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Duda T.F., W.G. Zhang, K.R. Helfrich, A.E. Newhall, Y.-T. Lin, J.F. Lynch, P.F.J. Lermusiaux, P.J. Haley Jr., J. Wilkin, 2014. Issues and Progress in the Prediction of Ocean Submesoscale Features and Internal Waves. OCEANS'14 MTS/IEEE.
Data-constrained dynamical ocean modeling for the purpose of detailed forecasting and prediction continues to evolve and improve in quality. Modeling methods and computational capabilities have each improved. The result is that mesoscale phenomena can be modeled with skill, given sufficient data. However, many submesoscale features are less well modeled and remain largely unpredicted from a deterministic event standpoint, and possibly also from a statistical property standpoint. A multi-institution project is underway with goals of uncovering more of the details of a few submesoscale processes, working toward better predictions of their occurrence and their variability. A further component of our project is application of the new ocean models to ocean acoustic modeling and prediction. This paper focuses on one portion of the ongoing work: Efforts to link nonhydrostatic-physics models of continental-shelf nonlinear internal wave evolution to data-driven regional models. Ocean front-related effects are also touched on.
Colin, M.E.G.D., T.F. Duda, L.A. te Raa, T. van Zon, P.J. Haley, Jr., P.F.J. Lermusiaux, W.G. Leslie, C. Mirabito, F.P.A. Lam, A.E. Newhall, Y.-T. Lin, J.F. Lynch, 2013. Time-Evolving Acoustic Propagation Modeling in a Complex Ocean Environment, Proceedings of OCEANS - Bergen, 2013 MTS/IEEE , vol., no., pp.1,9, 10-14 June 2013, doi: 10.1109/OCEANS-Bergen.2013.6608051.
During naval operations, sonar performance estimates often need to be computed in-situ with limited environmental information. This calls for the use of fast acoustic propagation models. Many naval operations are carried out in challenging and dynamic environments. This makes acoustic propagation and sonar performance behavior particularly complex and variable, and complicates prediction. Using data from a field experiment, we have investigated the accuracy with which acoustic propagation loss (PL) can be predicted, using only limited modeling capabilities. Environmental input parameters came from various sources that may be available in a typical naval operation.
The outer continental shelf shallow-water experimental area featured internal tides, packets of nonlinear internal waves, and a meandering water mass front. For a moored source/receiver pair separated by 19.6 km, the acoustic propagation loss for 800 Hz pulses was computed using the peak amplitude. The variations in sound speed translated into considerable PL variability of order 15 dB. Acoustic loss modeling was carried out using a data-driven regional ocean model as well as measured sound speed profile data for comparison. The acoustic model used a two-dimensional parabolic approximation (vertical and radial outward wavenumbers only). The variance of modeled propagation loss was less than that measured. The effect of the internal tides and sub-tidal features was reasonably well modeled; these made use of measured sound speed data. The effects of nonlinear waves were not well modeled, consistent with their known three-dimensional effects but also with the lack of measurements to initialize and constrain them.
Gawarkiewicz, G., S. Jan, P.F.J. Lermusiaux, J.L. McClean, L. Centurioni, K. Taylor, B. Cornuelle, T.F. Duda, J. Wang, Y.J. Yang, T. Sanford, R.-C. Lien, C. Lee, M.-A. Lee, W. Leslie, P.J. Haley Jr., P.P. Niiler, G. Gopalakrishnan, P. Velez-Belchi, D.-K. Lee, and Y.Y. Kim. 2011. Circulation and intrusions northeast of Taiwan: Chasing and predicting uncertainty in the cold dome. Oceanography, 24(4):110-121, http://dx.doi.org/10.5670/oceanog.2011.99.
An important element of present oceanographic research is the assessment and quantification of uncertainty. These studies are challenging in the coastal ocean due to the wide variety of physical processes occurring on a broad range of spatial and temporal scales. In order to assess new methods for quantifying and predicting uncertainty, a joint Taiwan-US field program was undertaken in August/ September 2009 to compare model forecasts of uncertainties in ocean circulation and acoustic propagation, with high-resolution in situ observations. The geographical setting was the continental shelf and slope northeast of Taiwan, where a feature called the “cold dome” frequently forms. Even though it is hypothesized that Kuroshio subsurface intrusions are the water sources for the cold dome, the dome’s dynamics are highly uncertain, involving multiple scales and many interacting ocean features. During the experiment, a combination of near-surface and profiling drifters, broadscale and high-resolution hydrography, mooring arrays, remote sensing, and regional ocean model forecasts of fields and uncertainties were used to assess mean fields and uncertainties in the region. River runoff from Typhoon Morakot, which hit Taiwan August 7-8, 2009, strongly affected shelf stratification. In addition to the river runoff, a cold cyclonic eddy advected into the region north of the Kuroshio, resulting in a cold dome formation event. Uncertainty forecasts were successfully employed to guide the hydrographic sampling plans. Measurements and forecasts also shed light on the evolution of cold dome waters, including the frequency of eddy shedding to the north-northeast, and interactions with the Kuroshio and tides. For the first time in such a complex region, comparisons between uncertainty forecasts and the model skill at measurement locations validated uncertainty forecasts. To complement the real-time model simulations, historical simulations with another model show that large Kuroshio intrusions were associated with low sea surface height anomalies east of Taiwan, suggesting that there may be some degree of predictability for Kuroshio intrusions.
Gangopadhyay, A., P.F.J. Lermusiaux, L. Rosenfeld, A.R. Robinson, L. Calado, H.S. Kim, W.G. Leslie and P.J. Haley, Jr., 2011. The California Current System: A Multiscale Overview and the Development of a Feature-Oriented Regional Modeling System (FORMS). Dynamics of Atmospheres and Oceans, 52, 131-169, doi:10.1016/j.dynatmoce.2011.04.003.
Duda, T.F., Y.-T. Lin, W.G. Zhang, B.D. Cornuelle, P.F.J. Lermusiaux, 2011. Computational Studies of 3D Ocean sound fields in areas of complex seafloor topography and active ocean dynamics. Proceedings of the 10th International Conference on Theoretical and Computational Acoustics, NTU, Taiwan, 12pp.
Lermusiaux, P.F.J., J. Xu, C.F. Chen, S. Jan, L.Y. Chiu and Y.-J. Yang, 2010. Coupled Ocean-Acoustic prediction of transmission loss in a continental shelfbreak region: predictive skill, uncertainty quantification and dynamical sensitivities. IEEE Transactions, Journal of Oceanic Engineering, 35(4) 895-916. doi:10.1109/JOE.2010.2068611.
Ramp, S.R., R. E. Davis, N. E. Leonard, I. Shulman, Y. Chao, A. R. Robinson, J. Marsden, P.F.J. Lermusiaux, D. Fratantoni, J. D. Paduan, F. Chavez, F. L. Bahr, S. Liang, W. Leslie, and Z. Li, 2009. Preparing to Predict: The Second Autonomous Ocean Sampling Network (AOSN-II) Experiment in the Monterey Bay. Special issue on AOSN-II, Deep Sea Research, Part II, 56, 68-86, doi: 10.1016/j.dsr2.2008.08.013.
Haley, P.J. Jr., P.F.J. Lermusiaux, A.R. Robinson, W.G. Leslie, O. Logutov, G. Cossarini, X.S. Liang, P. Moreno, S.R. Ramp, J.D. Doyle, J. Bellingham, F. Chavez, S. Johnston, 2009. Forecasting and Reanalysis in the Monterey Bay/California Current Region for the Autonomous Ocean Sampling Network-II Experiment. Special issue on AOSN-II, Deep Sea Research, Part II. ISSN 0967-0645, doi: 10.1016/j.dsr2.2008.08.010.
Lam, F.P, P.J. Haley, Jr., J. Janmaat, P.F.J. Lermusiaux, W.G. Leslie, and M.W. Schouten, 2009. At-sea Real-time Coupled Four-dimensional Oceanographic and Acoustic Forecasts during Battlespace Preparation 2007. Special issue of the Journal of Marine Systems on "Coastal processes: challenges for monitoring and prediction", Drs. J.W. Book, Prof. M. Orlic and Michel Rixen (Guest Eds.), 78, S306-S320, doi: 10.1016/j.jmarsys.2009.01.029.
Xu, J., P.F.J. Lermusiaux, P.J. Haley Jr., W.G. Leslie and O.G. Logutov, 2008. Spatial and Temporal Variations in Acoustic propagation during the PLUSNet-07 Exercise in Dabob Bay. Acoustical Society of America, Proceedings of Meetings on Acoustics (POMA). 155th Meeting, Vol. 4. 11pp. doi: 10.1121/1.2988093.
Robinson, A.R. and P.F.J. Lermusiaux, 2004. Prediction Systems with Data Assimilation for Coupled Ocean Science and Ocean Acoustics, Proceedings of the Sixth International Conference on Theoretical and Computational Acoustics (A. Tolstoy, et al., editors), World Scientific Publishing, 325-342. Refereed invited Keynote Manuscript.
Robinson, A.R., J. Sellschopp, W.G. Leslie, A. Alvarez, G. Baldasserini, P.J. Haley, P.F.J. Lermusiaux, C.J. Lozano, E. Nacini, R. Onken, R. Stoner, P. Zanasca, 2003. Forecasting synoptic transients in the Eastern Ligurian Sea. In "Rapid Environmental Assessment", Bovio, E., R. Tyce and H. Schmidt (Editors), SACLANTCEN Conference Proceedings Series CP-46, Saclantcen, La Spezia, Italy.
Oceanographic conditions in the Gulf of Procchio, along the northern Elba coast, are influenced by the circulation in the Corsica channel and the southeastern Ligurian Sea. In order to support ocean prediction by nested models, an initial 4-day CTD survey provided initial ocean conditions. The purposes of the forecasts were threefold: i) in support of AUV exercises; ii) as an experiment in the development of rapid environmental assessment (REA) methodology; and, iii) as a rigorous real time test of a distributed ocean ocean prediction system technology. The Harvard Ocean Prediction System (HOPS) was set up around Elba in a very high resolution domain (225 m horizontally) which was two-way nested in a high resolution domain (675 m) in the channel between Italy and Corsica. The HOPS channel domain was physically interfaced with a one-way nest to the CU-POM model run in a larger Ligurian Sea domain. Eleven nowcasts and 2-3 day forecasts were issued during the period 26 September to 10 October, 2000 for the channel domain and for a Procchio Bay operational sub-domain of the Elba domain.
After initialization with the NRV Alliance, CTD survey data adaptive sampling patterns for nightly excursions of the Alliance were designed on the basis of forecasts to obtain data for assimilation which would most efficiently maintain the structures and variability of the flow in future dynamical forecasts. Images of satellite sea surface temperature were regularly processed and used for track planning and also for model verification. Rapid environmental assessment (REA) techniques were used for data processing and transmission from ship to shore and vice versa for model results. ADCP data validated well the flow in the channel. Additionally and importantly, the direction and strength of the flow in Procchio Bay were correctly forecast by dynamics supported only by external observations. CU-POM model hydrographic and geostrophic flow data was assimilated successfully on boundary strips of the HOPS domain. Flow fields with/without CU-POM nesting were qualitatively similar and a quantitative analysis of differences is under study. A significant result was the demonstration of a powerful and efficient distributed ocean observing and prediction system with in situ data collected in the Ligurian Sea, satellite data collected at SACLANTCEN, forecast modeling at Harvard University and the University of Colorado, and adaptive sampling tracks designed at Harvard. The distributed system functioned smoothly and effectively and coped with the adverse six-hour time difference between Massachusetts and Italy.
Besiktepe, S.T., P.F.J. Lermusiaux and A.R. Robinson, 2003. Coupled physical and biogeochemical data driven simulations of Massachusetts Bay in late summer: real-time and post-cruise data assimilation. Special issue on "The use of data assimilation in coupled hydrodynamic, ecological and bio-geo-chemical models of the oceans", M. Gregoire, P. Brasseur and P.F.J. Lermusiaux (Eds.), Journal of Marine Systems, 40, 171-212.
Lermusiaux, P.F.J., C.-S. Chiu and A.R. Robinson, 2002. Modeling Uncertainties in the Prediction of the Acoustic Wavefield in a Shelfbreak Environment. Refereed invited Manuscript, Proceedings of the 5th International conference on theoretical and computational acoustics, May 21-25, 2001. (Eds: E.-C. Shang, Q. Li and T.F. Gao), World Scientific Publishing Co., 191-200.
Robinson, A.R., B.J. Rothschild, W.G. Leslie, J.J. Bisagni, M.F. Borges, W.S. Brown, D. Cai, P. Fortier, A. Gangopadhyay, P.J. Haley, Jr., H.S. Kim, L. Lanerolle, P.F.J. Lermusiaux, C.J. Lozano, M.G. Miller, G. Strout and M.A. Sundermeyer, 2001. The development and demonstration of an advanced fisheries management information system. Proc. of the 17th Conference on Interactive Information and Processing Systems for Meteorology, Oceanography and Hydrology, Albuquerque, New Mexico. American Meteorological Society, 186-190.
Fishery management regulates size and species-specific fishing mortality to optimize biological production from the fish populations and economic production from the fishery. Fishery management is similar to management in industries and in natural resources where the goals of management are intended to optimize outputs relative to inputs. However, the management of fish populations is among the most difficult. The difficulties arise because (a) the dynamics of the natural production system are extremely complicated; involving an infinitude of variables and interacting natural systems and (b) the size-and species-specific fishing mortality (i.e. system control) is difficult to measure, calibrate, and deploy. Despite the difficulties, it is believed that significant advances can be made by employing a fishery management system that involves knowing the short-term (daily to weekly) variability in the structures of environmental and fish fields. We need new information systems that bring together existing critical technologies and thereby place fishery management in a total-systems feedback-control context. Such a system would monitor the state of the structure of all stocks simultaneously in near real-time, be adaptive to the evolving fishery and consider the effects of the environment and economics. To do this the system would need to (a) employ new in situ and remote sensors in innovative ways, (b) develop new data streams to support the development of new information, (c) employ modern modeling, information and knowledge-base technology to process the diverse information and (d) generate management advice and fishing strategies that would optimize the production of fish.
The Advanced Fisheries Management Information System (AFMIS), built through a collaboration of Harvard University and the Center for Marine Science and Technology at the University of Massachusetts at Dartmouth, is intended to apply state-of-the-art multidisciplinary and computational capabilities to operational fisheries management. The system development concept is aimed toward: 1) utilizing information on the “state” of ocean physics, biology, and chemistry; the assessment of spatially-resolved fish-stock population dynamics and the temporal-spatial deployment of fishing effort to be used in fishing and in the operational management of fish stocks; and, 2) forecasting and understanding physical and biological conditions leading to recruitment variability. Systems components are being developed in the context of using the Harvard Ocean Prediction System to support or otherwise interact with the: 1) synthesis and analysis of very large data sets; 2) building of a multidisciplinary multiscale model (coupled ocean physics/N-P-Z/fish dynamics/management models) appropriate for the northwest Atlantic shelf, particularly Georges Bank and Massachusetts Bay; 3) the application and development of data assimilation techniques; and, 4) with an emphasis on the incorporation of remotely sensed data into the data stream.
AFMIS is designed to model a large region of the northwest Atlantic (NWA) as the deep ocean influences the slope and shelves. Several smaller domains, including the Gulf of Maine (GOM) and Georges Bank (GB) are nested within this larger domain (Figure 1). This provides a capability to zoom into these domains with higher resolution while maintaining the essential physics which are coupled to the larger domain. AFMIS will be maintained by the assimilation of a variety of real time data. Specifically this includes sea surface temperature (SST), color (SSC), and height (SSH) obtained from several space-based remote sensors (AVHRR, SeaWiFS and Topex/Poseidon). The assimilation of the variety of real-time remotely sensed data supported by in situ data will allow nowcasting and forecasting over significant periods of time.
A real-time demonstration of concept (RTDOC) nowcasting and forecasting exercise to demonstrate important aspects of the AFMIS concept by producing real time coupled forecasts of physical fields, biological and chemical fields, and fish abundance fields took place in March-May 2000. The RTDOC was designed to verify the physics, to validate the biology and chemistry but only to demonstrate the concept of forecasting the fish fields, since the fish dynamical models are at a very early stage of development. In addition, it demonstrated the integrated system concept and the implication for future coupling of a management model. This note reports on the RTDOC.
Robinson, A.R. and the LOOPS Group, 1999. Real-time Forecasting of the Multidisciplinary Coastal Ocean with the Littoral Ocean Observing and Predicting System (LOOPS). Preprint Volume of the Third Conference on Coastal Atmospheric and Oceanic Prediction and Processes, 3-5 November 1999, New Orleans, LA, American Meteorological Society, Boston, MA.