AMTDAtmospheric Measurement Techniques DiscussionsAMTDAtmos. Meas. Tech. Discuss.1867-8610Copernicus GmbHGöttingen, Germany10.5194/amtd-8-443-2015A novel retrieval of daytime atmospheric dust and volcanic ash heights through a synergy of AIRS infrared radiances and MODIS L2 optical depthsDeSouza-MachadoS.sergio@umbc.eduStrowL.https://orcid.org/0000-0001-5999-3519MaddyE.TorresO.ThomasG.https://orcid.org/0000-0002-7341-1420GraingerD.https://orcid.org/0000-0003-0709-1315RobinsonA.Joint Center for Earth Systems Technology/Physics Department, University of Maryland, Baltimore County, Baltimore, MD, USARiverside Technology, Inc, College Park, MD, USANASA Goddard, Greenbelt, MD, USAAtmospheric, Oceanic and Planetary Physics, University of Oxford, Oxford, UKRadiation Oncology and Molecular Radiation Sciences, Johns Hopkins Hospital, Baltimore, MD, USAnow at: Rutherford Appleton Laboratory Space, STFC Rutherford Appleton Laboratory, Harwell Science and Innovation Campus, Oxford, UKS. DeSouza-Machado (sergio@umbc.edu)13January20158144348510November201410December2014This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/This article is available from https://amt.copernicus.org/preprints/8/443/2015/amtd-8-443-2015.htmlThe full text article is available as a PDF file from https://amt.copernicus.org/preprints/8/443/2015/amtd-8-443-2015.pdf
We present a novel method to retrieve daytime atmospheric dust and
ash plume heights using a synergy of infrared hyper-spectral
radiances and retrieved visible optical depths. The method is
developed using data from the Atmospheric Infrared Sounder (AIRS)
and Moderate Resolution Imaging Spectroradiometer (MODIS), both of
which are on NASA's Aqua platform, and lends itself to also
a χ2 height derivation based on the smallest bias between
observations and calculations in the thermal infrared window. The
retrieval methodology is validated against almost 30 months of dust
centroid heights obtained from the Cloud-Aerosol Lidar and Infrared
Pathfinder Satellite Observations (CALIOP) data, and against ash
plume heights obtained from the Advanced Along-Track Scanning
Radiometer (AATSR) after the Puyehue Cordon Caulle volcanic eruption
of June 2011. Comparisons are also made against Goddard Chemistry
Aerosol Radiation and Transport (GOCART) climatological aerosol
heights. In general there is good agreement between the heights
from the CALIPSO data and the AIRS/MODIS retrieval, especially over
the Atlantic and Mediterranean regions; over land one there are more
noticeable differences. The AIRS/MODIS derived heights are within
typically 25 % of the CALIOP centroid heights.
Introduction
The Earth's atmosphere consists of well mixed and stable gases such as
nitrogen and oxygen, trace and greenhouse gases whose concentrations
in time and space are constantly changing, and clouds and
aerosols. While the gaseous atmosphere is mostly transparent to
incoming solar radiation, the Outgoing Long wave Radiation (OLR) in
the infrared is strongly absorbed and re-emitted by the trace and
greenhouse gases.
In addition clouds and aerosols also significantly affect the incoming
solar and outgoing thermal radiation. For example clouds and aerosols
scatter and absorb both solar and thermal radiation. Radiative
balance is affected by these atmospheric particles in ways that are
not fully understood, and indeed the radiative effects of naturally
occurring aerosols such as dust have not yet been determined
accurately enough so as to be able to state whether the
dominant aerosol radiative forcing effect is one of cooling or
heating. The dust scatters solar radiation and absorbs terrestrial
radiation before eventually falling out of the atmosphere; the local
heating changes air and surface temperatures and relative humidity in
the vicinity of the dust, affecting tropical weather and hurricane
formation; research studies of the effect of dust demonstrates the
changes to atmospheric geophysical variables ,
though the current AIRS L2 products do not account for the scattering
effects of aerosols . Aerosols indirectly affect climate
by serving as nuclei for cloud formation, and as sites for chemical
processes to occur .
Fine aerosol particles usually come from chemical processes and can
cause respiratory problems. Larger aerosol particles, predominantly
from atmospheric dust and volcanic events can limit
visibility. Atmospheric dust is emitted by the action of wind blowing
over arid regions; the dust emitted from the great deserts such as the
Sahara and Gobi, is usually lofted into the troposphere and
transported across continents by the prevailing
winds. Dust can affect the biochemistry of ocean coral reefs
, and act as a nutrient source for
phytoplankton. Springtime Asian “yellow” dust episodes cause health
problems and blanket whole urban and farm areas, with associated
cleaning costs and deposition of sand over good soil.
Eruptions from volcanoes impact human life both directly and
indirectly. Indirect effects come from the ejected gases and rocks;
the rock/ash plumes affect radiative forcing before they
fall/precipitate out of the atmosphere in a few months. Sulfuric gases
ejected high into the stratosphere become sulphate aerosols which can
remain in the atmosphere for up to 2–3 years; these aerosols
reflect incoming sunlight, which can cause stratospheric heating and
tropospheric cooling. Chemical reactions involving
chlorofluorocarbons (CFCs) on the surface of the aerosols can destroy
stratospheric ozone . Though volcanic events are
more isolated than dust storms, their direct impacts range from loss
of life and destruction of property. Recent volcanic events have also
led to financial impacts from the disruption and/or cancellation of
large numbers of flights whose paths are expected to cross the ash
plumes. Nine global Volcanic Ash Advisory Centers (VAAC), each having
well defined geographic regions to monitor, are responsible for
providing information about ash clouds and sulfur dioxide (SO2)
emissions that could pose hazards for the aviation industry, as winds
can transport fine ash particles and SO2 many miles away from the
actual eruption; these fine particles can be missed by aircraft radar
and clog or severely damage jet engines. The ash plumes cannot be
visibly seen at night, while during the day the plume may resemble
a water vapor or ice cloud. The VAACs use advection models to predict
the distribution of ash and SO2, driven by Numerical Weather
Prediction models. The accuracy is determined by the initial
conditions, which are the near-source injection heights of the ash.
For these and other reasons, detection and study of atmospheric clouds
and aerosols is important. Instruments designed to observe radiative
effects and retrieve aerosol and cloud properties operate mostly in
the Near Infrared (NIR) to Visible (VIS) to Ultraviolet (UV) (3 to
0.2 µm), as this range of wavelengths is well suited to
detect the scattering and absorptive effects both of small and large
particles in the atmosphere. When mounted on satellites, these
instruments cover huge swaths of the Earth's surface during daytime
overpasses, and are mostly insensitive to the cloud and aerosol layer
height. Conversely active instruments such as lidars and radars are
very sensitive to the height and to some extent can differentiate
between aerosol species; however the current generation of
satellite-borne active instruments have very limited area
coverage. Together, substantial progress has been made in the
retrieval of macroscopic aerosol and cloud parameters such as optical
depths and effective particle sizes (see for example the MODIS
products described in , and ), and
single scattering albedo and aerosol absorption optical depth from
near-ultraviolet (near-UV) observations from the Ozone Monitoring
Instrument (OMI) .
Though less sensitive than the above, passive infrared instruments
that operate in the 15 to 4 µm range work day and night,
and “see” the radiative effects of larger particles such as water
droplets and cirrus particles, as well as atmospheric dust and
volcanic ash. Additionally most clouds affect the thermal infrared
spectrum in the CO2 temperature sounding region which means
other than sub-visible clouds, cloud heights can usually be determined
via the CO2 slicing method (see for example
). However the infrared spectral signature of aerosols is
quite different, and there is still much to be done in operational
retrieval of aerosol layer heights; more accurate determination of
heights could for example lead to improved understanding of dust-cloud
interactions and modeling of dust sources and dust transport
, as well as improve aerosol retrievals of UV
instruments which have sensitivity to aerosol height .
When the appropriate refractive indices are used, Mie scattering
theory shows that the retrieved optical depths in the infrared are
about 2–4 times smaller than those retrieved in the visible
. In order to retrieve an accurate optical
depth using infrared radiances, dust/ash retrievals require both an
estimate of the atmospheric temperature and humidity profiles, as well
as accurate knowledge of the dust layer height. Previous work on
obtaining height estimates of dust has ranged from a look-up table
approach , to assuming climatological heights
such as that from Goddard Chemistry Aerosol Radiation
and Transport (GOCART) , to performing an iterative
retrieval which minimized the observed – calculated bias
radiances as a function of height. Recent work also shows the
viability of retrieving a dust vertical profile containing about 1.5
pieces of information, or slightly more than knowledge about the peak
of the profile .
In this paper, instead of obtaining optical depths using infrared
radiances, we turn the primary focus for daytime observations into
finding the mean aerosol height (i.e. 1 piece of information) by using
the MODIS L2 retrieved optical depths as a constraint. This
immediately allows us to have reliable estimates of dust- (and ash-)
heights over large areas of the planet, rather than relying on
climatology or sparser spatial measurements for instruments such as
CALIPSO. Since our retrieval is based on loops to find the height at
which the IR : VIS optical depth ratio is 1:4, we are also able to
simultaneously assess a height retrieval based on where the minimum
χ2 between observations and calculations occur; this same
looping can be used for a χ2 retrieval for night scenes, or when
visible ODs are otherwise unavailable, such as over sun glint regions.
We demonstrate the dust loading and height retrieval using co-located
AIRS/MODIS data. The estimates of plume heights and ash/cirrus loading
are validated by comparison against other satellite-based
instruments. Together, the results should prove valuable for
operational use by VAACs for volcanic ash detection and comparison
against models of ash dispersal and deposition, for dust source
modeling and transport, and also for improving atmospheric retrievals
in the presence of dust/ash.
The rest of the paper is organized as follows. We first describe the
AIRS instrument, followed by a short discussion of the dust flag
used in the AIRS L1 and L2 products. This is followed
by an outline of the retrieval algorithm, and a mention of the other
instruments used in this paper. The algorithm is tested by retrieving
3 years of dust heights using AIRS data, with validation from
a co-located lidar instrument. A second application to determine ash
plume heights from a volcanic eruption in S. America is also described
and validated.
The AIRS instrument
AIRS instrument on board NASA's polar orbiting Aqua
satellite was designed to provide improved temperature and humidity
profiles for numerical weather prediction and long-term climate
studies. An overview of the AIRS instrument and clear sky radiative
transfer algorithm (AIRS-RTA) on which the level 2 retrievals are
based, are given in . AIRS has 2378 infrared
channels, broadly covering the 649–2665 cm-1 spectral
range. The full widths at half maximum satisfy ν/δν≃1200, with the noise equivalent change in temperature (NEΔT)≤0.2K. AIRS has a 13.5 km nadir footprint.
Dust/ash detection
Refractive indices of different atmospheric scattering species lead to
distinct spectral signatures which impact measured InfraRed (IR)
radiances in distinct ways. With (almost) complete high-spectral
coverage of the 9–12 µm atmospheric window spectrum, data
from AIRS (and other hyperspectral infrared sounders) have been
demonstrated to contain much information when the particles are
typically larger than 1 µm in effective radius. Examples
include the retrieval of optical depths τ(ν) of clouds
and mineral based aerosols (dust, volcanic
ash) .
Silicate based absorbers such as desert dust and volcanic ash (basalt,
andesite or obsidian) absorb less at the 800 and 1200 cm-1
regions than at 960 cm-1, and on instruments on board high
altitude aircraft or orbiting satellites cause a “V” shaped
depression of the radiances (or equivalent Brightness Temperature
(BT)) measured across the thermal IR window
. This spectral
feature allows infrared spectral data to be queried for dust or
volcanic ash contamination day or night. Long term monitoring of the
dust flag implemented in the AIRS L1 and L2 products shows that it
performs very well over ocean for (visible) optical depths larger than
about 0.15, though depending on the dust source, the flag may not
trigger during some episodes where the dust is coming off the
northwest coast of Africa. Conversely surface emissivities serve to
make the product have less skill over land. The black curve in
Fig. shows an example of extreme infrared spectral
measurement obtained by the AIRS instrument in the vicinity of the
June 2011 Puyehue eruption over S. America; notice the brightness
temperature in the window region goes down to almost 220 K,
which is the temperature of the tropopause, suggesting the ash is
optically thick and at very high altitudes. The gray curve of
Fig. shows a more typical example of infrared
spectral measurements obtained for dust or ash contaminated scenes;
note this is also for high altitude ash, but the brightness
temperature depression is much less, which illustrates the complexity
in separating out height from aerosol loading in infrared
retrievals. Finally the light gray curve shows a typical measurement
over clear ocean. Different aerosol absorbers would show similar
V-shaped depressions but would have their own characteristic spectral
signatures see for example plots in.
Also designed for the same purposes, the Infrared Atmospheric Sounding
Interferometer (IASI) on board the Metop-A polar orbiting satellite
crosses the equator twice daily, with a 9:30 a.m. equatorial
ascending node. Recently the CRiS (Cross track Interferometric
Sounder) was launched on board the Suomi NPP satellite, in an orbit
similar to that of Aqua AIRS; designed for same purposes as AIRS and
IASI, all three instruments have multiple channels in the thermal
infrared window. With ∼2000km swaths, the ∼90 min Aqua, Metop-A and Suomi NPP orbits each yield almost twice
daily coverage of every spot on Earth; in particular dust or volcanic
ash in extreme latitudes can be more easily detected by an orbiting
satellite than by a geostationary satellite looking mainly over one
location. As infrared data can be acquired day or night, together
these three infrared instruments potentially offer six daily views
related to a dust or volcanic event, as long as there is no thick
cloud overlying the aerosol.
Retrieval algorithm for AIRS
The MODIS constrained height retrieval algorithm is a straightforward
adaption of the one used in , the main parts of which are
summarized here. The Schwartzchild Equation (SE) models the radiative
transfer through the atmosphere . Dividing the
atmosphere into the ∼100 layers used in the clear sky AIRS RTA
(which are 0.25 km thick at the surface and about
0.35 km thick at 15 km), we solve this equation by
recasting the cloud/aerosol scattering parameters into an effective
optical depth . The accuracy of the code is described in
, where retrieved AIRS optical depths were compared
against co-located aerosol optical depth retrievals from the other
A-Train instruments operating in the visible and/or ultraviolet, for
the case of a February 2007 Mediterranean dust storm. The accuracy of
the radiative transfer algorithm is sufficient to account for the
effects of clouds and ash/dust on infrared radiances, and is dominated
by errors when ascribing the height of the cloud/aerosol layer, as
well as in refractive indices. The scattering algorithm has been
integrated into the AIRS-RTA, henceforth called
SARTA_scatter, such that the RTA retained its speed and
accuracy. A 2378 channel run takes ≤0.2 s on a 2.7 GHz
machine, and would be proportionally less for the handful of channels
used for the retrieval.
The retrieval algorithm operates per AIRS
granule, which is a 6 min span over which AIRS spectra are obtained,
the instrument scanning ±48∘ on either side of nadir. The
dust flag allows us to subset which of the spectra is dust
contaminated, following which water vapor, ozone and temperature
profiles and surface parameters needed to compute radiances are
co-located using the nearest quarter degree grid point in the European
Center for Medium Range Weather Forecasting (ECMWF) forecast or
analysis model fields. Surface emissivity comes from
over ocean, and from the MODIS-derived land database
. The aerosol (dust or ash) is assumed to uniformly fill
the FOV and so we do not weight the radiance based on the clear
vs. aerosol fractions. For dust, refractive indices come from the
Saharan Dust optical parameters (collected in Barbados) compiled in
while for volcanic ash, basalt refractive indices are
used . The refractive constants of andesite and basalt
are quite similar, so differences in size distributions would dominate
the scattering parameters. Mie scattering parameters are computed
using a uni-modal log normal particle size distribution (σ =
2 µm).
The retrievals use a small subset of the thermal infrared AIRS
channels . For a fixed aerosol height and effective
particle size, Newton–Raphson methods are used to retrieve aerosol
loadings. The loadings Γj in gm-2 are related to
the thermal IR dust optical depth τ by
τ(ν)=τdust/ash(ν,〈rme〉)×Γj
Here τdust/ash(ν,〈rme〉)
is the optical depth for an aerosol loading of 1 gm-2 and
mean effective particle radius 〈rme〉. A fixed
maximum number of iterations (3) were used in the retrievals for each
height. The OD retrieval is performed for a set of discrete heights
z ranging from 1.5 to 6.0 km in steps of 0.5 km for
dust, while for volcanic ash plumes the heights z range from 2 to
15 km in steps of 1 km. The retrieval has been
parallelized for the latitude, longitude (lat,lon)
pairs of the dust-contaminated pixels. As a rule of thumb, given
a measured radiance spectrum having the characteristic “V” shaped
depression, the height/loading combinations are such that if the
aerosol is placed at a low altitude in the retrieval, the
corresponding aerosol loading needed to optimize the fit is larger
than if the aerosol were placed at a higher altitude; the highest
sensitivity occurs lower in the atmosphere, where one tends to lose
the surface contrast.
After running off the optical depth retrieval for each height step
z, a χ2(z,lat,lon) value quantifying the
difference in observations and calculations for a few channels in the
thermal infrared window is computed for each aerosol contaminated
(lat,lon) pixel; after all heights had been looped
over, the optimal height zchi(lat,lon)
at which the minimum χ2(z) occurred is saved. At any retrieval
height the accuracy of the χ2(z,lat,lon)
values depend on the accuracy and appropriateness of the scattering
parameters which were used; this also impacts the accuracy of the
optimal height zchi(lat,lon).
Simultaneously for data obtained during the daytime, the dust
contaminated AIRS observations were co-located to MODIS L2 optical
depths (see below) and the height
zMODIS(lat,lon) at which the MODIS/AIRS
optical depth ratio was f0=4 is also saved; if the scene was
night time the MODIS based height was assigned a NaN value. We point
out that if the AIRS dust was located in a MODIS sun-glint region for
which there is no retrieval, a 2d (latitude/longitude) interpolation
of the available MODIS L2 optical depth data was performed, so as to
obtain a MODIS-based height estimate. Most dust occurs in the topics
or mid-latitudes, for which MODIS aerosol retrievals are available; an
issue could arise for high latitude volcanic ash, as the MODIS aerosol
algorithm is not used for large solar zenith angles. The accuracy of
the daytime MODIS-derived heights would be mainly determined by the
accuracy of the co-located MODIS L2 optical depths, and to a lesser
extent the scattering parameters used in the AIRS retrieval scheme.
A set of monthly GOCART aerosol climatological heights (which does not
distinguish between day or night)
zGOCART(lat,lon,month) that has
been made available to us, are also co-located and saved for each
pixel. This means the retrieval package yields up to three dust/ash
heights.
Height retrieval sensitivity
The 961 cm-1 AIRS channel is typically most affected by
silicate-based aerosols such as volcanic ash or desert dust, as it is
spectrally close to the peak of the aerosol absorption, but still lies
outside the 10 µm ozone band which also affects TOA
radiances. Conversely the 1231 cm-1 channel is far less
affected by aerosols. Together, this means the Brightness Temperature
Difference (BTD) between these two channels (BT1231-BT961) is
a very good indicator of dust presence, as exploited in the dust flag
mentioned earlier. The BTD depends both on the aerosol loading and
height – for a fixed dust column loading (in gm-2),
simulations using our scattering code show the BTD varies almost
linearly with height. For example for a dust loading of
1 gm-2 the BTD varies (almost linearly) from
0.2 K at 1.5 km height, to 4.9 K at
10 km height. We note here that when the height is increased
to the tropopause, the sensitivity is lost – the BTD remains the same
for a given dust loading.
For any geophysical profile, this information can be turned into
a height sensitivity as follows. A dust loading of 1 gm-2
corresponds to a 10 µm optical depth of 0.18. Looping over
both heights and over aerosol loadings (in gm-2), we can
build up a 2-D matrix M of how the BTD varies with the
heights and AIRS optical depths. Using a factor f0 of 4 to change
the AIRS optical depth to MODIS optical depth, means we now have
a table of values for how the AIRS BTD changes with dust height and
MODIS AOD (for f0=4). We can use the same matrix M
to change to another set of MODIS optical depths, but with a factor
f, and use these to answer the question: for a fixed observed AIRS
BTD, and fixed retrieved MODIS L2 OD, how does the retrieved height
h change as the factor f relating the infrared to visible optical
depths is changed? Then
δ(BTD)=∂(BTD)∂hδh+∂(BTD)∂τMODISδτMODIS
where
the MODIS optical depth is related to the AIRS optical depth by
τMODIS=f0τAIRS, f0=4, and the heights h
are in km. Since the BTD is necessarily the same whatever value of f
is used, δ(BTD)=0, while δτMODIS=τAIRSδf, where we ignore errors in the MODIS L2 product. This gives
δh=-∂(BTD)∂τMODIS∂(BTD)∂h×τAIRSδf
As mentioned above, we use f0=4 and expect that value to vary
between 3 and 5, implying δf=±1; the partial derivatives
can easily be numerically evaluated, from which we can obtain δh. Figure illustrates the methodology. The left
panel shows the (AIRS) BTD (values noted from the colorbar) as
a function of height (in km, horizontal axis, in steps of
0.125 km) and MODIS AOD (vertical axis), where we used f0=4 to convert the AIRS infrared optical depths to MODIS AOD. One sees
that for low heights, the BTD does not change for smaller OD values;
the changes are much smaller than when the dust is at higher
altitudes.
The black and red crosshairs illustrate two points we chose – the
black crosshairs corresponds to a hypothetical BTD of +5 K
while the MODIS AOD is 2, and translates to a dust layer height of
4.125 km, while the red crosshairs corresponds to
a hypothetical BTD of +5 K while the MODIS AOD is 1, and
translates to a dust layer height of 6.125 km. Not shown here
is how these crosshairs move when we use a value of f= 3 or
f= 5; the former makes the black/red crosshairs move to
3.625 km/4.625 km while the latter makes the
black/red crosshairs move to 4.625 km/7.500 km. This
gives a sensitivity of about 0.6 and 1.3 km for the black and
red cross hairs respectively. The right hand panel shows the computed
uncertainty using the expressions given above for a uncertainty
δf= +1, and one sees from the shading at the crosshairs
that we get good agreement with the expected numbers.
As the climatology is changed (from example from tropical to US
Standard to Mid Latitude Summer), one notices variations in the
2d-sensitivity plot, but the overall features remain the same; namely
the larger sensitivity at low optical depths/high altitudes, compared
to larger optical depths/lower altitudes. This same methodology can
be applied to the NWP fields associated with any pixel. However on
a granule basis, it is easier to average the NWP profiles and do just
one sensitivity study whose results can be applied to all dust/ash
contaminated pixels present, at most separating out land from ocean
scenes.
Figure illustrates the multi-valued nature of the
BTDs – for example the crosshairs are for the same BTD of
5 K, but occur at different (optical depth, height) pairs; one
sees almost any BTD combination can be found at multiple
pairings. Plots with the same qualitative features can be made for
other pairs of thermal infrared channels, which would slightly change
the locations of the (optical depth, height) pairs. This makes
a χ2 retrieval feasible. However the values of χ2=∑i(obs(i)-cal(i))2 would be affected by errors in the
calculations for example due to incorrect size distributions and
scattering parameters. This makes the χ2 less robust than the
AIRS/MODIS synergy, and also harder to assign uncertainties to. Height
sensitivity for the χ2 retrieval was assessed by studying how
χ2 varied with height for a number of AIRS pixels; a general
flattening of the curve was typically observed, spanning about
±1.5 km.
Other instruments used in this study
Data products from three instruments are also used in this paper. The
visible optical depths used to constrain the daytime infrared
retrievals come from NASA's MODIS instrument, which is on the same
Aqua platform as the AIRS instrument. The Aqua satellite is part of
the A-train constellation, which consists of six satellites in
sun-synchronous orbits at an altitude of approximately 700 km
above the Earth at an inclination of 98.14∘. The afternoon
(A)-train satellites cross the equator at roughly 1:30 p.m. (local
time) in an ascending (daylight) mode. The orbit times are 90 min
with a repeat cycle of 16 days. Dust height validation comes from
using data products from Cloud-Aerosol Lidar with Orthogonal
Polarization (CALIOP), a lidar based instrument on the CALIPSO
satellite which is also part of the A-train satellite constellation;
this means the CALIPSO platform is on the same orbit as the Aqua
platform, though it lags behind by about a minute.
Ash plume height comparisons come from the Advanced Along-Track
Scanning Radiometer (AATSR) on board the the European Space Agency
(ESA) ENVISAT satellite. This satellite was launched on 1 March 2002
into a sun-synchronous polar orbit at an altitude of 800 km,
at an inclination of 98.55∘, crossing the Equator at
10:00 a.m. local time in a descending mode. It orbits the Earth in
about 101 min with a repeat cycle of 35 days. The ENVISAT mission was
ended in May 2012 after contact was lost with the satellite.
MODIS
MODIS is a high spatial resolution instrument (≤1km)
that acquires data in 36 spectral bands ranging from the visible to
the TIR. The MODIS Level 2 aerosol products assume spherical
particles to retrieve primary products, from which a number of other
parameters are derived and reported such as mean particle size,
fine/coarse mode ratio and Angstrom coefficients . All
six visible and near infrared channels are used to find the best fit
between a combination of models in a look up table and the measured
radiances. Once the aerosol model is derived, the optical depth is
retrieved from the 865 nm channel since it has the smallest
uncertainties from background particles and water-leaving
radiances. For this work, we use the Optical_Depth_Land_And_Ocean
product, which is the Aerosol Optical Thickness at 0.55 µm for both
Ocean (best) and Land (corrected) with best quality data (QA
Confidence Flag = 3), which is a combination of the over ocean is
the Effective_Optical_Depth_Average_Ocean total (fine+coarse) OD
product and the MODIS Deep Blue retrieval algorithm
. Comparisons between the Deep Blue algorithm and
AERONET sun photometers show agreement to within
20 % for dust retrievals over (bright) land surfaces
. The 10 km aerosol product was co-located
against pixels identified as dust/ash by the AIRS dust flag as
needed. In this paper we use the MODIS L2 Collection 051 data.
CALIOP
The CALIOP lidar on CALIPSO provides optical properties
and altitude resolution of clouds and aerosols, including dust. CALIOP
was launched in late April 2006 and became operational in June 2006.
It is a two-wavelength lidar that transmits and receives
back-scattered light at laser wavelengths of 532 and
1064 nm. CALIOP also has a polarization channel for the
532 nm wavelength. The CALIOP laser has a 25.25 Hz
repetition rate with a 70 m surface footprint. The data have
30 m vertical resolution from the surface to 8 km
altitude, and 60 m resolution above, with minimum horizontal
resolution of a single profile of 1/3km. A typical
horizontal averaging interval is 5 km (15 profiles) for
aerosols and dust. CALIOP is a nadir-only instrument, covering far
less of the globe than AIRS or MODIS. CALIPSO follows a similar ground
track to Aqua, offset by 170 km from AIRS nadir, and lagging
by about a minute. The L2 products include cloud and aerosol detection
information on a 5 km horizontal grid; the information is
broken into aerosol subtype (for example dust, smoke, marine aerosols)
and the optical properties are divided into for example extinction and
optical depth . For this paper the L2 weighted mean
aerosol heights were daily co-located against MODIS L2 data; we note
these heights were then averaged over a month for use as
a climatological database with the OMI aerosol retrieval algorithm
. No differentiation was needed to be made between
different aerosol subtypes seen by CALIOP as the AIRS dust flag allows
us to select the co-located dust/ash heights.
AATSR
AATSR was a multi-channel imaging radiometer which provides two views
of the Earth's surface, one centered at nadir and the other at
55∘ from zenith, providing collocated views with atmospheric
path lengths differing by a factor of two. The instrument provided
measurements of reflected and emitted radiation in seven channels
centered at 0.55, 0.66, 0.87, 1.6, 3.7, 11 and 12 µm, with
a 1 km nadir resolution and a 512 km swath. AATSR was
aboard ESA's ENVISAT platform, which was operation from mid-2002 until
April 2012 and provided a 10:30 a.m. local solar time sun-synchronous
orbit.
AATSR was the third in a series of Along-Track radiometers designed to
provide high precision and accuracy measurements of sea surface
temperature, however they have been applied to the retrieval of a wide
range of atmospheric and surface parameters including cloud and
aerosol properties , as well as land surface temperature and
classification. In particular, the parallax between the two views
allows the retrieval of so called stereo cloud top height, through
purely geometric and simple image processing methods see for
example. present a Stereo Ash Plume Height
retrieval algorithm that uses the distinctive ash (and mineral dust)
signature between the 11 and 12 µm channels (corresponding to 910 and
833 cm-1 in Fig. 1) to provide high contrast images of
volcanic ash plumes, aiding in the stereo imaging matching. This
algorithm, amongst other data, was tested on the Puyehue-Cordón
Caulle eruption of June 2011.
The AATSR instrument provides height retrievals over the peak
Puyehue-Cordón Caulle eruption period; CALIOP data was mostly
unavailable during this time since the instrument had been turned off
due to a solar flare event
(http://www-calipso.larc.nasa.gov/tools/instrument_status/).
Results and discussions
In this section we show the results of the MODIS-constrained and
χ2-daytime AIRS height retrievals, and compare them to available
data as well as to GOCART climatology. The first example spans about
3 years of dust height retrievals, for which we co-located
mean aerosol layer heights from CALIOP data for about half that
time. The second example is retrieval of ash plume heights from the
June 2011 Puyehue eruption in S. America; CALIOP data is unavailable
for this time, and so we use AATSR height retrievals for validation.
Dust heights from January 2006 to December 2009
Here we show a summary of height retrievals between January 2006 and
December 2009; for 30 months within this time period
(July 2006–December 2008) we co-located CALIOP mean aerosol heights
against MODIS L2 daytime (ascending A-Train mode) data
. We separate out the results into four regions:
Atlantic, Mediterranean, Pacific, and Africa/Arabia. The first three
are mostly over water while the last is mostly over land masses. For
all the figures in this section, blue circles (and shaded error bars)
correspond to the mean (and standard deviation) of the monthly GOCART
climatology; similarly red crosses correspond to the AIRS/MODIS height
retrievals, green squares to the χ2-based AIRS retrievals, while
black diamonds correspond to the mean CALIOP aerosol heights.
For each region, plots with two panels are presented. The left hand
panel shows the seasonal cycle over the 2006–2009 period, together
with the month to month variation of heights during the seasons. The
right hand panel shows the mean over the 36 months and the
corresponding variation of the mean from year to year, which is less
than the individual monthly variation. We also note that the GOCART
climatology varies both temporally and spatially, and so depending
where the dust storms were found year to year, there could be
variations in the averaged GOCART climatological heights.
Figure shows the temporal height variation
over the Atlantic region. Clearly seen in the left panel is the
seasonal cycle, with the aerosol layers at about 2 km in the
late fall/winter, and rising to about 4 km in the summer. For
the years considered here, the climatology shows a slight phase shift,
typically lagging behind the data by about a month or two, but on
average is in general agreement with the data. The right panel shows
that in general the AIRS MODIS and χ2 retrievals agree with each
other over the Atlantic and in general agree with the CALIOP heights;
however the GOCART climatology places the dust lower in the spring and
summer months, a manifestation of the phase shift evident in the time
series, and as seen in Table 1 serves to lower the correlation with
the CALIOP data.
The left panel of Fig. shows the temporal height
variation over the Pacific region, and shows it is mostly limited to the
expected Springtime Asian dust. Also seen is the GOCART climatology (blue
curve) typically being between 4–6 km, while both the CALIOP and
AIRS heights suggest lower dust altitudes (2 km) in late winter,
rising to about 4 km by late Spring. Averaged over the 3 year
time period, the right panel clearly shows the GOCART climatology places the
dust too high at all months. In addition in the early Spring the AIRS derived
heights are slightly higher than those from CALIOP, and almost 1 km
higher in the summer. One also sees a negative trend in the AIRS derived
heights over the 4 year interval.
Figure shows the temporal height variation over
the Mediterranean region. Especially in the summer, the CALIOP data is
generally slightly higher than that retrieved from the AIRS data,
while the GOCART climatology falls in between the CALIOP and AIRS
heights, being higher in the early Spring and lower in the summer, but
overall agreeing with the CALIOP and AIRS derived heights.
Finally Fig. shows the temporal height
variation over the African and Asian regions, typically the Sahara and
Middle Eastern deserts. The GOCART climatology in general shows the
lowest heights, while there are large differences in the MODIS/AIRS
vs. χ2 based retrievals, which we attribute both to land
emissivity issues and potential inaccuracies with MODIS Deep Blue
algorithm over land; for a few months the average χ2 retrieval
is closer to the CALIOP data than the AIRS/MODIS retrieval. This is
more clearly seen in the right panel of the figure, which shows that
of all the four regions considered, the largest differences between
the heights are over the African/Asian land masses, where typically
the χ2-based AIRS height was the highest, especially in the late
summer months, while the CALIOP heights lay in between these and the
GOCART climatology. Figure 3e of suggests the MODIS
Deep Blue algorithm slightly overestimates lower optical depths, and
underestimates optical depths greater than about 2; the former case of
OD overestimation would lead to the AIRS/MODIS height algorithm
placing dust layers lower in the atmosphere.
In summary, the GOCART aerosol climatological heights compared well
against the MODIS based heights and the χ2 based heights, except
noticeably for the springtime Asian dust over the Pacific, when the
GOCART heights were much higher than the other two heights, and to
a lesser extent over the Africa/Middle East land masses. All four
heights showed similar seasonal height variations. The correlations
between the CALIOP heights and the rest of the heights for the monthly
averaged data are shown in Table 1.
In particular the χ2-based retrieval produced similar results to
the MODIS-based height retrieval, which is promising for applying the
algorithm for nighttime scenes. This is summarized in the left portion
of Table 2, where one also sees that over land the χ2-based
retrieval differed the most from the other heights. Though not shown
here, plots similar to the right hand panels of
Figs. to ,
but for the variability of the monthly heights, yields the statistics
shown in the right portion of Table 2, indicating that the variability
in the χ2 retrieval can almost be double that of the other data
(MODIS- based, CALIOP and GOCART), while that of the GOCART
climatology is least.
Ash plume heights for the Puyehue-Calderon June 2011 eruption
Chile's Puyehue-Cordon Caulle Volcanic Complex (40.5∘ S,
72.1∘ W) belongs to the Lago Ranco chain, which is composed
of basalt and rhyolite. An eruption commencing 3 June 2011, was
violent enough for plumes to be ejected 11 km or more into the
atmosphere; less than 24 h later ash fall was being reported in
Argentina, east of the volcano. An initial CALIOP browse image
obtained at the beginning of the eruption on 5 June 2011 showed the
ash and cloud height at about 12 km. The CALIOP instrument was
then turned off for about 10 days following a solar event. However,
during these same days the AIRS dust flag showed the ash circumvented
the Southern Hemisphere in the extra-tropics; by 11 June 2011 the
volcanic ash plume had circumnavigated the entire Southern Hemisphere
(south of -40∘ S) and was approaching the western coast of the
S. American continent. In other words, the eruption loaded the
Southern Hemisphere atmosphere with volcanic ash as well as clouds for
a number of days at altitudes high enough to impact
aviation in the region.
Unlike the previous subsection where the AIRS/MODIS height retrieval
was temporally and spatially coincident with the CALIOP heights, here
the AIRS/MODIS data from the Aqua satellite is unlikely to be
temporally coincident with the AATSR height data. In order to validate
the data, for each day that we had height retrievals, we compared
probability distribution functions (pdfs) of the AATSR vs. AIRS/MODIS
heights, where the daily pdfs were constructed using data limited to
AIRS/MODIS being located within 10∘ of the central location of
the AATSR data. The timing of the eruption, during the Southern
Hemisphere winter coupled with the ash potentially being transported
to high latitudes, also meant that the sun could be quite low in the
horizon for many of the AIRS/MODIS Aqua overpasses. Collection 051
does not have retrievals for solar angles larger than 72∘
(this has been expanded to 84∘ for Collection 6 retrievals;
); for the June 2011 eruption, this limitation can be
triggered at latitudes higher than 47∘ S.
Figures and show the AATSR and AIRS height
retrievals for 6 June 2011. The AATSR data we have is limited to the
S. American continent, while the AIRS data shows the plume has already
blown over the S. Atlantic. Figure shows the corresponding
pdf comparisons; the thick curves show the “co-located” pdfs, which
for 6 June 2011 would be mostly limited to be within the continent of
S. America, while the thinner dashed curves are for all the AIRS
retrieved heights. One sees that both AIRS and AATSR see a dichotomous
height distribution. The low altitude heights for AATSR are mostly in
the 5 km range, while both the χ2 and MODIS based AIRS
height retrievals are more broadly distributed around 5–8 km,
The high altitude AIRS heights are themselves double peaked, with one
peak at 13 km and the other at 15 km, and is likely
due to the retrieval losing its sensitivity at higher altitudes.
Instead of showing data for all the remaining days, we summarize the
findings by stating that overall the time differences between the two
data sets prevent detailed comparisons, but the above results are
duplicated for the days from 7–14 June 2011. By 11 June 2011,
Fig. for the AIRS/MODIS combination showed some of the
ash was at a height of almost 18 km near Australia; in fact
some ash at a height of 15 km had circumvented the Southern
Hemisphere and come back to the S. American continent, as shown by the
high altitude co-located AATSR/AIRS pdf peaks in
Fig. . Also evident from the spatial distributions of
detected ash in Figs. and is that, as with
dust, the infrared ash detection is dependent on no clouds
overlying/obscuring the aerosol.
A height sensitivity analysis using heights up to 20 km and
a tropical profile, similar to that in Fig. , showed
that at the height uncertainties (using a default factor of 4 when
converting AIRS → MODIS optical depths), can translate to
height uncertainties as large as 3–4 km, especially for low
optical depths.
Finally Fig. shows results from a NOAA Hybrid
Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) Model
trajectory run , initialized at different
heights on 5 June 2011 and run to 11 June 2011. The model is used for
computing simple air parcel trajectories to complex dispersion and
deposition simulations, and the runs show the air masses initialized
between 12–13 km on 5 June 2011 remained relatively stable
and traversed the Southern Hemisphere within a week.
Conclusions
We have demonstrated a daytime large aerosol particle (atmospheric
dust/volcanic ash) height retrieval which uses visible sensor optical
depths as a constraint to retrieve the heights from infrared
radiances. Infrared radiances are sensitive both to aerosol loading
and aerosol layer heights; since the visible to optical depth ratio is
nominally on the order of 4 when the aerosol heights are correct, an
iterative retrieval is used where the aerosol height is varied until
this ratio is obtained. The obvious limit to this methodology is the
availability of the visible optical depths, which for the MODIS is
sensor is limited to daytime, over areas not contaminated by
sun-glint. In addition the method relies on the accuracy of the
visible ODs, which is better over ocean than over land. Other
limitations include the refractive indices and particle size
distributions (and effective sizes) used in the infrared retrieval.
An analytic expression relating AIRS/MODIS synergy height retrieval
uncertainties to observed BTDs and MODIS L2 optical depths was
derived, which can be applied to any geophysical profile.
The technique has been used to retrieve dust layer heights for the
2006–2009 period, and validated for the 30 months for which we
co-located dust heights obtained from the CALIOP instrument. In
general we see good agreement between the CALIOP and AIRS/MODIS
heights; over the Pacific we note that the GOCART climatology for
springtime aerosols yields heights that are significantly higher than
those obtained from either retrieval scheme described above, while the
largest differences between AIRS and CALIOP heights are over the
Africa/Asia land masses. Since the technique is limited to daytime
scenes, while looping over aerosol heights in the retrieval we also
save off the height where the thermal infrared window spectral
difference between AIRS observations and calculations are minimized;
the results over the Atlantic in particular show good agreement with
the other methods, but emissivity issues degrade the performance over
land. In addition we also retrieved volcanic ash heights for the
June 2011 Puyehue eruption in S. America; the validation data came
from the AATSR instrument as there was no CALIOP data available.
The work in this paper assumes that the visible/infrared optical depth
ratio f0 is 4. The heights from CALIOP are usually higher than
that retrieved from the AIRS/MODIS synergy; the height sensitivity of
Sect. shows that typically if f
increases, the retrieved height decreases; this means that the
MODIS/AIRS ratio is probably less than 4, though differences in size
distributions and refractive indices used to compute the MODIS vs.
AIRS scattering parameters, make this conjecture difficult to
investigate further. In addition depending on the magnitude of the
optical depth involved, the infrared measurements can penetrate some
way into the dust/ash plume and could result in a retrieved heights
lower than the CALIOP centroid height.
With infrared missions being planned into the foreseeable future, data
assimilation from instruments such as AIRS/MODIS, IASI/AVHRR and
CRiS/VIIRS can be used to improve source, transport and deposition
models both for atmospheric dust and VAACs, in conjunction with data
from other satellite instruments. Previous papers have demonstrated
that databases of infrared spectral signatures can
further be used to identify spieciation of dust and ash; in this paper
the optimal results for AIRS data were obtained using optical
constants of Saharan dust and basalt.
In the future we plan to utilize this height and optical depth
retrieval in an Optimal Estimation scheme as
a constraint on a scattering-based retrieval of atmospheric humidity
and temperature fields in the presence of aerosols, which should
improve the AIRS L2 products when aerosols are present, as indicated
by the dust flag. Bright surfaces negatively impact aerosol optical
depth retrievals of instruments operating in the visible wavelengths
over deserts; the aerosol ODs are more accurately retrieved using
shorter wavelengths but which also need height estimates of the
aerosols, which implies improved height retrievals could be used to
improve for example aerosol ODs retrieved using instruments operating
in the ultraviolet regimes.
Acknowledgements
This work has been supported by a NASA-JPL contract NNN12AA01C with
Science and Technology Corporation (STC), Columbia MD. We
acknowledge the use of ECMWF model fields to compute radiances.
Ruben Delgado ran off the NOAA HYSPLIT model. Paul Schou provided
assistance in downloading the relevant AIRS L1B data co-located with
the dust flag using OpenDap, and with plotting the data. The
development of the AATSR stereo height retrieval was supported by
the UK Natural Environment Research Council (NERC) National Centre
for Earth Observation and the NERC VANAHEIM project
(NE/1015592/1). The hardware used in the computational studies is
part of the UMBC High Performance Computing Facility (HPCF). The
facility is supported by the US National Science Foundation through
the MRI program (grant nos. CNS-0821258 and CNS-1228778) and the
SCREMS program (grant no. DMS-0821311), with additional substantial
support from the University of Maryland, Baltimore County
(UMBC). See www.umbc.edu/hpcf for more information on HPCF and
the projects using its resources.
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Pearson Correlation R against CALIOP heights, computed over months of July 2006–December 2008.
AIRS spectra obtained at three locations on 6 June 2011 over
S. America and the southern Atlantic Ocean. (H) in black is very
close to the Puyehue-Calderon volcano, (L) in dark gray is from the
ash plume that has drifted thousands of kilometers over the Atlantic
while (C) in light gray is from a clear scene over ocean.
Sensitivity of retrieved heights, using a tropical
profile. Left panel shows how BTD = BT1231 - BT961 varies as
a function of height (km) and MODIS AOD, where we use
τMODIS=4τAIRS. The right panel show
this translates to an uncertainty in retrieved height for an
uncertainty δf= +1, again as a function of height (km)
and MODIS AOD. The largest uncertainties are at the lower optical
depths (where it is difficult to distinguish from clear sky scenes)
and high altitudes (where a small change in loading can produce
large changes in BTD).
AIRS retrieved heights compared to CALIOP mean aerosol
heights, over the period 2006–2009. CALIOP data is available
starting July 2006. In this plot the Atlantic region is
considered. Blue is the GOCART climatology, red/green are the
MODIS-based and χ2-based AIRS retrievals, while black is the
CALIOP data. Left panel: 2006–2009 seasonal cycle; right panel:
monthly averages.
AIRS retrieved heights compared to CALIOP mean aerosol
heights, over the period 2006–2009. CALIOP data is available
starting July 2006. In this plot the Pacific region is
considered. Blue is the GOCART climatology, red/green are the
MODIS-based and χ2-based AIRS retrievals, while black is the
CALIOP data. Left panel: 2006–2009 seasonal cycle; right panel:
monthly averages.
AIRS retrieved heights compared to CALIOP mean aerosol
heights, over the period 2006–2009. CALIOP data is available
starting July 2006. In this plot the Mediterranean region is
considered. Blue is the GOCART climatology, red/green are the
MODIS-based and χ2-based AIRS retrievals, while black is the
CALIOP data. Left panel: 2006–2009 seasonal cycle; right panel:
monthly averages.
AIRS retrieved heights compared to CALIOP mean aerosol
heights, over the period 2006–2009. CALIOP data is available
starting July 2006. In this plot the Asia/Africa landmass region is
considered. Blue is the GOCART climatology, red/green are the
MODIS-based and χ2-based AIRS retrievals, while black is the
CALIOP data. Left panel: 2006–2009 seasonal cycle; right panel:
monthly averages.
AATSR height retrievals for 6 June 2011. One sees two plumes
over the S. American continent, one having a mean height of about
6 km and the other having a mean height of about
12 km.
AIRS height retrievals for 6 June 2011, based on constraints
using MODIS data. One sees the ash plumes have already been blown
over the S. Atlantic. The black box shows the AASTR data coverage, as
displayed in Fig. .
AIRS vs. AATSR height retrievals for 6 June 2011, compared
using pdfs. The thick curves are for the “co-located” heights,
which in this case would be mostly over land – the black curve is
for the AATSR heights, the blue curve is the MODIS based AIRS height
retrieval while the red curve is the χ2 based retrieval. The
dashed blue and red curves shows the corresponding histograms when
all AIRS retrieved heights are used.
AIRS height retrievals for 11 June 2011, based on constraints
using MODIS data. One sees some of the ash plumes is already near
Australia; in fact some of the ash has already traveled around the
hemisphere back to the S. American continent.
.
AIRS vs. AATSR height retrievals for 11 June 2011, compared
using pdfs. As in Fig. , the thick curves are for the
“co-located” heights, which in this case would be mostly over land
– the black curve is for the AATSR heights, the blue curve is the
MODIS based AIRS height retrieval while the red curve is the
χ2 based retrieval. The dashed blue and red curves shows the
corresponding histograms when all AIRS retrieved heights are
used. The AATSR data was located mostly over the S. American
continent, and the histogram shows a peak at about 5 km. The
AIRS data also showed some high altitude (15 km) ash had
circumvented the globe; the dashed curves for the AIRS retrieved
heights are for ash that is close to Australia.
NOAA HYSPLIT model for 5–15 June 2011, showing the
evolution of air masses at different heights during this time
period. It is seen the 12 km air mass remained relatively
stable, descending about 2 km in 10 days.