Our Common Future Under Climate Change

Research suggests that the Arctic responds to climate change earlier, and with greater intensity, than other components of the earth system, making it a useful barometer for the health of the global environment. Observed changes in the Arctic marine and cryosphere, including increased seasonality, rapid sea ice loss and accelerated melting of the Greenland ice sheet, are consistent with these ideas of �Arctic amplification�. Such changes can produce substantial environmental and societal stress, with regional implications and potentially profound global impacts. �The resulting challenges include accelerated coastal erosion, changing weather patterns and rising sea level. Arctic environmental change can also produce new opportunities, such as expanded resource extraction and shortened shipping routes. Accurate predictions of Arctic environmental change and its global impact are needed to inform the response to these challenges and support planning of future activity. However, current predictions sometimes differ from observed Arctic change, motivating efforts to advance our understanding of the physical processes.

This presentation will provide an overview of our current understanding of some prominent changes in the Arctic ocean and cryosphere. A complex interplay between the physics of the atmosphere, cryosphere and ocean, with the potential for positive feedbacks (such as that between reduced ice cover, reduced albedo and increased absorption of solar radiation, known as the ice-albedo feedback) govern the observed response to climate change. This motivates efforts to establish integrated, interdisciplinary, international programs to advance understanding and, ultimately, improve predictive ability. Sustained, climate-scale Arctic observing represents a critical component of such efforts, and the state of such observing systems and their underlying technologies will thus be briefly reviewed here.

Radiative feedbacks in the Arctic play a key role in determining the energy and moisture budgets both at the surface and top of atmosphere which, in turn, influences the atmospheric and oceanic circulation. The Arctic has experienced dramatic declines in summer sea ice over the past decade which has triggered a series of interconnected responses in the surface energy budget and the atmospheric feedbacks. The Arctic has become warmer, wetter, and cloudier. All of these changes further modulate the radiative fluxes at the surface. Observations indicate that the most pronounced warming occurs during boreal winter, with an increase in Arctic mean temperature of roughly 1K. This warming is associated with a pronounced sea ice loss in boreal summer which increases the evaporation rates (i.e. moisture flux). The resulting increase in water vapor and cloud cover enhances the downward long wave flux at the surface, contributing to earlier melt onset and the delayed autumn freeze up. This study will summarize the importance of these relationships using multiple observational data sets and compare the observed feedback strengths to those simulated in coupled ocean-atmosphere models.

The ecology of the Arctic is changing in response to shifts in the climate system.� Although Arctic species are well adapted to seasonal and diurnal variability in physical conditions, many of the observed climate-driven changes are leading to fundamental shifts in the structure and diversity of biological processes. What happens in both the marine and terrestrial environments has both local and global implications. For example, the tundra is a huge biome extending across 30 degrees latitutde.� Vegetation changes show a complex pattern at larger scales, but overall there has been a rapid increase in woody vegetation (shrubs, trees), changes in phenology and albedo as a consequence of earlier snowmelt, and changes in foodweb structure and trophic interactions.�� Freshwater ecosystems are facing similarly large changes, and the ability of rivers, lakes and wetlands to maintain adequate streamflows, water levels and water quality for ecosystem sustainability is poorly understood.� In the marine environment, there is already compelling evidence of a shift towards an increasingly pelagic system in the absence of summer sea ice.� In both terrestrial and marine ecoystems, extreme events (e.g. winter rain, fire, storm surges) can overturn long-term trends, but there are still insufficient observations to adequately predict the future. I will provide a brief overview of current understanding of how Arctic ecosystems are responding to climate change and variability, and the most important research needs identified during the 3rd International Conference on Arctic Research Planning (ICARP III).�

Some of the largest changes due to climate warming are expected in the Arctic. However, 21st century projections of the magnitude of these changes vary widely in the latest suite of global climate predictions. In addition, several studies point to strong sensitivity of climate projections to multi-parameter space, varying within physically acceptable bounds. Such variations and sensitivities are the source of large uncertainties and limited skill in reconstructions of the past and present Arctic System, and in projections of the future state of this region.�

We introduce a new tool for regional climate modelling, the Regional Arctic System Model (RASM), and�demonstrate its advanced capability in simulating some critical physical processes and feedbacks, which significantly improve model representation of observed seasonal to decadal variability and trends in the sea ice cover.

RASM is a limited-area, fully coupled ice-ocean-atmosphere-land model that uses the Community Earth System Model (CESM) framework. It includes the Weather Research and Forecasting (WRF) model, the LANL Parallel Ocean Program (POP) and Community Ice Model (CICE) and the Variable Infiltration Capacity (VIC) land hydrology model. The ocean and sea ice models used in RASM are regionally configured versions of those used in CESM, while WRF replaces the Community Atmospheric Model (CAM). RASM has recently been upgraded to CICE Version 5.0 (CICE5.0) with (i) the new prognostic salinity thermodynamic model to represent sea ice growth and melt, (ii) a new anisotropic rheology to capture anisotropic sea ice dynamics at the multi-floe scale (of order 2-10km) and (iii) a form drag scheme to more accurately approximate ice-ocean and ice-atmosphere stresses. In addition, a streamflow routing (RVIC) model was recently implemented in RASM to transport the freshwater flux from the land surface to the Arctic Ocean. The model�domain�is configured at an eddy-permitting resolution of 1/12� (or ~9km) for the ice-ocean and 50 km for the atmosphere-land model components.�It covers the entire Northern Hemisphere marine cryosphere, terrestrial drainage to the Arctic Ocean and its major inflow and outflow pathways, with optimal extension into the North Pacific / Atlantic to model the passage of cyclones into the Arctic.�All RASM components are coupled at high frequency (i.e. 20-minute intervals) to allow realistic representation of inertial interactions among the model components.

Model results are presented from both fully coupled and a subset of RASM, where the atmospheric and land components are replaced with prescribed realistic atmospheric reanalysis data for 1948-2009. Seleceted physical processes and resulting feedbacks will be discussed to emphasize the need for high model resultion and fine-tuning of�many present parameterizations of sub-grid physical processes when changing model spatial resolution. We also investigate sensitivity of simulated sea ice states to scale dependence of model parameters controlling ice dynamics, thermodynamics and coupling with the atmosphere and ocean. Finally, we�show that sea ice extent commonly used to evaluate the model skill is not a sufficient model constraint as the modeled sea ice thickness distribution and volume can vary significantly while ice extent remains unchanged.

The climate is changing, which is particularly visible in the Arctic sea ice state. To plan the access to shipping routes, resource extraction, etc. several groups with different interests would like to know the future development of Arctic sea ice coverage.

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Climate scenario simulations with global coupled climate models, contributing to the coupled model intercomparison project phase 5 (CMIP5), are used to exploit possible scenarios for the sea ice distribution under climate change during the coming decades. Their results are also discussed in the IPCC assessment report no. 5 (AR5). More than 30 models take part in the CMIP5 experiments and together they estimate a very large uncertainty range for Arctic sea ice. CMIP5 models simulate the global climate change and their individual strengths differ regionally. Several studies show that if a limited number of CMIP5 models are chosen with respect to their regional strengths, the range of uncertainty decreases considerably for selected variables.

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Within the projects ACCESS (Arctic Climate Change, Economics and Society) and ICE-ARC (Ice, Climate, Economics - Arctic Research on Change) we compare satellite sea ice concentration observations with simulated sea ice concentration of 34 CMIP5 models. The skill of the models varies within the region in the Arctic, the time period of the satellite observation used and the satellite data processing. Thus, we analyse two different satellite derived products over individual regions, which have been discussed as potential sites for resource extractions, as well as the whole Arctic for two different time periods. From this, we select the best four CMIP5 models with regard to the misfit between model and observations. Although the models agree on the general future reduction on sea ice area, they differ in the magnitude of the sea ice decrease and thus the timing of when the Arctic becomes �ice-free�.

The sea ice coverage correlates well with the near surface air temperature in summer and with the position of warm Atlantic water during winter. These correlations exist in the chosen models but with strong differences. For example, the position of the warm Atlantic water entering the Arctic via the Fram Strait and the Barents Sea Opening varies considerably in the four chosen models. Therefore, one reason for the differences in future sea ice estimates from different models is the simulated change of the atmospheric and oceanic northward heat transport into the Arctic.

Different sea ice projections between climate models can be understood not only being due to differences of the sea ice model component, but the model realisation of oceanic and atmospheric northward heat transport.