Sea ice drift
Background
Sea ice drift vectors deduced from satellite remote sensing offers valuable opportunities to study the dynamical processes of sea ice and its role in the Arctic climate system. In recent years, a number of sea ice drift products came to be available. The products have different advantages and weaknesses depending on sensors, frequencies, and algorithms used to derive the drift vectors. The temporal coverages are also different due to the different operational period of the satellite-borne sensors. In some cases, users find large differences of the ice drift estimates from different products and hesitate over which product to choose. These differences should be taken into account as uncertainties of the drift vectors of each product. Here we provide uncertainty estimates of respective ice drift products for practical use.
What user find on the website?
Users can find figures and respective data files in NetCDF-format of the monthly mean sea ice drift of each product and their corresponding uncertainty and bias maps.
Description of the data
This site provides uncertainty and bias estimates of monthly mean ice drift vectors from various products in the Arctic Ocean. The original sea ice drift vectors are provided from OSISAF (OSI-405), Ifremer (CERSAT), National Snow and Ice Data Center (Polar Pathfinder Daily 25 km EASE-Grid Sea Ice Motion Vectors, version 2) and Noriaki KIMURA at the National Institute of Polar Research, Japan. The uncertainties of respective products are assessed by high-resolution SAR data provided from Jet Propulsion Laboratory (Kwok et al., (2000)) based on the method described in Sumata et al. (2015). Note that only the two datasets (NSIDC and Kimura) give a full seasonal coverage. For other products summer ice drifts are not available due to limitations of sensor capability and the frequency used. There are additional missing months in some products due to technical problems of the sensors used.
OSI405-b
Source
European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) Ocean and Sea Ice Satellite Application Facility (OSISAF)
Satellite
SSMI/S (85 GHz), SSMIS (91 GHz), ASCAT, AMSR-E, AMSR2(37 GHz)
Resolution
62.5 km
Time period
2010-2015
Dataset
OSI405-b sea ice drift data (NetCDF)
Information
The OSI405-b product combines the single-sensor products to take the advantage of the different quality statistics of the different products and to compensate for missing data in each product. The product is continuously updated to exploit available satellite data with different operational periods. The latest version is OSI405c, which provides summer ice drift map as well as winter maps with uncertainty estimates.
OSI405-multi
Source
European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) Ocean and Sea Ice Satellite Application Facility (OSISAF)
Satellite
SSM/I (85 GHz), AMSR-E (37 GHz), ASCAT
Resolution
62.5 km
Time period
2006-2013
Dataset
OSI405-multi sea ice drift data (NetCDF)
Information
The OSI405-multi product combines the single-sensor products to take advantage of the different quality statistics of the different products and to compensate for missing data in each product. The merging method of the single-sensor products is described in Lavergne and Eastwood (2010) .
OSI405-amsr
Source
European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) Ocean and Sea Ice Satellite Application Facility (OSISAF)
Satellite
AMSR-E (37 GHz)
Resolution
62.5 km
Time period
2002-2006
Dataset
OSI405-amsr sea ice drift data (NetCDF)
Information
The OSI405-amsr product is a single-sensor product derived from Advanced Microwave Scanning Radiometer of the Earth Observation System (AMSR-E). A distinctive feature of the product is that a sequence of remotely sensed images is processed by the Continuous Maximum Cross-Correlation (CMCC) method, which builds on the Maximum Cross-Correlation (MCC) method but relies on a continuous optimization step for computing the motion vector (Lavergne et al., 2010).
CERSAT-merged
Source
Institut Français de Recherche pour l'Exploitation de la Mer (Ifremer)/CERSAT
Satellite
QuickSCAT, ASCAT, SSM/I (85 GHz)
Resolution
62.5 km
Time period
1991-2009
Dataset
CERSAT-merged sea ice drift data (NetCDF)
Information
The CERSAT-merged product is obtained from the combination of SSM/I 85GHz H/V brightness temperature maps and QuikSCAT backscatter map. The algorithms used to derive each single-sensor product are the same with that for CERSAT-amsr, and the merging process is described in Girard-Ardhuin et al. (2008).
CERSAT-amsr
Source
Institut Français de Recherche pour l'Exploitation de la Mer (Ifremer)/CERSAT
Satellite
AMSR-E (89 GHz)
Resolution
31.25 km
Time period
2002-2011
Dataset
CERSAT-amsr sea ice drift data (NetCDF)
Information
The CERSAT-amsr product is a single-sensor product derived from Advanced Microwave Scanning Radiometer of the Earth Observation System (AMSR-E). The algorithm used to derive CERSAT-amsr ice motion is the MCC method described in Ezraty et al. (2007). The ice motion is estimated from the displacement for 2, 3, and 6 day lags. The 6 day lag is particularly suitable to capture small displacements which cannot be detected by shorter time lags.
KIMURA
Source
Noriaki KIMURA / National Institute of Polar Research, Japan
Satellite
AMSR-E (89 GHz, 19 GHz), AMSR2
Resolution
Winter: 37.5 km, Summer: 75.0 km
Time period
2002-2011
Dataset
KIMURA sea ice drift data (NetCDF)
Information
The Kimura Product provides ice motion data from winter as well as summer. The winter ice drift (from December to April) is calculated from brightness temperature maps of AMSR-E 89 GHz H/V polarization channels, whereas the summer ice drift (from May to November) is obtained from those of 18.7 GHz channels. The algorithm used to deduce ice motions is the improved MCC method described in Kimura and Wakatsuchi (2000, 2004).
NSIDC
Source
Colorado University / National Snow and Ice Data Center
Satellite
AVHRR, SMMR, SSM/I, AMSR-E, IABP observations
Resolution
25.0 km
Time period
1980-2012
Dataset
NSIDC sea ice drift data (NetCDF)
Information
NSIDC (Polar Pathfinder Daily 25 km EASE-Grid Sea Ice Motion Vectors, Version 2) - The NSIDC product are sea-ice motions deduced from a variety of satellite-borne sensors (Advanced Very High Resolution Radiometer (AVHRR), Scanning Multichannel Microwave Radiometer (SMMR), SSM/I and AMSR-E, as well as the International Arctic Buoy Program (IABP) observations and wind effects on motion. Sea-ice motions are obtained from each satellite sensor using the MCC method and merged with the buoy data and winds using the cokriging method.
Literature
- Ezraty, R.; Girard-Ardhuin, F. and Piollé J.-F. (2007), Sea Ice Drift In The Central Arctic Estimated From Seawinds/QuikSCAT Backscatter Maps, User's Manual, Ver. 2.2, Laboratoire d’Océanographie Spatiale artement d’Océanographie Physique et Spatiale IFREMER, Brest, France.
- Girard-Ardhuin, F.; Ezraty, R.; Croizé-Fillon, D. and Piollé J.-F. (2008), A Sea Ice Drift in the Central Arctic Combining QuikSCAT and SSM/I Sea Ice Drift Data, User's Manual, Version 3.0 , Laboratoire d’Océanographie Spatiale artement d’Océanographie Physique et Spatiale IFREMER, Brest, France.
- Lavergne, T. and Eastwood, S. (2010), Low Resolution Sea Ice Drift Product User's Manual, GBL LR SID – OSI 405, The EUMETSAT Network of Satellite Application Facilities.
- Kimura, N. and M. Wakatsuchi (2000), Relationship between sea-ice motion and geostrophic wind in the Northern Hemisphere, Geophysical Research Letter, 27, 3735–3738, doi:10.1029/2000GL011495.
- Kimura, N. and M. Wakatsuchi (2004), Increase and decrease of sea ice area in the Sea of Okhotsk: Ice production in coastal polynyas and dynamical thickening in convergence zones, Journal of Geophysical Research, 109, C09S03, doi:10.1029/2003JC001901.
- Kwok, R.; Cunningham, G. F. and Nguyen D. (2000), Alaska SAR Facility RADARSAT Geophysical Processor System: Production Specification (Version 2.0), JPL D-13448, NASA Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California.
- Sumata, H.; Gerdes, R.; Kauker,F. and Karcher M. (2015), Empirical error functions for monthly mean Arctic sea-ice drift, Journal of Geophysical Research Oceans, 120, doi:10.1002/2015JC011151.
For the use of meereisportal.de, users are asked to include the following citation:
- Grosfeld, K.; Treffeisen, R.; Asseng, J.; Bartsch, A.; Bräuer, B.; Fritzsch, B.; Gerdes, R.; Hendricks, S.; Hiller, W.; Heygster, G.; Krumpen, T.; Lemke, P.; Melsheimer, C.; Nicolaus, M.; Ricker, R. and Weigelt, M. (2016), Online sea-ice knowledge and data platform <www.meereisportal.de>, Polarforschung, Bremerhaven, Alfred Wegener Institute for Polar and Marine Research & German Society of Polar Research, 85 (2), 143-155, doi:10.2312/polfor.2016.011 (PDF).
For the use of the specific data from the data portal of meereisportal.de, users are asked to include the associated citations as indicated below.
For all sea ice drift data, users are asked to include the following citation:
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OSISAF (OSI-405)
- Lavergne, T.; Eastwood, S.; Teffah, Z.; Schyberg, H.; and Breivik L.-A. (2010), Sea ice motion from low-resolution satellite sensors: An alternative method and its validation in the Arctic, Journal of Geophysical Research, 115, C10032, doi:10.1029/2009JC005958.
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Ifremer (CERSAT)
- Girard-Ardhuin, F.; and Ezraty, R. (2012), Enhanced Arctic sea ice drift estimation merging radiometer and scatterometer data, IEEE Transactions on Geoscience and Remote Sensing, 50(7), 2639–2648, doi:10.1109/TGRS.2012.2184124.
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NSIDC (Polar Pathfinder Daily 25km EASE-Grid Sea Ice Motion Vectors, version 2)
- Fowler, C., J. Maslanik, W. Emery, and M. Tschudi. 2013. Polar Pathfinder Daily 25 km EASE-Grid Sea Ice Motion Vectors. Version 2. (Daily and Mean Gridded Field), NASA National Snow and Ice Data Center Distributed Active Archive Center, Boulder, Colorado USA. doi:10.5067/LHAKY495NL2T
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KIMURA (ice drift product)
- Kimura, N.; Nishimura, A.; Tanaka, Y. and Yamaguchi, H. (2013), Influence of winter sea ice motion on summer ice cover in the Arctic, Polar Research, 32, 20193, doi:10.3402/polar.v32i0.20193.
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Uncertainty estimates
- Sumata, H.; Gerdes, R.; Kauker, R. and Karcher, M. (2015), Empirical error functions for monthly mean Arctic sea-ice drift, Journal Geophysical Research Oceans, 120, doi:10.1002/2015JC011151.
In case of questions or any difficulties, please contact us at: Meereisportal Team.