scholarly journals Sea ice concentration estimates from satellite passive microwave radiometry and openings from SAR ice motion

2002 ◽  
Vol 29 (9) ◽  
pp. 25-1-25-4 ◽  
Author(s):  
Ron Kwok
Keyword(s):  
Sea Ice ◽  
Passive Microwave ◽  
Microwave Radiometry ◽  
Sea Ice Concentration ◽  
Ice Concentration ◽  
Passive Microwave Radiometry

scholarly journals The 2018 North Greenland polynya observed by a newly introduced merged optical and passive microwave sea-ice concentration dataset

2019 ◽  
Vol 13 (7) ◽  
pp. 2051-2073 ◽  
Author(s):  
Valentin Ludwig ◽  
Gunnar Spreen ◽  
Christian Haas ◽  
Larysa Istomina ◽  
Frank Kauker ◽  
...  
Keyword(s):  
Sea Ice ◽  
Growth Yield ◽  
Thermal Infrared ◽  
Passive Microwave ◽  
Pressure System ◽  
Sea Ice Concentration ◽  
Sea Ice Thickness ◽  
Ice Growth ◽  
Spatial Coverage ◽  
Ice Concentration

Abstract. Observations of sea-ice concentration are available from satellites year-round and almost weather-independently using passive microwave radiometers at resolutions down to 5 km. Thermal infrared radiometers provide data with a resolution of 1 km but only under cloud-free conditions. We use the best of the two satellite measurements and merge thermal infrared and passive microwave sea-ice concentrations. This yields a merged sea-ice concentration product combining the gap-free spatial coverage of the passive microwave sea-ice concentration and the 1 km resolution of the thermal infrared sea-ice concentration. The benefit of the merged product is demonstrated by observations of a polynya which opened north of Greenland in February 2018. We find that the merged sea-ice concentration product resolves leads at sea-ice concentrations between 60 % and 90 %. They are not resolved by the coarser passive microwave sea-ice concentration product. The benefit of the merged product is most pronounced during the formation of the polynya. Next, the environmental conditions during the polynya event are analysed. The polynya was caused by unusual southerly winds during which the sea ice drifted northward instead of southward as usual. The daily displacement was 50 % stronger than normal. The polynya was associated with a warm-air intrusion caused by a high-pressure system over the Eurasian Arctic. Surface air temperatures were slightly below 0 ∘C and thus more than 20 ∘C higher than normal. Two estimates of thermodynamic sea-ice growth yield sea-ice thicknesses of 60 and 65 cm at the end of March in the area opened by the polynya. This differed from airborne sea-ice thickness measurements, indicating that sea-ice growth processes in the polynya are complicated by rafting and ridging. A sea-ice volume of 33 km3 was produced thermodynamically.

scholarly journals Summer and early-fall Sea-ice concentration in the Ross Sea: comparison of in Situ ASPeCt observations and satellite passive microwave estimates

2006 ◽  
Vol 44 ◽  
pp. 303-309 ◽  
Author(s):  
Margaret A. Knuth ◽  
Stephen F. Ackley
Keyword(s):  
Sea Ice ◽  
Satellite Data ◽  
Ross Sea ◽  
Passive Microwave ◽  
Sea Ice Concentration ◽  
Point Sampling ◽  
Continuous Sampling ◽  
Ice Concentration ◽  
Observation Protocol

AbstractSea-ice conditions were observed using the AsPeCt observation protocol on three cruises in the Ross Sea spanning the Antarctic Summer Season (APIs, December 1999–February 2000; Anslope 1, March–April 2003; Anslope 2, February–April 2004). An additional dataset was analyzed from helicopter video Surveys taken during the APIs cruise. The helicopter video was analyzed using two techniques: first, as an AsPeCt dataset where it was Sampled visually for ice concentration, floe Sizes and ice type on a point basis at 11 km intervals; Second, computerized image processing on a Subset of nine helicopter flights to obtain ice concentration on a continuous basis (1 S intervals) for the entire flight. This continuous Sampling was used to validate the point-sampling methods to characterize the ice cover; the ‘AsPeCt Sampling’ on the helicopter video and the use of the AsPeCt protocol on the Ship Surveys. The estimates for average ice concentration agreed within 5% for the continuous digitized data and point Sampling at 11 km intervals in this comparison. The Ship and video in Situ datasets were then compared with ice concentrations from SsM/I passive microwave Satellite data derived using the Bootstrap and NAsA-Team algorithms. Less than 50% of the variance in Summer ice concentration observed in Situ was explainable by Satellite microwave data. The Satellite data were also inconsistent in measurement, both underestimating and overestimating the concentration for Summer conditions, but improved in the fall period when conditions were colder. This improvement was in the explainable variance of >70%, although in Situ concentration was underestimated (albeit consistently) by the Satellite imagery in fall.

scholarly journals VALIDATION OF ASMR2 SEA ICE CONCENTRATION DATA USING MODIS DATA

2019 ◽  
Vol XLII-2/W13 ◽  
pp. 1741-1746
Author(s):  
K. Cho ◽  
R. Nagao ◽  
K. Naoki
Keyword(s):  
Sea Ice ◽  
Spatial Resolution ◽  
Microwave Radiometer ◽  
Threshold Level ◽  
Passive Microwave ◽  
Concentration Data ◽  
Sea Ice Concentration ◽  
Free Condition ◽  
Modis Data ◽  
Ice Concentration

<p><strong>Abstract.</strong> Passive microwave radiometer AMSR2 was launched by JAXA in May 2012 on-board GCOM-W satellite. The antenna diameter of AMSR2 is 2.0&amp;thinsp;m which provide highest spatial resolution as a passive microwave radiometer in space. The sea ice concentration images derived from AMSR2 data allow us to monitor the detailed sea ice distributions of whole globe every day. The AMSR bootstrap algorithm developed by Dr. Josefino Comiso is used as the standard algorithm for calculating sea ice concentration from AMSR2 data. Under the contract with JAXA, the authors have been evaluating the performance of the algorithm. The sea ice concentration estimated from AMSR2 data were evaluated using MODIS data observed from Aqua satellite within few minutes after AMSR2 observation from GCOM-W. Since the spatial resolution of MODIS is much higher than that of AMSR2, under the cloud free condition, the ice concentration corresponds to the size of a pixel of AMSR2 can be calculated much accurately with MODIS data. The procedures of the evaluation are as follows. Firstly, MODIS band 1 reflectance were binarized to discriminate sea ice(1) from open water(0) and sea ice concentration of each pixel size of AMSR2 were calculated. In calculating sea ice concentration from MODIS data, the selection of the threshold level of MODIS band 1 reflectance is critical. Through the detailed evaluation, the authors selected 5% as the optimum threshold level. Then the AMSR2 sea ice concentration of each pixel was compared with the sea ice concentration calculated from MODIS data. The result suggested the possibility of estimating sea ice concentration from AMSR2 data with less than 10% error under the cloud free condition.</p>

scholarly journals A long-term and reproducible passive microwave sea ice concentration data record for climate studies and monitoring

2013 ◽  
Vol 6 (1) ◽  
pp. 95-117
Author(s):  
G. Peng ◽  
W. N. Meier ◽  
D. J. Scott ◽  
M. H. Savoie
Keyword(s):  
Sea Ice ◽  
Passive Microwave ◽  
Climate Data ◽  
Concentration Data ◽  
Sea Ice Concentration ◽  
Ice Concentration ◽  
Data Record ◽  
Climate Data Record ◽  
Climate Studies

Abstract. A long-term, consistent, and reproducible satellite-based passive microwave sea ice concentration climate data record (CDR) is available for climate studies, monitoring, and model validation with an initial operation capability (IOC). The daily and monthly sea ice concentration data are on the National Snow and Ice Data Center (NSIDC) polar stereographic grid with nominal 25 × 25 km grid cells in both the Southern and Northern Hemisphere Polar Regions from 9 July 1987 to 31 December 2007 with an update through 2011 underway. The data files are available in the NetCDF data format at http://nsidc.org/data/g02202.html and archived by the National Oceanic and Atmospheric Administration (NOAA)'s National Climatic Data Center (NCDC) under the satellite climate data record program (http://www.ncdc.noaa.gov/cdr/operationalcdrs.html). The description and basic characteristics of the NOAA/NSIDC passive microwave sea ice concentration CDR are presented here. The CDR provides similar spatial and temporal variability as the heritage products to the user communities with the additional documentation, traceability, and reproducibility that meet current standards and guidelines for climate data records. The dataset along with detailed data processing steps and error source information can be found at: doi:10.7265/N5B56GN3.

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