Does microseisms in Hamburg (Germany) reflect the wave climate in the North Atlantic?

Essen, H.‐H.; Klussmann, J.; Herber, Rolf; Grevemeyer, Ingo

doi:10.1007/bf02763955

Cited by 11 publications

(15 citation statements)

References 11 publications

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“…In general, the correlation between ocean wave amplitudes and the square root of the microseism amplitudes is 5% higher than the correlation between the amplitudes. This finding is in accordance with the theory for the generation of secondary microseisms in coastal areas [e.g., Essen et al , 1999]. Thus we cross‐correlate the amplitudes of ocean wave height and the square root of the microseism amplitudes.…”

Section: Location Of Microseism Generation Areassupporting

confidence: 91%

“…Wave amplitudes are taken from the buoy measurements and the model results at a grid point spacing of 1.25° over the North Atlantic. A similar approach has been used by Essen et al [1999] and by Bromirski [2001], who used only buoy measurements. The typical propagation speed of microseism waves is 4 km s −1 , suggesting that the propagation time from the Norwegian coast to the seismic stations considered is less than 10 min.…”

Section: Location Of Microseism Generation Areasmentioning

confidence: 99%

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On the generation of secondary microseisms observed in northern and central Europe

et al. 2003

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Microseism recordings from four European broadband stations and from three seismic arrays in Scotland, Norway, and Germany are compared with model wave data of the oceanic wave field in the North Atlantic and local ocean wave data from the Norwegian coast at 60°N, both measured during February–March 2000. Two approaches have been tested to locate generation areas of microseismic energy: a new amplitude correlation technique and beam backprojection from the three seismic arrays. Both techniques reveal that the main generation areas are located in specific regions off the coast of Southwest Norway and North Scotland. Seismic stations distant from these generation areas record a superposition of seismic energy from different source regions. Those close to a specific source region also show a high correlation with it. Both techniques give upper limits for the extent of the generation area of the strongest storm on 6/7 March at the southwest Norwegian coast of about 500 km. By using marine X‐band radar measurements of the two‐dimensional wave height spectrum, we estimate that the relative change of the extension of the generation area off the coast of southwest Norway during several storms is less than a factor of 3. This indicates that the size of the generation area is controlled by static features as coastline or bathymetry, and not by the extent of the storms. Microseism energy appears to be mainly controlled by the wave height in distinct and identifiable generation regions, so that the wave climate in these regions can be studied using historical records of microseisms.

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Section: Location Of Microseism Generation Areassupporting

confidence: 91%

Section: Location Of Microseism Generation Areasmentioning

confidence: 99%

On the generation of secondary microseisms observed in northern and central Europe

et al. 2003

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“…Unfortunately details about the seismic data processing are missing to further verify that work. This quest for a quantitative link between wave climate and seismic noise has been taken up by others, with noteworthy efforts by Bromirski et al [1999] for California, and Essen et al [1999]for the North‐East Atlantic, while the analysis of many seismic records around the word indicate upward trends in seismic noise levels that was interpreted as an increase in ocean wave heights [ Aster et al , 2010]. Based on ocean wave buoy measurements, some skill was shown for the reconstruction of time series of the significant wave height ( H s ) over a few month period for Central California.…”

Section: Introductionmentioning

confidence: 99%

“…For the North Atlantic, a numerical wave model was used to find a significant correlation ( r = 0.71) for 6‐hourly time series between winter waves in various regions of the North‐East Atlantic, and noise levels at the Hamburg seismic station [ Essen et al , 1999]. Yet, with that correlation, seismic noise explains only half of the wave model variance ( r 2 = 0.5), and this was only applied to winters.…”

Section: Introductionmentioning

confidence: 99%

From seismic noise to ocean wave parameters: General methods and validation

et al. 2012

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[1] Seismic noise is an indirect source of information on ocean waves. Using a model of noise generation and propagation, seismic stations can be separated into those that are mostly sensitive to local sea states, and those that integrate sources from a large oceanic area. The model also provides a classification of noise-generating sea states into three classes. The analysis of Central California seismic noise data, well correlated with local waves, reveals that class I events dominate in summer, caused by a single wind-sea system, and for which ocean wave spectral levels are proportional to seismic spectral levels to an exponent b ≃ 0.9. In winter, noise is dominated by class II generation, for which coastal reflection is important, with a wave spectral density roughly proportional to the seismic spectral density to an exponent b ≃ 0.7. Sporadic events of class III probably produce some of the strongest noise events in Central California and need to be properly screened. These events are caused by opposed wave systems that are usually the wind-sea and a swell. This noise classification can be used to improve on the correlation between measured and estimated wave heights (up to r = 0.93 for daily averages). For other locations, where remote oceanic sources are recorded, a significant wave height estimated from the seismic noise compares well with area-averaged satellite data or wave model results (r > 0.85 for daily averages). These analyses pave the way for quantitative uses of seismic records, including the reconstruction of past wave climates, and the calibration of wave hindcasts.Citation: Ardhuin, F., A. Balanche, E. Stutzmann, and M. Obrebski (2012), From seismic noise to ocean wave parameters: General methods and validation,

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“…Ambient noise provides a continuous record which may be used in both seismic source and Earth structure investigations (Cessaro 1994;Friedrich et al 1998;Shapiro 2004;Gerstoft et al 2006;Chevrot et al 2007;Bensen et al 2008;Gerstoft et al 2008;Harmon et al 2010;Landès et al 2010;Köhler et al 2011;Tkalčić et al 2012). In addition, ambient noise generated by ocean storms can be used to infer their location and possible climate-related trends in storm severity (Bromirski 1999;Essen et al 1999;Grevemeyer et al 2000;Bromirski & Duennebier 2002;Essen 2003;Stutzmann et al 2009;Aster et al 2010;Hillers et al 2012).…”

Section: Introductionmentioning

confidence: 99%

Improved implementation of the fk and Capon methods for array analysis of seismic noise

Gal

Reading

Ellingsen

et al. 2014

Geophysical Journal International

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S U M M A R YThe frequency-wavenumber (fk) and Capon methods are widely used in seismic array studies of background or ambient noise to infer the backazimuth and slowness of microseismic sources. We present an implementation of these techniques for the analysis of microseisms (0.05-2 Hz) which draws on array signal processing literature from a range of disciplines. The presented techniques avoid frequency mixing in the cross-power spectral density and therefore yield an accurate slowness vector estimation of the incoming seismic waves. Using synthetic data, we show explicitly how the frequency averaged broad-band approach can result in a slowness-shifted spectrum. The presented implementation performs the slowness estimations individually for each frequency bin and sums the resulting slowness spectra over a specific frequency range. This may be termed an incoherently averaged signal, or IAS, approach. We further modify the method through diagonal loading to ensure a robust solution. The synthetic data show good agreement between the analytically derived and inferred error in slowness. Results for real (observed) data are compared between the approximate and IAS methods for two different seismic arrays. The IAS method results in the improved resolution of features, particularly for the Capon spectrum, and enables, for instance, Rg and Lg arrivals from similar backazimuths to be separated in the case of real data.

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Does microseisms in Hamburg (Germany) reflect the wave climate in the North Atlantic?

Cited by 11 publications

References 11 publications

On the generation of secondary microseisms observed in northern and central Europe

On the generation of secondary microseisms observed in northern and central Europe

From seismic noise to ocean wave parameters: General methods and validation

Improved implementation of the fk and Capon methods for array analysis of seismic noise

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