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MISR Level 2 Aerosol/Surface Products |
This statement applies to MISR Level 2 Aerosol/Surface Products for November 27, 2002, and beyond until such a time as further improvements to MISR software are made. See the Versioning Page for an in-depth explanation of the differences between various MISR product versions. Quality statements covering earlier time periods may be accessed through links at the bottom of this page.
An extensive review of product quality has not yet been performed. Please read the summary words of caution if you have not done so already.
Although there are warnings relating to Beta and Provisional quality parameters, the MISR Level 2 Aerosol/Surface software which generated these products is believed to be functioning well except where noted below. This statement highlights major known problems and issues with the products, as well as functionalities which are currently not implemented.
PRODUCT MATURITY
All aerosol parameters now have "Provisional" status with the
exception of
ChisqHomog,
OptDepthHomogCalcPerBand,
ChisqHomogCalcPerBand,
which have "Beta" status and
RegBestFitMixtureEqRefl,
RegSfcRetrOptDepthUnc,
OptDepthDWCalcPerBand,
OptDepthOTACalcPerBand,
ChisqAbsCalcPerBand,
which are not yet implemented.
Product users should be aware that the aerosol models used in the retrieval analyses provide a practical means of allowing a determination of optical depth, and some preliminary validations of optical depth have been performed, as described below. However, it has not yet been verified that any particular model which successfully fits the observations should necessarily be considered an indicator of the actual aerosol type. As the MISR retrieval process matures, the constraints and thresholds used will be tightened, resulting in a decrease of the number of successful aerosol models for any particular retrieval. This process, coupled with a more rigorous comparison of MISR and ground truth data (AERONET and field campaigns) which includes aerosol particle size distribution and other microphysical properties, will determine how and to what extent the model results can be interpreted. Both activities are in progress.
ACP DEPENDENCY
The quality of the aerosol product depends upon the quality of the Ancillary
Climatology Product (ACP). The ACP contains information on component aerosol
particle properties and mixtures of aerosol components assumed by the
retrieval algorithm. The ACP was updated in April 2002 with a new
aerosol component dataset and a new mixture dataset. Refer to the
ACP quality statement
for further information.
TASC DEPENDENCY
The MISR TASC (Terrestrial Atmosphere and Surface Climatology) dataset provides
information on the climatological conditions of the area being observed by the
MISR instrument. This information is used during the aerosol retrieval process.
The TASC dataset is gridded on a month-by-month temporal basis. We anticipate
that in a future upgrade, this information will be obtained from more timely
sources, e.g., the Data Assimilation Office (DAO).
CLOUD DETECTION STATUS
Cloud screening is performed prior to the aerosol retrievals. However, the
masks currently used do not detect some clouds. The user is cautioned to be
aware of this. Most of the detection blunders tend to occur on the edges of
well-defined clouds, causing the water or land aerosol retrieval algorithm to
be used improperly. These blunders manifest themselves as large values for the
aerosol optical depth (> 2). Cloud screening is currently performed with
algorithms which utilize the angle-to-angle differences in radiances across
MISR cameras, as well as with the MISR-derived Radiometric Camera-by-camera
Cloud Mask (RCCM) and Stereoscopically Derived Cloud Mask (SDCM). Improvements
to the cloud detection scheme are currently under development.
RELIABILITY OF AEROSOL OPTICAL DEPTHS OVER LAND
Comparisons of MISR optical depths with those from AERONET (ground based) show
a good correlation between the two datasets. These comparison studies are
currently in the preliminary stages but are expected to be more extensive in
the near future. Minor populations of retrieval blunders sporadically occur for
terrain types having low spatial contrast, most notable bright deserts and
snow/ice fields. They are manifested as anomalously large values of optical
depth (>2) which appear to be randomly scattered throughout an area.
Increased numbers of blunders occur over snow/ice fields as a consequence of
inadequate cloud screening. Blunder elimination is a high priority ongoing
task.
RELIABILITY OF AEROSOL OPTICAL DEPTHS OVER WATER
Comparisons of MISR optical depths with those from AERONET (ground based) show
a good correlation between the two datasets. These comparison studies are
currently in the preliminary stages but are expected to be more extensive in
the near future. On occasions where MISR and AERONET optical depths differ,
the MISR values are typically biased higher. This is the subject of an ongoing
investigation.
OPTICAL DEPTH UNCERTAINTIES
Estimates of the uncertainty in the aerosol optical depth over land have been
improved by application of more stringent constraints on the heterogeneous land
aerosol retrieval algorithm. Previous estimates were too large due to lack of
use of spectral information. Uncertainty estimates for aerosols over dark water
remain the same as for earlier versions of the algorithm.
EDGE-OF-SWATH ARTIFACTS OVER OCEAN
The retrieved optical depths over ocean at the edge of the MISR swath
occasionally appear brighter than the surrounding values. The cause of this
artifact is under investigation.
ALGORITHM UPDATES
The aerosol retrieval algorithms described in the Algorithm Theoretical Basis
document (Revision E, April 2001) have been modified and improved, based on
initial analyses of the data. The next release of this document will include an
updated description of these algorithms.
EXPERIMENTAL AEROSOL ALGORITHM OVER HOMOGENEOUS SURFACES
A new algorithm which retrieves aerosol properties over homogeneous surfaces
is included. However, due to its experimental nature, results from this
algorithm are included for diagnostic purposes only. Affected fields in the
aerosol product are ChisqHomog, OptDepthHomogCalcPerBand, and
ChisqHomogCalcPerBand.
SOME AEROSOL FIELDS NOT AVAILABLE
The following fields in the aerosol product are not currently computed, and
contain fill only: RegBestFitMixtureEqRefl; RegSfcRetrOptDepthUnc;
OptDepthDWCalcPerBand; OptDepthOTACalcPerBand; ChisqAbsCalcPerBand.
PRODUCT MATURITY
All surface parameters now have the "Provisional" status with the
exception of
BHRPAR,
DHRPAR,
BHRPARNumSubrCalcUsed,
DHRPARNumSubrCalcUsed,
which have "Beta" status.
AEROSOL DEPENDENCY
The land surface product relies on the aerosol product for atmospheric
correction information. Therefore, the quality of the land surface product
depends upon the quality of the aerosol product, and users are advised to refer
to the aerosol product for further information. In the future we anticipate
replicating the appropriate aerosol information within the land surface product.
RELIABILITY OF LAND SURFACE REFLECTANCE VALUES DEPENDENT UPON
AEROSOL OPTICAL DEPTH MAGNITUDE
At the current time land surface retrievals, particularly those with low
surface albedo, should be considered most reliable when the aerosol optical
depths are small (< 0.2). For higher albedo areas, such as deserts, good
results are obtained for optical depths < 0.4. Thus, it is recommended that
users examine the 'RegSfcRetrOptDepth' field in the land surface product as
part of their assessments of the surface parameters. This field is the aerosol
optical depth at 558 nm (green band), used in the surface retrieval process.
Other parameters which indicate the quality of the surface retrieval include
'LandBHRRelUnc' (ratio of BHR uncertainty to BHR value) and 'LandHDRFUncCamAvg'
(HDRF uncertainty averaged over the various cameras), which are derived from
the uncertainty in the retrieved aerosol optical depth. It can be assumed that
these uncertainty products also apply to the DHR and BRF surface products,
respectively. Inspection and analysis of these products, for both dark and
bright areas, indicates that they adequately represent the uncertainty
associated with their respective products, and therefore are good indicators of
product quality. Some sporadic but obvious retrieval blunders do occur,
however, for areas that are bright and have little contrast (e.g., deserts and
snow/ice fields) and these are easily seen in the images as anomalously bright
reflectances. Further refinements in the quality of the aerosol retrievals
over land are planned for future releases and these are expected to result in
improvements in the surface retrieval blunder rate and product quality at
larger optical depths.
QUILTING EFFECT IN LAND SURFACE REFLECTANCES
Most of the retrieved land surface reflectances are reported at a 1.1 km x
1.1 km spacing, whereas the retrieved aerosol optical depths are computed at
a coarser 17.6 km x 17.6 km spacing. It is assumed that aerosol amount is
constant over any particular 17.6 km region, which results in values of
aerosol optical depth that are inherently discontinuous going from one region
to an adjacent one. Therefore, the atmospheric correction process, using the
coarse resolution aerosol data with the fine resolution reflectance data,
occasionally produces a distinctive "quilting" effect in the
directional surface reflectance imagery, i.e., a discernable block pattern.
Imagery from the extreme off-nadir cameras at 446 nm (blue band) is
particularly prone to this effect. The aerosol optical depth discontinuities
are due to both real variation in aerosol amount on spatial scales smaller
than the 17.6 km spacing and to intrinsic uncertainties associated with the
aerosol retrieval process. The magnitude of this "quilting" effect
is well described by the surface reflectance uncertainty parameters,
mentioned in the previous section.
FILL VALUES IN LAND SURFACE REFLECTANCES
Land surface reflectances are computed separately for each MISR spectral
band. In some cases, the land retrievals succeed in one MISR band, but not
another. This can cause visualization problems when viewing a composite
image of land surface reflectances which contains spectral bands for both
successful and unsuccessful retrievals. This occasional algorithm failure in
certain bands (notably blue and/or red) is thought to be due to a software
error and is a high priority item for investigation and repair.
LAI/FPAR AVAILABILITY AT PROVISIONAL QUALITY LEVEL
The LAI/FPAR fields are now of "Provisional" quality. The software
which computes leaf-area index (LAI) and fraction of photosynthetically active
radiation (FPAR) uses Land Surface Reflectances (BHR and BRF) as input. Two
spectral bands, red and near-infrared, and 7 view directions are currently
used to produce LAI and FPAR.
The quality and spatial coverage of LAI and FPAR depend on the quality and coverage of the Land Surface Reflectances (BHR and BRF). Surface reflectances whose uncertainties exceed an acceptable level of 20% result in algorithm failure. The data analysis indicates that uncertainties in the MISR BHR of dense vegetations at red and blue spectral bands can substantially exceed the acceptable level. At these wavelengths, dense vegetations exhibit low reflectances. As indicated in section "RELIABILITY OF LAND SURFACE REFLECTANCE VALUES DEPENDENT UPON AEROSOL OPTICAL DEPTH MAGNITUDE", reliability of land surface retrievals can be low in this case. High uncertainties in BHR retrievals over dark surfaces, therefore, can result in algorithm failure, reducing the number of successful retrievals. With a probability of about 70%, uncertainties in retrieved LAIs do not exceed uncertainties in the MISR Surface Reflectances (BHR and BRF). Inspection and analysis of the LAI/FPAR product indicate that the successfully retrieved LAI/FPAR values follow regularities expected from physics.
Considerable attention was also paid to characterizing the quality of the LAI/FPAR parameters. The quality of LAI/FPAR retrievals can be assessed through examining LAINumGoodFit1 and LAINumGoodFit2 accompanying the product; that is, LAINumGoodFit1*LAINumGoodFit2>0 indicates highest retrieval quality; LAINumGoodFit1>0 and LAINumGoodFit2=0 - intermediate quality. The operational version of the algorithm does not archive low quality retrievals (LAINumGoodFit1=0 and LAINumGoodFit2>0). For more details on the performance of the provisional LAI/FPAR algorithm as well as how to interpret LAIMean1 and LAIMean2 as a function of biome type, the users is referred to Hu et al., Performance of the MISR LAI and FPAR Algorithm: A Case Study in Africa, Remote Sens. Environ, 2002 (PDF) (submitted for publication).
OCEAN NOT YET AVAILABLE
The Ocean Surface product, which contains surface reflectance properties over
ocean, has not yet been implemented. It is unavailable at this time.
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