Circulation and transformation of Atlantic and Arctic water masses in climate models

Ocean heat transport and associated heat loss to the atmosphere contributes significantly to the anomalously mild climate of northwestern Europe and its variability. In this thesis, the circulation and transformation of water masses in the northern North Atlantic and the Nordic Seas have been assessed and explored in state-of-the-art climate models. A most important aspect of model evaluation is to identify the degree of realism in model climatology and variability, e.g., for model improvement or in order to assess the potential for decadal-scale climate prediction. A main approach for assessing simulated ocean circulations herein is water mass analysis as routinely applied in observational oceanography. Air-sea exchange and water mass transformation at northern high latitudes are accordingly related to the Atlantic Meridional Overturning Circulation (AMOC). The variable overturning of the Bergen Climate Model (BCM) – the core model system in this thesis – is found to reflect decadal variability in dense water formation in the Labrador Sea and in the oceanic heat transport into the Nordic Seas, the overall constraint on the northernmost water mass transformation. The simulated AMOC is strongly interconnected with the horizontal Subpolar Gyre circulation. Decadal variability of BCM’s Subpolar Gyre, as its AMOC, can partly be explained as a response to distinct patterns of atmospheric variability. The intercomparison of BCM with two other climate models finds the model pathways for the North Atlantic Current and the model sea-ice covers to differ substantially, and hence their oceanic poleward transport of heat, their air-sea exchange, and consequent northern water mass transformation to be very different

Towards Hardware-Based Application Fingerprinting with Microarchitectural Signals for Zero Trust Environments

The interactions between software and hardware are increasingly important to computer system security. This research collects sequences of microprocessor control signals to develop machine learning models that identify software tasks. The proposed approach considers software task identification in hardware as a general problem with attacks treated as a subset of software tasks. Two lines of effort are presented. First, a data collection approach is described to extract sequences of control signals labeled by task identity during real (i.e., non-simulated) system operation. Second, experimental design is used to select hardware and software configuration to train and evaluate machine learning models. The machine learning models significantly outperform a Naive classifier based on Euclidean distances from class means. Various configurations produce balanced accuracy scores between 26.08% and 96.89%

Towards Hardware-Based Application Fingerprinting with Microarchitectural Signals for Zero Trust Environments

The interactions between software and hardware are increasingly important to computer system security. This research collects sequences of microprocessor control signals to develop machine learning models that identify software tasks. The proposed approach considers software task identification in hardware as a general problem with attacks treated as a subset of software tasks. Two lines of effort are presented. First, a data collection approach is described to extract sequences of control signals labeled by task identity during real (i.e., non-simulated) system operation. Second, experimental design is used to select hardware and software configuration to train and evaluate machine learning models. The machine learning models significantly outperform a Naive classifier based on Euclidean distances from class means. Various configurations produce balanced accuracy scores between 26.08% and 96.89%

Mangfold av tiltak En case-studie av hvordan jobber Helse Bergen med å redusere sykefraværet, og hvilken effekt har IA-avtalen hatt på arbeidet

Studien har hatt som formål å undersøke hvordan Helse Bergen jobber med å redusere sykefraværet og hvilken effekt har IA-avtalen hatt på arbeidet? For å svare på spørsmålet ble det brukt kvalitativ metode med dokumentanalyse og semi- strukturert intervju med nøkkelpersoner. Dokumentanalysen bygger på fire ulike dokumenter og er delt inn i tre fokusområder: redusering av sykefravær i arbeidslivet, sykefraværsarbeid på sykehus og hvordan jobber Helse Bergen jobber med sykefravær. Informantene består av individer fra foretaksverneombudet, personal- og organisasjonsavdelingen, leder av IA-arbeidet og enhetsleder. Før datainnsamlingen var fullført, ble det formulert tre forventninger som bygget på antakelsen om at ledelsen spiller en essensiell rolle i å redusere sykefraværet på arbeidsplassen. Forventning en motivasjon - Ledere har stor innvirkning på hvor motiverte de ansatte er i sitt arbeid. Å få hjelp, støtte og bli sett av sin leder er sentrale elementer for å forstå motivasjonen i organisasjonen. Forventning to endring og tilpasninger - Ledere spiller en sentral rolle i planlagte endringsprosesser, og det er ofte ledelse som er avgjørende for om slike endringsprosesser blir vellykkede. Forventning tre strategi og strategiske beslutninger - Ledelse blir forbundet med personer som innehar lederposisjoner og dermed beslutningsmyndighet. Dette innebærer at ledere spiller en sentral rolle i å forstå hvorfor og hvordan strategiske beslutninger bør tas. Funnene bekrefter forventingene. Både dokumentanalysen og studiens informanter påpeker at motivasjon er viktig for å lykkes med å redusere sykefraværet. Ledere i Helse Bergen tilbys kurs og veiledning om motivasjon for å opprettholde motivasjonen. Klinikkdirektører og divisjonsledere har jevnlige møter hvor de diskuterer hva som kan forbedres, og hva som allerede fungerer bra i enheten. Dette er et bevist valg Helse Bergen gjør for at endringsprosesser skal oppleves som vellykket. Studien har vist at Helse Bergen bruker nærværsarbeid som sin overordnede strategi for å redusere sykefraværet. Når ledelsen skal gjennomføre endringer og ta beslutninger som påvirker de ansatte, blir disse tatt i samråd med de ansatte.Masteroppgave i administrasjon og organisasjonsvitenskapAORG350MASV-AOR

On model differences and skill in predicting sea surface temperature in the Nordic and Barents Seas

The Nordic Seas and the Barents Sea is the Atlantic Ocean’s gateway to the Arctic Ocean, and the Gulf Stream’s northern extension brings large amounts of heat into this region and modulates climate in northwestern Europe. We have investigated the predictive skill of initialized hindcast simulations performed with three state-of-the-art climate prediction models within the CMIP5-framework, focusing on sea surface temperature (SST) in the Nordic Seas and Barents Sea, but also on sea ice extent, and the subpolar North Atlantic upstream. The hindcasts are compared with observation-based SST for the period 1961–2010. All models have significant predictive skill in specific regions at certain lead times. However, among the three models there is little consistency concerning which regions that display predictive skill and at what lead times. For instance, in the eastern Nordic Seas, only one model has significant skill in predicting observed SST variability at longer lead times (7–10 years). This region is of particular promise in terms of predictability, as observed thermohaline anomalies progress from the subpolar North Atlantic to the Fram Strait within the time frame of a couple of years. In the same model, predictive skill appears to move northward along a similar route as forecast time progresses. We attribute this to the northward advection of SST anomalies, contributing to skill at longer lead times in the eastern Nordic Seas. The skill at these lead times in particular beats that of persistence forecast, again indicating the potential role of ocean circulation as a source for skill. Furthermore, we discuss possible explanations for the difference in skill among models, such as different model resolutions, initialization techniques, and model climatologies and variance. © 2016 The Author(s

Variability along the Atlantic water pathway in the forced Norwegian Earth System Model

The growing attention on mechanisms that can provide predictability on interannual-to-decadal time scales, makes it necessary to identify how well climate models represent such mechanisms. In this study we use a high (0.25° horizontal grid) and a medium (1°) resolution version of a forced global ocean-sea ice model, utilising the Norwegian Earth System Model, to assess the impact of increased ocean resolution. Our target is the simulation of temperature and salinity anomalies along the pathway of warm Atlantic water in the subpolar North Atlantic and the Nordic Seas. Although the high resolution version has larger biases in general at the ocean surface, the poleward propagation of thermohaline anomalies is better resolved in this version, i.e., the time for an anomaly to travel northward is more similar to observation based estimates. The extent of these anomalies can be rather large in both model versions, as also seen in observations, e.g., stretching from Scotland to northern Norway. The easternmost branch into the Nordic and Barents Seas, carrying warm Atlantic water, is also improved by higher resolution, both in terms of mean heat transport and variability in thermohaline properties. A more detailed assessment of the link between the North Atlantic Ocean circulation and the thermohaline anomalies at the entrance of the Nordic Seas reveals that the high resolution is more consistent with mechanisms that are previously published. This suggests better dynamics and variability in the subpolar region and the Nordic Seas in the high resolution compared to the medium resolution. This is most likely due a better representation of the mean circulation in the studied region when using higher resolution. As the poleward propagation of ocean heat anomalies is considered to be a key source of climate predictability, we recommend that similar methodology presented herein should be performed on coupled climate models that are used for climate prediction.publishedVersio

Propagation of thermohaline anomalies and their predictive potential along the Atlantic water pathway

Abstract We assess to what extent seven state-of-the-art dynamical prediction systems can retrospectively predict winter sea surface temperature (SST) in the subpolar North Atlantic and the Nordic seas in the period 1970–2005. We focus on the region where warm water flows poleward (i.e., the Atlantic water pathway to the Arctic) and on interannual-to-decadal time scales. Observational studies demonstrate predictability several years in advance in this region, but we find that SST skill is low with significant skill only at a lead time of 1–2 years. To better understand why the prediction systems have predictive skill or lack thereof, we assess the skill of the systems to reproduce a spatiotemporal SST pattern based on observations. The physical mechanism underlying this pattern is a propagation of oceanic anomalies from low to high latitudes along the major currents, the North Atlantic Current and the Norwegian Atlantic Current. We find that the prediction systems have difficulties in reproducing this pattern. To identify whether the misrepresentation is due to incorrect model physics, we assess the respective uninitialized historical simulations. These simulations also tend to misrepresent the spatiotemporal SST pattern, indicating that the physical mechanism is not properly simulated. However, the representation of the pattern is slightly degraded in the predictions compared to historical runs, which could be a result of initialization shocks and forecast drift effects. Ways to enhance predictions could include improved initialization and better simulation of poleward circulation of anomalies. This might require model resolutions in which flow over complex bathymetry and the physics of mesoscale ocean eddies and their interactions with the atmosphere are resolved. Significance Statement In this study, we find that dynamical prediction systems and their respective climate models struggle to realistically represent ocean surface temperature variability in the eastern subpolar North Atlantic and Nordic seas on interannual-to-decadal time scales. In previous studies, ocean advection is proposed as a key mechanism in propagating temperature anomalies along the Atlantic water pathway toward the Arctic Ocean. Our analysis suggests that the predicted temperature anomalies are not properly circulated to the north; this is a result of model errors that seems to be exacerbated by the effect of initialization shocks and forecast drift. Better climate predictions in the study region will thus require improving the initialization step, as well as enhancing process representation in the climate models.Acknowledgments. The research leading to these results has received funding from the Blue-Action Project (European Union’s Horizon 2020 research and innovation program, Grant 727852), the Trond Mohn Foundation with the project Bjerknes Climate Prediction Unit (BCPU, Grant BFS2018TMT01), the NordForsk under the Nordic Centre of Excellence (ARCPATH, 76654), and from the Bjerknes Centre with the project SKD MEDEVAC. The research leading to these results has also received funding from the German Federal Ministry of Education and Research (BMBF) through the JPI Climate/JPI Oceans NextG-Climate Science-ROADMAP (FKZ: 01LP2002A; DM and Norwegian Grant 316618/JPIC/JPIO-04; HRL and NK and ANR-19-JPOC-003; JM). PO was funded by the Spanish Ministry for the Economy, Industry and Competitiveness through the grant RYC-2017-22772. SY also receives financial support from the Danish National Center for Climate Research (NCKF). The National Center for Atmospheric Research is a major facility sponsored by the U.S. National Science Foundation (NSF) under Cooperative Agreement 1852977. EM is supported by the U.S. NSF Office of Polar Programs Grant 1737377. The prediction simulations using EC-EARTH anomaly initialization system were performed by SMHI on resources provided by the Swedish National Infrastructure for Computing (SNIC).Peer Reviewed"Article signat per 16 autors/es: H. R. Langehaug, P. Ortega, F. Counillon, D. Matei, E. Maroon, N. Keenlyside, J. Mignot, Y. Wang, D. Swingedouw, I. Bethke, S. Yang, G. Danabasoglu, A. Bellucci, P. Ruggieri, D. Nicolì, and M. Årthun"Postprint (published version

Mechanisms of decadal North Atlantic climate variability and implications for the recent cold anomaly

Decadal sea surface temperature (SST) fluctuations in the North Atlantic Ocean influence climate over adjacent land areas and are a major source of skill in climate predictions. However, the mechanisms underlying decadal SST variability remain to be fully understood. This study isolates the mechanisms driving North Atlantic SST variability on decadal time scales using low-frequency component analysis, which identifies the spatial and temporal structure of low-frequency variability. Based on observations, large ensemble historical simulations, and preindustrial control simulations, we identify a decadal mode of atmosphere–ocean variability in the North Atlantic with a dominant time scale of 13–18 years. Large-scale atmospheric circulation anomalies drive SST anomalies both through contemporaneous air–sea heat fluxes and through delayed ocean circulation changes, the latter involving both the meridional overturning circulation and the horizontal gyre circulation. The decadal SST anomalies alter the atmospheric meridional temperature gradient, leading to a reversal of the initial atmospheric circulation anomaly. The time scale of variability is consistent with westward propagation of baroclinic Rossby waves across the subtropical North Atlantic. The temporal development and spatial pattern of observed decadal SST variability are consistent with the recent observed cooling in the subpolar North Atlantic. This suggests that the recent cold anomaly in the subpolar North Atlantic is, in part, a result of decadal SST variability.publishedVersio

The role of subpolar deep water formation and Nordic Seas overflows in simulated multidecadal variability of the Atlantic meridional overturning circulation

We investigate the respective role of variations in subpolar deep water formation and Nordic Seas overflows for the decadal to multidecadal variability of the Atlantic meridional overturning circulation (AMOC). This is partly done by analysing long (order of 1000 years) control simulations with five coupled climate models. For all models, the maximum influence of variations in subpolar deep water formation is found at about 45° N, while the maximum influence of variations in Nordic Seas overflows is rather found at 55 to 60° N. Regarding the two overflow branches, the influence of variations in the Denmark Strait overflow is, for all models, substantially larger than that of variations in the overflow across the Iceland–Scotland Ridge. The latter might, however, be underestimated, as the models in general do not realistically simulate the flow path of the Iceland–Scotland overflow water south of the Iceland–Scotland Ridge. The influence of variations in subpolar deep water formation is, on multimodel average, larger than that of variations in the Denmark Strait overflow. This is true both at 45° N, where the maximum standard deviation of decadal to multidecadal AMOC variability is located for all but one model, and at the more classical latitude of 30° N. At 30° N, variations in subpolar deep water formation and Denmark Strait overflow explain, on multimodel average, about half and one-third respectively of the decadal to multidecadal AMOC variance. Apart from analysing multimodel control simulations, we have performed sensitivity experiments with one of the models, in which we suppress the variability of either subpolar deep water formation or Nordic Seas overflows. The sensitivity experiments indicate that variations in subpolar deep water formation and Nordic Seas overflows are not completely independent. We further conclude from these experiments that the decadal to multidecadal AMOC variability north of about 50° N is mainly related to variations in Nordic Seas overflows. At 45° N and south of this latitude, variations in both subpolar deep water formation and Nordic Seas overflows contribute to the AMOC variability, with neither of the processes being very dominant compared to the other