CLOUDS.DOC
1. TITLE
1.1 Data Set Identification.
Monthly cloud products (C2)
(Monthly ; ISCCP/GISS)
1.2 Data Base Table Name.
Not applicable.
1.3 CD-ROM File Name.
\DATA\RADIATN\CLOUDS\nnn_nnnn\YyyMmm.sfx
Where nnn_nnnn is the parameter name (The Cloud data has 4 types of
parameters, see table below). Note: capital letters indicate fixed
values that appear on the CD-ROM exactly as shown here, lower case
indicates characters (values) that change for each path and file.
The format used for the filenames is: YyyMmm.sfx, where yy is the last
two digits of the year (e.g., Y87=1987), and mm is the month of the year
(e.g., M12=December). The filename extension (.sfx), identifies the
parameter in the file. Below is the list of extensions and their
associated parameters:
Parameter Description Parameter Directory Name Extension
-----------------------------------------------------------------------
Cloud Amount CLD_AMNT CAM
Cloud Top Pressure CLD_TPPR CTP
Cloud Optical Thickness CLD_OPTH COT
Cloud Water Path CLD_PATH CWP
1.4 Revision Date Of This Document.
April 5, 1995
2. INVESTIGATOR(S)
2.1 Investigator(s) Name And Title.
Dr. William B. Rossow
NASA Goddard Institute for Space Studies
2.2 Title Of Investigation.
International Satellite Cloud Climatology Project (ISCCP).
2.3 Contacts (For Data Production Information).
________________________________________________________
| Contact 1 |
______________|_________________________________________|
|2.3.1 Name |Alison Walker |
2.3.2 Address |ISCCP Global Processing Center |
|NASA Goddard Institute for Space Studies |
|2880 Broadway |
City/St.|New York, NY |
Zip Code|10025 |
2.3.3 Tel. |(212) 678-5542 |
2.3.4 Email |claww@nasagiss.giss.nasa.gov |
______________|_________________________________________|
________________________________________________________
| Contact 2 |
______________|_________________________________________|
|2.3.1 Name |Dr. William B. Rossow |
2.3.2 Address |ISCCP Global Processing Center |
|NASA Goddard Institute for Space Studies |
|2880 Broadway |
City/St.|New York, NY |
Zip Code|10025 |
2.3.3 Tel. |(212) 678-5567 |
2.3.4 Email |clwbr@nasagiss.giss.nasa.gov |
______________|_________________________________________|
2.4 Requested Form of Acknowledgment.
Pleas cite the following publication when these data are used:
Rossow, W.B., L.C. Garder, P.J. Lu and A.W. Walker, 1991. International
Satellite Cloud Climatology Project (ISCCP) Documentation of Cloud
Data. WMO/TD-No. 266 (revised), World Meteorological Organization,
Geneva, 76 pp. plus three appendices.
Rossow, W.B., and R.A. Schiffer, 1991: ISCCP cloud data products. Bull.
Amer. Meteor. Soc., 72:2-20.
3. INTRODUCTION
3.1 Objective/Purpose.
The purpose of the ISCCP C2 monthly mean cloud data is to provide a
global climatology of cloud properties to be used in the study of global
radiation balance and hydrological cycle.
3.2 Summary of Parameters.
Monthly mean; for cloud amount, cloud top pressure, cloud optical
thickness and cloud water path.
3.3 Discussion.
The ISCCP Stage C2 data represent a monthly summary of the ISCCP C1 data
(Rossow and Schiffer, 1991). Monthly averages are first made at constant
diurnal phase for each of the 3-hour periods; eight sets of averages for
each month describe the mean diurnal variations of cloud and surface
properties. The complete monthly mean is then constructed by averaging
these eight sets. The cloud data on this CD-ROM consists only of the
complete monthly mean data.
4. THEORY OF MEASUREMENTS.
The primary data sets used to infer the cloud properties are the Stage B3,
reduced resolution narrowband radiance (600 nm and 11,000 nm) measurements
made by the imaging radiometers on operational weather satellites (Schiffer
and Rossow, 1985; Rossow et al., 1987). These data have a nominal spatial
resolution of 30 km and temporal resolution of 3 hours produced by up to five
geostationary satellites (METEOSAT, INSAT, GMS, GOES-EAST and GOES-WEST) and
up to two polar orbiting NOAA satellite. Only one year of complete INSAT data
have been obtained but they are not included here. The absolute radiometric
calibration of all B3 radiances have been normalized to that of the AVHRR on
NOAA-7 in July 1983. Subsequent comparisons to aircraft data led to a
revision of the VIS radiance calibration, accomplished by multiplying all
values by a factor of 1.2. This corrected calibration is used to produce the
cloud products. No change was made in the IR absolute calibration.
The Stage C Cloud Data Products are produced by analysis of the visible (VIS =
600.0 nm) and thermal infrared (IR = 11,000 nm) radiances from all of the
satellites, merged into a single global product, and reduced in volume by
summarizing cloud variations at a 280 km resolution (equivalent to 2.5 degrees
lat/long at the equator). Stage C1 data report global results every 3 hours
(Rossow et al., 1991). Stage C2 data are monthly summaries of the Stage C1
data with the same spatial resolution and including mean diurnal variations.
The ISCCP C2 cloud data on this CD-ROM contains only the complete monthly mean
data for the parameters; cloud amount, cloud top pressure, cloud optical
thickness and column total of water. Note that the latter two parameters are
measured only during daytime, when visible radiances are available. This
version of water path was calculated after computing the spatial average cloud
optical thickness, from which it is derived; hence, the values reported are
expected to systematically underestimate actual water path values.
5. EQUIPMENT.
The primary ISCCP data set is radiance data obtained from a global set of
operational weather satellite imaging radiometers, which have in common a
narrowband spectral channel at about 600 nm near the peak of the solar
spectrum and one in the atmosphere's thermal opacity "window" near 11,000 nm.
Some of these radiometers have additional channels. The spatial resolution of
the raw images ranges between 1 - 4 km (visible channel) and between 4 - 7 km
(infrared channel). Imaging frequency (for a specific low latitude location)
varies from 48 to 14 times per day for geostationary satellites to twice daily
for polar orbiting satellites.
5.1 Instrument Description.
5.1.1 Platform.
The ISCCP data were derived from data obtained from the
following instruments/platforms:
Instruments Platforms
--------------------------------------------------------------
Advanced Very High Resolution National Oceanic Atmospheric
Radiometer (AVHRR) Administration Polar Orbiting
Environmental Satellite
(NOAA)
TIROS (Television and Infrared National Oceanic Atmospheric
Operational Satellite) Administration Polar Orbiting
Operational Vertical Sounder Environmental Satellite
(TOVS) (NOAA)
Visible Infrared Spin-Scan Geostationary Operational
Radiometer (VISSR) Environmental Satellites
(GOES)
Multispectral Imaging METEOSAT
Radiometer (MIR)
Visible Infrared Spin-Scan Geostationary Meteorological
Radiometer (VISSR) Satellite (GMS)
Visible Infrared Spin-Scan INSAT
Radiometer (VISSR)
5.1.2 Mission Objectives.
These are operational weather satellites.
5.1.3 Key Variables.
Radiances measured approximately at visible (600 nm) and near
infrared (11,000 nm) wavelengths were used from these instruments
to produce the ISCCP B3 data.
5.1.4 Principles of Operation.
NOAA/AVHRR:
The AVHRR is a four or five channel scanning radiometer that
operates in the visible, near-infrared, and far-infrared regions.
The fifth channel was added on the AVHRR/2 instrument flown on
NOAA-7, -9, -11 and -12. Scanning is provided by an elliptical
beryllium mirror rotating at 360 rpm about an axis parallel to the
Earth. A two-stage radiant cooler is designed to provide a basic
temperature of 95 degrees K for the IR detectors. The telescope
is an 8-inch afocal, all-reflective system, with polarization of
less than 10 percent. Instrument operation is controlled by 26
commands and monitored by 20 analog housekeeping parameters.
GOES/VISSR:
The VISSR instrument operates in the visible region of 0.55 to
0.75 micrometers and in the infrared region of 10.5 to 12.6
micrometers. Each of the eight photo-multiplier tubes on the
visible detector is 0.025 X 0.021 mrads, with a dynamic range of
3-100% albedo. The infrared portion of the instrument consists of
two detectors cooled to 95 degrees K, with an instantaneous field-
of-view (IFOV) of 192 X 192 microradians. The VISSR telescope has
an aperture of 40 cm and a focal length of 291 cm, and routes the
IR wavelengths to separate detectors. The video analog output of
all detectors is transmitted to the VISSR Digital Multiplexer
(VDM) where it is sequentially sampled every 2 microseconds by the
visible channel and every 8 microseconds by the IR channel.
METEOSAT/MIR:
The Multispectral Imaging Radiometer (MIR) sensor on METEOSAT is a
scanning radiometer which provides images in the visible and
thermal IR regions of the spectrum. The instrument produces
images of the full Earth disc viewed from a geostationary orbit.
A reduced image format, corresponding to a limited band across the
Earth's disc, may be selected by telecommand. The optical
reflector system of the radiometer includes a movable Ritchey-
Chretien telescope with primary and secondary mirrors. This
includes a mirror located in the center of the primary mirror
inclined at 45 degrees to the optical axis, four folding mirrors,
and a separation mirror for diverting light to the visible sensor.
The optically-collected visible and IR signals are converted into
analog electric signals by five detectors. These are divided into
two subsets, two visible and three IR. The detectors are
distributed across the focal plane of the radiometer and as a
result of the relative displacement of the detectors in this
plane, their respective fields-of-view (FOV) do not coincide but
are displaced relative to each other.
The two visible detectors are positioned in the focal plane of the
primary telescope. Their instantaneous FOV at the Earth's surface
(2.5 square km) is determined by their physical size (250 X 250
micrometers sensitive area) and the telescope's focal length (3650
millimeters). While the visible detectors function properly at
ambient temperatures, the three IR detectors must be cooled to
less than 95 degrees K.
Each IR detector is 70 square micrometers and generates an
instantaneous 5 km square FOV at the subsatellite point. One
visible channel time shares with the water vapor channel so that
the resolution of the visible image changes depending on the
choice of channels.
GMS/VISSR:
The GMS Visible and IR Spin-Scan Radiometer (VISSR) is very
similar to the scanning radiometers carried on Synchronous
Meteorological Satellite (SMS) and GOES (1 through 3) satellites
except for some modifications to stepping gears and detector
portions. The number of steps in each scan is 2500 for the IR
detector on GMS versus 1821 for GOES.
INSAT/VISSR:
The INSAT VISSR is also a scanning radiometer with a visible
channel covering 0.55 to 0.75 micrometers and an IR channel
covering the 10.5 to 12.5 micrometer spectral regions. The full
disc can be scanned every half-hour (23 minute scan plus 7 minute
housekeeping), processing from north to south. Sector scanning of
the 1/4 disc (full east to west, 1/4 north to south) is possible
every 6 minutes.
5.1.5 Instrument Measurement Geometry .
The following table lists the measuring geometry characteristics
for the satellites employed by the ISCCP program:
SATELLITE SCAN SYSTEM SCAN DIRECTION IMAGE VIEWING
ANGLE
------------------------------------------------------------------
NOAA Cross-track Moving south to 55.4 degrees
scan mirror north, scanning
west to east
GOES Spacecraft spin Stepping north to 20 X 20 degrees
motion plus south, scan west
scan mirror to east
METEOSAT Spacecraft spin Stepping south to 18 X 18 degrees
motion plus north, scan east
scan mirror west
GMS Spacecraft spin Stepping north to 18 X 18 degrees
motion plus south, scan west
scan mirror to east
INSAT Spacecraft spin Stepping north to Not available
motion plus south, scan east
scan mirror to west
------------------------------------------------------------------
5.1.6 Manufacturer of Instrument.
Not available at this revision.
5.2 Calibration.
Calibration procedures for the instruments can be found in Rossow et
al., (1987), Brest and Rossow (1992), and Desormeaux et al., (1993).
5.2.1 Specifications.
See section 5.2.
5.2.1.1 Tolerance.
See section 5.2.
5.2.2 Frequency of Calibration.
See section 5.2.
5.2.3 Other Calibration Information.
Although procedures are applied to normalize the radiances
measured by various satellites to the reference polar orbiter
(afternoon) measurements (Rossow et al. 1987), the precision of
the normalization procedures leaves small residual differences
which can be amplified by the process to retrieve physical
quantities. The collection of monthly comparison statistics
provides more statistical weight with which to estimate these
residuals.
To produce Stage C1 data, results from several satellites are
merged into a single global dataset. In regions where more than
one satellite provides results, the merger process selects the
preferred satellite according to a specified hierarchy that favors
data continuity and observations made closer to nadir view.
Frequency histograms of the differences in the overlapping
measurements between all pairs of satellites are collected and the
modal value estimated from the average of the mode value and the
three nearest values above and below the mode value. These
estimated differences for each satellite when compared to the
reference polar orbiter are applied to adjust for small residual
radiance calibration differences. The quantities in the hour-
monthly mean that are corrected are: cloud optical thickness and
water path. Magnitudes of these corrections are illustrated in
the table bellow.
Magnitude of calibration adjustments applied to Stage C2 data to
remove small residual calibration differences shown as the
standard deviation and range of all corrections applied to each
satellite over the period July 1983 - February 1987.
PARAMETER STD DEV RANGE
--------------------------------------------------------------
Cloud Optical Thickness 0.02 + or - 0.08
Cloud Water Path 0.02 + or - 0.08
Special METEOSAT adjustment
The spectral response of the METEOSAT "visible" channel is wider
than that of the other radiometers used in the ISCCP analysis;
normalization of METEOSAT radiances is done using spectrally
uniform targets (clouds and clear ocean areas). The spectral
response difference means that surface reflectance determined for
vegetated land areas are larger for METEOSAT than for the other
satellites. This difference in surface reflectance is removed in
the hour-monthly mean dataset by using regression relations that
are obtained by comparing METEOSAT and NOAA measurements as a
function of vegetation type and season. A single relationship that
varies with season was found to represent differences as a
function of vegetation type. Adjustment factors are applied for
each season and are given in the table below. Unadjusted values
can be recovered from Stage C2 values by multiplying by the slopes
given in the table below and adding the intercept values.
Adjustment factors applied to METEOSAT land surface reflectances
to reduce them to values measured at an approximate wavelength of
600 + or - 100 nm. Seasons are the standard three-month periods
for the northern hemisphere.
Adjustment: Adjusted = (original value - intercept)/slope
SLOPE INTERCEPT
---------------------
SEASON: Winter 0.893 0.1154
Spring 0.786 0.1135
Summer 0.752 0.1290
Fall 0.820 0.1362
6. PROCEDURE
6.1 Data Acquisition Methods.
The data sets described in this document were acquired from the
Greenhouse Effect Detection Experiment (GEDEX) CD-ROM. For more
information on the GEDEX CD-ROM contact the Goddard DAAC User support
office (see section 13). For additional information on data acquisition
of ISCCP-C2 data see Rossow et al., (1991).
6.2 Spatial Characteristics.
The Goddard DAAC converted the original ISCCP C2 data to a 1 degree equal
angle lat/long grid (see section 9.3.1). For information on the spatial
characteristics of the original ISCCP C2 data see Rossow et al., (1991).
6.2.1 Spatial Coverage.
The coverage is global. Data in each file are ordered from North
to South and from West to East beginning at 180 degrees West and
90 degrees North. Point (1,1) represents the grid cell centered
at 89.5 N and 179.5 W (see section 8.4).
6.2.2 Spatial Resolution.
The data are given in an equal-angle lat/long grid that has a
spatial resolution of 1 X 1 degree lat/long.
6.3 Temporal Characteristics.
6.3.1 Temporal Coverage.
January 1987 through December 1988.
The original ISCCP C2 data set covers the period from July 1983
through June 1991.
6.3.2 Temporal Resolution.
Monthly mean.
7. OBSERVATIONS
7.1 Field Notes.
Not applicable.
8. DATA DESCRIPTION
8.1 Table Definition With Comments.
Not applicable.
8.2 Type of Data.
--------------------------------------------------------------------------------
| 8.2.1 | | | |
|Parameter/Variable Name | | | |
--------------------------------------------------------------------------------
| | 8.2.2 | 8.2.3 | 8.2.4 | 8.2.5 |
| |Parameter/Variable Description |Range |Units |Source |
--------------------------------------------------------------------------------
|CLD_AMNT | | | |
| |The average frequency of cloudy |min = 0, |[percent] |ISCCP C2 |
| |(cloud amount) pixels |max = 100.0, | |on the |
| | |missing = | |GEDEX |
| | |-99.000 | |CD-ROM |
--------------------------------------------------------------------------------
|CLD_TPPR | | | |
| |Mean cloud top pressure |min = 1.0, |[millibars|ISCCP C2 |
| | |max = 1100.0, |] |on the |
| | |missing = | |GEDEX |
| | |-99.000 | |CD-ROM |
--------------------------------------------------------------------------------
|CLD_OPTH | | | |
| |Mean optical thickness |min = 0.2, |[Unitless]|ISCCP C2 |
| | |max = 119.59, | |on the |
| | |missing = | |GEDEX |
| | |-99.000 | |CD-ROM |
--------------------------------------------------------------------------------
|CLD_PATH | | | |
| |Cloud water mass (cloud water |min = 1.25, |[g] [m^-2]|ISCCP C2 |
| |path), per unit area |max = 752.46, | |on the |
| | |missing = | |GEDEX |
| | |-99.000 | |CD-ROM |
--------------------------------------------------------------------------------
8.3 Sample Data Base Data Record.
Not applicable.
8.4 Data Format.
The CD-ROM file format is ASCII, and consists of numerical fields of
varying length, which are space delimited and arranged in columns and
rows. Each column contains 180 numerical values and each row contain 360
numerical values.
Grid arrangement
ARRAY(I,J)
I = 1 IS CENTERED AT 179.5W
I INCREASES EASTWARD BY 1 DEGREE
J = 1 IS CENTERED AT 89.5N
J INCREASES SOUTHWARD BY 1 DEGREE
90N - | - - - | - - - | - - - | - -
| (1,1) | (2,1) | (3,1) |
89N - | - - - | - - - | - - - | - -
| (1,2) | (2,2) | (3,2) |
88N - | - - - | - - - | - - - | - -
| (1,3) | (2,3) | (3,3) |
87N - | - - - | - - - | - - - |
180W 179W 178W 177W
ARRAY(360,180)
8.5 Related Data Sets.
ISCCP-B3 data: reduced resolution radiances.
ISCCP-TV data: TOVS atmospheric properties.
ISCCP-SI data: merged snow and sea ice dataset.
ISCCP-C1 data: 30-hr cloud product.
9. DATA MANIPULATIONS
9.1 Formulas.
9.1.1 Derivation Techniques/Algorithms.
The cloud analysis algorithm for ISCCP-C1 was developed from a
three year pilot study that compared the performance of nine
different algorithms applied to the same data (Rossow et al.,
1985; Rossow, W.B. and R.A. Schiffer, 1991). This algorithm has
three fundamental parts: cloud detection, radiative transfer
model analysis, and statistical analysis.
A. Cloud Detection.
The cloud detection step analyzes the radiance data twice: first
to determine an estimate for the radiance values that represent
clear conditions and second, to determine which radiance
measurements deviate from these clear sky values (Rossow and
Garder, 1993a). Cloudy conditions are defined to be those that
exhibit radiance values that are sufficiently different from the
clear values.
To avoid spurious diurnal variations of cloudiness caused by
changes in methodology associated with the presence or absence of
VIS data, the clear sky composite procedure relies primarily on IR
radiance tests to obtain both the VIS and IR clear radiances.
However, since the daytime results can be improved by use of the
VIS channel measurements, these results are incorporated so that
the IR-only results can be reconstructed.
The algorithm used to produce this C1 data does not use any
correlative data to construct the clear sky composite, except four
classification data sets that indicate whether a particular
location is land, water, or coast, gives the type of vegetation
cover for land areas, indicates the presence of snow or sea ice
cover, and whether the topography is high or rough.
B. Radiative Transfer Model Analysis
Once pixels are classified as cloudy or clear, the radiances are
compared to radiative transfer model calculations designed to
simulate the measurements of the AVHRR channels (to which all the
radiometers have been normalized). These comparisons are used to
isolate the surface reflectances and temperatures from the clear
radiances and the cloud optical thicknesses and cloud top
temperatures from the cloudy radiances (Rossow et al. 1991).
Atmospheric properties that affect the satellite measured
radiances are specified from the correlative data.
C. Statistical Analysis
Averages and variances of all cloud, surface and radiance
quantities are reported in C1 data for 280 km regions; however,
only average quantities are included in the CD dataset. Cloud
parameters represent averages over all cloudy pixels in each
region at that time.
A single C1 data file represents the merging of analysis results
from all available satellites within the three hour time period.
The basic objective of the ISCCP-C2 analysis is to summarize the
cloud analysis results (Stage C1 data) on a monthly time scale.
To preserve information about diurnal variability, the results are
first averaged over the calendar month, separately for 00, 03, 06,
09, 12, 15, 18, and 21 GMT. Then, these eight results
are averaged to obtain the monthly mean values, but first
a number of adjustments are made.
Averaging the quantities from Stage C1 data to produce the Stage
C2 data can be done in two ways, depending on the purpose. Some
quantities, such as cloud optical thickness or cloud top
temperature, are related to the effect of clouds on radiation in a
non-linear way. Thus, an average value meant to be indicative of
the average radiative effect of clouds must give equal weight to
these values proportional to their radiative effect. Since these
quantities were retrieved from radiation measurements, this
weighting is also related to the variation of relative measurement
precision over the range of the parameters. All quantities in
Stage C2 data are averaged in this way, except for parameter 20,
called PATH. For most parameters, this weighting procedure
produces an average value that is not much different than that
given by a simple linear average. This is not the case for cloud
optical thickness, where a simple linear average produces a global
monthly mean value that is about 60% larger than that produced by
an energy-weighted average. The optical thicknesses give the
value that represents the average radiative effect of the clouds,
whereas water path is proportional to the cloud water content
times the vertical extent of the cloud. Optical thicknesses are
averaged in a non-linear manner, while water path represents the
linear average of optical thickness. For a constant cloud
particle size distribution (as assumed in the retrieval of optical
thicknesses), cloud water path, WP, is given by
WP = [40/3]*[r~ * PATH]/Q kg/m**2
where r~ is the average particle radius in cm, and Q is the
normalized Mie extinction efficiency at 0.6 micrometers
wavelength. For the cloud particle size distribution used, with
r~ approximately equal to -.001 cm,
WP = 6.292 PATH g/m**2
9.2 Data Processing Sequence.
9.2.1 Processing Steps and Data Sets.
The ISCCP C1 data are produced from the analysis of a reduced
resolution satellite radiance dataset (B3 data), together with
four correlative datasets that describe properties of the
atmosphere and surface. The B3 data have a nominal 30 km
resolution. Radiance values at the 30 kilometer resolution for
each of the sensors are normalized to the polar orbiter radiometer
response. Stage C1 data represent the global, merged results
reported every 3 hours with a spatial resolution of 280 km; Stage
C2 data are the monthly averages and the other summary statistics
of the Stage C1 quantities. The ISCCP-C2 data on this CD-ROM is
comprised of complete monthly means for the parameters; cloud
amount, cloud top pressure, cloud optical thickness and cloud
water path. The Goddard DAAC converted this data from it's
original grid to a 1 degree equal angle grid (see section 9.3.1).
9.2.2 Processing Changes.
Not available at this revision.
9.3 Calculations.
9.3.1 Special Corrections/Adjustments.
The mean cloud properties reported in the C1 product are the final
values from the radiative analysis. This means that the daytime
values of cloud top temperature (TC) and cloud top pressure (PC)
have been altered by the effects of the VIS channel measurements.
Since the same adjustment is not performed at night, direct
comparison of the day and night values of cloud top temperature
and pressure must be interpreted with caution. However, the
vertical distribution of clouds can be reconstructed from cloud
classes and the mean IR radiance values. The visible only (VIS-
ONLY) numbers can be subtracted from the total number of pixels at
each pressure level, while the IR radiances can be used to
estimate the cloud top temperature and pressure without TAU
corrections.
Producing the ISCCP-C2 product involved performing a number of
adjustments on the ISCCP-C1 data before determining the monthly
averages. The adjustments necessary included VIS adjustments
during daytime, VIS adjustments during nighttime, calibration
adjustments, standard adjustments, special METEOSAT adjustments,
and diurnal adjustments
VIS adjustments during daytime (Adj1):
In the Stage C1 data, two different versions of cloud amount and
cloud top temperature/pressure are reported for daytime
conditions. One version of cloud amount is obtained from the IR
radiances alone, as must be done for nighttime conditions; the
other version combines cloud detections from both the VIS and IR
radiances. IR radiances are insensitive to low-level clouds,
especially broken ones, the VIS radiances analysis detects more
low-level cloudiness than the IR analysis. Likewise, one version
of the cloud top temperature/pressure is obtained directly from
the IR radiances as is done for nighttime conditions and the other
version adjusts the values consistent with the cloud optical
thickness value retrieved from the VIS radiances. This adjustment
is significant only for optically thin clouds, which transmit IR
radiation from below the cloud and, consequently, appear to have a
higher temperature/pressure than they actually do. Thus, the
VIS/IR version is superior to the IR-only version. Stage C2 data
contain the VIS/IR versions of cloud amount, cloud top temperature
and cloud top pressure.
VIS adjustments during nighttime (Adj2):
The mean differences between the VIS/IR and IR-only results during
daytime conditions are used to adjust the nighttime results in the
hour-monthly mean data. Daytime differences between VIS/IR and
IR-only values of total cloud amount, mean cloud top pressure and
cloud top temperature are linearly interpolated over the nighttime
periods between the dusk and dawn values. This interpolated
difference is then added to the IR-only value during this time
period. The magnitude of these corrections is generally small.
The smaller (<= 5%) cloud amount adjustments are distributed
nearly uniformly over the globe with values slightly higher over
ocean than over land. The larger adjustments occur in near
coastal regions, land and ocean, in low latitudes primarily
associated with tropical rain forests and marine stratus regimes.
The unadjusted cloud amount is reported as the last parameter in
each map grid cell. The cloud top pressure correction is positive
where low clouds predominate, primarily in marine stratus regimes
over oceans, and negative where high, thin clouds predominate,
primarily over land, especially in desert areas.
Interpolation to fill during nighttime (Adj3)
Values of the cloud optical thickness (both TAU and PATH) are
interpolated over the nighttime period between the dusk and dawn
values.
Standard adjustment (Adj4):
To produce Stage C1 data, results from several satellites are
merged into a single global dataset. In regions where more than
one satellite provides results, the merger process selects the
preferred satellite according to a specified hierarchy that favors
data continuity and observations made closer to nadir view.
Frequency histograms of the differences in the overlapping
measurements between all pairs of satellites are collected and the
modal value estimated from the average of the mode value and the
three nearest values above and below the mode value. These
estimated differences for each satellite, when compared to the
reference polar orbiter, are applied to adjust for small residual
radiance calibration differences. The corrected quantities in the
hour-monthly mean are: cloud top and surface temperature, cloud
optical thickness and water path, and surface reflectance.
Magnitudes of these corrections are illustrated in the table
below. Actual calibration adjustments for each month are reported
in the record prefixes for each parameter for each satellite.
The magnitude of the calibration adjustments applied to Stage C2
data to remove small residual calibration differences are shown
here as the standard deviation and range of all corrections
applied to each satellite over the period July 1983 - February
1987.
Parameter Std Dev Range
----------------------------- ------- ---------
Cloud Top Temperature 0.74 K + - 2.5 K
Surface Temperature 1.10 K + - 3.0 K
Cloud Optical Thickness
and Water Path 0.02 + - 0.08
Surface Visible Reflectance 2% + - 8%
Special METEOSAT adjustment (Adj5):
The spectral response of the METEOSAT "visible" channel is wider
than that of the other radiometers used in the ISCCP analysis;
normalization of METEOSAT radiances is done using spectrally
uniform targets (clouds and clear ocean areas). The spectral
response difference means that surface reflectances calculated for
vegetated land areas from METEOSAT are larger than for the other
satellites. This difference in surface reflectance is removed in
the hour-monthly mean dataset by using regression relations that
are obtained by comparing METEOSAT and NOAA measurements as a
function of vegetation type and season. A single relationship
that varies with season was found to represent differences as a
function of vegetation. Adjustment factors are applied for each
season and are given in the table below. Unadjusted values can be
recovered from Stage C2 data by multiplying by the slopes (given
in the table below) and adding the intercept values.
Adjustment factors applied to METEOSAT land surface reflectances
to reduce them to values measured at an approximate wavelength of
0.6 + to - 0.1 micrometers are shown in the table below. Seasons
are the standard three-month periods in the northern hemisphere.
Adjustment: Adjusted Value = (Original Value - Intercept)/Slope
Season Slope Intercept
------ ----- ---------
Winter 0.893 0.1154
Spring 0.786 0.1135
Summer 0.752 0.1290
Fall 0.820 0.1362
Diurnal adjustment (Adj6):
Before the hour-monthly means are combined into a monthly mean,
small corrections are made to account for incomplete sampling of
the diurnal variations of cloud and surface properties. An
incomplete sample is less than 8 hour-monthly observations at low
and middle latitudes. These adjustments are determined using the
zonally averaged variations of the quantities in local time at all
locations with eight hour-monthly mean values available. The
diurnal average is calculated for the number of samples actually
available and compared with the average of eight samples to
determine the effect of sub-sampling on the diurnal average. The
calculations are performed within each latitude interval,
separately for land and water areas. The quantities that are
adjusted are the total cloud amount, cloud top temperature and
pressure, cloud optical thickness and water path, and the surface
temperature. These adjustments affect only the monthly mean
values and are not applied to the individual hour-monthly means.
Below is a description of the re-gridding process done by the
Goddard DAAC:
Physical Lay Out of Original Data: These data were subset
from the GEDEX CD. Resulting input data consisted of one file
for both 1987 and 1988. Within the file the data were
arranged with the four chosen parameters for a grid cell and
corresponding time, latitude, and longitude per line.
Logical Lay Out of Original Data: These data were on a 2.5 x
2.5 degree lat/lon grid (72 by 144 grid cells), with the data
starting at 0 longitude, -90 latitude and progressing eastward,
and then northward to 360 longitude, 90 latitude.
Processing steps done by the Goddard DAAC: Regrid each
latitude and longitude band of data by implementing the
following steps:
1) Replicated every data value in each latitude band 360 times,
assigning them to a temporary array. Each of the original
latitude bands had 144 data values, which replicated 360
times produces a temporary array of 51840 data values for
that latitude band.
2) The first 144 (temporary array) data values are summed and
then divided by the number (144) of original latitude band
values. This was repeated 359 more times, for every 144
(temporary array) data values, in affect performing a linear
interpolation of the data within the latitude band.
3) Step 1 and 2 were repeated until all latitude bands have
been interpolated.
4) A test for fill value occurrance was performed. If fill
value constitutes 50% or more of contributing values then
assign a fill value to that grid cell, otherwise compute the
average data value for grid cell from only those points
constituting data values. When assigning fill values, a new
fill value was used, as the existing one was extremely
large.
5) The same method, discussed above, was used for regridding
each longitude band of data, except that the number of
replications was 180. Utilizing the same test for fill
value mentioned above, and the same fill substitution.
6) The resulting array of data values were then split and
shifted from 0 longitude -> 360 longitude to -180 longitude
-> 180 longitude.
7) These data were then flip from -180 longitude, -90 latitude
to -180 longitude, 90 latitude.
9.4 Graphs and Plots.
Not available at this revision.
10. ERRORS
10.1 Sources of Error.
Some situations where the cloud properties are more uncertain are:
persistently cloudy locations, winter sea ice, and snow-covered land.
10.2 Quality Assessment.
10.2.1 Data Validation by Source.
Errors in clear-sky radiances (Rossow and Garder, 1993b),
suggest uncertainties in the ISCCP cloud detections of about 10%
with a small (3%-6%) negative bias over land. Some specific
regions exhibit both larger rms uncertainties and somewhat
larger biases in cloud amount approaching 10%. ISCCP cloud
detections are more in error over the polar regions than
anywhere else. Based on comparisons with and analysis of
radiances measured at other wavelengths. The ISCCP analysis
appears to miss 15%-25% of the clouds in summer but only 5%-10%
of the winter clouds.
The ISCCP cloud amounts appear (Rossow et al., 1993) too low
over land by about 10%. Somewhat less in summer and somewhat
more in winter, and about right (maybe slightly low) over
oceans. In polar regions, ISCCP cloud amounts are probably too
low by about 15%-25% in summer and 5%-10% in winter. Comparison
of the ISCCP climatology to three other cloud climatolgies shows
excellent agreement in the geographic distribution and seasonal
variation of cloud amounts: there is little agreement about
day/night contrasts in cloud amount. Notable results from ISCCP
are that the global annual mean cloud amount is about 63%. Being
about 23% higher over oceans than over land. The magnitude of
interannual variations of local (280-km scale) monthly mean
cloud amounts is about 7%-9%.
For additional information on assessment of cloud detection and
cloud amount errors, see Rossow and Garder (1993a).
For preliminary assessments of the radiation model errors, see
Minnis et al. 1993, Han et al. 1994, Rossow and Zhang 1994.
10.2.2 Confidence Level/Accuracy Judgment.
See section 10.2.1.
10.2.3 Measurement Error for Parameters and Variables.
See section 10.2.1.
10.2.4 Additional Quality Assessment Applied.
Not available at this revision.
11. NOTES
11.1 Known Problems With The Data.
Not available at this revision.
11.2 Usage Guidance.
Not applicable.
11.3 Other Relevant Information.
Not available at this revision.
12. REFERENCES
12.1 Satellite/Instrument/Data Processing Documentation.
Rossow, W.B., L.C. Garder, P-J. Lu and A.W. Walker, 1991.
"International Satellite Cloud Climatology Project (ISCCP)
Documentation of Cloud Data." WMO/TD No. 266 (revised). World
Meteorological Organization, Geneva, 76 pp. plus three appendices.
Rossow, W.B., E. Kinsella, A. Wolf, L. Garder, July 1985. revised August
1987. "International Satellite Cloud Climatology Project
Description of Reduced Resolution Radiance Data." WMO TD-No. 58,
World Meteorological Organization/International Council of
Scientific Unions.
World Climate Research Program, November, 1982. "The International
Satellite Cloud Climatology Project Preliminary Implementation
Plan." World Meteorological Organization. WCP-35.
12.2 Journal Articles and Study Reports.
Brest, C.L., and W.B. Rossow, 1992. Radiometric calibration and
monitoring of NOAA AVHRR data for ISCCP. Int. J. Remote Sensing,
13:235-273.
Desormeaux, Y., W.B. Rossow, C.L. Brest and G.G. Cambell, 1993.
Normalization and calibration of geostationary satellite radiances
for ISCCP. J. Atmos. Ocean Tech., 10:304-325.
Han, Q., W.B. Rossow and A.A. Lacis, 1994. Near-global survey of
effective cloud droplet radii in liquid water clouds using ISCCP
data. J. Climate, 7:465-497.
Hirai, M. et al., 1975. "Development of Geostationary Meteorological
Satellite (GMS) of Japan." Proc. of the Eleventh International
Symposium of Space Technology and Science, Tokyo, Japan, 461-465.
Matthews, E., and W.B. Rossow, 1987. "Regional and Seasonal Variations
of Surface Reflectance from Satellites Observations at 0.6 um. J.
Climate Appl. Meteor., 26:170-202.
Minnis, P., and E.F. Harrison, 1984. "Diurnal Variability of Regional
Cloud and Clear Sky Radiative Parameters Derived from GOES Data.
Part I: Analysis Method." J. Climate Appl. Meteor., 23:993-1011.
Minnis, P., P.W. Heck and D.F. Young, 1993. Inference of cirrus cloud
properties using satellite-observed visible and infrared radiances.
Part II: Verification of theoretical cirrus radiative properties.
J. Atmos. Sci., 50:1305-1322.
Raschke, E., W. Rossow and R. Schiffer, 1987. "The International
Satellite Cloud Climatology Project - Preliminary Results and its
Potential Aspects." Advanced Space Research, 7:(3)137-(3)145.
Rossow, W.B., and L. Garder, 1984. "Selection of Map Grid for Data
Analysis and Archival." J. Climate Appl. Meteor., 23:1253-1257.
Rossow, W.B., F. Mosher, E. Kinsella, A. Arking, M. Desbois, E.
Harrison, P. Minnis, E. Ruprecht, G. Seze, C. Simmer and E. Smith,
1985. "ISCCP Cloud Algorithm Intercomparison." J. Climate Appl.
Meteor., 24:877-903.
Rossow, W.B., 1989. "Measuring Cloud Properties from Space: A Review."
J. of Climate, 2:201-213.
Rossow, W.B., L.C. Garder, and L.C. Lacis, 1989. "Global, Seasonal
Cloud Variations from Satellite Radiance Measurements, Part I:
Sensitivity of Analysis." J. of Climate, 2:419-458.
Rossow, W.B., C.L. Brest, and L.C. Garder, 1989. "Global, Seasonal
Surface Variations from Satellite Radiance Measurements." J. of
Climate, 2:214-247.
Rossow, W.B., and R.A. Schiffer, 1991. "ISCCP Cloud Data Products."
Bull. Amer. Meteor. Soc., 72: 2-20.
Rossow, W.B., and L.C. Garder, 1993a. Cloud detection using satellite
measurements of infrared and visible radiances for ISCCP. J.
Climate, 6:2341-2369.
Rossow, W.B., and L.C. Garder, 1993b. Validation of ISCCP cloud
detections. J. Climate, 6:2370-2393.
Rossow, W.B., A.W. Walker and L.C. Garder, 1993: Comparison of ISCCP
and other cloud amounts. J. Climate, 6:2394-2418.
Rossow, W.B., and Y. Zhang, 1994. Calculation of surface and top-of-
atmosphere radiative fluxes from physical quantities based on ISCCP
datasets. Part II: Validation and first results. J. Geophys.
Res., (in press).
Schiffer, R.A., and W.B. Rossow, 1983. "The International Satellite
Cloud Climatology Project (ISCCP) -- The First Project of the World
Climate Research Program." Bull. Amer. Meteor. Soc., 64: 779-784.
Schiffer, R.A., and W.B. Rossow, 1985. "ISCCP Global Radiance Data Set.
A New Resource for Climate Research." Bull. Amer. Meteor. Soc., 66:
1498-1505.
Seze, G., and M. Desbois, 1987. "Cloud Cover Analysis from Satellite
Imagery using Spatial and Temporal Characteristics of the Data." J.
Climate Appl. Meteor., 26: 287-303.
Seze, G., and W.B. Rossow, 1987. "Time-cumulated Visible and Infrared
Histograms used as Descriptor of Cloud Cover." Advanced Space
Research, 7:(3)155-(3)158.
Seze, G., and W.B. Rossow, 1991. "Time-cumulated Visible and Infrared
Radiance Histograms Used as Descriptors of Surface and Cloud
Variations." Int. J. Remote Sensing, 12:877-920.
Seze, G., and W.B. Rossow, 1991. "Effects of Satellite Data Resolution
on Measuring the Space/Time Variations of Surfaces and Clouds."
Int. J. Remote Sensing, 12:921-952.
12.3 Archive/DBMS Usage Documentation.
Contact the EOS Distributed Active Archive Center (DAAC) at NASA Goddard
Space Flight Center (GSFC), Greenbelt Maryland (see Section 13 below).
Documentation about using the archive or information about access to the
on-line information system is available through the GSFC DAAC User
Services Office.
For information about the ISCCP C2 data base archive contact the EOS
DAAC at NASA Langley Research Center (LaRC), Hampton VA. The Langley
DAAC User and Data Services Office may be contacted as follows:
User and Data Services
Langley DAAC
Mail Stop 157B
NASA Langley Research Center
Hampton, VA 23681-0001
Telephone: (804) 864-8656
FAX: (804) 864-8807
e-mail: userserv@eosdis.larc.nasa.gov
13. DATA ACCESS
13.1 Contacts for Archive/Data Access Information.
GSFC DAAC User Services
NASA/Goddard Space Flight Center
Code 902.2
Greenbelt, MD 20771
Phone: (301) 286-3209
Fax: (301) 286-1775
Internet: daacuso@eosdata.gsfc.nasa.gov
13.2 Archive Identification.
Goddard Distributed Active Archive Center
NASA Goddard Space Flight Center
Code 902.2
Greenbelt, MD 20771
Telephone: (301) 286-3209
FAX: (301) 286-1775
Internet: daacuso@eosdata.gsfc.nasa.gov
13.3 Procedures for Obtaining Data.
Users may place requests by accessing the on-line system, by sending
letters, electronic mail, FAX, telephone, or personal visit.
Accessing the GSFC DAAC Online System:
The GSFC DAAC Information Management System (IMS) allows users to
ordering data sets stored on-line. The system is open to the public.
Access Instructions:
Node name: daac.gsfc.nasa.gov
Node number: 192.107.190.139
Login example: telnet daac.gsfc.nasa.gov
Username: daacims
password: gsfcdaac
You will be asked to register your name and address during your first
session.
Ordering CD-ROMs:
To order CD-ROMs (available through the Goddard DAAC) users should
contact the Goddard DAAC User Support Office (see section 13.2).
13.4 GSFC DAAC Status/Plans.
The ISLSCP Initiative I CD-ROM is available from the Goddard DAAC.
14. OUTPUT PRODUCTS AND AVAILABILITY
14.1 Tape Products.
All ISCCP data sets are archived at the ISCCP Central Archives at
Contact:
Satellite Data Services Division
National Climatic Data Center
NOAA
Washington, DC 20233, USA
Telephone: (301) 763-1372
FAX: (301) 763-2635
All ISCCP data sets are also available from the Langley DAAC.
Contact:
User and Data Services
Langley DAAC
Mail Stop 157B
NASA Langley Research Center
Hampton, VA 23681-0001
Telephone: (804) 864-8656
FAX: (804) 864-8807
e-mail: userserv@eosdis.larc.nasa.gov
14.2 Film Products.
Not available at this revision.
14.3 Other Products.
ISCCP-C2 CD-ROM
Contact:
User and Data Services (See section 14.1).
GEDEX CD-ROM
Contact:
Goddard DAAC User Support Office (see section 13).
15. GLOSSARY OF ACRONYMS
AVHRR Advanced Very High Resolution Radiometer
CD-ROM Compact Disk (optical), Read Only Memory
DAAC Distributed Active Archive Center
EOS Earth Observing System
FOV Field of View
GAC Global Area Coverage
GCM General Circulation Model of the atmosphere
GEDEX Greenhouse Effect Detection Experiment
GMS Geostationary Meteorological Satellite
GOES Geostationary Operational Environmental Satellite
GSFC Goddard Space Flight Center
IDS Inter disciplinary Science
IFOV Instantaneous Field Of View
INSAT Indian National Satellite System
IR InfraRed
ISCCP International Satellite Cloud Climatology Project
ISLSCP International Satellite Land Surface Climotology Project
LAC Local Area Coverage
MIR Multispectral Imaging Radiometer
NASA National Aeronautics and Space Administration
NOAA National Oceanic and Atmospheric Administration
PC Cloud Top Pressure
pixel Picture element
RMS Root Mean Square
TAU Optical Thickness
TC Cloud Top Pressure
TIROS Television and Infrared Operational Satellite
TOVS TIROS Operational Vertical Sounder
VISSR Visible Infrared Spin-Scan Radiometer
WP Cloud Water Path