David A. Bailey

Predicting 21st‐century polar bear habitat distribution from global climate models

Projections of polar bear (Ursus maritimus) sea ice habitat distribution in the polar basin during the 21st century were developed to understand the consequences of anticipated sea ice reductions on polar bear populations. We used location data from satellite- collared polar bears and environmental data (e.g., bathymetry, distance to coastlines, and sea ice) collected from 1985 to 1995 to build resource selection functions (RSFs). RSFs described habitats that polar bears preferred in summer, autumn, winter, and spring. When applied to independent data from 1996 to 2006, the RSFs consistently identified habitats most frequently used by polar bears. We applied the RSFs to monthly maps of 21st-century sea ice concentration projected by 10 general circulation models (GCMs) used in the Intergovern- mental Panel of Climate Change Fourth Assessment Report, under the A1B greenhouse gas forcing scenario. Despite variation in their projections, all GCMs indicated habitat losses in the polar basin during the 21st century. Losses in the highest-valued RSF habitat (optimal habitat) were greatest in the southern seas of the polar basin, especially the Chukchi and Barents seas, and least along the Arctic Ocean shores of Banks Island to northern Greenland. Mean loss of optimal polar bear habitat was greatest during summer; from an observed 1.0 million km 2 in 1985-1995 (baseline) to a projected multi-model mean of 0.32 million km 2 in 2090-2099 (� 68% change). Projected winter losses of polar bear habitat were less: from 1.7 million km 2 in 1985-1995 to 1.4 million km 2 in 2090-2099 (� 17% change). Habitat losses based on GCM multi-model means may be conservative; simulated rates of habitat loss during 1985-2006 from many GCMs were less than the actual observed rates of loss. Although a reduction in the total amount of optimal habitat will likely reduce polar bear populations, exact relationships between habitat losses and population demographics remain unknown. Density and energetic effects may become important as polar bears make long-distance annual migrations from traditional winter ranges to remnant high-latitude summer sea ice. These impacts will likely affect specific sex and age groups differently and may ultimately preclude bears from seasonally returning to their traditional ranges.

Improved Sea Ice Shortwave Radiation Physics in CCSM4: The Impact of Melt Ponds and Aerosols on Arctic Sea Ice*

AbstractThe Community Climate System Model, version 4 has revisions across all components. For sea ice, the most notable improvements are the incorporation of a new shortwave radiative transfer scheme and the capabilities that this enables. This scheme uses inherent optical properties to define scattering and absorption characteristics of snow, ice, and included shortwave absorbers and explicitly allows for melt ponds and aerosols. The deposition and cycling of aerosols in sea ice is now included, and a new parameterization derives ponded water from the surface meltwater flux. Taken together, this provides a more sophisticated, accurate, and complete treatment of sea ice radiative transfer. In preindustrial CO2 simulations, the radiative impact of ponds and aerosols on Arctic sea ice is 1.1 W m−2 annually, with aerosols accounting for up to 8 W m−2 of enhanced June shortwave absorption in the Barents and Kara Seas and with ponds accounting for over 10 W m−2 in shelf regions in July. In double CO2 (2XCO2) ...

Climate Sensitivity of the Community Climate System Model, Version 4

Equilibrium climate sensitivity of the Community Climate System Model, version 4 (CCSM4) is 3.208C for 18 horizontal resolution in each component. This is about a half degree Celsius higher than in the previous version (CCSM3). The transient climate sensitivity of CCSM4 at 18 resolution is 1.728C, which is about 0.28C higher than in CCSM3. These higher climate sensitivities in CCSM4 cannot be explained by the change to a preindustrial baseline climate. This study uses the radiative kernel technique to show that, from CCSM3 to CCSM4, the global mean lapse-rate feedback declines in magnitude and the shortwave cloud feedback increases. These two warming effects are partially canceled by cooling because of slight decreases in the global mean water vapor feedback and longwave cloud feedback from CCSM3 to CCSM4. A new formulation of the mixed layer, slab-ocean model in CCSM4 attempts to reproduce the SST and sea ice climatology from an integration with a full-depth ocean, and it is integrated with a dynamic sea ice model. These new features allow an isolation of the influence of ocean dynamical changes on the climate response when comparing integrations with the slab ocean and full-depth ocean. The transient climate response of the full-depth ocean version is 0.54 of the equilibrium climate sensitivity when estimated with the new slab-ocean model version for both CCSM3 and CCSM4. The authors argue the ratio is the same in both versions because they have about the same zonal mean pattern of change in ocean surface heat flux, which broadly resembles the zonal mean pattern of net feedback strength.

Greenhouse gas mitigation can reduce sea-ice loss and increase polar bear persistence

On the basis of projected losses of their essential sea-ice habitats, a United States Geological Survey research team concluded in 2007 that two-thirds of the world’s polar bears (Ursus maritimus) could disappear by mid-century if business-as-usual greenhouse gas emissions continue. That projection, however, did not consider the possible benefits of greenhouse gas mitigation. A key question is whether temperature increases lead to proportional losses of sea-ice habitat, or whether sea-ice cover crosses a tipping point and irreversibly collapses when temperature reaches a critical threshold. Such a tipping point would mean future greenhouse gas mitigation would confer no conservation benefits to polar bears. Here we show, using a general circulation model, that substantially more sea-ice habitat would be retained if greenhouse gas rise is mitigated. We also show, with Bayesian network model outcomes, that increased habitat retention under greenhouse gas mitigation means that polar bears could persist throughout the century in greater numbers and more areas than in the business-as-usual case. Our general circulation model outcomes did not reveal thresholds leading to irreversible loss of ice; instead, a linear relationship between global mean surface air temperature and sea-ice habitat substantiated the hypothesis that sea-ice thermodynamics can overcome albedo feedbacks proposed to cause sea-ice tipping points. Our outcomes indicate that rapid summer ice losses in models and observations represent increased volatility of a thinning sea-ice cover, rather than tipping-point behaviour. Mitigation-driven Bayesian network outcomes show that previously predicted declines in polar bear distribution and numbers are not unavoidable. Because polar bears are sentinels of the Arctic marine ecosystem and trends in their sea-ice habitats foreshadow future global changes, mitigating greenhouse gas emissions to improve polar bear status would have conservation benefits throughout and beyond the Arctic.

Late-Twentieth-Century Simulation of Arctic Sea Ice and Ocean Properties in the CCSM4

AbstractTo establish how well the new Community Climate System Model, version 4 (CCSM4) simulates the properties of the Arctic sea ice and ocean, results from six CCSM4 twentieth-century ensemble simulations are compared here with the available data. It is found that the CCSM4 simulations capture most of the important climatological features of the Arctic sea ice and ocean state well, among them the sea ice thickness distribution, fraction of multiyear sea ice, and sea ice edge. The strongest bias exists in the simulated spring-to-fall sea ice motion field, the location of the Beaufort Gyre, and the temperature of the deep Arctic Ocean (below 250 m), which are caused by deficiencies in the simulation of the Arctic sea level pressure field and the lack of deep-water formation on the Arctic shelves. The observed decrease in the sea ice extent and the multiyear ice cover is well captured by the CCSM4. It is important to note, however, that the temporal evolution of the simulated Arctic sea ice cover over the...

Twenty-First-Century Arctic Climate Change in CCSM4

AbstractThe authors summarize the twenty-first-century Arctic climate simulated by NCAR’s Community Climate System Model, version 4 (CCSM4). Under a strong radiative forcing scenario, the model simulates a much warmer, wetter, cloudier, and stormier Arctic climate with considerably less sea ice and a fresher Arctic Ocean. The high correlation among the variables composing these changes—temperature, precipitation, cloudiness, sea level pressure (SLP), and ice concentration—suggests that their close coupling collectively represents a fingerprint of Arctic climate change. Although the projected changes in CCSM4 are generally consistent with those in other GCMs, several noteworthy features are identified. Despite more global warming in CCSM4, Arctic changes are generally less than under comparable greenhouse forcing in CCSM3, as represented by Arctic amplification (16% weaker) and the date of a seasonally ice-free Arctic Ocean (20 years later). Autumn is the season of the most pronounced Arctic climate change...

The Influence of Local Feedbacks and Northward Heat Transport on the Equilibrium Arctic Climate Response to Increased Greenhouse Gas Forcing

AbstractThis study uses coupled climate model experiments to identify the influence of atmospheric physics [Community Atmosphere Model, versions 4 and 5 (CAM4; CAM5)] and ocean model complexity (slab ocean, full-depth ocean) on the equilibrium Arctic climate response to an instantaneous CO2 doubling. In slab ocean model (SOM) experiments using CAM4 and CAM5, local radiative feedbacks, not atmospheric heat flux convergence, are the dominant control on the Arctic surface response to increased greenhouse gas forcing. Equilibrium Arctic surface air temperature warming and amplification are greater in the CAM5 SOM experiment than in the equivalent CAM4 SOM experiment. Larger 2 × CO2 radiative forcing, more positive Arctic surface albedo feedbacks, and less negative Arctic shortwave cloud feedbacks all contribute to greater Arctic surface warming and sea ice loss in CAM5 as compared to CAM4. When CAM4 is coupled to an active full-depth ocean model, Arctic Ocean horizontal heat flux convergence increases in resp...

Snow‐albedo feedback and the spring transition in a regional climate system model: Influence of land surface model

Using the Arctic regional climate system model (ARCSYM), we investigate the spring seasonal transition and mechanisms controlling snowmelt over a domain covering the northern half of Alaska. Annual simulations for 1992 comparing the Biosphere-Atmosphere Transfer Scheme (BATS) and the land surface model scheme (LSM) show that the BATS experiment enters the spring transition with respect to the large-scale atmospheric regime approximately one month earlier than observed climate and the LSM experiment transitions a month later than observed, even though the air temperature in the LSM experiment is generally warmer than in the BATS experiment. A more detailed examination reveals that each simulation commences and completes the snowmelt period at about the same time but that the LSM snowmelt is more rapid than in the BATS experiment. Controlling the snowmelt is the initial snowpack depth and the surface energy budget, both of which involve a complex series of feedbacks between shortwave and longwave radiation, cloud, surface turbulent fluxes, and vegetation. The snowmelt over tundra regions dominates the more rapid snowmelt seen in the LSM simulation. It is determined that the most crucial differences between the BATS and the LSM schemes are the partitioning of net ground heat flux between patches of snow and bare ground and the formulation of snow albedo.

Development of an Antarctic Regional Climate System Model. Part I: Sea Ice and Large-Scale Circulation

Abstract A coupled atmosphere–ice regional model previously used for simulations in the Arctic has been implemented in the Antarctic. Three 14-month simulations were performed for 1988–89, with different oceanic specifications. The year 1988 was interesting as there were several sensible heat polynya events in the Cosmonaut Sea region, the investigation of which is the goal of future finer-resolution simulations. Overall, the regional climate model produces reasonable simulations of the Antarctic at 100-km resolution. Root-mean-square errors range from 4 hPa in surface pressure, 4 K in near-surface air temperature, and 3 m s−1 in near-surface winds, to 1 K in air temperature and 2 m s−1 in winds at the 500-hPa level. Tests of the coupled system response to oceanic heat flux suggest that the sea-ice simulation is more sensitive than the atmospheric circulation, but it could be expected that the atmosphere would respond to these changes in sea ice over longer time periods than those of interest here. This s...

Development of an Antarctic Regional Climate System Model. Part II: Station Validation and Surface Energy Balance

Abstract In this, the second part of the analysis of an Antarctic regional climate system model, the model results and analyses are compared to a series of observational data from automated weather stations at a number of Antarctic stations, radiosonde launches, and surface energy balance climatology. The observational analyses show significant biases in comparison with station data, which is attributable in part to the errors in and low resolution of the elevation dataset. This is a factor in model performance also. Further, a dominant factor in the generation of the model biases is the simulation of atmospheric water vapor and cloud. The known “cold” bias in the clear-sky longwave radiation scheme is amply compensated for by excessive cloudiness in many cases. The strong vertical moisture transport contributes to the excessive cloud formation. The biases explored in detail in this paper are common to regional and global simulations of the Antarctic region and highlight areas in which model development s...