Wave Prediction Research Articles

From research to applications – examples of operational ensemble post-processing in France using machine learning

Abstract. Statistical post-processing of ensemble forecasts, from simple linear regressions to more sophisticated techniques, is now a well-known procedure for correcting biased and poorly dispersed ensemble weather predictions. However, practical applications in national weather services are still in their infancy compared to deterministic post-processing. This paper presents two different applications of ensemble post-processing using machine learning at an industrial scale. The first is a station-based post-processing of surface temperature and subsequent interpolation to a grid in a medium-resolution ensemble system. The second is a gridded post-processing of hourly rainfall amounts in a high-resolution ensemble prediction system. The techniques used rely on quantile regression forests (QRFs) and ensemble copula coupling (ECC), chosen for their robustness and simplicity of training regardless of the variable subject to calibration. Moreover, some variants of classical techniques used, such as QRF and ECC, were developed in order to adjust to operational constraints. A forecast anomaly-based QRF is used for temperature for a better prediction of cold and heat waves. A variant of ECC for hourly rainfall was built, accounting for more realistic longer rainfall accumulations. We show that both forecast quality and forecast value are improved compared to the raw ensemble. Finally, comments about model size and computation time are made.

Transitional Waters Typology in Turkey: Melen Estuary Case Study

Balas, L.; Genc, A.N., and Eser, E., 2020. Transitional waters typology in Turkey: Melen Estuary case study. In: Malvarez, G. and Navas, F. (eds.), Global Coastal Issues of 2020. Journal of Coastal Research, Special Issue No. 95, pp. 18-22. Coconut Creek (Florida), ISSN 0749-0208.Transitional and coastal water bodies are dynamic and complex environments. Even though widespread typological descriptors have been defined for coastal waters, typology studies for transitional waters are still continuing in Turkey as in many European countries. Transitional waters include estuaries, lagoons, and deltas. In this manuscript, the typology study applied for the Melen estuary is presented. Melen Estuary located in the Western Black Sea Part of Turkey is one of the significant watersheds of Turkey as it supplies more than 50% of the drinking water to the city of Istanbul. In typology approach, System B is accepted, and the Guidance Document No 5 produced by the Common Implementation Strategy for the Water Framework Directive (2000/60/EC) Working Group 2.4 (COAST) is closely followed. In addition to the obligatory factors, current velocity, wave exposure, and mixing characteristics are investigated as the optional factors. Measurements and modeling studies are used together. The coastal processes in the Melen Estuary are modelled. The wind and wave climate, wind and wave-induced current patterns, and mixing zone are simulated by HYDROTAM-3D (Three dimensional hydrodynamic, transport and water quality model). In the long term directional wind analyses, six hourly predictions of the European Centre for Medium-Range Weather Forecasts (ECMWF) between 2000-2019 are analyzed. In the long term directional wave statistical analysis, six hourly wave predictions of ECMWF between 2000-2019 operational archive are used. The range of significant wave heights, with 12 hours/year exceedance probability, is estimated as 0.4m≤Hs,12≤3.2 m. The wave exposure index for Melen transitional water is calculated. The dominant wave direction interval is determined as North-Northeast. Based on the mixing studies, the degree of stratification is determined as partially stratified.

A Hardware-Oriented Echo State Network and its FPGA Implementation

This paper proposes implementation of an Echo State Network (ESN) to Field Programmable Gate Array (FPGA). The proposed method is able to reduce hardware resources by using fixed-point operation, quantization of weights, which includes accumulate operations and efficient dataflow modules. The performance of the designed circuit is verified via experiments including prediction of sine and cosine waves. Experimental result shows that the proposed circuit supports to 200 MHz of operation frequency and facilitates faster computing of the ESN algorithm compared with a central processing unit.

Freak Wave Prediction Based on the Nonlinear Schrödinger Equation

Wang, X.; Gao, Y.; Wu, M.; Cai, F., and Liu, X., 2020. Freak wave prediction based on the nonlinear Schrödinger equation. In: Zheng, C.W.; Wang, Q.; Zhan, C., and Yang, S.B. (eds.), Air-Sea Interaction and Coastal Environments of the Maritime and Polar Silk Roads. Journal of Coastal Research, Special Issue No. 99, pp. 310–318. Coconut Creek (Florida), ISSN 0749-0208.To explore a prediction method for freak waves, a theoretical derivation is given to calculate the eigenvalue of the nonlinear Schrödinger (NLS) equation from measured wave height time history data based on the inverse scattering transform of the third-order nonlinear Schrödinger equation. The method further predicts the temporal and spatial evolution of the wave envelope. Based on the envelope prediction results, the spatiotemporal information for large wave occurrence can be obtained. The prediction results of this paper are compared with measured wave trains to verify the validity and accuracy of the method. This method gives a new technical approach for providing large-wave warnings for ships or offshore platforms, as well as for finding periods for offshore operations under large wave conditions.

Sea trial on deterministic sea waves prediction using wave-profiling radar

Short-term deterministic sea wave prediction (DSWP) can facilitate the safe implementation of a number of maritime operations. Wave profile radars, based on the conventional X-band radars, have recently been proven to provide a low-cost convenient source of two-dimensional wave measurement for DSWP. The Golden Arrow sea trial in the North Atlantic was dedicated to collecting wave and vessel motion data for DSWP purposes, particularly under the large sea conditions that are of practical interest in marine operations. The field data were collected using a wave profiling radar and other measurement technologies for validation. This paper reports on the successful application of a recently developed technique by Al-Ani et al. in DSWP to the dedicated sea trial.

Long-term wave prediction and analysis based on time-series analysis

The efficiency of the oscillating float-type wave energy devices is closely related to the wave conditions in its working area. Seasonal changes in actual sea conditions are obvious, and they vary greatly throughout the year. Therefore, it is necessary to analyse and predict the wave, and adjust the oscillating float-type wave energy device’s parameters according to the wave conditions to improve the efficiency. Based on the analysis of the long-term wave variation and the short-term stationary characteristics of the wave, the moving regression algorithm is used to predict the wave. Adjust the device parameters according to the wave condition prediction data, and match the wave power and load power to achieve a certain efficiency in the wide power range of the device. The research results can be used for variable load control of wave energy devices.

A Lagrangian analysis of upper-tropospheric anticyclones associated with heat waves in Europe

Abstract. This study presents a Lagrangian analysis of upper-tropospheric anticyclones that are connected to surface heat waves in different European regions for the period 1979 to 2016. In order to elucidate the formation of these anticyclones and the role of diabatic processes, we trace air parcels backwards from the upper-tropospheric anticyclones and quantify the diabatic heating in these air parcels. Around 25 %–45 % of the air parcels are diabatically heated during the last 3 d prior to their arrival in the upper-tropospheric anticyclones, and this amount increases to 35 %–50 % for the last 7 d. The influence of diabatic heating is larger for heat-wave-related anticyclones in northern Europe and western Russia and smaller in southern Europe. Interestingly, the diabatic heating occurs in two geographically separated air streams; 3 d prior to arrival, one heating branch (remote branch) is located above the western North Atlantic, and the other heating branch (nearby branch) is located over northwestern Africa and Europe to the southwest of the target upper-tropospheric anticyclone. The diabatic heating in the remote branch is related to warm conveyor belts in North Atlantic cyclones upstream of the evolving upper-level ridge. In contrast, the nearby branch is diabatically heated by convection, as indicated by elevated mixed-layer convective available potential energy along the western side of the matured upper-level ridge. Most European regions are influenced by both branches, whereas western Russia is predominantly affected by the nearby branch. The remote branch predominantly affects the formation of the upper-tropospheric anticyclone, and therefore of the heat wave, whereas the nearby branch is more active during its maintenance. For long-lasting heat waves, the remote branch regenerates. The results from this study show that the dynamical processes leading to heat waves may be sensitive to small-scale microphysical and convective processes, whose accurate representation in models is thus supposed to be crucial for heat wave predictions on weather and climate timescales.

Stormtools Design Elevation (SDE) Maps: Including Impact of Sea Level Rise

Many coastal communities in the US use base flood elevation (BFE) maps for the 100-year return period, specified on Federal Emergency Management Agency (FEMA) Flood Insurance Rate Maps (FIRMs), to design structures and infrastructure. The FIRMs are increasingly known to have serious problems in accurately specifying the risk coastal communities face, as most recently evidenced during hurricanes Harvey and Irma in 2017 and Florence and Michael in 2018. The FIRM BFE maps also do not include the impact of sea level rise, which clearly needs to be considered in the design of coastal structures over the next several decades given recent National Oceanic and Atmospheric Administration (NOAA) sea level rise (SLR) projections. Here, we generate alternative BFE maps (STORMTOOLS Design Elevation (SDE) maps) for coastal waters of Rhode Island (RI) using surge predictions from tropical and extratropical storms of the coupled surge-wave models from the US Army Corp of Engineers, North Atlantic Comprehensive Coast Study (NACCS). Wave predictions are based on application of a steady state, spectral wave model (STWAVE), while impacts of coastal erosion/accretion and changes of geomorphology are modeled using XBeach. The high-resolution application of XBeach to the southern RI shoreline has dramatically increased the ability to represent the details of dune erosion and overtopping and the associated development of surge channels and over-wash fans and the resulting landward impact on inundation and waves. All methods used were consistent with FEMA guidelines for the study area and used FEMA-approved models. Maps were generated for 0, 2 ft (0.6 m), 5 ft (1.5 m), 7 ft (2.1 m), and 10 ft (3.1 m) of sea level rise, reflecting NOAA high estimates at various times for the study area through 2100. Results of the simulations are shown for both the southern RI shoreline (South Coast) and Narragansett Bay, to facilitate communication of projected BFEs to the general public. The maps are hosted on the STORMTOOLS ESRI Hub to facilitate access to the data. They are also now part of the RI Coastal Resources Management Council (CRMC) risk-based permitting system. The user interface allows access to all supporting data including grade elevation, inundation depth, and wave crest heights as well as corresponding FEMA FIRM BFEs and associated zones.

On Fully Describing the Probability Distribution of Quiescent Periods From Sea Spectral Density

A fundamental property of most sea conditions is that sets of large waves alternate with sets of smaller waves, known as quiescent periods. Exploiting the quiescent periods can expand the sea states under which the execution of many maritime operations can be considered safe. Building upon the work of Belmont et al. , we extend the methodology to fully describe the statistical distribution of the quiescent periods in terms of their time duration using sea spectra derived from current ship readings as well as metocean forecast. This provides the basis for a short- or long-term planning tool that complements deterministic wave prediction technology for executing wave-height-limited maritime operations. The method is evaluated using spectra calculated from field measurements in a dedicated sea trial and from standard parameterized oceanographic forms (JONSWAP and Pearson–Moskowitz).

Application of a numerical model for wave parameter hindcasting in the Marmara Sea Basin

One of the most important factors in design of coastal and marine structures is to determine the wave characteristics precisely. In this paper, wave characteristics of Sea of Marmara obtained during the time span between 1994 and 2014 by using the third generation spectral model MIKE 21 SW. Wind data was obtained from ECMWF ERA-Interim re-analyses wind dataset with a spatial resolution of 0.125 degree. The numerical model was calibrated with a wave data that measured for 1 year (2013) by measurement buoy on the Southern coast near the Istanbul in the Sea of Marmara. Numerical mesh optimization was also performed to obtain the most suitable domain to overcome the time efficiency problem in running time of the model. This research is recently amongst the first studies that deal with the determination of wave parameters in the Marmara Sea Basin. In addition, the relation between significant wave height and wave period is established. The results reveal that wave prediction capacity of the numerical model gives satisfactory results.

Linearly forced fluid flow on a rotating sphere

We investigate generalized Navier-Stokes (GNS) equations that couple nonlinear advection with a generic linear instability. This analytically tractable minimal model for fluid flows driven by internal active stresses has recently been shown to permit exact solutions on a stationary two-dimensional sphere. Here, we extend the analysis to linearly driven flows on rotating spheres. We derive exact solutions of the GNS equations corresponding to time-independent zonal jets and superposed westward-propagating Rossby waves, qualitatively similar to those seen in planetary atmospheres. Direct numerical simulations with large rotation rates obtain statistically stationary states close to these exact solutions. The measured phase speeds of waves in the GNS simulations agree with analytical predictions for Rossby waves.

Uncertainties of Estimating Extreme Significant Wave Height for Engineering Applications Depending on the Approach and Fitting Technique—Adriatic Sea Case Study

Studies on the extrapolation of extreme significant wave height, based on long-term databases, are extensively covered in literature. An engineer, working in the field of naval architecture, marine engineering, or maritime operation planning, when tackling the problem of extreme wave prediction, would typically follow relevant codes and standards. Currently, authorities in the field of offshore operation within its guidelines propose several methods: the initial-distribution, extreme value, and peak-over threshold approaches. Furthermore, for each proposed method, different mathematical fitting techniques are applicable to optimize the candidate distribution parameters: the least-square method, the method of moments, and the maximum likelihood method. A comprehensive analysis was done to determine the difference in the results depending on the choice of method and fitting technique. All combinations were tested on a long-term database for a location in the Adriatic Sea. The variability of the results and trends of extreme wave height estimates for long return periods are presented, and the limitations of certain methods and techniques are noted.

Numerical study of medium to large scale BLEVE for blast wave prediction

So far, the prediction of blast wave generated from the Boiling Liquid Expanding Vapour Explosion (BLEVE) has been already broadly investigated. However, only a few validations of these blast wave prediction models have been made, and some well-established methods are available to predict BLEVE overpressure in the open space only. This paper presents numerical study on the estimation of the near-field and far-field blast waves from BLEVEs. The scale effect is taken into account by conducting two different scale BLEVE simulations. The expansion of pressurized vapour and evaporation of liquid in BLEVE are both modelled by using CFD method. Two approaches are proposed to determine the initial pressure of BLEVE source. The vapour evaporation and liquid flashing are simulated separately in these two approaches. Satisfactory agreement between the CFD simulation results and experimental data is achieved. With the validated CFD model, the results predicted by the proposed approaches can be used to predict explosion loads for better assessment of explosion effects on structures.

Temperature-assisted broadly tunable supercontinuum generation in chalcogenide-glass-based capillary optical fiber

We propose an alternative technique for generating a tunable supercontinuum in a liquid-filled chalcogenide capillary optical fiber exhibiting three zero-dispersion wavelengths. To investigate the tunable supercontinuum, a nonlinear Schrödinger equation is solved to understand the soliton pulse dynamics. Utilizing temperature-assisted dispersion tailoring, the generation of dispersive waves that are tunable within a broad wavelength range of 3630–4650 nm and 2230–2560 nm is reported, with detailed investigations of various spectrograms confirming the predictions of dispersive waves through phase-matching characteristics. Also, temperature-controlled soliton spectral tunneling is numerically predicted in the same fiber and depends on the spectral width of the normal dispersion region between two anomalous regions.

Record-breaking heat wave in southern China and delayed onset of South China Sea summer monsoon driven by the Pacific subtropical high

We investigate a record-breaking heat wave in southern China (SC) and explore its association with the South China Sea (SCS) summer monsoon (SCSSM), using station observations and various reanalysis products. This heat wave event started in mid-May 2018 and persisted more than 15 days, when the maximum air temperature anomaly exceeded 6 °C. Meanwhile, the onset of the SCSSM was extremely late in 2018, primarily due to the intrusion of easterly winds over the SCS. We show that the anomalous easterlies over the SCS associated with the delayed SCSSM could block the moisture transport from the tropical oceans to SC, which led to decreased rainfall, increased surface radiation, and elevated probability of heat wave in SC during May 2018. Further analysis reveals that both SC heat waves and SCSSM were significantly affected by the Pacific subtropical high (PSH). The westward extension of the PSH can hinder the establishment of SCSSM via inducing easterly anomalies over the SCS, which reduces SC rainfall and results in a drier surface condition. Moreover, the westward displacement of the PSH may cause anomalously high pressures, descending air motions, and divergent winds over SC, which triggers above-normal air temperatures that are conducive to the occurrences of SC heat waves. This study also underlines the importance of Eurasian planetary wave trains in bridging the upstream climate variability and the changes in PSH during boreal spring, which could be used to improve the intra-seasonal predictions of SC heat wave and SCSSM onset.

Mitigation of model bias influences on wave data assimilation with multiple assimilation systems using WaveWatch III v5.16 and SWAN v41.20

Abstract. High-quality wave prediction with a numerical wave model is of societal value. To initialize the wave model, wave data assimilation (WDA) is necessary to combine the model and observations. Due to imperfect numerical schemes and approximated physical processes, a wave model is always biased in relation to the real world. In this study, two assimilation systems are first developed using two nearly independent wave models; then, “perfect” and “biased” assimilation frameworks based on the two assimilation systems are designed to reveal the uncertainties of WDA. A series of biased assimilation experiments is conducted to systematically examine the adverse impact of model bias on WDA. A statistical approach based on the results from multiple assimilation systems is explored to carry out bias correction, by which the final wave analysis is significantly improved with the merits of individual assimilation systems. The framework with multiple assimilation systems provides an effective platform to improve wave analyses and predictions and help identify model deficits, thereby improving the model.

Role of mangroves in wind-wave climate modeling – A review

Globally, there has been dedicated research on mangrove ecosystems, however, the modeling of wave-mangrove interaction is seldom considered in the operational wave prediction for vegetated coastlines. This review work apprises on the significant impact of mangroves on surface gravity wave characteristics. Prediction and quantification of wave attenuation characteristics by mangroves is an essential pre-requisite for coastal zone management activities along a mangrove dominated shoreline. Nevertheless, the dynamic impact of waves on mangroves is missing in the current regional wave forecasting systems. In this review article, the scientific advancements in wave-mangrove interaction studies are elucidated and focus on its significance in an operational wave modeling scheme for the Indian coast. The relevant studies on wave dissipation by mangroves and other vegetation; its nonlinear interaction in the presence of currents and extreme waves, and the need for improving its parameterization are considered distinctly. The study also highlights the importance to predict the futuristic scenarios of wave attenuation characteristics in mangrove dominated regions which are highly sensitive to effects from climate change. The authors believe that the research on dynamics of wave-mangrove interaction in India has an extensive scope, and possible future endeavors towards a realistic nearshore wave modeling along mangrove dominant coasts are presented in the concluding remarks.

Impact wave predictions by a Fuzzy ARTMAP neural network

Impact waves caused by landslides, rock blocks, and avalanches in lakes and dam reservoirs have provoked several disasters since the dawn of time; further, they have caused considerable number of deaths and property loss. Understanding the behavior and characteristics of these waves, principally their height, propagation velocity, and energy, are key for determining engineering parameters, and therefore developing alert systems and evacuation plans. Several studies have investigated impact waves using experimental, mathematical, and numerical models; however, few have used artificial neural networks. Considering the learning and prediction characteristics of neural networks, this work explores their application in the prediction of impact waves. The main objective is to verify the capability of a fuzzy ARTMAP neural network in predicting the evolution of the maximum wave height, one of the main parameters of impact waves. The experimental data used in this paper are from the work developed by Huber (1980) when studying the impact waves generated by dropping deformable material (granular) in a channel. This study uses different forms of normalization, as well as different training parameters. The Fuzzy ARTMAP neural network predicts adequately the evolution of the maximum wave heights, becoming useful for this kind of application.

Study on the selection and optimization of key elements in the offshore wave prediction

The accuracy of inshore wave prediction is closely related to the key elements selected in the prediction. There is a problem of selecting and sorting the key information needed in wave forecasting. This paper combines AHP with DEA to build a new evaluation model of selecting scheme. By calculating the relative weight of the key information in each selecting scheme and calculating the relative efficiency value of the model, the importance sorting of the elements needed in wave forecasting is obtained, and the specific selection scheme is verified by an example Application. The established AHP-EDA model has the value of trial and extension in supporting the key element selection process of wave prediction.

The Phillips spectrum and a model of wind-wave dissipation

We consider an extension of the kinetic equation developed by Newell & Zakharov (A.C. Newell and V.E. Zakharov. The role of the generalized Phillips' spectrum in wave turbulence. Phys.Lett.A, 372:4230-4233, 2008). The new equation takes into account not only the resonant four-wave interactions but also the dissipation associated with the wave breaking. A dissipation function that depends on the spectral energy flux is introduced into the equation. This function is determined up to a functional parameter, which optimal choice should be made based on comparison with the experiment. A kinetic equation with this dissipation function describes the transition from the Kolmogorov-Zakharov spectrum to the Phillips spectrum usually observed experimentally. The version of the dissipation function expressed in terms of the energy spectrum can be used for wave modeling and prediction of sea waves.