BOREAS RSS-10 TOMS Circumpolar One-Degree PAR Images Summary The BOREAS RSS-10 team investigated the magnitude of daily, seasonal, and yearly variations of PAR from ground and satellite observations. This data set contains satellite estimates of surface-incident photosynthetically active radiation (PAR, 400-700 nm, MJ m-2) at 1 degree spatial resolution. The spatial coverage is circumpolar from latitudes of 41 to 66 degrees N latitude. The temporal coverage is from May through September for years 1979 through 1989. Eleven-year statistics are also provided: mean, standard deviation, and coefficient of variation for 1979-1989. The PAR estimates were derived from the global gridded ultraviolet reflectivity data product (average of 360, 380 nm) from the Nimbus-7 Total Ozone Mapping Spectrometer (TOMS). Image mask data are provided for identifying the boreal forest zone, and ocean/land and snow/ice covered areas. The data are available as binary image format data files. Table of Contents * Data Set/Model Overview * Investigator(s) * Theory of Measurements * Equipment * Data Acquisition Methods * Observations * Data Description * Data Organization * Data Manipulations * Errors * Notes * Application of the Data Set/Model * Future Modifications and Plans * Software * Data Access * Output Products and Availability * References * Glossary of Terms * List of Acronyms * Document Information 1. Data Set Overview 1.1 Data Set Identification BOREAS RSS-10 TOMS Circumpolar One-Degree PAR Images 1.2 Data Set Introduction This data set contains circumpolar satellite-based estimates of monthly total photosynthetically active radiation (PAR, 400-700 nm) incident at the Earth's surface for latitudes between 41° N and 66° N. The spatial resolution is 1 degree. The estimation procedure employed gridded ultraviolet (UV) reflectivity data (average of 360, 380 nm) from the Nimbus-7 TOMS to account for the effects of clouds on a predicted clear-sky PAR irradiance. The TOMS gridded reflectivity data were produced by the NASA Ozone Processing Team (OPT) as part of the ozone monitoring procedure. PAR estimates for the months of May through September for years 1979 through 1989 are provided. Measurement units are megajoules per square meter (MJ m-2). Image data masks are provided for identifying data values associated with ocean or land areas, and the boreal forest zone. Additional data masks for snow and ice covered surfaces are provided to aid in identifying locations where the accuracy of the PAR estimates may be reduced. PAR estimates represent individual months in the active growing season (May through September), and 3-month and 5-month time periods (June-August, and May- September, respectively). Corresponding 11-year statistics are included (mean, standard deviation, and coefficient of variation for 1979-1989). 1.3 Objective/Purpose The purpose of the data set is to provide information on the spatial distribution and temporal dynamics of PAR within the circumpolar boreal forest zone. The data may be used for calculating vegetation-absorbed PAR, modeling primary production and associated processes, and in scaling those processes from the local scale to the biome scale. 1.4 Summary of Parameters and Variables Photosynthetically active radiation (PAR, 400-700 nm) incident at the Earth's surface during active growing season months (May through September), and corresponding 11-year statistics (mean, standard deviation, coefficient of variation). 1.5 Discussion Photosynthetically active radiation (PAR, 400-700 nm) provides the energy that supports primary production, and is a major determinant of the exchange of carbon dioxide and water between vegetation and the atmosphere. A full assessment of boreal ecosystem processes requires data and information on the amount, spatial distribution, and seasonal and interannual variability PAR in the boreal forest biome. The satellite remote sensing method introduced by Eck and Dye (1991) has proven effective for estimating surface-incident PAR on a global scale (Dye, 1992; Dye and Shibasaki, 1995). Early successes in applying the method to ultraviolet reflectivity data from Nimbus-7 TOMS led to elements of the BOREAS RSS-10 project aimed at refining the original algorithm and performing validations at the BOREAS sites. An additional objective for RSS-10 was the creation of a retrospective time-series PAR data set for the boreal forest zone from the Nimbus-7 TOMS data archive. The data set described here fulfills that objective. The failure of Nimbus-7 TOMS in 1993 and subsequent delays in the launch of a follow-on instrument hindered pursuit of the original objectives for algorithm refinement and validation because suitable UV reflectivity data concurrent with the BOREAS field experiment were not available. Consequently, the present data set contains PAR estimates from our original algorithm applied to Version 6 reflectivity data from Nimbus-7 TOMS (Eck and Dye, 1991, Dye, 1992; Dye and Shibasaki, 1995). Although Nimbus-7 TOMS data are available through early 1993, the instrument exhibited a significant calibration drift during its latter years from 1990 to 1993. This calibration drift which had not been fully corrected in the Version 6 reflectivity data set. The years 1990-1993 were therefore excluded from the PAR data set. As this data set is submitted, we have proposed a research plan for an improved TOMS PAR data set that combines an enhanced PAR algorithm with corrected Version 7 TOMS reflectivity data. 1.6 Related Data Sets BOREAS RSS-14 Level-3 Gridded Radiometer and Satellite Radiation Images AVHRR Land Pathfinder Climate Data Set (Normalized Difference Vegetation Index, 10-day composites, 1 degree resolution). (http://daac.gsfc.nasa.gov/CAMPAIGN_DOCS/LAND_BIO/GLBDST_main.html) 2. Investigator(s) 2.1 Investigator(s) Name and Title Brent Holben, Biospheric Sciences Branch, NASA GSFC Thomas Eck, Raytheon STX, Biospheric Sciences Branch, NASA GSFC Dennis Dye, Asst. Professor, Dept. of Geography & Center for Remote Sensing, Boston Univ. P.K. Bhartia, NASA GSFC 2.2 Title of Investigation Satellite Estimation of PAR and UV-B Irradiances and Long Term Estimates of Trends of UV-B from Ozone Depletion and Cloud Variability at the BOREAS Sites 2.3 Contact Information Contact 1 ------------- Dennis G. Dye Asst. Professor Dept. of Geography and Center for Remote Sensing Boston University Boston, MA Telephone: (617)353-4807 Fax: (617)353-8311 Email: ddye@bu.edu Contact 2 ---------- Brent Holben Biospheric Sciences Branch NASA Goddard Space Flight Center Greenbelt, Maryland 301-286-2975 301-286-0239 (fax) Brent.Holben@gsfc.nasa.gov Contact 3 ------------- Jaime Nickeson Raytheon STX Corporation NASA Goddard Space Flight Center Greenbelt, Maryland 301-286-3373 301-286-0239 (fax) Jaime.Nickeson@gsfc.nasa.gov 3. Theory of Measurements Modeling PAR Surface irradiance in the PAR band (400-700 nm) was estimated by accounting for the reduction in potential (clear sky) irradiance due to the backscatter of PAR to space by clouds and aerosols. The equation is: Ip = Ip*[1-(r-.05)/.90] where Ip is PAR irradiance (MJ m-2 day-1). Ip* is the potential (clear sky) PAR irradiance, and r is the TOMS-observed reflectivity averaged for the 360 nm and 380 nm channels on Nimbus-7 TOMS (henceforth referred to as simply 370 nm). The constants account for the variable contribution of the Earth surface background to the observed value of r as r varies between 0.05 (reflectivity for cloudless sky conditions) and 0.50 (reflectivity for 100% cloud-filled pixel). If the UV reflectivity of the Earth's surface was zero, the expression (1-r) could be used to adjust Ip for all measurements of r. Since this is not the case we must account for the contribution of the background reflectance. We adopted a constant reflectivity threshold of 0.05 for the TOMS measured reflectivity for a cloudless pixel. This 0.05 value is the median of the 0.02-0.08 reflectance range exhibited by the majority of the Earth's surfaces. As cloud reflectance increases, it is necessary to account for a decrease in the earth surface contribution to total scene reflectance. We assumed a reflectivity threshold of 0.5 for the underlying surface contribution to total pixel reflectance, which is approximately equal to the mean UV reflectance for a 100% cloud-filled field of view. For reflectivities greater than 0.50, the contribution of surface background reflectance to the measured total reflectance is assumed to be zero or negligible, and Ip is multiplied by (1-r) instead of [1-(r-0.05/0.90)]. We used the model of Goldberg and Klein (1980) to predict daily Ip (MJ m-2 day-1). Additional details are presented in Sections 9.1.1 and 9.2 and by Eck and Dye (1991). The Version 6 Ultraviolet Reflectivity Measurement (from McPeters et al., 1996). The reflectivity values account for an "effective" reflectivity, which is the reflectivity of a Lambertian reflective surface that would explain the observed backscattered radiance. The algorithm used for the Version 6 reflectivity is based on the treatment of Dave (1978), who represented the contribution of clouds and aerosols to the backscattered intensity by assuming that radiation is reflected from a particular pressure level called the "scene pressure" with a Lambert-equivalent "scene reflectivity" R. Version 6 reflectivity data incorporated a correction for an observed downward drift in the TOMS ozone values relative to those measured by the ground-based Dobson network. The drift was the result of an error in the correction for diffuser plate degradation. A correction referred to as the Pair Justification Method (PJM) was applied to account for the differential sensitivity to instrument degradation between wavelengths that should measure the same ozone value. Details on the Version 6 data set are contained in the “Nimbus-7 Total Ozone Mapping Spectrometer Data Product User’s Guide” (McPeters et al., 1993, 1996). 4. Equipment 4.1 Sensor/Instrument Description The Nimbus-7 TOMS measured solar irradiance and the radiance backscattered by the Earth's atmosphere in six 1-nm bands in the ultraviolet, located at approximately 380, 360, 340, 331, 317, and 312 nm. The sensor used a single monochromator and scanning mirror to sample the backscattered solar ultraviolet radiation at 35 sample points at 3-degree intervals along a line perpendicular to the orbital plane. In normal operation, the scanner measured 35 scenes (pixels), one for each scanner view angle, stepping from right to left. It would then quickly return to the first position, not making measurements on the retrace. Eight seconds after the start of the previous scan, another would begin. (from McPeters et al., 1996). A complete technical description of the TOMS instrument and its initial calibration are provided by Heath et al. (1975) 4.1.1 Collection Environment Not applicable. 4.1.2 Source/Platform The data source was the Nimbus-7 TOMS Gridded Reflectivity Data Product (monthly averages) produced by the NASA Ozone Processing Team (OPT). 4.1.3 Source/Platform Mission Objectives The Nimbus-7 platform carried sensors which supported a number of experiments related to pollution control, oceanography, and meteorology: (see also http://jwocky.gsfc.nasa.gov/data_access.html#n7m3 and McPeters et al. (1996)). (1) To observe gases and particulates in the atmosphere for the purpose of determining the feasibility of mapping sources, sinks, and dispersion mechanisms of atmospheric pollutants (2) To observe ocean color, temperature, and ice conditions, particularly in coastal zones, with sufficient spatial and spectral resolution to determine the feasibility of applications such as: (a) detecting pollutants in the upper level of the oceans (b) determining the nature of materials suspended in the water (c) to continue to make baseline measurements of variations in longwave radiation fluxes outside the atmosphere and of atmospheric constituents for the purpose of determining the effect of these variations on the Earth's climate. Our application of the averaged 360 and 380 nm reflectivity data from Nimbus-7 TOMS to estimate surface-incident PAR was not part of the original TOMS mission objectives. Recognition of the utility of the TOMS reflectivity data for purposes other than ozone monitoring has led to additional applications. In addition to PAR monitoring, TOMS data are now being employed in global monitoring of UV-B surface irradiance and atmospheric aerosol distributions (Herman et al., 1996, 1997). 4.1.4 Key Variables Monthly total surface irradiance in the PAR band (400-700 nm). 4.1.5 Principles of Operation Not applicable. 4.1.6 Sensor/Instrument Measurement Geometry The Nimbus-7 satellite was maintained in a near polar, sun-synchronous orbit at an altitude of 955 km. Equatorial crossings are local noon for ascending and local midnight for descending nodes. Spacecraft inclination was 99.1 degrees, with a maximum poleward latitude of 80.77 degrees. The orbital period was 104.16 minutes. Equator crossings on consecutive orbits are separated by 26.1 degrees longitude. TOMS scanned in 3-degree steps to 51 degrees on each side of the subsatellite point, in a direction perpendicular to the orbital plane. Consecutive cross-scans overlapped, providing contiguous spatial coverage, and full global coverage on a daily basis. (NASA, 1978). 4.1.7 Manufacturer of Sensor/Instrument The TOMS instrument was built by Beckman Instruments, Inc., of Anaheim, California, USA. 4.2 Calibration Portions of the following section on TOMS calibration were quoted from McPeters et al. (1996). An onboard wavelength monitor tracked changes in the wavelength scale between calibration and launch. Radiometric calibration was performed using the ratio of backscattered radiance to incident solar irradiance, I(t)/F(t). An aluminum diffuser plate was used to reflect sunlight into the instrument to measure solar irradiance. The diffuser plate was normally deployed once per week for TOMS solar irradiance measurements. Version 6 reflectivity data included corrections for time-dependent degradation of the diffuser plate (Herman et al., 1991). Errors associated with sea-glint contamination and spacecraft attitude were also corrected in Version 6. Details on the wavelength and radiometric calibration for Nimbus-7 TOMS is given by McPeters et al. (1993, 1996), and Herman et al. (1991). 4.2.1 Specifications Refer to Heath et al. (1975). 4.2.1.1 Tolerance Refer to Heath et al. (1975). 4.2.2 Frequency of Calibration The diffuser plate was normally deployed once per week for the TOMS solar irradiance measurements used in radiometric calibration (McPeters et al., 1993). The Nimbus-7 TOMS data archive was reprocessed in Version 6 to account for effects of diffuser plate degradation on the measured irradiance (Herman et al., 1991). (Note: Subsequent analysis revealed remnant calibration related errors. See section 10.1.1) 5. Data Acquisition Methods In normal operation, the TOMS scanner measured 35 scenes (pixels), one for each scanner view angle, stepping from right to left. It then quickly returned to the first position, not making measurements on the retrace. Eight seconds after the start of the previous scan, another would begin. (from McPeters et al., 1996). 6. Observations 6.1 Data Notes None given. 6.2 Field Notes Not applicable. 7. Data Description 7.1 Spatial Characteristics 7.1.1 Spatial Coverage The data array with dimensions of 25 rows by 360 columns covers the circumpolar region bounded by 41 and 66 degrees north latitude. The geographic coordinates of the upper-left and lower-right grid cells are indicated in the table below. The North American Datum 1983 (NAD83) coordinates refer to the center point of the grid cell. grid cell position coordinates (decimal degrees) ------------------ ----------------------------- Northwest corner 179.5 W, 65.5 N Southeast corner 179.5 E, 41.5 N 7.1.2 Spatial Coverage Map The spatial coverage of the data set corresponds to the non-stipled areas in the two northern hemisphere maps shown below . The top map has the same Plate Carree projection as the PAR data grid. The bottom map depicts the same region with a Lambert equal area projection centered on the north pole. 7.1.3 Spatial Resolution The nominal spatial resolution is 1 degree x 1 degree. This resolution was produced by resampling PAR estimates computed at 1 degree x 1.25 degree (latitude x longitude), which is the resolution of the monthly gridded reflectivity data product from the NASA Ozone Processing Team. The resampling was performed by computing the spatially weighted mean of the 1 x 1.25 degree PAR values occurring within each 1 x 1 degree cell in the target grid. 7.1.4 Projection The data grid is in a Plate Carree (equal angle) projection. 7.1.5 Grid Description Each pixel is a 1 x 1 degree cell of latitude, longitude. 7.2 Temporal Characteristics 7.2.1 Temporal Coverage The PAR data correspond to discrete calendar months, and account for differences in the number of days in each month with adjustments for leap years. For example, (monthly total PAR) = (daily total PAR) x (number of days in the month). The data set covers the months of May, June, July, August, and September for years 1979 to 1989. 7.2.2 Temporal Coverage Map Not available. 7.2.3 Temporal Resolution The base PAR data set has a temporal resolution of 1 month. This is equal to the temporal resolution of the gridded reflectivity data employed in the estimation procedure (monthly averages of daily reflectivities). Data for the 3- month (Jun/Jul/Aug) and 5-month (May/Jun/Jul/Aug/Sep) PAR sums are also provided. 7.3 Data Characteristics 7.3.1 Parameter/Variable The types of files provided in the data product are: parameter data type ----------- ---------- par1m 2-byte par3m 2-byte par5m 2-byte par1mav 2-byte par3mav 2-byte par5mav 2-byte par1msd 2-byte par3msd 2-byte par5msd 2-byte par1mcv 2-byte par3mcv 2-byte par5mcv 2-byte sm1m 1-byte sm1m11y 1-byte sm3m11y 1-byte sm5m11y 1-byte veg2mask 1-byte veg3mask 1-byte oceanmask 1-byte Equations for scaling from 2-byte integers (int) to floating point numbers (val) can be found in section 9.1. 7.3.2 Variable Description/Definition The following are descriptions of the file types provided: Parameter Description --------- ---------------- par1m Monthly total PAR (irradiance) par3m Total PAR for June,July,Aug. par5m Total PAR May,Jun,Jul,Aug.,Sep par1mav 11-yr. mean of par_1m par3mav 11-yr. mean of par_3m par5mav 11-yr. mean of par_5m par1msd 11-yr. std. dev. of par_1m par3msd 11-yr. std. dev. of par_3m par5msd 11-yr. std. dev. of par_5m par1mcv 11-yr. coeff. of var. of par_1m par3mcv 11-yr. coeff. of var. of par_3m par5mcv 11-yr. coeff. of var. of par_5m sm1m Monthly snow/ice mask. Data values indicate number of weeks in month with snow or ice in grid cell. sm1m11y Monthly snow/ice mask, 1979-89. Masked if snow/ice indicated for given month in one or more years. sm3m11y 3-month snow/ice mask, 1979-89. Masked if snow/ice indicated for one or more of the 3 months in one or more years. sm5m11y 5-month snow/ice mask, 1979-89. Masked if snow/ice indicated for one or more of the 5 months in one or more years. veg2mask Vegetation mask, Class 2 coniferous evergreen forest and woodland veg3mask Vegetation mask, Class 3 high latitude deciduous forest and woodland oceanmask Ocean/land mask 7.3.3 Unit of Measurement The following describe the units for the various file types: Parameter Units --------- ---------- par1m MJ/m2 par3m MJ/m2 par5m MJ/m2 par1mav MJ/m2 par3mav MJ/m2 par5mav MJ/m2 par1msd MJ/m2 par3msd MJ/m2 par5msd MJ/m2 par1mcv unitless par3mcv unitless par5mcv unitless sm1m weeks sm1m11y unitless sm3m11y unitless sm5m11y unitless veg2mask unitless veg3mask unitless oceanmask unitless 7.3.4 Data Source The following describe the source of the data file values: Parameter Source --------- ---------- par1m TOMS par3m TOMS par5m TOMS par1mav TOMS par3mav TOMS par5mav TOMS par1msd TOMS par3msd TOMS par5msd TOMS par1mcv TOMS par3mcv TOMS par5mcv TOMS sm1m Northern Hemisphere Weekly Snow Cover and Sea Ice Extent EOSDIS Distributed Active Archive Center, University of Colorado National Snow and Ice Data Center, 1978-1995 sm1m11y same as above sm3m11y same as above sm5m11y same as above veg2mask 1 degree global landcover map of Defries & Townshend (1994) Class 2 = coniferous evergreen forest and woodland. veg3mask 1 degree global landcover map of Defries & Townshend (1994) Class 3 = high latitude deciduous forest and woodland. oceanmask Ocean mask based on identification of non-land grid cells in 1 degree global landcover map of Defries & Townshend (1994) 7.3.5 Data Range The following are the range of values that can be expected after applying the equations given in Section 9.1: Parameter Range of Values --------- ------------------- par1m -1.0 to variable par3m -1.0 to variable par5m -1.0 to variable par1mav -1.0 to variable par3mav -1.0 to variable par5mav -1.0 to variable par1msd -1.0 to variable par3msd -1.0 to variable par5msd -1.0 to variable par1mcv -1.0 to 1.000 par3mcv -1.0 to 1.000 par5mcv -1.0 to 1.000 sm1m 0 to 5 sm1m11y 0 or 1 sm3m11y 0 or 1 sm5m11y 0 or 1 veg2mask 0 or 1 veg3mask 0 or 1 oceanmask 0 or 1 7.4 Sample Data Record Not applicable to image data. 8. Data Organization 8.1 Data Granularity The smallest orderable unit is the entire 11-year data set of 163 files. 8.2 Data Format(s) 8.2.1 Uncompressed Data Files All data files are binary encoded, stored as either 1 or 2 byte unsigned integers (integer*1 or integer*2). The 2-byte data have IEEE byte ordering. Variables originally computed as floating point numbers were scaled to 2-byte unsigned integers. Equations for reverting to floating point numbers are given in Section 9.1 The data set includes a total of 163 discrete files. Each data file is a binary image containing 360 samples in each of 25 lines. The data storage type for each variable is indicated in the table in Section 7.3.1. All the file type names that begin with “par” are two-byte integer images (files 1-99). The remainder of the files (files 100-163) are single-byte images. The files were each written in a single record, files 1 to 99 have a blocksize of 18,000 bytes 18,000 = 360 * 2 * 25), files 100-163 have a blocksize of 9,000. The 2-byte integer data must be scaled to floating point numbers, using the equations provided in Section 9.1 The list of individual files are given below. The order follows the listed variables in section 7.3, which gives the root names of the files. The root of the file name is followed by the last two digits of the year and/or the number corresponding to the month, for each variable set, if applicable. file 1: par1m7905.bin file 2: par1m7906.bin file 3: par1m7907.bin file 4: par1m7908.bin file 5: par1m7909.bin file 6: par1m8005.bin file 7: par1m8006.bin file 8: par1m8007.bin file 9: par1m8008.bin file 10: par1m8009.bin file 11: par1m8105.bin file 12: par1m8106.bin file 13: par1m8107.bin file 14: par1m8108.bin file 15: par1m8109.bin file 16: par1m8205.bin file 17: par1m8206.bin file 18: par1m8207.bin file 19: par1m8208.bin file 20: par1m8209.bin file 21: par1m8305.bin file 22: par1m8306.bin file 23: par1m8307.bin file 24: par1m8308.bin file 25: par1m8309.bin file 26: par1m8405.bin file 27: par1m8406.bin file 28: par1m8407.bin file 29: par1m8408.bin file 30: par1m8409.bin file 31: par1m8505.bin file 32: par1m8506.bin file 33: par1m8507.bin file 34: par1m8508.bin file 35: par1m8509.bin file 36: par1m8605.bin file 37: par1m8606.bin file 38: par1m8607.bin file 39: par1m8608.bin file 40: par1m8609.bin file 41: par1m8705.bin file 42: par1m8706.bin file 43: par1m8707.bin file 44: par1m8708.bin file 45: par1m8709.bin file 46: par1m8805.bin file 47: par1m8806.bin file 48: par1m8807.bin file 49: par1m8808.bin file 50: par1m8809.bin file 51: par1m8905.bin file 52: par1m8906.bin file 53: par1m8907.bin file 54: par1m8908.bin file 55: par1m8909.bin file 56: par3m79.bin file 57: par3m80.bin file 58: par3m81.bin file 59: par3m82.bin file 60: par3m83.bin file 61: par3m84.bin file 62: par3m85.bin file 63: par3m86.bin file 64: par3m87.bin file 65: par3m88.bin file 66: par3m89.bin file 67: par5m79.bin file 68: par5m80.bin file 69: par5m81.bin file 70: par5m82.bin file 71: par5m83.bin file 72: par5m84.bin file 73: par5m85.bin file 74: par5m86.bin file 75: par5m87.bin file 76: par5m88.bin file 77: par5m89.bin file 78: par1mav05.bin file 79: par1mav06.bin file 80: par1mav07.bin file 81: par1mav08.bin file 82: par1mav09.bin file 83: par3mav.bin file 84: par5mav.bin file 85: par1msd05.bin file 86: par1msd06.bin file 87: par1msd07.bin file 88: par1msd08.bin file 89: par1msd09.bin file 90: par3msd.bin file 91: par5msd.bin file 92: par1mcv05.bin file 93: par1mcv06.bin file 94: par1mcv07.bin file 95: par1mcv08.bin file 96: par1mcv09.bin file 97: par3mcv.bin file 98: par5mcv.bin file 99: sm1m7905.bin file 100:sm1m7906.bin file 101:sm1m7907.bin file 102:sm1m7908.bin file 103:sm1m7909.bin file 104:sm1m8005.bin file 105:sm1m8006.bin file 106:sm1m8007.bin file 107:sm1m8008.bin file 108:sm1m8009.bin file 109:sm1m8105.bin file 110:sm1m8106.bin file 111:sm1m8107.bin file 112:sm1m8108.bin file 113:sm1m8109.bin file 114:sm1m8205.bin file 115:sm1m8206.bin file 116:sm1m8207.bin file 117:sm1m8208.bin file 118:sm1m8209.bin file 119:sm1m8305.bin file 120:sm1m8306.bin file 121:sm1m8307.bin file 122:sm1m8308.bin file 123:sm1m8309.bin file 124:sm1m8405.bin file 125:sm1m8406.bin file 126:sm1m8407.bin file 127:sm1m8408.bin file 128:sm1m8409.bin file 129:sm1m8505.bin file 130:sm1m8506.bin file 131:sm1m8507.bin file 132:sm1m8508.bin file 133:sm1m8509.bin file 134:sm1m8605.bin file 135:sm1m8606.bin file 136:sm1m8607.bin file 137:sm1m8608.bin file 138:sm1m8609.bin file 139:sm1m8705.bin file 140:sm1m8706.bin file 141:sm1m8707.bin file 142:sm1m8708.bin file 143:sm1m8709.bin file 144:sm1m8805.bin file 145:sm1m8806.bin file 146:sm1m8807.bin file 147:sm1m8808.bin file 148:sm1m8809.bin file 149:sm1m8905.bin file 150:sm1m8906.bin file 151:sm1m8907.bin file 152:sm1m8908.bin file 153:sm1m8909.bin file 154:sm1m11y05.bin file 155:sm1m11y06.bin file 156:sm1m11y07.bin file 157:sm1m11y08.bin file 158:sm1m11y09.bin file 159:sm3m11y.bin file 160:sm5m11y.bin file 161:veg2mask.bin file 162:veg3mask.bin file 163:oceanmask.bin 8.2.2 Compressed CD-ROM Files On the BOREAS CD-ROMs, all the files listed above have been compressed with the Gzip compression program (file name *.gz). These data have been compressed using gzip version 1.2.4 and the high compression (-9) option (Copyright (C) 1992-1993 Jean-loup Gailly). Gzip (GNU zip) uses the Lempel-Ziv algorithm (Welch, 1994) used in the zip and PKZIP programs. The compressed files may be uncompressed using gzip (-d option) or gunzip. Gzip is available from many websites (for example, ftp site prep.ai.mit.edu/pub/gnu/gzip-*.*) for a variety of operating systems in both executable and source code form. Versions of the decompression software for various systems are included on the CD-ROMs. 9. Data Manipulations 9.1 Formulae Equations for scaling from 2-byte integers to floating point numbers (val). variable equation ----------- -------------------------------------- par1m val = (int/100.)-1. par1mav val = (int/100.)-1 par3m val = (int/10.)-1. par5m val = (int/10.)-1. par3mav val = (int/10.)-1. par5mav val = (int/10.)-1. par3msd val = (int/100.)-1. par5msd val = (int/100.)-1. par1msd val = (int/1000.)-1. par1mcv val = (int/1000.)-1. par3mcv val = (int/1000.)-1. par5mcv val = (int/1000.)-1. 9.1.1 Derivation Techniques and Algorithms The PAR estimation technique described by Eck and Dye (1991) consists of two main components: (1) estimation of the potential amount of PAR that would reach the surface under clear sky conditions, and (2) estimation of the actual amount of PAR incident at the surface under observed conditions using TOMS reflectivity. Potential (clear sky) Incident PAR Daily potential (clear sky) PAR at the surface was calculated using the spectral model described by Goldberg and Klein (1980), parameterized for the 400 - 700 nm band. The model is given as Ip* = Iop cos z[0.5(1+e-m*R)e-m*(????) + 0.05] where Ip* = potential PAR incident at the surface (kJ m-2 day-1) Iop = PAR at top of atmosphere (kJ m-2 day-1) m* = effective air mass for computing daily total irradiance R = Rayleigh scattering coefficient (0.131) ? = aerosol scattering and absorption coefficient (0.02) ? = ozone absorption coefficient for 400-700 nm band (0.053) ? = ozone amount (300 Dobson Units) Actual Incident PAR Estimation of actual surface-incident PAR (Ip, daily total, kJ m-2 day-1) is based in part on the the PAR reflectance inferred from the monthly average TOMS reflectivity (r ). Refer to Eck & Dye (1991) for details regarding the underlying rationale. For r < 0.5, Ip = Ip*[1 - (r - .05)/.90] For r ? 0.5, Ip = Ip*(1-r). Monthly total PAR is calculated as the sum of the daily total PAR values for all days in the month, with units conversion to MJ m-2. Snow/Ice Masks The snow/ice masks are intended to aid in identifying grid cells with PAR estimates that are not contaminated by snow and ice reflectance. The snow/ice image masks were created by reducing the spatial resolution of the Northern Hemisphere Weekly Snow Cover and Sea Ice Extent data product from NSIDC from 25 km to 1 degree, and their temporal resolution from 1 week to 1 month. This was achieved in two steps. First, a binning procedure was employed in which the 25 km weekly data were “mapped” onto a 1 degree grid. These 1 degree weekly data were then combined within monthly periods. For latitudes below 66 degrees north, typically between 8 and 20 input cells (25 km resolution) were associated with each output cell on the 1 degree target grid. If snow or ice cover was indicated by three or more of the input cells, the output cell was tagged accordingly as either snow or ice. When both snow and ice occurred in the same output cell, the category with greater number of occurrences was selected, and snow was selected in the case of equal occurrences. Each weekly file was assigned to a calendar month based on the calendar date of the end day in its weekly coverage period. If the end date was 3 or less, the weekly file was assigned to the preceding month. Consequently, the temporal resolution of the monthly PAR data has a uncertainty of +/- 3 days at the beginning and end of the month. The mask data values indicate the number of weeks during the month in which snow or ice was present in a significant area of the 1 degree PAR grid cell. Eleven-year snow/ice masks were created by compositing the individual months over 11-year period. A given grid cell is assigned a mask value if snow or ice is indicated for one or more years in the 11-year time series. The 11-year snow/ice masks may be applied to the 11-year PAR statistics data. Vegetation and Ocean/Land Masks The image masks for vegetation type and ocean/land areas were extracted from the 1 degree global map described by Defries and Townshend (1994, see also http://www.inform.umd.edu/GEOG/landcover/1d-map.html). 9.2 Data Processing Sequence 9.2.1 Processing Steps The RSS-10 team used the following processing steps: Compute monthly total PAR irradiances at the surface for grid cell center points using (see Section 9.1.1). Resample 1 x 1.25 degree monthly grid values to 1 x 1 degree grid based on spatially weighted averages. Compute 11-year statistics (mean, standard deviation, coefficient of variation) for 1 degree monthly PAR data Compute 11-year statistics (mean, standard deviation, coefficient of variation) for 1 degree monthly data. BORIS personnel processed the data by: Viewing randomly selected images on a display screen, Using the supplied information to inventory the data in the on-line database, Compressing the data files for distribution on CD-ROM. 9.2.2 Processing Changes None. 9.3 Calculations 9.3.1 Special Corrections/Adjustments None. 9.3.2 Calculated Variables PAR at the top of the atmosphere (Iop) was calculated according to the model of McCollough (1968): Iop =.378[A0+A1cos(d)+A2cos(2d)+B1sin(d)+B2sin(2d)] where A0, A1, A2, B1 and B2 are latitude-dependent coefficients given by McCollough (1968) and d is day of year. The constant .378 accounts for the fraction of extraterrestrial solar flux in the PAR band and includes a correction for McCollough’s (1968) assumed solar constant as adopted by Goldberg and Klein (1980). The effective daily total air mass (m*) was calculated using the equation of Goldberg and Klein (1980): m* = 0.179+130836m+0.39482m2 where m = (sin? sin? + cos? cos?)-1 ? = latitude ? = solar declination 9.4 Graphs and Plots None given. 10. Errors 10.1 Sources of Error Errors in Version 6 Reflectivity The Version 6 reflectivity for non-ozone-absorbing wavelengths was found to exhibit a wavelength dependence correlated with partially clouded scenes. Results from a quantitative assessment of the impact on PAR estimation accuracy is not available at this time. After 1989, Nimbus-7 TOMS sensor degradation introduced significant errors which were not fully corrected in the Version 6 reflectivities. PAR estimates for years 1990-1993 were excluded from the data set. Effects of Snow/Ice Surfaces The PAR estimates may be lower than actual PAR irradiance in locations where the surface was covered by snow or ice during the month(s) observed by the TOMS instrument. Results from a quantitative examination of this effect are not yet available, however such error may be expected to decrease as the snow/ice-free period within a the month increases. The user can assess the potential for snow/ice related effects at each grid cell location by referring to the snow/ice information provided with the data set. 10.2 Quality Assessment 10.2.1 Data Validation by Source None at this time for boreal sites. Eck and Dye (1991) and Dye (1995) present validation results for selected sites at middle and tropical latitudes. 10.2.2 Confidence Level/Accuracy Judgment PAR estimation accuracy is potentially reduced in areas covered by snow or ice. Model parameters for UV reflectivity and atmospheric ozone amount therefore do not account for potential geographic and temporal variations. See Sections 10.2.2 and 10.2.3. 10.2.3 Measurement Error for Parameters The present version of the PAR data set assumes constant values for atmospheric ozone amount (300 Dobson Units). This assumption introduces a maximum potential error in the PAR estimates of approximately -0.5% to +1% during June at boreal latitudes (Dye, 1992). Likewise, the background surface UV reflectivity is assumed constant at 5%. For a “true” background surface reflectivity between 4% and 7%, the predicted maximum PAR estimation error is less than approximately +/- 2% (Dye, 1992). 10.2.4 Additional Quality Assessments Results from an intercomparison of global-coverage TOMS PAR data with other satellite-derived PAR data sources are presented by Dye and Shibasaki (1995). 10.2.5 Data Verification by Data Center The data center has browsed samples of the image files. 11. Notes 11.1 Limitations of the Data None reported at this time. 11.2 Known Problems with the Data None. 11.3 Usage Guidance Before uncompressing the Gzip files on CD-ROM, be sure that you have enough disk space to hold the uncompressed data files. Then use the appropriate decompression program provided on the CD-ROM for your specific system. 11.4 Other Relevant Information None. 12. Application of the Data Set The data may be useful in the analysis and modeling of the spatial and temporal dynamics of PAR energy receipt and capture by vegetation at middle to high latitudes, and for application in process models of primary production. 13. Future Modifications and Plans A research plan for a second-generation PAR data set for the globe using reprocessed (Version 7) Nimbus-7 TOMS reflectivity data has been proposed. The improved data set will account for spatiotemporal variation in model parameters for surface UV reflectivity, ozone amount, and aerosol optical depth. The proposed project includes an extensive validation component involving comparisons to contemporaneous ground-based measurements. 14. Software 14.1 Software Description The software used to process the TOMS PAR data were prepared in Fortran, with each program addressing a specific task in the processing and analysis sequence. Fortner Transform software in conjunction with LS Fortran software was employed for creation, manipulation and analysis of the image data. Gzip (GNU zip) uses the Lempel-Ziv algorithm (Welch, 1994) used in the zip and PKZIP commands. 14.2 Software Access For information on the software used in processing this data set, contact: Dennis G. Dye Assistant Professor Dept. of Geography and Center for Remote Sensing Boston University Boston, MA tel: +1-617-353-4807 fax: +1-617-353-8311 ddye@bu.edu Gzip (GNU zip) uses the Lempel-Ziv algorithm (Welch, 1994) used in the zip and PKZIP commands. 15. Data Access 15.1 Contact Information Ms. Beth Nelson BOREAS Data Manager NASA GSFC Greenbelt, MD (301) 286-4005 (301) 286-0239 (fax) Elizabeth.Nelson@gsfc.nasa.gov 15.2 Data Center Identification See section 15.1. 15.3 Procedures for Obtaining Data Users may place requests by telephone, electronic mail, or FAX. 15.4 Data Center Status/Plans The RSS-10 TOMS PAR images are available from the EOSDIS ORNL DAAC (Earth Observing System Data and Information System) (Oak Ridge National Laboratory) (Distributed Active Archive Center). The BOREAS contact at ORNL is: ORNL DAAC User Services Oak Ridge National Laboratory Oak Ridge, TN (423) 241-3952 ornldaac@ornl.gov ornl@eos.nasa.gov 16. Output Products and Availability 16.1 Tape Products The data can be made available on 8 mm or DAT media. 16.2 Film Products None. 16.3 Other Products None. 17. References 17.1 Platform/Sensor/Instrument/Data Processing Documentation McPeters, R.D., Krueger, A.J., Bhartia, P.K., Herman, J.R., Oakes, A., Ahmad, Z., Cebula, R.P., Schlesinger, B.M., Swissler, T., Taylor, S.L., Torres, O., and Wellemeyer, C.G., 1993. Nimbus-7 Total Ozone Mapping Spectrometer (TOMS) Data Products User’s Guide, NASA Reference Publ., 1323, National Aeronautics and Space Admin., Washington, DC. McPeters, R.D., Bhartia, P.K., Krueger, A.J., Herman, J.R., Schlesinger, Wellemeyer, C.G., B.M., Seftor, C.J., Jaross, G., Taylor, S.L., Swissler, T., Torres, O., Labow, G., Byerly, W., and Cebula, R.P., 1996. Nimbus-7 Total Ozone Mapping Spectrometer (TOMS) Data Products User’s Guide, NASA Reference Publ., National Aeronautics and Space Admin., Washington, DC. NASA, 1978. The Nimbus 7 Users' Guide. C. R. Madrid, editor.Goddard Space Flight Center. Welch, T.A. 1984, A Technique for High Performance Data Compression, IEEE Computer, Vol. 17, No. 6, pp. 8 - 19. 17.2 Journal Articles and Study Reports Dave, J.V., 1978. Effect of aerosols on the estimation of total ozone in an atmospheric column from the measurement of its ultraviolet radiance. J. Atmos. Sci., 35:899-911. DeFries, R. S. and J. R. G. Townshend, 1994, NDVI-derived land cover classification at a global scale. International Journal of Remote Sensing, 15:3567-3586. Dye, D.G., 1992. Satellite estimation of the global distribution and interannual variability of photosynthetically active radiation. Ph.D. dissertation, University of Maryland at College Park. Dye, D.G., and Shibasaki, R., 1995. Intercomparison of global PAR data sets. Geophys. Res. Let., 22:2013-2016. Eck, T.F., and Dye, D.G., 1991. Satellite estimation of incident photosynthetically active radiation usng ultraviolet reflectance. Rem. Sensing Environ., 38:135-146. Goldberg, B., and Klein, W.H., 1980. A model for determining the spectral quality of daylight on a horizontal surface at any geographical location. Solar Energy, 24:351-357. Heath, D.F., Krueger, A.J., Roeder, H.A., Henderson, B.D., 1975. The Solar Backscatter Ultraviolet and Total Ozone Mapping Spectrometer (SBUV/TOMS) for NIMBUS G. Opt. Eng., 14:323-331. Herman, J.R., Hudson, R., McPeters, R., Stolarski, R., Ahmad, Z., Gu, X-Y, Taylor, S., and Wellemeyer, C., 1991. A new self-calibration method applied to TOMS/SBUC backscattered ultraviolet data to determine long term global ozone change. J. Geophys. Res., 96:7531-7546. Herman, J.R., P.K. Bhartia, J. Ziemke, Z. Ahmad, and D. Larko, 1996. UV-B increases (1979-1992) from decreases in ozone, Geophys. Res. Lett. 23, 2117. Herman, J.R., P.K. Bhartia, O. Torres, N.C. Hsu, C.J. Seftor, and E. Celerier, , 1997. Global distribution of absorbing aerosols from Nimbus-7/TOMS data, J. Geophys. Res., in press. McCollough, E.C., 1968. Total Daily radiant energy available extraterrestrially as a harmonic series in the day of the year. Arch. Met. Geophys. Biokl., Ser. B, 16: Sellers, P., F. Hall. 1994. Boreal Ecosystem-Atmosphere Study: Experiment Plan. Version 1994-3.0, NASA BOREAS Report (EXPLAN 94). Sellers, P., F. Hall, H. Margolis, B. Kelly, D. Baldocchi, G. den Hartog, J. Cihlar, M.G. Ryan, B. Goodison, P. Crill, K.J. Ranson, D. Lettenmaier, and D.E. Wickland. 1995. The boreal ecosystem-atmosphere study (BOREAS): an overview and early results from the 1994 field year. Bulletin of the American Meteorological Society. 76(9):1549-1577. Sellers, P., F. Hall, K.F. Huemmrich. 1996. Boreal Ecosystem-Atmosphere Study: 1994 Operations. NASA BOREAS Report (OPS DOC 94). Sellers, P., F. Hall. 1996. Boreal Ecosystem-Atmosphere Study: Experiment Plan. Version 1996-2.0, NASA BOREAS Report (EXPLAN 96). Sellers, P., F. Hall, K.F. Huemmrich. 1997. Boreal Ecosystem-Atmosphere Study: 1996 Operations. NASA BOREAS Report (OPS DOC 96). Sellers, P.J., F.G. Hall, R.D. Kelly, A. Black, D. Baldocchi, J. Berry, M. Ryan, K.J. Ranson, P.M. Crill, D.P. Lettenmaier, H. Margolis, J. Cihlar, J. Newcomer, D. Fitzjarrald, P.G. Jarvis, S.T. Gower, D. Halliwell, D. Williams, B. Goodison, D.E. Wickland, and F.E. Guertin. (1997). "BOREAS in 1997: Experiment Overview, Scientific Results and Future Directions", Journal of Geophysical Research (JGR), BOREAS Special Issue, 102(D24), Dec. 1997, pp. 28731-28770. 17.3 Archive/DBMS Usage Documentation None. 18. Glossary of Terms None. 19. List of Acronyms BOREAS - BOReal Ecosystem-Atmosphere Study BORIS - BOREAS Information System DAAC - Distributed Active Archive Center EOS - Earth Observing System EOSDIS - EOS Data and Information System GSFC - Goddard Space Flight Center NASA - National Aeronautics and Space Administration NSA - Northern Study Area (BOREAS) OPT - Ozone Processing Team ORNL - Oak Ridge National Laboratory PANP - Prince Albert National Park PAR - Photosynthetically Active Radiation SSA - Southern Study Area (BOREAS) TOMS - Total Ozone Mapping Spectrometer URL - Uniform Resource Locator (a World Wide Web address) UV - Ultraviolet 20. Document Information 20.1 Document Revision Date(s) Written: 18-Jul-1997 Last Updated: 14-Sep-1998 20.2 Document Review Date(s) BORIS Review: 10-Sep-1997 Science Review: 29-Jan-1998 20.2 Document Review Date(s) 20.3 Document 20.4 Citation Acknowledge Dennis G. Dye (Boston Univ.) and Thomas F. Eck (NASA-GSFC/Hughes STX) for providing TOMS PAR data. Cite relevant publications (see Section 17.2). 20.5 Document Curator 20.6 Document URL Keywords RADIATION PAR TOMS NIMBUS RSS10_PAR_TOMS.doc 09/14/98