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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  • Yu, L., Jin, X., & Schulz, E. W. (2019). Surface heat budget in the Southern Ocean from 42°S to the Antarctic marginal ice zone: four atmospheric reanalyses versus icebreaker Aurora Australis measurements. Polar Research, 38. https://doi.org/10.33265/polar.v38.3349

    Surface heat fluxes from four atmospheric reanalyses in the Southern Ocean are evaluated using air–sea measurements obtained from the Aurora Australis during off-winter seasons in 2010–12. The icebreaker tracked between Hobart, Tasmania (ca. 42°S), and the Antarctic continent, providing in situ benchmarks for the surface energy budget change in the Subantarctic Southern Ocean (58–42°S) and the eastern Antarctic marginal ice zone (MIZ, 68–58°S). We find that the reanalyses show a high-level agreement among themselves, but this agreement reflects a universal bias, not a “truth.” Downward shortwave radiation (SW↓) is overestimated (warm biased) and downward longwave radiation (LW↓) is underestimated (cold biased), an indication that the cloud amount in all models is too low. The ocean surface in both regimes shows a heat gain from the atmosphere when averaged over the seven months (October–April). However, the ocean heat gain in reanalyses is overestimated by 10–36 W m−2 (80–220%) in the MIZ but underestimated by 6–20 W m−2 (7–25%) in the Subantarctic. The biases in SW↓ and LW↓ cancel out each other in the MIZ, causing the surface heat budget to be dictated by the underestimation bias in sensible heat loss. These reanalyses biases affect the surface energy budget in the Southern Ocean by meaningfully affecting the timing of the seasonal transition from net heat gain to net heat loss at the surface and the relative strength of SW↓ at different regimes in summer, when the length-of-day effect can lead to increased SW↓ at high latitudes.

    View on polarresearch.net
  • Zawierucha, K., Marshall, C. J., Wharton, D., & Janko, K. (2019). A nematode in the mist: Scottnema lindsayae is the only soil metazoan in remote Antarctic deserts, at greater densities with altitude. Polar Research, 38. https://doi.org/10.33265/polar.v38.3494

    A decrease in biodiversity and density of terrestrial organisms with increasing altitude and latitude is a well-known ecogeographical pattern. However, studies of these trends are often taxonomically-biased toward well-known organisms and especially those with relatively large bodies, and environmental variability at the local scale may perturb these general effects. Here, we focus on understudied organisms—soil invertebrates—in Antarctic deserts, which are among the driest and coldest places on Earth. We sampled two remote Antarctic sites in the Darwin Glacier area and established an altitudinal gradient running from 210 to 836 m a.s.l. We measured soil geochemistry and organic matter content and linked these parameters with the presence of soil invertebrates. We found three general outcomes, two of which are consistent with general assumptions: (a) the hostile climatic condition of the Darwin Glacier region supports an extremely low diversity of soil metazoans represented by a single nematode species—Scottnema lindsayae; (b) soil geochemistry is the main factor influencing distribution of nematodes at the local scale. Contrary to our expectations, a positive correlation was found between nematode density and altitude. This last observation could be explained by an additional effect of soil moisture as we found this increased with altitude and may be caused by orographic clouds, which are present in this region. To the best of our knowledge such effects have been described in tropical and temperate regions. Potential effect of orographic clouds on soil properties in polar deserts may be a fruitful area of ecological research on soil fauna.

    View on polarresearch.net
  • Zhang, D., Huang, Y., Sun, B., Li, F., & Wang, H. (2019). Verification and Improvement of the Ability of CFSv2 to Predict the Antarctic Oscillation in Boreal Spring. Advances in Atmospheric Sciences, 36(3), 292–302. https://doi.org/10.1007/s00376-018-8106-6

    The boreal spring Antarctic Oscillation (AAO) has a significant impact on the spring and summer climate in China. This study evaluates the capability of the NCEP’s Climate Forecast System, version 2 (CFSv2), in predicting the boreal spring AAO for the period 1983–2015. The results indicate that CFSv2 has poor skill in predicting the spring AAO, failing to predict the zonally symmetric spatial pattern of the AAO, with an insignificant correlation of 0.02 between the predicted and observed AAO Index (AAOI). Considering the interannual increment approach can amplify the prediction signals, we firstly establish a dynamical–statistical model to improve the interannual increment of the AAOI (DY AAOI), with two predictors of CFSv2-forecasted concurrent spring sea surface temperatures and observed preceding autumn sea ice. This dynamical–statistical model demonstrates good capability in predicting DY AAOI, with a significant correlation coefficient of 0.58 between the observation and prediction during 1983–2015 in the two-year-out cross-validation. Then, we obtain an improved AAOI by adding the improved DY AAOI to the preceding observed AAOI. The improved AAOI shows a significant correlation coefficient of 0.45 with the observed AAOI during 1983–2015. Moreover, the unrealistic atmospheric response to March–April–May sea ice in CFSv2 may be the possible cause for the failure of CFSv2 to predict the AAO. This study gives new clues regarding AAO prediction and short-term climate prediction.

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Last update from database: 12/1/25, 3:10 AM (UTC)

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