OPeNDAP Dataset Query Form

OPeNDAP Dataset Access Form

Action:
Data URL:

Global Attributes:	Conventions: CF-1.6, ACDD-1.3 summary: The HGG product represents globally merged gridded data from all participating geostationary satellites and polar orbiters, reported on a 1. degree equal area grid every 3 hours. Data for each grid cell is selected from a hierarchy of satellite choices based on viewing angle. Empty grid cells are filled by diurnal interpolation within +/- 21 hours, daily interpolation within +/- 5 days, replication within 3 equal area grid cells poleward of 55 degrees, or weekly interpolation within +/- 2 weeks. Data reported include scene identification, cloud amounts, cloud type distribution, mean cloud properties, cloud type properties, surface properties, radiances and atmospheric profiles. keywords: EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC CHEMISTRY > OXYGEN COMPOUNDS > OZONE, EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC PRESSURE > SURFACE PRESSURE, EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC TEMPERATURE, EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC TEMPERATURE > SURFACE TEMPERATURE > AIR TEMPERATURE, EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC TEMPERATURE > SURFACE TEMPERATURE > SKIN TEMPERATURE, EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC TEMPERATURE > UPPER AIR TEMPERATURE > VERTICAL PROFILES, EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC WATER VAPOR, EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC WATER VAPOR > HUMIDITY, EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC WATER VAPOR > WATER VAPOR PROFILES, EARTH SCIENCE > ATMOSPHERE > CLOUDS, EARTH SCIENCE > ATMOSPHERE > CLOUDS > CLOUD MICROPHYSICS > CLOUD LIQUID WATER/ICE, EARTH SCIENCE > ATMOSPHERE > CLOUDS > CLOUD MICROPHYSICS > CLOUD OPTICAL DEPTH/THICKNESS, EARTH SCIENCE > ATMOSPHERE > CLOUDS > CLOUD PROPERTIES, EARTH SCIENCE > ATMOSPHERE > CLOUDS > CLOUD PROPERTIES > CLOUD FRACTION, EARTH SCIENCE > ATMOSPHERE > CLOUDS > CLOUD PROPERTIES > CLOUD TOP PRESSURE, EARTH SCIENCE > ATMOSPHERE > CLOUDS > CLOUD PROPERTIES > CLOUD TOP TEMPERATURE, EARTH SCIENCE > ATMOSPHERE > CLOUDS > CLOUD PROPERTIES > CLOUD VERTICAL DISTRIBUTION, EARTH SCIENCE > ATMOSPHERE > CLOUDS > CLOUD TYPES, EARTH SCIENCE > CRYOSPHERE > SNOW/ICE, EARTH SCIENCE > LAND SURFACE > SURFACE RADIATIVE PROPERTIES, EARTH SCIENCE > LAND SURFACE > SURFACE RADIATIVE PROPERTIES > REFLECTANCE, EARTH SCIENCE > LAND SURFACE > SURFACE THERMAL PROPERTIES, EARTH SCIENCE > LAND SURFACE > SURFACE THERMAL PROPERTIES > SKIN TEMPERATURE, EARTH SCIENCE > LAND SURFACE > TOPOGRAPHY > TERRAIN ELEVATION, EARTH SCIENCE > LAND SURFACE > TOPOGRAPHY > TERRAIN ELEVATION,EARTH SCIENCE > OCEANS > OCEAN TEMPERATURE > SEA SURFACE TEMPERATURE, EARTH SCIENCE > SPECTRAL/ENGINEERING > INFRARED WAVELENGTHS > BRIGHTNESS TEMPERATURE, EARTH SCIENCE > SPECTRAL/ENGINEERING > INFRARED WAVELENGTHS > INFRARED IMAGERY, EARTH SCIENCE > SPECTRAL/ENGINEERING > PLATFORM CHARACTERISTICS > VIEWING GEOMETRY, EARTH SCIENCE > SPECTRAL/ENGINEERING > SENSOR CHARACTERISTICS > VIEWING GEOMETRY, EARTH SCIENCE > SPECTRAL/ENGINEERING > VISIBLE WAVELENGTHS > VISIBLE IMAGERY, EARTH SCIENCE > SPECTRAL/ENGINEERING > VISIBLE WAVELENGTHS > VISIBLE RADIANCE keywords_vocabulary: NASA Global Change Master Directory (GCMD) Science Keyword Version 8.1 platform_vocabulary: NASA Global Change Master Directory (GCMD) Platforms Keyword Version 8.1 instrument_vocabulary: NASA Global Change Master Directory (GCMD) Instruments Keywords Version 8.1 processing_level: 3 cdm_data_type: Grid metadata_link: gov.noaa.ncdc.C00956 naming_authority: gov.noaa.ncdc institution: NOAA National Centers for Environmental Information (NCEI) project: International Satellite Cloud Climatology Project (ISCCP) program: NOAA Climate Data Record Program for satellites, FY 2016 acknowledgement: This project received funding support from NASA REASON PROGRAM, NASA MEASURES PROGRAM and NOAA CLIMATE DATA RECORD (CDR) PROGRAM license: No constraints on data access or use. contributor_name: William B. Rossow, Alison Walker, Violeta Golea, NOAA, EUMETSAT, ESA, JP/JMA, CHINA/CMA, BR/INPE, NASA contributor_role: principalInvestigator, processor, resourceProvider, resourceProvider, resourceProvider, resourceProvider, resourceProvider, resourceProvider, resourceProvider creator_name: NOAA National Centers for Environmental Information (NCEI); Ken Knapp, Bill Hankins, Alisa Young, Anand Inamdar creator_email: ncdc.isccp.team@noaa.gov creator_url: http://www.ncei.noaa.gov creator_type: institution creator_institution: NOAA National Centers for Environmental Information (NCEI) publisher_name: NOAA National Centers for Environmental Information (NCEI) publisher_email: ncdc.isccp.team@noaa.gov publisher_url: http://www.ncei.noaa.gov publisher_type: institution publisher_institution: NOAA National Centers for Environmental Information (NCEI) references: 'Please include a citation for this paper in addition to the dataset citation when using the dataset: Rossow, W.B. and R.A. Schiffer, 1999: Advances in understanding clouds from ISCCP. Bulletin of the American Meteorological Society, 80, 2261-2287. doi: http://dx.doi.org/10.1175/1520-0477(1999)080<2261:AIUCFI>2.0.CO;2','ISCCP CDR Climate Algorithm Theoretical Basis Document (C-ATBD)' comment: ---------- TO RE-MAP EQUAL-AREA MAP TO EQUAL-ANGLE (SQUARE LON,LAT) MAP ---------- For display purposes, the ISCCP equal-area map may be converted to an equal-angle map using replication. The variables 'eqlat_index', 'sqlon_beg' and 'sqlon_end'are provided for this purpose. Each equal-area cell is replicated into a specific range of longitude cells in the equal-angle map. For example, to remap an equal-area array eqvar[41252] to an equal-angle array sqmap[360,180], each eqvar[i] should be replicated into the range of cells indicated by sqlon_beg[i] and sqlon_end[i], and the lat index eqlat_index[i]. Using Fortran notation the assignment is: sqmap[sqlon_beg[i]:sqlon_end[i], eqlat_index[i]] = eqvar[i]. ---------- TO CONVERT COUNT UNITS TO PHYSICAL UNITS ---------- When attribute conversion_table is present for any variable, the reported values of count units may be converted to physical quantities by using the specified conversion table variable as a look-up table whose index is count value 0-255. For example, temperature = tmptab(count), temperature_variance = tmpvar(count), pressure = pretab(count), reflectance = rfltab(count), optical_depth = tautab(count), ozone = ozntab(count), humidity = humtab(count), water_path = wpatab(count). ---------- DEFINITION OF CLOUD TYPES ---------- VIS/IR cloud types are defined by a histogram of cloud top pressure and cloud optical depth, for both liquid and ice clouds. IR cloud types are defined by a histogram of cloud top pressure. Identification labels for the 18 VIS/IR cloud types and the 3 IR cloud types are given in the 'cloud_type_label' and 'cloud_irtype_label' variables, which correspond to the order of the cloud type variable arrays. ---------- TO COMPUTE CLOUD TOP HEIGHT ---------- Cloud top height in meters may be computed by applying lapse rate to the difference between cloud top temperature and surface temperature. Given rlapse 6.5, the formula is: height_meters = (ts - tc) / rlapse * 1000.0. ---------- TO COMPUTE TOTAL IR BRIGHTNESS TEMPERATURE ---------- Using IR cloud/clear categories: n_ir_clear = n_total - n_ir_cloudy, and then total_ir_bt = ( (n_ir_cloudy * ir_ircloudy) + (n_ir_clear * ir_irclear) ) / n_total, where ir_ircloudy and ir_irclear are values of count units. The resulting total_ir_bt can be converted from count units to physical units using the tmptab conversion table. Using VIS/IR cloud/clear categories: n_clear = n_total - n_cloudy, and then total_ir_bt = ( (n_cloudy * ir_visircloudy)+ (n_clear * ir_visirclear) / n_total, where ir_visircloudy and ir_visirclear are values of count units. The resulting total_ir_bt can be converted from count units to physical units using the tmptab conversion table. ---------- TO COMPUTE TOTAL VIS RADIANCE ---------- Using IR cloud/clear categories: n_ir_clear = n_total - n_ir_cloudy, and then total_vis_radiance = ( (n_ir_cloudy * vis_ircloudy) + (n_ir_clear * vis_irclear) ) / n_total. Using VIS/IR cloud/clear categories: n_clear = n_total - n_cloudy, and then total_vis_radiance = ( (n_cloudy * vis_visircloudy)+ (n_clear * vis_visirclear) / n_total. id: ISCCP.HGG.0.GLOBAL.1989.07.10.2100.GPC.10KM.CS00.EQ1.00.nc isccp_input_files: nom/ds/ISCCP.HGS.v01r00.NOAA.1989.07.10.2100.NOM.10KM.CS0219302223.EQ1.00.nc met/ds/ISCCP.HGS.0.MET4.1989.07.10.2100.ESA.10KM.CS0219302223.EQ1.00.nc gms/ds/ISCCP.HGS.0.GMS3.1989.07.10.2100.JMA.10KM.CS0219302223.EQ1.00.nc noa/ds/ISCCP.HGS.0.NOAB.1989.07.10.2100.NOA.10KM.CS0219302223.EQ1.00.nc goe/ds/ISCCP.HGS.0.GOE7.1989.07.10.2100.AES.10KM.CS0219302223.EQ1.00.nc time_coverage_start: 1989-07-10T19:30:00.000Z time_coverage_end: 1989-07-10T22:29:59.999Z time_coverage_duration: PT3H time_coverage_resolution: PT3H geospatial_bounds: POLYGON((-90.0 0.0, -90.0 360.0, 90.0 360.0, 90.0 0.0, -90.0 0.0)) geospatial_bounds_crs: EPSG:4326 geospatial_lat_units: degrees_north geospatial_lon_units: degrees_east geospatial_vertical_units: hPa geospatial_vertical_positive: down isccp_year: 1989 isccp_month: 7 isccp_day: 10 isccp_gmt: 21 isccp_number_of_satellites_contributing: 5 platform: GMS-3, METEOSAT-4,, GOES-7, instrument: VISSR-GMS, MVIRI,, VAS, isccp_percent_full_cells: 100 isccp_percent_empty_cells: 0 NCO: 4.4.4 title: International Satellite Cloud Climatology Project 3-hourly Gridded Global data -- ISCCP HGG Basic source: The source for the ISCCP Basic data files are the original ISCCP files. ISCCP Basic represents a subset of variables from ISCCP that have been remapped to equal-angle, do not use table to store data, etc. in order to make the files CF compliant date_issued: 2017-05-23T20:37:49Z product_version: v01r00 Basic date_created: 2017-05-23T20:37:49Z date_modified: 2017-05-23T20:37:49Z date_metadata_modified: 2017-05-23T20:37:49Z geospatial_lat_min: -90.0 geospatial_lat_max: 90.0 geospatial_lat_resolution: 1.0 geospatial_lon_min: 0.0 geospatial_lon_max: 360.0 geospatial_lon_resolution: 1.0 geospatial_vertical_min: 10.0 geospatial_vertical_max: 1025.0 history: Tue May 23 16:37:49 2017: ncatted -a units,lon_bounds,c,c,degrees_east -a comment,lon_bounds,c,c,longitude values at east and west bounds of the grid cell -a units,lat_bounds,c,c,degrees_north -a comment,lat_bounds,c,c,latitude values at north and south bounds of the gridcell -a units,pc_bounds,c,c,hPa -a comment,pc_bounds,c,c,Pressure values at bounds of the pressure bins -a units,tau_bounds,c,c,1 -a comment,tau_bounds,c,c,Optical depth values at bounds of the depth bins -a axis,lat,c,c,Y -a axis,lon,c,c,X -a geospatial_lat_min,global,m,f,-90 -a geospatial_lat_max,global,m,f,90 -a geospatial_lat_resolution,global,m,f,1 -a geospatial_lon_min,global,m,f,0 -a geospatial_lon_max,global,m,f,360 -a geospatial_lon_resolution,global,m,f,1 -a geospatial_vertical_min,global,m,f,10 -a geospatial_vertical_max,global,m,f,1025 -a units,satcodes,d,, -a units,satids,d,, -a units,satnames,d,, -a units,cloud_irtype_label,d,, -a units,cloud_type_label,d,, /snfs2/isccp-p/basic/intermediate//temp_file3.nc -O /snfs2/isccp-p/prd/basic/hgg/1989/ISCCP-Basic.HGG.0.GLOBAL.1989.07.10.2100.GPC.10KM.CS00.EA1.00.nc Tue May 23 16:37:49 2017: ncatted -a conversion_table,,d,, -a title,global,a,c, Basic -a description,snoice,m,c,Mean snow/ice cover for the cell -a source,global,o,c,The source for the ISCCP Basic data files are the original ISCCP files. ISCCP Basic represents a subset of variables from ISCCP that have been remapped to equal-angle, do not use table to store data, etc. in order to make the files CF compliant -a product_version,global,m,c,v01r00 Basic -a date_issued,global,m,c,2017-05-23T20:37:49Z -a date_created,global,m,c,2017-05-23T20:37:49Z -a date_modified,global,m,c,2017-05-23T20:37:49Z -a date_metadata_modified,global,m,c,2017-05-23T20:37:49Z -a description,levpc,c,c,Coordinate variable for cloud frequency histograms -a description,levtau,c,c,Coordinate variable for cloud frequency histograms -a units,^cldamt,m,c,percent -a bounds,time,c,c,time_bounds -a valid_min,n_total,m,s,0 -a valid_max,n_total,m,s,32766 -a valid_min,snoice,m,b,0 -a valid_max,snoice,m,b,100 -a long_name,cldamt,m,c,Cloud amount -a long_name,cldamt_ir,m,c,Cloud amount (using IR data) -a long_name,cldamt_irmarg,m,c,Cloud amount uncertainty (using IR data) -a note,cldamt_irmarg,c,c,This is the ISCCP variable: n_irmarg_cloudy represented as a fraction. It represents the fraction of pixels that are colder than clear sky by a smaller amount than what is flagged in cldamt_ir and represents cloud amount uncertainty. -a long_name,cldamt_types,m,c,Cloud amount by cloud type -a long_name,cldamt_irtypes,m,c,Cloud amount by IR cloud type -a calendar,time,c,c,gregorian -a cell_methods,eqheight,c,c,area: mean -a cell_methods,pc,c,c,area: mean -a cell_methods,pc_ir,c,c,area: mean -a cell_methods,pc_pcdist,c,c,area: mean -a cell_methods,pc_type,c,c,area: mean -a cell_methods,^sigma,c,c,area: standard_deviation -a cell_methods,^tc,c,c,area: mean -a cell_methods,tau,c,c,area: mean -a cell_methods,tau_ir,c,c,area: mean -a cell_methods,tau_type,c,c,area: mean -a cell_methods,^wp,c,c,area: mean /snfs2/isccp-p/basic/intermediate//temp_file2.nc -O /snfs2/isccp-p/basic/intermediate//temp_file3.nc Tue May 23 16:37:48 2017: ncks -a -4 -L 5 /snfs2/isccp-p/basic/intermediate//temp_file.nc -O /snfs2/isccp-p/basic/intermediate//temp_file2.nc 2017-05-10T14:53:12.000Z bhankins d1fill_weekly /snfs2/isccp-p/prd/wrkdirs/1989_07 1989 07 01 1989 07 31 2017-05-10T14:34:18.000Z bhankins d1fill_daily /snfs2/isccp-p/prd/wrkdirs/1989_07 1989 07 01 1989 07 31 2017-05-10T14:14:00.000Z bhankins d1fill_diurnal /snfs2/isccp-p/prd/wrkdirs/1989_07 1989 07 01 1989 07 31 2017-04-17T01:12:53.000Z bhankins d1fill_weekly /snfs2/isccp-p/prd/wrkdirs/1989_07 1989 07 01 1989 07 31 2017-04-17T01:00:04.000Z bhankins d1fill_daily /snfs2/isccp-p/prd/wrkdirs/1989_07 1989 07 01 1989 07 31 2017-04-17T00:19:04.000Z bhankins d1fill_diurnal /snfs2/isccp-p/prd/wrkdirs/1989_07 1989 07 01 1989 07 31 2017-04-17T00:13:32.000Z bhankins d1prod /snfs2/isccp-p/prd/wrkdirs/1989_07 1989 07 01 1989 07 31 Unlimited_Dimension: time

Variables:	satcodes: Array of 16 bit Integers [satpos = 0..11] satpos: long_name: Satellite code number _ChunkSizes: 12
	satids: Array of Strings [satpos = 0..11] satpos: long_name: Satellite short ID _ChunkSizes: 12, 4 DODS: strlen: 4 dimName: satid_len
	satnames: Array of Strings [satpos = 0..11] satpos: long_name: Satellite full name _ChunkSizes: 12, 20 DODS: strlen: 20 dimName: satname_len
	eqheight: Grid time: lat: lon: cell_methods: area: mean long_name: Equal-area cell mean topographic height units: m _ChunkSizes: 1, 180, 360
	lon: Array of 32 bit Reals [lon = 0..359] lon: long_name: Center longitude of square grid cell units: degrees_east valid_min: 0.0 valid_max: 360.0 bounds: lon_bounds standard_name: longitude axis: X _ChunkSizes: 360
	lon_bounds: Array of 32 bit Reals [lon = 0..359][edge = 0..1] lon: edge: units: degrees_east comment: longitude values at east and west bounds of the grid cell _ChunkSizes: 360, 2
	lat: Array of 32 bit Reals [lat = 0..179] lat: long_name: Center latitude of square grid cell units: degrees_north valid_min: -90.0 valid_max: 90.0 bounds: lat_bounds standard_name: latitude axis: Y _ChunkSizes: 180
	lat_bounds: Array of 32 bit Reals [lat = 0..179][edge = 0..1] lat: edge: units: degrees_north comment: latitude values at north and south bounds of the gridcell _ChunkSizes: 180, 2
	levpc: Array of 32 bit Reals [levpc = 0..6] levpc: description: Coordinate variable for cloud frequency histograms long_name: Pressure levels units: hPa bounds: pc_bounds _ChunkSizes: 7
	pc_bounds: Array of 32 bit Reals [levpc = 0..6][edge = 0..1] levpc: edge: units: hPa comment: Pressure values at bounds of the pressure bins _ChunkSizes: 7, 2
	levtau: Array of 32 bit Reals [levtau = 0..5] levtau: description: Coordinate variable for cloud frequency histograms long_name: Optical thickness levels units: 1 bounds: tau_bounds _ChunkSizes: 6
	tau_bounds: Array of 32 bit Reals [levtau = 0..5][edge = 0..1] levtau: edge: units: 1 comment: Optical depth values at bounds of the depth bins _ChunkSizes: 6, 2
	cloud_irtype_label: Array of Strings [cloud_irtype = 0..2] cloud_irtype: long_name: IR cloud type labels description: IR cloud types determined by cloud top pressure for blackbody clouds _ChunkSizes: 3, 80 DODS: strlen: 80 dimName: label_len
	cloud_type_label: Array of Strings [cloud_type = 0..17] cloud_type: long_name: Cloud type labels description: Cloud types determined by cloud top pressure adjusted for optically thinner clouds and optical thickness for liquid and ice clouds determined by cloud top temperature _ChunkSizes: 18, 80 DODS: strlen: 80 dimName: label_len
	time: Array of 32 bit Integers [time = 0..0] time: bounds: time_bounds calendar: gregorian long_name: Time units: hours since 1970-01-01 00:00:00 _ChunkSizes: 1048576
	satcode: Grid time: lat: lon: _Unsigned: false long_name: Satellite code number units: 1 valid_min: 0 valid_max: 99 _FillValue: -1 _ChunkSizes: 1, 180, 360
	cell_origin: Grid time: lat: lon: _Unsigned: false long_name: Cell origin code units: 1 _FillValue: -1 flag_values: 0, 1, 2 flag_meanings: original single-satellite-fill multi-satellite-fill _ChunkSizes: 1, 180, 360
	fill_gmts: Grid time: lat: lon: _Unsigned: false long_name: Number of missing GMTs in gap units: 1 _FillValue: -1 _ChunkSizes: 1, 180, 360
	fill_days: Grid time: lat: lon: _Unsigned: false long_name: Number of missing days in gap units: 1 _FillValue: -1 _ChunkSizes: 1, 180, 360
	scene: Grid time: lat: lon: _Unsigned: false long_name: Scene identification flag_values: 1, 2, 3, 101, 102, 103, -1 flag_meanings: day-water day-land day-coast night-water night-land night-coast no-data _ChunkSizes: 1, 180, 360
	snoice: Grid time: lat: lon: _Unsigned: false long_name: Snow/ice cover units: percent _FillValue: -1 valid_max: 100 description: Mean snow/ice cover for the cell valid_min: 0 _ChunkSizes: 1, 180, 360
	n_total: Grid time: lat: lon: long_name: Total number of pixels units: 1 _FillValue: 32767 standard_name: number_of_observations valid_min: 0 valid_max: 32766 _ChunkSizes: 1, 180, 360
	cldamt: Grid time: lat: lon: valid_min: -500 valid_max: 500 description: Cloud detected by either IR or VIS thresholds (IR at night but diurnally corrected), amount determined by ratio with total number of pixels standard_name: isccp_cloud_area_fraction add_offset: 50.0 scale_factor: 0.1 long_name: Cloud amount units: percent _ChunkSizes: 1, 180, 360
	cldamt_ir: Grid time: lat: lon: valid_min: -500 valid_max: 500 description: Cloud detected by IR threshold regardless of VIS threshold standard_name: isccp_cloud_area_fraction add_offset: 50.0 scale_factor: 0.1 long_name: Cloud amount (using IR data) units: percent _ChunkSizes: 1, 180, 360
	cldamt_irmarg: Grid time: lat: lon: valid_min: -500 valid_max: 500 description: Marginal cloud detection by IR threshold regardless of VIS threshold add_offset: 50.0 scale_factor: 0.1 long_name: Cloud amount uncertainty (using IR data) units: percent note: This is the ISCCP variable: n_irmarg_cloudy represented as a fraction. It represents the fraction of pixels that are colder than clear sky by a smaller amount than what is flagged in cldamt_ir and represents cloud amount uncertainty. _ChunkSizes: 1, 180, 360
	n_pcdist: Grid time: levpc: lat: lon: long_name: IR cloudy pixel fraction in each cloud-top pressure (PC) level units: 1 valid_min: -500 valid_max: 500 description: Cloud detected by IR threshold regardless of VIS threshold, cloud top located assuming blackbody standard_name: isccp_cloud_area_fraction add_offset: 50.0 scale_factor: 0.1 _ChunkSizes: 1, 7, 180, 360
	cldamt_irtypes: Array of 16 bit Integers [time = 0..0][cloud_irtype = 0..2][lat = 0..179][lon = 0..359] time: cloud_irtype: lat: lon: valid_min: -500 valid_max: 500 description: Cloud detected by IR threshold regardless of VIS threshold, IR type determined by cloud top pressure for blackbody standard_name: isccp_cloud_area_fraction add_offset: 50.0 scale_factor: 0.1 long_name: Cloud amount by IR cloud type units: percent _ChunkSizes: 1, 3, 180, 360
	n_pctaudist: Grid time: levtau: levpc: lat: lon: long_name: Cloudy pixel fraction in each cloud-top pressure (PC)/cloud optical depth (TAU) level units: 1 valid_min: -500 valid_max: 500 description: Cloud detected by either IR or VIS threshold, cloud top location adjusted for optically thinner clouds standard_name: isccp_cloud_area_fraction add_offset: 50.0 scale_factor: 0.1 _ChunkSizes: 1, 3, 4, 90, 180
	cldamt_types: Array of 16 bit Integers [time = 0..0][cloud_type = 0..17][lat = 0..179][lon = 0..359] time: cloud_type: lat: lon: valid_min: -500 valid_max: 500 description: Cloud detected by either IR or VIS threshold, type determined by cloud top location adjusted for optically thinner clouds and optical thickness for liquid or ice as determined by cloud top temperature standard_name: isccp_cloud_area_fraction add_offset: 50.0 scale_factor: 0.1 long_name: Cloud amount by cloud type units: percent _ChunkSizes: 1, 18, 180, 360
	pc: Grid time: lat: lon: long_name: Mean cloud-top pressure (PC) for cloudy pixels units: hPa valid_min: -495 valid_max: 525 description: Grid cell average of cloud top pressure with VIS-adjusted location during daytime and nighttime location diurnally corrected standard_name: air_pressure_at_cloud_top add_offset: 500.0 scale_factor: 1.0 cell_methods: area: mean _ChunkSizes: 1, 180, 360
	pc_ir: Grid time: lat: lon: long_name: Mean cloud-top pressure (PC) for IR-cloudy pixels units: hPa valid_min: -495 valid_max: 525 description: Grid cell average of cloud top pressures for clouds detected by IR threshold regardless of VIS threshold, no VIS-adjustment of location standard_name: air_pressure_at_cloud_top add_offset: 500.0 scale_factor: 1.0 cell_methods: area: mean _ChunkSizes: 1, 180, 360
	sigma_pc_ir: Grid time: lat: lon: long_name: Standard deviation of cloud-top pressure (PC) for IR-cloudy pixels units: hPa valid_min: -495 valid_max: 525 description: Grid cell spatial standard deviation of cloud top pressure for clouds detected by IR threshold regardless of VIS threshold, no VIS-adjustment of location add_offset: 500.0 scale_factor: 1.0 cell_methods: area: standard_deviation _ChunkSizes: 1, 180, 360
	tc: Grid time: lat: lon: long_name: Mean cloud-top temperature (TC) for cloudy pixels units: K valid_min: -900 valid_max: 1000 description: Grid cell average of cloud top temperature with VIS-adjusted location during daytime and nighttime location diurnally corrected standard_name: air_temperature_at_cloud_top add_offset: 250.0 scale_factor: 0.1 cell_methods: area: mean _ChunkSizes: 1, 180, 360
	tc_ir: Grid time: lat: lon: long_name: Mean cloud-top temperature (TC) for IR-cloudy pixels units: K valid_min: -900 valid_max: 1000 description: Grid cell average of cloud top temperatures for clouds detected by IR threshold regardless of VIS threshold, no VIS-adjustment of location standard_name: air_temperature_at_cloud_top add_offset: 250.0 scale_factor: 0.1 cell_methods: area: mean _ChunkSizes: 1, 180, 360
	sigma_tc_ir: Grid time: lat: lon: long_name: Standard deviation of cloud-top temperature (TC) for IR-cloudy pixels units: K valid_min: -500 valid_max: 400 description: Grid cell spatial standard deviation of cloud top temperature for clouds detected by IR threshold regardless of VIS threshold, no VIS-adjustment of location add_offset: 50.0 scale_factor: 0.1 cell_methods: area: standard_deviation _ChunkSizes: 1, 180, 360
	tau: Grid time: lat: lon: long_name: Mean cloud optical depth (TAU) for cloudy pixels units: 1 valid_min: -22500 valid_max: 22500 description: Grid cell (radiatively-weighted) average of cloud visible optical thickness during daytime and diurnally interpolated values during nighttime, liquid and ice clouds combined standard_name: atmosphere_optical_thickness_due_to_cloud add_offset: 225.0 scale_factor: 0.01 cell_methods: area: mean _ChunkSizes: 1, 180, 360
	tau_ir: Grid time: lat: lon: long_name: Mean cloud optical depth (TAU) for IR-cloudy pixels units: 1 valid_min: -22500 valid_max: 22500 description: Grid cell (radiatively-weighted) average of visible optical thickness for clouds detected by IR threshold regardless of VIS threshold, liquid and ice clouds combined standard_name: atmosphere_optical_thickness_due_to_cloud add_offset: 225.0 scale_factor: 0.01 cell_methods: area: mean _ChunkSizes: 1, 180, 360
	sigma_tau_ir: Grid time: lat: lon: long_name: Standard deviation of cloud optical depth (TAU) for IR-cloudy pixels units: 1 valid_min: -22500 valid_max: 22500 description: Grid cell spatial standard deviation of visible optical thickness for clouds detected by IR threshold regardless of VIS threshold, liquid and ice clouds combined add_offset: 225.0 scale_factor: 0.01 cell_methods: area: standard_deviation _ChunkSizes: 1, 180, 360
	wp: Grid time: lat: lon: long_name: Mean cloud water path (WP) for cloudy pixels units: cm valid_min: -25000 valid_max: 28550 description: Grid cell average of cloud water path (linear average of optical thickness times particle radius) during daytime and diurnally interpolated values during nighttime, liquid and ice clouds combined add_offset: 2500.0 scale_factor: 0.1 cell_methods: area: mean _ChunkSizes: 1, 180, 360
	wp_ir: Grid time: lat: lon: long_name: Mean cloud water path (WP) for IR-cloudy pixels units: cm valid_min: -25000 valid_max: 28550 description: Grid cell average of cloud water path (linear average of optical thickness times particle radius) for clouds detected by IR threshold regardless of VIS threshold, liquid and ice clouds combined add_offset: 2500.0 scale_factor: 0.1 cell_methods: area: mean _ChunkSizes: 1, 180, 360
	sigma_wp_ir: Grid time: lat: lon: long_name: Standard deviation of cloud water path (WP) for IR-cloudy pixels units: cm valid_min: -25000 valid_max: 28550 description: Grid cell spatial standard deviation of cloud water path for clouds detected by IR threshold regardless of VIS threshold, liquid and ice clouds combined add_offset: 2500.0 scale_factor: 0.1 cell_methods: area: standard_deviation _ChunkSizes: 1, 180, 360
	pc_pcdist: Grid time: levpc: lat: lon: long_name: cloud-top pressure (PC) means for IR PC distribution levels units: hPa valid_min: -495 valid_max: 525 description: Grid cell average cloud top pressures in seven pressure intervals for clouds detected by IR threshold regardless of VIS threshold, no VIS-adjustment of location standard_name: air_pressure_at_cloud_top add_offset: 500.0 scale_factor: 1.0 cell_methods: area: mean _ChunkSizes: 1, 7, 180, 360
	tc_pcdist: Grid time: levpc: lat: lon: long_name: cloud-top temperature (TC) means for IR cloud-top pressure (PC) distribution levels units: K valid_min: -900 valid_max: 1000 description: Grid cell average cloud top temperatures in seven pressure intervals for cloud detected by IR threshold regardless of VIS threshold, no VIS-adjustment of location standard_name: air_temperature_at_cloud_top add_offset: 250.0 scale_factor: 0.1 cell_methods: area: mean _ChunkSizes: 1, 7, 180, 360
	pc_type: Array of 16 bit Integers [time = 0..0][cloud_type = 0..17][lat = 0..179][lon = 0..359] time: cloud_type: lat: lon: long_name: cloud-top pressure (PC) means for cloud types units: hPa valid_min: -495 valid_max: 525 description: Grid cell average of liquid or ice cloud top pressures in three pressure intervals and three optical thickness intervals for clouds detected by either IR or VIS thresholds with location adjusted for optically thinner clouds standard_name: air_pressure_at_cloud_top add_offset: 500.0 scale_factor: 1.0 cell_methods: area: mean _ChunkSizes: 1, 18, 180, 360
	tc_type: Array of 16 bit Integers [time = 0..0][cloud_type = 0..17][lat = 0..179][lon = 0..359] time: cloud_type: lat: lon: long_name: cloud-top temperature (TC) means for cloud types units: K valid_min: -900 valid_max: 1000 description: Grid cell average of liquid or ice cloud top temperatures in three pressure intervals and three optical thickness intervals for clouds detected by either IR or VIS thresholds with location adjusted for optically thinner clouds standard_name: air_temperature_at_cloud_top add_offset: 250.0 scale_factor: 0.1 cell_methods: area: mean _ChunkSizes: 1, 18, 180, 360
	tau_type: Array of 16 bit Integers [time = 0..0][cloud_type = 0..17][lat = 0..179][lon = 0..359] time: cloud_type: lat: lon: long_name: cloud optical depth (TAU) means for cloud types units: 1 valid_min: -22500 valid_max: 22500 description: Grid cell average of liquid or ice cloud visible optical thicknesses in three pressure intervals and three optical thickness intervals for clouds detected by either IR or VIS thresholds with location adjusted for optically thinner clouds standard_name: atmosphere_optical_thickness_due_to_cloud add_offset: 225.0 scale_factor: 0.01 cell_methods: area: mean _ChunkSizes: 1, 18, 180, 360
	wp_type: Array of 16 bit Integers [time = 0..0][cloud_type = 0..17][lat = 0..179][lon = 0..359] time: cloud_type: lat: lon: long_name: cloud water path (WP) means for cloud types units: cm valid_min: -25000 valid_max: 28550 description: Grid cell average of liquid or ice cloud water path (linear average of optical thickness times particle radius) in three pressure intervals and three optical thickness intervals for clouds detected by either IR or VIS thresholds with location adjusted for optically thinner clouds add_offset: 2500.0 scale_factor: 0.1 cell_methods: area: mean _ChunkSizes: 1, 18, 180, 360
	time_bounds: Array of 32 bit Integers [time = 0..0][edge = 0..1] time: edge: long_name: Time bounds units: hours since 1970-01-01 00:00:00 comment: All satellite data are observations within these time bounds. Observations are point measures (i.e., instantaneous values, not averages in time) note: Current units do not allow the bounds to be +/- 1.5 hours. So they are left in integer values +/- 1 which means 1.5 hours calendar: gregorian _ChunkSizes: 1, 2

For questions or comments about this dataset, contact the administrator of this server [Support] at: climserv@ipsl.polytechnique.fr

For questions or comments about the OPeNDAP service bundled with the TDS, email THREDDS support at: support-thredds@unidata.ucar.edu

DDS:

Dataset {
    Int16 satcodes[satpos = 12];
    String satids[satpos = 12];
    String satnames[satpos = 12];
    Grid {
     ARRAY:
        Int16 eqheight[time = 1][lat = 180][lon = 360];
     MAPS:
        Int32 time[time = 1];
        Float32 lat[lat = 180];
        Float32 lon[lon = 360];
    } eqheight;
    Float32 lon[lon = 360];
    Float32 lon_bounds[lon = 360][edge = 2];
    Float32 lat[lat = 180];
    Float32 lat_bounds[lat = 180][edge = 2];
    Float32 levpc[levpc = 7];
    Float32 pc_bounds[levpc = 7][edge = 2];
    Float32 levtau[levtau = 6];
    Float32 tau_bounds[levtau = 6][edge = 2];
    String cloud_irtype_label[cloud_irtype = 3];
    String cloud_type_label[cloud_type = 18];
    Int32 time[time = 1];
    Grid {
     ARRAY:
        Byte satcode[time = 1][lat = 180][lon = 360];
     MAPS:
        Int32 time[time = 1];
        Float32 lat[lat = 180];
        Float32 lon[lon = 360];
    } satcode;
    Grid {
     ARRAY:
        Byte cell_origin[time = 1][lat = 180][lon = 360];
     MAPS:
        Int32 time[time = 1];
        Float32 lat[lat = 180];
        Float32 lon[lon = 360];
    } cell_origin;
    Grid {
     ARRAY:
        Byte fill_gmts[time = 1][lat = 180][lon = 360];
     MAPS:
        Int32 time[time = 1];
        Float32 lat[lat = 180];
        Float32 lon[lon = 360];
    } fill_gmts;
    Grid {
     ARRAY:
        Byte fill_days[time = 1][lat = 180][lon = 360];
     MAPS:
        Int32 time[time = 1];
        Float32 lat[lat = 180];
        Float32 lon[lon = 360];
    } fill_days;
    Grid {
     ARRAY:
        Byte scene[time = 1][lat = 180][lon = 360];
     MAPS:
        Int32 time[time = 1];
        Float32 lat[lat = 180];
        Float32 lon[lon = 360];
    } scene;
    Grid {
     ARRAY:
        Byte snoice[time = 1][lat = 180][lon = 360];
     MAPS:
        Int32 time[time = 1];
        Float32 lat[lat = 180];
        Float32 lon[lon = 360];
    } snoice;
    Grid {
     ARRAY:
        Int16 n_total[time = 1][lat = 180][lon = 360];
     MAPS:
        Int32 time[time = 1];
        Float32 lat[lat = 180];
        Float32 lon[lon = 360];
    } n_total;
    Grid {
     ARRAY:
        Int16 cldamt[time = 1][lat = 180][lon = 360];
     MAPS:
        Int32 time[time = 1];
        Float32 lat[lat = 180];
        Float32 lon[lon = 360];
    } cldamt;
    Grid {
     ARRAY:
        Int16 cldamt_ir[time = 1][lat = 180][lon = 360];
     MAPS:
        Int32 time[time = 1];
        Float32 lat[lat = 180];
        Float32 lon[lon = 360];
    } cldamt_ir;
    Grid {
     ARRAY:
        Int16 cldamt_irmarg[time = 1][lat = 180][lon = 360];
     MAPS:
        Int32 time[time = 1];
        Float32 lat[lat = 180];
        Float32 lon[lon = 360];
    } cldamt_irmarg;
    Grid {
     ARRAY:
        Int16 n_pcdist[time = 1][levpc = 7][lat = 180][lon = 360];
     MAPS:
        Int32 time[time = 1];
        Float32 levpc[levpc = 7];
        Float32 lat[lat = 180];
        Float32 lon[lon = 360];
    } n_pcdist;
    Int16 cldamt_irtypes[time = 1][cloud_irtype = 3][lat = 180][lon = 360];
    Grid {
     ARRAY:
        Int16 n_pctaudist[time = 1][levtau = 6][levpc = 7][lat = 180][lon = 360];
     MAPS:
        Int32 time[time = 1];
        Float32 levtau[levtau = 6];
        Float32 levpc[levpc = 7];
        Float32 lat[lat = 180];
        Float32 lon[lon = 360];
    } n_pctaudist;
    Int16 cldamt_types[time = 1][cloud_type = 18][lat = 180][lon = 360];
    Grid {
     ARRAY:
        Int16 pc[time = 1][lat = 180][lon = 360];
     MAPS:
        Int32 time[time = 1];
        Float32 lat[lat = 180];
        Float32 lon[lon = 360];
    } pc;
    Grid {
     ARRAY:
        Int16 pc_ir[time = 1][lat = 180][lon = 360];
     MAPS:
        Int32 time[time = 1];
        Float32 lat[lat = 180];
        Float32 lon[lon = 360];
    } pc_ir;
    Grid {
     ARRAY:
        Int16 sigma_pc_ir[time = 1][lat = 180][lon = 360];
     MAPS:
        Int32 time[time = 1];
        Float32 lat[lat = 180];
        Float32 lon[lon = 360];
    } sigma_pc_ir;
    Grid {
     ARRAY:
        Int16 tc[time = 1][lat = 180][lon = 360];
     MAPS:
        Int32 time[time = 1];
        Float32 lat[lat = 180];
        Float32 lon[lon = 360];
    } tc;
    Grid {
     ARRAY:
        Int16 tc_ir[time = 1][lat = 180][lon = 360];
     MAPS:
        Int32 time[time = 1];
        Float32 lat[lat = 180];
        Float32 lon[lon = 360];
    } tc_ir;
    Grid {
     ARRAY:
        Int16 sigma_tc_ir[time = 1][lat = 180][lon = 360];
     MAPS:
        Int32 time[time = 1];
        Float32 lat[lat = 180];
        Float32 lon[lon = 360];
    } sigma_tc_ir;
    Grid {
     ARRAY:
        Int16 tau[time = 1][lat = 180][lon = 360];
     MAPS:
        Int32 time[time = 1];
        Float32 lat[lat = 180];
        Float32 lon[lon = 360];
    } tau;
    Grid {
     ARRAY:
        Int16 tau_ir[time = 1][lat = 180][lon = 360];
     MAPS:
        Int32 time[time = 1];
        Float32 lat[lat = 180];
        Float32 lon[lon = 360];
    } tau_ir;
    Grid {
     ARRAY:
        Int16 sigma_tau_ir[time = 1][lat = 180][lon = 360];
     MAPS:
        Int32 time[time = 1];
        Float32 lat[lat = 180];
        Float32 lon[lon = 360];
    } sigma_tau_ir;
    Grid {
     ARRAY:
        Int16 wp[time = 1][lat = 180][lon = 360];
     MAPS:
        Int32 time[time = 1];
        Float32 lat[lat = 180];
        Float32 lon[lon = 360];
    } wp;
    Grid {
     ARRAY:
        Int16 wp_ir[time = 1][lat = 180][lon = 360];
     MAPS:
        Int32 time[time = 1];
        Float32 lat[lat = 180];
        Float32 lon[lon = 360];
    } wp_ir;
    Grid {
     ARRAY:
        Int16 sigma_wp_ir[time = 1][lat = 180][lon = 360];
     MAPS:
        Int32 time[time = 1];
        Float32 lat[lat = 180];
        Float32 lon[lon = 360];
    } sigma_wp_ir;
    Grid {
     ARRAY:
        Int16 pc_pcdist[time = 1][levpc = 7][lat = 180][lon = 360];
     MAPS:
        Int32 time[time = 1];
        Float32 levpc[levpc = 7];
        Float32 lat[lat = 180];
        Float32 lon[lon = 360];
    } pc_pcdist;
    Grid {
     ARRAY:
        Int16 tc_pcdist[time = 1][levpc = 7][lat = 180][lon = 360];
     MAPS:
        Int32 time[time = 1];
        Float32 levpc[levpc = 7];
        Float32 lat[lat = 180];
        Float32 lon[lon = 360];
    } tc_pcdist;
    Int16 pc_type[time = 1][cloud_type = 18][lat = 180][lon = 360];
    Int16 tc_type[time = 1][cloud_type = 18][lat = 180][lon = 360];
    Int16 tau_type[time = 1][cloud_type = 18][lat = 180][lon = 360];
    Int16 wp_type[time = 1][cloud_type = 18][lat = 180][lon = 360];
    Int32 time_bounds[time = 1][edge = 2];
} GEWEX_CA/ISCCP/1989/ISCCP-Basic.HGG.0.GLOBAL.1989.07.10.2100.GPC.10KM.CS00.EA1.00.nc;

OPeNDAP Dataset Access Form

Action:

Data URL:

Global Attributes:

Variables:

DDS: