Dr. William B. Rossow NASA Goddard Institute for Space Studies
________________________________________________________ | 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