Description: Climate model results for the Baltic Sea region from an ensemble of eight simulations using the Rossby Centre Atmosphere model version 3 (RCA3) driven with lateral boundary data from global climate models (GCMs) are compared with results from a downscaled ERA40 simulation and gridded observations from 1980-2006. The results showed that data from RCA3 scenario simulations should not be used as forcing for Baltic Sea models in climate change impact studies because biases of the control climate significantly affect the simulated changes of future projections. For instance, biases of the sea ice cover in RCA3 in the present climate affect the sensitivity of the model's response to changing climate due to the ice-albedo feedback. From the large ensemble of available RCA3 scenario simulations two GCMs with good performance in downscaling experiments during the control period 1980-2006 were selected. In this study, only the quality of atmospheric surface fields over the Baltic Sea was chosen as a selection criterion. For the greenhouse gas emission scenario A1B two transient simulations for 1961-2100 driven by these two GCMs were performed using the regional, fully coupled atmosphere-ice-ocean model RCAO. It was shown that RCAO has the potential to improve the results in downscaling experiments driven by GCMs considerably, because sea surface temperatures and sea ice concentrations are calculated more realistically with RCAO than when RCA3 has been forced with surface boundary data from GCMs. For instance, the seasonal 2 m air temperature cycle is closer to observations in RCAO than in RCA3 downscaling simulations. However, the parameterizations of air-sea fluxes in RCAO need to be improved.

Description: Pelagic, coupled ocean circulation-ecosystem models, are widely used in climate research. These tools aim to quantify fluxes of nutrients and carbon in the ocean and are, increasingly, the base of future projections. For this purpose it is crucial to quantify and identify the sources of uncertainties. In contrast to physical models, the underlying equations for ecosystem models are derived from empirical relationships rather than based on first principles. This resulted in the development of a multitude of different ecosystem models – different in respect to both, underlying principles and complexity. Clearly, the question arises, to what extent the sensitivities of these models are comparable. This study focuses on the intrinsic dynamics of some widely used, simple (containing 2–3 prognostic variables) ecosystem models in a 0-D framework (i.e., comprising only the well-mixed oceanic surface layer). A suite of differing model approaches is tuned such that their behavior is similar. The setup resembles the well-mixed oceanic surface layer in the Baltic proper. It is illustrated that strong differences between the model approaches appear due to exemplary, anticipated changes in the external nutrient and light conditions. Herewith, we demonstrate the well-known, but rarely demonstrated fact that, apparent consistency between modeled prognostic variables with today's data bases is not necessarily a good measure of forecast skill. The causes which lead to the different sensitivities are illustrated by considering the steady state solutions. It is pointed out, that apparently small changes in the model formulations can result in very different dynamical behavior and an enormous spread between the model approaches, despite the feasibility to tune a common behavior in a limited range of light and nutrient supply. In our examples, the sensitivity is mainly a function of the formulation of the loss rate of phytoplankton. It is thus, in particular, the formulation of highly unknown heteorotrophic processes that determines the model sensitivity.

Description: The aim of the present study is to investigate the influence of enhanced absorption of sunlight at the sea surface due to increasing water turbidity and its effect on the sea surface temperatures (SST) in the Baltic Sea. The major question behind our investigations is, whether this effect needs to be included in Baltic Sea circulation models or can be neglected. Our investigations cover both, mean state and SST trends during the recent decades. To quantify the impact of water turbidity on the mean state different sensitivity ocean hind-cast experiments are performed. The state-of-the art ocean model RCO (Rossby Centre Ocean model) is used to simulate the period from 1962 to 2007. In the first simulation, a spatially and temporally constant value for the attenuation depth is used, while in the second experiment a climatological monthly mean, spatially varying attenuation coefficient is derived from satellite observations of the diffuse attenuation coefficient at 490 nm. The inclusion of a spatially varying light attenuation leads to significant SST changes during summer. Maximum values of + 0.5 K are reached in the Gulf of Finland and close to the eastern coasts, when compared to a fixed attenuation of visible light of 0.2 m− 1. The temperature anomalies basically match the pattern of increased light attenuation with strongest effects in shallow waters. Secondary effects due to changes in the current system are of minor importance. Similar results are obtained when considering trends. In the absence of long-term basin wide observations of attenuation coefficients, some idealizations have to be applied when investigating the possible influence of long-term changes in water turbidity on the SST. Two additional sensitivity experiments are based on a combination of long-term Secchi depth station observations and the present day pattern of water turbidity, as observed by satellite. We show the potential of increased water turbidity to affect the summer SST trends in the Baltic Sea significantly, while the estimated effect is apparently too small to explain the overall extreme summer trends observed in the Baltic Sea. Highlights ► Investigation of the modeled influence of water turbidity on the sea surface temperature (SST) of the Baltic Sea. ► Hind-cast simulations (1962–2007) with different attenuation depths, using the regional ocean model RCO. ► The inclusion of an observed spatially varying light leads regionally to significant SST changes during summer. ► Secondary effects due to changes in the current system are of minor importance. ► The influence of increasing water turbidity on SST trends is regionally statistically significant while the effect is rather small.

Description: Pelagic biogeochemical models (BGCMs) have matured into generic components of Earth System Models. BGCMs mimic the effects of marine biota on oceanic nutrient, carbon and oxygen cycles. They rely on parameters that are adjusted to match observed conditions. Such parameters are key to determining the models’ responses to changing environmental conditions. However, many of these parameters are difficult to constrain and constitute a major source of uncertainty in BGCM projections. Here we use, for the first time, variance-based sensitivity analyses to map BGCM parameter uncertainties onto their respective local manifestation in model entities (such as oceanic oxygen concentrations) for both contemporary climate and climate projections. The mapping effectively relates local uncertainties of projections to the uncertainty of specific parameters. Further, it identifies contemporary benchmarking regions, where the uncertainties of specific parameters manifest themselves, thereby facilitating an effective parameter refinement and a reduction of the associated uncertainty. Our results demonstrate that the parameters that are linked to uncertainties in projections may differ from those parameters that facilitate model conformity with present-day observations. In summary, we present a practical approach to the general question of where present-day model fidelity may be indicative for reliable projections.

Description: Nitrogen fixers, or diazotrophs, play a key role in the nitrogen and carbon cycle of the world oceans. Diazotrophs are capable of utilising atmospheric dinitrogen which is a competitive advantage over generally faster growing ordinary phytoplankton in nitrogen-depleted conditions in the sun-lit surface ocean. In this study we argue that additional competitive advantages must be at play in order to explain the dynamics and distribution of diazotrophs in the global oceans. Backed by growing published evidence we test the effects of preferential grazing (where zooplankton partly avoids diazotrophs) and high-affinity diazotrophic phosphorus uptake in an Earth System Model of intermediate complexity. Our results illustrate that these fundamentally different model assumptions result in a very similar match to observation-based estimates of nitrogen fixation while, at the same time, they imply very different trajectories into our warming future. The latter applies to biomass, fixation rates as well as to the ratio of the two. We conclude that a more comprehensive understanding of the competition between ordinary and diazotrophic phytoplankton will reduce uncertainties in model-based projections of the oceanic N cycle.

Description: In late summer, massive blooms and surface scums of cyanobacteria emerge regularly in the Baltic Sea. The bacteria can produce toxins and add bioavailable nitrogen fixed from atmospheric nitrogen to an already over-fertilized system. This counteracts management efforts targeted at improving water quality. Despite their critical role, the controls on cyanobacteria blooms are not comprehensively understood yet. This limits the usability of models-based bloom forecasts and projections into our warming future. Here we add to the discussion by combining, for the first time, satellite estimates of cyanobacteria blooms with output of a high-resolution general ocean circulation model and in-situ nutrient observations. We retrace bloom origins and conditions by calculating the trajectories of respective water parcels backwards in time. In an attempt to identify drivers of bloom development, we find that blooms originate and manifest themselves predominantly offshore where conditions are more nutrient-depleted compared to more coastal environments.