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MISR Level 2 Top-of-Atmosphere/Cloud Products |
This statement applies to MISR Level 2 TC Stereo, Albedo and Classifiers for April 15, 2002, and beyond until such a time as further improvements to MISR software are made.
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.
Many of the algorithms used in the product retrievals have been developed specifically for the MISR instrument, and as such, are relatively untested. We expect to improve on these algorithms as we gain experience with the data. Trade-offs with the stereo-matching algorithms have been made at times to sacrifice accuracy or coverage for speed and vice-versa.
In spite of all the warnings, the MISR Level 2 TC Stereo, Albedo and Classifiers software which generated these products is believed to be functioning quite well except where noted below. This statement highlights major known problems with the products, as well as functionalities which are currently not implemented.
The Restrictive and Expansive albedos are still not ready for public release and thus have been set to NoRetrieval throughout the swath. Clear-Sky Modeling for the Local Albedo has not yet been implemented, nor have the Grey-Level Difference Vectors.
The Angular Signature Cloud Mask algorithm has not been implemented. So, all of the ASCM fields (both the cloud mask and the corresponding cloud fractions) contain "NoRetrieval" values in the Cloud Classifiers product.
REGISTRATION
Cloud motion calculations are quite sensitive to the quality of registration of
the D camera L1B2 ellipsoid-projected radiance products. Since Level 1 does not
yet utilize Reference Orbit Imagery (ROI) when performing registration
correction, the registration relies on a fairly static camera model. The camera
model changes periodically, and although the registration is typically much
better, the camera models in use only guarantee accuracy of 2 pixels or less in
the D cameras. Cloud height accuracy is nominally 562 m, corresponding to 1
pixel of accuracy in the A cameras. Under the best of conditions, the heights
often appear quantized. Further, they are occasionally made worse due to errors
in cloud motion caused by misregistration of the D cameras or difficulty in
applying the stereo-matchers to the scene. A 2 pixel D camera error translates
to a 10-15 m/s error in the cloud motion vectors, which propagates to an error
of 1100 m in height. We expect the registration reliability to improve
significantly when the ROI is used, and we anticipate a reduction in height and
wind uncertainties of approximately a factor of 2. For more details, including
a link to a list of orbits with known registration problems, see the
Georectification Page.
DOMAIN ARTIFACTS
Cloud motion retrievals are made on 70.4 km domains. This may at times result
in discontinuities at domain boundaries for cloud heights. In addition there
are "drop-outs" in the wind field where the stereo-matchers failed
to retrieve a strong signal. This will also lead to blockiness in the height
field. The source of each individual wind vector (0=StereoNotAttempted,
1=StereoFailed, 2=StereoSucceeded) is available in the product. When the wind
retrieval failed for whatever reason, a default value of 0.0 is used for the
winds and the subsequent height retrieval.
STRIPES
Horizontal stripes may occasionally appear in the product for some parameters.
This is due to one or more missing lines of data in Level 1, and often shows
up in Level 2 parameters as "No Retrieval" flag values. For more
details, see
EXCEPTIONS/ANOMALIES in the Level 1 Quality Statement.
BLUNDERS
The stereo-matching algorithms do not contain a robust method for detecting
blunders. As a result, spikes may occasionally appear in the cloud heights.
ALGORITHM UPDATES
The cloud motion and height retrievals have changed somewhat from the Level 2
Cloud Detection and Classification ATB (JPL D-11399, Rev. D). These changes
will be reflected in the next release of the document, Rev E. Highlights
include:
The histogramming of the cloud motion for each domain now involves the identification of clusters of points which may cross the histogram bin boundaries, resulting in a matrix which identifies the clusters. The clusters chosen for the two cloud layers must be local maxima in this matrix. The histogram now includes a center bin which is centered on 0.0 in each direction. We no longer concatenate bins with the same population together but rather choose the one with the smallest height range.
External meteorological inputs such as MODIS and NSIDC are not yet used. Instead, a static monthly climatology (the TASC dataset) is used.
The Level 1 Radiometric Camera-by-camera Cloud Mask (RCCM) still has not been successfully validated over land, but is working well over ocean. Therefore, the Stereoscopically Derived Cloud Mask relies solely on stereoscopically matched data to determine the presence over land, but does include the Level 1 Radiometric data as input over ocean.
If there are no successful stereo retrievals for a given 1.1km subregion, the stereoscopic height for that region is set to NoRetrieval except under the following circumstances: if the pixel is located over ocean and the RCCM indicates ClearHighConfidence, the surface height at that point is substituted for the final stereo height. Each retrieved surface height has a corresponding flag indicating its source (0=NoRetrieval, 1=Stereo, 2=Surface, 3=DefaultCloud, 4=MODIS).
When calculating the Reflecting Level Reference Altitude (RLRA) at 2.2 km resolution, it is set to NoRetrieval if all of the corresponding StereoHeights are also NoRetrieval.
ASCM NOT AVAILABLE
The Angular Signature Cloud Mask algorithm has not been implemented, and thus,
all of the ASCM fields contain "NoRetrieval" values in the Cloud
Classifiers product.
CLOUD AND TOPOGRAPHIC SHADOW MASKS NOT AVAILABLE
The cloud and topographic shadow masks are not yet part of the Classifiers
product.
CLOUD CLASSIFIERS FIELDS
The Cloud Classifiers contain the altitude-binned cloud fractions for each of
the three MISR cloud masks, SDCM, RCCM and eventually ASCM. The four possible
mask values for the cloud fractions are: CloudHighConfidence,
ClearHighConfidence, CloudHighConfidence (without the ASCM), and
CloudLowConfidence (without the ASCM). The product also contains the
angle-by-angle cloud fractions calculated from the RCCM. All these fields are
calculated at 17.6 km resolution.
Given that the algorithms for determining these classifiers are simple, the quality of these products is directly determined by that of the incoming data (the SDCM, the StereoHeights, the RCCM and eventually the ASCM). The reader is strongly urged to pay close attention to the quality statements for all these data.
RESTRICTIVE AND EXPANSIVE ALBEDOS NOT AVAILABLE
Algorithm problems with the restrictive and expansive albedos prevent us from
making this data publically available at this time. Therefore these products
are set to NoRetrieval (-9999.0) throughout the swath.
GREY-LEVEL DIFFERENCE VECTORS NOT AVAILABLE
The second and third texture indices in the reflecting level parameters
(grey-level difference vectors) have not yet been implemented.
CLEAR-SKY DETERMINISTIC MODELLING NOT AVAILABLE
The algorithm for calculating the clear-sky local albedo using deterministic
modelling has not been implemented yet, and thus, whenever the cloud masks
indicate the scene is clear, all the local albedo components are calculated
solid-angle weighting.
RLRA DISCONTINUITIES
The process of registering the BRF's from the surface ellipsoid to the
Reflecting Level Reference Altitude (RLRA) is dependent on the quality of the
incoming RLRA. If the RLRA is discontinuous due to mistakes or difficulties in
the stereoscopic height or wind retrieval, this will feed through to the
Top-of-Column BRF's and the Local Albedo and show up as discontinuous values in
those products. If there was no valid stereoscopic height retrieval anywhere
within a 2.2 km region (the resolution of the RLRA), the RLRA (and consequently
the reprojected BRF's, the number of un-obscured pixels and the Local Albedos)
will all be set to NoRetrieval.
MODEL DIFFERENCES
The Local Albedo calculation is first attempted by Deterministic Modeling (if
the scene is homogenous), then Stochastic Modeling and finally solid-angle
weighting. No modeling is attempted for clear-sky pixels or where the solar
zenith angle is < 25.8 degrees. The (Deterministic - Stochastic) model
difference is peaked at 0.0, with the bulk of the differences being less than
0.02 with no appreciable bias. The peak of the (Deterministic-SolidAngle)
difference distribution is also located at 0.0, but the SolidAngle albedos are
biased consistently higher than the Deterministic ones, with differences up to
0.08. There is some slight band-to-band variation present in the
model-difference distributions, but the shapes and peak locations of the
distributions are similar.
BAND DIFFERENCES
The Local Albedo of the Red, Green and NIR bands are all very similar, with
differences between them on the order of 1% or less. For low clouds, the Blue
band can be up to 5% higher than the Red due to the increased Rayleigh
scattering above the cloud-tops. This difference decreases as the cloud-top
height increases.
