![Page 1: 2. Creating your coastal model - Island Wakeswakes.uma.pt/cimar/PartIII_lecture2.pdf · { {Several courses: z2006, Lisbon; z2007, Lisbon; z2008, Sarigerme (Turkey); {Free code. Coastal](https://reader031.vdocuments.net/reader031/viewer/2022030408/5a8868077f8b9a882e8e36f2/html5/thumbnails/1.jpg)
2. Creating your coastal model
Ângela Canas (MARETEC, IST)
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
Contents
2.1. Definition of scope2.2. Definition of processes2.3. Definition of space/time scale2.4. Choice of modelling tool2.5. Modelling techniques2.6. Data requirements2.7. Model calibration2.8. Model validation2.9. Data assimilation
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.1. Definition of scope
Your model is what you make of it!
Model application
Model application
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.1. Definition of scope
Clearly state the objective:Which is the modelling area?What are the problems to be investigated?What is the desired outcome of model?
Justified recommendations;Quantitative relationships between variables;Schemes/charts;Etc.;
What are the intended results of model?Interest properties;Maximum/ minimum/ average, distribution.
Model application
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.1. Definition of scope
Objectives should not be changed in research… unless resources are exhausted:
Time;Computers;Data loss.
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.1. Definition of scope
Example:Calculate the average time needed for sediment aggregates of size 400 μm to be transported in Nazare Canyon from 50m shelf depth to 5000m abyssal plain.
D83 Hermes Project, 2007
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.2. Definition of processes
Elements of model:
Equations
Numerical algorithm
Computer code
Defined according to processes to be modeled!
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.2. Definition of processes
Important physical processes in Portuguese Coast:
Tide;Internal tides;Wind;Storms; Rivers;
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.2. Definition of processes
Tide:Tidal wave progresses around amphidromic points:
South to North in Portuguese Coast;
Important South to North residual current (0.02m/s) is created;
Nível normalizado (0-1)
N
Módulo velocidade (m/s)
NEstremadura Plateau
Tide only simulation
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.2. Definition of processes
Shallow water tides:High-frequency (6h or less) tides in shallow waters:
Shelf;Estuaries;
Caused by non linear terms in motion equations:
Bottom friction;Advection; Bathymetry: dark blue = 20m, bright red = 5000m
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.2. Definition of processes
Tide changes from South to North:
Semi diurnal amplitude increases;
Center
North
South
semi diurnal diurnal
quatradiurnal
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.2. Definition of processes
Tide changes within estuaries:
Tagus Estuary case;
measurements
Ocean Tagus river
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.2. Definition of processes
Internal tides:Tide flux interacts with bathymetry (e.g. canyons) in presence of stratification causing tide energy trapping:
Isotherms oscillate;Local turbulence and mixing is enhanced;
Affects sediment transport along shelf and shelf slope.
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.2. Definition of processes
Wind:Blowing persistently from North/NorthWest (Summer) in presence of stratification causes upwelling events;Characteristic of oriental margin of Atlantic/Pacific;Very relevant for biologic productivity;
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.2. Definition of processes
Storms:Extratropical storms (Lozano et al., 2004):
From southwest NorthAtlantic;Winter;Last for some days (4-5);3 storms per year;Extreme storm every 7 years (Andrade et al., 2008).
North Atlantic Oscillation (NAO) Sea level pressure gradient (Keim et al., 2004)
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.2. Definition of processes
Storm surge:Significant elevation of water level relative to tide (Gill, 1982);Can be produced in storms by:
Wind;Atmospheric pressure (Portuguese Coast, Fanjul et al., 1998);
Expressed by inverted barometer formulation:p refζ =-0.000101*(P-P )
Level change (m) due to atmospheric pressure
Reference pressure (101330Pa)
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.2. Definition of processes
Detided level changes in Tagus Estuary:
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.2. Definition of processes
Detided level changes in Tagus Estuary:
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.2. Definition of processes
Storm surge affects estuaries (Andrade et al., 2004; Valdemoro et al., 2007):
Hydrodynamics:Severe circulation change;
Water quality:Increased turbidity;Sediment transport;
Biology:Exposure of wetlands to coastal processes.
Tagus Estuary case:Main limiting factor for biologic productivity is turbidity (INAG, 2002).
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.2. Definition of processes
Rivers:Very important in estuaries and Regions of Fresh Water Influence (ROFI);Flow influences flushing time:
Time for measurable volume of water to be replaced by river water, ocean water or precipitation;
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.2. Definition of processes
Mondego Estuary case:
Influence of river flow (winter/summer situation) in residence time: Winter
Summer
Average estuary volume = 3.0x107 m3
WinterDaily volume change by tide (neap) =
7.5x106 m3;Daily volume change by river = 4.8x106 m3;
Residence time = 1 day.
SummerDaily volume change by tide (neap) =
7.5x106 m3;Daily volume change by river = 2592 m3;
Residence time = 10 days.
Average estuary volume = 2.9x107 m3
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.2. Definition of processes
Different relative importance (Martins, 1999):
Coast:Horizontal density gradients;Coriolis effect;Wind (surface);Tide (shelf);
Estuaries:Tide;Rivers;Wind (small).
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.3. Definition of space/time scale
Space:Extension of domain:
All relevant processes should be modelled or íntroduced through boundary;
Resolution:Should be smaller than scale of processes.
Tagus Estuary case:
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.3. Definition of space/time scale
Time:Resolution:
Should be smaller or equal than half the dominant period of signal to be simulated (Nyquist rule);Connected to spatial resolution in numerical discretizations according with the Courant number:
If Cr too high models with explicit discretizations become unstable.
UΔt/Δx = Courant number (<1 if 1D)
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2. Creating your coastal model
Ângela Canas (MARETEC, IST)
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
Contents
2.1. Definition of scope2.2. Definition of processes2.3. Definition of space/time scale2.4. Choice of modelling tool2.5. Modelling techniques2.6. Data requirements2.7. Model calibration2.8. Model validation2.9. Data assimilation
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.4. Choice of modelling tool
No need to invent the wheel!
“If I have seen further it is only by standing on the shoulders of Giants.”Isaac Newton
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
Equations
Numerical algorithm
Computer code
2.4. Choice of modelling tool
Able to meet modelling objective;Able to be used as Decision Support Tool;
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.4. Choice of modelling tool
Decision Support Tool model:Able to produce results that describe a reference situation:
e.g. characterization of ecosystem in a reference year prior to instalation of water sewage system;
Able to produce results that describe hypothetical scenarios:
e.g. several locations and configurations for sewage system and wide range of natural conditions and ecological stress;sensitivity analysis;comparison between each scenario and reference situation.
illustrates solution’s impact on environment
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.4. Choice of modelling tool
Decision Support Tool model:
One or more models;Results must be available in time for decisions;Typically used by non-specialists in numerical methods:
Pre and post process with GUI (Graphical User Interface).
GUI
Equations
Numerical algorithm
Computer code
Mod
el
GUI
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.4. Choice of modelling tool
Help on using model:Documentation:
Websites;Wiki websites;
Support software:Pre/post processing;Format conversion;
From others: Forums;Courses;
Your own: free codes!
MOHID Water case:www.mohid.com;www.mohid.com/wiki;www.mohid.com/forum;Several courses:
2006, Lisbon;2007, Lisbon;2008, Sarigerme (Turkey);
Free code.
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.4. Choice of modelling tool
Why freely available code is useful?Possible to identify model running error sources;Possible to compile model executables:
Latest model version in volatile codes;Adequate memory amount reserved;
Introduce changes in the code through programming.
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.5. Modelling techniques
Downscalling;Nesting;Boundary conditions;Vertical resolution;Initialization;Lagrangean tracers.
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.5. Modelling techniques
Downscalling:Transpose a model result to a smaller scale using another model (e.g. global to regional);
Scale connected with:Spatial horizontal resolution:
• Coarse solution considered in open boundary;• Detailed model with higher resolution;
Processes.
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.5. Modelling techniques
Operational Model for the Portuguese Coast case:
TemperatureSalinityVelocity
Tide
Mer
cato
r Oce
an(w
ww
.mer
cato
r-oc
ean.
fr)
8km 6km
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.5. Modelling techniques
Nesting:Same rationale as downscalling;Connection between scales is processed within same model;High resolution only where needed;Imposed constraints:
Boundary bathymetry should be concurrent;Spatial resolution increased maximum by factor of 3.
Tagus Estuary case:2km
300m
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.5. Modelling techniques
Mondego Estuary case:
2D model too strong sensibility to wind forcing;Nest in Portuguese Coast Model domain!
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.5. Modelling techniques
Boundary conditions:Open;Moving.
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.5. Modelling techniques
Open boundary conditions:
Arise because of need to confine domain to study area;Variables values introduced so that:
Info of what happens outside is guaranteed to enter domain;Waves (process or noise) generated inside the domain should be allowed to go out.
Nível normalizado (0-1)
N
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.5. Modelling techniques
Open boundary conditions types:Dirichelet:
Variable values are imposed in boundary;Newmann:
Gradient of variables is imposed in boundary;E.g. null gradient;
Radiation:Boundary values depend on internal model variability.
axP=
∂∂
aP =
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.5. Modelling techniques
Open boundary condition:Perfect condition does not exist;Most suitable condition depends on:
Domain;Processes.
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.5. Modelling techniques
Open boundary condition:
Hydrodynamic (water level):
Blumberg and Kantha (1985):
Flather (1976):
Water properties:Dirichelet (nested domain);Null gradient.
( ) ( )ηηηη−=∇+
∂∂
extd
E Tnc
t1.rr
( )( )ncqq Eextextrr .ηη −=−
Tide
Nes
ted
dom
ain
flow levelcelerity of waves
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.5. Modelling techniques
Moving boundaries:
Immersion/ submersion areas in estuaries;Reproduction of intertidal areas.
Tagus Estuary case:
Velocity modulus (m/s)
Leitão (2003)
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.5. Modelling techniques
Vertical resolution:Sigma coordinates:
Where bathymetry is important (e.g. estuaries);
Cartesian coordinates:Where density gradients are important;
Important rule:Layers should be oriented according with dominant flow.
sigma
cartesian
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.5. Modelling techniques
Vertical resolution:If inadequate model simulations may break;
Attention to density gradients between layers!
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.5. Modelling techniques
Initialization:Initial conditions are probably not best system representation:
First guesses which need to be evolved to best model solution;May be unstable and cause model disruption;
Approaches:Gradual connection of forces:
• Tide (slowstart e.g. for some days);• Baroclinic forces;
Spin up: time for model to recover from initial conditions.
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.5. Modelling techniques
Lagrangean tracers:Model follows moving elements;Useful to simulate localized processes with sharp gradients:
Submarine outfalls pollution;Sediment transport and erosion; Oil dispersion.
Garcia (2008)
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.5. Modelling techniques
Lagrangean tracers:Tracer:
Most important property is position (x, y, z);Other properties:
• Volume;• Others (each with a
concentration, e.g. Water properties, coliform bacteria).
Representation of:
( ),tt t
dx u x tdt
=
Water massSediment particle / Group of
particlesMolecule / Group of
moleculesPhytoplankton cell
Shark
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.5. Modelling techniques
Lagrangean tracers:Adquate for flushing time calculation;Mondego Estuary case:
Winter
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.5. Modelling techniques
Lagrangean tracers:Mondego Estuary case:
Winter: 1 day Summer: 10 days
Braunschweig et al. (2003)
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.6. Data requirements
Initial conditions;Boundary conditions;Bathymetry.
Model
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.6. Data requirements
Initial conditions:Schematic:
Null velocities;Constant value (water level, properties);
Solution from measurement interpolation;Past solution from model;Solution from other models (e.g. from a coarser scale);Solution of data assimilation (objective analysis) of measurements in a first guess solution.
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.6. Data requirements
Boundary conditions:Open:
Larger scale models: e.g. FES 95, MERCATOR, HYCOM (http://hycom.rsmas.miami.edu/hycom-model/index.html);Climatologies: e.g. Levitus (1982) Climatological atlas for the World Ocean (new version http://ingrid.ldeo.columbia.edu/SOURCES/.LEVITUS94/);Schematic;
Surface:Meteorological models;Reanalysis: ERA40 (http://www.ecmwf.int/research/era/do/get/era-40), NCEP (http://www.ncep.noaa.gov/);Climatologies: e.g. Hellerman and Rosenstein (1983);Schematic.
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.6. Data requirements
Mondego Estuary case:Model provided currents not strong enough so that nutrients are reallistically expelled from domain;Schematic land-sea breeze provided the adequate current magnitude for the nutrients not artificially accumulate in domain.
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.6. Data requirements
Boundary conditions:
Rivers:Measurements: case of Operational System for Tagus Estuary;River basin model results.
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.6. Data requirements
Boundary conditions:Bathymetry:
Bathymetric surveys;International sources:
• ETOPO (http://www.ngdc.noaa.gov/mgg/fliers/01mgg04.html);
• GEBCO (http://www.bodc.ac.uk/data/online_delivery/gebco/).
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.7. Model calibration
Objective:Tune the model so that differences between model solution and measurements are reduced;Parameters:
Wind friction factor;Bottom friction factor;Boundary conditions;Bathymetry.
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.8. Model validation
Quantitative:Statistical techniques:
Descriptive statistics:
• Average;• Standard
deviation (variability);
• Extremes: maximum, minimum;
Error statistics.
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.8. Model validation
Qualitative:Literature review;Known physics;Statistical techniques:
Harmonic analysis;Spectral analysis;EOF analysis:
• Decomposition of variability in modes.
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.9. Data assimilation
Models are not perfect nor measurement networks: why not take only the best from each one?
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
2.9. Data assimilation
Basic concepts;Approximations;Methods for coastal areas:
Variational assimilation;Sequential assimilation;
Implementation constraints/costs.
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
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Coastal ModellingDoctoral School in Marine & Environmental
Sciences - 2009
ReferencesAndrade, C., M. Freitas, J. Moreno and S. Craveiro, 2004, “Stratigraphical evidence of Late Holocene barrier breaching and extreme storms in lagoonal sediments of Ria Formosa, Algarve, Portugal”, Marine Geology, 210, pp. 339-362.Andrade, C., R. Trigo, M. Freitas, M. Gallego, P. Borges and A. Ramos, 2008, “Comparing historic records of storm frequency and theNorth Atlantic Oscillation (NAO) chronology for the Azores region”, Holocene, 18 (5), pp. 745-754.Braunschweig, F., F. Martins, P. Chambel and R. Neves, 2003, “A methodology to estimate renewal time scales in estuaries: the TagusEstuary case”, Ocean Dynamics, 53, pp. 137-145.Canas, A., 2008, Modelling and Data Assimilation Techniques for Operational Hydrodynamic Forecast in Tagus Estuary, Tese de doutoramento provisória, Instituto Superior Técnico, Universidade Técnica de Lisboa.Fanjul, E., B. Gomez, J. Carretero and I. Arevalo, 1998, “Tide and surge dynamics along the Iberian Atlantic coast”, Oceanologica Acta,21(2), pp. 131-143.Garcia, A., 2008, Tese de doutoramento, Instituto Superior Técnico, Universidade Técnica de Lisboa.Gill, A., 1982, Atmosphere-Ocean Dynamics, San Diego, California: Academic Press, International Geophysics Series, 662 p.Hellerman, S. and M. Rosenstein, 1983, “Normal monthly wind stress over the world ocean with error estimates”, Journal of Physical Oceanography, 13, pp. 1093-1104.INAG (Instituto da Água) / MARETEC, 2002, Water Quality in Portuguese Estuaries: Tejo, Sado and Mondego, Lisbon.Keim, B.; Muller, R., and Stone, G., 2004, “Spatial and temporal variability of coastal storms in the North Atlantic Basin”, Marine Geology,210, pp. 7-15.Leitão, P., 2003, Integração de Escalas e de processos na Modelação do Ambiente Marinho, Ph.D. thesis, Instituto Superior Técnico,Universidade Técnica de Lisboa, Lisboa.Levitus B., 1982, Climatological atlas for the World Ocean, NOAA Prog. Papers 13, US Government Printing Office, Washington DC.Lozano, I.; Devoy, R.; May, W., and Andersen, U., 2004, “Storminess and vulnerability along the Atlantic coastlines of Europe: analysis ofstorm records and of a greenhouse gases induced climate scenario”, Marine Geology, 210, 205-225.Martins, F., 1999. Modelação Matemática Tridimensional de Escoamentos Costeiros e Estuarinos usando uma Abordagem deCoordenada Vertical Genérica. Ph.D. Thesis, Instituto Superior Técnico, Universidade Técnica de Lisboa, Lisboa.Valdemoro, H.; Sánchez-Arcilla, A., and Jiménez, J., 2007, “Coastal dynamics and wetland stability. The Ebro delta case”, Hydrobiologia,577, pp. 17-29.