278
J. Kjellsson et al.
for more details). Their parameterization of subgrid processes should correspond to
a typical spreading rate of about 2 km/day. The same rate is reasonable for models
with a resolution of about 1–2 km while the models with a resolution of ∼1 km
might use the rate of about 700 m/day. Parameterizations leading to spreading rates
of 300–500 m/day may be recommended for extremely high-resolution models with
a grid step of ∼0.5 km. As the drifters in the uppermost layer have experienced a
certain impact of the local wind and waves on their drift the presented rates may to
some extent overestimate the actual spreading rates but the order of magnitude for
the spreading effects extracted from the experiments evidently is realistic.
The parameters characterizing the dynamics of spreading of objects in the uppermost layer are of utmost importance for the technique developed in this book. Its
key idea is to use the Lagrangian dynamics of currents to develop methods for the
reduction of environmental risks. Its key component is statistical analysis of large
sets of Lagrangian trajectories of simulated drifters or water particles. The results
are evidently highly sensitive with respect to the parameterization of subgrid-scale
processes that may randomly redirect drifters to largely different sea areas compared
to the modelled fields of currents (Döös 1995; de Vries and Döös 2001; Griffa et al.
2004; Andrejev et al. 2010).
The problem is even more complicated in strongly stratified sea areas such as
the Gulf of Finland where the drift is frequently steered by multi-layered dynamics
(Andrejev et al. 2004; Gästgifvars et al. 2006) and where it is not clear beforehand
which theoretical framework (predomination of 2D or 3D motion systems) should
be used in the analysis.
Similar problems intrinsically arise in the attempts of modelling pathways of different water masses (Meier 2007) and especially in simulations, both in forecast and
hindcast modes, of pollution transport by regional ocean models such as HIROMB
or Seatrack Web (Funkquist 2001; Gästgifvars et al. 2006; Verjovkina et al. 2010).
This chapter has contributed by presenting results from recently deployed surface
drifters of different types as well as drifters simulated with an ocean model and a
trajectory code, and comparing these to each other and the theoretical expectations
and discussing the implications for Lagrangian modelling in the Baltic Sea.
Acknowledgements This study was performed in the framework of the BalticWay project, which
was jointly supported by the funding from the by the Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning (Formas, Ref. No. 2008–1900), Estonian Science Foundation and the European Commission’s Seventh Framework Programme (FP7 2007–
2013) under grant agreement No. 217246 made with the joint Baltic Sea research and development
programme BONUS. The research was partially supported by the Estonian Science Foundation
(grant No. 9125), targeted financing by the Estonian Ministry of Education and Research (grant
SF0140007s11), and by the European Regional Development Fund via support to the Centre of
Excellence for Non-linear Studies CENS. The authors wish to thank Tallink Silja shipping company for allowing us to deploy the SVP drifters from the Stockholm–Riga line and in particular we
wish to thank Captain Lembit Uustulnd and his crew on M/S Silja Festival for permission and help
in deployment of the drifters. We also acknowledge and appreciate the help given by Prof. Peter
Lundberg and Dr. Anders Engqvist in deployment. The experiments with the surface drifters in
the Gulf of Finland were performed very professionally by Mr Mikk Viidebaum. His cooperation
towards deployment and rescue of SVP drifters is also gratefully acknowledged. Finally, we also
express our gratitude to Markus Meier and Anders Höglund at the Swedish Meteorological and
J. Kjellsson et al.
for more details). Their parameterization of subgrid processes should correspond to
a typical spreading rate of about 2 km/day. The same rate is reasonable for models
with a resolution of about 1–2 km while the models with a resolution of ∼1 km
might use the rate of about 700 m/day. Parameterizations leading to spreading rates
of 300–500 m/day may be recommended for extremely high-resolution models with
a grid step of ∼0.5 km. As the drifters in the uppermost layer have experienced a
certain impact of the local wind and waves on their drift the presented rates may to
some extent overestimate the actual spreading rates but the order of magnitude for
the spreading effects extracted from the experiments evidently is realistic.
The parameters characterizing the dynamics of spreading of objects in the uppermost layer are of utmost importance for the technique developed in this book. Its
key idea is to use the Lagrangian dynamics of currents to develop methods for the
reduction of environmental risks. Its key component is statistical analysis of large
sets of Lagrangian trajectories of simulated drifters or water particles. The results
are evidently highly sensitive with respect to the parameterization of subgrid-scale
processes that may randomly redirect drifters to largely different sea areas compared
to the modelled fields of currents (Döös 1995; de Vries and Döös 2001; Griffa et al.
2004; Andrejev et al. 2010).
The problem is even more complicated in strongly stratified sea areas such as
the Gulf of Finland where the drift is frequently steered by multi-layered dynamics
(Andrejev et al. 2004; Gästgifvars et al. 2006) and where it is not clear beforehand
which theoretical framework (predomination of 2D or 3D motion systems) should
be used in the analysis.
Similar problems intrinsically arise in the attempts of modelling pathways of different water masses (Meier 2007) and especially in simulations, both in forecast and
hindcast modes, of pollution transport by regional ocean models such as HIROMB
or Seatrack Web (Funkquist 2001; Gästgifvars et al. 2006; Verjovkina et al. 2010).
This chapter has contributed by presenting results from recently deployed surface
drifters of different types as well as drifters simulated with an ocean model and a
trajectory code, and comparing these to each other and the theoretical expectations
and discussing the implications for Lagrangian modelling in the Baltic Sea.
Acknowledgements This study was performed in the framework of the BalticWay project, which
was jointly supported by the funding from the by the Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning (Formas, Ref. No. 2008–1900), Estonian Science Foundation and the European Commission’s Seventh Framework Programme (FP7 2007–
2013) under grant agreement No. 217246 made with the joint Baltic Sea research and development
programme BONUS. The research was partially supported by the Estonian Science Foundation
(grant No. 9125), targeted financing by the Estonian Ministry of Education and Research (grant
SF0140007s11), and by the European Regional Development Fund via support to the Centre of
Excellence for Non-linear Studies CENS. The authors wish to thank Tallink Silja shipping company for allowing us to deploy the SVP drifters from the Stockholm–Riga line and in particular we
wish to thank Captain Lembit Uustulnd and his crew on M/S Silja Festival for permission and help
in deployment of the drifters. We also acknowledge and appreciate the help given by Prof. Peter
Lundberg and Dr. Anders Engqvist in deployment. The experiments with the surface drifters in
the Gulf of Finland were performed very professionally by Mr Mikk Viidebaum. His cooperation
towards deployment and rescue of SVP drifters is also gratefully acknowledged. Finally, we also
express our gratitude to Markus Meier and Anders Höglund at the Swedish Meteorological and