Publications

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2014
Li, L, Miller AJ, McClean JL, Eisenman I, Hendershott MC.  2014.  Processes driving sea ice variability in the Bering Sea in an eddying ocean/sea ice model: anomalies from the mean seasonal cycle. Ocean Dynamics. 64:1693-1717.: Springer Berlin Heidelberg   10.1007/s10236-014-0769-7   AbstractWebsite

A fine-resolution (1/10°) ocean/sea ice model configured in the Community Earth System Model framework is compared with observations and studied to determine the basin-scale and local balances controlling the variability of sea ice anomalies from the mean seasonal cycle in the Bering Sea for the time period 1980–1989. The model produces variations in total Bering Sea ice area anomalies that are highly correlated with observations. Surface air temperature, which is specified from reanalysis atmospheric forcing, strongly controls the ice volume variability in this simulation. The thermodynamic ice volume change is dominated by surface energy flux via atmosphere-ice sensible heat flux, except near the southern ice edge where it is largely controlled by ocean-ice heat flux. While thermodynamic processes dominate the variations in ice volume in the Bering Sea on the large scale, dynamic processes are important on the local scale near ice margins (both oceanic and land), where dynamic and thermodynamic ice volume changes have opposite signs and nearly cancel each other. Ice motion is generally consistent with winds driving the flow, except near certain straits in the north where ice motion largely follows ocean currents. Two key climate events, strong ice growth with cold air temperature and northerly wind anomalies in February 1984 and weak ice growth with warm air temperature and southerly wind anomalies in February 1989, are studied here in detail. While the processes controlling the ice changes are generally similar to those in other years, these large events help reveal the characteristic spatial patterns of ice growth/melt and transport anomalies.

Li, L, McClean JL, Miller AJ, Eisenman I, Hendershott MC, Papadopoulos CA.  2014.  Processes driving sea ice variability in the Bering Sea in an eddying ocean/sea ice model: Mean seasonal cycle. Ocean Modelling. 84:51-66.   http://dx.doi.org/10.1016/j.ocemod.2014.09.006   AbstractWebsite

The seasonal cycle of sea ice variability in the Bering Sea, together with the thermodynamic and dynamic processes that control it, are examined in a fine resolution (1/10°) global coupled ocean/sea-ice model configured in the Community Earth System Model (CESM) framework. The ocean/sea-ice model consists of the Los Alamos National Laboratory Parallel Ocean Program (POP) and the Los Alamos Sea Ice Model (CICE). The model was forced with time-varying reanalysis atmospheric forcing for the time period 1970–1989. This study focuses on the time period 1980–1989. The simulated seasonal-mean fields of sea ice concentration strongly resemble satellite-derived observations, as quantified by root-mean-square errors and pattern correlation coefficients. The sea ice energy budget reveals that the seasonal thermodynamic ice volume changes are dominated by the surface energy flux between the atmosphere and the ice in the northern region and by heat flux from the ocean to the ice along the southern ice edge, especially on the western side. The sea ice force balance analysis shows that sea ice motion is largely associated with wind stress. The force due to divergence of the internal ice stress tensor is large near the land boundaries in the north, and it is small in the central and southern ice-covered region. During winter, which dominates the annual mean, it is found that the simulated sea ice was mainly formed in the northern Bering Sea, with the maximum ice growth rate occurring along the coast due to cold air from northerly winds and ice motion away from the coast. South of St Lawrence Island, winds drive the model sea ice southwestward from the north to the southwestern part of the ice-covered region. Along the ice edge in the western Bering Sea, model sea ice is melted by warm ocean water, which is carried by the simulated Bering Slope Current flowing to the northwest, resulting in the S-shaped asymmetric ice edge. In spring and fall, similar thermodynamic and dynamic patterns occur in the model, but with typically smaller magnitudes and with season-specific geographical and directional differences.

2010
Overland, JE, Alheit J, Bakun A, Hurrell JW, Mackas DL, Miller AJ.  2010.  Climate controls on marine ecosystems and fish populations. Journal of Marine Systems. 79:305-315.   10.1016/j.jmarsys.2008.12.009   AbstractWebsite

This paper discusses large-scale climate variability for several marine ecosystems and suggests types of ecosystem responses to climate change. Our analysis of observations and model results for the Pacific and Atlantic Oceans concludes that most climate variability is accounted for by the combination of intermittent 1-2 year duration events, e.g. the cumulative effect of monthly weather anomalies or the more organized El Nino/La Nina, plus broad-band "red noise" intrinsic variability operating at decadal and longer timescales. While ocean processes such as heat storage and lags due to ocean circulation provide some multi-year memory to the climate system, basic understanding of the mechanisms resulting in observed large decadal variability is lacking and forces the adoption of a "stochastic or red noise" conceptual model of low frequency variability at the present time. Thus we conclude that decadal events with rapid shifts and major departures from climatic means will occur, but their timing cannot be forecast. The responses to climate by biological systems are diverse in character because intervening processes introduce a variety of amplifications, time lags, feedbacks, and non-linearities. Decadal ecosystem variability can involve a variety of climate to ecosystem transfer functions. These can be expected to convert red noise of the physical system to redder (lower frequency) noise of the biological response, but can also convert climatic red noise to more abrupt and discontinuous biological shifts, transient climatic disturbance to prolonged ecosystem recovery, and perhaps transient disturbance to sustained ecosystem regimes. All of these ecosystem response characteristics are likely to be active for at least some locations and time periods, leading to a mix of slow fluctuations, prolonged trends, and step-like changes in ecosystems and fish populations in response to climate change. Climate variables such as temperatures and winds can have strong teleconnections (large spatial covariability) within individual ocean basins, but between-basin teleconnections, and potential climate-driven biological synchrony over several decades, are usually much weaker and a highly intermittent function of the conditions prevailing at the time within the adjoining basins. As noted in the recent IPCC 4th Assessment Report, a warming trend of ocean surface layers and loss of regional sea ice is likely before 2030, due to addition of greenhouse gases. Combined with large continuing natural climate variability, this will stress ecosystems in ways that they have not encountered for at least 100s of years. Published by Elsevier B.V.