2002
DOI: 10.1002/joc.793
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Changes in seasonal and annual high‐frequency air temperature variability in the Arctic from 1951 to 1990

Abstract: A detailed analysis of intraseasonal (within season) and interannual (between years) temperature variability for the whole Arctic for the period 1951-90 is provided. For this purpose four temperature variables were used: average (TMEAN), maximum (TMAX) and minimum (TMIN) temperatures, and the diurnal temperature range (DTR). The source data for the analysis were the daily TMAX and TMIN for ten stations representing almost all climatic regions in the Arctic. The methods of calculation of temperature variability… Show more

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Cited by 25 publications
(25 citation statements)
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“…A strong seasonality in ITV is obvious, as already indicated by earlier studies (e.g. Przybylak 2002, Chapman & Walsh 2007. The strongest variability of 3 to 6°C was found in winter and transition seasons along the sea ice edges due to the high interannual sea ice variability.…”
Section: Variability and Change In Seasonal Temperaturesupporting
confidence: 80%
See 1 more Smart Citation
“…A strong seasonality in ITV is obvious, as already indicated by earlier studies (e.g. Przybylak 2002, Chapman & Walsh 2007. The strongest variability of 3 to 6°C was found in winter and transition seasons along the sea ice edges due to the high interannual sea ice variability.…”
Section: Variability and Change In Seasonal Temperaturesupporting
confidence: 80%
“…However, the examined stations were primarily located in North America (most of them on the mainland), Eurasia (only very few of them in the Arctic region), and Australia. Arctic-specific studies include those of Przybylak (2002), who studied 10 stations representing the major Arctic climate regions, and Overland et al (2004), who analyzed 59 stations covering the pan-Arctic. Due to this poor spatial data coverage in the Arctic, all earlier studies do not allow us to assess the considerable regional-scale temperature variability that can be simulated by regional climate models (RCMs).…”
Section: Introductionmentioning
confidence: 99%
“…The proposed mechanism has implications for changes in Arctic surface temperatures. Kahl et al [2001] show that 500 hPa temperatures in the Arctic have not experienced any trend over the past 50 years, while surface air temperatures experienced a less than expected warming trend [ Polyakov et al , 2002; Przybylak , 2002]. General circulation models (GCMs) predict the surface warming in the Arctic to be 3.5–5°C by the year 2100, i.e., 3–5°C/100 years [ IPCC , 2001]; while the observed rates of Arctic warming over the 20th century are 0.5°C/100 years [ Polyakov et al , 2002].…”
Section: Summary and Implicationsmentioning
confidence: 99%
“…Our findings demonstrate that anthropogenic influence is detectable in Antarctic land surface temperature, and distinguishable from a naturally forced response, even given the limited station network and short period for which data are available, and that circulation changes, which are largely anthropogenic 8 , have reduced warming rates over most of Antarctica in models and observations in recent decades. In the Arctic, some authors have suggested that observed Arctic temperature changes are inconsistent with climate model predictions 27 , and dominated by internal variability 28,29 , and indeed so far no formal attribution studies of Arctic temperature change exist. We find that anthropogenic influence on Arctic temperature is detectable and distinguishable from the influence of natural forcings.…”
mentioning
confidence: 99%