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Ocean wave forecasting from Sverdrup and Munk to ocean satellites

Ocean wave forecasting from Sverdrup and Munk to ocean satellites. Klaus Hasselmann Max Planck Institute of Meteorology Hamburg. Opening of the Mohn-Sverdrup Center for Global Ocean Studies and Operational Oceanography, Nansen Center, Bergen, 20 th October 2004.

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Ocean wave forecasting from Sverdrup and Munk to ocean satellites

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  1. Ocean wave forecasting from Sverdrup and Munk to ocean satellites Klaus Hasselmann Max Planck Institute of Meteorology Hamburg Opening of the Mohn-Sverdrup Center for Global Ocean Studies and Operational Oceanography, Nansen Center, Bergen, 20th October 2004

  2. Why should someone who has not worked in ocean waves for more than 10 years agree to give this talk? • The name Mohn-Sverdrup Center: The 1947 Sverdrup-Munk paper was the first ocean wave forecasting paper and started a new field, motivating also the speaker. • The co-author of that paper is here and greatly encouraged the speaker as a young scientist working on waves in Walter Munk’s newly founded IGPP in the early sixties. • The famous Munk-Snodgrass et al experiment on swell propagation across the Pacific stimulated the later JONSWAP experiment on wave growth in the North Sea, laying the foundations for the so-called third generation wave model WAM which now runs at more than 200 centers. • The advent of operational global ocean satellites in the last decade, measuring two-dimensional wave spectra day and night in all weathers, has created exciting new challenges. • This is a good opportunity to find out what my former colleagues in ocean wave research have been up to in the last ten years, and distill from this some useful comments …

  3. ….. for example: • the title of my talk should be changed

  4. Ocean wave forecasting from Sverdrup and Munk to ocean satellites, supercomputers and ocean model networks Klaus Hasselmann Max Planck Institute of Meteorology Hamburg Opening of Mohn-Sverdrup Center for Global Ocean Studies and Operational Oceanography, Nansen Center, Bergen, 20th October 2004

  5. ….. for example: • • the title of my talk should be changed • • there is a large applications market for a suite of ocean models built around a set of ocean wave models, run on a supercomputer facility • • the creation of the Mohn-Sverdrup Center is therefore a very timely undertaking, with much of the needed expertise available here in Norway

  6. ….. for example: • • the title of my talk should be changed • • there is a large applications market for a suite of ocean models built around a set of ocean wave models, run on a supercomputer facility • • the creation of the Mohn-Sverdrup Center is therefore a very timely undertaking, with much of the needed expertise available here in Norway • GOOD LUCK OLA!

  7. advances experiment theory modelling events 1 1947 Sverdrup-Munk windsea and swell forecasts: empirical prediction of significant wave height Hs and period Tsas function of fetch and duration

  8. advances experiment theory modelling events 1 2 1957: Theories of wave generation (Phillips, Miles), nonlinear energy transfer(H), spectral transport equation (Gelci et al, H)

  9. SPECTRAL WAVE TRANSPORT EQUATION The action density N is conserved in water with slowly varying depth h and current U = Source terms: Swind+Sdiss + (Snonlin)) group velocity refraction

  10. advances experiment theory modelling events 1 2 3 1964 Snodgrass, Munk et al. Wave propagation across the Pacific. First derivation of spectral energy balance for swell from large instrument array

  11. advances experiment theory modelling events 1 2 3 4 1966-69: First wave models based on spectral transport equation (Pierson-Tick, Barnett, Ewing)

  12. JONSWAP experiment

  13. JONSWAP experiment

  14. advances experiment theory modelling events 1 2 3 4 5 1969: JONSWAP, windsea growth measurements with large instrument array in the North Sea

  15. The JONSWAP spectrum E JONSWAP: Pierson-Moskowitz: f

  16. The JONSWAP spectrum E JONSWAP: peak grows Pierson-Moskowitz: Snl weak, no shift in peak f

  17. The JONSWAP spectrum E JONSWAP: Snl dominant, shift in peak peak shifts peak grows Pierson-Moskowitz: Snl weak, no shift in peak f

  18. But: The computation of the five-dimensional nonlinear transfer integral was too time-consuming to be applied in routine wave forecasting model. Therefore:

  19. advances experiment theory modelling back to square 1! events 1 2 3 4 5 1969: JONSWAP, windsea growth measurements with large instrument array in the North Sea

  20. Why did the fetch laws of Sverdrup and Munk work reasonably well? Because the nonlinear tranfer continually adjusts the windsea spectrum to a quasi-universal form, independent of the details of the space-time structure of the generating windfield. One can then derive dynamical equations for the evolution of the characteristic scale variables Hs and Ts of the windsea spectrum. This can be augmented by the existent spectral transport models for swell. => 2nd generation wave models

  21. advances experiment theory modelling Marginal improvement over square 1 events 1 2 3 4 5 6 1974: Second generation wave models: dynamic eqs. for Hs and Ts

  22. advances experiment theory modelling events 1 2 3 4 5 6 7 1979: SEASAT, MARSEN (Marine Remote Sensing Experiment)

  23. SEASAT 79, MARSEN

  24. advances experiment theory modelling events 1 2 3 4 5 6 7 8 1980-85: SWAMP, DIA nonlinear wave transfer, 3rd generation wave model WAM, SAR inversion

  25. advances experiment theory modelling events 1 2 3 4 5 6 7 8 9 The 90’s: begin of global ocean satellite era: ERS1/2, Topex/Poseidon, Envisat,…

  26. Global, all weather, day-and night measurements of: • wave height (altimeter) • two dimensional wave spectra (SAR) • surface wind speed and direction (scatterometer) • sea surface elevation (altimeter) • sea ice extent and age (microwaves, SAR) • sea surface temperature (microwaves and IR, when cloud free) • sea surface colour (multi-spectral optics - for daytime clear-sky )

  27. Patrick Heimbach

  28. Patrick Heimbach

  29. Challenges of global ocean satellites for ocean wave modelling • Retrieval of wave height and ocean wave spectra from satellite data: in the case of the SAR, this requires complex nonlinear integral inversion algorithms • Assimilation of retrieved wave data in wave models

  30. + OTHER APPLICATIONS

  31. Challenges of global ocean satellites for ocean wave modelling • Retrieval of wave height and ocean wave spectra from satellite data: in the case of the SAR, this requires complex nonlinear integral inversion algorithms • Assimilation of retrieved wave data in wave models • Continual improvements of wave models based on routine quality checking against satellite data

  32. PARSA StatisticsSouthern Winter 1996 HsPARSA [m] fmPARSA [Hz] PARSA HsECMWF [m] fmECMWF [Hz] • Indication ofModel underestimates Hs at high sea states • Indication formodel underestimates of mean period for longer waves J.Schulz-Stellenfleth

  33. Challenges of global ocean satellites for ocean wave modelling • Retrieval of wave height and ocean wave spectra from satellite data: in the case of the SAR, this requires complex nonlinear integral inversion algorithms • Assimilation of retrieved wave data in wave models • Continual improvements of wave models based on routine quality checking against satellite data • Implication for application centres such as the Mohn-Sverdrup Center: strong interaction with operational forecasting centres such as ECMWF

  34. Applications of ocean modelling • ship routing based on global wind and wave forecasts (e.g. from ECMWF)

  35. Applications of ocean modelling • ship routing based on global wind and wave forecasts (e.g. from ECMWF) • origin and impact of freak waves

  36. Selkirk, Fall 1988, steel from Europe to North America seas up to 80 feet, microburst anemometer 90 knots, 12 feet crack Def. Rogue waves: 2 times significant wave height, up 30 deg out of the usual sea way

  37. Origin: • Are they simply the tail end of the linear Gaussian distribution of wave heights? • Or do they represent a fundamentally strongly nonlinear phenomenon? • Do they depend on the occurrence of non-equilibrium “super-saturated” spectra, for example in localized cross-sea areas?

  38. Origin: • Are they simply the tail end of the linear Gaussian distribution of wave heights? • Or do they represent a fundamentally strongly nonlinear phenomenon? • Do they depend on the occurrence of non-equilibrium “super-saturated” spectra, for example in localized cross-sea areas? Impact: • ship motions

  39. Application of the Wave Elevation Maps: Numerical Studies of Vessel Stability under heavy Sea States* Phase 2 Phase 1 Phase 3 Phase 4 Phase 5 • Courtesy Pastor Wouter DNV, Norway • OMAE 2003 Maxwave project

  40. Simulation von Schiffsbewegungen (FSG) Hochaufgelöste zeitliche und räumliche DatenBeispiel: Seegang 28.12.1961-03.01.1962 Heinz Günther & Jan Tellkamp (FSG), Seegang: HIPOCAS

  41. Origin: • Are they simply the tail end of the linear Gaussian distribution of wave heights? • Or do they represent a fundamentally strongly nonlinear phenomenon? • Do they depend on the occurrence of non-equilibrium “super-saturated” spectra, for example in localized cross-sea areas? Impact: • ship motions • ship safety and insurance industry

  42. Global Sea State - Ship losses • EU Project MAXWAVE • PI: GKSS, W.Rosenthal • DLR • Universities • Weather centers • Ship building • Norske Veritas • 43,600 Ships of trade, 1.2 Million People • Rate of loss 130 Ships p.a. • 1000 sailors lose their life every year • GOALS • Existence • Forecasting • Improved Design

  43. Applications of ocean modelling • ship routing based on global wind and wave forecasts (e.g. from ECMWF) • origin and impact of freak waves • coupled high resolution wind, wave, storm surge, current, transport models, nested in global forecast, hindcast or climate models, for comprehensive studies (e.g. offshore oil operations, windparks, salmon farms, coastal protection …. )

  44. Applications of ocean modelling • ship routing based on global wind and wave forecasts (e.g. from ECMWF) • origin and impact of freak waves • coupled high resolution wind, wave, storm surge, current, transport models, nested in global forecast, hindcast or climate models, for comprehensive studies (e.g. offshore oil operations, windparks, salmon farms, coastal protection …. ) An example: the suite of models developed at GKSS (Geesthacht Forschungszentrum, near Hamburg) in collaboration with DKRZ, MPIM, BSH, DWD and other institutions

  45. Compilation of 44 years of wind, waves, currents and sea level NCEP Globale Reanalysen ( 210 km x 210 km )1958 - 2002 BAW - TELEMAC 2DWasserstand und barotrope Strömung 21.02.1993 12 UTC REMO Windgeschwindigkeit und Richtung 21.02.1993 12 UTC HIPOCAS:Für Rekonstruktionen verwendete Modellkette Gebiet hier: Nordsee und östlicher Nordatlantik WAM sig. Wellenhöhe und Richtung 21.02.1993 12 UTC Auflösung etwa 50 x 50 km Auflösung zwischen etwa 100 m und 5km Auflösung etwa 5 x 5 km

  46. Past trends in frequency and intensity of extreme sea states Rekonstruktion der Vergangenheit Beispiel: Rekonstruierte Trends Änderung der Häufigkeit von extremen Seegangsereignissen Beispiel: Rekonstruierte Trends Änderung der Intensität dieser Ereignisse

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