Experience from compilation of global wave statistics

Hogben, N.

doi:10.1016/0029-8018(88)90017-0

Cited by 20 publications

(10 citation statements)

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“…Random and systematic uncertainties of visual wave data in the VOS collections arise from the inaccuracy of observational techniques and the coding system. During the past 50 years a number of attempts have been made to assess these uncertainties [e.g., Brooks and Jasper , 1957; Bretschneider , 1962; Hogben and Lumb , 1967; Quayle , 1974; Hoffman and Miles , 1976; Jardine , 1979; Laing , 1985; Soares , 1986; Hogben , 1988; Wilkerson and Earle , 1990; Hogben and Tucker , 1994; Gulev and Hasse , 1998]. However, in most cases only limited subsets of observations were used to quantify the uncertainties.…”

Section: Developing a Global Climatology Of Wind Wave Parametersmentioning

confidence: 99%

“…SWH is defined in terms of spectral moments as SWH = 4√ m 0 , where m 0 is the zeroth moment of the spectrum, which is equal to the sea surface variance [e.g., Srokosz and Challenor , 1987]. Traditionally, SWH is derived from estimates of wind sea and swell using the formula of Hogben [1988], which follows from the definition of SWH: where h w and h s are the wind sea and swell heights respectively. However, comparisons with instrumental measurements [ Wilkerson and Earle , 1990; Gulev and Hasse , 1998] show that it tends to overestimate the observed SWH by several tens of centimeters.…”

Section: Developing a Global Climatology Of Wind Wave Parametersmentioning

confidence: 99%

“…Limited subsets of visual wave observations at OWSs for the period 1950–1970 were used to analyze the variability of surface waves [ Walden et al , 1970; Rodewald , 1972; Rye , 1976]. Many works estimated the accuracy of these data and found many sources of errors of both random and systematic nature [ Houmb et al , 1978; Jardine , 1979; Dacunha et al , 1984; Laing , 1985; Soares , 1986; Hogben et al , 1983; Hogben , 1988; Wilkerson and Earle , 1990; Hogben and Tucker , 1994]. Gulev and Hasse [1998] used wind wave reports from the Comprehensive Ocean‐Atmosphere Data Set (COADS) [ Woodruff et al , 1998] and produced a North Atlantic climatology of the basic wave parameters for the period 1964–1993.…”

Section: Introductionmentioning

confidence: 99%

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Assessment of the reliability of wave observations from voluntary observing ships: Insights from the validation of a global wind wave climatology based on voluntary observing ship data

et al. 2003

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[1] This paper describes development and validation of a global climatology of basic wave parameters based on the voluntary observing ship (VOS) data from the Comprehensive Ocean-Atmosphere Data Set collection. Climatology covers the period 1958-1997 and presents heights and periods for the wind sea, swell, and significant wave height (SWH) over the global ocean on 2°Â 2°spatial resolution. Significant wave height has been derived from separate sea and swell estimates by taking square root of the sum of squares for the seas and swells propagating approximately in the same direction and assuming SWH to be equal to the higher of the two components in all other cases. Special algorithms of corrections were applied to minimize some biases, inherent in visual wave data. Particularly, we corrected overestimation of small seas, corrected underestimation of periods, and analyzed separation between sea and swell. Validation included estimation of random observational errors, observation of sampling errors, and comparison with the alternative wave data. Estimates of random observational errors show that for the majority of locations, observational uncertainties are within 20% of mean values, which allows us to discuss quantitatively the produced climatology. Biases associated with inadequate sampling were quantified using the data from high-resolution WAM hindcast for the period 1979-1993. The highest sampling biases are observed in the South Ocean, where wave height may be underestimated by 1-1.5 m because of poor sampling, primarily associated with a fair weather bias of ship routing and observation. Comparison to the other VOS-based products shows in general higher SWH in our climatology, especially in the midlatitudes. However, comparison with the altimeter data shows that even for well-sampled regions, high waves are still underestimated in VOS, suggesting a ubiquitous fair weather bias. Further ways of improving VOS-based wave climatologies and possible applications are discussed.

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Section: Developing a Global Climatology Of Wind Wave Parametersmentioning

confidence: 99%

Section: Developing a Global Climatology Of Wind Wave Parametersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Assessment of the reliability of wave observations from voluntary observing ships: Insights from the validation of a global wind wave climatology based on voluntary observing ship data

et al. 2003

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“…Analysis of climate variability based on these data was for a long time limited to the consideration of the OWS subsets (Walden et al 1970;Rodewald 1972;Rye 1976). More extensive use of these data for climate research requires correction of many biases and minimization of observational errors inherent to visual observations (Houmb et al 1978;Jardine 1979;Dacunha et al 1984;Laing 1985;Soares 1986;Hogben et al 1983;Hogben 1988;Wilkerson and Earle 1990;Hogben and Tucker 1994;Gulev et al 2003a,b). Gulev and Hasse (1998) Worley et al 2005).…”

Section: Introductionmentioning

confidence: 99%

Variability of the Winter Wind Waves and Swell in the North Atlantic and North Pacific as Revealed by the Voluntary Observing Ship Data

2006

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This paper analyses secular changes and interannual variability in the wind wave, swell, and significant wave height (SWH) characteristics over the North Atlantic and North Pacific on the basis of wind wave climatology derived from the visual wave observations of voluntary observing ship (VOS) officers. These data are available from the International Comprehensive Ocean-Atmosphere Data Set (ICOADS) collection of surface meteorological observations for 1958-2002, but require much more complicated preprocessing than standard meteorological variables such as sea level pressure, temperature, and wind. Visual VOS data allow for separate analysis of changes in wind sea and swell, as well as in significant wave height, which has been derived from wind sea and swell estimates. In both North Atlantic and North Pacific midlatitudes winter significant wave height shows a secular increase from 10 to 40 cm decade Ϫ1 during the last 45 yr. However, in the North Atlantic the patterns of trend changes for wind sea and swell are quite different from each other, showing opposite signs of changes in the northeast Atlantic. Trend patterns of wind sea, swell, and SWH in the North Pacific are more consistent with each other. Qualitatively the same conclusions hold for the analysis of interannual variability whose leading modes demonstrate noticeable differences for wind sea and swell. Statistical analysis shows that variability in wind sea is closely associated with the local wind speed, while swell changes can be driven by the variations in the cyclone counts, implying the importance of forcing frequency for the resulting changes in significant wave height. This mechanism of differences in variability patterns of wind sea and swell is likely more realistic than the northeastward propagation of swells from the regions from which the wind sea signal originates.

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“…The Wave Climate Synthesis method, pioneered by Hogben and collaborators (Andrews, et al, 1983, Hogben, 1987, and Hogben and Dacunha, 1985 at British Maritime Technology (formerly National Maritime Institute), is based on the concept of relating long-term marginal probabilities of significant wave height P(H ) and wind ^GLERL Contribution No. 539.…”

Section: Approachmentioning

confidence: 99%

Estimating Long-Term Wave Statistics From Long-Term Wind Statistics

Liu

1986

Int. Conf. Coastal. Eng.

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The Wave Climate Synthesis method, which derives long-term wave statistics from long-term wind statistics directly, is tested with four years of wind and wave measurements recorded from eight NOMAD buoys in the Great Lakes during 1981-1984. The results show that it is an excellent method for estimating long-term wave statistics and design wave height. While the method is by no means intended to replace wave hindcasting procedures, it is shown to be a useful additional tool for the coastal engineer.

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Experience from compilation of global wave statistics

Cited by 20 publications

References 2 publications

Assessment of the reliability of wave observations from voluntary observing ships: Insights from the validation of a global wind wave climatology based on voluntary observing ship data

Assessment of the reliability of wave observations from voluntary observing ships: Insights from the validation of a global wind wave climatology based on voluntary observing ship data

Variability of the Winter Wind Waves and Swell in the North Atlantic and North Pacific as Revealed by the Voluntary Observing Ship Data

Estimating Long-Term Wave Statistics From Long-Term Wind Statistics

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