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 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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The latent heat fluxes (LHF) and sensible heat fluxes (SHF) over the Southern Ocean from six different data sets are inter-compared for the period 1988- 2000. The six data sets include three satellite-based products, namely, the second version of the Goddard Satellite-Based Surface Turbulent Fluxes data set (GSSTF-2), the third version of the Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data (HOAPS-3) and the Japanese Ocean Fluxes Data Sets with Use of Remote Sensing Observations (J-OFURO); two global reanalysis products, namely, the National Centers for Environmental Prediction-Department of Energy Reanalysis 2 data set (NCEP-2) and the European Centre for Medium-Range Weather Forecasts 40 Year Re-analysis data set (ERA-40); and the Objectively Analyzed Air-Sea Fluxes for the Global Oceans data set (OAFlux). All these products reveal a similar pattern in the averaged flux fields. The zonal mean LHF fields all exhibit a continuous increase equatorward. With an exception of HOAPS-3, the zonal mean SHF fields display a minimum value near 50°S, increasing both pole- and equatorward. The differences in the standard deviation for LHF are larger among the six data products than the differences for SHF. Over the regions where the surface fluxes are significantly influenced by the Antarctic Oscillation and the Pacific-South American teleconnection, the values and distributions of both LHF and SHF are consistent among the six products. It was found that the spatial patterns of the standard deviations and trends of LHF and SHF can be explained primarily by sea-air specific humidity and temperature differences; wind speed plays a minor role. Keywords: Latent heat flux; sensible heat flux; Southern Ocean.
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Topic
- meteorologi
- Antarktis (1)
- atmosfæren (1)
- klimatologi (2)
- observasjoner (1)
- Sørishavet (1)
Resource type
- Journal Article (2)
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Online resource
- yes (2)