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
1994 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-195276., NASA contractor report -- NASA CR-195276.|
|Contributions||Maslanik, James., Steffen, Konrad., United States. National Aeronautics and Space Administration.|
|The Physical Object|
1 Passive Microwave Sea Ice Concentration Climate Data Record 1. Intent of This Document and POC 1a) This document is intended for users who wish to compare satellite derived observations with climate model output in the context of the CMIP/IPCC historical experiments. Satellite data, particularly that from the thermal infrared bands of Landsat and Advanced Very High Resolution Radiometer (AVHRR), have been used extensively in land surface temperature (LST) modelling (Qin and Karnieli ), however few procedures exist that use satellite observations for surface air temperature estimation (Prince et al. ). NASA team algorithm for sea ice concentration retrieval from Defense Meteorological Satellite Program special sensor microwave imager: comparison with Landsat satellite data, J. Geophys. Res., 96 (C12), 21,,,
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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 And passive microwave satellite data book 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 goes 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. and passive microwave satellite data book 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.
Sobrino and G. So`ria Global Change Unit, Department of Thermodynamics, University of Valencia, Burjassot, Spain A. 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), $K, CU, BU, Assessment of Climate Variability of the Greenland Ice Sheet: Integration of In Situ and Satellite Data, NASA. In the third section we describe the temperature retrieval. In the fourth section a validation of the TEMPERA data and comparison with radiosonde and satellite data is presented.
2 Measurement method and instrument description Measurement method TEMPERA measures thermal radiation from 51–57GHz in the oxygen-emission region of the Cited by: Estimation of snow surface temperature for NW Himalayan regions using passive microwave satellite data K K Singh1,$,*, V D Mishra1, Dhiraj Kumar Singh2 & A Ganju1 1Snow and Avalanche Study Establishment (SASE), ChandigarhIndia 2Rayat Institute of Engineering & Information Technology, S B S Nagar, PunjabIndia.
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 BoxUniversity 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. 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. Florio, S. Lele, Y.
Chi Chang, R. Sterner, G. 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. tu data 2. riod a 3. e Current Status 1. Data • - present 2. u Data • - present 3.
of versions 4. Ship SSTs corrected using buoy SSTs Looking Forward 1. Version2 becomes operational 2. TMI 3. NOAA- n availableavailable http: ////st/oist/oi --p AVHRR-only AMSR+AVHRR a Dick Reynolds, NCDC. The use and impacts of sea surface temperature from passive microwave measurements, ECMWF workshop on using low frequency passive microwave measurements in research and operational applications, DecemberReading Overview of PMW for SST + • All weather advantage (not precipitating) • Combined ability for retrieval of SST plus.
Melt Transition Retrieval From Passive Microwave Data Background The seasonal variability in the physical properties of snow has strong effects on its microwave properties. The microwave emissivity e of snow and the measured microwave brightness temperature T B are functions of frequency f and polarization p.
They are related by T. Quantitative analysis of the atmospheric effects on observations made by the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) has been performed.
The differences between observed brightness temperatures at the top of the atmosphere and at the bottom of the atmosphere were analyzed using a database of simulated observations, which.
and tracking using satellite passive microwave data 31 JanuaryUTC AMSR-E •Retrieval of atmospheric columnar water vapor fields from satellite passive microwave data (e.g., SSM/I and AMSR-E) •Detection of vortex structures in these fields •Polar low parameter (life time, size, location, moving speed) estimation.
What we need is an independently-constructed surface temperature series that uses the same raw data set to compare CRUTEM4 against, and some years ago I constructed one. It uses unadjusted GHCN v2 data from very-carefully-selected surface temperature stations, all of which are guaranteed free of significant UHI gradients.
Accurate calculation of the time of melt onset, freeze onset, and melt duration over Arctic sea-ice area is crucial for climate and global change studies because it affects accuracy of surface energy balance estimates.
This comparative study evaluates several methods used to estimate sea-ice melt and freeze onset dates: (1) the melt onset database derived from SSM/I passive.
The retrieval of the atmospheric humidity parameters from NOAA/AMSU data for winter season. Izabela Dyras, Bożena Łapeta, Danuta Serafin-Rek Satellite Research Department, Institute of Meteorology and Water Management, P.
Borow Krakow, Poland (@). Abstract: The passive microwave AMSU data from the NOAA-KLM. Satellite data was introduced into the present system come from the polar orbiting NOAA satellite system. The Advanced Very High Resolution Radiometer (AVHRR/3) is a multipurpose imaging instrument used for global measurement providing the characteristics of cloud cover, sea surface temperature, ice, snow and vegetation cover.
Atmospheric correction for sea surface temperature retrieval from single thermal channel radiometer data onboard Kalpana satellite Naveen R Shahi1,∗, Neeraj Agarwal2, Aloke K Mathur1 and Abhijit Sarkar1 1Atmospheric and Oceanic Sciences Group, Space Applications, Centre (ISRO), AhmedabadIndia.
2Max Planck Institute, Hamburg, Germany. ∗e-mail: .The data used in this investigation contained passive microwave data from the SSM/I, which is a seven-channel, four-frequency, linearly polarized passive microwave radiometer.
The channels are horizontal and vertical polarization at, and GHz and only.Active (imaging radar) and passive (radiometer) microwave systems are increasingly used for Arctic ecological research. Unfortunately, until now ecologists interested in remote sensing often lacked access to the full suite of physical and analytical techniques of microwave systems, data processing, and ecological applications because a suitable reference book did not by: 3.