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Dash, Mihir K.
- Recent Trends in Wind-Wave Climate for the Indian Ocean
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Authors
Affiliations
1 Department of Ocean Engineering and Naval Architecture, Indian Institute of Technology, Kharagpur 721 302, IN
2 Centre for Oceans, Rivers, Atmosphere and Land Sciences, Indian Institute of Technology, Kharagpur 721 302, IN
1 Department of Ocean Engineering and Naval Architecture, Indian Institute of Technology, Kharagpur 721 302, IN
2 Centre for Oceans, Rivers, Atmosphere and Land Sciences, Indian Institute of Technology, Kharagpur 721 302, IN
Source
Current Science, Vol 108, No 12 (2015), Pagination: 2191-2201Abstract
Surface gravity waves play an important role in ocean engineering studies and their influence on the dynamics of the coastal zone is critical. Proper knowledge on wind-wave climatology is an area of immense interest to engineers and climate modellers. Climate change has influenced weather patterns over global oceans and at present is a matter of serious concern, as it can have long-term repercussions. There is a need to understand the recent trends in variability of windwaves for planning operations. To improve climate projections the Intergovernmental Panel on Climate Change report highlights the need and importance for wind-wave climate study. With this motivation, we study the variability of recent trends in maximum wind speed (MWS) and maximum significant wave height (MSWH) exclusively based on altimeter data for the Indian Ocean basin. We use daily data of MWS and MSWH from eight satellite missions covering a period of 21 years (1992-2012). The findings indicate that regions in the Southern Ocean (between 45°S and 55°S) experienced the largest variability in wind-wave climate. Higher MSWH resulting from increased MWS has practical implications on swell generation field that eventually cross the hemisphere influencing wind-waves elsewhere. The study also reveals the impact of wind-wave activity for the Indian Ocean basin in the past decade.Keywords
Climate, Indian Ocean, Maximum Wave Height, Maximum Wind Speed, Satellite Observations.- Prediction of Sea Ice Edge in the Antarctic Using GVF Snake Model
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Authors
Affiliations
1 Royal Institute of Technology, Stockholm, SE
2 Indian Institute of Technology, Kharagpur, IN
1 Royal Institute of Technology, Stockholm, SE
2 Indian Institute of Technology, Kharagpur, IN
Source
Journal of Geological Society of India (Online archive from Vol 1 to Vol 78), Vol 78, No 2 (2011), Pagination: 99-108Abstract
Antarctic sea ice cover plays an important role in shaping the earth's climate, primarily by insulating the ocean from the atmosphere and increasing the surface albedo. The convective processes accompanied with the sea ice formation result bottom water formation. The cold and dense bottom water moves towards the equator along the ocean basins and takes part in the global thermohaline circulation. Sea ice edge is a potential indicator of climate change. Additionally, fishing and commercial shipping activities as well as military submarine operations in the polar seas need reliable ice edge information. However, as the sea ice edge is unstable in time, the temporal validity of the estimated ice edge is often shorter than the time required to transfer the information to the operational user. Hence, an accurate sea ice edge prediction as well as determination is crucial for fine-scale geophysical modeling and for near-real-time operations. In this study, active contour modelling (known as Snake model) and non-rigid motion estimation techniques have been used for predicting the sea ice edge (SIE) in the Antarctic. For this purpose the SIE has been detected from sea ice concentration derived using special sensor microwave imager (SSM/I) observations. The 15% sea ice concentration pixels are being taken as the edge pixel between ice and water. The external force, gradient vector flow (GVF), of SIE for total the Antarctic region is parameterised for daily as well as weekly data set. The SIE is predicted at certain points using a statistical technique. These predicted points have been used to constitute a SIE using artificial intelligence technique, the gradient vector flow (GVF). The predicted edge has been validated with that of SSM/I. It is found that all the major curvatures have been captured by the predicated edge and it is in good agreement with that of the SSM/I observation.Keywords
Sea Ice Modelling, Sea Ice Edge, Snake Model, Antarctica.References
- CHENYANG, Xu and PRINCE, J.L. (1997) Gradient Vector Flow: A New External Force for Snakes, Proc. IEEE Conf. on Comp. Vis. Patt. Recog. (CVPR), Los Alamitos: Comp. Soc. Press, pp.66-71, June 1997.
- COHEN, L.D. (1991) Note on active contour models and balloons. CVGIP: Image Understanding, v.53, pp.211-218.
- COMISO, J.C., CAVALIERI, D., PARKINSON, C. and GLOERSEN, P. (1997) Passive microwave algorithms for sea ice concentrations. Remote Sensing of the Environment, v.60, pp.357-384.
- GLOERSON, P., CAMPBE, W.J., CAVALIER, D.J., COMISO, J.C., PARKINSON C.L. and ZWALLY H.J. (1992) Arctic and Antarctic Sea Ice:178-1987. NASA-SP_511, 290p.
- KASS, M., WITKIN, A. and TERZOPOULOS, D. (1987) Snakes: The Active contour models. Internat. Jour. Computer Vision, v.1, pp.321-331.
- LAMB, H.H. (1982) The climate environment of the Arctic Ocean. In: L. Ray (Ed.), The Arctic Ocean. John Wiley and Sons, New York, pp.135-161
- VOWINCKELL, E. and ORWING, S. (1970) The climate in the north polar basin, climate of the polar regions. World Survey of Climatology, Elsevier, Amsterdam, v.14, pp.129-252.
- VYAS, N.K., DASH, M.K., BHANDARI, S.M., KHARE, N., MITRA, A. and PANDEY, P.C. (2003) On the secular trend in sea ice extent over the Antarctic region based on OCEANSAT - 1 MSMR Observations. Internat. Jour. Remote Sensing, v.24, pp.2277- 2287.