University of AlaskaFairbanks
University of AlaskaFairbanks
Weingartner T.J.,University of AlaskaFairbanks |
Potter R.A.,University of AlaskaFairbanks |
Stoudt C.A.,University of AlaskaFairbanks |
Dobbins E.L.,University of AlaskaFairbanks |
And 4 more authors.
Journal of Geophysical Research: Oceans | Year: 2017
We used a 5 year time series of transport, temperature, and salinity from moorings at the head of Barrow Canyon to describe seasonal variations and construct a 37 year transport hindcast. The latter was developed from summer/winter regressions of transport against Bering-Chukchi winds. Seasonally, the regressions differ due to baroclinicity, stratification, spatial, and seasonal variations in winds and/or the surface drag coefficients. The climatological annual cycle consists of summer downcanyon (positive and toward the Arctic Ocean) transport of ∼0.45 Sv of warm, freshwaters; fall (October-December) upcanyon transport of ∼-0.1 Sv of cooler, saltier waters; and negligible net winter (January-April) mass transport when shelf waters are saline and near-freezing. Fall upcanyon transports may modulate shelf freezeup, and negligible winter transports could influence winter water properties. Transport variability is largest in fall and winter. Daily transport probability density functions are negatively skewed in all seasons and seasonal variations in kurtosis are a function of transport event durations. The latter may have consequences for shelf-basin exchanges. The climatology implies that the Chukchi shelf circulation reorganizes annually: in summer ∼40% of the summer Bering Strait inflow leaves the shelf via Barrow Canyon, but from fall through winter all of it exits via the western Chukchi or Central Channel. We estimate a mean transport of ∼0.2 Sv; ∼50% less than estimates at the mouth of the canyon. Transport discrepancies may be due to inflows from the Beaufort shelf and the Chukchi shelfbreak, with the latter entering the western side of the canyon. © 2017. American Geophysical Union. All Rights Reserved.
Stefanescu E.R.,State University of New York at Buffalo |
Patra A.K.,State University of New York at Buffalo |
Madankan R.,State University of New York at Buffalo |
Jones M.,New York University |
And 6 more authors.
Journal of Advances in Modeling Earth Systems | Year: 2014
Uncertainty in predictions from a model of volcanic ash transport in the atmosphere arises from uncertainty in both eruption source parameters and the model wind field. In a previous contribution, we analyzed the probability of ash cloud presence using weighted samples of volcanic ash transport and dispersal model runs and a reanalysis wind field to propagate uncertainty in eruption source parameters alone. In this contribution, the probabilistic modeling is extended by using ensemble forecast wind fields as well as uncertain source parameters. The impact on ash transport of variability in wind fields due to unresolved scales of motion as well as model physics uncertainty is also explored. We have therefore generated a weighted, probabilistic forecast of volcanic ash transport with only a priori information, exploring uncertainty in both the wind field and the volcanic source. © 2014. The Authors.
Johnstone J.F.,University of Saskatchewan |
Johnstone J.F.,University of Alaska Fairbanks |
Chapin III F.S.,University of Alaska Fairbanks |
Hollingsworth T.N.,University of AlaskaFairbanks |
And 3 more authors.
Canadian Journal of Forest Research | Year: 2010
In the boreal forests of interior Alaska, feedbacks that link forest soils, fire characteristics, and plant traits havesupported stable cycles of forest succession for the past 6000 years. This high resilience of forest stands to fire disturbanceis supported by two interrelated feedback cycles: (i) interactions among disturbance regime and plant-soil-microbial feedbacks that regulate soil organic layer thickness and the cycling of energy and materials, and (ii) interactions among soil conditions, plant regeneration traits, and plant effects on the environment that maintain stable cycles of forest community composition. Unusual fire events can disrupt these cycles and trigger a regime shift of forest stands from one stability domain to another (e.g., from conifer to deciduous forest dominance). This may lead to abrupt shifts in forest cover in response to changing climate and fire regime, particularly at sites with intermediate levels of moisture availability where stand-scale feedback cycles are only weakly constrained by environmental conditions. However, the loss of resilience in individual stands may foster resilience at the landscape scale, if changes in the landscape configuration of forest cover types feedback to stabilize regional patterns of fire behavior and climate conditions.