 and 867 nm), which makes it possible to distinguish aerosol
types qualitatively and surface structure from the change in
reflectance with view angle. This passive stereoscopic imagery method
produces cloud and aerosol plume heights, along with cloud-tracked winds
aloft. MISR has a swath of 380 km common to all cameras, so global coverage
is obtained every 9 days at the Equator and every 2 days at the poles
. The MISR standard stereo-height product provides vertical
resolution of 275–500 m and a horizontal resolution of 1.1 km
.
MINX has a graphical user interface that displays the nine MISR multi-angle
images. They can be visualised one by one or as an animated loop, providing a
3-D view of the plume that can help to assess its structure and dynamical
behaviour. In addition, MODIS thermal anomalies can be superimposed, which
helps identify the locations of smoke sources from active fires. A user needs
to digitise the boundaries of the plume, starting at the source point, and to
indicate the direction of smoke transport. The MINX stereoscopic algorithm
also calculates wind speed from the displacement of plume contrast elements,
which is used subsequently to compute wind-corrected heights, accounting for
displacement due to the proper motion of the plume elements between camera
views. As with the MISR standard stereo-height product, MINX automatically
retrieves smoke plume heights and wind speed at a horizontal resolution of
1.1 km and vertical resolution of 250–500 m, but with greater accuracy for
the plume itself due to the user inputs . MINX plume
heights are reported above the geoid, which correspond to the level of
maximum spatial contrast in the multi-angle imagery, typically near the plume
top, but actually offer a distribution of heights in most cases, because
aerosol plumes are rarely uniform . Additionally, MINX
provides local terrain height from a digital elevation map (DEM) product.
Here we report heights above the terrain by taking account of the DEM
values. Further information from the MISR standard aerosol product about
aerosol amount and type is collected and reported, along with FRP from MODIS
. MINX has been successfully used to investigate fire smoke
plume heights over many regions across the world
e.g..
There are several limitations to the MISR-MINX approach that must be
considered when studying smoke plume heights. For example, MISR obtains
global coverage only about once per week, and the Terra overpass time in the late
morning does not coincide with the typical, late-afternoon peak of fire
intensity. MODIS does not observe FRP under cloud and dense smoke, and the
MINX operator must decide whether to include any pyrocumulus clouds in the
plume-height retrieval. These are the key limitations: they and others are
discussed further in the literature
e.g.. In addition, three MINX
versions were used to generate the data in this study, which might introduce
an additional bias. MINXv2 and v3 included only MISR red-band plume height
retrievals, whereas MINXv4 considers both red- and blue-band images. Over
land, digitalisation with the blue band usually provides higher-quality
retrievals, especially for optically thin plumes over bright surfaces. In
contrast, the red band provides higher vertical resolution over dark surfaces and
sometimes performs better for optically dense smoke layers
. We take these limitations into account throughout our
analysis.
MINX smoke plume database
We limited our study to the burning season (July–November) for the period of
2005–2012. Using MINX, we developed a climatology of plume heights across
the Amazon, consisting of 10 858 smoke plumes in the region
(25∘ S–5∘ N latitude and 80–40∘ W longitude).
Over this domain, the NASA Terra satellite overpass is every 4–8 days at
10:00–11:00 local time. Table 1 summarises the number of smoke plumes in
each year and the digitising source. The climatology includes a combination
of smoke plumes extracted from different projects and created with different
versions of MINX (v2–4): plumes for August–September in the years 2006 and 2007
are from the MISR Plume Height Project ; plumes in the year
2008 are from the global digitalisation effort made for the AeroCom project
(MPHP2 and ); and the 5 remaining years and additional
months are digitised as a part of the current project.
Summary of MISR smoke plumes over the Amazon domain (2005–2012).
Number of plumesa
Year
Total
Blue band
Red band
MINX version
Reference
2005
927
122
805
v3/v4
This study
2006
513
501
12
v2/v4
MPHPb/This study
2007
858
670
188
v2/v4
MPHPb/This study
2008
889
889
0
v3.1
MPHP2c
2009
150
55
95
v3/v4
This study
2010
1373
0
1373
v3
This study
2011
320
320
0
v4
This study
2012
363
30
333
v3/v4
This study
2005–2012
5393
2587
2806
a Total number of plumes and number of plumes digitised with blue- or red-band
retrievals.
b MISR Plume Height Project; data from
https://misr.jpl.nasa.gov/getData/accessData/MISRPlumeHeight/ (last
access: 4 February 2019). c MISR Plume Height Project2; data from
https://misr.jpl.nasa.gov/getData/accessData/MisrMinxPlumes2/ (last
access: 4 February 2019).
MINX computes several plume heights that describe the altitude that smoke
reaches in the atmosphere. In this work, we use the best-estimate maximum and
median smoke plume heights, which represent the distribution of stereo
heights obtained at the level of maximum spatial contrast over the plume
area . In addition, as in previous studies, we remove smoke
plumes with poor-quality retrieval flags. This screening leaves a total of
5393 plumes, about 56 % of the original database, with 77 % and
23 % plumes digitised in the red and blue bands, respectively. Our final
dataset includes plumes digitised in years with intense fire activity
associated with severe drought conditions (e.g. 2005, 2007 and 2010)
, in years with low fire intensity and considerable
precipitation (2009 and 2011) and in 1 year when
land-management policy measures limited deforestation (2006)
. Thus, our climatology is intended to capture smoke
plume variability under diverse conditions.
As mentioned in Sect. , the MISR colour band image used
by the MINX algorithm to compute smoke plume heights influences the quality
of the plume height and wind speed retrievals. A large majority of the fires
detected across our domain have optically thin smoke plumes. Thus, blue-band
plume retrievals are more successful, with about 60 % of the smoke plumes
receiving good- or fair-quality flags compared to 36 % for the red-band
retrievals. In our dataset overall, most of the plumes were digitised from
red-band images, as it was the default option for MINX v2–3. However,
whenever both band retrievals are available for a plume, the blue band is
preferred in this study. The choice of the band colour for the retrievals
does not significantly affect the results presented here, as the difference
in heights for smoke plumes digitised with both bands is negligible
(∼60 m), lower than the ±250 m MINX uncertainty.
Land cover unit data
We use the MODIS Level 3 land cover product MCD12Q1 to
determine the type of land cover associated with each of our fire smoke
plumes. This product contains 17 International Geosphere-Biosphere Programme
(IGBP) land cover classes, at a horizontal resolution of 500 m and annual
temporal resolution, from 2001 to the present day. It is available from the
Land Processes Distributed Active Archive Center
(https://e4ftl01.cr.usgs.gov/MOTA/MCD12Q1.051/, last access:
4 February 2019). We merge land cover classes having similar characteristics
into four land types representing the main biomes across the Amazon: tropical
forest, savanna, grassland and crops.
Atmospheric conditions
To assess the role of atmospheric conditions on the final
elevation of smoke plumes across the Amazon, we analyse data from the second
Modern Era Retrospective-analysis for Research and Applications (MERRA-2)
reanalysis model simulation . We focus on the height of
the planetary boundary layer (PBL) and the atmospheric stability at the
location of our fires. As in previous studies
e.g., we define the atmospheric stability
as the vertical gradient of potential temperature. We use data from MERRA-2
at a horizontal resolution of 0.625∘ longitude by 0.5∘
latitude, with 42 vertical pressure levels between the surface and
0.01 hPa. MERRA-2 provides hourly PBL height above ground level and
potential temperature profiles every 6 h (0:00, 06:00, 12:00 and 18:00 UT),
so we linearly interpolate these data to the time and location of each fire
plume origin.
Drought conditions
To determine the presence and magnitude of droughts over
the Amazon during our study period, we use the MODIS drought severity index
(DSI). The DSI is a global drought index derived by combining the MODIS16
Evapotranspiration e.g. and the MODIS13 vegetation index
(NDVI) data products . DSI provides drought conditions on a
global scale for all vegetated areas at 8-day and annual temporal resolutions
and 0.5 or 0.05∘ horizontal spatial resolution for 2000–2011
. In this work, we use the 8-day temporal resolution DSI and
interpolate the data to the time and location of our fire smoke plumes.
Following , we further define drought conditions as
“extreme severe” (DSI ≤-1.2), “mild moderate”
(-1.2≤ DSI <-0.29), “normal” (-0.29> DSI >0.29) and “wetter
than normal” (DSI ≥0.29).
CALIOP observations
We also use extinction profiles derived from the CALIOP
instrument to provide an independent assessment of the vertical smoke
distribution across the Amazon. CALIOP is a space-borne two-wavelength
polarisation lidar (532 and 1064 nm) that flies aboard the CALIPSO satellite
. CALIPSO was launched in 2006 into a sun-synchronous polar
orbit of 705 km altitude as a part of the A-Train constellation, with an
orbit repeat cycle of 16 days. CALIOP collects backscatter and depolarisation
data that constrain the vertical structure and some properties of aerosols
and clouds around the globe . In addition, CALIOP
provides a characterisation of the aerosol type (i.e. dust, polluted dust,
marine, clean continental, pollution and biomass burning) based on an externally
determined surface type along with measured depolarisation ratios, integrated
backscatter altitude and colour ratio . This aerosol-type
classification can be used to indicate the likely sources that contribute to
aerosol mass loading at specific locations and times at which the instrument has
coverage.
We use CALIOP Level 2 version 4 day and night data
(CAL_LID_L2_05kmAPro-Standard-V4-10) over the Amazon for the July to
November burning season, from 2006 to 2012. In this work, we filter the data
following . This filtering approach uses cloud-aerosol
distinction scores, extinction uncertainty values, atmospheric volume
descriptors, extinction quality control flags and total column optical
depths, and assumes that extinction observations classified as “clear air”
have zero aerosol extinction (rather than the fill value). CALIOP daytime
retrievals can be biased low due to the noise from scattered solar radiation
. However, we analyse both day (i.e. early
afternoon, ∼ 13:30 LT equator crossing time) and night profiles to
identify any differences in smoke heights, as well as to allow a better
comparison with the MISR smoke plumes, which are retrieved during late
morning.
The CALIOP swath is ∼100 m wide, so sampling is effectively a
curtain. To obtain a climatology of CALIOP smoke plumes as in MISR, we
developed an approach to identify individual smoke plumes in the CALIOP data.
We first grid all CALIOP aerosol extinction profiles classified as smoke (day
and night) at a horizontal resolution of 0.5∘×0.5∘
over the Amazon region, and a vertical resolution of 250 m, from the surface
to 12 km. We chose this horizontal resolution to optimise computer processing time. Within each grid cell, we then determine the vertical
distribution of smoke extinction. We define the maximum smoke plume height in
each grid cell as the maximum altitude reached by the extinction classified
as smoke. Similarly to the MINX definition of median plume height, we consider
the median of the CALIOP vertical extinction distribution as the height at
which most of the smoke is probably concentrated. Smoke does tend to concentrate
either in the PBL or in thin layers in the FT .
To ensure we do not introduce a bias into the CALIOP plume heights due to the
0.5∘×0.5∘ horizontal resolution, we also retrieved
the smoke plumes for the 2007 burning season at a horizontal resolution of
0.1∘×0.1∘ and find no significant differences. For
this subset, our 0.5∘×0.5∘ method returns 131
plumes, with an average altitude of 3.65 km for the maximum plume heights,
whereas the 0.1∘×0.1∘ method returns 149 plumes,
with an average altitude of 3.74 km.
To identify CALIOP smoke plumes associated with active fires, we select only
those CALIOP-derived grid cells that contain at least two MODIS Collection 6
fire pixels at 80 % confidence level or higher, at
the time of CALIOP overpass. We also use the mean terrain elevation across
each grid cell to reference the maximum and median heights to ground level,
as CALIOP provides observations above sea level. We estimate the mean terrain
elevation using terrain elevation from the CALIOP digital elevation map.
Figure shows an example of our approach for the
CALIOP observation of 25 September 2010 at 06:25 UTC. For this example, we
identify a CALIOP smoke plume with 2 km median and 4.5 km maximum height
above ground level. A total of 2460 plumes are characterised with our
approach over the Amazon for the months of July to November from 2006 to 2012;
about 65 % of these plumes are linked to active fires with some
confidence (i.e. having a clear connection to a MODIS fire pixel), and we
only consider those in our analysis, a total of 1600 plumes.
Example of the approach followed for the CALIOP smoke plume
characterisation. The map shows estimated smoke plume median heights (gridded
at 0.5×0.5 horizontal resolution) for 25 September 2010 at
06:25 UTC. MODIS active-fire pixels associated with the CALIOP smoke plumes
are represented with open circles. The insert displays the vertical
distribution of aerosol extinction for a specific smoke plume in the map,
with extinction values coloured by classified aerosol types. Dashed black
line represents the averaged extinction profile for the aerosols classified
as smoke (pink dots). In this profile, the CALIOP smoke plume has a median
height of ∼2 km (green colour in the smoke plume median height scale)
and a maximum height of 4.5 km above the terrain.
Previous studies used other CALIOP products to determine the vertical
distribution of smoke plumes. The level 2 aerosol layer product is commonly
used to analyse smoke plume heights from CALIOP, as it reports the top and
base heights of aerosol layers. used their smoke layer top
altitudes and extinction coefficient profiles over Borneo for
September–October 2006. Using the CALIOP Level 1 attenuated backscatter
profiles at 532 nm, estimated smoke injection heights
from agricultural fires over Europe. They selected only those profiles of
constant attenuated backscatter coefficient with height, without strong
convection, and that were collocated with MODIS active-fire pixels from the
Aqua satellite. Recently, used 6 years of the CALIOP
Level 2 vertical feature mask (VFM) data and aerosol layer products over six
regions to investigate the most probable height (MPH) of dust and smoke
layers. They used two approaches to obtain MPH: one based on the probability
distribution of the vertical profiles of occurrence frequency (OF) (i.e.
ratio of number of samples classified as dust or smoke by the VFM to the
total samples per grid) and the other as the probability distribution of the
aerosol optical depth (AOD) vertical profiles. So MPH_OF and MPH_AOD
correspond to the altitude with the largest OF and mid-visible AOD for a
certain type of aerosol. Our definition of CALIOP median plume height is most
similar to their MPH_AOD. However, analysed vertical
profiles over large-scale regions (e.g. the entire Amazon or Sahara),
whereas in the current work, we analysed and then aggregated the heights for
individual smoke plumes.
Our initial objective was to compare the CALIOP with the MISR plumes to
assess the diurnal smoke evolution, as CALIOP has a later sampling time than
MISR over the Amazon (14:00–15:00 vs. 10:00–11:00 LT). However, despite
our effort to develop a comprehensive CALIOP climatology, none of the CALIOP
plumes coincide with the MISR plumes. As previous studies discuss
e.g., CALIOP and MISR, in addition to having
different sampling times, also have different swath widths (380 km vs.
70 m). These differences make it difficult to observe the same fire on the
same day, but they make CALIOP and MISR observations complementary: MISR
provides late-morning near-source constraints on aerosol plume vertical
distribution, whereas CALIOP in general offers more regional constrains,
later in the day . Some differences between the products are
thus expected.
Results and discussion
Smoke plume height observations
Figure maps the biomes of the Amazon region
for which the MISR plume climatology was developed.
Figure presents the time series of the smoke plume
heights for the biomass-burning seasons (July–November) during the
2005–2012 study years. We also include a statistical summary of the number
of plumes within the time series by year, month, biome and drought conditions
in Fig. S1 in the Supplement. The largest number of plumes is recorded in 2010, with about
25 % of the total plumes in the database, whereas the smallest is in 2009
(3 %). These 2 years are the driest and the wettest in the climatology, respectively. Most of the plumes were observed in August and September
(85 %), at the peak of the burning season in most vegetated locations, in
the dominant biomes of savanna (48 %) and tropical forest (46 %), and
during dry conditions (76 %). We find important interannual variability
in the type of fires, with fires over tropical forest dominant in 2005
(65 %) and 2010 (47 %), 2 of the 3 drought years in our
database as shown in Sect. below and the majority
of fires in savanna (54–65 %) for the other years. We note that a
large fraction of the plumes were observed in 2008 (17 %), even though it
was not a drought year. The majority of plumes in the 2008 record are
digitised with blue-band retrievals (Table 1), which produce higher-quality
results in many situations, especially for optically thin plumes over land
surfaces.
Locations of the MISR plumes analysed (black dots) over the four
main biomes considered in the study. The black square represents the Amazon
domain.
Time series of the 2005–2012 MISR Amazon smoke-plume-height
climatology, covering the July–November burning season for each year. Each
blue dot represents the maximum smoke height above ground level (agl) for one
plume.
Throughout the study period, we find significant variability in smoke plume
height, with altitudes ranging from a few metres (essentially near-surface)
to 5 km, depending on the biome (Fig. ). Smoke plumes
over cropland fires are scarce compared to the other fire types, as these
fires are small and tend to be underdetected by MISR . We
summarise the statistical parameters of the
smoke plumes for all observations except the cropland cases in Table . Over the Amazon,
the vertical distribution of smoke varies by biome. Statistically, the
highest smoke altitudes averaged by biome are detected over grasslands, with
median and maximum heights of 794 and 1120 m, respectively, whereas the
lowest heights are detected over tropical forest (601 and 845 m, respectively). In all the biomes, more than 85 % of the smoke is located
at altitudes below 2 km (Fig. S2 in the Supplement).
Similar altitudes and distributions have been found across comparable fires
in other parts of the world. For example, altitudes between 700 and 750 m
were detected over the tropical forest in central America and Indonesia
. In contrast, smoke plume heights over the
Amazon are substantially lower than smoke plumes observed over the boreal
biomes (960–1040 m) . There are several
factors that influence smoke altitudes and contribute to the differences
between biomes, such as fire intensity, availability of fuel, combustion
efficiency, atmospheric stability and entrainment
e.g..
We assess some of these factors for our Amazon dataset next.
Effect of atmospheric and fire conditions on smoke plumes
We explore the relationship between smoke plume
height, fire characteristics (i.e. MODIS FRP and AOD) and atmospheric
conditions derived in the vicinity of the fires throughout the burning
season, across the major biomes in the Amazon except cropland. For
atmospheric conditions, we focus both on how smoke plume height relates to
boundary layer height and on the effect of atmospheric stability on plume
rise. We consider atmospheric stability conditions above our fires as the
average of the atmospheric stability over the atmospheric column
(K km-1; Sect. ) from the surface, at the origin of
the fire, to the maximum altitude that smoke reached in the atmosphere. We
add a buffer of 10 % to the maximum altitude to account for any potential
influence that the atmosphere above the plume might have over the column. We
include a summary of these main parameters in Table .
Statistical summary for main smoke plume parameters and atmospheric conditionsa. Atm stab is atmospheric stability.
Tropical forest
Savanna
Grassland
Median height (m)
601 ± 339
743 ± 422
794 ± 471
Max height (m)
845 ± 499
1040 ± 585
1120 ± 653
MODIS FRP (MW)
209 ± 537
360 ± 658
421 ± 614
AOD (unitless)
0.51 ± 0.34
0.33 ± 0.28
0.35 ± 0.29
Atm stab (K km-1)
4.21 ± 2.97
3.16 ± 3.16
2.52 ± 2.50
BL height (m)
1270 ± 514
1490 ± 507
1620 ± 530
Plumes in FT (%)b
3–15
4–17
5–19
Number
1744
2084
166
a Reported the average ± SD and number of observations.
b Reported range from more and less conservative
definitions of plume in the FT (see text for explanation).
Consistent with previous studies
e.g., we find
that the highest-altitude smoke plumes tend to be associated with highest
MODIS FRP values, though there is significant variability in the relationship
in all the biomes (r2=0.2; Fig. S3 in the Supplement). Smoke plumes
detected over tropical forest fires have the lowest FRP (209 MW) and largest
AOD values (0.51) (Table ). The other two main biomes
(savanna and grassland) have FRP and AOD values similar to each other
(360–421 MW and 0.33–0.35, respectively). Tropical forest has deeper root
systems, which allow fires to access deeper soil layers
that can maintain higher moisture content and lower oxygen availability than
other biomes, such as grasslands. High fuel moisture content and low oxygen
availability favour smouldering rather than flaming fires, which in turn
tends to produce greater smoke emission but lower radiant emissivity
. Therefore, the low FRP and high AOD in tropical forest
fires are consistent with these conditions, in which smouldering fires
predominate, whereas high FRP and low AOD are typical with drier, less dense
fuels, e.g. savanna and grassland, that tend to produce flaming fires
. In addition, high smoke opacity and tree canopy obscuring
the fire-emitted 4-micron radiance as viewed by MODIS, as well as low radiant
emissivity, rather than just low radiative total fire intensity, probably
contribute to these differences .
The atmospheric stability structure affects the vertical motion of smoke and
is a key factor in plume rise, either enhancing or suppressing the lifting.
Some studies have shown the important role that atmospheric stability plays
in plume rise e.g.,
and the quantitative representation of this factor still remains an open
question in plume-rise model parameterisations. For instance,
showed that, in North America, fires that inject smoke
to high altitudes tend to be associated with higher FRP and weaker
atmospheric stability conditions than those that inject smoke at low
altitudes, in which smoke tends to be trapped within the boundary layer.
Similar results were found for agricultural fires over eastern Europe
.
To analyse the influence of atmospheric stability over Amazon fires
qualitatively, we divide our plume dataset into two groups that we define as
having weak and strong atmospheric stability conditions based on MERRA-2
reanalysis. Over the Amazon, and at the locations and times studied,
atmospheric stability ranges from -3 to 23 K km-1. We designate
atmospheric stability <2 K km-1 as “weak” and atmospheric
stability >4 K km-1 as “strong”. Each group contains about
30 % of plumes in the database. Figure shows the
vertical distribution of smoke stereo-height retrievals for the plumes
classified under weak and strong atmospheric stability conditions. Our
comparison supports previous observations that plumes under weak atmospheric
conditions tend to inject smoke to higher altitudes than those encountering
strong stability, with maximum plume heights of 1150 and 654 m, respectively. A similar pattern is found for the median plume heights (821
and 482 m, respectively). Weak atmospheric stability conditions are also
associated with deeper PBLs (∼1500 m) than strong stability conditions
(∼1200 m) (not shown).
Vertical distribution of MISR stereo-height retrievals for all the
plumes analysed, under strong (blue) and weak (red) atmospheric stability
conditions.
Atmospheric conditions also correlate with biome type. We find that tropical
forest fires tend to be associated with more stable atmospheric conditions
than grassland fires (4.2 vs. 2.5 K km-1). Shallower PBLs are also
observed over tropical forest (1270 m) compared to grassland (1620 m).
Tropical forests typically have higher relative humidity conditions and more
constant temperatures than grasslands, which favours more stable conditions
and lower PBL heights . We note that our dataset was fully
acquired at Terra overpass time, which occurs between about 10:00–11:00 LT. This might produce a bias toward the more stable atmospheric conditions
that occur preferentially during the morning; later in the afternoon
convection tends to become more important .
Seasonality of smoke plumes heights
Figure shows the seasonal cycle of maximum plume height
with FRP, AOD and atmospheric conditions over the major Amazon biomes. We
further disaggregate these observations by biome, season and dry or wet years in
Table S2 in the Supplement. For these biomes, we find minimum plume heights
of 600–750 m in July and maximum plume heights of 900–1400 m in October
and November. Similarly, over tropical forest and grassland, MODIS FRP values
follow the plume-height patterns, with maximum values toward the end of the
burning season (180–200 MW) compared to the early season (90 MW). For
savanna fires, MODIS FRP remains mostly constant throughout the season
(∼150–200 MW). Savannas are known to be fire-adapted, and combustion
efficiency typically remains constant throughout the season .
All these patterns are similar in wet and dry years, although larger MODIS
FRP values are observed over savanna and grassland fires in dry years
(Table S2).
Seasonal cycle of MISR smoke plume maximum height above the terrain
(black circles), MODIS FRP (red diamonds), PBL heights (black triangles),
atmospheric stability (blue diamonds) and MISR AOD (green diamonds). Monthly
median values are shown for tropical forest, savanna and grassland biomes.
Vertical bars indicate the 10th and 90th percentiles. Distributions with fewer
than 10 observations are omitted and all years are included.
Some previous studies show the seasonal peak in MODIS FRP over the Amazon
earlier, in August–September . However, their work relies on
the maximum MODIS FRP detected by the Terra and Aqua satellites (4 times a day) over the Amazon, whereas our seasonality shows the monthly median
MODIS FRP observed by Terra, collocated with the MISR smoke plume
observations (once a day). In addition, the MISR swath is substantially
narrower than MODIS (380 vs. 2330 km), and many fires detected by MODIS are
not observed by MISR. Our seasonality thus captures the fire intensity that
drives the smoke plumes detected specifically by MISR, i.e. only at about
10:30 local time, and the seasonal differences provide at least some
indication of possible bias introduced by the MISR sampling of fires.
In contrast to the seasonality of plume heights and fire intensity, the peak
monthly AOD occurs in September across the major biomes, with a median AOD of
0.6 in tropical forest and 0.3 in savanna and grasslands compared to AOD
values of 0.04–0.1 in July and November. Over the Amazon, total AOD
correlates well with the number of fires, and both tend to peak during
September each year . reported optical
depths in the polluted biomass-burning season (July–November) to be 6 times
larger (on average) than in the pristine wet season (December–June), with
highest values in September and October, for a site in the central Amazon
near Manaus. In our dataset, September, together with August, are the months
in which the largest number of plumes were detected (Fig. S1 in the Supplement).
However, our monthly statistics might be influenced by the number of
observations in each month. For example, the number of fires in August is
driven by the year 2010, in which an unusually large number of fires were
observed compared to the other August months. In addition, the large monthly
median values in November are based on the lowest number of plumes (Fig. S1 in
the Supplement), although the few fires detected by MISR for those months
were large and intense.
Boundary layer heights and atmospheric stability conditions may also vary by
biome and throughout the season, influencing plume-rise spatial and temporal
distributions. On a seasonal basis, the PBL height does not follow a clear
cycle in any of our biomes, but higher PBL heights are observed over
grassland fires (Table ) and across all the biomes
during dry years (Table S2). More stable atmospheric conditions are found at
the beginning (3.6 K km-1 in July) compared to the end of the burning
season (1.9 K km-1 in November).
Previous studies have shown that a substantial fraction of smoke is injected
above the boundary layer (i.e. into the FT), although this fraction varies
depending on biome and fire type. For tropical fires over central America and
Indonesia, smoke from about 4–6 % of fires is reported to reach the FT
. This fraction is larger for boreal fires
(>16 %), where fires are more intense and the BL is typically lower
than in tropical regions . Following
these studies, we consider that smoke reaches the FT when the median height
of the plume is at least 500 m above the PBL height. This is a conservative
definition that takes into account uncertainties in MINX and MERRA
e.g.. Because fires over the
Amazon tend to be smaller in size than those in boreal forests, we also
consider a less conservative definition. We assume a plume is injected into
the FT when the maximum plume height is at least 250 m above the PBL height.
We understand that this is an upper limit, but it provides a bracket to our
results. We include the percentage of the
smoke plumes injected into the FT for both definitions in Table , and present the seasonality of these percentages in
Fig. . Our analysis
shows that fires at the end of the burning season are more likely to inject
smoke in the FT, with 15 %–40 % in November vs. 2 %–10 % in
July and 5 %–22 % at the peak of the burning season
(August–September). This pattern seems to be related to a combination of
more intense fires and less stable atmospheric conditions. We find no
influence of the monthly PBL depth variability, although deeper PBL heights
are found across the Amazon in drier conditions (i.e. over grassland fires
and/or dry years). Interestingly, our analysis also shows a slightly larger
percentage of fires injecting smoke into the FT over grassland
(5 %–19 %) compared to tropical forest (3 %–15 %). As
mentioned above, grassland fires are associated with high PBL heights but
also with large FRP values, suggesting that these fires are energetic enough
to produce the buoyancy needed for the smoke to reach the FT.
Seasonal variation of Amazon plume injection above the PBL
(percent). Bar plots indicate the average of (median
plume - PBL height) > 0.5 km (dark grey) and (maximum plume - PBL
height) > 0.25 km (light grey) (see text for explanation).
Interannual variability of smoke plumes and drought conditions
We use MODIS DSI to assess the effect of drought
conditions on smoke plume rise and the extent that these conditions control
the interannual variability of smoke plumes across the region. We present the
interannual variability of MISR plume heights, MODIS FRP and MISR AOD in
Fig. , and summarise the annual averages of
MODIS DSI, atmospheric stability, PBL height and percentage of smoke plumes
in the FT in Table . In addition, we include the
annual relationship of MISR plume heights, MODIS FRP and MISR AOD with MODIS
DSI, and the percentage of plumes in the FT per drought level in
Fig. . In our dataset, 76 % of plumes are recorded under
extreme–mild drought conditions vs. 7 % plumes in wet conditions, as
discussed in Sect. . During drought years (2005, 2007 and
2010), smoke plumes register the lowest MODIS DSI annual averages values
(-0.89, -0.91 and -1.50, respectively) compared to the other years in the climatology
(-0.63 to 0.18). Note that DSI is higher in wetter years.
Interannual variability of MISR maximum plume heights above the
terrain, MODIS FRP and MISR AOD, for the aggregate of tropical forest,
savanna and grassland. Bar plots indicate the distribution of the data for
each year. The medians (red circles) and the means (black squares) are shown
along with the central 67 % (box) and the central 90 % (thin black
whiskers). The number of observations (in black) and the median values (in
red) included in each distribution are given at the top of the plot. Drought
years are in pink and non-drought years are in light blue. The same data,
stratified by biome type, are plotted in Fig. S4 in the Supplement.
Relationship between MODIS DSI at the location of the plumes and
MISR maximum plume height, MODIS FRP and MISR AOD annually averaged, for
tropical forest (green), savanna (blue) and grassland (red). Symbols
represent the annual average and bars the standard error of the mean.
Regression lines are weighted by the number of plumes in each year;
relationships with absolute r<0.4 are plotted in dashed lines. Also
included is the percentage of smoke plumes in the FT in each biome and by
drought condition. Bar plots indicate the average of (median
plume - PBL height) > 0.5 km (light colour) and (maximum plume - PBL
height) > 0.25 km (dark colour), based on MERRA-2 PBL heights (see text
for explanation).
Summary of the main atmospheric parameters calculated at the location of the plumes per yeara.
Year
Number
BL height
Atm. Stab
Percent in FTc
(m)
(K km-1)
2005b
927
1370 ± 546
4.32 ± 3.01
3–13
2006
513
1210 ± 518
3.50 ± 2.89
6–25
2007b
858
1380 ± 539
3.96 ± 3.30
3–18
2008
889
1480 ± 558
3.02 ± 2.28
4–23
2009
150
1100 ± 377
3.22 ± 2.60
4–27
2010b
1373
1550 ± 498
3.69 ± 3.53
2–7
2011
320
1150 ± 296
2.73 ± 2.38
8–28
2012
363
1330 ± 453
3.20 ± 3.29
4–13
a Reported the average ± SD.
b Drought years. c Reported as percentage of plumes
where (median plume - PBL height) > 0.5 km and maximum
plume–BL height > 0.25 km (see text for explanation).
We find a significant positive relationship between MISR maximum plume
heights and MODIS DSI (r=0.7; p<0.01) in tropical forest and savanna
fires, with higher maximum plume heights in normal and/or wetter-than-normal (1000–1100 m) severe drought conditions (750–900 m)
(Fig. ). Consistently, on an annual basis, these two biomes show
the lowest smoke plume heights during dry years (Fig. S4 in the Supplement).
Smoke plume heights in grassland fires, however, do not show any strong
relationship with DSI (r=0.1) or clear interannual variability driven by
droughts (Fig. S4). In general, lowest median smoke heights are observed in
our dataset during the drought years of 2005 and 2010
(Fig. ), which are driven by tropical forest
observations as it is the dominant biome (Fig. S1).
The relationship between MODIS FRP and drought levels over the Amazon is not
straightforward on an annual basis as we do not observe any clear interannual
variability of FRP driven by drought in
Fig. . However, our analysis shows some
patterns when we subdivide the data by biome (Figs. and S4 in
the Supplement). For example, we find a significant positive relationship
between MODIS FRP and DSI (r=0.6; p<0.01) in tropical forest, with lower
FRP in extreme dry than normal–wet conditions (170 vs. ∼250 MW;
Fig. ). Contrariwise, savanna and grassland fires have higher
FRP in extreme and mild dry than in wet conditions (∼500 vs. 250 MW),
although the relationship is weak (r=-0.4; p<0.01). As mentioned above,
interpretation of FRP can be complicated by factors such as overlying smoke
opacity and fire emissivity .
The relationship between smoke plume height, FRP and drought conditions over
the Amazon is somewhat complex. Drought conditions over the Amazon increase
fuel flammability and the number of fires, but do not necessarily increase smoke
elevation. Drought also decreases fuel load, i.e. fuel available to burn,
especially over grassland. reported that drought in the
Amazon favours understory fires for tropical forest, which are dominated by
smouldering combustion and are linked to low-altitude smoke plumes. In
addition, spatial changes in drought location can influence the type of biome
affected and hence the type of fire regime in a given year. For example, the
drought in 2005 was located at the north-eastern and central regions, and
the large majority of the plumes recorded by MISR (65 %; Fig. S1) were from
tropical forest fires, i.e. related to smouldering and fires that inject
smoke to lower altitudes. In 2007, drought shifted to the south-eastern
region, and the majority of the plumes (60 %; Fig. S1) were from savanna
and grassland fires associated with more flaming burning conditions, i.e.
higher FRP and smoke plume altitudes. Our analysis supports this observation.
In 2005, a drought year, the smallest MODIS FRP (150 MW) and lowest smoke plume
heights (750 m) were recorded over tropical forest (Fig. ),
whereas in 2007, another drought year, larger FRP (500 and 750 MW)
associated with higher smoke plume heights (1100 and 1300 m) was recorded
over savanna and grassland fires, respectively.
In addition to the influence of drought in controlling the type of fires,
drought can also affect atmospheric conditions. We find that during drought
years, PBL heights tend to be about 200 m deeper than in wet years
(Table ). However, on an annual basis, atmospheric
stability does not vary significantly, with values of
∼3–4 K km-1, across the Amazon for the averaged biomass-burning
season (Table ). We also observe that a lower
percentage of fires inject smoke plumes into the FT in drought compared to
non-drought years (2 %–18 % vs. 4 %–28 %;
Table ). On a biome basis, tropical forest fires
inject a larger percentage of smoke plumes into the FT in wet than
extreme–dry conditions (27 % vs. 12 %, Fig. ), and
shallower PBL heights may partially explain the larger percentage of MISR
plumes detected in the FT during non-drought years. Contrariwise, grassland
fires, although with fewer observations, inject more smoke plumes into the FT
during extreme dry than wet conditions (25 % vs. 13 %,
Fig. ). These fires are associated with high FRP values in dry
conditions and this extra fire energy may be enough to produce the buoyancy
needed to lift smoke directly into the FT, regardless of the PBL height. Note
that in Fig. (right bottom), we present the data only
subdivided by MODIS DSI and biome, regardless of the year, as in the rest of
the panels in Fig. .
Consistent with previous studies that have shown significant positive
relationships between drought conditions and aerosol loading
e.g., we find a significant relationship
between MISR AOD and MODIS DSI on an annual basis in tropical forest and
savanna fires (r=-0.7 and p<0.01; Fig. ). Years with drier
conditions have almost a factor of 3 greater AOD compared with years with
wet conditions. Larger aerosol loading in drought periods is likely due to
increases in the number and size of fires e.g. and
subsequent increases in aerosol emissions. In addition, MISR AOD shows
significant interannual variability, with the largest AOD values recorded in
2005, 2007 and 2010 (0.4–0.6; Fig. ), and in
particular over tropical forest fires (0.6, Fig. S4 in the Supplement). Our
results suggest that fires during drought periods might significantly degrade
regional air quality, as they are associated with low smoke altitude and high
aerosol loading.
CALIOP smoke plume observations
To further investigate smoke rise over the Amazon, we develop a climatology
of smoke plume heights using CALIOP extinction profiles
(Sect. ). We identify a total of 1600 CALIOP smoke plumes
linked to active fires from July to November 2006–2012 (Fig. S5 in the
Supplement). Although the CALIOP climatology is one-third of the size of the MISR
climatology, these datasets agree well with respect to the temporal and
spatial distributions. Similarly to MISR, the largest number of plumes
correspond to the years 2007 and 2010 (22 % and 29 %), whereas the
lowest records are in 2009 and 2011 (4 % and 7 %). Most of the CALIOP
plumes are also recorded at the peak of the biomass-burning season
(September; 51 %) and over savanna and tropical forest (37 % and
57 %, respectively) compared to grassland.
Time series of the CALIOP smoke plumes (2006–2012) for daytime and
nighttime observations. Each dot represents the maximum (blue) and median
(black) smoke plume height above the terrain. Eighteen points for which the
CALIOP height exceeds 6 km are plotted at the top of the charts.
Figure displays the time series of derived median
and maximum heights, for daytime and night-time observations. We include both
daytime and night-time CALIOP observations to assess any day–night
differences in smoke plume rise. Similarly to the MISR climatology, we find
large variability in the CALIOP smoke plume heights; the median heights range
from 0.8 to 4.4 km (daytime) and 1.1 to 4.5 km (night-time). Maximum smoke
plume heights are obviously higher, typically spanning 1.8–5 km (daytime)
and 2.4–5.8 km (night-time). About 18 maximum plume height observations
fell above 6 km (shown saturated at 6 km in
Fig. ). Here we examine the vertical distribution
of aerosol plumes individually. Ten cases show high-altitude smoke (>6 km) in a layer that extends through the column to near-surface (Fig. S6
in the Supplement, right panel), implying that smoke from the active fire
below was lifted by fire-induced buoyancy, atmospheric processes and/or
both. The remaining cases show that high-altitude smoke was disconnected from
the surface smoke layer (Fig. S6, left panel), and we suggest that this smoke
could be residual smoke from older fires, smoke transported from the source
and concentrated in an elevated layer, aerosol that was wrongly classified as
smoke by the CALIOP algorithm, and/or the result of CALIOP not being able to
detect lower-level aerosol due to thick smoke aloft or the presence of clouds
in the column. We include these observations in our analysis, but note that
they represent only 1 % of the total observations within the climatology
and do not significantly impact the overall statistics shown here.
Average CALIOP and MISR plume heights per biome, time of the season
and dry or wet years. The burning season is divided into early
(July–August–September) and later (October–November) periods, and dry
years (2007, 2010) and wet years (2006, 2008, 2009, 2011). Bars represent
MISR plume heights (grey) and combined daytime and night-time CALIOP plume
heights (red).
Figure summarises the median and maximum heights for
the CALIOP smoke plumes per biome, season and wet or dry years. Night-time plume
heights are on average ∼ 250 m higher than daytime plume heights
(Fig. ). Differences between daytime and night-time
CALIOP observations have been attributed in the past to a low bias in the
daytime retrievals due to noise from scattered solar radiation
e.g.. Therefore, our observed difference in
daytime and night-time CALIOP plume heights might result from differences in data
quality rather than reflecting smoke diurnal variability. We combine daytime and
night-time CALIOP observations in Fig. and include the
MISR plume heights for comparison. Average CALIOP median plume heights range
from 2.1 km (tropical forest and savanna) to 2.3 km (grassland). Maximum
plume heights are similar across all biomes (∼3.2 km). Similarly to MISR,
CALIOP detects higher smoke plumes during the late burning season (2.1 and
3.3 km for the median and maximum plume heights, respectively) than the
early season (1.9 and 3.0 km). In
contrast, CALIOP observes smoke at higher altitudes during dry (2.2 and
3.4 km) than wet years (2.0 and 3.2 km). As discussed above, for the time
and location of the MISR observations, a deeper PBL is observed in dry
compared to wet years. Likewise, PBL heights at the CALIOP smoke plumes are
2.4 and 2.6 km in wet and dry years, respectively, and thus a deeper PBL
during drought conditions explains the higher altitudes observed by CALIOP
under drier conditions.
Smoke plume height values over the Amazon similar to ours were reported in
other studies of CALIOP and surface-based lidar
measurements . Using the CALIOP vertical feature mask and
AOD profiles, reported an average for the most probable
smoke height of 1.6–2.5 km for September fires. Their definition is
comparable to our CALIOP median plume height, which produced a value of
2.3±0.7 km for the September months. Over Manaus in 2008,
reported biomass-burning layers at 3–5 km elevation, with
most of the smoke trapped below 2 km. Other CALIOP smoke plume heights have
been reported over eastern Europe (1.7–6 km) and several regions and biomes
across Asia
(0.8–5.3 km).
In our study, CALIOP observes smoke at systematically higher altitudes than
MISR, with median plume heights up to 1.4 km higher (2.2 km for the maximum
plume heights). However, CALIOP still shows that the majority of the smoke is
located at altitudes below 2.5 km above ground, consistent with previous
observations from lidar measurements . Differences between
MISR and CALIOP smoke plume heights are consistent with deeper PBL heights at
the time of the CALIOP observation, as PBL is expected to grow further later
in the day, and fires might also increase in intensity. We find that PBL
height at the location and time of the CALIOP daytime smoke plumes is on average
about 1.4 km higher than for MISR smoke plumes, specifically 2.7 km for
CALIOP and 1.3 km for MISR.
found similar differences between CALIOP and MISR
(1–2.8 km) in peatland fires over south-eastern Asia. In addition, CALIOP
height retrievals are more sensitive to thin aerosol layers than MISR stereo
analysis, so CALIOP is more likely to detect low-density smoke at the plume top
: this would include smoke that might have been lifted later
in the day by convection, air mass advection or fire buoyancy
. Although we only select CALIOP plumes that are
directly linked to active fires with some confidence, fires can burn for
several days (and even weeks); in particular, deforestation fires can leave
residual smoke layers over the region for many days or even weeks. As such,
our CALIOP plume heights may include low-density smoke at higher altitudes,
possibly from old fires.
Some previous studies with MISR smoke plume height have also analysed the
altitude of smoke clouds, that is, dispersed smoke not easily associated
with a particular fire . Smoke clouds tend to
occur at higher altitudes than smoke plumes; they typically represent fire
plumes at a later stage of evolution. Over Borneo peatland fires,
show that MISR smoke clouds and CALIOP smoke plumes had
similar altitudes during their period of study. The analysis of smoke clouds
over the Amazon may support the expectation that plume heights tend to grow
even larger than observed by MISR later in the afternoon. In addition,
transported smoke is more likely to have stayed aloft longer than near-source
smoke and would therefore have more opportunity to mix upward.
Summary and conclusions
A climatology of smoke plumes from
MISR and CALIOP observations is used to characterise the magnitude and
variability of smoke altitude across the Amazon during eight biomass-burning
seasons. Biome type, fire and smoke properties (FRP and AOD), atmospheric
conditions (PBL height and atmospheric stability) and regional drought state
are included in the analysis to explore the degree to which each contributes
to the observed variability.
Analysis of the smoke plume climatology shows large differences in
smoke-plume elevation over the main biomes in the Amazon, with heights
ranging a few hundred metres to 5.2 km above ground level. Smoke from plumes
observed by MISR (10:00–11:00 LT) is mainly concentrated at altitudes below
1.5 km. As expected, smoke plume elevations are higher in our CALIOP
climatology, ranging from 0.8 to 6 km during the daytime (14:00–15:00 LT),
although the majority are concentrated below 2.5 km. We find that CALIOP
smoke plume heights are about 1.4–2.2 km higher than MISR smoke plumes due
to a deeper PBL later in the day, possibly more energetic afternoon fires and
CALIOP's greater sensitivity to very thin aerosol layers
. Thus, our CALIOP plume climatology includes
fresh smoke from active fires and low-density smoke at higher altitudes, some
of which might be from old fires. Our results show that over the Amazon, and
similarly to other fire regions studied previously, on average, smoke plume
heights tend to increase later in the afternoon due to greater near-surface
convection, greater fire intensity and possibly self-lofting. Direct
injection of smoke to altitudes higher than 6 km (middle-to-upper troposphere) did not seem to be significant over the Amazon during our study
period.
For our main biomes in the Amazon, smoke plume heights are substantially
lower over moist tropical forest fires (0.8 km, maximum plume height
definition) than grassland fires (1.1 km), although grassland fire smoke plumes represent a small fraction (4 %) of cases in the climatology. The
MISR and CALIOP Amazon plume climatologies show a well-defined plume height
seasonal cycle in the main biomes, with larger heights toward the end of the
burning season. Using MODIS FRP and MERRA-2-estimated atmospheric stability
conditions, we determine that higher smoke-plume elevations in
October–November are the result of the combination of more intense fires and
a less stable atmosphere. Less than 5 % of the fires inject smoke into
the FT (i.e. median plume–PBL height > 500 m) using a conservative
criterion, although an additional 15–19 % of the fires may inject some
smoke based on a looser criterion (i.e. maximum plume–PBL height
>250 m). This fraction increases throughout the burning season, with about
15 %–40 % of the fires injecting smoke above the FT in November.
Previous studies have shown a direct connection between drought, large-scale
climate processes (e.g. ENSO) and the number of fire occurrences
e.g.. We find a negative relationship
between MISR plume heights and drought conditions in tropical forest fires,
as wet years show smoke plume altitudes 300 m higher than dry years.
reported that drought conditions over the Amazon favour
understory fires, for which smouldering combustion dominates, favouring lower
smoke injection heights. In addition to low-altitude smoke, we find that
drought conditions are also related to deeper PBL heights, which can reduce
the frequency with which smoke is able to reach the FT.
A relationship between fire intensity (as approximated by FRP) and drought
conditions is not clear in our study. We detect the highest FRP values in
grassland fires during dry periods and the lowest FRP values for tropical
forest fires under similar dry conditions but without a significant
relationship between FRP and DSI, nor any interannual variability of FRP
driven by droughts. This lack of relationship may be due to the different
locations of drought in different years, the types of fire recorded by MISR
in a given year, and/or the low performance of MODIS FRP under dense smoke
conditions.
Consistent with previous observations, we find larger MISR AOD during drought
compared to non-drought periods. Our analysis confirms the important effect
that biomass burning has on smoke aerosol loading over the region, from the
surface to the lower free troposphere. Strong land management policies that
control fires over the Amazon may become crucial as increases in drought
frequency are projected in a future climate ; this would
have important consequences for fire activity and thus air quality.
A variety of smoke injection height schemes are used to represent fire
emissions over the Amazon, from fire emissions injected below 3 km
or into the model-defined PBL to
complex plume-rise models, in which a significant fraction of emissions are
in some conditions injected above 6 km . Recent efforts
have shown the value of using MISR-derived smoke plume heights to initialise
model fire emission injection . Over the Amazon,
show that a new injection scheme based on MISR plume-height
observations, which included vertical smoke profiles used in this study
, provide a better representation of CO observations over the
region. With a very narrow swath but sensitivity to subvisible aerosol,
CALIOP tends to sample aerosol layers downwind, providing information
complementary to the near-source mapping offered by MISR .
Thus, observations from both CALIOP and MISR provide a way to study smoke
plume heights across the Amazon during the biomass-burning season.
Ultimately, this information will help improve the representation of biomass
burning emissions in Earth system atmospheric models and should aid our
understanding of the feedbacks between drought, terrestrial ecosystems and
atmospheric composition over the region.
A next step in our work includes the evaluation of the influence of smoke
plume height on the atmospheric composition over the Southern Hemisphere
based on insights from the analysis of the smoke plume climatology across the
Amazon and further application of this approach to other geographic regions.