scholarly journals NASA sea ice validation program for the Defense Meteorological Satellite Program special sensor microwave imager

1991 ◽  
Vol 96 (C12) ◽  
pp. 21969 ◽  
Author(s):  
Donald J. Cavalieri
Keyword(s):  
Sea Ice ◽  
Defense Meteorological Satellite Program ◽  
Microwave Imager ◽  
Meteorological Satellite

scholarly journals Evaluation of operational SSM/I ice-concentration algorithms

2001 ◽  
Vol 33 ◽  
pp. 102-108 ◽  
Author(s):  
Walter N. Meier ◽  
Michael L. Van Woert ◽  
Cheryl Bertoia
Keyword(s):  
The United States ◽  
Substantial Improvement ◽  
The Arctic ◽  
Ongoing Research ◽  
Defense Meteorological Satellite Program ◽  
Ice Concentration ◽  
Operational Activities ◽  
High Resolution Satellite Imagery ◽  
Microwave Imager ◽  
Meteorological Satellite

AbstractThe United States National Ice Center (NIC) provides weekly ice analyses of the Arctic and Antarctic using information from ice reconnaissance, ship reports and high-resolution satellite imagery. In cloud-covered areas and regions lacking imagery, the higher-resolution sources are augmented by ice concentrations derived from Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) passive-microwave imagery. However, the SSM/I-derived ice concentrations are limited by low resolution and uncertainties in thin-ice regions. Ongoing research at NIC is attempting to improve the utility of these SSM/I products for operational sea-ice analyses. The refinements of operational algorithms may also aid future scientific studies. Here we discuss an evaluation of the standard operational ice-concentration algorithm, Cal/Val, with a possible alternative, a modified NASA Team algorithm. The modified algorithm compares favorably with Cal/Val and is a substantial improvement over the standard NASA Team algorithm in thin-ice regions that are of particular interest to operational activities.

scholarly journals Polynya Signature Simulation Method polynya area in comparison to AMSR-E 89GHz sea-ice concentrations in the Ross Sea and off the Adélie Coast, Antarctica, for 2002–05: first results

2007 ◽  
Vol 46 ◽  
pp. 409-418 ◽  
Author(s):  
Stefan Kern ◽  
Gunnar Spreen ◽  
Lars Kaleschke ◽  
Sara De La Rosa ◽  
Georg Heygster
Keyword(s):  
Sea Ice ◽  
Ross Sea ◽  
Open Water ◽  
Simulation Method ◽  
Ross Ice Shelf ◽  
Terra Nova Bay ◽  
Defense Meteorological Satellite Program ◽  
First Results ◽  
Daily Scale ◽  
Microwave Imager

AbstractThe Polynya Signature Simulation Method (PSSM) is applied to Special Sensor Microwave/Imager observations from different Defense Meteorological Satellite Program spacecraft for 2002–05 to analyze the polynya area in the Ross Sea (Ross Ice Shelf polynya (RISP) and Terra Nova Bay polynya (TNBP)) and off the Adélie Coast (Mertz Glacier polynya (MGP)), Antarctica, on a sub-daily scale. The RISP and the MGP exhibit similar average total polynya areas. Major area changes (>10000km2; TNPB: >2000km2) occur over a range of 2–3 to 20 days in all regions. Sub-daily area changes are largest for the MGP (5800km2) and smallest for the TNBP (800km2), underlining the persistence of the forcing of the latter. ARTIST sea-ice (ASI) algorithm concentration maps obtained using 89 GHz Advanced Microwave Scanning Radiometer (AMSR-E) data are compared to PSSM maps, yielding convincing agreement in the average, similarly detailed winter polynya distribution. Average ASI algorithm ice concentrations take values of 25–40% and 65–80% for the PSSM open-water and thin-ice class, respectively. The discrepancy with expected values (0% and 100%) can be explained by the different spatial resolution and frequency used by the methods. A new land mask and a mask to flag icebergs are introduced. Comparison of PSSM maps with thermal ice thickness based on AVHRR infrared temperature and ECMWF ERA-40 data suggests an upper thickness limit for the PSSM thin-ice class of 20–25 cm.

scholarly journals Assessment of the relative accuracy of hemispheric-scale snow-cover maps

2002 ◽  
Vol 34 ◽  
pp. 24-30 ◽  
Author(s):  
Dorothy K. Hall ◽  
Richard E. J. Kelly ◽  
George A. Riggs ◽  
Alfred T. C. Chang ◽  
James L. Foster
Keyword(s):  
Snow Cover ◽  
Near Infrared ◽  
Passive Microwave ◽  
Defense Meteorological Satellite Program ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Microwave Imager ◽  
Meteorological Satellite ◽  
Microwave Data

AbstractThere are several hemispheric-scale satellite-derived snow-cover maps available, but none has been fully validated. For the period 23 October–25 December 2000, we compare snow maps of North America derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and operational snow maps from the U.S. National Oceanic and Atmospheric Administration (NOAA) National Operational Hydrologic Remote Sensing Center (NOHRSC), both of which rely on satellite data from the visible and near-infrared parts of the spectrum; we also compare MODIS maps with Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) passive-microwave snow maps for the same period. The maps derived from visible and near-infrared data are more accurate for mapping snow cover than are the passive-microwave-derived maps, but discrepancies exist as to the location and extent of the snow cover even between operational snow maps. The MODIS snow-cover maps show more snow in each of the 8 day periods than do the NOHRSC maps, in part because MODIS maps the effects of fleeting snowstorms due to its frequent coverage. The large (~30 km) footprint of the SSM/I pixel, and the difficulty in distinguishing wet and shallow snow from wet or snow-free ground, reveal differences up to 5.33 x 106 km2 in the amount of snow mapped using MODIS vs SSM/I data. Algorithms that utilize both visible and passive-microwave data, which would take advantage of the all-weather mapping capability of the passive-microwave data, will be refined following the launch of the Advanced Microwave Scanning Radiometer (AMSR) in the fall of 2001.

scholarly journals Comparison of Remotely Sensed Wind Data over Sulawesi and Maluku Islands Sea Areas

2016 ◽  
Vol 1 (1) ◽  
Author(s):  
Faisal Mahmuddin
Keyword(s):  
Statistical Parameters ◽  
Daily Data ◽  
Long Duration ◽  
Defense Meteorological Satellite Program ◽  
Microwave Imager ◽  
Microwave Radiometers ◽  
Ocean Wind ◽  
Meteorological Satellite ◽  
Term Data

<p class="TTPKeywords"><span>In order to obtain accurate prediction of ocean wind energy, long term data are needed. However, one data sources might not able to provide long duration data. Therefore, the data need to be combined with other sources of data. However, before combining the data, it is important to compare and validate them to confirm their accuracy. In the present study, wind speed data collected by QuikScat and SSM/I (SSMIS) missions are compared and analyzed. QuikScat data were collected by a satellite with the same name, while Special Sensor Microwave Imager (SSM/I) and Special Sensor Microwave Imager Sounder (SSMIS) data are processed and offered by Remote Sensing System (RSS). SSM/I (SSMIS) are passive microwave radiometers carried onboard Defense Meteorological Satellite Program (DMSP). For the comparison, 5 (five) arbitrary positions over Sulawesi and Maluku islands sea areas are chosen for the analyses. For the evaluation purposes, beside time series of daily data from several chosen positions in research location, several statistical parameters are also computed and compared such as mean, standard deviation, root mean square (RMS), correlation coefficient. </span></p>

Comparison of Remotely Sensed Wind Data over Sulawesi and Maluku Islands Sea Areas

2016 ◽  
Vol 1 ◽  
Author(s):  
Faisal Mahmuddin
Keyword(s):  
Statistical Parameters ◽  
Daily Data ◽  
Long Duration ◽  
Defense Meteorological Satellite Program ◽  
Microwave Imager ◽  
Microwave Radiometers ◽  
Ocean Wind ◽  
Meteorological Satellite ◽  
Term Data

<p class="TTPKeywords"><span>In order to obtain accurate prediction of ocean wind energy, long term data are needed. However, one data sources might not able to provide long duration data. Therefore, the data need to be combined with other sources of data. However, before combining the data, it is important to compare and validate them to confirm their accuracy. In the present study, wind speed data collected by QuikScat and SSM/I (SSMIS) missions are compared and analyzed. QuikScat data were collected by a satellite with the same name, while Special Sensor Microwave Imager (SSM/I) and Special Sensor Microwave Imager Sounder (SSMIS) data are processed and offered by Remote Sensing System (RSS). SSM/I (SSMIS) are passive microwave radiometers carried onboard Defense Meteorological Satellite Program (DMSP). For the comparison, 5 (five) arbitrary positions over Sulawesi and Maluku islands sea areas are chosen for the analyses. For the evaluation purposes, beside time series of daily data from several chosen positions in research location, several statistical parameters are also computed and compared such as mean, standard deviation, root mean square (RMS), correlation coefficient. </span></p>

scholarly journals The Performance of Hydrological Monthly Products Using SSM/I–SSMI/S Sensors

2013 ◽  
Vol 14 (1) ◽  
pp. 266-274 ◽  
Author(s):  
Daniel Vila ◽  
Cecilia Hernandez ◽  
Ralph Ferraro ◽  
Hilawe Semunegus
Keyword(s):  
Time Series ◽  
Quality Control ◽  
Information Service ◽  
Valuable Contribution ◽  
Climate Monitoring ◽  
Defense Meteorological Satellite Program ◽  
Microwave Imager ◽  
National Environmental ◽  
Meteorological Satellite ◽  
Rainfall Estimates

Abstract Global monthly rainfall estimates and other hydrological products have been produced from 1987 to the present using measurements from the Defense Meteorological Satellite Program (DMSP) series of the Special Sensor Microwave Imager (SSM/I). The aim of this paper is twofold: to present the recent efforts to improve the quality control (QC) of historical antenna temperature of the SSM/I sensor (1987–2008) and how this improvement impacts the different hydrological products that are generated at NOAA/National Environmental Satellite, Data, and Information Service (NESDIS). Beginning in 2005, the DMSP Special Sensor Microwave Imager/Sounder (SSMI/S) has been successfully operating on the F-16, F-17, and F-18 satellites. The second objective of this paper is focused on the application of SSMI/S channels to evaluate the performance of several hydrological products using the heritage of existing SSM/I algorithms and to develop an improved strategy to extend the SSM/I time series into the SSMI/S era, starting with data in 2009 for F-17. The continuity of hydrological products from SSM/I to SSMI/S has shown to be a valuable contribution for the precipitation and climate monitoring community but several sensor issues must be accounted for to meet this objective.

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