Global Estimates of Extreme Wind Speed and Wave Height

J. Vinoth Faculty of Engineering and Industrial Sciences, Swinburne University of Technology, Melbourne, Australia

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I. R. Young Faculty of Engineering and Industrial Sciences, Swinburne University of Technology, Melbourne, Australia

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Abstract

A long-term dataset of satellite altimeter measurements of significant wave height and wind speed, spanning 23 years, is analyzed to determine extreme values corresponding to a 100-yr return period. The analysis considers the suitability of both the initial distribution method (IDM) and peaks-over-threshold (POT) approaches and concludes that for wave height both IDM and POT methods can yield reliable results. For the first time, the global POT results for wave height show spatial consistency, a feature afforded by the larger dataset. The analyses also show that the POT approach is sensitive to spatial resolution. Since wind speed has greater spatial and temporal variability than wave height, the POT approach yields unreliable results for wind speed as a result of undersampling of peak events. The IDM approach does, however, generate extreme wind speed values in reasonable agreement with buoy estimates. The results show that the altimeter database can estimate 100-yr return period significant wave height to within 5% of buoy measurements and the 100-yr wind speed to within 10% of buoy measurements when using the IDM approach. Owing to the long dataset and global coverage, global estimates of extreme values can be developed on a 1° × 1° grid when using the IDM and a coarser 2° × 2° for the POT approach. The high-resolution 1° × 1° grid together with the long duration of the dataset means that finescale features not previously identified using altimeter data are clearly apparent in the IDM results. Goodness-of-fit tests show that the observed data conform to a Fisher–Tippett Type 1 (FT-1) distribution. Even in regions such as the Gulf of Mexico where extreme forcing is produced by small-scale hurricanes, the altimeter results are consistent with buoy data.

Corresponding author address: I. R. Young, Vice-Chancellor, Swinburne University of Technology, P.O. Box 218, Hawthorn, VIC 3122, Australia. Email: iyoung@swin.edu.au

Abstract

A long-term dataset of satellite altimeter measurements of significant wave height and wind speed, spanning 23 years, is analyzed to determine extreme values corresponding to a 100-yr return period. The analysis considers the suitability of both the initial distribution method (IDM) and peaks-over-threshold (POT) approaches and concludes that for wave height both IDM and POT methods can yield reliable results. For the first time, the global POT results for wave height show spatial consistency, a feature afforded by the larger dataset. The analyses also show that the POT approach is sensitive to spatial resolution. Since wind speed has greater spatial and temporal variability than wave height, the POT approach yields unreliable results for wind speed as a result of undersampling of peak events. The IDM approach does, however, generate extreme wind speed values in reasonable agreement with buoy estimates. The results show that the altimeter database can estimate 100-yr return period significant wave height to within 5% of buoy measurements and the 100-yr wind speed to within 10% of buoy measurements when using the IDM approach. Owing to the long dataset and global coverage, global estimates of extreme values can be developed on a 1° × 1° grid when using the IDM and a coarser 2° × 2° for the POT approach. The high-resolution 1° × 1° grid together with the long duration of the dataset means that finescale features not previously identified using altimeter data are clearly apparent in the IDM results. Goodness-of-fit tests show that the observed data conform to a Fisher–Tippett Type 1 (FT-1) distribution. Even in regions such as the Gulf of Mexico where extreme forcing is produced by small-scale hurricanes, the altimeter results are consistent with buoy data.

Corresponding author address: I. R. Young, Vice-Chancellor, Swinburne University of Technology, P.O. Box 218, Hawthorn, VIC 3122, Australia. Email: iyoung@swin.edu.au

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