3 edition of Ice surface temperature retrieval from AVHRR, ATSR, and passive microwave satellite data found in the catalog.
Ice surface temperature retrieval from AVHRR, ATSR, and passive microwave satellite data
by National Aeronautics and Space Administration, National Technical Information Service, distributor in [Washington, DC, Springfield, Va
Written in English
|Statement||Jeff Key, James Maslanik, Konrad Steffen.|
|Series||NASA contractor report -- NASA CR-197542.|
|Contributions||Maslanik, James A., Steffen, Konrad., United States. National Aeronautics and Space Administration.|
|The Physical Object|
ABSTRACT. The surface temperature of sea ice controls the rate of ice growth and heat exchange between the ocean and the atmosp here. An algorithm for the satellite retrieval of ice surface temperature has recently been published, but due to the lack of valida tion data has not been extensively tested. NOAA/NSIDC Climate Data Record of Passive Microwave Sea Ice Concentration, Version 2. This data set provides a monthly Climate Data Record (CDR) of sea ice concentration from passive microwave data for both the north and south polar regions. The NOAA/NSIDC CDR is based on the recommendations from the National Research Council (NRC) ().
National Snow and Ice Data Center, Cooperative Institute for Research in Environmental Sciences, Campus Box , University of Colorado, Boulder, CO USA E-mail: @ ABSTRACT. Passive microwave sea-ice concentration fields provide some of the longest-running and most consistent records of changes in sea ice. N. Maaß et al.: Snow thickness retrieval over thick Arctic sea ice using SMOS satellite data at the bottom. The emission model then describes the bright-ness temperature above snow-covered sea ice as a function of the air permittivity, of the water temperature and permittivity, and of the temperatures, permittivities and thicknesses of the.
Integrating AVHRR satellite data and NOAA ground observations to predict surface air temperature: A statistical approach E. N. Florio, S. R. Lele, Y. Chi Chang, R. Sterner, G. E. Glass Bloomberg School of Public HealthCited by: ). The refreezing of melt water can also create ice lay-ers that adversely impact the ability of ungulate travel and foraging (Hansen et al., ; Grenfell and Putkonen, ), and exert uncertainties in snow mass retrieval from passive microwave satellite data (Derksen et al., ; Rees et al., ). Winter warming and melt events may.
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Ice surface temperature retrieval from AVHRR, ATSR, and passive microwave satellite data: Algorithm development and application: NTRS Full-Text: View Document [PDF Size: KB] Author and Affiliation:Author: Jeff Key, James Maslanik, Konrad Steffen.
Classification of merged AVHRR and SMMR Arctic data with neural networks. Ice surface temperature retrieval from AVHRR, ATSR, and passive microwave satellite data: Algorithm.
Get this from a library. Ice surface temperature retrieval from AVHRR, ATSR, and passive microwave satellite data: algorithm development and application: semi-annual report, year 2. [Jeffrey R Key; James Maslanik; Konrad Steffen; United. Get this from a library. Ice surface retrieval from AVHRR, ATSR and passive microwave satellite data: algorithm development and application, NAGW, year 2 annual report.
[Jeffrey R Key; James Andrew Maslanik; Konrad Steffen; United States. retrieval of the sea ice surface temperature (IST) in the kin. Profiles that have at least 10 levels are retained in Arctic, an area where the first effects of a changing the analysis. New algorithm VASIA2 of sea ice concentration retrieval from satellite microwave radiometry data is presented.
• The algorithm is based solely on a theoretical model and calculations. • No tie-points are used in the algorithm. • The design of VASIA2 practically precludes the effect of atmospheric variation on the calculation results.
•Cited by: 6. To minimize gaps due to the masking of persistent clouds, weekly surface temperatures are usually the final masking is done on an orbit to orbit basis.
Only the data from the middle are chosen from the AVHRR measurements that and passive microwave satellite data book from ' to +So from maps are created from all available orbital data during the day. Kerr, Y.H., J.P.
Lagouarde and J. Imbernon (): Accurate Land Surface Temperature Retrieval from AVHRR Data with Use of an Improved Split Window Algorithm. Remote Sensing of Environment, 41, – CrossRef Google ScholarCited by: This product consists of meteorological data from Arctic weather stations and Antarctic stations, extracted from the National Climatic Data Center (NCDC)'s Integrated Surface Hourly (ISH) database.
Variables include wind direction, wind speed, visibility, air temperature, dew point temperature, and sea level pressure.
Snow depth distribution over sea ice in the Southern Ocean from satellite passive microwave data. In Antarctic Sea Ice: Physical Processes, Interactions and Variability, Washington, DC: American Geophysical Union. Thermodynamical effect of the snow cover Maass et al.
Snow thickness retrieval over thick Arctic sea ice using SMOS satellite. Anderson, Mark R., "Snow Melt on Sea Ice Surfaces as Determined from Passive Microwave Satellite Data" ().
Papers in the Earth and Atmospheric Sciences. Thumbnails Captions; Average Arctic sea ice concentration for March from the HadISST data set. (Figure by D.
Schneider, NCAR). Annual Antarctic sea ice extent for from the HadiSST data set. and are covered by two climatologies. The relationship between AVHRR thermal radiances and the surface (skin) temperature of Arctic snow‐covered sea ice is examined through forward calculations of the radiative transfer equation, providing an ice/snow surface temperature retrieval algorithm for the central Arctic by: This data set is generated from brightness temperature data and is designed to provide a consistent time series of sea ice concentrations spanning the coverage of several passive microwave data are provided in the polar stereographic projection at a grid cell size of 25 x 25 km.
This is the most recent version of these data. This paper describes a method for NOAA-AVHRR satellite data processing in sea ice and oceanographic studies in the polar seas.
This method includes geometrical processing to generate gridded and corrected images according to a polar stereographic map, ice and cloud discrimination during summer, and the production of combined sea ice and sea surface Author: Kergomard Claude.
This dataset contains two-dimensional precipitation and surface products from the JPSS Microwave Integrated Retrieval System (MIRS) using sensor data from the Advanced Technology Microwave Sounder (ATMS) onboard the Suomi National Polar-orbiting Partnership (S-NPP) h Year: It is a spatially gridded (5° × 5°) global surface temperature dataset, with monthly resolution from January to present.
We combine a global sea surface (water) temperature (SST) dataset with a global land surface air temperature dataset into this merged dataset of both the Earth’s land and ocean surface temperatures.
Finally, we apply the AVHRR ice-thickness data to an assessment of satellite passive-microwave remote sensing as a means of gaining wider estimates of thin sea-ice distri-bution, as reported from the Arctic by Cavalieri () and Martin and others ().
The advantage of satellite passive-microwave data compared to visible/thermal-infrared data. Seasonal variability and trends in the surface temperature of ice-covered areas over land in the Arctic, including glaciers, snow, permafrost, and the Greenland ice sheet, have been studied using the AVHRR surface-temperature data (Comiso, ).
Comparison of results from AVHRR and MODIS from to as well as an update of earlier Author: Josefino C. Comiso, Dorothy K. Hall, Ignatius Rigor. Key, J.,The Cloud and Surface Parameter Retrieval (CASPR) System for Polar AVHRR User’s Guide, Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin, West Dayton St., Madison, WI61 pp.
DISCLAIMER This program is File Size: KB. The most widely used sea ice data sets for climate research are derived from passive microwave instruments, including SMMR, SSMI, SSMIS, AMSR-E and AMSR-2, flying on various satellite platforms.
The algorithms applied to the microwave brightness temperatures use different combinations of channels, making different corrections for weather.Surface temperature retrieval from Along Track Scanning Radiometer 2 data: Algorithms and validation J.
A. Sobrino and G. So`ria Global Change Unit, Department of Thermodynamics, University of Valencia, Burjassot, Spain A. J. Prata Atmospheric Research Division, Commonwealth Scientific and Industrial Research Organisation, Aspendale, Victoria Cited by: Ice Surface Temperature Retrieval from AVHRR, ATSR, and Passive Microwave Satellite Data: Algorithm Development and Application, NASA.
PI (Co-PIs: J. Maslanik, K. Steffen), $K, CU, BU, Assessment of Climate Variability of the Greenland Ice Sheet: Integration of In Situ and Satellite Data, NASA.