A report on the 3-D acoustic working group meeting at Long Beach, MS July 7-8, 1988

At the request of ONR Code 11250A, the Woods Hole Oceanographic Institution (Dr. James F. Lynch) convened a workshop to bring together a group of acoustic and ocean modelers to review and discuss 1. the state of development and the need for three-dimensional numerical acoustic research propagation and scattering models; 2. the interfacing of acoustic models with available oceanographic data and ocean model outputs. The workshop was hosted by the Institute for Naval Oceanography (Dr. Ching-Sang Chiu) at Long Beach, MS on July 7-8, 1988. This report summarizes the research presentations and the recommendations made by the group. The workshop was an initial attempt to promote the interaction between the ocean and acoustic modeling communities. This interaction between the communities is essential to the development of truly interactive basic research acoustic and ocean models. We anticipate more workshops of such nature to be held in the future. The findings and recommendations generated by these workshops are expected to have a strong impact on the direction of future three-dimensional modeling research in both acoustics and oceanography .Funding was provided by the Office of Naval Research under contract Number N00014-88-K-0363

HF Radar Measurements of Surface Waves in the Gulf of Naples (Southeastern Tyrrhenian Sea): Comparison With Hindcast Results at Different Scales

HF radar systems wave measurements are evaluated against numerical simulations in the Gulf of Naples (Southeastern Tyrrhenian Sea). Wave measurements are obtained from three CODAR SeaSonde HF radars installed along the coast of the Gulf of Naples. The numerical models employed are WavewatchIII, implemented on a regional scale with a resolution of about 10 km in longitude and latitude in the whole Mediterranean Sea, and SWAN, implemented with a 200 m resolution in the area of interest. Numerical simulations are also validated against experimental data acquired by a buoy installed offshore the Gulf of Naples. The agreement between HF radar measurements and model hindcasts is evaluated through the estimate of statistical error indices for the main wave characteristics (significant wave height, mean period, and mean direction). The consistency between wave parameters retrieved by HF radars and hindcasted by the models opens the way to future integration of the two systems as well as to the utilization of HF radar wave parameters that could be envisaged for data assimilation in wave models

Assimilation of ocean-colour plankton functional types to improve marine ecosystem simulations

We assimilated plankton functional types (PFTs) derived from ocean colour into a marine ecosystem model, to improve the simulation of biogeochemical indicators and emerging properties in a shelf sea. Error-characterized chlorophyll concentrations of four PFTs (diatoms, dinoflagellates, nanoplankton and picoplankton), as well as total chlorophyll for comparison, were assimilated into a physical-biogeochemical model of the North East Atlantic, applying a localized Ensemble Kalman filter. The reanalysis simulations spanned the years 1998 to 2003. The skill of the reference and reanalysis simulations in estimating ocean colour and in situ biogeochemical data were compared by using robust statistics. The reanalysis outperformed both the reference and the assimilation of total chlorophyll in estimating the ocean-colour PFTs (except nanoplankton), as well as the not-assimilated total chlorophyll, leading the model to simulate better the plankton community structure. Crucially, the reanalysis improved the estimates of not-assimilated in situ data of PFTs, as well as of phosphate and pCO2, impacting the simulation of the air-sea carbon flux. However, the reanalysis increased further the model overestimation of nitrate, in spite of increases in plankton nitrate uptake. The method proposed here is easily adaptable for use with other ecosystem models that simulate PFTs, for, e.g., reanalysis of carbon fluxes in the global ocean and for operational forecasts of biogeochemical indicators in shelf-sea ecosystems

The impact of stochastic physics on climate sensitivity in EC-Earth

Stochastic schemes, designed to represent unresolved sub-grid scale variability, are frequently used in short and medium-range weather forecasts, where they are found to improve several aspects of the model. In recent years, the impact of stochastic physics has also been found to be beneficial for the model's long term climate. In this paper, we demonstrate for the first time that the inclusion of a stochastic physics scheme can notably affect a model's projection of global warming, as well as its historical climatological global temperature. Specifically, we find that when including the 'stochastically perturbed parametrisation tendencies' scheme (SPPT) in the fully coupled climate model EC-Earth v3.1, the predicted level of global warming between 1850 and 2100 is reduced by 10% under an RCP8.5 forcing scenario. We link this reduction in climate sensitivity to a change in the cloud feedbacks with SPPT. In particular, the scheme appears to reduce the positive low cloud cover feedback, and increase the negative cloud optical feedback. A key role is played by a robust, rapid increase in cloud liquid water with SPPT, which we speculate is due to the scheme's non-linear interaction with condensation.Comment: Under review in Journal of Geophysical Research: Atmosphere

Marine Data Prediction: An Evaluation of Machine Learning, Deep Learning, and Statistical Predictive Models.

Nowadays, ocean observation technology continues to progress, resulting in a huge increase in marine data volume and dimensionality. This volume of data provides a golden opportunity to train predictive models, as the more the data is, the better the predictive model is. Predicting marine data such as sea surface temperature (SST) and Significant Wave Height (SWH) is a vital task in a variety of disciplines, including marine activities, deep-sea, and marine biodiversity monitoring. The literature has efforts to forecast such marine data; these efforts can be classified into three classes: machine learning, deep learning, and statistical predictive models. To the best of the authors' knowledge, no study compared the performance of these three approaches on a real dataset. This paper focuses on the prediction of two critical marine features: the SST and SWH. In this work, we proposed implementing statistical, deep learning, and machine learning models for predicting the SST and SWH on a real dataset obtained from the Korea Hydrographic and Oceanographic Agency. Then, we proposed comparing these three predictive approaches on four different evaluation metrics. Experimental results have revealed that the deep learning model slightly outperformed the machine learning models for overall performance, and both of these approaches greatly outperformed the statistical predictive model

A comprehensive numerical study of aerosol-cloud-precipitation interactions in marine stratocumulus

Three-dimensional large-eddy simulations (LES) with detailed bin-resolved microphysics are performed to explore the diurnal variation of marine stratocumulus (MSc) clouds under clean and polluted conditions. The sensitivity of the aerosol-cloud-precipitation interactions to variation of sea surface temperature, free tropospheric humidity, large-scale divergence rate, and wind speed is assessed. The comprehensive set of simulations corroborates previous studies that (1) with moderate/heavy drizzle, an increase in aerosol leads to an increase in cloud thickness; and (2) with non/light drizzle, an increase in aerosol results in a thinner cloud, due to the pronounced effect on entrainment. It is shown that for higher SST, stronger large-scale divergence, drier free troposphere, or lower wind speed, the cloud thins and precipitation decreases. The sign and magnitude of the Twomey effect, droplet dispersion effect, cloud thickness effect, and cloud optical depth susceptibility to aerosol perturbations (i.e., change in cloud optical depth to change in aerosol number concentration) are evaluated by LES experiments and compared with analytical formulations. The Twomey effect emerges as dominant in total cloud optical depth susceptibility to aerosol perturbations. The dispersion effect, that of aerosol perturbations on the cloud droplet size spectrum, is positive (i.e., increase in aerosol leads to spectral narrowing) and accounts for 3% to 10% of the total cloud optical depth susceptibility at nighttime, with greater influence in heavier drizzling clouds. The cloud thickness effect is negative (i.e., increase in aerosol leads to thinner cloud) for non/light drizzling cloud and positive for a moderate/heavy drizzling clouds; the cloud thickness effect contributes 5% to 22% of the nighttime total cloud susceptibility. Overall, the total cloud optical depth susceptibility ranges from ~0.28 to 0.53 at night; an increase in aerosol concentration enhances cloud optical depth, especially with heavier precipitation and in a more pristine environment. During the daytime, the range of magnitude for each effect is more variable owing to cloud thinning and decoupling. The good agreement between LES experiments and analytical formulations suggests that the latter may be useful in evaluations of the total cloud susceptibility. The ratio of the magnitude of the cloud thickness effect to that of the Twomey effect depends on cloud base height and cloud thickness in unperturbed (clean) clouds

Wave Energy Assessment in Southern Central Java Island and Control Method for Maximizing the Captured Power in Wave Energy Converters

This thesis discusses the wave energy potential of the Indian Ocean on the south coast of Central Java Island, where no previous known similar study has been conducted. A control technique that involves a dynamic electrical model was established. The following objectives were achieved. The first was to determine the ideal location to implement wave energy conversion (WEC), and the second objective was to simulate the significant wave height by using the novel control method. To achieve these goals, the following steps and procedures were implemented. Wave energy assessment was conducted for the Indian Ocean on the south coast of Central Java Island, Indonesia. Results are analyzed with MIKE 21 Spectral Wave by adopting a 10-year hindcast spectral wave model. The model was developed by incorporating wind data from the European Centre for Medium-Range Weather Forecasts with a 0.125° spatial interval and an hourly time resolution. The model was validated with buoy observation data provided by Badan Pengkajian dan Penerapan Teknologi or Agency for the Assessment and Application of Technology, Indonesia. The buoy is located at a longitude of 110.547° and a latitude of −8.1364° and provides monthly data on significant wave height and wave period at an hourly data interval (June 2014). Validation showed that the model result matches the data, and the average error is approximately 0.042%. Time domain monthly analysis revealed that the minimum mean wave power appeared in December, January, and February, whereas the maximum mean wave power occurred in July, August, and September with a value of more than 10 kW/m during the dry season in Indonesia. The dominant significant wave height was between 1 and 2 m. The spatial analysis provided six coordinate points in Penyu Bay and Yogyakarta Coast as candidates for WEC location; the 10-year mean wave power was approximately 13–16 kW/m, and the distance from the coast was less than 350 m. Furthermore, modeling and a control strategy for WECs were discussed. The heaving point absorber from Uppsala University was adopted. The control objective of the proposed method was to maximize the captured mechanical power under the constraint of the maximum control force. The proposed method comprised high-level and low-level controllers. The high-level controller produced the optimum reference in terms of reference velocity to satisfy the control objective. The low-level controller tracked the reference and provided robustness against model uncertainties. The low-level controller was designed before the high-level controller. The main controller in the low-level controller is a proportional–integral–derivative controller. This controller was designed with ∞ theory, and the genetic algorithm was utilized to solve the infinity norm of the robustness problem. The high-level controller was designed by using the obtained dynamic of the feedback control system in the low-level controller with the mechanical model of WECs. Simulation studies were also conducted. Results of nominal and perturbation cases and those of monochromatic and polychromatic sea states were compared

Useful applications of earth-oriented satellites - Oceanography

Planning efforts toward oceanographic satellite system as part of NASA Earth Resources Progra

Retrieval of Ocean Surface Currents and Winds Using Satellite SAR backscatter and Doppler frequency shift

Ocean surface winds and currents play an important role for weather, climate, marine life, ship navigation, oil spill drift and search and rescue. In-situ observations of the ocean are sparse and costly. Satellites provide a useful complement to these observations. Synthetic aperture radar (SAR) is particularly attractive due to its high spatial resolution and its capability to extract both sea surface winds and currents day and night and almost independent of weather.The work in this thesis involves processing of along-track interferometric SAR (ATI-SAR) data, analysis of the backscatter and Doppler frequency shift, and development of wind and current retrieval algorithms. Analysis of the Doppler frequency shift showed a systematic bias. A calibration method was proposed and implemented to correct for this bias. Doppler analysis also showed that the wave contribution to the SAR Doppler centroid often dominates over the current contribution. This wave contribution is estimated using existing theoretical and empirical Doppler models. For wind and current retrieval, two methods were developed and implemented.The first method, called the direct method, consists of retrieval of the wind speed from SAR backscatter using an empirical backscatter model. In order to retrieve the radial current, the retrieved wind speed is used to correct for the wave contribution. The current retrieval was assessed using two different (theoretical and empirical) Doppler models and wind inputs (model and SAR-derived). It was found that the results obtained by combining the Doppler empirical model with the SAR-derived wind speed were more consistent with ocean models.The second method, called Bayesian method, consists of blending the SAR observables (backscatter and Doppler shift) with an atmospheric and an oceanic model to retrieve the total wind and current vector fields. It was shown that this method yields more accurate estimates, i.e. reduces the models biases against in-situ measurements. Moreover, the method introduces small scale features, e.g. fronts and meandering, which are weakly resolved by the models.The correlation between the surface wind vectors and the SAR Doppler shift was demonstrated empirically using the Doppler shift estimated from over 300 TanDEM-X interferograms and ECMWF reanalysis wind vectors. Analysis of polarimetric data showed that theoretical models such as Bragg and composite surface models over-estimate the backscatter polarization ratio and Doppler shift polarization difference. A combination of a theoretical Doppler model and an empirical modulation transfer function was proposed. It was found that this model is more consistent with the analyzed data than the pure theoretical models.The results of this thesis will be useful for integrating SAR retrievals in ocean current products and assimilating SAR observables in the atmospheric, oceanic or coupled models. The results are also relevant for preparation studies of future satellite missions