Human use of land has transformed ecosystem pattern and process across most of the terrestrial biosphere, a global change often described as historically recent and potentially catastrophic for both humanity and the biosphere. Interdisciplinary paleoecological, archaeological, and historical studies challenge this view, indicating that land use has been extensive and sustained for millennia in some regions and that recent trends may represent as much a recovery as an acceleration. Here we synthesize recent scientific evidence and theory on the emergence, history, and future of land use as a process transforming the Earth System and use this to explain why relatively small human populations likely caused widespread and profound ecological changes more than 3,000 y ago, whereas the largest and wealthiest human populations in history are using less arable land per person every decade. Contrasting two spatially explicit global reconstructions of land-use history shows that reconstructions incorporating adaptive changes in land-use systems over time, including land-use intensification, offer a more spatially detailed and plausible assessment of our planet's history, with a biosphere and perhaps even climate long ago affected by humans. Although land-use processes are now shifting rapidly from historical patterns in both type and scale, integrative global land-use models that incorporate dynamic adaptations in human-environment relationships help to advance our understanding of both past and future land-use changes, including their sustainability and potential global effects.Anthropocene | environmental history | holocene | niche construction | agriculture

Small changes in the ways that the ocean transports heat to the overlying ice cover could have a substantial effect on future changes in Arctic ice cover.

The connection between sea ice variability and cloud cover over the Arctic seas during autumn is investigated by analyzing the 40-yr ECMWF Re-Analysis (ERA-40) products and the Television and Infrared Observation Satellite (TIROS) Operational Vertical Sounder (TOVS) Polar Pathfinder satellite datasets. It is found that cloud cover variability near the sea ice margins is strongly linked to sea ice variability. Sea ice retreat is linked to a decrease in low-level cloud amount and a simultaneous increase in midlevel clouds. This pattern is apparent in both data sources. Changes in cloud cover can be explained by changes in the atmospheric temperature structure and an increase in near-surface temperatures resulting from the removal of sea ice. The subsequent decrease in static stability and deepening of the atmospheric boundary layer apparently contribute to the rise in cloud level. The radiative effect of this change is relatively small, as the direct radiative effects of cloud cover changes are compensated for by changes in the temperature and humidity profiles associated with varying ice conditions.

The response of tropical Pacific SST to increased atmospheric CO2 concentration is reexamined with a new focus on the latitudinal SST gradient. Available evidence, mainly from climate models, suggests that an important tropical SST fingerprint to global warming is an enhanced equatorial warming relative to the subtropics. This enhanced equatorial warming provides a fingerprint of SST response more robust than the traditionally studied El Niño–like response, which is characterized by the zonal SST gradient. Most importantly, the mechanism of the enhanced equatorial warming differs fundamentally from the El Niño–like response; the former is associated with surface latent heat flux, shortwave cloud forcing, and surface ocean mixing, while the latter is associated with equatorial ocean upwelling and wind-upwelling dynamic ocean–atmosphere feedback.

The simulation of Arctic cloud cover and the sensitivity of Arctic climate to cloud changes are investigated using an atmosphere-mixed-layer ocean GCM (GENESIS2). The model is run with and without changes in three-dimensional cloud fraction under 2 ϫ CO 2 radiative forcing. This model was chosen in part because of its relatively successful representation of modern Arctic cloud cover, a trait attributable to the parameterized treatment of mixed-phase microphysics. Simulated modern Arctic cloud fraction is insensitive to model biases in surface boundary conditions (SSTs and sea ice distribution), but the modeled Arctic climate is sensitive to high-frequency cloud variability. When forced with increased CO 2 the model generally simulates more (less) vertically integrated cloudiness in high (low) latitudes. In the simulation without cloud feedbacks, cloud fraction is fixed at its modern control value at all grid points and all levels while CO 2 is doubled. Compared with this fixed-cloud experiment, the simulated cloud changes enhance greenhouse warming at all latitudes, accounting for one-third of the global warming signal. This positive feedback is most pronounced in the Arctic, where approximately 40% of the warming is due to cloud changes. The strong cloud feedback in the Arctic is caused not only by local processes but also by cloud changes in lower latitudes, where positive top-of-the-atmosphere cloud radiative forcing anomalies are larger. The extra radiative energy gained in lower latitudes is transported dynamically to the Arctic via moist static energy flux convergence. The results presented here demonstrate the importance of remote impacts from low and midlatitudes for Arctic climate change.

The influence of the Laurentian Great Lakes on climate is assessed by comparing two decade-long simulations, with the lakes either included or excluded, using the Abdus Salam International Centre for Theoretical Physics Regional Climate Model, version 4. The Great Lakes dampen the variability in near-surface air temperature across the surrounding region while reducing the amplitude of the diurnal cycle and annual cycle of air temperature. The impacts of the Great Lakes on the regional surface energy budget include an increase (decrease) in turbulent fluxes during the cold (warm) season and an increase in surface downward shortwave radiation flux during summer due to diminished atmospheric moisture and convective cloud amount. Changes in the hydrologic budget due to the presence of the Great Lakes include increases in evaporation and precipitation during October–March and decreases during May–August, along with springtime reductions in snowmelt-related runoff. Circulation responses consist of a regionwide decrease in sea level pressure in autumn–winter and an increase in summer, with enhanced ascent and descent in the two seasons, respectively. The most pronounced simulated impact of the Great Lakes on synoptic systems traversing the basin is a weakening of cold-season anticyclones.

Seasonal predictions of Arctic sea ice have typically been based on statistical regression models or on results from ensemble ice model forecasts driven by historical atmospheric forcing. However, in the rapidly changing Arctic environment, the predictability characteristics of summer ice cover could undergo important transformations. Here global coupled climate model simulations are used to assess the inherent predictability of Arctic sea ice conditions on seasonal to interannual timescales within the Community Climate System Model, version 3. The role of preconditioning of the ice cover versus intrinsic variations in determining sea ice conditions is examined using ensemble experiments initialized in January with identical ice-ocean-terrestrial conditions. Assessing the divergence among the ensemble members reveals that sea ice area exhibits potential predictability during the first summer and for winter conditions after a year. The ice area exhibits little potential predictability during the spring transition season. Comparing experiments initialized with different mean ice conditions indicates that ice area in a thicker sea ice regime generally exhibits higher potential predictability for a longer period of time. In a thinner sea ice regime, winter ice conditions provide little ice area predictive capability after approximately 1 year. In all regimes, ice thickness has high potential predictability for at least 2 years.

Projected changes in lake-effect snowfall by the mid-and late twenty-first century are explored for the Laurentian Great Lakes basin. Simulations from two state-of-the-art global climate models within phase 5 of the Coupled Model Intercomparison Project (CMIP5) are dynamically downscaled according to the representative concentration pathway 8.5 (RCP8.5). The downscaling is performed using the Abdus Salam International Centre for Theoretical Physics (ICTP) Regional Climate Model version 4 (RegCM4) with 25-km grid spacing, interactively coupled to a one-dimensional lake model. Both downscaled models produce atmospheric warming and increased cold-season precipitation. The Great Lakes' ice cover is projected to dramatically decline and, by the end of the century, become confined to the northern shallow lakeshores during mid-to-late winter. Projected reductions in ice cover and greater dynamically induced wind fetch lead to enhanced lake evaporation and resulting total lake-effect precipitation, although with increased rainfall at the expense of snowfall. A general reduction in the frequency of heavy lake-effect snowstorms is simulated during the twenty-first century, except with increases around Lake Superior by the midcentury when local air temperatures still remain low enough for wintertime precipitation to largely fall in the form of snow. Despite the significant progress made here in elucidating the potential future changes in lake-effect snowstorms across the Great Lakes basin, further research is still needed to downscale a larger ensemble of CMIP5 model simulations, ideally using a higher-resolution, nonhydrostatic regional climate model coupled to a threedimensional lake model.