The Netherlands. The Netherlands: 18% water (area) 180 x 300 km2; ~ 21% below sea population: 17 mln; ~ 30-40% below sea 2

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Transcription:

(3) Where Applied Mathematics, Hydrodynamics and Ocean Science meet: Predictive, Diagnostic & Sea Going Assessments of Water levels & Global- and Internal Tides 1: Dr. R. (Ramses) van der Toorn, Prof. Dr. A.W. Heemink, (TUD) 2: Dr. M. Verlaan (Deltares) 3: Dr. Th. Gerkema, Dr. H. van Haren (NIOZ) (2) (1 )

The Netherlands The Netherlands: 18% water (area) 180 x 300 km2; ~ 21% below sea population: 17 mln; ~ 30-40% below sea 2

The Netherlands The Netherlands: water management 1953 flood: 1800 killed, 100000 lost home. Oosterscheldekering (finished 1986) Oosterschelde: crucial eco-zone ocean species breed here 3

The Netherlands The Netherlands Rotterdam harbor: largest port in Europe offshore 4 Petrochemicals

The Netherlands The Netherlands Rotterdam harbor: largest port in Europe Maeslantkering: storm surge protection: 5

Water Level / Storm Surge Forecasting Dutch Continental Shelf Model (DCSMv6) Water Level Forecasting content: non-linear shallow water dynamics captures tide-surge interaction 6

Water Level / Storm Surge Forecasting Dutch Continental Shelf Model (DCSMv6) Water Level Forecasting content: non-linear shallow water dynamics captures tide-surge interaction bathymetry 7

Water Level / Storm Surge Forecasting Dutch Continental Shelf Model (DCSMv6) Water Level Forecasting content: non-linear shallow water dynamics captures tide-surge interaction bathymetry forcing: tidal (gravity field: sun, moon)* meteorology (pressure, winds) R Re α 8 *Courtesy: E. Schrama, TU Delft

Water Level / Storm Surge Forecasting Dutch Continental Shelf Model (DCSMv6) Water Level Forecasting content: non-linear shallow water dynamics captures tide-surge interaction bathymetry forcing: tidal (gravity field: sun, moon) meteorology (pressure, winds) operation: data assimilation: Kalman Filtering RMSE(m) a.f.o. lead time, with and without Kalman Filter real time input data stations 5/6 December 2013 storm surge event, Hoek van Holland 9

Water Level / Storm Surge Forecasting Dutch Continental Shelf Model (DCSMv6) Water Level Forecasting content: non-linear shallow water dynamics captures tide-surge interaction bathymetry forcing: tidal (gravity field: sun, moon) meteorology (pressure, winds) operation: data assimilation: Kalman Filtering (dynamic) calibration (parametric) comes first in real life comes last this presentation: link to oceanography & science! 10

Global Ocean Mixing As Driven by Mechanics Abyssal Recipes II: Energetics of Tidal and Wind Mixing Walter Munk & Carl Wunsch Deep Sea Res., 1998 Something Stirs in the Deep Peter Killworth Nature, December 1998 11

Mixing in Action.. Kelvin-Helmholtz billows, "Extremely long Kelvin-Helmholtz billow trains in the Romanche Fracture Zone" Hans van Haren, Louis Gostiaux, Eugene Morozov & Roman Tarakanov Geophys. Res. Lett., Dec. 2014 12

Mixing in Action.. Kelvin-Helmholtz billows.. shear induced overturning.. "Extremely long Kelvin-Helmholtz billow trains in the Romanche Fracture Zone" Hans van Haren, Louis Gostiaux, Eugene Morozov & Roman Tarakanov Geophys. Res. Lett., Dec. 2014 13

Mixing in Action.. wave breaking and turbulence, over sea-mount slopes.. "Where large deep-ocean waves break" Hans van Haren, Andrea Cimatoribus and Louis Gostiaux Geophys. Res. Lett., April 2015 14

Relations global tides and mixing forcing Tides Mixing dissipation Global tide models can distinguish between impact/significance of bottom friction dissipation wave drag dissipation (parameterized generation by tide-topography interaction): M2 wave drag dissipation Modelling the global tides: modern insights from FES2004 F.Lyard, F. Lefevre, T. Letellier; Oc. Dyn. (2006) 15

Water Level Forecasting Dutch Continental Shelf Model (DCSMv6) Water Level Forecasting content: non-linear shallow water dynamics captures tide-surge interaction bathymetry forcing: tidal (gravity field: sun, moon) meteorology (pressure, winds) operation: data assimilation: Kalman Filtering (dynamic) real time adjustment of dynamic fields calibration (parametric) optimization of model parameters for model accuracy bathymetry bottom roughness "(..) water-level forecasting (..) through direct modeling of tide, surge and non-linear interaction" F.Zijl, M. Verlaan, H. Gerritsen, Ocean Dyn. (2013) 63 16

Segmentation for Calibration init left: segmentation for calibration of bottom roughness and bathymetry right: calibrated bottom roughness 17

Calibrated Energy Dissipation vs. bathymetry 18

The next step (in progress) Global tide model 19

Global flood risk and intervention analyzer Starts in 2015 PL: Hessel Winsemius

Case: Storm December 5 2013 again: tide & surge

Necessary improvements (in progress!) Self attraction and loading Tides modify the gravity potential as well Internal tides Tides create internal tide where there is stratification and steep bathymetry This creates dissipation (roughly ¼ of total tidal dissipation on global scale) N= f x =β g h x g ρ ρ0 z Depends on stratification

Conclusion Ocean Science: Global effort ongoing, inspired by the vision of Munk & Wunsch '98, to construct & verify a detailed picture of the ocean's distributions & dynamics complementary approaches: theory & observations of mixing & dissipation processes global circulation models (not in this presentation) tidal modeling modeling of dynamics satellite data assimilation Hydrology: water-level forecasting (tide & surge) physics based simulation of dynamics parameter tuning & Kalman filtering => data assimilation improving forecasts thanks to increased physical content.... to the extent that engineering meets science: tuning forecast models hinted where increased dissipation occurs in the ocean => to be explored and continued.. 23

Thank you 24