Surface currents in operational oceanography: Key applications, mechanisms, and methods

Röhrs, Johannes; Sutherland, Graig; Jeans, Gus; Bedington, Michael; Sperrevik, Ann Kristin; Dagestad, Knut‐Frode; Gusdal, Yvonne; Mauritzen, Cecilie; Dale, Andrew; LaCasce, J. H.

doi:10.1080/1755876x.2021.1903221

Cited by 32 publications

(22 citation statements)

References 252 publications

(317 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Wind conditions can play an important role both for onset -for mid channel blooms low wind speeds are a factor in K. mikimotoi bloom formation (Gentien et al 2007)but also for its impact on advection itself. Direct and indirect wind forcing (the latter via wind waves) are key to predict surface advection (Röhrs et al 2021). The PML model does not account for the Stokes drift, the resultant Lagrangian transport from surface waves, and this can be a significant component of drift.…”

Section: Advection Of High Biomass Blooms Simulated With Lagrangian P...mentioning

confidence: 99%

Assessing the Performance and Application of Operational Lagrangian Transport HAB Forecasting Systems

et al. 2022

Self Cite

View full text Add to dashboard Cite

Availability of operational regional hydrodynamic models and near real time Harmful Algal Bloom (HAB) alerts from monitoring stations and remote sensing products have allowed the proliferation of short term advective HAB forecasts. However, their predictive ability in simulating HAB transport needs to be continuously evaluated in events of different HAB species to assess their applicability to different domains and the impacts of the choices made in model setup. Here we review the performance of three different modelling systems which were part of the PRIMROSE project against historical bloom events in different regions in the European Atlantic Area. The objectives are to understand their predictive ability and to demonstrate some aspects of Lagrangian model setup that are relevant to HAB early warning systems; in particular the use of advection-diffusion only models (without a biological component) and the effects of model configuration, especially model resolution. Hindcast and forecast simulations have been run in examples of high biomass blooms detected in satellite imagery; in the western English Channel, several events of potentially toxic species like Karenia mikimotoi and Prorocentrum cordatum (minimum) were simulated and in Western France a bloom of Mesodinium rubrum, prey of the toxic Dinophysis spp. Additionally, some simulations for studying the evolution of low biomass Dinophysis spp. blooms in Galicia-North Portugal were undertaken with models of different setup. Several metrics have been used to quantify the model performance and to compare the results of the different model configurations, showing that differences in hydrodynamical model configuration (initiation, resolution, forcing, and simulation domain) result in differences in the predicted transport of HABs. We find that advection only is a reasonable approximation but that it may do worse in an early (onset) phase than later on, and we find transport is generally increases with increasing resolution. Our results confirm that Lagrangian particle tracking tools can be integrated operationally in HAB early warning systems providing useful information on potential HAB evolution to users.

show abstract

Section: Advection Of High Biomass Blooms Simulated With Lagrangian P...mentioning

confidence: 99%

Assessing the Performance and Application of Operational Lagrangian Transport HAB Forecasting Systems

et al. 2022

Self Cite

View full text Add to dashboard Cite

show abstract

“…The ability to provide efficient emergency services in this region for search-and-rescue, accidental oil spills, ship drift, etc, is much reduced compared to mainland Norway due to the vast distances and challenging environmental conditions. Contingency models for decision support are based on short term forecast models for the weather, surface waves, ocean circulation and sea ice distribution, and increased predictability in these models translate directly into better emergency preparedness (Röhrs et al, 2023). Of particular interest are upper ocean transport processes (e.g.…”

Section: Introductionmentioning

confidence: 99%

Barents-2.5km v2.0: An operational data-assimilative coupled ocean and sea ice ensemble prediction model for the Barents Sea and Svalbard

Röhrs

Gusdal

Rikardsen

et al. 2023

Preprint

View full text Add to dashboard Cite

Abstract. An operational ocean and sea ice forecast model, Barents-2.5, is implemented at MET Norway for short-term forecasting at the coast off Northern Norway, the Barents Sea, and waters around Svalbard. Primary forecast parameters are the sea ice concentration (SIC), sea surface temperature (SST), and ocean currents. The model is also a substantial input for drift modeling of pollutants, ice berg, and in search-and-rescue pertinent applications in the Arctic domain. Barents-2.5 has recently been upgraded to include an Ensemble Prediction System with 24 daily realizations of the model state. SIC, SST and in-situ hydrography are constrained through the Ensemble Kalman Filter (EnKF) data assimilation scheme executed in daily forecast cycles with lead time up to 66 hours. While the ocean circulation is not directly constrained by assimilation of ocean currents, the model ensemble represents the given uncertainty in the short-term current field by retaining the current state for each member throughout forecast cycles. Here we present the model setup and a validation in terms of SIC, SST and in-situ hydrography. The performance of the ensemble to represent the models uncertainty, and the performance of the EnKF to constrain the model state are discussed, in addition to the model’s forecast capabilities for SIC and SST.

show abstract

“…The difficult environmental conditions of the Arctic make remote sensing a good alternative to in-situ measurements of ocean currents [26]. Indeed, in the last thirty years, different remote sensing approaches have provided regular measurements of key variables such as the sea surface temperature (SST) and sea surface height (SSH).…”

Section: Introductionmentioning

confidence: 99%

Surface and Interior Dynamics of Arctic Seas Using Surface Quasi-Geostrophic Approach

et al. 2023

View full text Add to dashboard Cite

This study assesses the capability of Surface Quasi-Geostrophy (SQG) to reconstruct the three-dimensional (3D) dynamics in four critical areas of the Arctic Ocean: the Nordic, Barents, East Siberian, and Beaufort Seas. We first reconstruct the upper ocean dynamics from TOPAZ4 reanalysis of sea surface height (SSH), surface buoyancy (SSB), and surface velocities (SSV) and validate the results with the geostrophic and total TOPAZ4 velocities. The reconstruction of upper ocean dynamics using SSH fields is in high agreement with the geostrophic velocities, with correlation coefficients greater than 0.8 for the upper 400 m. SSH reconstructions outperform surface buoyancy reconstructions, even in places near freshwater inputs from river discharges, melting sea ice, and glaciers. Surface buoyancy fails due to the uncorrelation of SSB and subsurface potential vorticity (PV). Reconstruction from surface currents correlates to the total TOPAZ4 velocities with correlation coefficients greater than 0.6 up to 200 m. In the second part, we apply the SQG approach validated with the reanalysis outputs to satellite-derived sea level anomalies and validate the results against in-situ measurements. Due to lower water column stratification, the SQG approach’s performance is better in fall and winter than in spring and summer. Our results demonstrate that using surface information from SSH or surface velocities, combined with information on the stratification of the water column, it is possible to effectively reconstruct the upper ocean dynamics in the Arctic and Subarctic Seas up to 400 m. Future remote sensing missions in the Arctic Ocean, such as SWOT, Seastar, WaCM, CIMR, and CRISTAL, will produce enhanced SSH and surface velocity observations, allowing SQG schemes to characterize upper ocean 3D mesoscale dynamics up to 400 m with higher resolutions and lower uncertainties.

show abstract

Surface currents in operational oceanography: Key applications, mechanisms, and methods

Cited by 32 publications

References 252 publications

Assessing the Performance and Application of Operational Lagrangian Transport HAB Forecasting Systems

Assessing the Performance and Application of Operational Lagrangian Transport HAB Forecasting Systems

Barents-2.5km v2.0: An operational data-assimilative coupled ocean and sea ice ensemble prediction model for the Barents Sea and Svalbard

Surface and Interior Dynamics of Arctic Seas Using Surface Quasi-Geostrophic Approach

Contact Info

Product

Resources

About