Examining Scattering Mechanisms of Bubbled Freshwater Lake Ice with Time-Series of RADARSAT-2 (C-band) and UW-Scat (X-, Ku-band) Polarimetric Observations.

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Examining Scattering Mechanisms of Bubbled Freshwater Lake Ice with Time-Series of RADARSAT-2 (C-band) and UW-Scat (X-, Ku-band) Polarimetric Observations Grant E. Gunn1, Claude R. Duguay2, Don Atwood3 1. Department of Geography, Environment and Spatial Sciences, Michigan State University, 673 Auditorium Road, East Lansing, Michigan, 48825, United States 2. Department of Geography and Environmental Management, University of Waterloo, 200 University Avenue West, Waterloo, Ontario, N2L 3G1, Canada 3. Michigan Technological Research Institute, 600 Green Ct. #100, Ann Arbor, MI 48105, United States Introduction Results Results Continued Lakes comprise 2% of globally available freshwater, and play significant role in the biological, chemical and physical processes in the cold-regions water cycle [1]. Knowledge of the surface and thermal state of lakes is useful in numerical weather prediction or regional climate models for regions where lakes comprise a large portion of the landscape [2]. Lake ice phenology and thickness are useful indicator for change in climate, as Arctic regions have exhibited amplified warming [3]. Recent studies have introduced case for single-bounce interaction from floating bubbled lake ice whereby the incident microwave signal is insensitive to presence of tubular bubbles, contrary to previous double-bounce hypothesis [4]. This paper presents a time-series of in-situ ground based X- (9.6 GHz) and Ku-band (17.2 GHz) observations collected during winter 2009-2010 using University of Waterloo scatterometer (UW-Scat) coincident to C-band (5.3 GHz) RADARSAT-2 quad-pol acquisitions to further assess scattering mechanisms in tubular-bubbled freshwater ice on Malcolm Ramsay Lake near Churchill, Manitoba. Distance between Peak 1 and 2 returns ( 𝑑 𝑠 ) in range of UW-Scat are related to ice thickness through 𝑑 𝑠 = 2 𝑑 𝑚𝑒𝑎𝑠 cos 𝜃 where 𝑑 𝑚𝑒𝑎𝑠 is measured ice thickness and 𝜃 is UW-Scat incidence angle. Fig. 4 confirms that peak UW-Scat returns correspond to snow-ice and ice-water interface accounting for refractive index of ice. What scattering mechanism occurs at the ice-water interface? Fig. 4: Verification of assumption of interactions at the snow-ice and ice-water interface represented by Peak 1 and 2 in range. P2 – P1 for X- and Ku-band tracked slant range and measured ice thickness with a near 1:1 relationship. Backscatter Mechanisms in Ice Co-pol Phase Difference ( ∆𝝓 𝑯𝑯𝑽𝑽 ) ∆𝝓 𝑯𝑯𝑽𝑽 generated from UW-Scat processing software; from RADARSAT-2 acquisitions by applying band maths to the covariance matrix in Sentinel Application Platform (SNAP): ∆𝝓 𝑯𝑯𝑽𝑽 = tan −1 ℑ (𝑅 ℎ / 𝑅 𝑉 ) ℜ (𝑅 ℎ / 𝑅 𝑉 ) As per established understanding of ∆𝝓 𝑯𝑯𝑽𝑽 , Single Bounce: ∆𝝓 𝑯𝑯𝑽𝑽 = 0⁰ Double Bounce: ∆𝝓 𝑯𝑯𝑽𝑽 = +/- 180⁰ Volume Scatter: ∆𝝓 𝑯𝑯𝑽𝑽 = uniform phase difference across angles. Backscatter from ice is dependent on: the difference in permittivity properties of the media in the sensor field of view, microwave interaction with scattering centers at media interfaces or within the snow or ice volume. Interface Surfaces: The magnitude of the signal scattered back to the sensor from a surface is proportional to the surface roughness (RMS of height deviations & correlation length). Inclusions: Several studies identified tubular bubbles as a strong source of double bounce backscatter over freshwater ice. Recent work suggests the diameter and contrast in dielectrics presented by tubular bubbles acts as anisotropic homogenous medium with modified permittivity parameters through the effective medium theory) [5]. Fig. 7: RADARSAT-2 σ° (VV (A), HH (B), VH (C)), Yamaguchi decomposition showing surface (D), double (E) and volume scatter (F). UW-Scat (Fig 5): ∆𝝓 𝑯𝑯𝑽𝑽 at all sites on lake for all dates with returns near ice-snow (Peak 1) and ice-water (Peak 2) interface observed: ∆𝝓 𝑯𝑯𝑽𝑽 Peak 1: centred at 0⁰, little variability. ∆𝝓 𝑯𝑯𝑽𝑽 Peak 2: centred at 0⁰ with increase in variability (+/- 150⁰) Polarimetric Decomposition Yamaguchi 3-component decomposition produced for time-series of RADARSAT-2 FQ11 acquisitions (Fig. 7, 8). Surface Bounce identified as dominant scattering mechanism contributing to overall σ°, on average 10/14 times greater in intensity than volume/double-bounce, respectively. Volume scatter is second largest contributor with the exception of Site 4, with thin surface ice types observed (lowering depolarizing scatter potential). Spatial variability of surface-, double-, and volume-scatter indicates regional variability in geophysical parameters related to each scattering mechanism. Fig. 1: UW-Scat static observation sites on Malcolm Ramsay Lake, near Churchill, Manitoba, Canada. Fig. 5: UW-scat co-pol phase difference ( ∆𝝓 𝑯𝑯𝑽𝑽 ) for Peak 1 (A, C) and Peak 2 (B, D) at all floating sites. Observations were collected for over a range of (21 - 60°). Data Fig. 8: Time series of RADARSAT-2 FQ11 Yamaguchi decomposition for whole lake RADARSAT-2: ∆𝝓 𝑯𝑯𝑽𝑽 for late season scenes for beam modes FQ1, FQ11, FQ 18 (Fig 6). Lake-wide ∆𝝓 𝑯𝑯𝑽𝑽 centred at 0⁰ with standard deviation of +/-2.75⁰ across beam modes. Conclusions Meteorological station observations collected at north edge of lake (Fig 2). In-situ sampling (Sites 1 – 4) (Fig 3). -Snow pits (depth, density, stratigraphy) Ice thickness, cores. UW-Scat (X-, Ku-bands) (σ°) - VV, VH, HH, HV - 21 – 60⁰ incidence angle. RADARSAT-2 acquisitions (σ°) - 4 beam modes (FQ1, FQ11, FQ18, FQ21) - Full winter time series coincident with UW-SCAT. Co-pol phase difference ( ∆𝝓 𝑯𝑯𝑽𝑽 ) - UW-Scat & RADARSAT-2 Yamaguchi decomposition (RADARSAT-2) Co-pol phase difference at C-, X-, Ku-band and 3-component Yamaguchi decomposition provide evidence that odd/surface-bounce is the primary scattering mechanism from the ice-water interface. Proposed physical mechanisms controlling surface bounce at ice-water interface to be surface roughness at two scales (Fig. 9): Increase in bubble density terminus protruding from ice-water interface (small scale). Orientation of facets at ice-water interface produce confluence of angles that produce local mirror-like geometry (large scale). Future Work: Further test hypothesis; obtain accurate measurements of RMS roughness and correlation length of ice-water interface. Fig. 2: Meterological station wind speed (A) and air temperature (B) collected on the north shoreline during UW-Scat and SAR observation period. Fig. 6: Lake-wide ∆𝝓 𝑯𝑯𝑽𝑽 for late- winter RADARSAT-2 acquisitions at FQ1, FQ11, and FQ 18. ∆𝝓 𝑯𝑯𝑽𝑽 Interpretation for Bubbled Lake Ice ∆𝝓 𝑯𝑯𝑽𝑽 centred at 0⁰ for C-, X-, and Ku-bands suggest dominant single or odd-bounce interaction with the ice-water interface for floating ice tubular bubble inclusions, contrary to double-bounce hypothesis for floating lake ice. ∆𝝓 𝑯𝑯𝑽𝑽 distribution variability increases in Fig 5B, D for interactions near the ice-water interface at X- and Ku-band; indicate presence of an additional scattering mechanism. With increase in n, would ∆𝝓 𝑯𝑯𝑽𝑽 begin to resemble histogram synonymous with volume & single/odd bounce? Fig. 9: Updated contribution of scattering mechanisms to total backscatter as determined by Yamaguchi three-component decomposition. Fig. 3: In-situ snow and ice properties for Sites 1 – 4 (A – D). Ice stratigraphy derived from ice cores extracted at the end observation period (4/4/2010). [1] L. C. Brown & C. R. Duguay, “The response and role of ice cover in lake-climate interactions,” Prog. Phys. Geogr., vol. 34, no. 5, pp. 671–704, Jul. 2010; [2] H. Kheyrollah Pour, L. Rontu, C. Duguay, K. Eerola, & E. Kourzeneva, “Impact of satellite-based lake surface observations on the initial state of HIRLAM. Part II: Analysis of lake surface temperature and ice cover,” Tellus A, vol. 66, 21395, 2014. [3] J. E., Overland, E. Hanna, I. Hanssen-Bauer, S. J. Kim, J. Walsh, M. Wang, & U. S. Bhatt, U. S. “Air Temperature,” in Arctic Report Card, 2014. M. O. Jeffries, J. Richter-Menge, and J. E. Overland, 2014. [4] D. Atwood, G. E. Gunn, C. Roussi, J. Wu, C. Duguay, & K. Sarabandi, “Microwave Backscatter from Arctic Lake Ice and Polarimetric Implications,” IEEE Trans. Geosci. Remote Sens., vol. 53, no. 11, pp. 5972-5982, 2015. [5] J. Wu, D. Atwood & K. Sarabandi, "Scattering phenomenology of arctic lake ice," 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Beijing, pp. 3668-3671, 2016. This research was made possible with financial support from the European Space Agency (ESTEC Contracts No. 4000103590/11/NL/FF/fk and 4000106960/12/NL/BJ/lf) and the NSERC to C. Duguay, and G. Gunn. Logistics for field data collection was provided by the Churchill Northern Studies Centre. The authors would like to thank all those that assisted in field work. RADARSAT-2 Data and Product © MacDonald, Dettwiler and Associates Ltd. (2010) – All Rights Reserved.