What is a Cloud (According to MODIS)

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What is a Cloud(According to MODIS)

• Steve Ackerman
• Rich Frey
• CIMSS/UW-Madison

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What is a cloud? I know one when I see one.
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What is a cloud? I know one when I see one.
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GCMs make extensive comparison with satellite
derived cloud amount. Total cloud amount from
different satellite algorithms can vary
significantly even among accepted standards, as
shown below in a comparison of annual zonal mean
cloud fraction from CLAVR, ISCCP and UW-HIRS.
Global distributions demonstrate expected
patterns but can differ in magnitude by more then
10.
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What is a cloud?

• The answer to that question is determined by the
  application. What is considered a cloud in some
  applications may be defined as clear in other
  applications.
• Detection of clouds is also a function of
  instrument capability and algorithm design.
• Cloud detection is a function of contrast between
  the target (e.g. cloud) and the background.
  Contrast can be
• Spatial Large fov are generally more uniform
  lowering contrast
• Temporal Clouds can be detected in a sequence
  of images if the clouds are moving
• Spectral Spectral contrast is determined by the
  radiative properties of the cloud and surface.

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What is a cloud? I know one when I see one.
Preparing for CALIPSO and MODIS
The number of occurrences that MAS scene was
identified as clear and the cloud physics lidar
(McGill, 2002) detected a cloud optical depths
(visible wavelengths). This figure suggests that
the cloud limit is approximately optical depth
0.3
Water, Weather
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The total cloud fraction is a function of cloud
optical depth, and the cloud fractions when
considering the plus and minus sigma values of
optical depth from June 2004. Each optical depth
time profile has an associated error bar due to
the molecular return and the density profile.
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GLI and MODIS observations were compared to the
HSRL site over the University of
Wisconsin-Madison. Comparison indicates passive
approach flags a cloudy region as Uncertain
Clear, the optical depth is less then
approximately 0.3.
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Field of View
The percent of total observations of clear
(blue), high cloud (green) and total cloud (red)
as a function of MODIS fov size. Smaller FOVs are
more likely to be all clear or all cloud cover.
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Additional spectral observations can improve
cloud detection capability.
Left Cloud fraction increase due to addition
cloud detected by the MODIS 1.38 micron channel.
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Top Zonal mean frequencies of cloudy conditions
for October 16,2003, daytime ocean scenes as a
function of three cloud detection tests and the
combination of all 16 tests from MODIS. Note, in
this case a single spectral test does very well.
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Zonal mean frequencies of cloudy conditions for
October 16,2003, daytime land scenes as a
function of three cloud detection tests and the
combination of all 16 tests from MODIS.
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Thresholds
0.86 reflectance (x-axis) versus the percentage
of pixels less then that value (e.g. cloud
fraction if this reflectance was a threshold )
for ocean scenes solar zenith angles and viewing
angle s between 0 - 10 degrees. For different
viewing geometries, the cloud detection threshold
varies. A small change in the threshold can
result in a large change in cloud amount.
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Sensitivity to Input Reflectance Biases and
Reflectance Thresholds Daytime Terra MODIS Data
from April 1, 2003 60N to 60S, No Snow/Ice
Nadir Cloud Amount ( 0.9? vza) Cloud Amount from All Pixels
Collection 5 Cloud Mask Water 68.9 Land 51.1 Water 72.7 Land 54.1
Increase All B1, B2 Reflectances by 5 of Original Water 69.4 (0.5) Land 51.4 (0.3) Water 73.3 (0.6) Land 54.6 (0.5)
Decrease All B1, B2 Reflectances by 5 of Original Water 68.4 (-0.5) Land 50.7 (-0.4) Water 72.2 (-0.5) Land 53.6 (-0.5)
Increase VIS/NIR Reflectance Test Thresholds by 1 Water 67.4 (-1.5) Land 50.8 (-0.3) Water 70.7 (-2.0) Land 53.6 (-0.5)
Decrease VIS/NIR Reflectance Test Thresholds by 1 Water 72.0 (3.1) Land 51.4 (0.3) Water 75.5 (2.8) Land 54.7 (0.6)
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Summary

• Cloud detection optical depth threshold limit
  appears to be approximately 0.3
• Cloud coverage varies with the spatial and
  spectral resolution of the instrument.
• Cloud detection thresholds vary as a function of
  viewing geometry, scene illumination and thermal
  structure of the scene.
• The dependence of cloud detection on these
  parameters and the need to monitor with changing
  instruments and satellites, will likely make it
  difficult to compare cloud amounts from different
  approaches and achieve the 1 accuracy needed for
  long-term monitoring of cloud amount.