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Sea Ice Studies in the Northern Sea Route by Use of Synthetic Aperture Radar

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Sea Ice Studies in the Northern Sea Route by Use of Synthetic Aperture Radar NERSCNERSC Nansen Environmental and Telemark University College Remote Sensing Center Sea Ice Studies in the Northern Sea Route by use of Synthetic Aperture Radar by Maria Lundhaug Dr. Ing. Thesis February 2002 the Norwegian University of Science and Technology URN:NBN:no-2344 Abstract The main objective of this thesis is to contribute to the understanding of sea ice pro- cesses in the Northern Sea Route, mainly with use of remote sensing data from Synthetic Aperture Radar (SAR). Multivariate data analysis is the main tool used in this work. SAR signatures of different sea ice types and open water in winter were studied, and separation of water and sea ice types using different multivariate regression algorithms was done. Polynya areas along the coasts were investigated. Structure characteristics of different sea ice types and open water were investigated. The summer sea ice in the Laptev Sea was also studied. The Laptev Sea as well as other parts of the Northern Sea Route are expected to become important areas for future oil and gas exploration and exploitation. Results from a statistical analysis of 105 SAR images and corresponding meteorological data are presented, covering parts of the Pechora and Kara Sea in the Russian Arctic. Wind, temperature and other variables for the SAR sample areas were collected, and a manual sea ice classification of the SAR samples was performed. All variables were input to different multivariate regression techniques. First, ice was separated from water. Next, young ice was separated from rough first year ice. The study indicated that the mean and standard deviation of the backscattering coefficients together with temperature values were the most important information to separate the classes. SAR image data has been used to investigate specific polynya events in detail, addressing widths, refreezing and duration. A polynya index derived from ice concentration data from Special Sensor Microwave Imager (SSM/I) was used in the description of polynya variability during a decade (1990-1999) in response to atmospheric forcing. The observed polynya widths were compared to the results from a simple one-dimensional polynya model. The best agreement was found for the Vize and Ushakova Island and the Novaya Zemlya coast due to low variability of polynya widths. Less agreement was found at the Yamal and Taymyr due to high polynya variability not captured by the model. Sample areas of open water, young ice and first year ice were investigated by the angle measure technique (AMT) and classified by multivariate regression. The separation of ice and water was relatively sucessfull, opposed to the separation of young ice and first year ice. The individual samples were best separated on one pixel scale, corresponding to backscattering differences between neighboring pixels. The AMT produce mean angle information that to some extent can be related to ice type. URN:NBN:no-2344 i Finally, a demonstration and validation study of the capabilities of SAR imagery to pro- vide accurate ice information to support ice navigation was carried out. The experiment was set up in August-September 1997. RADARSAT and ERS-2 SAR images combined with SSM/I data and in situ observations from icebreakers were used. These data were used to analyze ice concentration, ice types, ice drift and other ice features present in this period. The capability of RADARSAT ScanSAR and ERS SAR images to determine these ice parameters during late summer conditions in the Laptev Sea area is discussed. URN:NBN:no-2344 ii Acknowledgments This work was funded by a dr. ing. grant from Telemark University College (HiT), Department of Technology, Porsgrunn, Norway with further support from Nansen Envi- ronmental and Remote Sensing Center (NERSC), Bergen, Norway. I would like to thank my supervisors Prof. Kim H. Esbensen (HiT) and Prof. Ola M. Johannessen (NERSC) for their valuable comments and suggestions during the writing of the thesis. Research Director Stein Sandven (NERSC) has reviewed my work and suggested research approaches. I would also like to thank all the people at NERSC and HiT who have helped and encouraged me in different ways. The work during these three years would have been much harder without the support and encouragement from Tor, my parents, Kamilla and good friends. Non numeranda, sed ponderanda argumenta. URN:NBN:no-2344 iii Contents 1 Introduction 1 1.1 Background ................................. 1 1.1.1 Northern Sea Route . ...................... 1 1.1.2 Sea ice in the Arctic . ...................... 3 1.1.3 Sea ice as a sensitive indicator of climate change . ...... 7 1.1.4 Sea ice transport of sediments and pollution . ........... 9 1.2 Objectives . ................................. 12 1.3 Approach . ................................. 14 1.4 General outline of the thesis . ...................... 14 2 Remote sensing of sea ice 18 2.1 Background ................................. 18 2.2 Active microwave remote sensing of sea ice ................ 19 2.3 Passive microwave remote sensing of sea ice ................ 31 2.4 Physical basis for microwave remote sensing of sea ice .......... 44 2.5 Problems in remote sensing of sea ice . ................. 45 3 ERS SAR studies of sea ice signatures in the Pechora and Kara Sea region 48 3.1 Introduction ................................. 49 3.1.1 Background . ............................ 49 URN:NBN:no-2344 iv 3.1.2 Description of the Pechora and Kara Sea region .......... 50 3.2 Data analysis ................................ 53 3.2.1 SAR data . ............................ 53 3.2.2 Temperature and wind data ..................... 54 3.2.3 SAR analysis ............................ 54 3.2.4 Sea ice classification . ...................... 55 3.3 Results and discussion ........................... 59 3.3.1 Multivariate regression . ...................... 64 3.4 Summary . ................................. 69 4 SAR and SSM/I study of coastal polynyas in the Pechora and Kara Seas 71 4.1 Introduction ................................. 73 4.1.1 General review of polynyas in the Arctic . ........... 73 4.1.2 Polynyas and other ice characteristics in the Pechora and Kara Seas 74 4.1.3 Outline of the paper . ...................... 77 4.2 Data sets, analysis methods and model description . ........... 77 4.2.1 SAR ................................. 77 4.2.2 SSM/I ................................ 80 4.2.3 NCEP data . ............................ 80 4.2.4 Polynya model ........................... 81 4.3 Results of data analyses and model calculations . ........... 83 4.3.1 Description of specific polynya events . ........... 83 4.3.2 Polynya widths from SAR ..................... 90 4.3.3 Polynya backscattering characteristics from ERS SAR ...... 94 4.3.4 Polynya index from SSM/I analysis ................ 97 4.3.5 Model results ............................ 98 URN:NBN:no-2344 v 4.4 Summary and discussion..........................102 5 The angle measure technique applied to ERS SAR data 107 5.1 Introduction .................................108 5.2 Data sets . .................................110 5.2.1 ERS-1/2 SAR data . ......................110 5.2.2 Temperature data ..........................111 5.3 Data analysis ................................113 5.3.1 Angle measure technique ......................113 5.3.2 Multivariate regression . ......................114 5.4 Results and discussion ...........................115 5.4.1 Characterization of SAR samples by AMT . ...........115 5.4.2 Multivariate regression . ......................118 5.5 Conclusion .................................124 6 Sea ice investigations in the Laptev Sea area in late summer using SAR data 126 6.1 Introduction .................................127 6.2 Data acquisition and icebreaker expedition .................129 6.2.1 Use of passive microwave satellite (SSM/I) data ..........129 6.2.2 Acquisition and processing of SAR data . ...........130 6.2.3 Data transmission to I/B Sovetsky Soyuz . ...........130 6.2.4 Meteorological data . ......................133 6.2.5 Preprocessing of the SAR images .................133 6.3 Characterization of ice conditions from SAR data . ...........134 6.3.1 August 10-11: Nordenskjold Archipelago and western Vilkitsky Strait . ......................134 URN:NBN:no-2344 vi 6.3.2 August 14-17: First ScanSAR survey of Vilkitsky Strait area and western Laptev Sea . ...........136 6.3.3 August 26-31: Repeated ScanSAR survey of Vilkitsky Strait and western Laptev Sea . ......................137 6.3.4 September 3-6: ScanSAR coverage of more ice areas in western Laptev Sea and around New Siberian Islands . ......140 6.4 Validation of SAR ice observation using icebreakers . ...........140 6.5 Example of comparison of RADARSAT and ERS data ..........146 6.6 Ice concentration analysis ..........................151 6.7 Discussion and conclusions . ......................154 7 Summary and conclusion 160 7.1 Future work .................................164 A Multivariate statistical methods 168 A.1 Introduction .................................168 A.2 Descriptive statistics ............................168 A.2.1 Basic definitions ..........................168 A.2.2 Vector and matrix algebra .....................170 A.2.3 Symmetric matrices . ......................171 A.3 Multivariate linear regression . ......................171 A.3.1 Classical linear regression model . .................171 A.3.2 Multivariate multiple regression . .................172 A.3.3 Model fit . ............................173 A.4 Principal component analysis
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