This data set is no longer available for use because of errors in the data. However, replacement data are expected sometime in 2013. If you need information pertaining to the data errors, please see the Error Sources Section of the guide documentation. If you have further questions, contact NSIDC User Services by e-mail: email@example.com or by telephone +1 303.492.6199.
The Advanced Very High Resolution Radiometer (AVHRR) Polar Pathfinder Twice-Daily 5 km EASE-Grid Composites are a collection of products for both poles, consisting of twice-daily calibrated and gridded satellite channel data and derived parameters. Data include five AVHRR channels, clear sky surface broadband albedo and skin temperature, solar zenith angle, satellite elevation angle, sun-satellite relative azimuth angle, surface type mask, cloud mask, and Universal Coordinated Time (UTC) of acquisition. AVHRR Polar Pathfinder data extend pole ward from 48.4 degrees north and 53.2 degrees south latitudes, from 24 July 1981 through 30 June 2005. Data are in 1-byte and 2-byte integer grid format and are available by FTP.
Note: Due to a problem with the NOAA-16 scan motor, all the channel data is shifted sporadically between 2001 and 2005, causing the channels to contain data from another channel; thus, the derived parameters also contain errors during this time-period. See Table 12 in the Error Sources section of this document for specific dates.
The following example shows how to cite the use of this data set in a publication. For more information, see our Use and Copyright Web page.
The following example shows how to cite the use of this data set in a publication. List the principal investigators, year of data set release, data set title and version number, dates of the data you used (for example, March to June 2004), publisher: NSIDC, and digital media.
Fowler, Chuck, James Maslanik, Terry Haran, Ted Scambos, Jeffrey Key, and William Emery. 2000, updated 2007. AVHRR Polar Pathfinder Twice-daily 5 km EASE-Grid Composites V003 , [list dates of data used]. Boulder, Colorado USA: National Snow and Ice Data Center. Digital media.
|Data format||1-byte and 2-byte big-endian integer grid format.|
|Spatial coverage and resolution||Spatial coverage extends pole ward from 48.4°N and 53.2°S latitudes, at 5 km resolution.|
|Temporal coverage and resolution||Temporal coverage is from 24 July 1981 to 30 June 2005.
This data set consists of twice-daily composites approximately 0400 hours (morning) and 1400 hours (afternoon) for the Northern Hemisphere, and 0200 hours (morning) and 1400 hours (afternoon) for the Southern Hemisphere.
|Grid type and size||EASE-Grid projection of the Northern and Southern Hemispheres.
The Northern Hemisphere grid is 1805 pixels by 1805 pixels.
The Southern Hemisphere grid is 1605 pixels by 1605 pixels.
|File naming convention||Example: a16_n005_2005181_9999_smsk.v3|
|File size||Northern Hemisphere: 6.52 MB (2-byte) and 3.26 MB (1-byte) per granule.
Southern Hemisphere: 5.15 MB (2-byte) and 2.58 MB (1-byte) per granule.
|Parameter(s)||Channel 1 Top of the Atmosphere (TOA) Reflectance
Channel 2 TOA Reflectance
Channel 3 TOA Brightness Temperature
Channel 3A TOA Reflectance
Channel 3B TOA Brightness Temperature
Channel 4 TOA Brightness Temperature
Channel 5 TOA Brightness Temperature
Clear Sky Surface Broadband Albedo
Clear Sky Surface Skin Temperature
Solar Zenith Angle
Satellite Elevation Angle
Sun-satellite Relative Azimuth Angle
Surface Type Mask
Universal Coordinated Time (UTC) of Acquisition
|Procedures for obtaining data||Date are currently unavailable becasue of data errors. However, replacement data are expected by the end of 2012. If you need information pertaining to the data errors, please see the Error Sources Section of the guide documentation. If you have further questions, contact NSIDC User Services by e-mail: firstname.lastname@example.org or by telephone +1 303.492.6199.|
Chuck Fowler, James Maslanik, and William Emery
Colorado Center for Astrodynamics Research
CCAR, 431 UCB
University of Colorado
Boulder, CO 80309-0431
Terry Haran and Ted Scambos
National Snow and Ice Data Center
CIRES, 449 UCB
University of Colorado
Boulder, CO 80309-0449
1225 W. Dayton St.
Madison, WI 53706
NSIDC User Services
National Snow and Ice Data Center
CIRES, 449 UCB
University of Colorado
Boulder, CO 80309-0449 USA
phone: +1 303.492.6199
fax: +1 303.492.2468
form: Contact NSIDC User Services
Date are currently unavailable becasue of data errors. However, replacement data are expected by the end of 2012. If you need information pertaining to the data errors, please see the Error Sources Section of the guide documentation. If you have further questions, contact NSIDC User Services by e-mail: email@example.com or by telephone +1 303.492.6199.
Individual parameters are stored as 1-byte or 2-byte raster files for each date, time, and hemisphere. Cell size is 5 km, with either 1 or 2 bytes per cell. Refer to the File Naming Convention section of this document. Byte order is big-endian. The Northern Hemisphere grid is 1805 pixels wide by 1805 pixels high, centered on the North Pole. The Southern Hemisphere grid is 1605 pixels wide by 1605 pixels high, centered on the South Pole.
Formats for 1-byte raster files are summarized in Tables 1 and 2. Formats for 2-byte raster files are summarized in the Parameter Description section.
Surface Type Mask (SMSK)
|20-29||mostly first-year ice (range indicates total ice concentration in tens of percent; for example, a value of 20 indicates more first-year ice than multiyear ice with a total ice concentration between one and ten percent)|
|30-39||mostly multi-year ice (range is same as above; however, multiyear ice is dominant)|
|50||snow covered land|
Cloud Mask (CMSK)
Versions 1 and 2 Data (1981 to 1993)
|Bit 0||The least significant bit. Cloud mask from Cloud and Surface Parameter Retrieval (CASPR) single-day algorithm.||0 - clear|
|1 - cloud|
|Bit 1||Cloud mask based on a time-filtered series of channel four.||0 - clear|
|1 - cloud|
|Bit 2||Cloud mask based on multi day CASPR algorithm.||0 - clear|
|1 - cloud|
|Bit 7||Set if no valid data are present.||0 - valid data|
|1 - missing data|
Cloud Mask (CMSK)
Version 3 Data (1994 to 2005)
|Bit 0||The least significant bit. Cloud mask from CASPR single-day algorithm.||0 - clear|
|1 - cloud|
|Bit 1||Cloud mask from updated CASPR multi day algorithm.||0 - clear|
|1 - cloud|
|Bit 2||Set if no valid data are present.||0 - valid data|
|1 - missing data|
|Note: See Summary of bit processing for more information.|
Time Mask (Time)
|Data are in increments of 0.1 hours with cell values ranging from 0 to 239 for Version 1 and 2 data, and 0 to 244 for Version 3 data.|
This section explains the file naming convention used for this product with an example.
Example file name: a16_n005_2005181_9999_smsk.v3
|indicates AVHRR Polar Pathfinder|
|represents which satellite the data came from such as NOAA-16|
|represents the Northern or Southern hemisphere (n for northern and s for southern)|
|represents the 5 km resolution|
|3-digit day of year|
|the hour (0400 or 1400 for north files, 0200 or 1400 for south files, and 9999 for north and south surface type mask files - one per day)|
|zzzz||the file type as listed below:
The file naming convention is the same for AVHRR files ordered through the GISMO interface except that the text subset_ is appended to the front of the file name.
|represents the version number of the data, such as v3 for Version 3|
Northern Hemisphere: 6.52 MB (2-byte) and 3.26 MB (1-byte) per granule.
Southern Hemisphere: 5.15 MB (2-byte) and 2.58 MB (1-byte) per granule.
Spatial coverage extends from 48.4 degrees to 90.0 degrees north latitude, and from 53.2 degrees to 90.0 degrees south latitude. The actual coverage extends beyond these limits in the grid corners. Tables 5 and 6 summarizes the values of corner pixels for each hemisphere.
Note: For the Northern Hemisphere, the center of the tangent pixels is 48.42649 north latitude and the outer edge is 48.40237 north latitude. For the Southern Hemisphere, the center of the tangent pixels is 53.21244 south latitude and the outer edge is 53.18868 south latitude.
of Corner Pixel
|Upper left||29.74956° N, 135.00000° W||29.71269° N, 135.00000° W|
|Upper right||29.74956 N°, 135.00000° E||29.71269° N, 135.00000° E|
|Lower left||29.74956 N°, 45.00000° W||29.71269° N, 45.00000° W|
|Lower right||29.74956 N°, 45.00000° E||29.71269° N, 45.00000° E|
of Corner Pixel
|Lower left||36.99339° S, 135.00000° W||36.95776° S, 135.00000° W|
|Lower right||36.99339° S, 135.00000° E||36.95776° S, 135.00000° E|
|Upper left||36.99339° S, 45.00000° W||36.95776° S, 45.00000° W|
|Upper right||36.99339° S, 45.00000° E||36.95776° S, 45.00000° E|
Click on the thumbnails below to see detailed coverage maps.
AVHRR Global Area of Coverage (GAC) data are generated from the original Local Area Coverage (LAC) imagery by applying a sub sampling procedure. For every third line in the image, a series of five pixels is selected. The first four pixels are averaged, and the fifth pixel is removed. Data are regridded to the EASE-Grid projection with a 5 km pixel spacing.
The data are received as swath data. The AVHRR instrument scans in the across-track direction with a continuously rotating scan mirror, viewing a swath of over 100 degrees and up to 55 degrees off-nadir.
Data are georeferenced to the Equal Area Scalable Earth-Grid (EASE-Grid) projection, an azimuthal equal area projection. Please review the All About EASE-Grid Web site for general information on the EASE-Grid, and the Summary of NOAA/NASA Polar Pathfinder Grid Relationships Web page for details of map projection parameters.
The data are provided in EASE-grid projection. The Northern Hemisphere grid is 1805 pixels by 1805 pixels, centered on the North Pole. The Southern Hemisphere grid is 1605 pixels by 1605 pixels, centered on the South Pole. Cell size is 5 km. Grid coordinates begin in the upper left corner of the grid. See the NOAA/NASA Polar Pathfinder Web page for more information.
Temporal coverage is from 24 July 1981 to 30 June 2005. Exclusive of missing dates, the average availability of data at any location is greater than 95 percent for the north polar regions and 96 percent for the south polar regions. Tables 7, 8, and 9 summarize the temporal coverage for Versions 1, 2, and 3 data. Table 10 summarizes the missing dates of temporal coverage.
Missing Dates of Temporal Coverage
|1981||22 August - 31 August
29, 30 November
25, 26, 29 September
28 - 31 December
|1983||2 - 7, 9 - 13 January
1 - 3 May
6, 17 - 23 August
21 - 26 September
12, 13, 19, 20, 23 - 26, 28 - 31 December
|1984||1 - 10, 14, 15 January
18 - 22, 24, 25 February
23 - 30 March
10, 14 - 19 April
4 - 6 June
13, 18 November
6, 9 December
|1985||1 - 3, 13, 17, 20, 23 January
8 - 10 February
11, 12 April
7, 14 December
|1986||28 - 31 January
14, 15 March
18 - 21 May
13, 14 June
27 - 31 December
3, 24 November
|1989||18 - 21 May|
|1990||18 - 21 February|
|1991||17 - 27 July|
|1994||14 September - 31 December|
|1995||1 - 20 January
5, 19 - 21 March
21, 22 May
|1997|| 8, 17, 18 February
12 March - 22 April
11, 14, 23 June
10 - 12 February
28, 29, 31 May
7 - 9, 13, 16 - 19 July,
4 - 9 August
Twice-daily composites are produced at target times of 0400 (morning) and 1400 (afternoon) local time for the Northern Hemisphere, and 0200 (morning) and 1400 (afternoon) local time for the Southern Hemisphere. The precise local time for 90 percent of the cells in each grid is within one hour of the target time. See the Processing Steps section of this document for more information.
The AVHRR Polar Pathfinder twice-daily 5 km EASE-grid composites contain the following parameters:
AVHRR 5 km Data Products and Volumes for Both Hemispheres
|Channel 1 TOA Reflectance||2||2||23||% reflectance||0.1||0 to 1000|
|Channel 2 TOA Reflectance||2||2||23||% reflectance||0.1||0 to 1000|
|Channel 3 TOA Brightness Temperature||2||2||23||kelvin||0.1||<1900 to 3100>|
|Channel 3A TOA Reflectance||2||2||23||% reflectance||0.1||<0 to 1000>|
|Channel 3B TOA Brightness Temperature||2||2||23||kelvin||0.1||<1900 to 3100>|
|Channel 4 TOA Brightness Temperature||2||2||23||kelvin||0.1||<1900 to 3100>|
|Channel 5 TOA Brightness Temperature||2||2||23||kelvin||0.1||<1900 to 3100>|
|Clear Sky Surface Broadband Albedo||2||2||23||% albedo||0.1||<0 to 1000>|
|Clear Sky Surface Skin Temperature||2||2||23||kelvin||0.1||<1900 to 3100>|
|Solar Zenith Angle||2||2||23||degrees||0.1||<0 to 900>|
|Satellite Elevation Angle||2||2||23||degrees||0.1||0 to 900|
|Sun-satellite Relative Azimuth Angle||2||2||23||degrees||0.1||0 to 1800|
|Surface Type Mask||1||1||6||n/a||n/a||10 to 60|
|Cloud Mask||1||2||12||n/a||n/a||0 to 7, 128|
|Time of Acquisition (UTC)||1||2||12||hour||0.1||0 to 239a
0 to 244b
a Versions 1 and 2 data
b Version 3 data
Data were scaled (except for surface type and cloud mask, indicated by N/A) with a scaling factor. The original data values can be recovered using the following equation: orig_value=Scaling_Factor * scaled_value.
A known problem exists with the Version 1 and 2 products. When the start of Acquisition Time (UTC) for an orbital swath started near the end of a UTC day, for example, 1983, day 122, 23:54, the end of the swath would extend into the beginning of the following day, for example, 1983, day 123, 00:06. As a result, the corresponding next day pixels are included in the current day composite. This is not a problem in and of itself. However, the UTC parameters for these next day pixels contain hour values of zero and greater, for example, 1983, day 123, 0.1. This causes the pixels to appear to have an acquisition time 24 hours earlier than their true acquisition time. Version 3 data labels next day pixels with a time of acquisition value of 24 or greater, for example, 1983, day 123, 24.1 from the preceding example.
A known problem exists with the NOAA-16 Version 3 data. Due to a problem with the scan motor, all the channel data are shifted sporadically causing the channels to contain data from another channel; thus, the derived parameters are in error when this channel shift occurs. The dates when the scan motor problem affects the data are list in Table 12. Note however that the scan motor problem does not affect the entire composited image on these dates, but rather there are patches of bad data within the composite. See Figure 1 for an example. For more information regarding the scan motor problem, please visit the NOAA Satellite and Information Services: Office of Satellite Operations NOAA 16 AVHRR Subsystem Summary Web page.
|2001||1 January (missing files)|
|6, 23, 31 January
1, 13, 19, 27 February
13, 14 March
3, 8, 9, 28 April
|2003||11, 17, 22 March
19 - 22, 24 September
5, 22, 26 December
|2004||14 - 24 January
10, 16 - 18, 20 - 31 March
1 - 9, 12 - 14, 20 - 29 April
2 - 5, 8 - 15, 19 - 21, 29, 30 May
6, 10 - 17, 21, 23, 25, 27, 28 - 31 July
1 - 3 August
9, 20 September
|2005||30 March (missing files)|
Figure 1. Northern Hemisphere Composite at 1400 Hours Showing Patches of Bad Data
Graphs spanning the entire temporal coverage of the data indicate that sensor calibration errors have occurred. Albedo measurements in areas where only small variances are expected, consistently show a substantial dip in 1995 and again in 2001 to 2005. This unusual pattern is most likely resulting from incorrect sensor calibration during those periods. Figures 2 through 4 show the albedo dip patterns at Summit, South Dome, and Humboldt glaciers in Greenland.
Figure 2. Albedo Measurements at Summit Glacier
Figure 3. Albedo Measurements at South Dome Glacier
Figure 4. Albedo Measurements at Humbolt Glacier
Projection inconsistencies were found between the CASPR processing Versions 2 and 3, resulting in slight geolocation variance. Instances in which the two processing versions are intermixed can cause animated images to appear to jitter. From 2002 to 2005, an incorrect ephemeris was used causing a geographic shift in the data.
The swath compositing seems to be in error between 26 July – 2 August, 1983. Starting on 15 May 2004, the swath composite shows similar errors, which increase in intensity throughout the 2004 summer months.
Isolated instances of misidentified data parameters were found. In these cases, either the land masking or the IR/Vis channels is interchanged.
Channel data are accurate to within approximately ± 0.2 percent based on sensor noise level of 0.4 Data Number (DN). Temperatures are accurate to within approximately two kelvin. Relative albedos in adjacent grid cells are accurate to within approximately five percent. However, large errors are expected in the absolute albedo values. See below for more information.
Product validation is a continuing process that takes advantage of comparative data as they become available. Comparisons were made between AVHRR Polar Pathfinder clear sky skin temperatures and surface-based measurements obtained at the South Pole over a seven-day period in 1995. These field data were collected by Robert Stone of the Cooperative Institute for Research in Environmental Sciences (CIRES) using a sled-mounted KT-19 pyrometer. Excluding observations when cloud cover was present, the agreement was generally within 0.5 kelvin. For data averaged over a four-hour period, temperatures were within 0.1 kelvin. A mean of -38.15 degrees Celsius for the AVHRR Polar Pathfinder observations, versus a mean of -38.25 degrees Celsius for the field data.
Evaluations were also performed for the AVHRR Polar Pathfinder retrievals of surface albedo over the Greenland Ice Sheet through comparisons with albedo measured at 14 Automatic Weather Stations (AWS) around the Greenland Ice Sheet from January 1997 to August 1998. Results show that AVHRR-derived surface albedo values are, on average, 10 percent less than those measured by the AWS stations. However, station measurements tend to be positively biased by about four percent, and the differences in absolute albedo may be less, about six percent. In regions of Greenland where the albedo variability is small, such as the dry snow facies, the AVHRR albedo uncertainty exceeds the natural variability. Stroeve concluded that while further work is needed to improve the absolute accuracy of the AVHRR-derived surface albedo, the data provide temporally and spatially consistent estimates of the Greenland Ice Sheet albedo (Stroeve et al. 2001) and (Stroeve 2002).
Analyses of the AVHRR Polar Pathfinder data, compared with data from the Surface Heat Budget of the Arctic Ocean (SHEBA) project, are in progress. See (Maslanik et al. 2000) for preliminary results. The cloud masking process was assessed and refined throughout the duration of the project to optimize the algorithm for the entire areas of coverage. Comparisons of areally-averaged cloud fractions from the AVHRR Polar Pathfinder Twice-daily 5 km EASE-Grid Composites with field observations at the SHEBA field site show that the AVHRR data were within nine percent of the cloud lidar/radar observations averaged from April to July 1998 with Pathfinder data underestimating cloud fraction relative to the field measurements. Differences in monthly means for this period ranged from 2 percent in June to 21 percent in July. Comparison of all-sky skin temperature and albedo values derived from the AVHRR Polar Pathfinder Twice-daily 5 km EASE-Grid Composites with SHEBA observations is described in (Maslanik et al. 2000).
Other validation studies of surface temperature and albedo retrieval procedures included surface observations from a NOAA research site near Barrow, Alaska, 71.32 degrees north latitude, 156.61 degrees west longitude. Daily AVHRR data from a preliminary Pathfinder data set from mid-1992 to mid-1993 were used for this validation (Meier et al. 1997). Surface temperature estimates agreed with observations, with a correlation coefficient of 0.98, a bias of -0.97, and a RMSE of 4.70. For surface albedo, the bias (mean error) in the estimates was near zero, r=0.81, bias=0.00, RMSE=0.17, but the individual observations exhibited significant variability, attributed to surface inhomogeneity and retrieval scheme sensitivity to changes in atmospheric aerosol and water vapor amounts.
Accuracies of the products are difficult to determine given the limited nature of existing case studies. Also, conditions vary substantially across the large product domains and over time. Plans are being developed to further define product accuracies for snow-covered areas, sea ice, and ice sheets. Based on studies to date, accuracies in general are approximately ± 2 kelvin for AVHRR-derived clear sky skin temperatures and ± 0.06 kelvin for albedo. Much of this error is likely due to uncertainties in the performance of the cloud detection methods. For clear sky conditions, accuracies for albedo and temperature products are expected to be in the range noted in the Greenland Barrow case studies.
Data and related information will be updated as appropriate.
Additional comparisons with in situ measurements of albedo and temperature are planned. More information on the characteristics and quality of the AVHRR Polar Pathfinder data is provided by (Maslanik et al. 1998), (Maslanik et al. 2000), (Stroeve et al. 2001), and (Stroeve 2002).
Comparison with in situ measurements of albedo and temperature is in progress. Results will be summarized here as they become available.
Remote sensing in the optical part of the electromagnetic spectrum (400-2500 nm) involves measuring the combined reflectance of solar radiation from both the Earth's surface and atmosphere. There are several specific definitions of reflectance referenced in Table 13, but in general, reflectance involves the diffuse scattering of light by a geometrically complex surface (Hapke 1993). Reflectance varies according to the degree of collimation, the incident irradiance, and the collimation of the detector. Collimation refers to the degree of angular diffusion of the the incident light or the size of the angular field of view of the detector. For instance, direct beam solar energy is considered highly collimated whereas the diffuse sky radiance is uncollimated; a narrow-angle field of view detector can be considered collimated while a hemispherical sensor such as a pyranometer is an uncollimated detector (Diner et al. 1999).
|Bidirectional Reflectance Distribution Function (BRDF)||Surface-leaving radiance divided by incident irradiance from a single direction|
|Bidirectional Reflectance Factor (BRF)||Surface-leaving radiance divided by radiance from a Lambertian reflector illuminated from a single direction|
|Hemispherical-Directional Reflectance Factor (HDRF)||Surface-leaving radiance divided by radiance from a Lamberian reflector illuminated under the same ambient conditions|
|Directional Hemispherical Reflectance (DHR)||Radiant exitance divided by irradiance under illumination from a single direction|
|Bihemispherical Reflectance (BHR)||Radiant exitance divided by irradiance under ambient illumination conditions|
The percentage of incident solar radiation reflected back by an object is called albedo. Surface objects with a high albedo reflect more solar energy and appear as bright objects in a visible/near-infrared image. Objects with a low albedo reflect only a small portion of incident solar radiation and appear as dark objects on a visible/near-infrared image. Figure 5 summarizes how variations of reflectance depend upon the degree of collimation (Hapke 1993).
Figure 5. Variations of Reflectance
AVHRR Channels 1 and 2 measure the upwelling radiance at the Top-of-Atmosphere (TOA) emanating from both the Earth surface and atmospheric scattering. TOA radiance is converted to a TOA BRF using the the exo-atmospheric solar irradiance, Earth-Sun distance, solar zenith angle, and spectral response functions of the AVHRR channels. The surface albedo is obtained from the TOA BRF after applying an atmospheric correction and a conversion from directional reflectance to hemispherical reflectance. Figure 6 shows a summary of the solar and satellite angles used in processing the AVHRR Polar Pathfinder products.
Figure 6. Summary of Solar and Satellite Angles Used in Processing AVHRR Polar Pathfinder Products
Channel 3A on the NOAA 16 AVHRR/3 instrument allows improved discrimination between snow and clouds by using the 1.6 µm wavelength. At 1.6 µm, snow has very low reflectance, while the reflectance of clouds remains high. Refer to Figure 7. Therefore, both cirrus and optically thick clouds can be directly classified and distinguished from snow at the 1.6 µm wavelength (Warren 1982).
Figure 7. Satellite Channel Wavelengths in Micrometers (µm), and Typical Reflectance Spectra for Snow and Clouds
All objects radiate energy according to their blackbody temperature. A blackbody is a hypothetical object that absorbs all incoming thermal energy, but with none of that energy reflected or transmitted. Since no object can ideally absorb 100 percent of incident energy, a blackbody serves as a comparative measure of thermal emission. As the temperature of an object increases, the total amount of the emitted energy also increases, and the wavelength of that energy becomes shorter, as Wien's displacement law describes. According to the Stefan-Boltzman law, objects with a higher temperature give off more thermal energy per unit area than objects with a lower temperature. Remote sensing in the thermal infrared spectral region (approximately 7 µm to 14 µm) involves measuring the radiance of objects. More specifically, thermal remote sensing measures the differences in the ability of objects to absorb shortwave energy and emit it back as longwave energy. Researchers are primarily interested in measuring the actual temperature of objects, rather than radiance. Radiance is simply a measure of the emitted energy of an object, while temperature is a measure of the kinetic (thermal) energy of an object. AVHRR channels 3-5 measure TOA brightness temperature. Refer to the NOAA Polar Orbiter Data User's Guide for details on how radiance values are converted to surface temperature, and the Derivation Techniques and Algorithms section of this document for algorithms used in the AVHRR Polar Pathfinder Twice-Daily 5 km EASE-Grid Composites.
The current series of NOAA Polar Orbiting Environmental Satellites (POES) has been operational since mid-1978. NOAA-7, -9, -11, -14, and -16 satellite data were used for the AVHRR Polar Pathfinder Twice-Daily 5 km EASE-Grid Composites. Refer to Table 14 for the dates of operation.
|NOAA-7||23 July 1981 - 31 December 1984|
|NOAA-9||1 January 1985 - 7 November 1988|
|NOAA-11||8 November 1988 - 31 December 1994|
|NOAA-14||1 January 1995 - 31 December 2000|
|NOAA-16||1 January 2001 - 30 June 2005|
The primary instruments aboard this third generation of satellites (TIROS-N and NOAA-6 through NOAA-16) are the AVHRR sensor and the TIROS Operational Vertical Sounder (TOVS). However, the AVHRR instrument was updated to Version AVHRR/3, which now has 6 channels. AVHRR/3 was first carried on NOAA-15 and launched in May 1998.
The ascending portion of the orbit crosses the equator at local time in the afternoon. Refer to Figure 8. The satellites are placed in orbit so that the equator crossing time is about 1400 local solar time. However, as the satellite remains in orbit, the equator crossing time shifts to later in the afternoon.
Figure 8. AVHRR Polar Pathfinder Equator Crossing Times
The AVHRR sensor was originally designed for use as an imaging radiometer for meteorological purposes, rather than for quantitative radiometric sensing (Cracknell 1997). However, as new applications evolved, quantitative radiometric data became necessary. Channels 1 and 2 were designed to provide direct quasi-linear conversion between the 10-bit digital numbers and reflectance. The thermal channels were designed to provide this conversion between the digital numbers and the temperature in degrees Celsius or kelvin. The primary reason for the introduction of the five-channel system was the need for atmospheric correction calculations in determining sea surface temperature (Cracknell 1997).
The AVHR/3 sensor on the NOAA-16 platform was designed for improved cloud detection over snow- and ice-covered surfaces.
The scan mirror collects earth observation data during a discrete part of the scan cycle. The scan mirror observes the scene below the spacecraft in a continuous line from horizon to horizon as it rotates. Energy from the scene is collected by a telescope and separated according to wavelength by beam splitters. Signals are amplified, filtered, and applied to the 10-bit analog/digital converter, which samples all five channels simultaneously. In Version 3, the NOAA-16 platform contains the AVHRR/3 instrument which has a dual Channel 3 for better cloud detection. Channel 3A collects data during the day at 1.6 microns, and Channel 3B collects data during the night at 3.7 microns. If the calibrated data has a value range below 1200 kelvin with a scaling factor of 10, the data is from Channel 3A. If the calibrated data has a value range of 2000 kelvin and above with a scaling factor of 10, the data is from Channel 3B. However, there are periods of time when Channel 3A is turned off. Thus, for information regarding the NOAA 16 AVHRR subsystem history, specifically the new Channels 3A and 3B, refer to the NOAA Satellite and Information Service: Office of Satellite Operations: NOAA 16 AVHRR Subsystem Summary Web page.
AVHRR and AVHRR/3 Channel Wavelengths are summarized in Table 15.
|0.58 µm to 0.68 µm (visible)|
|0.725 µm to 1.05 µm (reflected infrared)|
|3.55 µm to 3.92 µm (reflected/thermal infared)|
|1.58 -1.64 µm (reflected/thermal infared, collects data during the day)|
|3.55 -3.93 µm (reflected/thermal infared, collects data during the night)|
|10.3 µm to 11.3 µm (thermal infrared)|
|11.5 µm to 12.5 µm (thermal infrared)|
The 10-bit resolution digital data is processed to create a direct readout of High Resolution Picture Transmission (HRPT) data, Automatic Picture Transmission (APT) data, 4 km GAC data, and 1 km LAC data, to ground stations throughout the world (Cracknell 1997).
The AVHRR instrument scans in the across-track direction with a continuously rotating scan mirror, viewing a swath of over 100 degrees and up to 55 degrees off-nadir. Spatial resolution is approximately 1.1 km when the view is at nadir. Scanning to 55 degrees (68 degrees satellite zenith angle relative to the earth's surface) off nadir results in a ground resolution of over 2.4 km by 6.5 km at the maximum off-nadir position (Cracknell 1997).
The AVHRR/3 is an imaging system in which a small field of view (1.3 milliradians by 1.3 milliradians) is scanned across the earth from one horizon to the other by continuous 360 degree rotation of a flat scanning mirror. The orientation of the scan lines are perpendicular to the spacecraft orbit track and the speed of rotation of the scan mirror is selected so that adjacent scan lines are contiguous at the subsatellite (nadir) position. Complete strip maps of the earth from pole to pole are thus obtained as the spacecraft travels in orbit at an altitude of approximately 833 km (450 miles). The analog data output from the sensors is digitized on board the satellite at a rate of 39,936 samples per second per channel. Each sample step corresponds to an angle of scanner rotation of 0.95 milliradians. At this sampling rate, there are 1.362 samples per Instantanous Field of View (IFOV). A total of 2048 samples will be obtained per channel per Earth scan, which will span an angle of ±55.4 degrees from the nadir (subpoint view). All six spectral channels of the AVHRR/3 are registered so that they all measure energy from the same spot on the earth at the same time. All six channels are also calibrated so that the signal amplitude in each channel is a measure of the scene radiance. Although the AVHRR/3 has six channels, only five are transmitted to the ground at any one time. The radiometers are designed to operate within specification for a period of three years in orbit (Goodrum et al. 2000).
The first AVHRR sensor was designed and built by ITT Aerospace in 1976. Subsequent instruments were built by ITT Aerospace under contract with NASA, which procured the instruments on behalf of NOAA (Cracknell 1997).
AVHRR/3 was designed and built by ITT Industries' Aerospace/Communications Division (A/CD), and it was first carried on NOAA-15 and launched in May 1998.
When the AVHRR Polar Pathfinder program began, calibrations were based on the NOAA Polar Orbiter Data (POD) User's Guide (Kidwell 1995). Since then, at least four different publications have presented different methods of calibrating AVHRR data. Even with extensive pre-launch testing and calibrations, satellite sensors change over time, and improved methods are developed. In some cases, particularly for the visible channels, the sensor characteristics are not fully predictable, and the satellite must be in orbit before changes can be detected to make the proper corrections. However, the calibrations for this data set follows the guide lines in two publications: NOAA Polar Orbiter Data User's Guide: Section 3.3 Calibration of AVHRR Data was used for NOAA 7 through NOAA 14 satellite data, and NOAA KLM User's Guide: Section 7.1 AVHRR was used for the NOAA 16 satellite data.
The POD calibration method for Channels 1 (visible) and 2 (near-infrared) used pre-launch values. The primary use of these channels has traditionally been for vegetation studies over land. Investigations revealed that the two channels drifted from the initial launch conditions. A set of time-varying coefficients was subsequently developed to correct for the drifting sensors. In 1999, the calibration for NOAA-14 changed and new time-varying equations were recommended (Rao and Chen 1999). See the Derivation Techniques and Algorithms section of this document for more information.
At the start of the AVHRR Polar Pathfinder program, calibration of the thermal channels followed the guidelines in the POD. The methodology is as follows:
This method was optimized for a narrow range of AVHRR sea surface temperature products. The Walton method describes an effective method for correcting AVHRR thermal channels 3, 4, and 5 to accommodate the wide range of temperatures in the polar regions. The NOAA/NASA Land Pathfinder group also selected this method, and it is used for the AVHRR Polar Pathfinder 5km Data Set.
The Walton method applies a non-linear correction to the radiance, which is then converted to brightness temperature using a quadratic function with coefficients derived from pre-flight calibrations. The result, while not optimized for the narrower range needed for sea surface temperature measurements, appears to be an improvement for polar regions.
The Walton calibration method was implemented in March 1999 for thermal channels from all NOAA AVHRR satellites. Correction tables were generated for previously processed data to closely match the new calibration techniques. These corrections appear to be compatible to within 0.1 degrees (Walton et al. 1998).
Refer to Figure 9 for a summary of the steps used in processing the AVHRR Level 1B GAC data, which were obtained from a variety of sources. Data from NCAR were used for initial development and testing of processing and algorithms. The GSFC DAAC supplied several years worth of GAC data on 8 mm tapes. NSIDC copied GAC data from optical platters, loaned from JPL. A Digital Equipment Corporation (DEC) computer and VAX/VMS operating system were used for the copying. Finally, data from NOAA SAA were used to complete the GAC data set.
Figure 9. AVHRR Polar Pathfinder 5 km Processing
Clear sky surface skin temperature, albedo, and cloud masking are all derived from the Cloud and Surface Parameter Retrieval (CASPR) system.
The general methodology in Steps 2 through 4 was used by Csiszar and Gutman (1999) for global land studies. The albedo provided here is a directional-hemispherical, apparent albedo, where apparent albedo is measured by up- and down-looking radiometers in the field.
Step 1: Normalize Channels 1 and 2 with respect to the solar zenith angle:
P1,toa= C1 / 100 * cos(zen)
P2,toa= C2 / 100 * cos(zen)
C1 = percent reflectance for channel 1
C2 = percent reflectance for channel 2
zen = solar zenith angle
p1,toa = channel 1 reflectance
p2,toa = channel 2 reflectance
Step 2: Convert the narrowband reflectances in Channels 1 and 2 to a broadband reflectance. The narrow-to-broadband conversion takes the form:
ptoa = a + bp1,toa + cp2,toa
p1,toa = channel 1 reflectance
p2,toa = channel 2 reflectance
ptoa = broadband TOA reflectance
a, b, c = regression coefficients (Refer to Table 16)
To develop the regression relationship, the radiative transfer model Streamer is used to simulate the TOA reflectances over a broad range of viewing and illumination angles, atmospheric conditions, and surface types and albedos (Key and Schweiger 1998). Separate sets of coefficients are determined for different surface types. Refer to the Atmospheric and Anisotropic Reflectance Correction Source Code Document for details.
Step 3: Correct for the dependence of the sun-satellite-surface geometry on reflectance. This is done with data presented in Suttles et al. (1988) who used the Earth Radiation Budget Experiment (ERBE) and Geostationary Operational Environmental Satellite (GOES) data to determine TOA Anisotropic Reflectance Factors (ARFs) for the broad shortwave band over various surfaces. To convert the directional reflectance to albedo, the ERBE/GOES ARFs are used:
atoa = ptoa / f
ptoa = reflectance observed at the sensor simulated by Streamer in Step 1
f = anisotropic reflectance factor atoa = TOA albedo. The f factor is derived from a tri-linear interpolation of two tables: rmatrx and albmn.
rmatrx: Anisotropic reflectance values based on ERBE and GOES. Dimension is (3,10,7,8) with three scene types, ten solar zenith bins, seven viewing zenith bins, and eight relative azimuth bins.
albmn: Normalizing factors for albmn. Dimension is (3,10) with three scene types and ten solar zenith bins.
Preliminary results show that under certain circumstances, the reflectance of mixed pixels of open ocean and ice could have incorrect values. A Channel 1 value less than 0.0 indicates open ocean, and a value greater than 0.3 is pure ice. Values between these limits indicate pixels with mixed surface types. The final value is a weighted average of the two. Algorithms are provided in the Atmospheric and Anisotropic Reflectance Correction Source Code Document.
Step 4: Finally, the apparent clear sky surface broadband albedo is estimated with a regression relationship of the form:
surface_albedo = (atoa - a) / b
a and b are a function of water vapor, aerosol amount, and solar zenith angle. The coefficients were determined with Streamer for a variety of surface and atmospheric conditions.
For open ocean, a simpler approach is taken:
surface_albedo = a + b*atoa + c*cos(zen) + d*pw + e*aertau
a, b, c, d, e = coefficients determined empirically using modeled albedos
pw = precipitable water
zen = solar zenith angle
aertau = atmospheric aerosols
Details are provided in the Atmospheric and Anisotropic Reflectance Correction Source Code Document.
For both cases, the aerosol optical depth is set to 0.06. Also, for both cases, the water vapor is estimated from Channels 4 and 5 using the formula:
PW = exp[b0 + b1(T4-T5) + b2(T5)] cos(theta)
pw = precipitable water
theta = scan angle
b0, b1, b2 = coefficients determined over a range of surface temperatures and water vapor amounts using AVHRR radiances modeled with LOWTRAN-7. Arctic rawinsonde data were employed.
b0 = -10.4974
b1 = 0.751008
b2 = 0.0453005
Details are provided in the Retrieval of Precipitable Water Source Code Document. The calculated surface albedo is an apparent albedo, one that is measured with radiometers and which varies with changes in atmospheric conditions, particularly for bright surfaces.
|20-29||Predominately first-year ice|
|30-39||Predominately multiyear ice|
Ranges for first-year and multiyear ice types indicate the predominant ice type and the total ice concentration in tens of percent. For example, a value of 24 means that first-year ice predominates and that the total ice concentration is between 41 and 50 percent.
The above tests are done in a clear-conservative mode, meaning that the threshold is set so that values are more likely to be clear. Next, the following three steps are done:
The only distinction between surface types is land and ocean. Land may be snow-free or snow-covered. Ocean can be open water or sea ice. Additionally, the nighttime procedure does not incorporate any surface type distinction. Comparisons with SHEBA surface observations of cloud amount (synoptic observations every three hours) yield a bias of 0.1 and a root mean square error (RMSE) of 0.3.
Figure 6 summarizes the generation of 5 km AVHRR Polar Pathfinder products.
The AVHRR Polar Pathfinder Twice-daily 5 km EASE-Grid Composites consist of several versions. Refer to Table 18.
|Version 0||No data of this version is available. This version is only available internally and was processed using the older calibration methods.|
|Version 1||Calibration corrections were applied to Version 0 data Channels 4 and 5 to within 0.1 kelvin.|
|Version 2||Data were processed using the most currently accepted calibration techniques.|
|Version 3||Fixes NOAA-14 visible channel calibration problem. All future processing, including the 2001 - 2005 update, will be at this level.|
Diner, D. J., J. V. Martonchik, C. Borel, S. A. W. Gerstl, H. R. Gordon, Y. Knyazikhin, R. Myneni, B. Pinty, M. M. Verstraete. 1999. MISR Level 2 Surface Retrieval Algorithm Theoretical Basis. Jet Propulsion Laboratory.
Gustafson, G. B. et al. 1994. Support of Environmental Requirements for Cloud Analysis and Archive (SERCAA), Phillips Laboratory, Hanscom Air Force Base, Scientific Report No. 2, PL-TR-94-2114, 100 pp.
Rao, C. R. N. and J. Chen. 1994. Post-launch Calibration of the Visible and Near-infrared Channels of the Advanced Very High Resolution Radiometer on NOAA-7, -9, and -11 Spacecraft. NOAA Technical Report NESDIS 78:22 .
Rao, C. R. N. and J. Chen. 1999. Revised post-launch calibration of channels 1 and 2 of the Advanced Very High Resolution Radiometer on board the NOAA-14 spacecraft. http://noaasis.noaa.gov/NOAASIS/ml/aboutn14vis.html.
Schweiger, A., Chuck Fowler, J. Key, J. Maslanik, J. Francis, Richard Armstrong, Mary Joe Brodzik, Ted Scambos, Terry Haran, M. Ortmeyer, S. Khalsa, D. Rothrock, and Ron Weaver. 1999. P-Cube: A Multisensor Data Set for Polar Climate Research. Proceedings on the 5th Conference on Polar Meteorology and Oceanography, American Meteorological Society, Dallas, TX, 15-20 Jan., 136-141.
Schweiger, A. J. and J. R. Key. 1992. Arctic Cloudiness: Comparison of ISCCP-C2 and Nimbus-7 Satellite-derived Cloud Products with a Surface-based Cloud Climatology. Journal of Climate 5(12):1514-1527.
Stowe, L.L., E.P. McClain, R. Carey, P. Pellegrino, and G.G. Gutman. 1991. Global Distribution of Cloud Cover Derived from NOAA/AVHRR Operational Satellite Data. Advances in Space Research 11(3): 51- 54.
Stroeve, Julienne C., J. E. Box, Chuck Fowler, Terry Haran, and Jeffrey Key. March 2001. Intercomparison Between in Situ and AVHRR Polar Pathfinder-derived Surface Albedo Over Greenland. Remote Sensing of the Environment 75(3):360-374.
Suttles, J. T., R. N. Green, P. Minnis, G .L. Smith, W. F. Staylor, B. A. Wielicki, I. J. Walker, D. F. Young, V. R. Taylor, and L. L. Stowe. 1988. Angular Radiation Models for Earth-Atmosphere System. Shortwave Radiation, NASA Reference Publication 1(1184):144.
Walton, C. C., J. T. Sullivan, C. R. N. Rao, and M. P. Weinreb. 1998. Corrections for Detector Nonlinearities and Calibration Inconsistencies of the Infrared Channels of the Advanced Very High Resolution Radiometer. Journal of Geophysical Research 103(C2):3323-3337.
The following acronyms and abbreviations are used in this document.
|APP||AVHRR Polar Pathfinder|
|APT||Automatic Picture Transmission|
|ARF||Anisotropic Reflectance Factor|
|ASCII||American Standard Code for Information Interchange|
|AVHRR||Advanced Very High Resolution Radiometer|
|AWS||Automatic Weather Station|
|BRDF||Bidirectional Reflectance Distribution Function|
|BRF||Bidirectional Reflectance Factor|
|CASPR||Cloud and Surface Parameter Retrieval|
|CCAR||Colorado Center for Astrodynamics Research|
|CIRES||Cooperative Institute for Research in Environmental Sciences|
|CLAVR||Clouds from AVHRR|
|DAAC||Distributed Active Archive Center|
|DEC||Digital Equipment Corporation|
|DHR||Directional Hemispherical Reflectance|
|DN||Data (or Digital) Number|
|EASE-Grid||Equal Area Scalable Earth-Grid|
|EOS||Earth Observing System|
|ERBE||Earth Radiation Budget Experiment|
|FTP||file transfer protocol|
|GAC||Global Area Coverage|
|GISMO||Graphical Interface for Subsetting, Mapping, and Ordering|
|GOES||Geostationary Operational Environmental Satellite|
|GSFC||Goddard Space Flight Center|
|HDRF||Hemispherical-Directional Reflectance Factor|
|HRPT||High Resolution Picture Transmission|
|IABP||International Arctic Buoy Programme|
|IFOV||Instantaneous Field of View|
|JPL||Jet Propulsion Laboratory|
|LAC||Local Area Coverage|
|MCC||Maximum Cross Correlation|
|NASA||National Aeronautics and Space Administration|
|NAVSPASUR||Naval Space Surveillance Center|
|NCAR||National Center for Atmospheric Research|
|NSIDC||National Snow and Data Center|
|NOAA||National Oceanic and Atmospheric Administration|
|POD||Polar Orbiter Data|
|POES||Polar Orbiting Environmental Satellites|
|RMS||Root Mean Square|
|RMSE||Root Mean Square Error|
|SAA||Satellite Active Archive|
|SERCAA||Support of Environmental Requirements for Cloud Analysis and Archives|
|SHEBA||Surface Heat Balance of the Arctic|
|SMMR||Scanning Multichannel Microwave Radiometer|
|SSM/I||Special Sensor Microwave/Imager|
|TOA||Top of Atmosphere|
|TIROS||Television and Infrared Observation Satellite|
|TOVS||TIROS Operational Vertical Sounder|
|UTC||Universal Coordinated Time|
May 2012 - added note about data not being available