[Image] AVHRR Weekly Global Gridded MCSST Summary: The AVHRR MCSST data set contains weekly averaged Multi-Channel Sea-Surface Temperature (MCSST) data derived from the NOAA Advanced Very High Resolution Radiometer (AVHRR). Data for both the ascending pass (daytime) and descending pass (nighttime) are available globally in Hierarchical Data Format (HDF) or in Raw Binary Format. Data are given on an equal-angle grid of 2048 pixels longitude by 1024 pixels latitude; therefore, the spatial resolution in pixels per degree of longitude and latitude is 2048/360 or approximately 5.689. Data currently exist for the period between 11 November 1981 and 6 December 2000. More recent data will be provided as available. This product is also referred to as JPL PO.DAAC product 016. Table of Contents: * 1 Data Set Overview * 2 Investigator(s) * 3 Theory of Measurements * 4 Equipment * 5 Data Acquisition Methods * 6 Observations * 7 Data Description * 8 Data Organization * 9 Data Manipulations * 10 Errors * 11 Notes * 12 Application of the Data Set * 13 Future Modifications and Plans * 14 Software * 15 Data Access * 16 Output Products and Availability * 17 References * 18 Glossary of Terms * 19 List of Acronyms * 20 Document Information 1. Data Set Overview: Data Set Identification: AVHRR weekly global gridded MCSST Data Set Data Set Introduction: This product consists of weekly averages of global Multi-Channel Sea Surface Temperature (MCSST) for the period between 11 November 1981 and 6 December 2000. Data were derived from measurements of emitted and reflected radiance by the 5-channel AVHRR instruments aboard the NOAA-7, -9, -11 and -14 satellites. Data from both the ascending pass (daytime) and descending pass (nighttime) are available with a spatial resolution of 2048/360 pixels per degree of longitude and latitude. Objective/Purpose: To produce satellite-derived sea surface temperature (SST) data with measurement accuracies, temporal resolutions and spatial resolutions sufficient for climate studies, mesoscale oceanography, and large-scale processes. Summary of Parameters: Sea Surface Temperatures (in degrees Celsius) can be derived from Digital Number (DN) values. Discussion: In each data file, there are three data sets: valid, interpolated and flag. Valid Data Daytime and nighttime sea surface temperature values from the NOAA/NESDIS Global Retrieval Tapes were binned and averaged into eight-day measurements by the University of Miami, Rosenstiel School of Marine and Atmospheric Sciences (UM/RSMAS). It is important to note that each eight-day average overlaps the previous average by one day. These eight-day averages are the MCSST weekly values given in this data set. Missing values are indicated by a DN of 0, ice values by 254 and land values by 255. Interpolated Data Wherever possible, missing values of eight-day valid data were filled and smoothed by the University of Miami, Rosenstiel School of Marine and Atmospheric Sciences (UM/RSMAS). As a result, this data set does not have any missing values over open ocean. However, missing values may still exist over large lakes and some small seas. These few remaining missing values are indicated by a digital number value of 0. Ice values are indicated by a digital number value of 254 and land values by 255. Flag Data The third data set contains the flags and number of observations for the valid MCSST data set. Flag values of 0 indicate missing data. Ice values are represented by 254 and land values by 255. Values greater than 0 and less than 254 represent the number of valid temperatures used in calculating the weekly average. Related Data Sets: AVHRR monthly global MCSST coregistered with CZCS data CD-ROM (PO.DAAC product 015) AVHRR Oceans Pathfinder global equal-angle all SST v1 (PO.DAAC product 050) AVHRR Oceans Pathfinder global equal-angle best SST v1 (PO.DAAC product 051) AVHRR Oceans Pathfinder global equal-area all SST v1 (PO.DAAC product 052) AVHRR Oceans Pathfinder global 0.5-deg resolution SST v1 (PO.DAAC product 053) AVHRR Oceans Pathfinder global equal-angle all SST v3 (PO.DAAC product 070) AVHRR Oceans Pathfinder global equal-angle best SST v3 (PO.DAAC product 071) AVHRR Oceans Pathfinder global equal-area all SST v3 (PO.DAAC product 072) AVHRR Oceans Pathfinder global 0.5-deg resolution SST v3 (PO.DAAC product 073) 2. Investigator(s): Dr. Otis Brown Rosenstiel School of Marine and Atmospheric Science University of Miami 4600 Rickenbacker Causeway Miami, Florida 33149 obrown@rsmas.miami.edu 3. Theory of Measurements: The history of SST computation from AVHRR radiances is discussed at length by [McClain et al., 1985]. Briefly, radiative transfer theory is used to correct for the effects of the atmosphere on the observations by utilizing "windows" of the electromagnetic spectrum where little or no atmospheric absorption occurs. Channel radiances are transformed (through the use of the Planck function) to units of temperature, then compared to a-priori temperatures measured at the surface. This comparison yields coefficients which, when applied to the global AVHRR data, give estimates of surface temperature which have been nominally accurate to 0.3° C. 4. Equipment: Sensor/Instrument Description: Collection Environment: NOAA polar-orbiting satellites Source/Platform: NOAA-7, NOAA-9, NOAA-11 and NOAA-14 Source/Platform Mission Objectives: The objective of the AVHRR is to measure multispectral radiance for the study of meterologic, oceanographic and hydrologic parameters such as sea surface temperature, ice extent and clouds. Key Variables: The AVHRR measures emitted and reflected radiation. Principles of Operation: The AVHRR is a four or five channel scanning radiometer which measures emitted and reflected radiation in the visible, near-infrared and thermal infrared regions of the electromagnetic spectrum. The table below was adapted from the NOAA Polar Orbiter Data User's Guide [Kidwell, 1995] and shows the portion of the spectrum measured by each channel. Please note that the data described in this document were obtained from the 5 channel AVHRR instruments, referred to as the AVHRR/2, flown on the NOAA-7, -9, -11 and -14 satellites. Spectral band widths (µ m) of the AVHRR Platform Channel Number 1 2 3 4 5 TIROS-N 0.55-0.90 0.725-1.10 3.55-3.93 10.5-11.5 NOAA-6,-8,-10 0.58-0.68 0.725-1.10 3.55-3.93 10.5-11.5 NOAA-7,-9,-11,-12,-14 0.58-0.68 0.725-1.10 3.55-3.93 10.3-11.3 11.5-12.5 NOAA-13 0.58-0.68 0.725-1.0 3.55-3.93 10.3-11.3 11.4-12.4 Each AVHRR scan views Earth for 51.282 milliseconds, during which time each channel of the analog data output is digitized. Scans occur at the rate of 6 per second, and the sampling rate of the AVHRR sensors is 39,936 samples per second per channel. During a scan, the detectors view an internal target, cold space, and the external scene. The temperature of the internal target is monitored, and space is assumed to have a black-body temperature of 3K. In this way, a simple two-point linear calibration is done internally [Schwalb, 1978]. Sensor/Instrument Measurement Geometry: The AVHRR has a cross-track scanning system which uses an elliptical beryllium mirror rotating at 360 RPM about an axis parallel to the Earth. The 110.8° cross-track scan equates to a swath width of about 2700 km. This swath width is greater than the 25.3° separation between successive orbital tracks, and provides overlapping coverage. Coverage is global, twice daily, at an instantaneous field of view (IFOV) of ~1.4 milliradians, giving a ground field of view of ~1.1 km at nadir for a nominal altitude of 833 km. Manufacturer of Sensor/Instrument: ITT Aerospace 1919 West Cook Road P.O. Box 3700 Ft. Wayne, Indiana 46801 (219) 327-9200 Calibration: Specifications: Descriptions of the pre-launch calibrations of the visible channels (channels 1 and 2) and the infrared (IR) channels (channels 3,4 and 5) are given in the Polar Orbiter User's Guide [Kidwell, 1995]. After launch, the IR channels are calibrated using a view of a stable blackbody and space as a reference. No in-flight visible channel calibration is performed. Tolerance: The design goals for the infrared (IR) channels were a noise equivalent differential temperature of 0.12K at 300K and a signal to noise ratio of 3:1 at 0.5% albedo [Kidwell, 1995]. Using the calibration techniques developed by Brown et al [1985], the overall calibration error estimate of the infrared channels derived from the thermal vacuum test is within 0.2° K. Frequency of Calibration: The thermal infrared channels are calibrated in flight using a view of a stable blackbody and space as a reference. Channels 1 and 2 have no onboard calibration capabilities, however, they are calibrated before launch. Other Calibration Information: In an effort to develop a consistent set of in-flight calibration algorithms for channels 4 and 5, a radiance-based correction procedure was developed to account for the non-linear response characteristics of the detectors. This procedure resulted in a consistent algorithm applied over the entire range of AVHRR operating temperatures, representing a significant improvement over the operational NOAA product. 5. Data Acquisition Methods: "The AVHRR provides high-quality digital measurements that have a basic spatial resolution of 1.1 km at nadir in the visible (0.55 - 0.68 microns) and reflected-infrared (0.725-1.1 microns) bands and in three emitted-IR "window" channels (3.55-3.93, 10.3-11.3, and 11.5-12.5 microns).... The full-resolution measurements are available locally by direct readout HRPT (High Resolution Picture Transmission) and by means of limited temporary onboard tape storage LAC (Local Area Coverage). GAC (Global Area Coverage) data is provided twice daily at a nominal resolution of 4 km (four of every five samples along the scan line are used to compute one average value, and the data from only every third scan line are processed) by means of onboard data reduction and tape recording" [McClain et al, 1985]. The GAC Level 1B data, provided by the NOAA National Environmental Satellite Data and Information Service (NESDIS), is used in the derivation of the multi-channel sea surface temperature. 6. Observations: Data Notes: Not Applicable Field Notes: A buoy match-up data set is used in computing the calibration coefficients used to calculate sea surface temperature. 7. Data Description: Spatial Characteristics: Spatial Coverage: The data are available as a global set (2048x1024 pixels). However, it should be noted that there are areas, particularly north of 60° North and south of 60° South, where there are very few values due to extensive periods of cloud cover and darkness. Spatial Coverage Map: AVHRR Daytime Weekly-Averaged Valid Multichannel Sea Surface Temperature [Image] AVHRR Daytime Weekly-Averaged Interpolated Multichannel Sea Surface Temperature [Image] Spatial Resolution: The spatial resolution in pixels per degree of longitude and latitude is 2048/360 or 5.689. Therefore, at the equator, there are 19.55 km per pixel. Because the data are on an equal-angle grid, the number of kilometers per pixel in the longitudinal direction decreases with the cosine of latitude. Projection: Global images of daytime and nighttime MCSST are on an equal-angle grid. The global grid contains 2048 samples from east to west and 1024 lines from north to south. Grid Description: The MCSST data sets are on an equal angle grid of 2048 columns by 1024 rows. Therefore, an equal-angle grid element spans 0.1757812 degrees (360/2048 or 180/1024) in longitude and latitude. Latitude and longitude coordinates are assigned to each grid element based on its center. To calculate the latitude and longitude of a grid point, the following equations can be used: longitude = xgp * dx +(dx/2) latitude = (90. - (ygp * dy)) - (dy/2) where: xgp= grid point in the x-direction (0 through 2047) ygp= grid point in the y-direction (0 through 1023) dx = 360 deg/2048 grid pt = 0.17578125 dy = 180 deg/1024 grid pt = 0.17578125 Please note that adding dx/2 and -dy/2 moves the geographic coordinates to the center of a grid box. Therefore, the top left corner of the Raster image corresponds to 0,90 (0° East, 90° North) and the lower right corresponds to 360, -90 (360° East, 90° South). The first grid element is centered at 90 - (0.1757812/2) latitude and (0.1757812/2) longitude. Temporal Characteristics: Temporal Coverage: Weekly averaged data exist for the period between 11 November 1981 and 6 December 2000. More recent data will be added to this product as they become available. Temporal Coverage Map: The table below lists the operational dates and nominal ascending node equator-crossing times for all platforms as found in the Polar Orbiter User's Guide [Kidwell, 1995]. Please note, however, that the data described in this document are derived only from NOAA-7, -9, -11 and -14 "afternoon" equator crossing satellites which carry the 5-channel AVHRR instrument. Satellite Operational Dates Northbound Equator Crossing Time TIROS-N OCT 19, 1978 - JAN 30, 15:00 LST 1980 NOAA-6 JUN 27, 1979 - MAR 5, 19:30 LST 1983 NOAA-7 AUG 24, 1981 - FEB 1, 14:30 LST 1985 NOAA-8 MAY 3, 1983 - OCT 31, 19:30 LST 1985 NOAA-9 FEB 25, 1985 - NOV 7, 14:20 LST 1988 NOAA-10 NOV 17, 1986 - SEP 16, 19:30 LST 1991 NOAA-11 NOV 8, 1988 - APR 11, 13:40 LST 1995 NOAA-12 SEP 16, 1991 - present 19:30 LST NOAA-13 AUG 9, 1993 - AUG 21, 13:40 LST 1993 NOAA-14 DEC 30, 1994 - present 13:40 LST Temporal Resolution: Daytime and nighttime sea surface temperature values from the NOAA/NESDIS Global Retrieval Tapes were binned and averaged into eight-day measurements by the University of Miami, Rosenstiel School of Marine and Atmospheric Sciences (UM/RSMAS). It is important to note that each eight-day average overlaps the previous average by one day. These eight-day averages are the MCSST weekly values given in this data set. Daytime and nighttime MCSST values are binned separately. Data Characteristics: Parameter/Variable: Sea Surface Temperature (SST) Variable Description/Definition: Sea Surface Temperature - temperature of emitted energy from the sea surface. Unit of Measurement: MCSST data are provided in the form of digital numbers (DN). Each digital number is a value between 0 and 255. To convert the DN to an SST value in degrees Celsius, use the following equation: SST (° C) = 0.15 * DN -2.1 Data Source: AVHRR Data Range: Digital numbers range between 0 and 255. 0 is the flag value for missing data. Digital numbers of 254 and 255 are also flag values and indicate ice and land, respectively. After converting DN to SST, non-flag values of SST should have a maximum value of approximately 32° C for summer months in the Persian Gulf and a minimum of approximately -2° C in polar regions. Sample Data Record: The minimum and maximum digital numbers for each of the three data sets in the file sd1981321.hdf are 0 and 255, respectively. However, 0 and 255 are the flag values for missing data and land. Excluding all flag values, the minimum and maximum digital numbers for the valid data set in sn1981321.hdf are 1 and 235. For the interpolated data set, the minimum and maximum non-flag digital numbers are 1 and 235. For the flag/number of observations data set, the non-flag minimum and maximum are 1 and 252. File Naming Convention: The global weekly files are named according the following convention: styyyyddd.fff where: s = sea surface temperature t = (d)aytime or (n)ighttime yyyy= four digit year ddd = three digit julian day marking the end of a week data format fff = hdf denotes Hierarchical Data Format dat denotes Raw Binary Format 8. Data Organization: Data Granularity: A general description of data granularity as it applies to the IMS appears in the EOSDIS Glossary. The basic granule is one data file which contains three data sets. However, subsetting capabilities are available from the MCSST Homepage. Data Format: The data are available in Raw Binary or HDF (Hierarchical Data Format). For more information on HDF, contact the National Center for Supercomputing Applications, http://hdf.ncsa.uiuc.edu. 9. Data Manipulations: Formulae: Derivation Techniques and Algorithms: MCSST data is provided in the form of digital numbers (DN). Each digital number is a value between 0 and 255. To convert the DN to an SST value in degrees Celsius, use the following equation: SST (° C) = 0.15 * DN -2.1 Data Processing Sequence: Processing Steps: MCSST values are originally derived from the AVHRR GAC 1B data provided on the NOAA/NESDIS Global Retrieval Tapes. An overview of the process used to obtain MCSST values is provided by McClain et al [1985]. The daytime and nighttime MCSST values are then binned separately and averaged into eight-day measurements by the University of Miami, Rosenstiel School of Marine and Atmospheric Sciences (UM/RSMAS). It is important to note that each eight-day average overlaps the previous average by one day. These weekly averages are given in the valid data set (the first data set) of each data file. The number of observations used in computing the weekly averages of the valid data set are provided in the third data set of each data file. The weekly averaged interpolated data are contained in the second data set of each file. These values are computed by the University of Miami using a two step process. First, wherever possible, missing values are filled. Missing values are identified by searching every other row and column of the valid data set iteratively. In this way, sst values are locally dependent. Once a missing value is identified, the value is filled by performing a weighted average on the surrounding eight pixels, provided that atleast one of these pixels contains a value. The two horizontal and two vertical pixels are weighted more heavily than the four diagonal pixels, because the horizontal and vertical pixels are geographically closer to the missing value. The iterations continue until all possible missing values are filled. It is important to note that a canonical ice mask is applied over the north and south poles. These values are treated the same as the valid MCSST data so that the interpolation will trend to colder values in higher latitudes. Similarly, a land mask is applied so that any valid data which fall on a land pixel are ignored. As a result of this procedure, some large lakes and small seas will not be filled due to the lack of valid MCSST data in these regions. The second step in the process is the relaxation or smoothing of the filled data. The filled values are also located by searching every other row and column iteratively, thus allowing the field to relax more smoothly. Once a filled value is found, the pixel will be evaluated based on the surrounding eight pixels. A value may change to more closely resemble surrounding valid MCSST measurements or surrounding filled values which were found in the early iterations. Processing Changes: The basic algorithms for producing MCSST values have changed very little since operational processing began in November 1981. "The coefficients of the atmospheric correction equations are tuned shortly after the launch of each satellite using a large set of match-ups (within 25km and 6 hours) between MCSSTs and drifting buoy measurements at 1m depth. Once the coefficients are determined, they are rarely changed until the next satellite launch" [McClain et al, 1989]. Calculations: Special Corrections/Adjustments: Cloud filtering and atmospheric attenuation corrections have been applied to the data [McClain et al, 1985]. Refinements and modifications have also been developed to handle occurrences, such as volcanic eruptions and large sandstorms, which may interfere with the measurement of sea surface temperature. More details about some of these refinements can be found in McClain et al [1989]. Calculated Variables: Sea Surface Temperature Graphs and Plots: Not Applicable. 10. Errors: Sources of Error: The weekly data provided to the PO.DAAC from the University of Miami were originally stored as 16-bit integers in DSP Format. The PO.DAAC converted these data from 16-bit integers in DSP to 8-bit raster images in HDF (Hierarchical Data Format). The digital numbers in DSP ranged from -20 to 350. Therefore, to convert the data from integers to bytes, the data had to be scaled to values ranging from 0 to 255. Scaling the integers resulted in floating point values. Converting these floating point values to bytes truncates the decimal part of the float. As a result, the HDF values of sea surface temperature could vary from the DSP values of sea surface temperature by as much as 0.15° Celsius. The data in Raw Binary format were derived from the HDF data, and therefore will also by as much as 0.15\260 Celsius from DSP data. Major sources of error in radiometric determination are sun glint (AVHRR channel 3) and water vapor absorption in the lower atmosphere (AVHRR channels 4 and 5) [Brown et al, 1985]. Another source of error is aerosol absorption. The aerosol content in the atmosphere is increased during volcanic eruptions and large dust storms such as those from the Sahara. This is especially apparent in data after the El Chichon volcanic eruption in April 1982 and the Mount Pinatubo volcanic eruption in June 1991 [McClain et al,1989]. The accuracy of SST measurements may also be limited by sensor design and calibration, atmospheric correction algorithms, data processing procedures and local variations in air-sea interaction [Brown et al, 1993]. The problem of skin/bulk temperature differences also occurs; however, the use of a temperature-dependent bias correction from the satellite and buoy match-ups attempts to adjust for this effect [McClain, 1985]. Quality Assessment: Data Validation by Source: Information not available. Confidence Level/Accuracy Judgement: McClain et al [1985] determined that the technique used with the NOAA-9 satellite yielded consistent biases near -0.1° C and rms differences near 0.5° C. Measurement Error for Parameters: Excluding periods of high aerosol absorption, McClain et al [1985] calcualted the global statistical measures of the MCSST anomolies relative to ship data to be as follows: biases, 0.3-0.4° C (MCSST lower than ship); standard deviations, 0.5-0.6° C; cross correlations, +0.3 to +0.7. Additional Quality Assessments: A detailed analysis of the calibration procedures for the NOAA AVHRR based on thermal vacuum test data was performed by Brown et al [1985]. The overall calibration error derived from this test is within 0.2° K. Data Verification by Data Center: Information not available. 11. Notes: Limitations of the Data: "Among the primary limitations of the MCSST, or any other infrared method, is lack of retrievals in areas of persistent cloud cover. The relatively high resolution of the AVHRR, however, does enable more retrievals to be made in patchy cloud cover than with the other sensors" [McClain et al, 1985]. Known Problems with the Data: The first row of weekly MCSST data, the row corresponding to 90 °N, contains erroneous data in the flag data set (the third data set in the file) for the entire time series. Erroneous data for this latitude also exist in the valid and interpolated data sets (the first and second data sets in the file) for the period between week 322 of 1986 and present. In order to adjust for this slight error, it is recommended that the user set the Digital Numbers for this latitude to 254, the value of ice. The weekly data provided to the PO.DAAC from the University of Miami were originally stored as 16-bit integers in DSP Format. The PO.DAAC converted these data from 16-bit integers in DSP to 8-bit raster images in HDF (Hierarchical Data Format). The digital numbers in DSP ranged from -20 to 350. Therefore, to convert the data from integers to bytes, the data had to be scaled to values ranging from 0 to 255. Scaling the integers resulted in floating point values. Converting these floating point values to bytes truncates the decimal part of the float. As a result, the HDF values of sea surface temperature could vary from the DSP values of sea surface temperature by as much as 0.15° Celsius. The data in Raw Binary format were derived from the HDF data, and therefore will also by as much as 0.15\260 Celsius from DSP data. "The eruptions of the El Chichon volcano in Mexico in April 1982 resulted in very large volumes of sulphuric acid droplet clouds being injected into the stratosphere and distributed initially into a relatively narrow zonal band around the world. This volcanic aerosol layer had a significant effect on the retrieval of MCSSTs for several months and was detectable throught the remainder of 1982. The MCSST algorithm rejected virtually all the daytime measurements as cloud-contiminated over large areas of the tropics and subtropics. Only nighttime MCSSTs were obtained during this period, and these retrievals were sometimes several degrees too cold from the attenuating effects of the aerosol" [McClain, 1989]. Similar problems also occurred after the eruption of Mount Pinatubo in June 1991. Usage Guidance: It should be noted that there are areas, particularly north of 60° North and south of 60° South, where there are very few values due to extensive periods of cloud cover and darkness. It is recommended that caution be exercised when using interpolated data in these regions. In addition, NOAA, the original data source, did not process all of the data due to operational difficulties. Therefore, in some cases, data are sparser than one would expect. Any Other Relevant Information about the Study: None. 12. Application of the Data Set: Global and regional climate studies, air-sea interaction studies, mesoscale oceanography, calculation of heat transport in the ocean, El Nino predictions, fishery research. 13. Future Modifications and Plans: As part of the AVHRR Oceans Pathfinder project, JPL is tasked with reprocessing historical AVHRR data to produce a satellite SST database for global climate studies. This project has implemented new procedures to improve the calibration accuracy of the data. The number of valid retrievals has also increased by an approximate factor of two. For more information, see the AVHRR Oceans Pathfinder Homepage, http://podaac.jpl.nasa.gov/sst/. 14. Software: Software Description: Read Software is available on the PO.DAAC FTP site (podaac.jpl.nasa.gov). Programs to read the Raw Binary data are provided in FORTRAN and IDL. Programs to read the HDF data and attributes are written in C, FORTRAN and IDL. Please note that unlike Raw Binary data, the HDF library must be installed before the HDF data can be read. To obtain the HDF library, please contact the National Center for Supercomputing Applications, http://hdf.ncsa.uiuc.edu. Software Access: The software is in the pub/sea_surface_temperature/avhrr/mcsst/software directory on the PO.DAAC FTP site (podaac.jpl.nasa.gov). 15. Data Access: Contact Information: User Services Office Physical Oceanography Distributed Active Archive Center (PO.DAAC) Jet Propulsion Laboratory (JPL) MS Raytheon-299 4800 Oak Grove Drive Pasadena, CA 91109, U.S.A. Phone: (626) 744-5508 Fax: (626) 744-5506 Email: podaac@podaac.jpl.nasa.gov URL: http://podaac.jpl.nasa.gov Data Center Identification: Jet Propulsion Laboratory Physical Oceanography Distributed Active Archive Center (PO.DAAC) Procedures for Obtaining Data: Data are available on the PO.DAAC FTP site (podaac.jpl.nasa.gov) in the pub/sea_surface_temperature/avhrr/mcsst directory. Data may also be ordered on 8mm tapes by using the MCSST Homepage or by contacting the User Services Office. Orders can also be placed through the Information Management System (IMS). See http://www-v0ims.gsfc.nasa.gov/v0ims/eosdis_home.html for further information. Data Center Status/Plans: None 16. Output Products and Availability: Data are available via anonymous FTP to podaac.jpl.nasa.gov in the pub directory. Data may also be provided on 8mm tape by request. 17. References: Brown, J.W., O.B. Brown, and R.H. Evans, Calibration of Advanced Very High Resolution Radiometer Infrared Channels: A New Approach to Nonlinear Correction, Journal of Geophysical Research, 98, 18257-18268, 1993. Brown, O.B., J.W. Brown, and R.H. Evans, Calibration of Advanced Very High Resolution Radiometer Infrared Observations, Journal of Geophysical Research, 90, 11667-11677, 1985. Kidwell, K., NOAA Polar Orbiter User's Guide. NCDC/NESDIS, National Climatic Data Center, Washington, D.C., 1995. On-line document available at: http://www2.ncdc.noaa.gov/POD McClain, E.P., Global sea surface temperatures and cloud clearing for aerosol optical depth estimates, Int. J. Remote Sensing, 10, 763-769, 1989. McClain, E.P., W.G. Pichel, and C.C. Walton, Comparative Performance of AVHRR-Based Multichannel Sea Surface Temperatures, Journal of Geophysical Research, 90, 11587-11601, 1985. Schwalb, A., The TIROS-N/NOAA A-G satellite series, NOAA Tech. Memo. NESS 95, 1978. 18. Glossary of Terms: AVHRR Advanced Very High Resolution Radiometer is a four (TIROS-N, NOAA-6, NOAA-8, NOAA-10) or five (NOAA-7, -9, -11, -12, -13, -14) channel scanning radiometer capable of providing global daytime and nighttime surface radiation in real time (HRPT) and recorded (LAC and GAC) modes. NOAA National Oceanic and Atmospheric Administration / TIROS-N spacecraft are third generation polar-orbiting, meteorological satellites that operate in pairs in orbits that are 90 degress apart (7:30 am and 2:30 pm equator crossing times.) SEA SURFACE TEMPERATURE Temperature of emitted energy from the sea surface. 19. List of Acronyms: AVHRR Advanced Very High Resoultion Radiometer DN Digital Number GAC Global Area Coverage HDF Hierarchical Data Format HRPT High Resolution Picture Transmission IDL Interactive Data Language IFOV Instantaneous Field of View IMS Information Management System IR Infrared LAC Local Area Coverage MCSST Multichannel Sea Surface Temperature NESDIS National Environmental Satellite Data and Information Service NOAA National Oceanic and Atmospheric Administration PO.DAAC Physical Oceanography Distributed Active Archive Center SST Sea Surface Temperature TIROS-N Television Infrared Observing satellite series N. UM/RSMAS University of Miami, Rosenstiel School of Marine and Atmospheric Sciences URL Uniform Resource Locator 20. Document Information: Document Revision Date: 11 February 1998 -- Raw Binary Format availability noted 9 December 1997 -- Errors in Data noted 7 January 1997 -- original revision Document Review Date: 23 October 1995 Document ID: Citation: Document Curator: PO.DAAC MCSST Data Team kelly@podaac.jpl.nasa.gov Document URL: http://podaac.jpl.nasa.gov:2031/DATASET_DOCS/avhrr_wkly_mcsst.html