39 research outputs found
Updated MISR over-water research aerosol retrieval algorithm – Part 2: A multi-angle aerosol retrieval algorithm for shallow, turbid, oligotrophic, and eutrophic waters
Coastal waters serve as transport pathways to the ocean for all agricultural
and other runoff from terrestrial sources, and many are the sites for
upwelling of nutrient-rich, deep water; they are also some of the most
biologically productive on Earth. Estimating the impact coastal waters have
on the global carbon budget requires relating satellite-based remote-sensing
retrievals of biological productivity (e.g., chlorophyll a concentration)
to in situ measurements taken in near-surface waters. The Multi-angle Imaging
SpectroRadiometer (MISR) can uniquely constrain the “atmospheric
correction” needed to derive ocean color from remote-sensing imagers. Here,
we retrieve aerosol amount and type from MISR over all types of water. The
primary limitation is an upper bound on aerosol optical depth (AOD), as the
algorithm must be able to distinguish the surface. This updated MISR research
aerosol retrieval algorithm (RA) also assumes that light reflection by the
underlying ocean surface is Lambertian. The RA computes the ocean surface
reflectance (Rrs) analytically for a given AOD, aerosol optical
model, and wind speed.
We provide retrieval examples over shallow, turbid, and eutrophic waters and
introduce a productivity and turbidity index (PTI), calculated from retrieved
spectral Rrs, that distinguished water types (similar to the the normalized difference vegetation index,
NDVI, over land). We also validate the new algorithm by comparing spectral AOD and
Ångström exponent (ANG) results with 2419 collocated AErosol RObotic NETwork (AERONET)
observations. For AERONET 558 nm interpolated
AOD < 1.0, the root-mean-square error (RMSE) is 0.04 and linear
correlation coefficient is 0.95. For the 502 cloud-free MISR and AERONET
collocations with an AERONET AOD > 0.20, the ANG RMSE is 0.25 and
r is 0.89. Although MISR RA AOD retrieval quality does not appear to be
substantially impacted by the presence of turbid water, the MISR-RA-retrieved
Ångström exponent seems to suffer from increased uncertainty under
such conditions.
MISR supplements current ocean color sources in regions where sunglint
precludes retrievals from single-view-angle instruments. MISR atmospheric
correction should also be more robust than that derived from single-view
instruments such as the Moderate Resolution Imaging Spectroradiometer (MODIS).
This is especially true in regions of shallow,
turbid, and eutrophic waters, locations where biological productivity can be
high, and single-view-angle retrieval algorithms struggle to separate
atmospheric from oceanic features.</p
Constraining chemical transport PM<sub>2.5</sub> modeling outputs using surface monitor measurements and satellite retrievals: application over the San Joaquin Valley
Advances in satellite retrieval of aerosol type can improve the
accuracy of near-surface air quality characterization by providing broad
regional context and decreasing metric uncertainties and errors. The
frequent, spatially extensive and radiometrically consistent instantaneous
constraints can be especially useful in areas away from ground monitors and
progressively downwind of emission sources. We present a physical approach to
constraining regional-scale estimates of PM2.5, its major chemical
component species estimates, and related uncertainty estimates of chemical
transport model (CTM; e.g., the Community Multi-scale Air Quality Model)
outputs. This approach uses ground-based monitors where available, combined
with aerosol optical depth and qualitative constraints on aerosol size,
shape, and light-absorption properties from the Multi-angle Imaging
SpectroRadiometer (MISR) on the NASA Earth Observing System's Terra
satellite. The CTM complements these data by providing complete spatial and
temporal coverage. Unlike widely used approaches that train statistical
regression models, the technique developed here leverages CTM physical
constraints such as the conservation of aerosol mass and meteorological
consistency, independent of observations. The CTM also aids in identifying
relationships between observed species concentrations and emission sources.Aerosol air mass types over populated regions of central California are
characterized using satellite data acquired during the 2013 San Joaquin field
deployment of the NASA Deriving Information on Surface Conditions from Column
and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ)
project. We investigate the optimal application of incorporating 275 m
horizontal-resolution aerosol air-mass-type maps and total-column aerosol
optical depth from the MISR Research Aerosol retrieval algorithm (RA) into
regional-scale CTM output. The impact on surface PM2.5 fields
progressively downwind of large single sources is evaluated using
contemporaneous surface observations. Spatiotemporal R2 and RMSE values for the model, constrained by both satellite and surface monitor measurements based on 10-fold cross-validation, are 0.79 and 0.33 for PM2.5, 0.88 and
0.65 for NO3−, 0.78 and 0.23 for SO42−, 1.00 and
1.01 for NH4+, 0.73 and 0.23 for OC, and 0.31 and 0.65
for EC, respectively. Regional cross-validation temporal and spatiotemporal
R2 results for the satellite-based PM2.5 improve by 30 % and
13 %, respectively, in comparison to unconstrained CTM simulations and
provide finer spatial resolution. SO42− cross-validation values
showed the largest spatial and spatiotemporal R2 improvement, with a
43 % increase. Assessing this physical technique in a well-instrumented
region opens the possibility of applying it globally, especially over areas
where surface air quality measurements are scarce or entirely absent.</p
Aerosol Airmass Type Mapping Over the Urban Mexico City Region From Space-based Multi-angle Imaging
Using Multi-angle Imaging SpectroRadiometer (MISR) and sub-orbital measurements from the 2006 INTEX-B/MILAGRO field campaign, in this study we explore MISR's ability to map different aerosol air mass types over the Mexico City metropolitan area. The aerosol air mass distinctions are based on shape, size and single scattering albedo retrievals from the MISR Research Aerosol Retrieval algorithm. In this region, the research algorithm identifies dust-dominated aerosol mixtures based on non-spherical particle shape, whereas spherical biomass burning and urban pollution particles are distinguished by particle size. Two distinct aerosol air mass types based on retrieved particle microphysical properties, and four spatially distributed aerosol air masses, are identified in the MISR data on 6 March 2006. The aerosol air mass type identification results are supported by coincident, airborne high-spectral-resolution lidar (HSRL) measurements. Aerosol optical depth (AOD) gradients are also consistent between the MISR and sub-orbital measurements, but particles having single-scattering albedo of approx. 0.7 at 558 nm must be included in the retrieval algorithm to produce good absolute AOD comparisons over pollution-dominated aerosol air masses. The MISR standard V22 AOD product, at 17.6 km resolution, captures the observed AOD gradients qualitatively, but retrievals at this coarse spatial scale and with limited spherical absorbing particle options underestimate AOD and do not retrieve particle properties adequately over this complex urban region. However, we demonstrate how AOD and aerosol type mapping can be accomplished with MISR data over complex urban regions, provided the retrieval is performed at sufficiently high spatial resolution, and with a rich enough set of aerosol components and mixtures
MISR Update
The document was presented at the 2013 AEROCENTER Annual Meeting held at the GSFC Visitors Center, May 31, 2013. The organizers of the meeting are posting the talks to the public Aerocenter website
Informing Aerosol Transport Models With Satellite Multi-Angle Aerosol Measurements
As the aerosol products from the NASA Earth Observing System's Multi-angle Imaging SpectroRadiometer (MISR) mature, we are placing greater focus on ways of using the aerosol amount and type data products, and aerosol plume heights, to constrain aerosol transport models. We have demonstrated the ability to map aerosol air-mass-types regionally, and have identified product upgrades required to apply them globally, including the need for a quality flag indicating the aerosol type information content, that varies depending upon retrieval conditions. We have shown that MISR aerosol type can distinguish smoke from dust, volcanic ash from sulfate and water particles, and can identify qualitative differences in mixtures of smoke, dust, and pollution aerosol components in urban settings. We demonstrated the use of stereo imaging to map smoke, dust, and volcanic effluent plume injection height, and the combination of MISR and MODIS aerosol optical depth maps to constrain wildfire smoke source strength. This talk will briefly highlight where we stand on these application, with emphasis on the steps we are taking toward applying the capabilities toward constraining aerosol transport models, planet-wide
Evolving Particles in the 2022 Hunga Tonga—Hunga Ha'apai Volcano Eruption Plume
The Multi-angle Imaging SpectroRadiometer (MISR) aboard NASA’s Terra satellite observed the Hunga Tonga—Hunga Ha’apai (HTHH) 15 January eruption plume on seven occasions between 15 and 23 January 2022. From the MISR multi-angle, multi-spectral imagery we retrieve aerosol plume height geometrically, along with plume-level motion vectors, and derive radiometrically constraints on particle effective size, shape, and light-absorption properties. Parts of two downwind aerosol layers were observed in different places and times, one concentrated in the upper troposphere (11-18 km ASL), and a mid-stratosphere layer ~23 – 30+ km ASL. After the initial day (1/15), the retrievals identified only spherical, non-light-absorbing particles, typical of volcanic sulfate/water particles. The near-tropopause plume particles show constant, medium-small (several tenths of a micron) effective size over four days. The mid-stratosphere particles were consistently smaller, but retrieved effective particle size increased between 1/17 and 1/23, though they might have decreased slightly on 1/22. As a vast amount of water was also injected into the stratosphere by this eruption, models predicted relatively rapid growth of sulfate particles from the modest amounts of SO2 gas injected by the eruption to high altitudes along with the water (Zhu et al, 2022). MISR observations up to ten days after the eruption are consistent with these model predictions. The possible decrease in stratospheric particle size after initial growth was likely caused by evaporation, as the plume mixed with drier, ambient air. Particles in the lower-elevation plume observed on 1/15 were larger than all the downwind aerosols and contained significant non-spherical (likely ash) particles
MISR research-aerosol-algorithm refinements for dark water retrievals
We explore systematically the cumulative effect of many assumptions made in
the Multi-angle Imaging SpectroRadiometer (MISR) research aerosol retrieval
algorithm with the aim of quantifying the main sources of uncertainty over
ocean, and correcting them to the extent possible. A total of 1129
coincident, surface-based sun photometer spectral aerosol optical depth (AOD)
measurements are used for validation. Based on comparisons between these data
and our baseline case (similar to the MISR standard algorithm, but without
the "modified linear mixing" approximation), for 558 nm AOD
< 0.10, a high bias of 0.024 is reduced by about one-third when (1)
ocean surface under-light is included and the assumed whitecap reflectance at
672 nm is increased, (2) physically based adjustments in particle
microphysical properties and mixtures are made, (3) an adaptive pixel
selection method is used, (4) spectral reflectance uncertainty is estimated
from vicarious calibration, and (5) minor radiometric calibration changes are
made for the 672 and 866 nm channels. Applying (6) more stringent cloud
screening (setting the maximum fraction not-clear to 0.50) brings all median
spectral biases to about 0.01. When all adjustments except more stringent
cloud screening are applied, and a modified acceptance criterion is used, the
Root-Mean-Square-Error (RMSE) decreases for all wavelengths by 8–27%
for the research algorithm relative to the baseline, and is 12–36%
lower than the RMSE for the Version 22 MISR standard algorithm (SA, with no
adjustments applied). At 558 nm, 87% of AOD data falls within the
greater of 0.05 or 20% of validation values; 62% of the 446 nm AOD
data, and > 68% of 558, 672, and 866 nm AOD values fall
within the greater of 0.03 or 10%. For the Ångström exponent
(ANG), 67% of 1119 validation cases for AOD > 0.01 fall
within 0.275 of the sun photometer values, compared to 49% for the SA.
ANG RMSE decreases by 17% compared to the SA, and the median absolute
error drops by 36%
MISR empirical stray light corrections in high-contrast scenes
We diagnose the potential causes for the Multi-angle Imaging
SpectroRadiometer's (MISR) persistent high aerosol optical depth (AOD) bias
at low AOD with the aid of coincident MODerate-resolution Imaging
Spectroradiometer (MODIS) imagery from NASA's Terra satellite. Stray light
in the MISR instrument is responsible for a large portion of the high AOD
bias in high-contrast scenes, such as broken-cloud scenes that are quite
common over ocean. Discrepancies among MODIS and MISR nadir-viewing blue,
green, red, and near-infrared images are used to optimize seven parameters
individually for each wavelength, along with a background reflectance
modulation term that is modeled separately, to represent the observed
features. Independent surface-based AOD measurements from the AErosol
RObotic NETwork (AERONET) and the Marine Aerosol Network (MAN) are compared
with MISR research aerosol retrieval algorithm (RA) AOD retrievals for 1118 coincidences to
validate the corrections when applied to the nadir and off-nadir cameras.
With these corrections, plus the baseline RA corrections and enhanced cloud
screening applied, the median AOD bias for all data in the mid-visible
(green, 558 nm) band decreases from 0.006 (0.020 for the MISR standard
algorithm (SA)) to 0.000, and the RMSE decreases by 5 % (27 % compared
to the SA). For AOD<sub>558 nm</sub> < 0.10, which includes about half
the validation data, 68th percentile absolute AOD<sub>558 nm</sub> errors for
the RA have dropped from 0.022 (0.034 for the SA) to < 0.02
(~ 0.018)