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Local and remote impacts of seasonal snow cover on atmospheric circulation have been explored extensively, with observational and modelling efforts focusing on how Eurasian autumn snow-cover variability potentially drives Northern Hemisphere atmospheric circulation via the generation of deep, planetary-scale atmospheric waves. Despite climate modelling advances, models remain challenged to reproduce the proposed sequence of processes by which snow cover can influence the atmosphere, calling into question the robustness of this coupling. Here, we summarize the current level of understanding of snow–atmosphere coupling, and the implications of this interaction under future climate change. Projected patterns of snow-cover variability and altered stratospheric conditions suggest a need for new model experiments to isolate the effect of projected changes in snow on the atmosphere.

Anthropogenic‐aerosol (AA) radiative forcing modulates multidecadal greenhouse radiative forcing. However, decadal climate responses to AA are poorly characterized given AA forcing uncertainty and internal climate variability. This motivates revisiting a recent claim that AA drove a negative trend in the Pacific Decadal Oscillation and an associated cooling influence in the 10–15 years following the late‐1990's El Niño. The average of a 50‐member initial condition ensemble of the second generation Canadian Earth System Model version 2 that was forced only with AA does not exhibit the negative‐Pacific Decadal Oscillation/slowdown response. However, spurious responses of this kind, that are artifacts of subsetting the large ensemble (LE) in a manner consistent with published literature, can readily be found. This illustrates the caution needed in interpreting regional‐ and decadal‐scale responses to AA and suggests that improved characterization of model uncertainty in AA over the recent period is required. Pollution associated with the emission of aerosols from industry and transportation have been considered to be important to explain the long‐term behavior of global mean temperature over the past half century. On shorter timescales of a couple of decades or less, recent work has suggested that these so called anthropogenic aerosols(AAs) have also limited the amount of global warming that has taken place in recent years. The sources and processes associated with AA are highly complex and uncertain, and so we here are revisiting a recent claim that AA played a detectable role in modulating global temperatures in the 10–15 years after the late 1990's El Niño. We use a large number of simulations of the Canadian Earth System Model version 2 that sample the chaotic variability of climate, and this ensemble shows that AA does not lead to a strong signal over this period. However, we show that if we look at smaller samples of this ensemble, a spurious signal can arise that falsely gives the appearance that AA is driving large signals. Although the required ensemble is only available for version 2 of the Canadian Earth System Model, this result suggests that caution is needed in saying that AA has caused recent unexplained trends in the temperature record. The role of anthropogenic aerosols (AA) forcing in driving recent temperature trends is revisited using a large initial condition ensembleIn the CanESM2 model, AA does not greatly impact global temperature trends after the late 1990's period, if enough realizations are sampledThe appearance of AA related trends in smaller subsets of the LE suggests caution is needed in interpreting the role of AA in recent trends

Two coupled climate models, CESM1 and CanESM2, are used to isolate the climate response to Arctic sea ice loss (high‐latitude warming). The sea ice loss and radiative forcing protocols differ between the sets of experiments. This response is compared to the remaining climate change signal, which is dominated by low‐latitude warming. Some aspects of the wintertime circulation response to sea ice loss are remarkably robust: warming over much of the high latitude and midlatitude; weak cooling over eastern Eurasia, strengthening of the Aleutian Low and Siberian High, equatorward intensification of the lower tropospheric winds, and increased precipitation over high latitudes. Pattern scaling separates the parts of the response that scale with low‐latitude warming and with sea ice loss. The thermal response patterns, for both sea ice loss and low‐latitude warming, are similar between the models. However, the circulation response patterns that scale with low‐latitude warming differ between the models. Preliminary evidence shows that these conclusions apply to other models driven by distinctive sea ice loss protocols. Arctic sea ice is melted in two climate models in such a way as to isolate its impact on the atmosphere from the general climate change response. We find that sea ice loss alone generates changes to atmospheric circulation patterns that are consistent between different climate models, but that the remaining signal, dominated by warming in the tropics, depends on the model used. As a result, the full circulation response to climate change remains uncertain. In contrast, the temperature and precipitation responses to both Arctic sea ice loss and tropical warming are consistent between the models. Preliminary results show that these conclusions apply to other models and are not sensitive to the method used to melt the sea ice. Different coupled model atmospheric circulation responses to sea ice loss in isolation are similar in Northern Hemisphere winterThe low‐latitude warming circulation response is model dependentThere often is a tug of war between the response to low‐latitude warming and to sea ice loss

Results of an earlier study suggest that sea ice drift in climate models is unrealistic, and this has undermined confidence in model projections of “long‐term” (i.e., secular) Arctic sea ice loss. We revisit this by analyzing 22 models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5). It is shown that, when consistent temporal sampling is applied, sea ice drift speed in models and observations come into closer agreement than previously suggested. There is still considerable intermodel scatter in climatological drift speed, and we show that much of this likely relates to prescribed parameters in the sea ice models. Since 1979, observations show a long‐term positive trend of annual mean Arctic average sea ice drift speed resulting primarily from sea ice thinning, and most of the CMIP5 models qualitatively reproduce this. The simulated annual mean drift speed trends reflect strong cancellation between winter trends (which are positive in most models and in good agreement with observations) and summer trends (which are negative in most models and in poor agreement with observations). Positive Arctic average drift speed trends do not consistently coincide with positive trends of Fram Strait outflow. The simulated regional relationship between sea ice strength and drift speed changes dramatically as the Arctic transitions from full to partial ice cover, and this “sea ice extent effect” likely influences simulated summer drift speed trends. Altogether, these results highlight aspects in which models show encouraging agreement with observations, while pinpointing aspects in which models require improvement. Sea ice drift in climate models is more realistic than previously suggestedMost models produce realistic long‐term increases in winter Arctic average sea ice drift speedMost models produce long‐term decreases of summer Arctic average drift speed, in poor agreement with observations

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.

Cold weather operability is sometimes a limiting factor in the use of biodiesel blends for transportation. Regional temperature variability can therefore influence biodiesel adoption, with potential economic and environmental implications. This study assesses present and future biodiesel cold weather operability limits in North America according to temperature data from weather stations, atmospheric reanalysis, and global climate models with highest resolution over Ontario, Canada. Future temperature projections using the RCP8.5 climate change scenario show increases in the potential duration for certain seasonal fuel blends. For example, biodiesel blends whose cloud point temperature is −9 °C may expand their duration by 3–7% in North America for nonwinter seasons according to projections for 2040. Cloud point specifications among supply orbits in Ontario increase up to +6 °C during nonwinter seasons, with most increases observed in Fall and Spring. In winter, however, the modeling suggests no change in Ontario cloud point specifications because the coldest temperatures by mid-century are not significantly warmer than the past climate normal according to our climate simulations. This study provides a quantitative analysis on biodiesel usage scenarios under a changing climate, including Ontario region geographic temperature clusters that could prove useful for biodiesel blend-related decision-making.

Given uncertainty in the processes involved in polar amplification, elucidating the role of poleward heat and moisture transport is crucial. The Polar Amplification Model Intercomparison Project (PAMIP) permits robust separation of the effects of sea ice loss from sea surface warming under climate change. We utilize a moist isentropic circulation framework that accounts for moisture transport, condensation, and eddy transport, in order to analyze the circulation connecting the mid‐latitudes and the Arctic. In PAMIP's atmospheric general circulation model experiments, prescribed sea ice loss reduces poleward heat transport (PHT) by warming the returning moist isentropic circulation at high latitudes, while prescribed warming of the ocean surface increases PHT by strengthening the moist isentropic circulation. Inter‐model spread of PHT into the Arctic reflects the tug‐of‐war between sea‐ice and surface‐warming effects. A major conundrum in current climate science is to understand what Arctic changes imply for the climate and environment in mid‐latitude regions. The Polar Amplification Model Intercomparison Project (PAMIP) designed a set of climate model experiments to specifically answer this question in a carefully designed, idealized framework. PAMIP's approach is to separate historic and projected climate change into parts associated with Arctic sea ice loss and ocean surface warming and investigate how these two contributions can influence the atmosphere. To isolate these effects, only models can be used, because, in reality, sea ice loss and ocean surface warming are strongly linked together. This letter focuses on what the PAMIP experiments imply for the transport and redistribution of heat and moisture in the atmosphere. In PAMIP, we learn that Arctic sea ice loss causes the atmosphere to reduce the transport of dry and cold air away from the Arctic while ocean warming causes more transport of moist warm air toward the Arctic. These two effects are in a tug‐of‐war, suggesting that climate change can cause a mix of competing impacts on the global energy transport from the tropics to the Arctic. Sea ice loss exports static energy from the Arctic by warming the equatorward branch of the global mass circulationSea surface warming imports static energy into the Arctic by increasing the mid‐latitude mass transport, overwhelming the sea ice effectThere is more spread amongst models for the effect of sea‐surface warming than for sea ice loss Sea ice loss exports static energy from the Arctic by warming the equatorward branch of the global mass circulation Sea surface warming imports static energy into the Arctic by increasing the mid‐latitude mass transport, overwhelming the sea ice effect There is more spread amongst models for the effect of sea‐surface warming than for sea ice loss

Arctic moisture transport is dominated by planetary‐scale waves in reanalysis. Planetary waves are influenced by localized Sea‐Surface Temperature (SST) features such as the tropical warm pool. Here, an aquaplanet model is used to clarify the link between tropical SST anomalies and Arctic moisture transport. In a zonally uniform setup with no climatological east‐west gradients, Arctic moisture transport is dominated by transient planetary waves, as in reanalysis. Warming tropical SSTs by heating the ocean strengthens Arctic moisture transport, mediated mostly by changes in water vapor rather than eddies. This strengthening occurs whether the tropical warming is zonally uniform or localized. Cooling tropical SSTs weakens Arctic moisture transport; however, unlike warming, the pattern matters, with localized cooling producing stronger transport changes owing to nonlinear feedbacks in the surface energy budget. Thus, the simulations show that localized tropical SST anomalies influence Arctic moisture transport differently than uniform anomalies, but only in cooling scenarios. Northward transport of water vapor strongly influences Arctic climate. Most of the transport is accomplished by atmospheric waves with large east‐west scale extending around the earth. These waves can be generated by warm ocean waters in the western tropical Pacific. Here, a simplified climate model with an ocean‐covered surface is used to clarify the processes linking the tropical ocean and Arctic moisture transport. Arctic transport in the model is accomplished by waves that are similar to observations, suggesting it is a useful tool. Warming the tropical ocean strengthens Arctic transport similarly whether the warming pattern is concentrated in a specific location or spread out equally at all longitudes. The strengthening results mostly from an increase in water vapor arising from an increase in the holding capacity of the atmosphere at warmer temperatures. Cooling the tropical ocean weakens Arctic transport but, unlike warming, cooling concentrated in a specific location weakens the transport more than if it is spread out equally at all longitudes. The different responses arise because ocean temperatures adjust differently to warming vs. cooling. Thus, localized cooling of tropical ocean temperatures appears to be a special case in terms of its influence on moisture transport into the Arctic. Arctic moisture transport is dominated by transient planetary waves in aquaplanet model driven by zonally uniform boundary conditionsTropical sea‐surface temperature anomalies affect Arctic moisture transport mostly via changes in water vaporLocalized tropical perturbations alter Arctic moisture transport more than uniform perturbations for cooling but not warming Arctic moisture transport is dominated by transient planetary waves in aquaplanet model driven by zonally uniform boundary conditions Tropical sea‐surface temperature anomalies affect Arctic moisture transport mostly via changes in water vapor Localized tropical perturbations alter Arctic moisture transport more than uniform perturbations for cooling but not warming

A weak instability mode, associated with phase-locked counterpropagating coastal Kelvin waves in horizontal anticyclonic shear, is found in the semigeostrophic (SG) equations for stratified flow in a channel. This SG instability mode approximates a similar mode found in the Euler equations in the limit in which particle-trajectory slopes are much smaller than f/N,where fis the Coriolis frequency and N> fthe buoyancy frequency. Though weak under normal parameter conditions, this instability mode is of theoretical interest because its existence accounts for the failure of an Arnol’d-type stability theorem for the SG equations. In the opposite limit, in which the particle motion is purely vertical, the Euler equations allow only buoyancy oscillations with no horizontal coupling. The SG equations, on the other hand, allow a physically spurious coastal “mirage wave,” so called because its velocity field vanishes despite a nonvanishing disturbance pressure field. Counterpropagating pairs of these waves can phase-lock to form a spurious “mirage-wave instability.” Closer examination shows that the mirage wave arises from failure of the SG approximations to be self-consistent for trajectory slopes f/N.

Snow albedo feedback (SAF) is important for global climate change, with strong regional impacts over northern continental areas. SAF calculated from the seasonal cycle is a good predictor of SAF in climate change among a suite of coupled climate models. A previous linear decomposition of the simulated total SAF (NET) found 80% was related to the albedo contrast of snow covered and snow‐free land (SNC), and 20% was related to the temperature dependence of snow albedo (TEM). By contrast, recent work using snow cover and surface albedo derived from APP‐x satellite observations found that TEM and SNC contributed almost equally to NET. In the present study, revised estimates of TEM and SNC for northern land areas are calculated for the period 1982–99 using a simplified and reproducible method for comparing SAF in models and observations. The observed NET is −1.11% K−1, of which 69% comes from SNC and 31% from TEM; the approximate additivity of SNC and TEM indicates that these two terms fully explain the total SAF. Regionally, the SNC term dominates equatorward of 65°N, while TEM dominates over the Arctic. The mean of 17 CMIP3 climate models shows NET is 7% larger than observed, caused primarily by a bias in TEM equatorward of 65°N. A newer model (NCAR CCSM4) with improved land surface and snow schemes reproduces observed values of NET and SNC closely. However, TEM in all models examined is 50–100% weaker than observed over the Arctic. There is a strong correlation between SAF in the seasonal cycle and SAF in climate change for all components, but the correlation is weakest for TEM. The TEM term also exhibits a much larger spread in the seasonal cycle than in climate change, which partially explains a discrepancy between previous published studies examining TEM. Snow albedo feedback (SAF) is compared in models and satellite observationsModels closely reproduce observed SAF and its componentsRegional model biases are largest for the albedo‐temperature component of SAF