Predicting September sea ice: Ensemble skill of the SEARCH Sea Ice Outlook 2008–2013

Since 2008, the Study of Environmental Arctic Change Sea Ice Outlook has solicited predictions of September sea-ice extent from the Arctic research community. Individuals and teams employ a variety of modeling, statistical, and heuristic approaches to make these predictions. Viewed as monthly ensembles each with one or two dozen individual predictions, they display a bimodal pattern of success. In years when observed ice extent is near its trend, the median predictions tend to be accurate. In years when the observed extent is anomalous, the median and most individual predictions are less accurate. Statistical analysis suggests that year-to-year variability, rather than methods, dominate the variation in ensemble prediction success. Furthermore, ensemble predictions do not improve as the season evolves. We consider the role of initial ice, atmosphere and ocean conditions, and summer storms and weather in contributing to the challenge of sea-ice prediction

Sleeping more as a way to lose weight

Caloric consumption in a society with readily available food is likely to be approximately proportional to the number of hours of being awake. Thus, replacing 1 h of inactive wakefulness (e.g. watching TV), with sleeping is likely to result in a substantial reduction in caloric intake. Calculations are presented to illustrate the possible benefits of such a switch on weight reduction.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75728/1/j.1467-789X.2006.00262.x.pd

Predicting September sea ice: Ensemble skill of the SEARCH Sea Ice Outlook 2008-2013

Abstract Since 2008, the Study of Environmental Arctic Change Sea Ice Outlook has solicited predictions of September sea-ice extent from the Arctic research community. Individuals and teams employ a variety of modeling, statistical, and heuristic approaches to make these predictions. Viewed as monthly ensembles each with one or two dozen individual predictions, they display a bimodal pattern of success. In years when observed ice extent is near its trend, the median predictions tend to be accurate. In years when the observed extent is anomalous, the median and most individual predictions are less accurate. Statistical analysis suggests that year-to-year variability, rather than methods, dominate the variation in ensemble prediction success. Furthermore, ensemble predictions do not improve as the season evolves. We consider the role of initial ice, atmosphere and ocean conditions, and summer storms and weather in contributing to the challenge of sea-ice prediction. Key Points Analysis of Sea Ice Outlook contributions 2008-2013 shows bimodal success Years when observations depart from trend are hard to predict despite preconditioning Yearly conditions dominate variations in ensemble prediction success

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

Antarctic Climate Response to Stratospheric Ozone Depletion in a Fine Resolution Ocean Climate Model

We investigate the impact of stratospheric ozone depletion on Antarctic climate, paying particular attention to the question of whether eddy parameterizations in the ocean fundamentally alter the results. This is accomplished by contrasting two versions of the Community Climate System Model (version 3.5), one at 0.1° ocean and sea ice resolution and the other at 1° with parameterized ocean eddies. At both resolutions, pairs of integrations are performed: one with high (1960) and one with low (2000) ozone levels. We find that the effect of ozone depletion is to warm the surface and the ocean to a depth of 1000 m and to significantly reduce the sea ice extent. While the ocean warming is somewhat weaker when the eddies are resolved, the total loss of sea ice area is roughly the same in the fine and coarse resolution cases

Antarctic Ocean and Sea Ice Response to Ozone Depletion: A Two-Time-Scale Problem

The response of the Southern Ocean to a repeating seasonal cycle of ozone loss is studied in two coupled climate models and is found to comprise both fast and slow processes. The fast response is similar to the interannual signature of the southern annular mode (SAM) on sea surface temperature (SST), onto which the ozone hole forcing projects in the summer. It comprises enhanced northward Ekman drift, inducing negative summertime SST anomalies around Antarctica, earlier sea ice freeze-up the following winter, and northward expansion of the sea ice edge year-round. The enhanced northward Ekman drift, however, results in upwelling of warm waters from below the mixed layer in the region of seasonal sea ice. With sustained bursts of westerly winds induced by ozone hole depletion, this warming from below eventually dominates over the cooling from anomalous Ekman drift. The resulting slow time-scale response (years to decades) leads to warming of SSTs around Antarctica and ultimately a reduction in sea ice cover year-round. This two-time-scale behavior—rapid cooling followed by slow but persistent warming—is found in the two coupled models analyzed: one with an idealized geometry and the other with a complex global climate model with realistic geometry. Processes that control the time scale of the transition from cooling to warming and their uncertainties are described. Finally the implications of these results are discussed for rationalizing previous studies of the effect of the ozone hole on SST and sea ice extent.United States. National Aeronautics and Space Administration. Modeling, Analysis, and Prediction Program (Grant)National Science Foundation (U.S.) (Frontiers in Earth System Dynamics Project

Arctic climate response to forcing from light-absorbing particles in snow and sea ice in CESM

The presence of light-absorbing aerosol particles deposited on arctic snow and sea ice influences the surface albedo, causing greater shortwave absorption, warming, and loss of snow and sea ice, lowering the albedo further. The Community Earth System Model version 1 (CESM1) now includes the radiative effects of light-absorbing particles in snow on land and sea ice and in sea ice itself. We investigate the model response to the deposition of black carbon and dust to both snow and sea ice. For these purposes we employ a slab ocean version of CESM1, using the Community Atmosphere Model version 4 (CAM4), run to equilibrium for year 2000 levels of CO<sub>2</sub> and fixed aerosol deposition. We construct experiments with and without aerosol deposition, with dust or black carbon deposition alone, and with varying quantities of black carbon and dust to approximate year 1850 and 2000 deposition fluxes. The year 2000 deposition fluxes of both dust and black carbon cause 1–2 °C of surface warming over large areas of the Arctic Ocean and sub-Arctic seas in autumn and winter and in patches of Northern land in every season. Atmospheric circulation changes are a key component of the surface-warming pattern. Arctic sea ice thins by on average about 30 cm. Simulations with year 1850 aerosol deposition are not substantially different from those with year 2000 deposition, given constant levels of CO<sub>2</sub>. The climatic impact of particulate impurities deposited over land exceeds that of particles deposited over sea ice. Even the surface warming over the sea ice and sea ice thinning depends more upon light-absorbing particles deposited over land. For CO<sub>2</sub> doubled relative to year 2000 levels, the climate impact of particulate impurities in snow and sea ice is substantially lower than for the year 2000 equilibrium simulation

VPLanet: The Virtual Planet Simulator

We describe a software package called VPLanet that simulates fundamental aspects of planetary system evolution over Gyr timescales, with a focus on investigating habitable worlds. In this initial release, eleven physics modules are included that model internal, atmospheric, rotational, orbital, stellar, and galactic processes. Many of these modules can be coupled simultaneously to simulate the evolution of terrestrial planets, gaseous planets, and stars. The code is validated by reproducing a selection of observations and past results. VPLanet is written in C and designed so that the user can choose the physics modules to apply to an individual object at runtime without recompiling, i.e., a single executable can simulate the diverse phenomena that are relevant to a wide range of planetary and stellar systems. This feature is enabled by matrices and vectors of function pointers that are dynamically allocated and populated based on user input. The speed and modularity of VPLanet enables large parameter sweeps and the versatility to add/remove physical phenomena to assess their importance. VPLanet is publicly available from a repository that contains extensive documentation, numerous examples, Python scripts for plotting and data management, and infrastructure for community input and future development.Comment: 75 pages, 34 figures, 10 tables, accepted to the Proceedings of the Astronomical Society of the Pacific. Source code, documentation, and examples available at https://github.com/VirtualPlanetaryLaboratory/vplane