Evaluation of Passive Microwave Sea Ice Concentration in Arctic Summer and Antarctic Spring by Using KOMPSAT-1 EOC Hoonyol Lee and Hyangsun Han E-Mail:

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Presentation transcript:

Evaluation of Passive Microwave Sea Ice Concentration in Arctic Summer and Antarctic Spring by Using KOMPSAT-1 EOC Hoonyol Lee and Hyangsun Han Kangwon National University, Chuncheon, Kangwon , Republic of Korea Passive microwave sensors such as the SSM/I and the AMSR-E have been observing polar sea ice concentration (SIC) playing important roles in the global climatic and environmental studies. To evaluate the passive microwave SIC we observed sea ice with the 6 m-resolution, Electro-Optical Camera (EOC) sensor onboard KOMPSAT-1 satellite. A total of 72 cloud-free EOC images, 18 km x 18 km each, of arctic sea ice edges were obtained from July to August and 68 images across the antarctic continental edges from September to November, We classified arctic sea ice types into land-fast ice, pack ice, and drift ice according to ice distribution and movement characteristics, and compared with SSM/I SIC calculated from NASA Team (NT) algorithm. The correlations between EOC and SSM/I SICs were related to the spatiotemporal stability of sea ice in arctic summer showing high correlation for stable land-fast ice and low for less stable pack ice and drift ice. In case of pack ice, SSM/I SIC were lower than EOC SIC by 19.63% in average due to the underestimation problem of NT algorithm for ice ridge and new ice. For drift ice, SSM/I SIC showed 20.17% higher than EOC SIC in average partly due to wider IFOV of SSM/I than EOC swath resulting in the insertion of pack ice nearby and partly due to the condition of wet snow on drift ice causing overestimation in NT algorithm. In the Antarctic spring, sea ice types in the EOC images, mostly of land fast ice or pack ice, were classified into white ice (W), grey ice (G), and dark-grey ice (D) and then compared with SSM/I NT and AMSR-E NT2 SICs. EOC SIC of W and G, excluding D, showed best fit to SSM/I NT SIC suggesting that the SSM/I NT algorithm responds to young ice in addition to multi-year ice and first- year ice while AMSR-E SIC responds to all types of sea ice. I. The Arctic Sea Ice KOMPSAT-1 EOC orbits (red lines) for the Arctic. The relationship between EOC and SSM/I NT SIC of the Arctic. The vertical bars are the spatio-temporal standard deviation of SIC for SSM/I cubic pixels ( ). Black points: Land-fast ice Red points: Pack ice. Blue points: Drift ice. I - i. Land-fast Ice I - ii. Pack Ice I - ii. Drift Ice II. The Antarctic Sea Ice KOMPSAT-1 EOC orbits (red lines) for the Antarctic. Classification of EOC ice types W: White ice G: Grey ice D: Dark-grey ice O: Open water SSM/I NT vs. EOCAMSR-E NT2 vs. EOC PM SIC EOC Algorithm SSM/I NASA Team AMSR-E NASA Team 2 StabilityStableUnstableAllStableUnstableAll 1.2%4.2%2.1%0.7%7.5%2.8% W 4.2%18.1%8.1%11.8%16.2%13.1% RMSE6.2%25.5%14.4%17.9%21.2%18.8% W+G -2.3% -3.1%-2.5%3.0%1.3%2.5% RMSE 3.2% 7.9%4.9%4.6%8.7%6.0% W+G+D -4.5%-13.3%-7.0% 0.3% -7.3%-1.9% RMSE5.1%14.8%9.0% 1.4% 12.2%6.7% Statistics on the comparisons between SSM/I NT, AMSR-E NT2, and EOC SICs. III. Conclusion W O G D W: 51.8%, G: 29.0%, D: 13.0% AMSR-E: 89%, SSM/I: 80% AMSR-E – SSM/I: 9% W: 97.4%, G: 1.0%, D: 0.5% AMSR-E: 98%, SSM/I: 96% AMSR-E – SSM/I: 2% O W D G W O G G, D (a) A portion of KOMPSAT-1 EOC image (Greenland Sea, 2 km×2 km) on 25 August (b) ENVISAT ASAR image (Greenland Sea, 100 km×100 km) on 25 August 2005 is overlaid by KOMPSAT-1 EOC images obtained on the same day. (c) The relationship between SSM/I NT SIC and EOC SIC of land-fast ice. (a) A portion of KOMPSAT-1 EOC image (Laptev Sea, 2 km×2 km) on 12 July (b) ENVISAT ASAR image (Laptev Sea, 100 km×100 km) on 11 July 2005 is overlaid by KOMPSAT-1 EOC images obtained on 12 July (c) The relationship between SSM/I NT SIC and EOC SIC of pack ice. (a) A portion of KOMPSAT-1 EOC image (Greenland Sea, 2 km×2 km) on 25 August (b) ENVISAT ASAR image (Greenland Sea, 100 km×100 km) on 25 August 2005 is overlaid by KOMPSAT-1 EOC images obtained on the same day. (c) The relationship between SSM/I NT SIC and EOC SIC of drift ice. Comparison of AMSR-E NT2 and SSM/I NT SIC data point used for the comparisons with EOC SIC. AMSR-E NT2 SIC shows generally higher value than SSM/I NT SIC by 4.7% due to the detection of ice type C and thin ice for the Antarctic sea ice in the NT2 algorithm in addition to ice type A and B in the NT algorithm. Comparison of SSM/I and AMSR-E SIC data points used for the comparisons with EOC SIC. AMSR-E SIC shows generally higher value than SSM/I SIC by 4.7% due to the detection of ice type C and thin ice for the Antarctic sea ice in the AMSR-E NT2 algorithm in addition to ice type A and B in the SSM/I NT algorithm. Comparison of SSM/I SIC with EOC SICs of (a) W, (b) W+G, and (c) W+G+D. Stable (black) points are SIC with < 2.5%. SSM/I SIC correlates well with EOC SIC of white and grey ice (W+G) in (b) both for stable SICs and all SICs. Comparison of AMSR-E SIC with EOC SICs of (a) W, (B) W+G, and (c) W+G+D. AMSR-E SIC of stable (black) points correlates well with the summation of all ice types of EOC SIC in (c), indicating that AMSR-E SIC responds to dark-grey ice in addition to white and grey ice. (a)(b) (c) (a) (b) (c) (a)(b) (c) (a) (b) (c) (a) (b) (c)