Statistical properties of global significant wave heights and their use for validation

Global data sets of significant wave height (Hs) from altimeter measurements and from the wave model WAM are analyzed statistically to assess the quality of the data. Hs derived from the altimeters aboard Seasat (1978), Geosat (1988), ERS-1 (1993, 1994), and TOPEX (1993, 1994) and from WAM (1988, 1993) and, in addition, from in situ data of Ocean Weather Station M in the North Atlantic are used. First, collocated data sets are compared through linear regression and principal component analysis. From this, a good agreement between Hs of the ERS-1 altimeter (1993) and the WAM model is inferred. Second, the Hs frequency distributions are described by the first four moments. Using the first four moments of linear order statistics, the lognormal and the general extreme value distribution function are found to approximate distributions of Hs best. Hs from Seasat and ERS-1 (1993) deviate from these empirical distribution functions, manifesting weaknesses in the data. Although Hs from ERS-1 have weaknesses, their assimilation into WAM has a positive impact. The assessment of the quality of this existing Hs data provides a prerequisite for the coming assimilation schemes using wave data from synthetic aperture radars and also for climate research studies.

[1]  J. Tournadre,et al.  Local climatology of wind and sea state by means of satellite radar altimeter measurements , 1990 .

[2]  E. Bauer.  CHARACTERISTIC FREQUENCY DISTRIBUTIONS OF REMOTELY SENSED IN SITU AND MODELLED WIND SPEEDS , 1996 .

[3]  D.J.T. Carter,et al.  An assessment of Geosat wave height and wind speed measurements , 1992 .

[4]  J. Gower,et al.  Intercalibration of wave and wind data from TOPEX/POSEIDON and moored buoys off the west coast of Canada , 1996 .

[5]  Frank Monaldo,et al.  Expected differences between buoy and radar altimeter estimates of wind speed and significant wave height and their implications on buoy‐altimeter comparisons , 1988 .

[6]  Julius Goldhirsh,et al.  Validation of Geosat altimeter‐derived wind speeds and significant wave heights using buoy data , 1987 .

[7]  Piero Lionello,et al.  A sequential assimilation scheme applied to global wave analysis and prediction , 1995 .

[8]  Application of wave spectra retrieved from ERS-1 SAR wave mode spectra in a wind- and wave-data assimilation system , 1995, 1995 International Geoscience and Remote Sensing Symposium, IGARSS '95. Quantitative Remote Sensing for Science and Applications.

[9]  Roland Romeiser,et al.  Global validation of the wave model WAM over a one-year period using Geosat wave height data , 1993 .

[10]  P. D. Cotton,et al.  Cross calibration of TOPEX, ERS‐I, and Geosat wave heights , 1994 .

[11]  Hans C. Graber,et al.  Validation and assimilation of Seasat altimeter wave heights using the WAM wave model , 1992 .

[12]  G. Brown,et al.  Waveheight and wind speed measurements from the SEASAT radar altimeter , 1982 .

[13]  Donald E. Barrick,et al.  Rough Surface Scattering Based on the Specular Point Theory , 1968 .

[14]  P. Janssen.  Quasi-linear Theory of Wind-Wave Generation Applied to Wave Forecasting , 1991 .

[16]  J. Hosking.  L‐Moments: Analysis and Estimation of Distributions Using Linear Combinations of Order Statistics , 1990 .

[17]  K. Hasselmann,et al.  Assimilation of wave data into the wave model WAM using an impulse response function method , 1996 .

[18]  Michael H. Freilich,et al.  Derivation of satellite wind model functions using operational surface wind analyses: An altimeter example , 1993 .

[19]  Interannual variations and longer‐term changes in the sea state of the North Atlantic from 1970 to 1982 , 1984 .

[20]  Philip S. Callahan,et al.  Comparison of TOPEX/POSEIDON σ0 and significant wave height distributions to Geosat , 1994 .