MOPITT Cloud Detection Algorithm
Juying Warner, David Grant, and
NCAR/MOPITT team members
Abstract
The measurements of Pollution in the Troposphere (MOPITT) instrument aboard the
Earth Observing System (EOS) Terra spacecraft measures tropospheric CO and CH4 by
use of a nadir-viewing geometry. MOPITT cloud algorithm detects and removes
measurements contaminated by clouds before retrieving CO profiles and CO and CH4
total column amounts. This algorithm combines MOPITT radiances and MODIS
(MODerate-resolution Imaging Spectroradiometer) cloud mask to achieve maximum
coverage and accuracy. The cloud detection algorithm using only MOPITT radiances
will be reviewed. The collocation method between MOPITT and MODIS field of views
is also described. The performances of the cloud mask using only MOPITT radiances are
evaluated when compared with MODIS cloud mask on a global base. A hybrid method
that combines MOPITT and MODIS cloud mask is developed to optimize global
coverage and accuracy of MOPITT CO and CH4 products.
1
1. Introduction
The measurements of Pollution in the Troposphere (MOPITT) instrument aboard
the Earth Observing System (EOS) Terra spacecraft measures tropospheric CO and CH4
by use of a nadir-viewing geometry (Drummond, 1992)1. The MOPITT instrument is a
gas correlation radiometer that measures the CO profiles by the use of atmospheric and
terrestrial thermal radiation in the spectral region near 4.7 µm. It also measures the CO
and CH4 total column amounts by the use of reflected solar radiation in the spectral
regions of 2.3 and 2.2 µm, respectively. In these spectral regions, the radiances are very
sensitive to attenuation by clouds in the instrument field of views (FOVs). Wylie et al.
(1994) 2 studied global cloud coverage using four years of High-Resolution Infrared
Radiation Sounder (HIRS) data with a spatial resolution of 20 km X 20 km at nadir and
found that only approximately 22-25% of the pixels were cloud free. Because MOPITT
has a FOV of 22 km X 22 km, a large percentage of its global data set will be covered, or
partially covered, with clouds.
MOPITT cloud detection (MOPCLD), which used only MOPITT information,
compares the observed thermal and solar radiances against model calculated clear sky
radiances to determine the presence of clouds in the FOV as described by Warner et al.
(2001) 3. The radiative transfer forward model used in MOPITT cloud detection and
retrieval was developed and described by Edwards et al. (1999) 4. MOPCLD was
developed by using simulated MOPITT radiances and tested against aircraft
measurements. This report reviews MOPCLD procedures that are currently used in the
MOPITT operational processor and discusses MOPCLD performances by comparing its
decisions with those from other instruments.
MODIS instrument, also aboard EOS/Terra, was designed to determine cloud
properties and other physical properties in the atmosphere. MODIS cloud mask
(Ackerman et al., 1998) 5 is used in MOPITT cloud detection algorithm by combining
with MOPCLD to achieve maximum accuracy and global coverage. MOPITT and
MODIS footprints are collocated and the technique is described in section 3. To
maximize the global coverage pixels with low cloud covers are identified and used in
MOPITT retrieval, since MOPITT radiances are not sensitive to the portion of the
atmosphere close to the surface, and hence, to low cloud. This hybrid method that
combines MOPCLD and MODIS cloud mask is discussed in Section 5.
2. Review of MOPITT cloud detection algorithm
MOPCLD threshold method compares the observed radiances with calculated
clear sky radiances, and currently only one MOPITT thermal channel at 4.7 µm is used.
For each MOPITT spectral band, there are two sets of signals, average signals and
difference signals (Drummond, 1992)1. An average signal is the average of the two
signals taken in each MOPITT modulation by the sensor, and the average signals
generally represent the background radiation. A difference signal is the difference of the
two signals in each modulation and is primarily used to retrieve CO and CH4 information.
Only average signals are examined for cloud detection.
2
MOPITT cloud thresholds, based on observed channel radiance and model
calculated clear column radiance, are for day- and nighttime as:
Rch1A_observed/Rch1A_calculated  0.955
(5)
In inequalities (5), Rch1A is the Average radiance from channel-1, which is the CO channel
from the Length Modulation Cell (LMC) at a nominal cell pressure of 20 kPa
(Drummond, 1992)1. When temperature inversions occur in the atmosphere clouds are
warmer than the underlying surface, the Rch1A ratio between cloudy and clear scenes may
be greater than 1. The threshold method based on thermal information will not work in
areas where the surface radiative cooling is very large. Therefore, only latitudes within
65 degrees North and South are included in this method.
MOPITT solar channels are not currently used in the L2 processing since detailed
study of calibration is still underway. This information will be added to MOPITT L2
cloud detection in the ways discussed by Warner et al., 20013. Validation of MOPCLD
has been focused on comparisons with other satellite instruments, and some results from
the comparisons to MODIS cloud mask are summarized in section 4.
3. Collocation of MOPITT and MODIS field of views
MOPITT and MODIS instruments are aboard the same satellite platform and their
measurements overlap a large geographical area close to nadir and are at the same time.
MOPITT sensors scan across orbit from one side at approximately 30 satellite viewing
angle to the other side, pausing for approximately 0.45 seconds to take measurements of
an array of four 22X22km pixels. This array of four pixels is called a stare. Between
each two stares, the sensors jump over a viewing angle equivalent to a pixel size leaving
a gap between two stares, and after the sensors reach one side, they return in the same
scan pattern and fill up the gaps. Figure 1 shows a schematic drawing of a MOPITT
track (29 stares) overlaid by MODIS cloud mask pixels. MODIS instrument, on the other
hand, scans in a continuous circle across orbit and takes measurements of the earth within
55 satellite angles. The MODIS swaths are more than twice as wide as those of the
MOPITT and provide complete overlap for MOPITT passes. The spatial resolution of
MODIS cloud mask is 1X1 km, even though some of the MODIS cloud decisions are
based on higher resolution measurements (250mX250m and 500mX500m) (Ackerman et
al., 1998) 5. Therefore, each MOPITT pixel can be collocated to approximately 484
MODIS 1X1km pixels.
To find the compromise between minimizing processing time and achieving
accurate collocation, we match only one nadir pixel from each MOPITT track of 116
pixels to a MODIS pixel using latitude and longitude information. We then map the
pixels from each instrument using index numbers relative to the pair of collocated pixels.
For each MOPITT pixel, we include a fixed set of index numbers from a MODIS granule
and determine the cloudiness of the MOPITT pixel based on the cloud decisions of the
3
MODIS pixels. The matching of indices from both instruments is derived based on the
measurement viewing angles. When the view angle of a MODIS pixel falls within a
MOPITT view angle, the MODIS pixel is collocated to that MOPITT pixel. MODIS
detectors are grouped in 10 in each scan path, and at large satellite zenith angles the
pixels from one 10-pixel group overlap with the adjacent groups. Therefore, in each
MOPITT pixel there are more MODIS pixels at the edges of a path than at nadir due to
bow-tie effect.
Figure 1. Example of MODIS cloud
mask (as image) collocated to a
MOPITT track, whose footprints are
estimated as yellow rectangular. The
color of the image is based on MODIS
cloud mask confidence levels, black –
99% confidence clear, blue – 95%
confidence clear, pink – 66% confidence
clear, and white – cloudy.
Figure 1 shows an example of
the collocated MOPITT and MODIS pixels. The approximated MOPITT pixel footprints
are outlined in yellow boxes, and MODIS pixels are shown as an underlying image.
Black refers to 99% confidence clear, blue is 95% confidence clear, and white is cloudy.
The 66% confidence clear is plotted in pink, but not shown due to the lack of pixels in
that category in this example. For the definitions of MODIS cloud mask confidence
levels, see Ackerman et al. (1998) 5.
The cloudiness of a MOPITT pixel can be calculated by taking the ratio of the
number of MODIS cloudy pixels to the total number of MODIS pixels inside the
MOPITT pixel. The definition of clear for a MOPITT pixel depends on how much cloud
the radiances can tolerate before impacting the retrievals beyond the precision
requirements. If, however, any non-zero cloudiness in a MOPITT pixel is considered
cloudy, the number of cloud free MOPITT pixels is very low. To find the appropriate
cloud tolerance level, we compare the global coverage with the standard deviations of CO
Table 1: Cloud-free MOPITT global coverage based on MODIS cloud mask at different
cloud tolerances. Total pixels: 423772 (60S–60N).
Cloud Tolerance
0.0%
2.5%
3.0%
4.0%
5.0%
6.0%
7.5%
10.0%
Cloud-free MOPITT pixels
Number of pixels
54392
89062
92191
98004
102400
106311
111401
119085
4
Cloud-free MOPITT pixels
Global Percentage coverage
12.8%
21.0%
21.8%
23.1%
24.2%
25.1%
26.3%
28.1%
retrievals for different levels of cloudiness. Table 1 lists the cloud-free global coverage
at each cloud tolerance level from 0.0% to 10%. Note that the global coverage is too low
(12.8%) if cloud tolerance is set to zero. Five percent of cloud tolerance agrees the most
with previous studies (Wylie et al., 1994) 2, and it is used in the MOPITT operational
cloud detection routines. The impact of 5% cloud tolerance to MOPITT CO retrievals is
discussed in the next section.
4. Comparisons of cloud masks between MOPITT and MODIS
MOPCLD is compared against MODIS cloud mask for Aug. 23, 2000 global
dataset. Only latitudes within 60 North and South are included in this test because the
qualities of MOPCLD at high latitudes are not reliable. NCEP meteorological and
climatological data are used in the forward model calculations. Both MOPITT CO
products and MODIS cloud mask presented in this section are older version beta
products, and V3 versions are available now for both instruments.
Table 2 shows a summary of the comparison results. The first column lists the
cloud tolerance levels and the second column lists the percent of pixels for which
MOPCLD and MODIS cloud mask agree. For a zero cloud tolerance (second row),
MOPCLD and MODIS cloud mask agree for 83% of all pixels globally, which include
both clear and cloudy cases. Column 3 shows the cases where pixels are classified as
cloudy by MODIS cloud mask and as clear by MOPCLD. MOPCLD failed to detect
approximately 10% of the cloudy pixels compared with MODIS cloud mask. Nearly 7%
of the clear pixels classified by MODIS are detected as cloudy by MOPCLD as shown in
column 4. At 5% cloud tolerance level, there is an 80% agreement between the two
cloud algorithms and MOPCLD fails to detect approximately 6% of the cloudy pixels.
Table 2: Comparison of MODIS cloud mask and MOPITT cloud detection. Total pixels:
423772 (60S–60N); MOPITT clear pixels: 66764 (16%).
Cloud
Tolerance
0.0%
2.5%
3.0%
4.0%
5.0%
6.0%
7.5%
10.0%
MODIS and
MOPITT agree
83.3%
81.0%
80.8%
80.2%
79.8%
79.4%
78.9%
78.1%
MODIS cloudy
MOPITT clear
9.8%
6.9%
6.6%
6.2%
5.9%
5.6%
5.3%
4.8%
MODIS clear
MOPITT cloudy
6.9%
12.1%
12.6%
13.6%
14.3%
15.0%
15.8%
17.1%
To determine the effects of undetected cloud on MOPITT CO retrieval, we have
studied the mean and standard deviation (SDV) of CO total column retrievals while
allowing several levels of cloud contamination that passed MOPCLD threshold tests
erroneously. Table 3 lists the mean and SDV of CO mixing ratio (in ppbv) at levels 350,
500, 700, 850mb, and total column CO (in Mol/cm2x1016), respectively, for eight levels
of contamination by undetected clouds. The levels of cloud contamination are shown in
5
the first column where the lower bounds of the ranges of cloud cover in each MOPITT
pixel are listed. The percentage cloud covers are determined by MODIS cloud mask.
For an example shown at the 3rd row in Table 3, we sampled the pixels that passed
MOPITT cloud detection and that contained less than 2.5% cloud cover in each pixel
determined from MODIS cloud mask. The percent ratios of the SDVs over the means for
CO mixing ratios and total column amount range from 8 (total column CO) - 14% (CO
mixing ratio at 850hPa). For undetected cloud over 30%, the percentage range of SDVs
over means increases to 12 – 20%. In summary, using only MOPITT thermal radiance
threshold tests causes approximately 4-6% decrease in precision.
Table 3: The mean and SDV of CO mixing ratio at levels 350, 500, 700, 850mb, and total
column CO, respectively, at eight levels of contamination by undetected cloud.
Undetected
cloud
0%
2.5%
5%
10%
15%
20%
25%
30%
350 mb
ppbv
mean
sdv
87.31 9.38
87.24 9.68
87.19 10.1
87.18 10.6
87.1
10.8
87.2
10.9
87.3
11.0
87.5
11.2
500 mb
ppbv
mean
sdv
103.3 9.79
103.7 11.0
103.9 11.6
103.7 12.3
103.8 12.5
104.0 12.9
104.3 13.1
104.6 13.4
700 mb
ppbv
mean
sdv
128.0 17.2
128.3 18.6
128.5 19.8
128.0 21.3
128.3 22.2
128.8 22.6
129.5 23.1
129.9 23.9
850mb
ppbv
mean
sdv
143.9 20.3
144.1 22.0
144.3 23.5
143.8 25.3
144.1 26.6
144.7 27.2
145.6 27.8
146.1 28.8
Total Col.
Mol/cm2x1016
mean
sdv
216.4
19.2
216.4
21.4
216.5
22.5
216.0
23.6
216.0
24.6
216.6
25.1
217.5
25.8
218.1
26.5
As discussed in the last section, a five-percent cloud tolerance is used when
MODIS cloud mask is incorporated into MOPITT operational cloud algorithm to obtain
reasonable global coverage. Table 3 raw 4 represents the retrieval uncertainties when
both MOPITT threshold tests and MODIS cloud mask are used to detect cloud. With 5%
or lower undetected cloud contamination, the percent ratios of SDVs over means range
approximately 10-15%. This is a decrease of approximate 1% precision compared with if
2.5% or less cloud tolerance were used, however, the global coverage increases by 3%
when a 5% cloud tolerance is used.
Note that Table 3 includes only clouds that cannot be detected by MOPCLD
threshold method, and if all clouds were included the SDVs would have been much
higher. Undetected clouds by MOPCLD represent mostly low-level clouds since
MOPITT thermal channel weighting functions peak at and above 850hPa (Pan et al.,
1995) 6. The thermal channel radiances are not very sensitive to clouds with tops below
850hPa. These radiances can be used in MOPITT CO mixing ratio profile retrieval once
areas with low level clouds can be located.
5. A hybrid method for MOPITT V3:
To maximize accuracy and global coverage, MODIS cloud mask and MOPCLD
are combined in MOPITT V3 cloud detection algorithm. A MOPITT pixel is considered
clear when both methods agree as clear and when there is only low cloud in the FOVs.
Additional tests are taken to locate low level cloud when MODIS cloud mask classifies a
6
pixel as cloudy and MOPCLD classifies it as clear. When MODIS cloud mask classifies
a pixel as cloudy and MOPCLD classifies it as clear, this pixel is considered cloudy. In
areas MODIS cloud mask is not available only MOPCLD is used, and only MODIS
cloud mask is used in the polar-regions (above 65N and below 65S).
Low level cloud tests are performed when MODIS cloud mask identifies a pixel
as cloudy and MOPCLD as clear. This indicates mostly that MOPITT thermal channel
radiance for this pixel is not very sensitive to the cloud detected by MODIS cloud mask.
Individual tests from the mask are examined to determine what physical properties are
involved in this cloudy decision. Figure 2 shows an example of MOPCLD decision,
MODIS cloud mask decision and 7 test flags in the mask for 2000 MOPITT pixels for
Figure 2. An example of MOPCLD decision, MODIS cloud mask decision and 7 test
flags in the mask for 2000 MOPITT pixels.
daytime cases only. The left top panel shows MOPCLD radiance ratio (Robs/Rcal) in green
and percent cloud cover determined from MODIS pixels inside each MOPITT pixel (in
red). The left second panel shows the IR threshold flags from MODIS cloud mask
averaged to MOPITT resolution. The left third and forth panels show the brightness
temperature (BT) difference test and visible reflectance test, respectively. The right 1st
through 4th panels show cirrus test, 1.38m channel test, 3.9-11m test, and visible ratio
test, respectively. No-cloud is indicated when the flags are one, and cloud when zero
(Ackerman et al., 1998)5. A value between zero and one is the average value of MODIS
pixels within a MOPITT pixel, indicating that some MODIS pixels are cloudy and some
are clear.
7
In this example, the majority of the pixels are clear from MOPCLD decisions
shown as Robs/Rcal being larger than 0.95. The IR temperature threshold, BT difference
tests and the 1.38m high cloud test test, as well as the cirrus test, indicate clear for the
majority of the pixels especially for pixel numbers from 1.07x104 to 1.2x104. However,
the visible reflectance test, visible ratio test and BT11-BT3.8 test show the presence of
clouds in the FOVs. This is an indication that the clouds under consideration are warmer,
and in general, lower clouds.
The IR temperature threshold test simply checks the brightness temperature (BT)
over ocean and the colder pixels are considered cloudy. BT difference test uses the
principle of the differential water vapor absorption that exists between different window
regions (8.6 and 11m and 11 and 12m). This test is effective in measuring high and/or
thin clouds. When BT difference test views a pixel as clear erroneously, the condition of
the contaminating cloud is very similar to the underlying surface, and therefore, the cloud
is most likely low cloud. Cirrus cloud test and 1.38m high cloud test are both sensitive
to high and thin cloud and their decisions confirm that the majority of the pixels in the
example in Figure 2 are low clouds. The cloudy decisions from MODIS cloud mask for
these pixels are based on the visible and solar nature of the clouds. Note that the pixels in
this example are not necessary adjacent pixels.
To achieve maximum efficiency in data processing, we use only a minimum
number of flags to detect daytime low clouds. When MOPCLD detects a pixel as clear
and MODIS cloud mask is cloudy, we check the IR temperature threshold test and the
visible reflectance test. When the average value of the IR temperature threshold test is
greater than 0.9 and the visible reflectance test is less than 0.95, this pixel is classified as
over low clouds. These thresholds are chosen to allow certain range of noise introduced
in determining the test flags with the belief that the cloud characteristics are similar
within the size of a MOPITT pixel.
For nighttime, only BT difference test is examined when MODIS cloud mask
decision is cloudy and MOPCLD is clear. Most of the nighttime tests are effective for
high clouds such as CO2 spectral band test for high clouds, H2O spectral band test for
high clouds, 1.38m, BT3.7-BT12, and BT difference tests. For details of these tests see
Ackerman et al., 1998. Low clouds at night are most likely detected by BT11-BT3.8 or
temporal consistency and spatial variability test over water. We isolated cases as low
clouds when they can not be detected by high cloud tests but detected by other/low cloud
tests.
The global coverage of MOPITT CO retrieval has increased to 27-30% for V3,
from about 20-25% for MOPCLD only, and from approximately 13% for MODIS cloud
mask only at zero cloud tolerance. This is a significant improvement over the previous
versions of MOPITT processor. We also studied the SDVs of the CO retrieval to
evaluate the quality of the V3 cloud processing. Table 4 lists The SDVs of CO total
column amounts when MODIS and MOPCLD agree as clear skies (2nd and 4th columns)
and when low-clouds are added (3rd and 5th columns) for over ocean (a) and over land (b)
8
for Aug. 23, 2000. The rows are for each 5-degree latitude range and are listed by the
lower bounds. The SDVs changes for ocean at daytime are within 5% and in most of
the latitude range there is approximately no change. For ocean at nighttime the SDVs
changes are larger for the tropical area and are very small over the rest of the areas. The
higher SDVs over tropical region at night may be due to contamination by undetected
thin cirrus clouds and further study is necessary. Over land, in most of the areas the
SDVs increase by less than 10%, but in some areas the change is more than 30%. Further
validations are necessary to locate the sources of uncertainties.
Table 4. The SDVs of CO total column amounts when MODIS and MOPCLD
agree as clear skies (2nd and 4th columns) and when low-clouds are added (3rd and 5th
columns) for over ocean (a) and over land (b). The rows are for each 5-degree latitude
range and are listed by the lower bound.
Lat
60
55
50
45
40
35
30
25
20
15
10
5
0
-5
-10
-15
-20
-25
-30
-35
-40
-45
-50
-55
-60
Daytime
Nighttime
MODIS/MOPCLD Low -cloud MODIS/MOPCLD Low -cloud
2.2 4E+1 8
2.3 1E+1 8
2.2 1E+1 8
2.2 7E+1 8
2.3 0E+1 8
2.3 3E+1 8
-999 9
2.3 1E+1 8
2.3 2E+1 8
2.1 7E+1 8
-999 9
2.2 9E+1 8
2.2 6E+1 8
2.2 4E+1 8
2.3 8E+1 8
2.3 5E+1 8
2.1 5E+1 8
2.1 5E+1 8
2.1 7E+1 8
2.2 7E+1 8
2.2 4E+1 8
2.2 3E+1 8
2.2 0E+1 8
2.2 1E+1 8
2.3 1E+1 8
2.2 5E+1 8
2.2 3E+1 8
2.2 4E+1 8
1.9 1E+1 8
2.0 0E+1 8
1.9 5E+1 8
2.0 7E+1 8
2.0 1E+1 8
2.0 8E+1 8
1.9 6E+1 8
1.9 9E+1 8
2.1 2E+1 8
2.0 6E+1 8
2.1 8E+1 8
2.0 4E+1 8
2.0 3E+1 8
2.0 8E+1 8
2.1 7E+1 8
2.0 8E+1 8
1.9 4E+1 8
2.0 2E+1 8
2.2 5E+1 8
2.0 2E+1 8
1.8 6E+1 8
1.9 1E+1 8
1.5 5E+1 8
1.8 6E+1 8
1.9 0E+1 8
1.9 1E+1 8
1.4 7E+1 8
1.7 3E+1 8
1.7 3E+1 8
1.7 3E+1 8
1.7 5E+1 8
1.6 7E+1 8
1.7 4E+1 8
1.6 8E+1 8
1.7 7E+1 8
1.6 9E+1 8
1.7 5E+1 8
1.6 6E+1 8
1.7 7E+1 8
1.6 4E+1 8
1.7 1E+1 8
1.6 2E+1 8
1.6 0E+1 8
1.5 8E+1 8
1.4 8E+1 8
1.5 0E+1 8
1.7 5E+1 8
1.5 8E+1 8
1.4 4E+1 8
1.4 2E+1 8
1.4 5E+1 8
1.4 4E+1 8
1.3 9E+1 8
1.4 1E+1 8
1.4 2E+1 8
1.3 9E+1 8
1.2 2E+1 8
1.3 0E+1 8
1.1 7E+1 8
1.2 5E+1 8
1.0 6E+1 8
1.1 2E+1 8
1.0 8E+1 8
1.1 0E+1 8
9.1 1E+1 7
9.3 7E+1 7
8.8 6E+1 7
8.3 0E+1 7
8.4 0E+1 7
8.4 7E+1 7
-999 9
9.7 6E+1 7
Lat
60
55
50
45
40
35
30
25
20
15
10
5
0
-5
-10
-15
-20
-25
-30
-35
-40
-45
-50
-55
-60
Daytime
Nighttime
MODIS/MOPCLD Low -cloud MODIS/MOPCLD Low -cloud
2.6 0E+1 8
1.9 9E+1 8
1.8 6E+1 8
2.0 4E+1 8
2.3 4E+1 8
1.8 4E+1 8
2.0 0E+1 8
2.2 3E+1 8
2.1 5E+1 8
2.3 9E+1 8
1.6 2E+1 8
2.0 5E+1 8
2.2 5E+1 8
2.5 5E+1 8
1.5 5E+1 8
2.0 2E+1 8
2.0 7E+1 8
2.2 6E+1 8
1.5 0E+1 8
1.6 7E+1 8
2.1 4E+1 8
2.4 3E+1 8
1.2 6E+1 8
1.7 5E+1 8
2.0 3E+1 8
2.3 2E+1 8
1.5 2E+1 8
1.7 6E+1 8
2.2 0E+1 8
2.3 5E+1 8
1.7 9E+1 8
1.9 0E+1 8
2.1 5E+1 8
2.4 7E+1 8
1.9 7E+1 8
1.9 5E+1 8
2.1 9E+1 8
2.3 3E+1 8
2.2 7E+1 8
2.1 6E+1 8
2.2 6E+1 8
2.4 1E+1 8
2.1 1E+1 8
2.4 7E+1 8
2.4 4E+1 8
2.1 7E+1 8
2.1 9E+1 8
2.1 6E+1 8
2.1 9E+1 8
2.2 6E+1 8
2.1 9E+1 8
2.4 6E+1 8
2.2 3E+1 8
2.1 3E+1 8
1.7 6E+1 8
2.2 2E+1 8
1.8 9E+1 8
1.7 9E+1 8
1.5 9E+1 8
1.9 8E+1 8
1.7 3E+1 8
1.6 6E+1 8
-999 9
1.9 4E+1 8
1.7 6E+1 8
1.7 6E+1 8
1.6 8E+1 8
1.7 1E+1 8
1.6 4E+1 8
2.1 4E+1 8
1.5 2E+1 8
1.6 0E+1 8
1.6 2E+1 8
1.7 7E+1 8
1.3 9E+1 8
1.4 7E+1 8
1.6 4E+1 8
1.4 7E+1 8
1.3 2E+1 8
1.3 8E+1 8
1.8 4E+1 8
1.2 9E+1 8
1.1 3E+1 8
1.3 3E+1 8
1.0 9E+1 8
1.1 3E+1 8
1.2 0E+1 8
1.2 2E+1 8
1.1 3E+1 8
1.2 0E+1 8
-999 9
1.0 8E+1 8
9.1 0E+1 7
8.0 4E+1 7
-999 9
9.4 6E+1 7
-999 9
-999 9
-999 9
-999 9
a: ocean
b: land
Users are strongly encouraged to check cloud descriptions in the MOPITT L2 products
before using MOPITT products. Available cloud descriptions are listed in Table 5. For V3, only
Cloud Descriptions 1 through 5 are included in MOPITT products. Cloud Description 0 will be
added once MOPITT solar channel radiances are available. Cloud Descriptions 6 through 10 are
reserved for cloud-cleared pixels and cloud clearing is not operating for V3. Cloud Descriptions
11 through 15 are used in a file that stores the radiances discarded due to cloud and other
reasons.
Table 5: Cloud descriptions in MOPITT L2 products.
Cloud Description
0
MOPCLD only clear, thermal and cloudtop used
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
MOPCLD only clear, thermal only
MOPCLD and MODIS cloud mask agree on clear
MODIS cloud mask only clear (when MOPCLD cloudy)
MOPCLD overriding MODIS cloud mask over low clouds
(MODIS test flags used)
MODIS cloud mask only, clear over polar regions
reserved for cloud cleared pixels
reserved for cloud cleared pixels
reserved for cloud cleared pixels
reserved for cloud cleared pixels
reserved for cloud cleared pixels
MOPCLD only, cloudy (when MODIS data missing)
First 2 stares in a pocket discarded
MOPCLD and MODIS cloud mask agrees on cloudy
MOPCLD clear, MODIS cloudy and failed low cloud tests
MODIS cloud mask only, cloudy over polar regions
6. Summary:
We have used MODIS cloud mask in MOPITT cloud algorithm in two ways:
evaluating the quality of cloud detection with MOPCLD and in a hybrid method that
combines cloud decisions from both instruments. Cloud detection decisions from
MOPCLD and MODIS cloud mask agree for 80% of the total pixels. However, a large
number of pixels in the MOPITT CO retrievals are contaminated with cloud if only
MOPCLD is used. When only MODIS cloud mask is used, the global coverage is very
low because all types of clouds are detected including those that MOPITT radiances are
not sensitive to. MOPITT V3 hybrid method uses MODIS cloud mask to detect clear
pixels and to help detecting low clouds. The global coverage of MOPITT products has
increased by more than 50% compared with using MODIS cloud mask only or MOPCLD
only. MOPITT products at the polar-regions are added because of the use of MODIS
cloud mask. The uncertainties defined by the ratios of the SDVs over the means have
been reduced from MOPCLD only cases.
The validations of MOPITT cloud detection algorithm have been limited to the
comparisons with MODIS cloud mask. Global validations of this method against ground
and aircraft cloud measurements are necessary. Further improvements of MOPITT cloud
detection included the use of MOPITT solar channels. To further increase the global
coverage of the MOPITT products, techniques that reconstruct clear column radiances
using the cloudy measurements are being studied.
Acknowledgements
The National Aeronautics and Space Administration (NASA) Earth Observing System
(EOS) Program funded this work under contract NAS5-30888. Meteorological data was
provided by NASA DAO. The authors wish to thank Dr. Steven Ackerman and the
MODIS cloud mask team at the CIMMS/University of Wisconsin for providing MODIS
cloud mask information and many communications. MODIS cloud mask datasets are
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provided by NASA Goddard DAAC. The operational processing of the collocation of
MOPITT and MODIS measurements are carried out at NASA Langley DAAC.
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