NASA Climatology Interdisciplinary Data Collection

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[CIDC FTP Data] [ISCCP D2 IDC Data on FTP] Data Access ISCCP D2 Cloud Data Mean Mean cloud Mean cloud Mean cloud top mean cloud cloud fraction(%) top pressure temperature optical water thickness path Clear sky surface reflectance Clear sky surface temperature IR low cloud IR low cloud top IR low cloud top fraction(%) pressure temperature IR mid cloud IR mid cloud top IR mid cloud top fraction(%) pressure temperature IR high cloud IR high cloud top IR high cloud top fraction(%) pressure temperature Cumulus,liquid, Stratocumulus,liquid, Stratus,liquid, low cloud fraction(%) low cloud fraction(%) low cloud fraction(%) Cumulus, ice, Stratocumulus,ice , Stratus,ice, low cloud fraction(%) low cloud fraction(%) low cloud fraction(%) Altocumulus,liquid, Altostratus,liquid, Nimbostratus,liquid, mid cloud fraction(%) mid cloud fraction(%) mid cloud fraction(%) Altocumulus,ice, Altostratus,ice, Nimbostratus,ice, mid cloud fraction(%) mid cloud fraction(%) mid cloud fraction(%) Cirrus Cirrostratus high cloud high cloud Deep convective fraction(%) fraction(%) high cloud fraction(%) TOVS TOVS Ice/snow TOVS TOVS precipitable precipitable cover surface near-surface water(1000- 685 water (685 - pressure air temperature mb) 310 mb) [rule] Readme Contents Data Set Overview Sponsor Original Archive Future Updates The Data Characteristics Source The Files Format Name and Directory Information Companion Software The Science Theoretical Basis of Data Processing Sequence and Algorithms Scientific Potential of Data Validation of Data Contacts Points of Contact References [rule] Data Set Overview Cloud cover is an extremely important climate parameter. Though only some clouds bring precipitation, all affect the heat exchange between the Sun, Earth and cold space, and they are also quite variable in time, from region to region, and in the effects they produce. Clouds modulate the solar irradiance incident on the Earth's surface (the insolation) and this affects the productivity of plants both on land and in the water as well as the surface temperature and heat budget. Numerous efforts to produce cloud climatologies from both surface and satellite observations have been made. At present the most important of these is the ongoing International Satellite Cloud Climatology Project (ISCCP). A combination of satellite-measured radiances, TOVS atmospheric temperature/humidity and ice/snow data are used by ISCCP to produce a global dataset on cloud and surface variables. An overview of the Project and the data products is given in Rossow and Schiffer (1991); the algorithm and its effectiveness are described by Rossow and Garder (1993a&b) while Rossow et al. (1993) compare the resulting products to other cloud climatologies. The ISCCP D-series, which is described in this readme and more extensively in Rossow et al. (1996), is a revised version of the C-series dataset. The ISCCP D2-series products are gridded data averaged over each month. These data set(presently covering the period 1986-1987 & 1989-1992) are originally produced on an equal area map grids which has a constant 2.5 degree latitude increments and varaiable longitude increments ranging from 2.5 degree at the equator to 120 degree at the pole. The Goddard DAAC has regridded a subset (36 out of the original 130 parameters) of these dataset to 1x1 degree equal angle grid for inclusion in the Interdisciplinary data collection. Sponsor The production and distribution of this data set are funded by NASA's Earth Science enterprise. The data are not copyrighted; however, we request that when you publish data or results using these data please acknowledge as follows: The authors wish to thank William B. Rossow, and the Goddard Institute for Space Studies (GISS),New York, NY, USA, for the production of this data set, and the Distributed Active Archive Center (Code 902) at the Goddard Space Flight Center, Greenbelt, MD, 20771, for putting these data in their present format and distributing them. These distribution activities were sponsored by NASA's Earth Science enterprise. Original Archive The original ISCCP D2 cloud data set was produceded by the Goddard Institute for Space Studies at New York, NY. This data set in its original format can be obtained from NASA Langley Research Center, Distributed Active Archive Center . This is the long term archive for the data and also the source for detailed information concerning the ISCCP D series and other data products. Note: The format of the data in the GISS and LaRC archives is different than that stored at the Goddard DAAC. The Goddard DAAC regridded the original equal area grid to a 1 by 1degree (lat/lon) equal angle grid. For more details see Processing Sequence and Algorithms. Future Updates Additional years of the ISCCP D-2 data are being processed. The Data The monthly mean data is presented on 1x1 degree latitude-longitude world grid that starts at (89.5N, 179.5W) and runs eastward and southward to latitude 89.5 S. The original ISCCP D1 (daily) and D2 (monthly mean) products were calculated on an approximately equal area world grid (280x280 km^2) which is equivalent to a 2.5x2.5 degree latitude-longitude grid at the equator. The latitude band widths were fixed to 2.5 degree and grid size along the longitude was varied to provide an integer number of cells in a latitude zone and grid cell area as close to an equatorial grid cell as possible. Map grids started from south pole to north pole. In each latitude zone, all longitudes were indexed in order from the Greenwich meridian eastward(0 - 360 degree) before going to the next latitude zone. Here we have interpolated a subset (36 out of the original 130 parameters) of the equal area monthly mean products to a 1x1 degree grid for easy comparison to the other Interdisciplinary Data Collection products. Characteristics * Parameters: Parameter Description Range Units cldfrc mean cloud fraction 0.5 - percent 100 cldprs mean cloud top pressure 35 - millibars 985 cldtmp mean cloud top temperature 180 - Kelvin 320 cldtau mean cloud optical 0.09 - dimensionless thickness 50 cldwpt mean cloud water path 0 - g/m^2 400 srfref mean clear sky surface 0.0 - fraction reflectance 1.1 srftmp mean clear sky surface 199 - Kelvin temperature 325 irlfrc infrared cloud fraction, 0 - 93 percent for low-level clouds infrared cloud top irlprs pressure, for low-level 550 - millibars clouds 1000 infrared cloud top irltmp temperature, for low-level 225 - Kelvin clouds 315 irmfrc infrared cloud fraction, 0 - 82 percent for mid-level clouds infrared cloud top irmprs pressure, for mid-level 435 - millibars clouds 680 infrared cloud top irmtmp temperature, for mid-level 211 - Kelvin clouds 287 irhfrc infrared cloud fraction, 0 - 84 percent for high-level clouds mean infrared cloud top irhprs pressure, for high-level 20 - millibars clouds 495 infrared cloud top irhtmp temperature, for 180 - Kelvin high-level clouds 264 clfrc cumulus (liquid) low-level 0 - 80 percent cloud fraction stratocumulus sclfrc (liquid)low-level cloud 0 - 88 percent fraction slfrc stratus (liquid)low-level 0 - 50 percent cloud fraction cifrc cumulus (ice)low-level 0 - 72 percent cloud fraction stratocumulus scifrc (ice)low-level cloud 0 - 91 percent fraction sifrc stratus (ice) cloud 0 - 50 percent low-level fraction altocumulus aclfrc (liquid)mid-level cloud 0 - 38 percent fraction altostratus aslfrc (liquid)mid-level cloud 0 - 62 percent fraction nimbostratus nslfrc (liquid)mid-level cloud 0 - 75 percent fraction acifrc altocumulus (ice)mid-level 0 - 95 percent cloud fraction asifrc altostratus (ice)mid-level 0 - percent cloud fraction 100 mean nimbostratus nsifrc (ice)mid-level cloud 0 - 50 percent fraction crfrc mean cirrus high-level 0 - percent cloud fraction 100 crsfrc mean cirrostratus 0 - 77 percent high-level cloud fraction dcfrc mean deep convective 0 - 62 percent high-level cloud fraction iscvr mean ice/snow cover 0 - percent 100 tvprs TOVS mean surface pressure 475 - millibars 1000 tvtmp TOVS mean near-surface air 216 - kelvin temperature 322 tvprw1 TOVS mean precipitable 0 - 5 cm water for 1000 - 680 mb tvprw6 TOVS mean precipitable 0.03 - cm water for 680 - 310 mb 2.0 * Temporal Coverage: 1/86-1/87;1/89-12/93 are available in 1988) * Temporal Resolution: Gridded monthly means * Spatial Coverage: Global * Spatial Resolution: 1 degree x 1 degree equal angle grid (re-gridded from equal area grid) Source ISCCP was established in 1982 as part of the World Climate Research Programme (WCRP) to collect and analyze satellite radiance measurements to infer the global distribution of clouds, their properties, and their diurnal, seasonal, and interannual variations. Data collection began on 1 July 1983 and is currently planned to continue through 30 June 2000. The first phase of the project produced the gridded, 3-hourly (stage C1) and monthly (stage C2) datasets (Rossow, and Schiffer 1991, Rossow et al. 1989). A subset of the monthly mean C2 data, consisting of six parameters and covering the period of July 1983 to June 1991, is available as part of the Interdescipline Dataset Collection. In the second phase of the project new versions of products (D-series) have been produced, with the addition of a 30 km research product. The processing of the D-series data is on-going. There are four principle product levels: * Reduced Resolution Radiance Data(B3) These data are a reduced resolution version (in both time and space) of the original visible and infrared images from all of the operational weather satellites. The data consist of radiances (4-7 km pixels) spaced at 30 km interval, every 3 hours, from the individual satellites. The calibration and navigation data are also appended (Rossow et al., 1987). When the D algorithms were introduced, a new (BT) calibration table product was also added. * Pixel Level Cloud Product(DX) These products consist of calibrated radiances and viewing geometry, cloud detection results, cloud and surface properties from radiative analysis for individual satellite at a 30 km resolution. * Gridded Cloud Product(D1) These are spatial averages of the 3-hourly DX quantities and statistical summaries on a global equal area grid ( approximate 280 km by 280 km cell size). These products are obtained by merging the results from all satellites. The atmosphere and surface properties from TOVS are appended as well. * Climatological Summary Product(D2) The D2 products are monthly averages of D1 quantities and statistics including the data sets corresponding to eight 3-hourly monthly means( periods centered on, 0, 3, 6, 9, 12, 15, 18, and 21 hours UTC) for each product at equal area grid. There are a total of 130 parameters for each map grid cells in the original D2 data set. We have chosen 6 of these and only the monthly means (average of the eight 3-hour monthly mean sets) to include in the Interdisciplinary Data Collection. The resulting datasets and analysis products are being used to improve understanding and modeling of the role of clouds in climate, with the primary focus being the elucidation of the effects of clouds on the radiation balance. These data can also used to support many other cloud studies, including understanding of the hydrological cycle. Data are collected from the suite of weather satellites operated by several nations and processed by several groups in government agencies, laboratories, and universities. For each operational satellite, a Satellite Processing Center (SPC) collects the raw satellite data and sends it to the Global Processing Center (GPC). The Correlative Data Center coordinates the delivery of other satellite and conventional weather data to the GPC. The Satellite Calibration Center (SCC) normalizes the calibration of the geostationary satellites with respect to a polar orbiter satellite standard. All ISCCP data products are archived at the NASA Langley Research Center, Distributed Active Archive Center. The satellites involved in the D-version products are listed in the table below: Temporal and Regional Coverage Satellite Sensor start end Longitudes NOAA-7 AVHRR 07/83 01/85 global NOAA-8 AVHRR 10/83 06/84 global NOAA-9 AVHRR 02/85 10/88 global NOAA-10 AVHRR 12/86 08/91 global NOAA-11 AVHRR 11/88 09/94 global NOAA-12 AVHRR 09/91 ----- global NOAA-14 AVHRR 02/95 ----- global GOES-5 VISSR 07/83 07/84 112W-50W GOES-6 VISSR 07/83 01/89 135W-98W 04/87 04/92 135W-98W GOES-7 VISSR 05-92 ----- 112W-50W GOES-8 I-M Imager 03/95 ---- 112W-50W GOES-9 I-M Imager ----- ---- 135W-98W METEOSAT-2 MIR 07/83 07/88 60W-60E 08/88 06/89 60W-60E METEOSAT-3 MIR 02/90 04/90 60W-60E 05/92 04/95 112W-50W 07/89 01/90 60W-60E METEOSAT-4 MIR 05/90 01/94 60W-60E METEOSAT-5 MIR 06/95 ----- 60W-60E GMS-1 VISSR 02/84 05/84 140E 07/83 01/84 140E GMS-2 VISSR 07/84 09/84 140E GMS-3 VISSR 10/84 11/89 160W-80E GMS-4 VISSR 12/89 08/91 160W-80E GMS-5 VISSR 09/91 ---- 160W-80E INSAT-1 VHRR 04/88 03/89 74.5E Notes: NOAA-7, 9, 11 & 14 were/are afternoon polar orbiting satellites, while NOAA 8, 10 12 were/are morning polar orbiting satellites. NOAA-14 was launched as a afternoon satellite, because NOAA-13 launched failed. METEOSAT-3 was re-positioned, in May 1992, to a GOES-East position. The Files Compressed: The data files have been compressed using Lempel-Ziv coding. Files with a .gz ending are compressed versions of the .bin file. When decompressing the files use the -N option so that the original .bin file name ending is restored. For additional information on decompression see aareadme file in the directory: software/decompression/ Uncompressed: The ISCCP subset presented here consists of 3132 datafiles (=87 monthly mean data filess per parameter x 36 parameters). Though size of single data file is only .259 MB but if whole 4 years worth of data is downloaded it would require ~476 MB of disk storage. Format * File Size: 259200 bytes, 64800 data values * Data Format: IEEE floating point notation * Headers, trailers, and delimiters: none * Fill value: -999.99 * Continent mask: none (data valid over land and water) * Orientation: North to South Start position: (179.5W, 89.5N) End position: (179.5E, 89.5S) Name and Directory Information Naming Convention: The file naming convention for the monthly files is isccp_d2.pppppp.1nmegg.[yymm].ddd where isccp_d2 = data product designator pppppp = parameter (cldfrc,cldtmp,cldprs,cldtau,...) 1 = number of levels(=1) n = pressure levels for vertical coordinate, (n=not applicable) m = temporal period, (m = monthly) e = horizontal grid resolution, (e = 1 x 1 degree) gg = spatial coverage, gg = global (land and ocean) yy = year mm = month ddd = file type designation, (gz=compressed, bin=binary, ctl=GrADS control file) NOTE: When decompressing the data files be sure to use the -N option. This will restore the original .bin filename. For additional information on decompression see the format section of this readme and the aareadme file in the directory: software/decompression/ Directory Path: /data/inter_disc/radiation_clouds/isccp_d2/pppppp/yyyy/ where pppppp is the parameter and yyyy is year. Companion Software Several software packages have been made available on the CIDC CD-ROM set. The Grid Analysis and Display System (GrADS) is an interactive desktop tool that is currently in use worldwide for the analysis and display of earth science data. GrADS meta-data files (.ctl) have been supplied for each of the data sets. A GrADS gui interface has been created for use with the CIDC data. See the GrADS document for information on how to use the gui interface. Decompression software for PC and Macintosh platforms have been supplied for datasets which are compressed on the CIDC CD-ROM set. For additional information on the decompression software see the aareadme file in the directory: software/decompression/ Sample programs in FORTRAN, C and IDL languages have also been made available to read these data. You may also acquire this software by accessing the software/read_cidc_sftwr directory on each of the CIDC CD-ROMs The Science Theoretical Basis of Data The ISCCP cloud analysis has two main components, cloud detection and radiative analysis, respectively. The cloud detection component has four major steps, the first two were part of the C-series cloud product (Rossow and Garder 1993a), and the last two are new to the D-series. The first three steps, of the cloud detection component, produce the refined clear-sky radiances, while the fourth step is a final threshold test using the refined clear-sky radiances. A brief synopsis of the four steps are as follows: 1. The first estimate of the clear sky radiance values is derived by performing a series of test (Rossow et al. 1989) using space-time variations of the IR and VIS radiances. The VIS radiance are normalized and are expressed as fractional values of the sensor measurement when looking directly at the Sun. These unitless radiances go to zero as the solar zenith angle approaches 90 degrees; reflectance, on the other hand normally increase. 2. The first threshold test is performed by determining which radiance measurements deviate from the first clear sky values by an amount greater than the uncertainty in the estimated clear radiances. 3. Additional test are performed to remove some infrequent errors in the clear sky radiances that occur under certain circumstances. These test are performed based on the results of the first two test. Estimates of the daytime clear solar reflectance for the polar orbiting satellites NIR channel, are also acquired. 4. The final step involves repeating a threshold test using the final refined clear sky radiances, produced from the first three step, with three changes: o the IR thresholds for land surfaces are reduced by 2.0 K, o the VIS threshold test is changed to a test of reflectance values instead of radiance values, and o NIR threshold test is performed for polar orbiting data over ice and snow-covered surfaces only The first threshold test is done only on the IR and VIS, comparing them to the clear sky radiance derived in the first step. Any observed radiance which varies from the corresponding clear sky radiance by more than the threshold values is regarded as cloudy All remaining values are called clear. The threshold values vary (see table below) depending on surface type. First Cloud Threshold Values (Rossow et al., 1996) SURFACE TYPES RADIANCE 1 2 3 4 IR (K) 2.5 4.0 6.0 8.0 VIS (fraction of Sun looking measurement) 0.03 0.03 0.06 0.06 IR SURFACE TYPES: Type 1 = "low variability" water - all open water except Type 2, Type 2 = "high variability" water - water within 75 km of a coastline, water within 50 km of sea ice, or sea ice-covered water, Type 3 = "low variability" land - all open land including land within 50 km of a coastline or snow-covered land except Type 4, Type 4 = "high variability" land - high topography pixels (height > 1750 m), all pixels within 300 km regions that are rough topography (standard deviation of heights > 1000 m) or that are high topography (mean height > 2500 m), or permanently ice-covered locations (Iceland, Greenland and Anarctica). VIS SURFACE TYPES: The VIS types are basically divided into two groups. The first group consists of all open water including near-coast and sea ice-covered water. This group uses the threshold value 0.03. The second group consist of all land type include snow and ice covered land. This group uses the threshold value 0.06. In the fourth step the threshold test is repeated on the final clear sky radiance using the threshold values, for IR, VIS, NIR and TNIR (NIR brightness temperature) listed below. Final Cloud Detection Threshold Interval Values (Rossow et al., 1996) SURFACE TYPES WAVELENGTH 1 2 3 4 IR (K) 2.5 3.5 4.0 6.0 VIS Reflectance 0.030 0.030 0.060 0.090 VIS Radiance Limit 0.025 0.025 0.040 0.040 TNIR (K) 8.0 8.0 8.0 8.0 NIR Reflectance 0.045 0.045 0.055 0.055 Surface types for the IR test: Type 1 = open water, Type 2 = near-coastal water, sea ice margin and sea ice, Type 3 = open land, and Type 4 = near-coastal land, high topography, snow margin, and snow and ice-covered land. Surface types for the VIS & NIR test: The same four surface types are used for the VIS and NIR tests, except the sea ice margin and sea ice are changed to Type 3. In the radiation analysis component of the ISCCP cloud analysis, surface properties are retrieved from the final clear sky radiance, and used with the atmospheric data to do further analyses of individual pixel radiances. From this analysis surface properties and cloud properties are deduced for each individual pixel, based on whether the threshold tests indicate clear or cloudy conditions. Information on cloud types are derived based on ranges of values (see table below) from the Cloud Top Pressure (cldprs) and Cloud Optical Thickness (cldtau). Cloud Types (Rossow et al., 1996) NAME CLDPRS RANGE CLDTAU TYPE (mb) RANGE LOW Cumulus > 680 <= 3.55 liquid, ice Stratocumulus > 680 3.55 - liquid, ice 22.63 Stratus > 680 > 22.63 liquid, ice MIDDLE Altocumulus 440 - 680 <= 3.55 liquid, ice Altostratus 440 - 680 3.55 - liquid, ice 22.63 Nimbostratus 440 - 680 > 22.64 liquid, ice HIGH Cirrus <= 440 <= 3.55 ice Cirrostratus <= 440 3.55 - ice 22.63 Deep Convection <= 440 > 22.63 ice The ISCCP products include the infrared estimates for both day and night observations but the combined VIS/IR/NIR products, cloud optical thickness estimate and surface reflectance are available only during the day. The combined VIS/IR/NIR products are more accurate. Therefore a correction is made to the infrared only nighttime cloud products when the mean diurnal total cloud fraction is calculated. The correction is determined from a comparison of daytime VIS/IR/NIR and IR only cloud fractions. Processing Sequence and Algorithms The ISCCP project collects visible (~0.6 micrometers), near infrared (~3.7 micrometers) and thermal infrared (~11 micrometers) data from several geostationary weather satellites and from the National Oceanic and Atmospheric Administration (NOAA) operational meteorological satellites which are in Sun-synchronous near polar orbits. A subset of the monthly mean (D2) products was incorporated into the Interdiscipline Data Collection. A hierarchy of satellite data, which indicated a preference for data from one satellite over another, was used if data were available from more than one satellite for one location during a single time step. Geostationary satellite data were given higher preference over the NOAA polar orbiting data, for latitudes of 55 degrees and below. Data with the smallest satellite zenith angle are preferred in cases where geostationary data overlaps. NOAA polar orbiting data are used above 55 degrees latitude, due to the high satellite zenith angle of geostationary data above that latitude. The geostationary satellites involved are the GOES 5-9, METEOSAT 2-5 and the GMS 1-5, and INSAT-1. Due to numerous problems 3-hourly coverage from 55 N to 55 S is not always available in some regions. This is particularly true around India. The NOAA 7-14 satellites, which observe all regions on the Earth at least twice a day, were used to fill data gaps in these regions. Atmospheric effects on the satellite radiances were taken into account, in the ISCCP D series processing, by using atmospheric temperature and humidity profile data and ozone column abundance data in the radiative model. The TIROS Operational Vertical Sounder (TOVS) atmospheric datasets and the NOAA GFDL temperature/humidity and NIMBUS 4 BUV ozone climatology datasets were used for this purpose. In our interdisciplinary data collection, we have included four parameters of the TOVS datasets that are used in the ISCCP algorithm and are part of the ISCCP-D dataset. A merged ice/snow cover dataset was develop by ISCCP to help differentiate between clear and cloudy scenes in high latitude and higher elevation regions. The input datasets used in this merged ice/snow cover product are the U.S. Navy weekly sea ice analyses (from paper maps) through 1991, sea ice derived from daily analysis of the SSM/I microwave measurements after 1991, and NOAA's Synoptic Analysis Branch northern hemisphere weekly snow and ice cover charts. Three other datasets along with the ice/snow cover were used to specify different surface types as a function of latitude/longitude: 1. Masaki (1972) land/water/coast classification 2. U.S. Navy topographic height dataset from NCAR 3. Matthews (1983) land vegetation types The current version of the ISCCP C2-series was released 1991. Since then the C-series data has gone through an extensive review and a number of improvements have been recommended. The D-series data was developed as a result of this process. A synopses of the changes between the C-series and D-series datasets is listed below. Highlights of differences between the C-series and D-series cloud data (Rossow et al., 1996) Revised VIS and IR calibrations to eliminate spurious changes between different reference polar orbits. (Brest et al. 1996) Radiance Calibrations Revised normalizations of geostationary satellite calibrations to eliminate occasional short-term deviations. (Brest et al. 1996) Improved cirrus detection over land by lowering IR threshold from 6 K to 4 K Improved polar cloud detection over ice and snow surfaces by Cloud Detection lowering VIS threshold from 0.12 to 0.06 and by using threshold test on 3.7 micrometer radiances Improved detection of low clouds at high latitudes by changing to VIS reflectance threshold test Improved treatment of cold (top temperature < 260 K) clouds by using ice polycrystal scattering phase function to retrieve optical thickness and top temperature Improved retrieval of cloud optical thickness over ice and snow surfaces using 3.7 micrometer Radiation Model radiances Improved retrieval of cloud top temperatures by including effects of IR scattering Improved retrieval of surface and cloud top temperatures by adopting new treatment of water vapor continuum absorption in IR Better resolved variations of optically thicker clouds by adding 6th optical thickness category Added correct cloud water path parameter Reported actual average values of cloud top temperature, pressure, optical thickness and water path for each of nine cloud types defined by cloud top pressure and Gridded Product optical thickness in the 3-hourly Contents dataset Reported separate cloud properties for liquid and ice forms of low and middle-level clouds Provided conversion of cloud top pressures to cloud top heights above mean sea level based on atmospheric temperature profile added cloud amount frequency distribution to monthly dataset Archived pixel-level cloud Increase Resolution products with resolution of 30 km and 3 hr The ISCCP D2 data sets described in this readme have been reformatted for a subset of parameters, so that they are consistent with other CIDC data sets. Rergridding from an equal area world grid to 1 x 1 degree equal angle grid For consistency with the other data sets in the Goddard DAAC's Interdisciplinary Data Collection, the original data in HDF format was extracted from the long term data archive at Langley Research Center (LaRC) DAAC and converted from 8-bit quantities (scaled integer values) into 32-bit floating point quantities (unscaled values) and regridded to 1 x 1 degree equal angle grid from their original approximate 280 km x 280 km equal area grid maps. In the regridding process the original data at equal area grid with constant 2.5 degree latitudinal increments and variable longitudinal increments, ranging from 2.5 degree at the equator to 120 degree at the pole were replicated as many time as needed to produce a 1 by 1 degree latitude-longitude equal angle product. A weighted average was used in cases where two equal area grid cells overlapped a single one degree grid cell. This weighting was based on the percent area each original equal area grid cells covered in the 1 degree area. Changes in grid area due to changing latitude were taken into consideration in this procedure. This regridding method is different from the one used by ISCCP to convert their data from approximate 280km xx 280 km equal area to 2.5 by 2.5 degree equal angle. Their method did not use a weighted average in cases where grid cells overlapped, but instead chose one of the grid cell values over another. As a result the values from the statistical files in the original dataset can not be related to all of the grid values in this regridded dataset. Also, the south to north orientation was reversed, and for each latitude zone, data along the longitude was made to start from 180 west going towards east,again for conformity to the existing criteria, and gif images, created from the resultant files, were visually inspected to assure that the data was free of artifacts introduced by these procedures. Scientific Potential of Data The monthly mean summary of the data set given here can be used for many types of climate studies including: * Study of global, seasonal, and interannual cloud variability (Rossow et al., 1993) * Correlation with other climate parameters (Kyle et al., 1995) * Investigation of global energy transport (Sohn and Smith, 1992). Validation of Data The ISCCP D-series product was produced in part as a result of intensive research done on the C-series data, in which over 200 research articles have been written. Similar research is continuing with the D-series product and includes comparison of observations from an on-going series of field experiments. Rossow et al. (1996) discuss the differences between the ISCCP C series and D series algorithms, as well as on-going validation efforts being made on the D-series product. The ISCCP project has documented known and fixed data errors in their dataset. Contacts Points of Contact For information about or assistance in using any DAAC data, contact EOS Goddard Distributed Active Archive Center (DAAC) Code 902 NASA Goddard Space Flight Center Greenbelt, Maryland 20771 e-mail: daacuso@daac.gsfc.nasa.gov 301-614-5224 (voice) 301-614-5268 (fax) For questions about ISCCP science, contact Dr. William B. Rossow NASA Goddard Institute for Space Studies 2880 Broadway New York, NY 10025 USA e-mail: clwbr@giss.nasa.gov (212) 678-5567 The long term archives for the ISCCP data products are at: (Not including the Stage DX 30 km resolution data) ISCCP Central Archives National Climatic Data Center Federal Building 151 Patton Ave. Asheville, NC 28801-5001 email: satorder@ncdc.noaa.gov (704) 271-4800 (option #5) (voice) (704) 271-4876 (Including the Stage DX 30 km resolution data) Langley DAAC Mail Stop 157B NASA Langley Research Center Hampton, VA 23681-0001 e-mail: userserv@eosdis.larc.nasa.gov telnet eosdis.larc.nasa.gov (804) 864-8656 (voice) (804) 864-9807 (fax) References Brest, C.L., and W.B. Rossow, 1992. Radiometric calibration and monitoring of NOAA AVHRR data for ISCCP. Int. J. Remote Sens., 13:235-273. Brest, C.L., W.B. Rossow, and M.D. Roiter, 1996. Update on ISCCP calibration for visible and infrared radiances. J. Atmos. Ocean. Tech., (submitted). Kyle, H. L., M. Weiss, and P. Ardanuy, 1995. Cloud, surface temperature, and outgoing longwave radiation for the period from 1979 to 1990, J. Climate, 8:2644-2658. Masaki, G.T., 1972 (rev., 1976). The Wolf Plotting and Contouring Package. GSFC Computer Program Lib. #A00227, Computer Sciences Corporation, Goddard Space Flight Center, Greenbelt, MD, 187 pp. Matthews, E., 1983. Global vegetation and land use: New high-resolution data bases for climate studies. J. Clim. Appl. Meteor., 26:170-202. 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 detection, J. Climate, 6: 2370-2393. Rossow, W. B., and Y.-C Zhang, 1995. Calculation of surface and top of atmosphere radiative fluxes from physical quantities based on ISCCP data sets: 2. Validation and first results, J. Geophys. Res., 100:1167-1197. Rossow, W. B., E. Kinsella, A. Wolf, and L. Garder, 1987. International satellite Cloud Climatology Project (ISCCP) Description of Reduced Resolution Radiance Data. In, WMO/TD No. 58, (eds), World Meteorological Organization, Geneva, 143 pp. Rossow, W.B., L.C. Garder, and A.A. Lacis, 1989. Global seasonal cloud variations from satellite radiance measurements. Part I: Sensitivity of Analysis. J. Climate, 2:419-458. 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., A. W. Walker, D. E. Beuschel, and M. D. Roiter, 1996. International Satellite Cloud Climatology Project (ISCCP): documentation of new cloud datasets, 115 pages, available on internet at : http://isccp.giss.nasa.gov/documents.html Sohn, B. J., and E. A. Smith, 1992. Global energy transports and the influence of cloud on transport requirements: A satellite analyses, J. Climate, 5:717-734. ------------------------------------------------------------------------ [NASA] [GSFC] [Goddard DAAC] [cidc site] NASA Goddard GDAAC CIDC Last update:Mon Aug 18 17:10:29 EDT 1997 Page Author: Page Author: James McManus -- mcmanus@daac.gsfc.nasa.gov Web Curator: Daniel Ziskin -- ziskin@daac.gsfc.nasa.gov NASA official: Paul Chan, DAAC Manager -- chan@daac.gsfc.nasa.gov