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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During the 35th Indian Scientific Expedition to Antarctica, measurements of atmospheric carbon dioxide (CO 2 ) were carried out using a Li-Cor CO 2 /H 2 O analyser at Bharati, the Indian Antarctic research station. This study examines the short-term variability of atmospheric CO 2 during the austral summer (January–February) of 2016. An average of 396.25 ± 4.20 ppm was observed during the study period. Meteorological parameters such as relative humidity, precipitation, wind speed, air temperature and atmospheric boundary layer height in conjunction with photosynthetically active radiation, the biological activity indicator which modulates atmospheric CO 2 concentration have been investigated. High wind speed (>20 m s −1 ) combined with precipitation scavenges CO 2 in the atmosphere, resulting in low concentrations at the study site. The lowest CO 2 concentration of 385 ppm coincided with heavy precipitation of 15 mm during study period. Statistical analysis of the data shows that precipitation and relative humidity independently correlated 55% (r = −0.55) and 32% (r = −0.32), respectively, with the variability of CO 2 mixing in the atmosphere at the study site. Atmospheric CO 2 was significantly correlated with precipitation alone with a p value of 0.003. Further, multiple regression analysis was performed to test the significant relation between variability of atmospheric CO 2 and meteorological parameters. Long-range air-mass transport analysis depicted that the majority of the air masses are reaching the study site through the oceanic region.
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- karbondioksid
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- antropogenisk CO2 (1)
- atmosfæren (1)
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- forskning (1)
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