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Validation of decadal simulations of mesoscale structures in the North Sea and Skagerrak. Jon Albretsen and Lars Petter Røed. Outline. Background and motivation Models and configuration Validation results Application to ecosystem Conclusions. Feistein Lighthouse.
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Validation of decadal simulations of mesoscale structures in the North Sea and Skagerrak Jon Albretsen and Lars Petter Røed
Outline • Background and motivation • Models and configuration • Validation results • Application to ecosystem • Conclusions Feistein Lighthouse
Background and Motivation • Switching to ROMS • To become our new NOWP model (decision based on earlier model-model comparison and validation results, LaCasce et. al, 2007) Old model: MIPOM - old code, yesterdays numerics New model: ROMS – modern code, sophisticated numerics, e.g., better conservation properties, able to run with higher vertical resolution • Applications to cod fish eggs/larvae drift from the North Sea to Skagerrak • What is the chance of the spawned North Sea cod fish eggs to enter the Skagerrak?
Background and Motivation • Goal: • investigate the skill of the various models with respect to its ability to reproduce the statistical properties • To be presented • Results from 27 year long hindcast simulations of the North Sea/Skagerrak area on eddy-permitting (4km) and eddy-resolving (1.5km) grids (period is 1981-2007) using MI-POM and ROMS • Validation tools • Mainly probability distributions (PDF’s), but also time series and vertical sections
Computational Domains • Atmospheric forcing: • ERA40 and ECMWF OA • OBC: • 4 km: SODA reanalysis + climatology 2005-2007 • 1.5 km nested to 4 km • Tides included • Rivers: • Climatology • Baltic S=12 psu • No data-assimilation 4 km 1.5 km
1981-2007 average daily mean (2007-3-9) Circulation pattern in the area of interest ROMS 4km surface currents
Observations for validation • Institute of Marine Research: • Current measurements (one location, valid from 27.10.1992-4.4.1993) • Monthly data from the Hirtshals – Torungen section (12 stations, all years)
Validation of current speed Average current speed Standard deviation Observation period: Nov 1992 – Mar 1993 Model values from the exact same period (daily means) 58.37N,8.51E: Measured total depth: 120m Equil. depth: 233m (4km) and 163m (1.5km)
Validation of current speed Average current speed Standard deviation Observation period: Nov 1992 – Mar 1993 Model values from Nov-Mar all winters from 1981-2007 (daily means)
Validation of current speed Obs. period: Nov'92-Mar'93, Model: same period: Statistical skill: the models' abilities to reproduce the statistical properties of the observed currents 75m 13m Obs. period: Nov'92-Mar'93, Model: same period 26 winters: 75m 13m
Validation of current direction Obs. period: Nov'92-Mar'93, Model: same period: 13m 75m Obs. period: Nov'92-Mar'93, Model: same period 26 winters: 13m 75m Currents from the NE parallel to the: - coast: 238 deg - local isobaths: 225 deg
Validation of current speed 13m depth 75m depth Useful to denote forecast skill Observation period: Nov 1992 - Mar 1993 Model values from the exact same period (daily means)
Validation of hydrography Average density: M1.5 Obs. R4.0 M4.0 R1.5
Validation of geostrophic velocities Average velocity: M1.5 Obs. R4.0 M4.0 R1.5
Applications Simulate drift of cod eggs/larvae from the North Sea to Skagerrak Example from one location based on: Currents from ROMS 4km, 10m depth, 22.2.–1.5. 2006 Probability for a particle to enter Skagerrak: 92%
Results – particle drift Probabilities for particles entering Skagerrak from locations in the North Sea between 1981 and 2007 at 10m depth 1981-2007-average Annual-variability between 1981 and 2007
Conclusions • Eddy resolution is crucial to get the mesoscale statistics of the circulation correct, and in particular the strength of the current jets • This is brought about by the much better resolved topography when employing the 1.5 km mesh in combination with eddy resolution (particularly important regarding circulation in areas exhibiting prominent topographic features as f. ex. the Norwegian Trench cutting into the heart of the North Sea/Skagerrak area)
Conclusions • MI-POM reproduces temperature and salinity well on average, but with the largest, positive salinity bias along the Norwegian coast in Skagerrak (the Baltic outflow challenge) • The analytical expressions in ROMS for surface heat and salinity fluxes creates positive biases in both temperature and salinity (~1oC warm-bias in the Skagerrak and slightly saltier than MI-POM) • Applying similar surface heat and salinity flux algorithms in ROMS as in MI-POM will hopefully improve the modelled hydrography without downgrading the quality of the currents • The model simulations form a valuable basis for analysis of statistical properties of the pathways important for the migration, growth and recruitment of fish stocks