A simple empirical model is proposed to retrieve wave period from Ku‐band radar altimeter backscatter and significant wave height. The model formulation is heuristic, and fitted using a large dataset of collocated Topex altimeter and buoys measurements. Empirical models are proposed for the zero up‐crossing, the mean and the peak wave period, and compared with models by Davies et al. [1997] and Hwang et al. [1998]. Their performance is assessed using an independent validation dataset, and gives a retrieval error of 0.8s. Regional analysis indicates that the wave period models perform better in wind seas than in swell‐dominated conditions.
Abstract. The ERA (European Centre for Medium-Range Weather Forecasts Reanalysis) project resulted in a homogeneous data set describing the atmosphere over a time span of 15 years, from 1979 to 1993. To validate (part of) these data against independent observations we use the ERA surface winds to drive the WAM wave model. The modeled significant wave heights are then compared with observations. From this comparison the quality of the fbrcing winds is assessed. The patterns of computed wave heights agree well with observed patterns, and they are of the right magnitude. This confirms the realistic nature of the ERA winds. If one looks in detail, it appears that the significant wave heights resulting from the model are systematically lower than the observed ones in areas of high winds and waves and higher in areas of low winds and waves. It is argued that underestimation at high winds speeds is •nost likely a resolution effect, as wind and thus wave peaks are missed by finite resolution in space and time, while overestimation at low wind speeds most likely results from internal WAM errors. It is concluded that the monthly mean ERA winds are slightly (less than 5%) too low in areas of high winds, while from this study it is not, possible to draw a decisive conclusion on the quality of ERA winds at low wind speeds. At the same time, the hindcast data form a 15-year climatology of global waves. This climatology is analyzed in terms of annual cycle and trends. The largest trends in significant wave height occur in the North Atlantic with an increase of more than 12 cm/yr in January, and south of Africa where the increasing trend exceeds 7 cm/yr in July. These trends, however, are only marginally significant. Furthermore, they exhibit a large month-to-month variability, so that on a seasonal basis the trends are significant only in small parts of the ocean. In conclusion, we are unable to confirm a significant change in wave height during the ERA period.
A method of calibrating estimates of significant wave height (Hs) from satellite altimeters against buoy data is proposed, which compares monthly means in 2° latitude × 2° longitude bins obtained from the satellite data with mean values obtained from hourly buoy measurements. The method is applied to Geosat data, ERS‐1 fast‐delivery and off‐line products and to TOPEX Ku band data. Results for Geosat data are in good agreement with those from earlier work in which individual altimeter and buoy values were compared, lending support to the proposed method. Based upon these results, linear functions are derived for estimating buoy measurements of Hs from ERS‐1 and TOPEX altimeter data. Significant differences are found between the ERS‐I fast delivery and off‐line values. Regression, from 60°S to 60°N, of corresponding 2°×2° mean wave heights for individual months from ERS‐1 and TOPEX confirm that there are significant differences between the data from these satellites. Comparisons of means from ERS‐1 and from TOPEX with those from Geosat for the same calendar month but 5 years apart show wider scatter about the regression line, indicating the between‐year variability in individual 2°×2° bins.
Satellite altimetry gives a new perspective on ocean wave climate. Measurements around the British Isles show a strong seasonality, with exceptionally large average wave heights to the west and north of the British Isles in the winter. Furthermore, the interannual variability of winter wave climate is very high. Most of this variability can be described by a strong linear dependence on the North Atlantic Oscillation (NAO) index. This relationship may largely explain observations of increasing wave heights in the northeastern Atlantic and northern North Sea during the latter decades of the 20th century, coincident with a long-term rise in the NAO.
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