Jean-Raymond Bidlot

Intercomparison of the Performance of Operational Ocean Wave Forecasting Systems with Buoy Data

The monthly exchange of ocean wave model data has successfully been taking place among five operational weather centers. The data are compared with observations obtained from moored buoys and platforms. The analysis of 3 yr of data has helped to quantify the global and regional skills, strengths, and weaknesses of the different ocean wave forecasting systems. Since the quality of ocean wave forecasts is intrinsically linked to the quality of the forcing wind fields, it is not surprising to find that the center with the lowest wind speed errors also has the lowest wave height errors. The benefit of using a third-generation Wave Model (WAM), for example, is not so tangible in terms of wave height statistics but it is definitively evident in terms of peak periods. Even though WAM has proved to be well suited for global wave forecasting, it is also clear that research is still needed to reduce the model tendency to underpredict some storms when it is forced by operational global wind fields. It appeared that assimilating altimeter wave heights has a positive impact on the model performance. It is also argued that the height of the wind speed observations should be taken into account when assimilating the data or simply when evaluating model performance since it might otherwise introduce a systematic negative bias into the analysis. Last, this exchange of data should continue and possibly extend to other forecasting centers as a tool for model developers but also as a continuous reference for marine forecasters.

A global perspective on Langmuir turbulence in the ocean surface boundary layer

The turbulent mixing in thin ocean surface boundary layers (OSBL), which occupy the upper 100 m or so of the ocean, control the exchange of heat and trace gases between the atmosphere and ocean. Here we show that current parameterizations of this turbulent mixing lead to systematic and substantial errors in the depth of the OSBL in global climate models, which then leads to biases in sea surface temperature. One reason, we argue, is that current parameterizations are missing key surface-wave processes that force Langmuir turbulence that deepens the OSBL more rapidly than steady wind forcing. Scaling arguments are presented to identify two dimensionless parameters that measure the importance of wave forcing against wind forcing, and against buoyancy forcing. A global perspective on the occurrence of wave-forced turbulence is developed using re-analysis data to compute these parameters globally. The diagnostic study developed here suggests that turbulent energy available for mixing the OSBL is under-estimated without forcing by surface waves. Wave-forcing and hence Langmuir turbulence could be important over wide areas of the ocean and in all seasons in the Southern Ocean. We conclude that surface-wave-forced Langmuir turbulence is an important process in the OSBL that requires parameterization. Citation: Belcher, S. E., et al. (2012), A global perspective on Langmuir turbulence in the ocean surface boundary layer, Geophys. Res. Lett., 39, L18605, doi: 10.1029/2012GL052932.

Intercomparison of Different Wind–Wave Reanalyses

Abstract This paper describes the comparison of wind speed and significant wave height data from several reanalyses. The data are assessed against time-averaged altimeter and buoy measurements. The comparisons between the datasets are made in terms of description of short-scale features, monthly means, and long-scale features— namely trends and variability. The results show that although the quality of the datasets in terms of their comparisons with observations differs, most of the long-scale features are equally present in all datasets. The differences between the several wave datasets are larger than those between the wind speed datasets; moreover, differences in wave datasets exist even when the forcing winds used to produce the different wave reanalyses are the same. Most of the discrepancies between the datasets occur in the Tropics, testifying that the physics in that region is still poorly known. The data before the mid-1980s show significant discrepancies also in the Southern Hemisphere, most of ...

Error Estimation of Buoy, Satellite, and Model Wave Height Data

Abstract Triple collocation is a powerful method to estimate the rms error in each of three collocated datasets, provided the errors are not correlated. Wave height analyses from the operational European Centre for Medium-Range Weather Forecasts (ECMWF) wave forecasting system over a 4-yr period are compared with independent buoy data and dependent European Remote Sensing Satellite-2 (ERS-2) altimeter wave height data, which have been used in the wave analysis. To apply the triple-collocation method, a fourth, independent dataset is obtained from a wave model hindcast without assimilation of altimeter wave observations. The seasonal dependence of the respective errors is discussed and, while in agreement with the properties of the analysis scheme, the wave height analysis is found to have the smallest error. In this comparison the altimeter wave height data have been obtained from an average over N individual observations. By comparing model wave height with the altimeter superobservations for different v...

Verification of the ECMWF Wave Forecasting System against Buoy and Altimeter Data

Abstract The present status of ocean wave modeling at the European Centre for Medium-Range Weather Forecasts (ECMWF) is reviewed. Ocean waves are forecasted globally up to 10 days by means of the Wave Model (WAM), which is driven by 10-m winds from the ECMWF atmospheric model. Initial conditions are provided by assimilation of ERS-1 data into the first-guess wave field. The analyzed wave height and peak period field are verified against buoy data and show a considerable improvement compared to verification results of a decade ago. This is confirmed by a comparison of first-guess wave height against ERS-1 altimeter data. The main reasons for this improvement are (i) the higher quality of ECMWF winds compared to a decade ago, (ii) the improved physics of the WAM model, and (iii) the assimilation of ERS-1 data. The forecast skill of the ECMWF wave forecasting system is also studied by comparing forecasts with buoy data and verifying analysis. Error growth in forecast wave height is less rapid than in forecas...

Effects of Observation Errors on the Statistics for Ensemble Spread and Reliability

Abstract The effects of observation errors on rank histograms and reliability diagrams are investigated using a perfect model approach. The three-variable Lorenz-63 model was used to simulate an idealized ensemble prediction system (EPS) with 50 perturbed ensemble members and one control forecast. Observation errors at verification time were introduced by adding normally distributed noise to the true state at verification time. Besides these simulations, a theoretical analysis was also performed. One of the major findings was that rank histograms are very sensitive to the presence of observation errors, leading to overpopulated upper- and lowermost ranks. This sensitivity was shown to grow for larger ensemble sizes. Reliability diagrams were far less sensitive in this respect. The resulting u-shaped rank histograms can easily be misinterpreted as indicating too little spread in the ensemble prediction system. To account for this effect when real observations are used to assess an ensemble prediction syste...

Surface wave effects in the NEMO ocean model: Forced and coupled experiments

The NEMO general circulation ocean model is extended to incorporate three physical processes related to ocean surface waves, namely the surface stress (modified by growth and dissipation of the oceanic wave field), the turbulent kinetic energy flux from breaking waves, and the Stokes-Coriolis force. Experiments are done with NEMO in ocean-only (forced) mode and coupled to the ECMWF atmospheric and wave models. Ocean-only integrations are forced with fields from the ERA-Interim reanalysis. All three effects are noticeable in the extra-tropics, but the sea-state dependent turbulent kinetic energy flux yields by far the largest difference. This is partly because the control run has too vigorous deep mixing due to an empirical mixing term in NEMO. We investigate the relation between this ad hoc mixing and Langmuir turbulence and find that it is much more effective than the Langmuir parameterization used in NEMO. The biases in sea surface temperature as well as subsurface temperature are reduced, and the total ocean heat content exhibits a trend closer to that observed in a recent ocean reanalysis (ORAS4) when wave effects are included. Seasonal integrations of the coupled atmosphere-wave-ocean model consisting of NEMO, the wave model ECWAM and the atmospheric model of ECMWF similarly show that the sea surface temperature biases are greatly reduced when the mixing is controlled by the sea state and properly weighted by the thickness of the uppermost level of the ocean model. These wave-related physical processes were recently implemented in the operational coupled ensemble forecast system of ECMWF.

Evaluation of Medium-Range Forecasts for Hurricane Sandy

AbstractOn 30 October 2012 Hurricane Sandy made landfall on the U.S. East Coast with a devastating impact. Here the performance of the ECMWF forecasts (both high resolution and ensemble) are evaluated together with ensemble forecasts from other numerical weather prediction centers, available from The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) archive. The sensitivity to sea surface temperature (SST) and model resolution for the ECMWF forecasts are explored. The results show that the ECMWF forecasts provided a clear indication of the landfall from 7 days in advance. Comparing ensemble forecasts from different centers, the authors find the ensemble forecasts from ECMWF to be the most consistent in the forecast of the landfall of Sandy on the New Jersey coastline. The impact of the warm SST anomaly off the U.S. East Coast is investigated by running sensitivity experiments with climatological SST instead of persisting the SST anomaly from the an...

Approximate Stokes Drift Profiles in Deep Water

AbstractA deep-water approximation of the Stokes drift velocity profile is explored as an alternative to the monochromatic profile. The alternative profile investigated relies on the same two quantities required for the monochromatic profile, namely, the Stokes transport and the surface Stokes drift velocity. Comparisons with parametric spectra and profiles under wave spectra from the Interim ECMWF Re-Analysis (ERA-Interim) and buoy observations reveal much better agreement than the monochromatic profile even for complex sea states. That the profile gives a closer match and a more correct shear has implications for ocean circulation models since the Coriolis–Stokes force depends on the magnitude and direction of the Stokes drift profile, and Langmuir turbulence parameterizations depend sensitively on the shear of the profile. The alternative profile comes at no added numerical cost compared to the monochromatic profile.

Refinements to a prognostic scheme of skin sea surface temperature

[1] Refinements to a prognostic scheme of skin sea surface temperature (SST) are proposed and tested. The refinements consist of two modifications of a Monin-Obukhov similarity function for stable conditions and mixing enhancement by the Langmuir circulation. The modified scheme is tested with the European Centre for Medium-Range Weather Forecasts model. The modified scheme shows better agreement of the diurnal SST amplitude with estimates from satellite observations. The scheme is also validated with moored buoy observations of the Arabian Sea Mixed Layer Dynamics Experiment. The off-line model with the modified scheme reproduces the observed diurnal SST variability well. Additionally, it is found that the parameterization of the effect of the Langmuir circulation enhances ocean mixing and reduces the diurnal variability of SST under wavy conditions.