Category: theses

Understanding the dynamics of recent Norwegian extreme weather events and their influence on energy production

Pecnjak, Martin (2021-08-05). Understanding the dynamics of recent Norwegian extreme weather events and their influence on energy production (Master’s thesis, University of Bergen, Bergen, Norway). https://bora.uib.no/bora-xmlui/handle/11250/2778409 .

Summary: The growing frequency and severity of extreme weather events in the Northern Hemisphere has prompted a lot of research being done on their origin and physical mechanisms. Both simplified and complex approaches have been introduced in defining and understanding these events, where they look into high-amplitude quasi-stationary Rossby waves and their quasi-resonant amplification. However, different approaches exist to investigating extreme events and these were just a motivation for this thesis. Since the resonance method is suit- able mostly for summer events and the events discussed in this thesis have happened in all seasons, a different approach was needed. The events in question were a winter drought, two summer and autumn floods, a winter snowfall and a spring/summer heatwave in the areas of south and southwestern Norway. In order to detect certain features which would help solve this issue, we look into anomalies of different meteorological variables such as geopoten- tial height, surface temperature, precipitation and snowfall rate and zonal and meridional winds. Deep and thorough statistical and dynamical analyses are applied to define the out- comes and the physical origins which would help us obtain a clear picture on the whole case. The finite-amplitude local wave activity (LWA) diagnostic, as a measure of the meandering of the jet stream, has helped to give a clear picture along with the large-scale circulation. This method can be used as a proxy for the strength of the eddy-driven jet and the storm track. It has proven to be the key factor in defining what has exactly caused the events in ques- tion. The results and findings have shown that the LWA is a conclusive tool in determining whether an extreme event was related to a blocking pattern or not, while the LWA budget equation components have shed light on the so far poorly understood dynamical aspects which led to the events. The zonal LWA flux has proven to be a good predictor of blocking with its onset in the early stages of the events, similar to the traffic jam concept introduced by (Nakamura and Huang, 2018). The jet stream has a capacity for the LWA flux similar to how a highway has a capacity for the number of vehicles on it. If the capacity is exceeded, blocking occurs, and this is readily shown in the results and findings of this work. As for the budget equation components, the zonal LWA flux convergence has proven to be the key in maintaining the increase of the LWA as well as also having an early onset in each blocking event in agreement with the LWA flux. On the other hand, the residual in the LWA budget, which represents the non-conservative small-scale processes (diabatic sources and sinks of LWA), dampens the LWA. The LWA method has also proven to be useful in all seasons. The motivation for the thesis also came from the influence of the events on the meteorological variables related to the Norwegian energy production. The results show us clues into possible ways of improving forecasting of such events and minimizing their harmful impacts. They also show possibilities in improving energy management, infrastructure, allocation of resources and preparedness of the society for damages and hazards caused by the events. This was not fully investigated in this thesis and is the next step in the research of this topic.

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Future Abrupt Changes in Winter Barents Sea Ice Area

Rieke, Ole (2021-06-01). Future Abrupt Changes in Winter Barents Sea Ice Area (Master’s thesis, University of Bergen, Bergen, Norway). https://bora.uib.no/bora-xmlui/handle/11250/2762637 .

Summary: The Barents Sea is an area of strong anthropogenic winter sea ice loss that is superimposed by pronounced internal variability on interannual to multidecadal timescales. This internal variability represents a source of large uncertainty in future climate projections in the Barents Sea. This study aims to investigate internal variability of Barents Sea ice area and its driving mechanisms in future climate simulations of the Community Earth System Model Large Ensemble under the RCP8.5 climate scenario. We find that although sea ice area is projected to decline towards ice-free conditions, internal variability remains strong until late in the 21st century. A substantial part of this variability is expressed as events of abrupt change in the sea ice cover. These internally-driven events with a duration of 5-9 years can mask or enhance the anthropogenically-forced sea ice trend and lead to substantial ice growth or ice loss. Abrupt sea ice trends are a common feature of the Barents Sea in the future until the region becomes close to ice-free. Interannual variability in general, and in form of these sub-decadal events specifically, is forced by a combination of ocean heat transport, meridional winds and ice import, with ocean heat transport as the most dominant contributor. Our analysis shows that the influence of these mechanisms remains largely unchanged throughout the simulation. Investigation of a simulation from the same model where global warming is limited to 2°C shows that both mean and variability of sea ice area in the Barents Sea can be sustained at a substantial level in the future, and that abrupt changes can continue to occur frequently and produce sea ice cover of similar extent to present day climate. This highlights that future emissions play an essential role in the further decline of the Barents Sea winter sea ice cover. The results of this thesis contribute to a better understanding of Arctic sea ice variability on different time scales, and especially on the role of internal variability which is important in order to predict future sea ice changes under anthropogenic warming.

Link to publication. You are most welcome to contact us or the corresponding author(s) directly, if you have questions.

Future Abrupt Changes in Winter Barents Sea Ice Area

Rieke, Ole (2021-06-01). Future Abrupt Changes in Winter Barents Sea Ice Area (Master’s thesis, University of Bergen, Bergen, Norway). https://bora.uib.no/bora-xmlui/handle/11250/2762637

Summary: The Barents Sea is an area of strong anthropogenic winter sea ice loss that is superimposed by pronounced internal variability on interannual to multidecadal timescales. This internal variability represents a source of large uncertainty in future climate projections in the Barents Sea. This study aims to investigate internal variability of Barents Sea ice area and its driving mechanisms in future climate simulations of the Community Earth System Model Large Ensemble under the RCP8.5 climate scenario. We find that although sea ice area is projected to decline towards ice-free conditions, internal variability remains strong until late in the 21st century. A substantial part of this variability is expressed as events of abrupt change in the sea ice cover. These internally-driven events with a duration of 5-9 years can mask or enhance the anthropogenically-forced sea ice trend and lead to substantial ice growth or ice loss. Abrupt sea ice trends are a common feature of the Barents Sea in the future until the region becomes close to ice-free. Interannual variability in general, and in form of these sub-decadal events specifically, is forced by a combination of ocean heat transport, meridional winds and ice import, with ocean heat transport as the most dominant contributor. Our analysis shows that the influence of these mechanisms remains largely unchanged throughout the simulation. Investigation of a simulation from the same model where global warming is limited to 2°C shows that both mean and variability of sea ice area in the Barents Sea can be sustained at a substantial level in the future, and that abrupt changes can continue to occur frequently and produce sea ice cover of similar extent to present day climate. This highlights that future emissions play an essential role in the further decline of the Barents Sea winter sea ice cover. The results of this thesis contribute to a better understanding of Arctic sea ice variability on different time scales, and especially on the role of internal variability which is important in order to predict future sea ice changes under anthropogenic warming.

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Training of supermodels in the context of weather and climate forecasting

Schevenhoven, Francine (2021-02-08). Training of supermodels in the context of weather and climate forecasting (PhD thesis, University of Bergen, Bergen, Norway). https://bora.uib.no/bora-xmlui/handle/11250/2727454 .

Summary: Given a set of imperfect weather or climate models, predictions can be improved by combining the models dynamically into a so called `supermodel’. The models are optimally combined to compensate their individual errors. This is different from the standard multi-model ensemble approach (MME), where the model output is statistically combined after the simulations. Instead, the supermodel can create a trajectory closer to observations than any of the imperfect models. By intervening during the forecast, errors can be reduced at an early stage and the ensemble can exhibit different dynamical behavior than any of the individual models. In this way, common errors between the models can be removed and new, physically correct behavior can appear.
In our simplified context of models sharing the same evolution function and phase space, we can define either a connected or a weighted supermodel. A connected supermodel uses nudging to bring the models closer together, while in a weighted supermodel all model states are replaced at regular time intervals (i.e., restarted) by the weighted average of the individual model states. To obtain optimal connection coefficients or weights, we need to train the supermodel on the basis of historical observations. A standard training approach such as minimization of a cost function requires many model simulations, which is computationally very expensive. This thesis has focused on developing two new methods to efficiently train supermodels. The first method is based on an idea called cross pollination in time, where models exchange states during the training. The second method is a synchronization-based learning rule, originally developed for parameter estimation.
The techniques are developed on low-order systems, such as Lorenz63, and later applied to different versions of the intermediate-complexity global coupled atmosphere-ocean-land model SPEEDO. Here the observations are from the same models, but with different parameters. The applicability of the method to real observations is tested using sensitivity to noisy and incomplete data. The characteristics the individual models should have in order to be combined together into a supermodel are identified, as well as which physical variables should be connected in a supermodel, and which ones should not. Both training methods result in supermodels that outperform both the individual models and the MME, for short term predictions as well as long term simulations. Furthermore, we show that the novel use of negative weights can improve predictions in cases where model errors do not cancel (for instance, all models are too warm with respect to the truth). A crucial advantage of the proposed training schemes is that in the present context relatively short training periods suffice to find good solutions. Although the validity of our conclusions in the context of real observations and model scenarios has yet to be proved, our results are very encouraging. In principle, the methods are suitable to train supermodels constructed using state-of-the art weather and climate models.

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Mechanisms and pathways of ocean heat anomalies in the Arctic-Atlantic region

Asbjørnsen, Helene (2020-12-10). Mechanisms and pathways of ocean heat anomalies in the Arctic-Atlantic region (PhD thesis, University of Bergen, Bergen, Norway). https://bora.uib.no/bora-xmlui/handle/11250/2712025 .

Summary: Along the Atlantic water pathway, from the Gulf Stream in the south to the Arctic Ocean in the north, variability in ocean heat content is pronounced on interannual to decadal time scales. Ocean heat anomalies in this Arctic-Atlantic sector are known to affect Arctic sea ice extent, marine ecosystems, and continental climate. However, there is at present neither consensus nor any complete understanding of the mechanisms causing such heat anomalies. This dissertation obtains a more robust understanding of regional ocean heat content variability by assessing the mechanisms and pathways of ocean heat anomalies in the Arctic-Atlantic region. The results are presented in three papers.

The first paper investigates the link between a variable Nordic Seas inflow and large- scale ocean circulation changes upstream. Using a global, eddy-permitting ocean hind- cast together with a Lagrangian analysis tool, numerical particles are seeded at the Iceland-Scotland Ridge and tracked backward in time. Water from the subtropics sup- plied by the North Atlantic Current (NAC) is found to be the main component of the Nordic Seas inflow (64%), while 26% of the inflow has a subpolar or Arctic origin. Different atmospheric patterns are seen to affect the circulation strength along the advective pathways, as well as the supply of subtropical and Arctic-origin water to the ridge through shifts in the NAC and the subpolar front. A robust link between a high transport of Arctic-origin water and a cold and fresh inflow is furthermore established, while a high transport of subtropical water leads to higher inflow salinities. The second paper investigates the mechanisms of interannual heat content variability in the Norwegian Sea downstream of the Iceland-Scotland Ridge, using a state-of-the-art ocean state estimate and closed heat budget diagnostics. Ocean advection is found to be the primary contributor to heat content variability in the Atlantic domain of the Norwegian Sea, although local surface fluxes also play an active role. Anomalous heat advection furthermore depends on the strength of the Atlantic water inflow and the conditions upstream of the ridge. Combined, the two papers demonstrate the importance of gyre dynamics and large-scale wind forcing in causing variability at the ridge, while high- lighting the impacts on Norwegian Sea heat content downstream.

For the third paper, warming trends in the Barents Sea and Fram Strait are explored, and, thus, the mechanisms underlying recent Atlantification of the Arctic Ocean. The Barents Sea is seen to transition to a warmer state, with reduced sea ice concentrations and Atlantic water extending further poleward. The mechanisms driving the warming are, however, found to be regionally dependent and not stationary in time. In the ice- free region, ocean advection is found to be a major driver of the warming trend due to increasing inflow temperatures in the late 1990s and early 2000s, while reduced ocean heat loss is contributing to the warming trend from the mid-2000s and onward. A considerable upper-ocean warming and a weakened stratification is seen in the ice- covered northwestern Barents Sea. However, in contrast to what has been previously hypothesized, the results do not point to increased upward heat fluxes from the Atlantic water layer to the Arctic surface layer as the source of the upper-ocean warming.

The supply of Atlantic heat to the Nordic Seas and the Arctic Ocean has been scrutinized using both Lagrangian methods and heat budget diagnostics. Combined, the three papers demonstrate the important role of ocean heat transport in causing regional heat content variability and change in the Arctic-Atlantic region. A better understanding of interannual to decadal ocean heat content variability has implications for future prediction efforts, and for how we understand the ocean’s role in ongoing and future climate change.

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Atlantic Multidecadal Variability (AMV) in the Norwegian Earth System model

Vågane, Julie Solsvik (2020-06-26). Atlantic Multidecadal Variability (AMV) in the Norwegian Earth System model (Master’s thesis, University of Bergen, Bergen, Norway). http://bora.uib.no/handle/1956/22970 .

Summary: The causes of low-frequency sea surface temperature (SST) variations in the Atlantic, known as Atlantic Multidecadal Variability (AMV), are debated. AMV has climatic impacts on for instance hurricane activity and Sahel rainfall, and understanding AMV can improve decadal predictions. While some discuss whether AMV arises due to external forcing, the ocean dynamics or the thermodynamic atmosphere-ocean interaction, others question the very existence of AMV. In this thesis, I look at the Norwegian Earth System Model (NorESM), investigating low-frequency variability and possible drivers for AMV in the North Atlantic. I compute a heat budget and a multiple linear regression (MLR) model, and investigate the influence of the dynamics and thermodynamics on AMV on different time scales and regions. I use the North Atlantic Oscillation (NAO) and the Atlantic Meridional Overturning circulation (AMOC) to characterize the large-scale impacts associated with ocean and atmospheric circulation patterns. The MLR model with NAO and AMOC, manages to explain 20.5 % of the temperature tendency on an interannual time scale, and 34.8 % on a decadal time scale in the subpolar gyre (SPG). In the tropics, the variance explained is smaller, only explaining 6.5 % interannually and 9.6 % decadally. Through a comparison with observations, I found that the AMOC amplitude is underestimated and the SST is off by over 1C. This may influence the performance of the MLR model. Finally, I present some ideas for improving the MLR model and the possibility for decadal predictions.

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