K. E. McCusker

The reversibility of sea ice loss in a state-of-the-art climate model

Rapid Arctic sea ice retreat has fueled speculation about the possibility of threshold (or ‘tipping point’) behavior and irreversible loss of the sea ice cover. We test sea ice reversibility within a state-of-the-art atmosphere–ocean global climate model by increasing atmospheric carbon dioxide until the Arctic Ocean becomes ice-free throughout the year and subsequently decreasing it until the initial ice cover returns. Evidence for irreversibility in the form of hysteresis outside the envelope of natural variability is explored for the loss of summer and winter ice in both hemispheres. We find no evidence of irreversibility or multiple ice-cover states over the full range of simulated sea ice conditions between the modern climate and that with an annually ice-free Arctic Ocean. Summer sea ice area recovers as hemispheric temperature cools along a trajectory that is indistinguishable from the trajectory of summer sea ice loss, while the recovery of winter ice area appears to be slowed due to the long response times of the ocean near the modern winter ice edge. The results are discussed in the context of previous studies that assess the plausibility of sea ice tipping points by other methods. The findings serve as evidence against the existence of threshold behavior in the summer or winter ice cover in either hemisphere.

Inability of stratospheric sulfate aerosol injections to preserve the West Antarctic Ice Sheet

Injection of sulfate aerosols into the stratosphere has the potential to reduce the climate impacts of global warming, including sea level rise (SLR). However, changes in atmospheric and oceanic circulation that can significantly influence the rate of basal melting of Antarctic marine ice shelves and the associated SLR have not previously been considered. Here we use a fully coupled global climate model to investigate whether rapidly increasing stratospheric sulfate aerosol concentrations after a period of global warming could preserve Antarctic ice sheets by cooling subsurface ocean temperatures. We contrast this climate engineering method with an alternative strategy in which all greenhouse gases (GHG) are returned to preindustrial levels. We find that the rapid addition of a stratospheric aerosol layer does not effectively counteract surface and upper level atmospheric circulation changes caused by increasing GHGs, resulting in continued upwelling of warm water in proximity of ice shelves, especially in the vicinity of the already unstable Pine Island Glacier in West Antarctica. By contrast, removal of GHGs restores the circulation, yielding relatively cooler subsurface ocean temperatures to better preserve West Antarctica.

Consistency and discrepancy in the atmospheric response to Arctic sea-ice loss across climate models

The decline of Arctic sea ice is an integral part of anthropogenic climate change. Sea-ice loss is already having a significant impact on Arctic communities and ecosystems. Its role as a cause of climate changes outside of the Arctic has also attracted much scientific interest. Evidence is mounting that Arctic sea-ice loss can affect weather and climate throughout the Northern Hemisphere. The remote impacts of Arctic sea-ice loss can only be properly represented using models that simulate interactions among the ocean, sea ice, land and atmosphere. A synthesis of six such experiments with different models shows consistent hemispheric-wide atmospheric warming, strongest in the mid-to-high-latitude lower troposphere; an intensification of the wintertime Aleutian Low and, in most cases, the Siberian High; a weakening of the Icelandic Low; and a reduction in strength and southward shift of the mid-latitude westerly winds in winter. The atmospheric circulation response seems to be sensitive to the magnitude and geographic pattern of sea-ice loss and, in some cases, to the background climate state. However, it is unclear whether current-generation climate models respond too weakly to sea-ice change. We advocate for coordinated experiments that use different models and observational constraints to quantify the climate response to Arctic sea-ice loss.Changes in Northern Hemisphere atmospheric temperature, pressure patterns and winds emerge as a consistent response to Arctic sea-ice loss in six coupled climate models.

Remarkable separability of circulation response to Arctic sea ice loss and greenhouse gas forcing

Arctic sea ice loss may influence midlatitude climate by changing large-scale circulation. The extent to which climate change can be understood as greenhouse gas-induced changes that are modulated by this loss depends on how additive the responses to the separate influences are. A novel sea ice nudging methodology in a fully coupled climate model reveals that the separate effects of doubled atmospheric carbon dioxide (CO2) concentrations and associated Arctic sea ice loss are remarkably additive and insensitive to the mean climate state. This separability is evident in several fields throughout most of the year, from hemispheric to synoptic scales. The extent to which the regional response to sea ice loss sometimes agrees with and sometimes cancels the response to CO2 is quantified. The separability of the responses might provide a means to better interpret the diverse array of modeling and observational studies of Arctic change and influence.

Tiling soil textures for terrestrial ecosystem modelling via clustering analysis: a case study with CLASS-CTEM (version 2.1)

We investigate the application of clustering algorithms to represent sub-grid scale variability in soil texture for use in a global-scale terrestrial ecosystem model. Our model, the coupled Canadian Land Surface Scheme – Canadian Terrestrial Ecosystem Model (CLASS-CTEM), is typically implemented at a coarse spatial resolution (approximately 2.8× 2.8) due to its use as the land surface component of the Canadian Earth System Model (CanESM). CLASS-CTEM can, however, be run with tiling of the land surface as a means to represent sub-grid heterogeneity. We first determined that the model was sensitive to tiling of the soil textures via an idealized test case before attempting to cluster soil textures globally. To cluster a high-resolution soil texture dataset onto our coarse model grid, we use two linked algorithms – the Ordering Points to Identify the Clustering Structure (OPTICS) algorithm (Ankerst et al., 1999; Daszykowski et al., 2002) and the algorithm of (Sander et al., 2003) – to provide tiles of representative soil textures for use as CLASS-CTEM inputs. The clustering process results in, on average, about three tiles per CLASS-CTEM grid cell with most cells having four or less tiles. Results from CLASS-CTEM simulations conducted with the tiled inputs (Cluster) versus those using a simple grid-mean soil texture (Gridmean) show CLASS-CTEM, at least on a global scale, is relatively insensitive to the tiled soil textures; however, differences can be large in arid or peatland regions. The Cluster simulation has generally lower soil moisture and lower overall vegetation productivity than the Gridmean simulation except in arid regions where plant productivity increases. In these dry regions, the influence of the tiling is stronger due to the general state of vegetation moisture stress which allows a single tile, whose soil texture retains more plant-available water, to yield much higher productivity. Although the use of clustering analysis appears promising as a means to represent sub-grid heterogeneity, soil textures appear to be reasonably represented for global-scale simulations using a simple gridmean value.

High-Latitude Dynamics of Atmosphere–Ice–Ocean Interactions

The workshop on Dynamics of Atmosphere–Ice–Ocean Interactions in the High Latitudes attracted 90 scientists who met to 1) identify challenges in polar prediction, 2) explore our understanding of the coupled climate system in the high latitudes, and 3) identify research priorities to improve our knowledge and predictive capabilities. We summarize the workshop discussions for four main themes.