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This paper describes work to improve the understanding of the broad range of factors affecting the occurrence of flooding in Barrow, Alaska, using as a basis the series of extreme events that have affected the community over the past 50 years. A numerical weather prediction model and a storm surge inundation model have been applied to the 21 case studies identified in National Weather Service data as high wind events. Based on this simulation work flow, a reduced-form model that adequately describes the flooding response has been developed. Specifically, it was found that when wind is forecast to be greater than 13 m s-1 (30 mph) for at least 20 h, this is the most accurate predictor of the possibility of damaging flood. It was found that wind direction, the magnitude of fetch to the sea ice edge (when present), and maximum wind speed were in contrast relatively small contributors to the likelihood of flooding. [ABSTRACT FROM AUTHOR]

An intensive approach to Barrow, Alaska's adaptations to climate change and variability during recent decades suggests reconsideration of the interconnected roles of science, policy, and decision-making structures. First, profound uncertainties are inherent in unique interactions among the many natural and human factors affecting Barrow's vulnerability. Science cannot significantly reduce these uncertainties through extensive approaches, but intensive approaches can reconstruct and update local trends, clarify the underlying dynamics, and harvest experience for policy purposes. Second, sound policies to reduce Barrow's vulnerability to coastal erosion and flooding must incorporate these profound uncertainties and the multiple values of the community. Minimizing vulnerability to climate change is only one of the community's interests, and must compete with other interests for limited time, attention, funds and other resources. Third, the community itself is in the best position to understand its own context, to decide on sound policies, and to take responsibility for those decisions. In short, local context matters in science, policy, and decision-making structures for adaptation to climate change and variability. Overall, cognitive constraints may be the most important human dimension of climate change. Factoring the global problem into more tractable local problems would make the most of our cognitive capacity. [ABSTRACT FROM AUTHOR]

The coastal geography of Barrow, Alaska, makes the city vulnerable to weather events that cause flooding and erosion. This study uses the self-organizing map (SOM) algorithm, an unsupervised learning process that codifies large, multivariate datasets onto a 2-dimensional array, or map, to study large-scale circulation patterns associated with temperature and high wind extremes at Barrow. The analysis first uses the SOM algorithm to produce an automated 55 yr synoptic climatology of daily sea level pressure patterns for the western Arctic for August to November, when the area is potentially ice free. The results are in agreement with previous Arctic climatologies, showing the Aleutian Low to be dominant in southern Alaska, and high pressure prevalent over the Beaufort and Chukchi Seas. The SOM algorithm is then used to study circulation patterns associated with temperature and high wind extremes at Barrow. These results show that high winds are associated with patterns containing a strong pressure gradient between the Aleutian Low and the Beaufort and Chukchi Seas and also with patterns that contain a low pressure system to the north of Barrow. High (low) air temperature extreme anomalies are associated with patterns that produce strong, southerly (northerly) air flow at Barrow. This study demonstrates the utility of using SOMs to investigate the relationship between local weather conditions and large-scale patterns. This approach can be applied to future global climate model (GCM) simulations to investigate the impact of changes in large-scale circulation patterns to local extreme events. [ABSTRACT FROM AUTHOR]

The Beaufort–Chukchi cyclones of October 1963 and August 2000 produced the highest winds ever recorded in Barrow, Alaska. In both cases, winds of 25 m s[sup -1] were observed with gusts unofficially reported at 33 m s[sup -1] . The October 1963 storm caused significant flooding, contaminated drinking water, and interrupted power supplies. The August 2000 storm caused the wreck of a $6 million dredge, and removed roofs from 40 buildings. Both storms were unusual in that they tracked eastward from the East Siberian Sea into the Chukchi and Beaufort Seas, rather than following a more typical northward track into the Arctic Ocean. This paper addresses, through modeling and analysis, the development processes of these two storms. The October 1963 system was a long-lived, warm core, zonally elongated cyclone that traversed around the Arctic basin through the Canadian Archipelago. The August 2000 system was an open-wave cyclone that dissipated rapidly into a weak, cold core eddy in the Alaskan sector of the Beaufort Sea. Approximating the contributions to development using terms in a quasigeostrophic omega equation, it was found that both storms were characterized by the increasing importance of the convergence of the Q vector (representing differential vorticity advection and thermal advection) in the midtroposphere, at the expense of forcing by the turbulent fluxes of heat, moisture, and momentum in the boundary layer. However, the influence of surface turbulent fluxes in the early stages of development was important, particularly for the August 2000 cyclone, which passed over an extensive coastal lead in the East Siberian Sea. This study concludes that the observed retreat in western Arctic ice cover is unlikely to be an important contributor to increasing cyclonic activity in the region, but that ice retreat north of Eurasia could have an impact. [ABSTRACT FROM AUTHOR]

Experiments have been conducted with a regional climate model to indicate the conditions required to generate preferred regions of frontal activity in the Alaskan region. Several objective methods of frontal identification were first investigated. It was found that· the vertical component of relative vorticity,· a thermal front parameter -&nablaB;|&nablaB;T[sub 850] | · n, where T[sub 850] is the 850-hPa temperature and n is a unit vector in the direction of the 850-hPa temperature gradient, and· a parameter derived from the Q vector as a measure of vertical motionwere useful in combination to determine the occurrence of fronts. The preferred locations for frontal activity were located to the southern side of the eastern Brooks Range and over the Alaska Range. These diagnostics were then used to characterize frontal frequency in a series of experiments removing topographic and vegetation contrasts. It was found that the removal of the treeline contrast and its associated heating gradient had a small effect on frontal frequency in the immediate vicinity of the tree line, but that the largest impact was in response to the removal of topography, greatly reducing frontal frequency. The coastal contrast was found to have a limited role in synoptic frontal activity in the Alaskan region. [ABSTRACT FROM AUTHOR]

Mosses dominate the surface cover in high northern latitudes and have the potential to play a key role in modifying the thermal and hydrologic regime of Arctic soils. These modifications in turn feed back to influence surface energy exchanges and hence may affect regional climate. However, mosses are poorly represented in models of the land surface. In this study the NCAR Land Surface Model (LSM) was modified in two ways. First, additional soil texture types including mosses and lichens were added to more realistically represent northern soils. Second, the LSM was also modified so that a different soil texture type could be specified for each layer. Several experiments were performed using climate data from an Arctic tundra site in 1995. The model was run for a homogeneous loam soil column and then also for columns that included moss, lichen, peat, and sand. The addition of a surface layer of moss underlain by peat and loam had a substantial impact on modeled surface processes. First, moss acted as an insulative layer producing cooler summer temperatures (6.9°C lower at 0.5 m) and warmer winter temperatures (2.3°C higher at 0.5 m) when compared with a homogenous loam soil column. Second, a soil column with a moss surface had a greater surface infiltration, leading to greater storage of soil moisture in lower layers when compared with a homogeneous loam column. Last, moss modulated the surface energy exchanges by decreasing soil heat flux (57% in July) and increasing turbulent fluxes of heat (67% in July) and moisture (15% in July). Mosses were also more effective contributors to total latent heating than was a bare loam surface. These results suggest that the addition of moss and the ability to prescribe different soil textures for different soil layers result in a more plausible distribution of heat and water within the column and that these modifications should be incorporated into regional and global climate models. [ABSTRACT FROM AUTHOR]

Biome differences in surface energy balance strongly affect climate. However, arctic vegetation is considered sufficiently uniform that only a single arctic land surface type is generally used in climate models. Field measurements in northern Alaska show large differences among arctic ecosystem types in summer energy absorption and partitioning. Simulations with the Arctic Regional Climate System Model demonstrate that these variations in land surface parameters and ecological processes cause variation in surface fluxes that is sufficiently large to affect the regional climate. Plausible changes in arctic vegetation in response to high-latitude warming would feed back positively to local summer warming. This local warming could extend into the boreal zone. Climate feedbacks that operate during the growing season are particularly likely to impact vegetation and ecosystem properties. These field and model results suggest that vegetation changes within a biome could be climatically important and warrant consideration in regional climate modeling. [ABSTRACT FROM AUTHOR]