Understanding differences in North Atlantic poleward ocean heat transport and its variability in global climate models

The ocean heat transport from the North Atlantic to the Barents Sea impacts the sea ice extent and the energy budget of the Arctic. The analyzed climate models from the fifth (CMIP5) and sixth Coupled Model Intercomparison Project phase 6 (CMIP6) phases of the Coupled Model Intercomparison Project show large intermodel differences in the ocean heat transport with biases of several Terawatts at the Iceland-Scotland Ridge and Barents Sea Opening (BSO). While both model generations show a large spread in mean volume transports, in CMIP6 temperatures are more homogeneous and realistic, yielding heat transports closer to observations. On all time scales, changes in heat transport reflect changes in volume transport, while temperature changes affect the heat transport variability on longer time scales, especially at the BSO. The temporal variability of heat and volume transports is linked to wind forcing south of Iceland and along the Norwegian coast in all models but has different magnitudes.publishedVersio

Blocking Gibbs sampling in the mixed inheritance model using graph theory

International audienc

Hvordan jobber pedagogisk leder i barnehagen med trygghet i tilvenning for 1-åringen?

Formulering av problemstillingen var viktig for meg for å få dekt det jeg ville belyse i oppgaven min. Jeg var usikker på hvor jeg ville legge fokuset og hvordan problemstillingen min skulle belyse det jeg ville skrive om i oppgaven. Det var viktig for meg at problemstillingen var konkret, samtidig som den inneholder det som virkelig interesser meg. Derfor falt valget på å forske på hvordan pedagogisk leder jobber med å opprettholde trygghet for 1-åringen i tilvenningen. Problemstillingen min lyder dermed: «Hvordan jobber pedagogisk leder i barnehagen med trygghet i tilvenning for 1-åringen?»publishedVersio

Rekruttering av lærere til videregående skoler - Om å balansere omdømme og identitet: Et studie av de videregående skolene i Østfold fylkeskommune

Østfold fylkeskommune ville kunne gi rom for mangfoldet, gjennom å vise diversiteten i organisasjonen. Det arbeidet vil kunne bli utslagsgivende for å nå frem i mylderet av konkurrerende arbeidsgivere. Er man fast bestemt på å øke fokuset på omdømme, bør arbeidet rettes mot virksomhetenes identitet, der de ansatte kjenner seg igjen i fremstillingen av egen skole. Fylkeskommunen vil også kunne gi et bilde av seg selv som en arbeidsgiver som tilbyr de ansatte et sikkerhetsnett, kompetanseheving og karrieremuligheter, og dermed tilby både nåværende og fremtidige ansatte en attraktiv arbeidsplas

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

The efficiency of mapping of quantitative trait loci using cofactor analysis in half-sib design

This simulation study was designed to study the power and type I error rate in QTL mapping using cofactor analysis in half-sib designs. A number of scenarios were simulated with different power to identify QTL by varying family size, heritability, QTL effect and map density, and three threshold levels for cofactor were considered. Generally cofactor analysis did not increase the power of QTL mapping in a half-sib design, but increased the type I error rate. The exception was with small family size where the number of correctly identified QTL increased by 13% when heritability was high and 21% when heritability was low. However, in the same scenarios the number of false positives increased by 49% and 45% respectively. With a liberal threshold level of 10% for cofactor combined with a low heritability, the number of correctly identified QTL increased by 14% but there was a 41% increase in the number of false positives. Also, the power of QTL mapping did not increase with cofactor analysis in scenarios with unequal QTL effect, sparse marker density and large QTL effect (25% of the genetic variance), but the type I error rate tended to increase. A priori, cofactor analysis was expected to have higher power than individual chromosome analysis especially in experiments with lower power to detect QTL. Our study shows that cofactor analysis increased the number of false positives in all scenarios with low heritability and the increase was up to 50% in low power experiments and with lower thresholds for cofactors

Farm-Scale Crop Yield Prediction from Multi-Temporal Data Using Deep Hybrid Neural Networks

publishedVersio