Assessment of SARAL/AltiKa Wave Height Measurements Relative to Buoy, Jason-2, and Cryosat-2 Data

SARAL/AltiKa GDR-T are analyzed to assess the quality of the significant wave height (SWH) measurements. SARAL along-track SWH plots reveal cases of erroneous data, more or less isolated, not detected by the quality flags. The anomalies are often correlated with strong attenuation of the Ka-band backscatter coefficient, sensitive to clouds and rain. A quality test based on the 1Hz standard deviation is proposed to detect such anomalies. From buoy comparison, it is shown that SARAL SWH is more accurate than Jason-2, particularly at low SWH, and globally does not require any correction. Results are better with open ocean than with coastal buoys. The scatter and the number of outliers are much larger for coastal buoys. SARAL is then compared with Jason-2 and Cryosat-2. The altimeter data are extracted from the global altimeter SWH Ifremer data base, including specific corrections to calibrate the various altimeters. The comparison confirms the high quality of SARAL SWH. The 1Hz standard deviation is much less than for Jason-2 and Cryosat-2, particularly at low SWH. Furthermore, results show that the corrections applied to Jason-2 and to Cryosat-2, in the data base, are efficient, improving the global agreement between the three altimeters.

Wind Waves in the Arctic Seas: Envisat and AltiKa Data Analysis

Wind-generated waves in the Kara, Laptev, and East-Siberian Seas are investigated using altimeter data from Envisat RA-2 and SARAL-AltiKa. Only isolated ice-free zones had been selected for analysis. Wind seas can be treated as pure wind-generated waves without any contamination by ambient swell. Such zones were identified using ice concentration data from microwave radiometers. Altimeter data, both significant wave height (SWH) and wind speed, for these areas were further obtained for the period 2002-2012 using Envisat RA-2 measurements, and for 2013 using SARAL-AltiKa. Dependencies of dimensionless SWH and wavelength on dimensionless wave generation spatial scale are compared to known empirical dependencies for fetch-limited wind wave development. We further check sensitivity of Ka- and Ku-band and discuss new possibilities that AltiKa's higher resolution can open.

The transformed-stationary approach: a generic and simplified methodology for non-stationary extreme value analysis

Statistical approaches to study extreme events require, by definition, long time series of data. In many scientific disciplines, these series are often subject to variations at different temporal scales that affect the frequency and intensity of their extremes. Therefore, the assumption of stationarity is violated and alternative methods to conventional stationary extreme value analysis (EVA) must be adopted. Using the example of environmental variables subject to climate change, in this study we introduce the transformed-stationary (TS) methodology for non-stationary EVA. This approach consists of (i) transforming a non-stationary time series into a stationary one, to which the stationary EVA theory can be applied, and (ii) reverse transforming the result into a non-stationary extreme value distribution. As a transformation, we propose and discuss a simple time-varying normalization of the signal and show that it enables a comprehensive formulation of non-stationary generalized extreme value (GEV) and generalized Pareto distribution (GPD) models with a constant shape parameter. A validation of the methodology is carried out on time series of significant wave height, residual water level, and river discharge, which show varying degrees of long-term and seasonal variability. The results from the proposed approach are comparable with the results from (a) a stationary EVA on quasi-stationary slices of non-stationary series and (b) the established method for non-stationary EVA. However, the proposed technique comes with advantages in both cases. For example, in contrast to (a), the proposed technique uses the whole time horizon of the series for the estimation of the extremes, allowing for a more accurate estimation of large return levels. Furthermore, with respect to (b), it decouples the detection of non-stationary patterns from the fitting of the extreme value distribution. As a result, the steps of the analysis are simplified and intermediate diagnostics are possible. In particular, the transformation can be carried out by means of simple statistical techniques such as low-pass filters based on the running mean and the standard deviation, and the fitting procedure is a stationary one with a few degrees of freedom and is easy to implement and control. An open-source MAT-LAB toolbox has been developed to cover this methodology, which is available at https://github.com/menta78/tsEva/(Mentaschi et al., 2016).

Comparison and validation of physical wave parameterizations in spectral wave models

Recent developments in the physical parameterizations available in spectral wave models have already been validated, but there is little information on their relative performance especially with focus on the higher order spectral moments and wave partitions. This study concentrates on documenting their strengths and limitations using satellite measurements, buoy spectra, and a comparison between the different models. It is confirmed that all models perform well in terms of significant wave heights; however higher-order moments have larger errors. The partition wave quantities perform well in terms of direction and frequency but the magnitude and directional spread typically have larger discrepancies. The high-frequency tail is examined through the mean square slope using satellites and buoys. From this analysis it is clear that some models behave better than the others, suggesting their parameterizations match the physical processes reasonably well. However none of the models are entirely satisfactory, pointing to poorly constrained parameterizations or missing physical processes. The major space-time differences between the models are related to the swell field stressing the importance of describing its evolution. An example swell field confirms the wave heights can be notably different between model configurations while the directional distributions remain similar. It is clear that all models have difficulty in describing the directional spread. Therefore, knowledge of the source term directional distributions is paramount in improving the wave model physics in the future.

Effects of an asymmetric friction on the nonlinear equilibration of a baroclinic system

Following some recent linear and nonlinear studies the authors examine, using numerical simulations of a classical two-layer model, the effect of an asymmetric friction on the nonlinear equilibrium of moderately unstable baroclinic systems, The results show that the presence of an asymmetric friction leads to a significant wave scale selection: ''long'' waves (in terms of their zonal wavelengths) emerge with a traditional asymmetric friction (with the upper layer less viscous than the lower layer), while only ''short'' waves dominate with a nontraditional asymmetric friction (with the lower layer less viscous than the upper layer). The role of the nonlinear interactions and. more precisely, the effects of an asymmetric friction on the wave-mean flow and wave-wave interactions; and their consequences on the wave scale selection are examined.

In-situ based reanalysis of the global ocean temperature and salinity with ISAS: variability of the heat content and steric height

The In Situ Analysis System (ISAS) was developed to produce gridded fields of temperature and salinity that preserve as much as possible the time and space sampling capabilities of the Argo network of profiling floats. Since the first global re-analysis performed in 2009, the system has evolved and a careful delayed mode processing of the 2002-2012 dataset has been carried out using version 6 of ISAS and updating the statistics to produce the ISAS13 analysis. This last version is now implemented as the operational analysis tool at the Coriolis data centre. The robustness of the results with respect to the system evolution is explored through global quantities of climatological interest: the Ocean Heat Content and the Steric Height. Estimates of errors consistent with the methodology are computed. This study shows that building reliable statistics on the fields is fundamental to improve the monthly estimates and to determine the absolute error bars. The new mean fields and variances deduced from the ISAS13 re-analysis and dataset show significant changes relative to the previous ISAS estimates, in particular in the southern ocean, justifying the iterative procedure. During the decade covered by Argo, the intermediate waters appear warmer and saltier in the North Atlantic and fresher in the Southern Ocean than in WOA05 long term mean. At inter-annual scale, the impact of ENSO on the Ocean Heat Content and Steric Height is observed during the 2006-2007 and 2009-2010 events captured by the network.

Swell dissipation from 10 years of Envisat ASAR in wave mode

Swells are found in all oceans and strongly influence the wave climate and air-sea processes. The poorly known swell dissipation is the largest source of error in wave forecasts and hindcasts. We use synthetic aperture radar data to identify swell sources and trajectories, allowing a statistically significant estimation of swell dissipation. We mined the entire Envisat mission 2003–2012 to find suitable storms with swells (13 < T < 18 s) that are observed several times along their propagation. This database of swell events provides a comprehensive view of swell extending previous efforts. The analysis reveals that swell dissipation weakly correlates with the wave steepness, wind speed, orbital wave velocity, and the relative direction of wind and waves. Although several negative dissipation rates are found, there are uncertainties in the synthetic aperture radar-derived swell heights and dissipation rates. An acceptable range of the swell dissipation rate is −0.1 to 6 × 10−7 m−1 with a median of 1 × 10−7 m−1.