Western Arctic Climate Change
ACKNOWLEDGMENTS
This study was supported by the National Science Foundation under grant OPP-9321547 and NOAA's Climate Monitoring and Diagnostics Laboratory.
INTRODUCTION
General circulation model (GCM) simulations indicate that the Arctic is especially prone to warming in response to globally increasing concentrations of greenhouse gases. There is observational evidence to support these predictions, some of which resembles the "fingerprint" of greenhouse-induced change that models predict. There remains, however, considerable debate as to whether the observed pattern of change is a result of anthropogenic effects or is a manifestation of natural climate variability. Following is an overview of an analysis of variations in western Arctic climate with a focus on records from the NOAA/ESRL Barrow Observatory (71.3°N, 156.6°W) (BRW), the northernmost climate monitoring site in the United States.
![[MAP OF THE AREA]](graphics/arcticback96.gif)
BRW Barrow, AK (71.32°N,156.61°W)
BTI Barter Island, AK (70.13°N, 143.63°W)
MYS Mys Schmidt(68.92°N, 179.48°W)
OVV Ostrov Vrangelya (70.97°N, 178.53°W)Map of the western Arctic showing four meteorological stations referred to in the following discussion.
The coastal region of the western Arctic is especially sensitive climatically because it is near cryospheric boundaries and it is influenced by both extratropical and Arctic synoptic activity. Observations from coastal sites along eastern Siberia and Alaska show similar variations in temperature. The Barrow climate has been found to be representative of the region as a whole.
ARCTIC CLOUD EFFECTS
Thermal cloud-radiative forcing and advective processes during winter and spring are proposed as factors contributing to the regional climate variations for the period 1965-1995. To test this hypothesis, monthly mean surface and upper-level temperatures were correlated with sky cover observations and flow patterns referenced to Barrow. In addition, the radiative effects of advective cloud systems during the cold season are quantified empirically to demonstrate how clouds impact the Arctic temperature regime.
In Figure 1 BRW annual mean temperatures (1965-1995) are compared with available data from Barter Island (BTI), Mys Schmidt (MYS), and Ostrov Vrangelya (OVV). Seven-year smoothed time series are shown to reveal the multiyear variability of the regional climate. Linear regressions were performed (on the actual monthly averages) and confidence levels of the fits determined on the basis of the Student t statistic for each of the time series. The analysis suggests that, from the mid 1960s warming in the western Arctic has exceeded 1.0 °C, and in the case of Barrow, the 30-year trend exceeds 1.4 °C, noting that this longer record includes the very warm years of the mid 1990s. Annual and monthly comparisons of the overlapping time series from all four stations revealed similar multiyear features suggesting that the region as a whole is affected by similar thermodynamic processes associated with synoptic scale circulation patterns.
![[GRAPH AS DESCRIBED BELOW]](graphics/w_arc_t4.gif)
Figure 1. Seven-year smoothed time series of annual mean temperatures at four western Arctic sites. The actual data (not shown) were fitted linearly to evaluate trends. The results are given in the legend as temperature changes over 30 years, on the basis of the regressions. The confidence level of each fit is given in parentheses. Stations are indicated on the map above.
Other studies show that beginning in the mid-1970s the Aleutian Low pressure system intensified resulting in increased cyclonic activity in the north Pacific. As a result transient disturbances may have advected more warm, moist air into the Arctic enhancing cloudiness. As a consequence the surface and atmospheric radiative balance may have been perturbed. A quantitative illustration of how these processes can affect the temperature regime in the vicinity of Barrow is presented in Figure 2. The figure shows seven-year smoothed monthly average temperature and total sky cover time series and linear fits for1965-1995 for February and November. These months exhibited the most pronounced 30-year temperature changes over the period, but are of opposite sign. The legends give correlation coefficients relating temperature and sky cover. Significant positive correlations are found whether warming or cooling occurs over long time periods. For instance, the February warming and November cooling relate to an 11% increase and a 15% decrease in total sky cover, respectively. Figure 3 shows more clearly the sensitivity of surface temperature to changes in sky cover for February and November. In terms of climate change, it appears that it does not take a drastic change in cloudiness to cause a significant change in temperature in this region of the Arctic. All months that are snow-covered in Barrow indicate positive correlations between temperature and cloudiness, an indication that cloudiness is a primary factor that controls winter surface temperatures in this region. This, in turn, is a manifestation of radiative forcing by clouds that results when thermal emission to the surface is enhanced relative to that of the clear Arctic atmosphere as discussed below.
![[GRAPH AS DESCRIBED BELOW]](graphics/brwt_s.gif)
Figure 2. Time series of surface temperature and total sky cover for Barrow (1965-1995) with linear fits superimposed (thin solid lines). The curves represent seven-year smoothed data. Legends give (+/-) 30-year temperature changes on the basis of the regressions and their confidence levels ( ). Correlation coefficients relating monthly values of temperature and sky cover are given [in brackets]. The respective scales have equal ranges, but their limits vary.
![[GRAPH AS DESCRIBED BELOW]](graphics/w_arct4.gif)
Figure 3. Scatter plots showing the relationship between surface temperature and sky cover at Barrow for February and November 1965-1995. The monthly data have been fitted linearly to illustrate the sensitivity of temperature to small changes in cloudiness that underlie the trends shown in Figure 2.
CLOUD-RADIATIVE FORCING
To better understand how clouds modulate the long-term climate of the region it is helpful to examine how they radiatively affect surface temperatures on shorter time scales. This is illustrated in Figure 4, which shows time series of daily mean values of surface temperature Ts, longwave downwelling irradiance (LWD), and sky cover (SC) for the 1993-1994 "winter" at Barrow. Correlation coefficients relating Ts and SC to LWD are given in the legends. LWD is a function of the mean radiating temperature and the effective emissivity of the atmosphere. Because clouds tend to be warm relative to the surface under the inversion conditions that persist in winter at Barrow, and their emissivities are large compared with clear air, LWD is enhanced during cloudy periods. During the winter at Barrow temperature increases exceeding 10°C in response to increases in LWD of 80-100 W m-2 are common. The dramatic fluctuations apparent in Figure 4 occur on synoptic time scales. Even during April, when the daily mean solar flux is large, clouds tend to warm rather than cool the surface, a feature of polar climate referred to as the "radiation paradox." Measurements of LWD are a very good proxy for evaluating cloud effects during winter because this radiative quantity accounts inherently for changes in cloud temperature and/or cloud opacity, and it can be measured with reasonable accuracy.
![[GRAPH AS DESCRIBED BELOW]](graphics/win9394.gif)
Figure 4. Composite plot of daily mean surface temperatures Ts, downward longwave irradiances LWD, and total sky cover SC, in tenths, (spikes; lower, left scale) at Barrow for the winter 1993/1994. Correlation coefficients relating Ts to LWD and LWD to SC are given [in brackets].
DYNAMICAL FORCING ASSOCIATED WITH CIRCULATION PATTERNS
During the cold season, horizontal advection is suppressed within the stable Arctic boundary layer, and because extensive ice and snow cover limits local sources of water vapor, cloud formation is inhibited. Therefore, the advection of heat and moisture above the inversion layer is an important factor influencing regional cloud distributions. To evaluate transport aloft, the 850 mb (between about 1350 m and 1400 m altitude) wind field above Barrow was examined. Twice-daily rawinsonde data from the National Weather Service at Barrow were used in this analysis. Here, only results for February and November are presented; these can be compared directly with coincident time series of temperature and sky cover (see Figure 2).
The wind data were first divided into sixteen 22.5° sectors centered at bearings of 0.0° (N), 22.5° (NNE), 45.0° (NE), etc. Then, linear regressions were computed to evaluate the frequency and speed distributions in each sector, by month, over the period 1965-1995. For February and November southwestly winds revealed the greatest variability. The results are presented in Figure 5, which shows seven-year smoothed time series of the frequency and average speed of southwesterlies at the 850 mb level in the vicinity of Barrow. Plot legends give the percentage increase or decrease in frequency and the change in wind speed for a 30-year period on the basis of the regressions; confidence levels are also given. By comparing these results with those shown in Figure 2 it is apparent that there is a physical link between the upper-level southwesterly winds, cloudiness, and surface temperature there. It appears that a long-term intensification of southwesterlies in February has contributed to the warming whereas diminishing southwesterlies in November have, on average, resulted in cooler, less cloudy conditions. Each of these trends is most likely associated with changes in synoptic-scale circulation patterns, which may not necessarily be a manifestation of global warming.
![[GRAPH AS DESCRIBED BELOW]](graphics/brw_wind2.gif)
Figure 5. Seven-year smoothed time series of the percent frequency and average wind speed WS of 850 mb southwesterly winds over Barrow for February and November (1965-1995). Corresponding thin lines are linear fits to monthly values. Plot legends give the 30-year change in frequency and speed based on the respective regressions. The confidence level of each fit is given in parentheses.
In other words, variations in western Arctic temperatures during the cold season are associated with cloud-radiative effects that in turn relate to advective processes. While not a direct consequence of greenhouse warming, the changes may relate indirectly to global warming through physical teleconnections that link the Arctic to the tropical and north Pacific. Warmer conditions at Barrow prevail when cyclonic activity increases in the north Pacific resulting in the advection of clouds northward. If instead, outflow from anticyclones centered in the Beaufort Sea is dominant, colder, drier air influences the continental regions to the south. Because GCMs do not always simulate the positions and/or intensities of the Aleutian Low, Siberian Anticyclone or Beaufort Sea anticyclone correctly, and these are primary centers of synoptic activity in the region, predictions of Arctic climate based on such models must be viewed with caution. Moreover, the teleconnections between tropical and polar regions are not yet understood fully.REFERENCE
Stone , R.S., Variations in Western Arctic Temperatures in Response to Cloud-radiative and Synoptic-scale Influences, J. Geophys. Res., 102(D18),21,769-21,776,1997.
RELATED LINKS
Instrumental Climate History for Alaska
ARM - North Slope of Alaska/Adjacent Arctic Ocean Site
The Alaska Climate Research Center
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