Studies of climate change typically consider measurements or predictions of temperature over extended periods of time. Climate, however, is much more than temperature. Over the oceans, changes in wind speed and the surface gravity waves generated by such winds play an important role. We used a 23-year database of calibrated and validated satellite altimeter measurements to investigate global changes in oceanic wind speed and wave height over this period. We find a general global trend of increasing values of wind speed and, to a lesser degree, wave height, over this period. The rate of increase is greater for extreme events as compared to the mean condition.
Since 1985, for a period of more than 23 yr, seven altimeter missions have provided global coverage of significant wave height and wind speed. This study undertakes a long-term analysis of the accuracy and stability of altimeter-derived values of significant wave height and wind speed from the following satellites: European Remote Sensing-1 (ERS-1), ERS-2, Environmental Satellite (Envisat), Geosat, Geosat Follow-On (GFO), Jason-1, and the Ocean Topography Experiment (TOPEX). This study is a necessary step in developing a quality-controlled and fully calibrated and validated dataset from the combined satellites. Calibration of all altimeters is performed against National Oceanographic Data Center (NODC) buoy data over the extended period. These calibrations are validated using intercomparisons between satellite missions at crossover ground points. This analysis shows that, for a number of the satellites, small “step like” changes occur during the missions. These inconsistencies are removed by subdividing these missions and undertaking a partial calibration for each section of the mission. The analysis also highlights that care is necessary when attempting to apply relationships between radar cross section and wind speed derived for one altimeter to other platforms. Before undertaking such steps, it is first necessary to apply a platform-specific radar cross-sectional offset to the data.
Measurements collected during the AUSWEX field campaign, at Lake George (Australia), resulted in new insights into the processes of wind wave interaction and whitecapping dissipation, and consequently new parametrizations of the input and dissipation source terms. The new nonlinear wind input term developed accounts for dependence of the growth on wave steepness, airflow separation, and for negative growth rate under adverse winds. The new dissipation terms feature the inherent breaking term, a cumulative dissipation term and a term due to production of turbulence by waves, which is particularly relevant for decaying seas and for swell. The latter is consistent with the observed decay rate of ocean swell. This paper describes these source terms implemented in WAVEWATCH III and evaluates the performance against existing source terms in academic duration-limited tests, against buoy measurements for windsea-dominated conditions, under conditions of extreme wind forcing (Hurricane Katrina), and against altimeter data in global hindcasts. Results show agreement by means of growth curves as well as integral and spectral parameters in the simulations and hindcast.Keywords: wave modelling, wind input, negative input, whitecapping dissipation, swell dissipation 105 ("negative input") is that it is calculated from friction velocity and thus wind speed and does not dissipate swells in absence of wind (Tolman and Chalikov, 1996; Tolman, 2002). The input in TEST451 accounts for swell dissipation due to interaction with the air and thus can become negative (Ardhuin et al., 2010(Ardhuin et al., , 2011a. The dissipation includes a threshold and cumulative term. 110 The outline of the paper is as follows. Section 2 provides detailed description of the wind input term and the dissipation source terms implemented in WAVEWATCH. Section 3 contains description of the setup and results for the idealised academic tests and simulations selected to test the performance of the observation-based source terms. In Section 4 the results are discussed 115 and the conclusions are formulated in Section 5. 6 2. Source terms 2.1. Wind input The wind input function represents the energy flux transferred from wind to waves. This term is due to form drag, i.e. pressure acting on the surface 120 slope of the waves (e.g. Donelan et al., 2006). AUSWEX data analysis and the wind input parameterization reported by Donelan et al. (2005, 2006) and Babanin et al. (2007a) shows dependencies that have not been reported in previous experiments. Measurements of wave growth during AUSWEX were available for a range of wind-forcing conditions including very young waves 125 U 10 /c p = 5.1 − 7.6 (c p is the phase speed at the spectral peak) of varying steepness. This unique dataset revealed a number of new features: (i) full airflow separation with a relative reduction of wind input for conditions of strong winds/steep waves, if compared with its extrapolation from the moderate conditions (Donelan et al., 2006); (ii) dependence of the wave growth rate on 130 w...
[1] Global altimeter data spanning a period of more than 20 years is analyzed to determine whether there are measurable trends in extreme value return period estimates of wind speed and wave height. The data is subdivided into sections of 4 years duration and extreme value analysis applied to each section. The trends in values across these sections indicate that there appears to be a positive trend in 100 year return period values of wind speed but no consistent trends for 100 year return period wave height. However, the statistical uncertainty associated with estimates of the extreme value wind speed and wave heights is such that the quantitative values of trend are not reliable. Reliable values will require a longer-duration data set.
Altimeter data from transects across the Southern Ocean are analyzed to determine the decay of oceanic swell. The resulting decay rate is shown to be proportional to wavenumber squared and swell amplitude cubed. Such a decay relationship is consistent with turbulent interaction with the background, either in the air or water. The present data cannot distinguish between these two cases. The results are consistent with the limited previous studies and present a source term suitable for use in wave prediction models.
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