Towards quantifying the increasing role of oceanic heat in sea ice loss in the new Arctic

The loss of Arctic sea ice has emerged as a leading signal of global warming. This, together with acknowledged impacts on other components of the Earth system, has led to the term “the new Arctic.” Global coupled climate models predict that ice loss will continue through the twenty-first century, with implications for governance, economics, security, and global weather. A wide range in model projections reflects the complex, highly coupled interactions between the polar atmosphere, ocean, and cryosphere, including teleconnections to lower latitudes. This paper summarizes our present understanding of how heat reaches the ice base from the original sources—inflows of Atlantic and Pacific Water, river discharge, and summer sensible heat and shortwave radiative fluxes at the ocean/ice surface—and speculates on how such processes may change in the new Arctic. The complexity of the coupled Arctic system, and the logistic and technological challenges of working in the Arctic Ocean, require a coordinated interdisciplinary and international program that will not only improve understanding of this critical component of global climate but will also provide opportunities to develop human resources with the skills required to tackle related problems in complex climate systems. We propose a research strategy with components that include 1) improved mapping of the upper- and middepth Arctic Ocean, 2) enhanced quantification of important process, 3) expanded long-term monitoring at key heat-flux locations, and 4) development of numerical capabilities that focus on parameterization of heat-flux mechanisms and their interactions.publishedVersio

Identifying uncertainties in Arctic climate change projections

Wide ranging climate changes are expected in the Arctic by the end of the 21st century, but projections of the size of these changes vary widely across current global climate models. This variation represents a large source of uncertainty in our understanding of the evolution of Arctic climate. Here we systematically quantify and assess the model uncertainty in Arctic climate changes in two CO2 doubling experiments: a multimodel ensemble (CMIP3) and an ensemble constructed using a single model (HadCM3) with multiple parameter perturbations (THC-QUMP). These two ensembles allow us to assess the contribution that both structural and parameter variations across models make to the total uncertainty and to begin to attribute sources of uncertainty in projected changes. We find that parameter uncertainty is an major source of uncertainty in certain aspects of Arctic climate. But also that uncertainties in the mean climate state in the 20th century, most notably in the northward Atlantic ocean heat transport and Arctic sea ice volume, are a significant source of uncertainty for projections of future Arctic change. We suggest that better observational constraints on these quantities will lead to significant improvements in the precision of projections of future Arctic climate change

Towards quantifying the increasing role of oceanic heat in sea ice loss in the new Arctic

The loss of Arctic sea ice has emerged as a leading signal of global warming. This, together with acknowledged impacts on other components of the Earth system, has led to the term “the new Arctic.” Global coupled climate models predict that ice loss will continue through the twenty-first century, with implications for governance, economics, security, and global weather. A wide range in model projections reflects the complex, highly coupled interactions between the polar atmosphere, ocean, and cryosphere, including teleconnections to lower latitudes. This paper summarizes our present understanding of how heat reaches the ice base from the original sources—inflows of Atlantic and Pacific Water, river discharge, and summer sensible heat and shortwave radiative fluxes at the ocean/ice surface—and speculates on how such processes may change in the new Arctic. The complexity of the coupled Arctic system, and the logistic and technological challenges of working in the Arctic Ocean, require a coordinated interdisciplinary and international program that will not only improve understanding of this critical component of global climate but will also provide opportunities to develop human resources with the skills required to tackle related problems in complex climate systems. We propose a research strategy with components that include 1) improved mapping of the upper- and middepth Arctic Ocean, 2) enhanced quantification of important process, 3) expanded long-term monitoring at key heat-flux locations, and 4) development of numerical capabilities that focus on parameterization of heat-flux mechanisms and their interactions

Near-term climate change:Projections and predictability

This chapter assesses the scientific literature describing expectations for near-term climate (present through mid-century). Unless otherwise stated, ‘near-term’ change and the projected changes below are for the period 2016-2035 relative to the reference period 1986-2005. Atmospheric composition (apart from CO2; see Chapter 12) and air quality projections through to 2100 are also assessed. Decadal Prediction. The nonlinear and chaotic nature of the climate system imposes natual limits on the extent to which skilful predictions of climate statistics may be made. M.del-based ‘predictability’ studies, which probe these limits and investigate the physical mechanisms involved, support the potential for the skilful prediction of annual to decadal average temperature and, to a lesser extent precipitation. Predictions for averages of temperature, over large regions of the planet and for the global mean, exhibit positive skill when verified against observations for forecast periods up to ten years (high confidence). Predictions of precipitation over some land areas also exhibit positive skill. Decadal prediction is a new endeavour in climate science. The level of quality for climate predictions of annual to decadal average quantities is assessed from the past performance of initialized predictions and non-initialized simulations. {11.2.3, Figures 11.3 and 11.4}. In current results, observation-based initialization is the dominant contributor to the skill of predictions of annual mean temperature for the first few years and to the skill of predictions of the global mean surface temperature and the temperature over the North Atlantic, regions of the South Pacific and the tropical Indian Ocean for longer periods (high confidence)