Atsushi Nomura
ECMWF Reanalysis Project
Shinfield Park, Reading
Berkshire RG2 9AX, UK
Robert Grumbine
#206 5200 Auth Rd.
World Weather Building
Camp Springs, MD 20746
_______________________________________________ | Contact 1 | ______________|________________________________| 2.3.1 Name |Mr. Robert Grumbine | 2.3.2 Address |#206 5200 Auth Rd. | |World Weather Building | City/St.|Camp Springs, MD | Zip Code|20746 | 2.3.3 Tel. |(301) 763-8133 | 2.3.4 Email |wd21rg@hp20.wwb.noaa.gov | |grumbine@beaufort.gsfc.nasa.gov | ______________|________________________________| 2.4 Requested Form of Acknowledgment. Please use the following citation whenever these data are used: A. Nomura and R. Grumbine, personal communication, 1995. 3. INTRODUCTION 3.1 Objective/Purpose. Sea ice concentrations derived from satellite-based passive microwave observations have been collected continuously since 1978 for a number of scientific programs. The basic data are archived at the National Snow and Ice Data Center (NSIDC), World Data Center for Glaciology - A. These data have been used for climate change detection, operational sea ice forecasting, climate modeling, and climate reanalysis. 3.2 Summary of Parameters. Sea ice concentration (fraction of grid cell area which is covered by sea ice) expressed as a percent. 3.3 Discussion. The underlying data set which has been collected are passive microwave brightness temperatures. These data are useful for several scientific purposes, especially for estimating sea ice concentration. The basic data are collected on a large swath scanning microwave radiometer, at a resolution of approximately 25 km from a polar orbiting satellite. The satellite covers the mid-latitudes with about a three day repeat time. High latitude points are passed nearly every day. The brightness temperatures are converted to ice concentrations by use of the NASA Team algorithm [Cavalieri, 1992]. The annual average accuracy, estimated by comparison with LANDSAT imagery (itself estimated to be accurate to about 4%) collocated and at the same time, is 7%, with a bias of -4%. That is, the passive microwave estimate is biased about 4% low. The errors are greater in summer, but the verification itself is suspect owing to errors which also affect the LANDSAT comparison set [Cavalieri, 1992]. An ice concentration of 15% typically corresponds to the ice edge. Values less than that are normally weather contamination. A 38% concentration corresponds to the main body of the ice pack [Cavalieri, 1992]. 4. THEORY OF MEASUREMENTS This data set consists of global gridded data of monthly sea ice concentrations derived from passive microwave radiometry. In the polar regions, the contributions from the atmosphere are low, in the absence of storms, for the wavelength span of passive microwave radiometers (0.8 cm to 4.5 cm). The contributions from the surface can be expressed as a product of the emissivity and the physical temperature of the radiating layer. This linear relationship holds because the Rayleigh-Jeans approximation to the Planck blackbody law is valid for passive microwave radiometers (SMMR, SSM/I) wavelength intervals over the range of physical temperatures encountered on the Earth. Radiances are frequently described in terms of brightness temperature. Depending on the polarized component and the wavelength of the radiation, the emissivities of ice-free open water lie in the range 0.28 - 0.75, and those of sea ice lie in the range 0.52 - 96. Except at wavelengths shorter than 1 cm, there is no overlap in the water versus ice emissivity ranges, and sea ice can readily be discerned against the background of open ocean. Moreover, sea ice emissivities vary with ice type, allowing some ice types to be distinguished, within certain limitations, by multichannel microwave observations. For additional information on Microwave properties of sea ice and open ocean see Gloersen et al. (1992). 5. EQUIPMENT 5.1 Instrument Description. 5.1.1 Platform (Satellite). Nimbus 7 SMMR for 25 October 1978 to 20 August 1987 DMSP F-8 SSMI for 9 July 1987 to 31 December 1991 5.1.3 Key Variables. SMMR: Brightness temperature for vertical and horizontal polarization at 18.0, 21.0, and 37.0 GHz. SSMI: Brightness temperature for vertical and horizontal polarization at 19.3 and 37.0 GHz, vertical polarization at 22.2 GHz. 5.1.4 Principles of Operation. See Gloersen et al. (1992). 5.1.5 Instrument Measurement Geometry. See Gloersen et al. (1992). 5.1.6 Manufacturer of Instrument. See Gloersen et al. (1992). 5.2 Calibration. 5.2.1 Specifications. See Gloersen et al. (1992). 5.2.1.1 Tolerance See Gloersen et al. (1992). 5.2.2 Frequency of Calibration. See Gloersen et al. (1992). 5.2.3 Other Calibration Information. See Gloersen et al. (1992). 6. PROCEDURE 6.1 Data Acquisition Methods. The brightness temperature data are available from the NSIDC on CD-ROM, as are the NASA Team algorithms for processing the brightness temperatures to obtain ice concentrations. Already mapped ice concentrations are also available from NSIDC, again on CD-ROM. 6.2 Spatial Characteristics. The NSIDC data are mapped on a polar stereographic grid with a true latitude of 70 N or S, and resolution of 25 km at that latitude. The data here have been averaged to a 1 degree regular latitude-longitude grid. 6.2.1 Spatial Coverage. The coverage is global. Data in each file are ordered from North to South and from West to East beginning at 180 degrees West and 90 degrees North. Point (1,1) represents the grid cell centered at 89.5 N and 179.5 W (see section 8.4). 6.2.2 Spatial Resolution. The data are given in an equal-angle lat/long grid that has a spatial resolution of 1 X 1 degree lat/long. 6.3 Temporal Characteristics. 6.3.1 Temporal Coverage January 1987 through December 1988. 6.3.2 Temporal Resolution Monthly. 7. OBSERVATIONS 7.1 Field Notes. Not applicable. 8. DATA DESCRIPTION 8.1 Table Definition With Comments. Not applicable. 8.2 Type of Data. ----------------------------------------------------------------------------- | 8.2.1 | | | | |Parameter/Variable Name | | | | ----------------------------------------------------------------------------- | | 8.2.2 | 8.2.3 | 8.2.4 | 8.2.5 | | |Parameter/Variable Description |Range |Units |Source | ----------------------------------------------------------------------------- |SEA_ICE | | |SMMR, SSMI, | | |Sea ice concentration as percent |min = 0, |[%] |NASA Team | | |of pixel area covered by ice. |max = 100 | |algorithm | | | | | |as quality | | | | | |controlled | | | | | |by NMC/NCAR | | | | | |and ECMWF | | | | | |reanalysis | | | | | | | ----------------------------------------------------------------------------- 8.3 Sample Data Record. Not applicable. 8.4 Data Format. The CD-ROM file format is ASCII, and consists of numerical fields of varying length, which are space delimited and arranged in columns and rows. Each column contains 180 numerical values and each row contain 360 numerical values. Grid arrangement ARRAY(I,J) I = 1 IS CENTERED AT 179.5W I INCREASES EASTWARD BY 1 DEGREE J = 1 IS CENTERED AT 89.5N J INCREASES SOUTHWARD BY 1 DEGREE 90N - | - - - | - - - | - - - | - - | (1,1) | (2,1) | (3,1) | 89N - | - - - | - - - | - - - | - - | (1,2) | (2,2) | (3,2) | 88N - | - - - | - - - | - - - | - - | (1,3) | (2,3) | (3,3) | 87N - | - - - | - - - | - - - | 180W 179W 178W 177W ARRAY(360,180) 8.5 Related Data Sets. The basic ice concentration and brightness temperature data sets are available from the NSIDC at the full time and space resolution described above. These data do contain some extraneous apparent ice, so processing such as that described in section 9 is necessary prior to use. 9. DATA MANIPULATIONS 9.1 Formulas. 9.1.1 Derivation Techniques/Algorithms. Not applicable. 9.2 Data Processing Sequence. 9.2.1 Processing Steps and Data Sets. 1. Obtain brightness temperature grids and NASA Team algorithm from NSIDC. 2. Apply NASA Team algorithm to brightness temperatures to obtain estimated ice concentrations. 3. If SST at time of collection is greater than +1 C, set ice concentration to zero. 4. Regrid onto a 1 degree latitude longitude grid. SST is obtained from the Reynolds 'improved' SST available on this CD-ROM (Reynolds and Smith, 1993). 9.2.2 Processing Changes. The NASA Team algorithm tie points are re-calibrated for each satellite. 9.3 Calculations. 9.3.1 Special Corrections/Adjustments. The NASA Goddard DAAC applied the inverse of it's land/sea mask to the sea ice data. Land values are 0. 9.4 Graphs and Plots. The SMMR ice atlas [Gloersen, et al., 1992] provides color maps of monthly averaged ice concentration and growth. 10. ERRORS 10.1 Sources of Error. The concentration algorithm can falsely report melting ice as being sea surface. This leads to the underestimation of ice concentration, particularly in summer, mentioned above. In situations with high winds, waves, or rain, it is possible for the algorithm to report ice as being present when there is in fact none. The Nomura [1993] quality control described above removes most of this contamination. 10.2 Quality Assessment. The quality of the ice concentration algorithm is assessed in Cavalieri [1992]. The Nomura quality control is assessed in Nomura [1993]. 10.2.1 Data Validation by Source. Quality control applied by the NMC/ECMWF Reanalysis project. At high latitudes, pixels are revisited on approximately a daily basis (poleward of about 70). At mid latitudes, a given pixel is visited at least once every three days. 10.2.2 Confidence Level/Accuracy Judgment. Most of the concerns regarding the accuracy and precision of the ice concentration data apply to use of a single days' concentration map, at full resolution. After averaging over time to produce a monthly averaged map, the weather contamination problem is largely removed, as few polar areas have persistent heavy rain or winds. The spatial averaging similarly removes much of the ice edge and melting effects. The time of greatest error will be in the summer hemisphere ice pack, when extensive melt ponds can be present in the Arctic. (This is less of a problem in the Antarctic as the ice is thinner and doesn't support melt ponds as large or as long as the Arctic's.) If an ice-no ice decision is desired, a 50% concentration is recommended for all seasons other than summer, then to lower that cutoff to 45% for the Arctic in summer. 10.2.3 Measurement Error for Parameters and Variables. The annual average accuracy, estimated by comparison with LANDSAT imagery (itself estimated to be accurate to about 4%) collocated and at the same time is 7%, with a bias of -4% [Cavalieri, 1992]. That is, the passive microwave estimate is biased about 4% low. 10.2.4 Additional Quality Assessment Applied. Not available at this revision. 11. NOTES 11.1 Known Problems With The Data. None reported at this revision. 11.2 Usage Guidance. The concentrations are respectable as concentrations. Deriving features, such as the ice edge, are not recommended as the data have been spatially reduced from the original data set. 11.3 Other Relevant Information. None at this revision. 12. REFERENCES 12.1 Satellite/Instrument/Data Processing Documentation. Gloersen, P., W. J. Campbell, D. J. Cavalieri, J. C. Comiso, C. L. Parkinson, and H. J. Zwally, 1992. Arctic and Antarctic Sea Ice, 1978-1987: Satellite Passive-Microwave Observations and Analysis, NASA SP-511, 290 pp, Washington, D.C. Cavalieri, D. J., ed., 1992. NASA Sea Ice Validation Program for the Defense Meteorological Satellite Program Special Sensor Microwave Imager: Final Report, NASA Technical Memorandum 104559, 126 pp, Washington, D.C. Cooperative Institute for Research in Environmental Sciences, 1992. DMSP SSM/I Brightness Temperature and Sea Ice Concentration Grids for the Polar Regions on CD-ROM, User's Guide, NSIDC Special Report - 1. 12.2 Journal Articles and Study Reports. Nomura, A. 1993. Sea surface temperature and sea ice data for the ECMWF Reanalysis (ERA) system ECMWF Re-analysis project, report no. 2, 12.3 Archive/DBMS Usage Documentation. Contact the EOS Distributed Active Archive Center (DAAC) at NASA Goddard Space Flight Center (GSFC), Greenbelt Maryland (see Section 13 below). Documentation about using the archive or information about access to the on-line information system is available through the GSFC DAAC User Services Office. 13. DATA ACCESS 13.1 Contacts for Archive/Data Access Information. GSFC DAAC User Services NASA/Goddard Space Flight Center Code 902.2 Greenbelt, MD 20771 Phone: (301) 286-3209 Fax: (301) 286-1775 Internet: daacuso@eosdata.gsfc.nasa.gov 13.2 Archive Identification. Goddard Distributed Active Archive Center NASA Goddard Space Flight Center Code 902.2 Greenbelt, MD 20771 Telephone: (301) 286-3209 FAX: (301) 286-1775 Internet: daacuso@eosdata.gsfc.nasa.gov 13.3 Procedures for Obtaining Data. Users may place requests by accessing the on-line system, by sending letters, electronic mail, FAX, telephone, or personal visit. Accessing the GSFC DAAC Online System: The GSFC DAAC Information Management System (IMS) allows users to ordering data sets stored on-line. The system is open to the public. Access Instructions: Node name: daac.gsfc.nasa.gov Node number: 192.107.190.139 Login example: telnet daac.gsfc.nasa.gov Username: daacims password: gsfcdaac You will be asked to register your name and address during your first session. Ordering CD-ROMs: To order CD-ROMs (available through the Goddard DAAC) users should contact the Goddard DAAC User Support Office (see section 13.2). 13.4 GSFC DAAC Status/Plans. The ISLSCP Initiative I CD-ROM is available from the Goddard DAAC. 14. OUTPUT PRODUCTS AND AVAILABILITY 14.1 Tape Products. None. 14.2 Film Products. None. 14.3 Other Products. None. 15. GLOSSARY OF ACRONYMS SSMI Special Sensor Microwave Imager SMMR Scanning Multichannel Microwave Radiometer NSIDC National Snow and Ice Data Center NASA National Association for the selection of acronyms ECMWF European Center for Medium Range Weather Forecasting NMC National Meteorological Center (US)