Estimation of extreme wave heights using GEOSAT measurements

Panchang, Vijay; Zhao, Liuzhi; Demirbilek, Zeki

doi:10.1016/s0029-8018(97)10026-9

Cited by 38 publications

(27 citation statements)

References 21 publications

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“…However, as polar-orbiting satellites revisit the same location once every 10-35 days, the temporal resolution is very poor for wave measurement. Within the context of extreme value statistics, this problem is addressed by Cooper and Forristall (1997), Panchang et al (1999), and Anderson et al (2001). A common approach has been to bin data into larger geographical areas, (e.g., 28 3 28), with assumed statistical homogeneous wave conditions.…”

Section: Introductionmentioning

confidence: 99%

Wave Extremes in the Northeast Atlantic

2012

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The objective of this study is to compute 100-yr return value estimates of significant wave height using a new hindcast developed by the Norwegian Meteorological Institute. This regional hindcast covers the northeast Atlantic and spans the period 1958-2009.The return value estimates are based upon three different stationary models commonly applied in extreme value statistics: the generalized extreme value (GEV) distribution, the joint GEV distribution for the r largest-order statistic (rLOS), and the generalized Pareto (GP) distribution. Here, the qualitative differences between the models and their corresponding confidence intervals are investigated.

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Section: Introductionmentioning

confidence: 99%

Wave Extremes in the Northeast Atlantic

2012

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“…Although the altimeter can only provide a measure of wave height (and, less directly, wave period), it has given good coverage of the oceans since 1985. The data have proved useful for wave climatologies (Barstow & Krogstad 1995;Josberger & Mognard 1996;Young & Holland 1996;Cotton et al 1997), estimation of extreme waves (Carter et al 1993;Cooper & Forristall 1997;Panchang et al 1999), and verification of wave model simulations (Laing 1992;Romeiser 1993;Sterl et al 1998). …”

Section: Introductionmentioning

confidence: 99%

New Zealand wave climate from satellite observations

Laing

2000

New Zealand Journal of Marine and Freshwater Research

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Wave data derived from radar altimeters carried on four satellite missions are combined into a wave climatology for New Zealand waters. These data provide extensive observations of wave conditions around New Zealand, where the paucity of measurements has previously hindered definition of the wave climate. The data span the period 1985 to the present with the exception of a 2-year gap in 1989-91. The spatial distribution of the long-term mean of significant wave heights (SWH) indicates a strong latitudinal variation in the south-west Pacific, with values of over 4 m at latitudes of 50-60°S and under 2.5 m towards the tropics. The shadowing of New Zealand is quite marked; a result of the dominant contribution of south-westerly wave events. The annual range of the mean SWH also varies over the region; within 0.6 m in the north and 1.3 m in the south. A principal component analysis of the monthly anomalies in mean SWH identifies spatial patterns of variation. Some components vary with the local wind more than others suggesting that some anomalies are associated with wind sea and some with swell. Some patterns also appear to vary with the Southern Oscillation Index and can be related to the wind anomalies associated with El Nino events. Frequency distributions of SWH are also determined, and it is noted that in the north of the region the spatial pattern of the high waves differs considerably from the means. M99071

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“…In particular, these authors stated that radii of 100 -200 km would yield reliable estimation of 50-yr extreme 5 wave heights. In a similar exercise, Panchang et al (1999) arrived at the same conclusions about the usefulness of satellite track data within an area with a radius of 200 km. According to the balance between spatial and temporal resolution is partially accomplished by using a multiplatform altimeter data, obtaining a mesoscale variability of 100 to 300 km.…”

Section: Validated Swh Modeled Results Inmentioning

confidence: 60%

“…This has been solved by averaging satellite track data from multiple missions 20 within a certain quadrangle (latitude, longitude). The first attempts to analyze extreme wave heights were carried out by Carter (1993), Cooper and Forristall (1997) and Panchang et al (1999). Carter (1993) computed monthly mean values of SWH in 2 • latitude × 2 • longitude bins and compared them with buoy data.…”

Section: Validated Swh Modeled Results Inmentioning

confidence: 99%

Estimation of extreme wave heights return period from short-term interpolation of multi-mission satellite data: application to the South Atlantic

Salcedo-Castro¹,

Silva²,

Camargo³

et al. 2017

Preprint

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Abstract. We analyzed the spatial pattern of wave extremes in the South Atlantic Ocean by using multiple altimeter platforms spanning the period 1993-2015. Unlike the traditional approach adopted by previous studies, consisting in computing the monthly mean, median or maximum values inside a bin of certain size, we tackled the problem with a different procedure in order to capture more information from short term events. All satellite tracks occurring during two-day temporal window were added in the whole area and then gridded data was generated onto a mesh size of 2• × 2 • through optimal interpolation. The 1Ocean Sci. Discuss., https://doi

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Estimation of extreme wave heights using GEOSAT measurements

Cited by 38 publications

References 21 publications

Wave Extremes in the Northeast Atlantic

Wave Extremes in the Northeast Atlantic

New Zealand wave climate from satellite observations

Estimation of extreme wave heights return period from short-term interpolation of multi-mission satellite data: application to the South Atlantic

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