Efficient Kalman filter techniques for the assimilation of tide gauge data in three‐dimensional modeling of the North Sea and Baltic Sea system

Sørensen, Jacob Viborg Tornfeldt; Madsen, Henrik

doi:10.1029/2003jc002144

Cited by 34 publications

(23 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition, improvements are seen in the eastern North Sea, where the coast is more exposed to direct open ocean sea level variations. Finally, opposed to earlier results by Sørensen et al [2004], we see model improvements in the Baltic Sea, indicating that it also benefits from the distributed information of the blended product and we have overcome problems with single point assimilation of tide gauges alone.…”

Section: Discussioncontrasting

confidence: 49%

“…Sparse data sets require accurate error modeling, otherwise, erroneous error descriptions and hence error correlations may easily spread wrong updates into areas where no other measurements constrain the solution. The observed deterioration of sea level predictions on intermediate time prediction horizons [Sørensen et al, 2004;Verlaan et al, 2005] is an example of such an effect. Here we seek to minimize this effect by using the blended product instead of individual tide gauges.…”

Section: Assimilation Setupmentioning

confidence: 99%

See 1 more Smart Citation

Blending of satellite and tide gauge sea level observations and its assimilation in a storm surge model of the North Sea and Baltic Sea

Madsen

Høyer

et al. 2015

JGR Oceans

View full text Add to dashboard Cite

Coastal storm surge forecasts are typically derived from dedicated hydrodynamic model systems, relying on Numerical Weather Prediction (NWP) inputs. Uncertainty in the NWP wind field affects both the preconditioning and the forecast of sea level. Traditionally, tide gauge data have been used to limit preconditioning errors, providing point information. Here we utilize coastal satellite altimetry sea level observations. Careful processing techniques allow data to be retrieved up to 3 km from the coast, combining 1 Hz and 20 Hz data. The use of satellite altimetry directly is limited to times when the satellite passes over the area of interest. Instead, we use a stationary blending method developed by Madsen et al. (2007) to relate the coastal satellite altimetry with corresponding tide gauge measurements, allowing generation of sea level maps whenever tide gauge data are available. We apply the method in the North Sea and Baltic Sea, including the coastal zone, and test it for operational nowcasting and hindcasting of the sea level. The feasibility to assimilate the blended product into a hydrodynamic model is assessed, using the ensemble optimal interpolation method. A 2 year test simulation shows decreased sea level root mean square error of 7–43% and improved correlation by 1–23% in all modeled areas, when validated against independent tide gauges, indicating the feasibility to limit preconditioning errors for storm surge forecasting, using a relatively cost effective assimilation scheme.

show abstract

Section: Discussioncontrasting

confidence: 49%

Section: Assimilation Setupmentioning

confidence: 99%

Blending of satellite and tide gauge sea level observations and its assimilation in a storm surge model of the North Sea and Baltic Sea

Madsen

Høyer

et al. 2015

JGR Oceans

View full text Add to dashboard Cite

show abstract

“…The regional hydrodynamic model was set up covering the northwestern part of the Atlantic Ocean and the European northwest shelf with the DHI modelling software MIKE 21 Flexible Mesh HD (Rasmussen 1991), with the purpose of providing accurate boundary conditions to the 3-dimensional (3D) local fine-meshed hydrodynamic model (see also Skov et al 2014). The latter was forced by tide and wind, and integrated data assimilation following Sørensen et al (2004). The tidal potential forcing was implemented as an equilibrium tide.…”

Section: Hydrodynamic Modelmentioning

confidence: 99%

Real-time species distribution models for conservation and management of natural resources in marine environments

Skov¹,

Heinänen²,

Thaxter³

et al. 2016

Mar. Ecol. Prog. Ser.

View full text Add to dashboard Cite

Species distribution models in marine environments typically use static variables, partly due to the limited availability of fine-resolution dynamic predictor variables and sufficiently detailed species abundance data. Our aim was to describe and quantify the dynamic coupling between the distribution of marine species (seabirds) and the natural variability of their habitat in real time through the combination of a high-resolution hydrodynamic model, aerial digital surveys and real-time species distribution modelling. We used a 2-step (delta) generalized additive model at 500 m spatial resolution for assessment and prediction of the changing patterns of wintering red-throated divers (RTDs) Gavia stellata in the outer Thames estuary, United Kingdom. Our dynamic species distribution models successfully resolved the major oscillations in the distribution of RTDs and confirmed their tight association with frontal zones where the probability of prey encounter was higher. The relative model standard errors (%) were generally below 30% in the high-density areas. Area under the curve (AUC) values indicated that the models were capable of distinguishing presence from absence about 75% of the time. The predictive power of the achieved distribution models made it possible to accurately identify areas where RTDs were concentrated. Comparisons between visual aerial and digital stills aerial surveys documented that, in spite of similar patterns, the aerial digital surveys generally recorded significantly higher densities of RTDs than the visual aerial surveys. This study demonstrates how marine distribution models with assimilation of habitat variables from a well-calibrated fine-resolution hydrodynamic model coupled with the use of digital aerial surveys can facilitate the capture of detailed associations between seabirds and their dynamic habitats.

show abstract

“…Different data assimilation techniques have been used to demonstrate improvements in the storm surge modelling, when compared to control runs (Verlaan et al, 2005;Peng and Xie, 2006;Sørensen and Madsen, 2004). Very few studies have directly assimilated satellite observations into storm surge models and then assessed the change in performance.…”

Section: Recent Advancesmentioning

confidence: 99%

Progress in satellite remote sensing for studying physical processes at the ocean surface and its borders with the atmosphere and sea ice

Shutler

Quartly

Donlon³

et al. 2016

Progress in Physical Geography: Earth and Environment

View full text Add to dashboard Cite

Physical oceanography is the study of physical conditions, processes and variables within the ocean, including temperature–salinity distributions, mixing of the water column, waves, tides, currents and air–sea interaction processes. Here we provide a critical review of how satellite sensors are being used to study physical oceanography processes at the ocean surface and its borders with the atmosphere and sea ice. The paper begins by describing the main sensor types that are used to observe the oceans (visible, thermal infrared and microwave) and the specific observations that each of these sensor types can provide. We then present a critical review of how these sensors and observations are being used to study: (i) ocean surface currents, (ii) storm surges, (iii) sea ice, (iv) atmosphere–ocean gas exchange and (v) surface heat fluxes via phytoplankton. Exciting advances include the use of multiple sensors in synergy to observe temporally varying Arctic sea ice volume, atmosphere–ocean gas fluxes, and the potential for four-dimensional water circulation observations. For each of these applications we explain their relevance to society, review recent advances and capability, and provide a forward look at future prospects and opportunities. We then more generally discuss future opportunities for oceanography-focused remote sensing, which includes the unique European Union Copernicus programme, the potential of the International Space Station and commercial miniature satellites. The increasing availability of global satellite remote-sensing observations means that we are now entering an exciting period for oceanography. The easy access to these high quality data and the continued development of novel platforms is likely to drive further advances in remote sensing of the ocean and atmospheric systems.

show abstract

Efficient Kalman filter techniques for the assimilation of tide gauge data in three‐dimensional modeling of the North Sea and Baltic Sea system

Cited by 34 publications

References 29 publications

Blending of satellite and tide gauge sea level observations and its assimilation in a storm surge model of the North Sea and Baltic Sea

Blending of satellite and tide gauge sea level observations and its assimilation in a storm surge model of the North Sea and Baltic Sea

Real-time species distribution models for conservation and management of natural resources in marine environments

Progress in satellite remote sensing for studying physical processes at the ocean surface and its borders with the atmosphere and sea ice

Contact Info

Product

Resources

About