Antarktis-bibliografi er en database over den norske Antarktis-litteraturen.
Hensikten med bibliografien er å synliggjøre norsk antarktisforskning og annen virksomhet/historie i det ekstreme sør. Bibliografien er ikke komplett, spesielt ikke for nyere forskning, men den blir oppdatert.
Norsk er her definert som minst én norsk forfatter, publikasjonssted Norge eller publikasjon som har utspring i norsk forskningsprosjekt.
Antarktis er her definert som alt sør for 60 grader. I tillegg har vi tatt med Bouvetøya.
Det er ingen avgrensing på språk (men det meste av innholdet er på norsk eller engelsk). Eldre norske antarktispublikasjoner (den eldste er fra 1894) er dominert av kvalfangst og ekspedisjoner. I nyere tid er det den internasjonale polarforskninga som dominerer. Bibliografien er tverrfaglig; den dekker både naturvitenskapene, politikk, historie osv. Skjønnlitteratur er også inkludert, men ikke avisartikler eller upublisert materiale.
Til høyre finner du en «HELP-knapp» for informasjon om søkemulighetene i databasen. Mange referanser har lett synlige lenker til fulltekstversjon av det aktuelle dokumentet. For de fleste tidsskriftartiklene er det også lagt inn sammendrag.
Bibliografien er produsert ved Norsk Polarinstitutts bibliotek.
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Results 2 resources
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The Inverse Gaussian approximation of transit time distribution method (IG-TTD) is widely used to infer the anthropogenic carbon (Cant) concentration in the ocean from measurements of transient tracers such as chlorofluorocarbons (CFCs) and sulfur hexafluoride (SF6). Its accuracy relies on the validity of several assumptions, notably (i) a steady state ocean circulation, (ii) a prescribed age tracer saturation history, e.g., a constant 100% saturation, (iii) a prescribed constant degree of mixing in the ocean, (iv) a constant surface ocean air-sea CO2 disequilibrium with time, and (v) that preformed alkalinity can be sufficiently estimated by salinity or salinity and temperature. Here, these assumptions are evaluated using simulated “model-truth” of Cant. The results give the IG-TTD method a range of uncertainty from 7.8% to 13.6% (11.4 Pg C to 19.8 Pg C) due to above assumptions, which is about half of the uncertainty derived in previous model studies. Assumptions (ii), (iv) and (iii) are the three largest sources of uncertainties, accounting for 5.5%, 3.8% and 3.0%, respectively, while assumptions (i) and (v) only contribute about 0.6% and 0.7%. Regionally, the Southern Ocean contributes the largest uncertainty, of 7.8%, while the North Atlantic contributes about 1.3%. Our findings demonstrate that spatial-dependency of , and temporal changes in tracer saturation and air-sea CO2 disequilibrium have strong compensating effect on the estimated Cant. The values of these parameters should be quantified to reduce the uncertainty of IG-TTD; this is increasingly important under a changing ocean climate.
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A suite of standard ocean hydrographic and circulation metrics are applied to the equilibrium physical solutions from 13 global carbon models participating in phase 2 of the Ocean Carbon-cycle Model Intercomparison Project (OCMIP-2). Model-data comparisons are presented for sea surface temperature and salinity, seasonal mixed layer depth, meridional heat and freshwater transport, 3-D hydrographic fields, and meridional overturning. Considerable variation exists among the OCMIP-2 simulations, with some of the solutions falling noticeably outside available observational constraints. For some cases, model-model and model-data differences can be related to variations in surface forcing, subgrid-scale parameterizations, and model architecture. These errors in the physical metrics point to significant problems in the underlying model representations of ocean transport and dynamics, problems that directly affect the OCMIP predicted ocean tracer and carbon cycle variables (e.g., air-sea CO2 flux, chlorofluorocarbon and anthropogenic CO2 uptake, and export production). A substantial fraction of the large model-model ranges in OCMIP-2 biogeochemical fields (±25–40%) represents the propagation of known errors in model physics. Therefore the model-model spread likely overstates the uncertainty in our current understanding of the ocean carbon system, particularly for transport-dominated fields such as the historical uptake of anthropogenic CO2. A full error assessment, however, would need to account for additional sources of uncertainty such as more complex biological-chemical-physical interactions, biases arising from poorly resolved or neglected physical processes, and climate change.
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