High-Resolution Measurement-Based Phase-Resolved Prediction of Ocean Wavefields

Transcription

1 High-Resoltion Measrement-Based Phase-Resolved Prediction of Ocean Wavefields Lian Shen Department of Civil Engineering Johns Hopkins University Baltimore, MD phone: (410) fax: (410) Award Nmber: N LONG-TERM GOAL The primary focs of this research is to develop a phase-resolved capability for intermediate scale, O(10)km, wave environment prediction by integrating whole-field and mltiple-point direct measrements of the wave and atmospheric environment with nonlinear simlation-based reconstrction of the wavefield. Given remote and direct physical measrements of a realistic ocean wavefield, we aim to obtain a high-resoltion description of the wavefield with direct wave comptations inclding realistic environmental effects sch as wind forcing and wave breaking dissipation. We will inform and gide the measrements necessary for achieving this reconstrction and address the validity, accracy and limitations of sch wavefield reconstrctions. OBJECTIVES The scientific and technical objectives of this research are: development of wave reconstrction and prediction capability nderstanding reliability/accracy/robstness and limitations of direct wave measrement based, phase-resolved modeling direct qantitative comparisons between wave model prediction and field measrements APPROACH For wave reconstrction and prediction, we se a high-order spectral (HOS) method to simlate fll nonlinear wave interactions inclding wind forcing and wave breaking modeling. The simlation ses as inpt hybrid (radar and probe) measrement data that may be noisy, ncertain/incomplete. Physicsbased wind-forcing models will be developed based on a copling of large-eddy simlation of winds (LES) and large-wave simlation (LWS) of dynamic waves and wave grops with nonlinear wavefield evoltion comptations. We will adopt an adaptive simlation methodology to model local steep wave dynamics and wave breaking, and incorporate wave breaking dissipation into deterministic wave reconstrction and forecast. The simlation will be compared to and validated with field measrements directly. Finally, a mltiscale approach will be employed to incorporate data from meso-scale meteorological models, ABL simlations, fine-scale CFD, and field measrements at varios scales to provide spatial-temporal inpt for wavefield simlation. 1

2 Report Docmentation Page Form Approved OMB No Pblic reporting brden for the collection of information is estimated to average 1 hor per response, inclding the time for reviewing instrctions, searching existing data sorces, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this brden estimate or any other aspect of this collection of information, inclding sggestions for redcing this brden, to Washington Headqarters Services, Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Site 1204, Arlington VA Respondents shold be aware that notwithstanding any other provision of law, no person shall be sbject to a penalty for failing to comply with a collection of information if it does not display a crrently valid OMB control nmber. 1. REPORT DATE 30 SEP REPORT TYPE Annal 3. DATES COVERED to TITLE AND SUBTITLE High-Resoltion Measrement-Based Phase-Resolved Prediction Of Ocean Wavefields 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Johns Hopkins University,Department of Civil Engineering,Baltimore,MD, PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10. SPONSOR/MONITOR S ACRONYM(S) 12. DISTRIBUTION/AVAILABILITY STATEMENT Approved for pblic release; distribtion nlimited 13. SUPPLEMENTARY NOTES code 1 only 14. ABSTRACT 11. SPONSOR/MONITOR S REPORT NUMBER(S) 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT a. REPORT nclassified b. ABSTRACT nclassified c. THIS PAGE nclassified Same as Report (SAR) 18. NUMBER OF PAGES 8 19a. NAME OF RESPONSIBLE PERSON Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18

3 In order to nderstand the reliability/accracy/robstness and limitations of direct wave measrement based phase-resolved modeling, we will first se the existing wave reconstrction/prediction capability and available radar data to test ot the accracy of radar measrements of ocean srface waves and to answer the fndamental qestion of how well marine radar systems can represent the ocean srface wave field. Based on spatial/temporal predictions of simlated wavefields in relation to hybrid radar and probe wave data, we will then develop a theoretical framework for giding deployment of wave sensing systems and data tilization and interpretation. We will se existing radar wave measrements to test and to validate the accracy of the reconstrction and forecasting model, to investigate the niqeness and robstness of the reconstrction scheme, and to develop a framework to properly retrieve wave information in shadows and gaps of radar-sensed wavefield data. Finally, we will characterize and qantify the effects of noise and ncertainty in sensing data on phase-resolved wavefield prediction, and develop efficacios approaches to minimize these effects in the prediction. Direct qantitative comparisons between wave model prediction and field measrements will be performed. We will first analyze and incorporate measrement data for development of efficient wind forcing and wave breaking dissipation models in direct physical context. The phase-resolved wave simlation will then be sed as a powerfl vehicle to nderstand effects of local trblence processes on large-scale nonlinear wavefield evoltion dynamics. Finally, we will evalate and qantify the validity, efficacy, and limitations of the overall approach, and to develop models and parameterizations to gide practical applications based on this capability. WORK COMPLETED Fiscal year of 2007 is the planning year for this five-year High Resoltion Air-Sea Interaction DRI. The major work incldes: Attending two planning meetings in SIO in March and Jne, respectively; interacting with other investigators; contribting to the science plan. Frther development of nmerical capabilities for the interaction of ocean and wind trblence with dynamically-evolving srface waves. Initial investigation of pressre variation in wind-wave field for the modeling of wind inpt to wavefield. Initial investigation of mltiscale modeling and data assimilation. RESULTS The main task in this fiscal year is the planning of the DRI. We attended the two planning meetings at SIO in March and Jne, respectively. We interacted with other investigators, participated in the planning of field measrements in the coming years, and contribted to the science plan. Besides the planning activities, sbstantial stdy on the modeling for high-resoltion phase-resolved wave simlation has been performed. One important qestion is how the pressre varies in wind-wave interactions. Sch information is essential for the deployment of pressre sensors in the DRI. It also plays an important role in the stdy of effects of wind inpt on the deterministic prediction of wave 2

4 propagation. In connection with the PI s YIP project, we investigated pressre statistics in wind-wave interactions. Figre 1 shows the phase-averaged wave-correlated pressre contors of winds over waves with wave age = 2 and 14. It is fond that, for the yong wave with wave age = 2, the pressre contors are tilted at a short distance above the wave. For the intermediate wave with = 14, the high pressre region does not extend vertically mch comparing to the wave crest. In the presence of a wind-generated srface drift, the low pressre region is shifted towards the trogh, while the high pressre region is extended slightly towards the downstream direction. The effect of srface drift on the pressre field for the intermediate wave is less obvios. From the above observation, it is clear that the pressre field information may vary significantly in the vertical direction near the water srface, which indicates the importance of obtaining correct pressre data near the water srface. While Figre 1 considers the averaged effect of wind inpt to waves, it is also important to consider the flctation of the wind pressre. Sch gst effect may be essential for the investigation of wave deterministic prediction, and it is likely that or wind inpt model will have a stochastic component in addition to the phase-resolved mean wind inpt. For this prpose, we investigated the probability density distribtion of the pressre. Figre 2 shows that the yong wave has a wider pressre distribtion, i.e. more variation, than the matre wave. It is also fond that the yong wave is affected sbstantially by the wind-indced srface drift. Figre 3 shows that in the presence of a wind drift, there exists a significant downstream phase drift, which needs to be captred in the phase-resolved wave prediction for growing sea. Figre 4 compares the histograms of pressre distribtion at two different heights above the wave. It is shown that at the leeside and at the trogh, the pressre obtained at some distance above has more flctations than the tre wind inpt at the wave srface. Sch effects shold be taken into accont in the deployment of pressre measrement sensors and in the analysis of wind inpt data. An important isse in this DRI is the mltiscale modeling and data assimilation for varios measrement and modeling components that are at different scales. It is essential for the SNOW simlation to have wind inpt over the entire prediction domain at a resoltion that matches the simlation. In the fiscal year of 2007, we stdied a promising mltiscale modeling and data assimilation approach. Or method bilds on physics-based pscaling, which links the small-scale physics to parameterization at large scale (a typical example is the extraction of srface roghness for large-scale atmospheric modeling from phase-resolved wave simlation), and on downscaling, which interpolates small-scale phenomena from large-scale data (e.g. from COAMPS or remote sensing data). The downscaling and pscaling modeling are dynamically connected by a sccessive mltiscale simlation approach we developed. While Figres 1 to 4 are for small-scale simlations, large-scale simlation is illstrated in the example shown in Figre 5. In Figre 5, the interaction of the winds with a JONSWAP wavefield is simlated. The coherent wave-indced strctres in the atmosphere as well as small-scale flctations are clearly seen. This mltiscale modeling approach, together with the advanced data assimilation techniqes sing observability with model variability and sbdomain observability, is among the topics of or ongoing research. We hope they will enable s to integrate direct and remote ocean sensing sch as radar and lidar into reliable reconstrction and prediction of the phase-resolved wavefield. 3

5 IMPACT/APPLICATION This project is part of an overall coordinated effort involving experimentalists and modelers aiming at basic scientific nderstanding of the air-sea-wave interaction physics and nmerical prediction capability development. Developments in this project wold lead to improved predictions of the phase-resolved srface wavefield arond srface vessels and contribte to the safety and effectiveness of naval operations and sea keeping in moderate to high winds and sea states. RELATED PROJECTS This work is part of the ONR High Resoltion Air-Sea Interaction DRI. Figre 1. Phase-averaged wave-correlated pressre contors for srface waves with wave age = 2 and 14, respectively. In the two lower figres, the wind-generated srface drift is considered. 4

6 Figre 2. Probability density fnction of pressre on the srface of water waves for wave ages of = 2, 14, and 25. Here, the wind-generated srface drift is considered in the three figres on the right. The pressre vale is normalized by the root-meansqare of the srface pressre flctation. Figre 3. Phase shift effect cased by wind-generated srface drift. 5

7 Figre 4. Histograms of pressre distribtion probability at different locations for wind over water wave. Wave age is = 2. Here, the pressre is normalized by the rootmean-sqare of the srface pressre flctation. 6

8 Figre 5. Illstration of pressre distribtion in the wind field over water waves at large scales. The wavefield is obtained from HOS wave simlation of a JONSWAP spectrm. 7