This paper reviews developments for the Community Land Model, version 4 (CLM4), examines the land surface climate simulation of the Community Climate System Model, version 4 (CCSM4) compared to CCSM3, and assesses new earth system features of CLM4 within CCSM4. CLM4 incorporates a broad set of improvements including additions of a carbon–nitrogen (CN) biogeochemical model, an urban canyon model, and transient land cover and land use change, as well as revised soil and snow submodels. Several aspects of the surface climate simulation are improved in CCSM4. Improvements in the simulation of soil water storage, evapotranspiration, surface albedo, and permafrost that are apparent in offline CLM4 simulations are generally retained in CCSM4. The global land air temperature bias is reduced and the annual cycle is improved in many locations, especially at high latitudes. The global land precipitation bias is larger in CCSM4 because of bigger wet biases in central and southern Africa and Australia. New earth system capabilities are assessed. The present-day air temperature within urban areas is warmer than surrounding rural areas by 1°–2°C, which is comparable to or greater than the change in climate occurring over the last 130 years. The snow albedo feedback is more realistic and the radiative forcing of snow aerosol deposition is calculated as +0.083 W m−2 for present day. The land carbon flux due to land use, wildfire, and net ecosystem production is a source of carbon to the atmosphere throughout most of the historical simulation. CCSM4 is increasingly suited for studies of the role of land processes in climate and climate change.

Motivated by the need to predict how the Arctic atmosphere will change in a warming world, this article summarizes recent advances made by the research consortium NETCARE (Network on Climate and Aerosols: Addressing Key Uncertainties in Remote Canadian Environments) that contribute to our fundamental understanding of Arctic aerosol particles as they relate to climate forcing. The overall goal of NETCARE research has been to use an interdisciplinary approach encompassing extensive field observations and a range of chemical transport, earth system, and biogeochemical models. Several major findings and advances have emerged from NETCARE since its formation in 2013. (1) Unexpectedly high summertime dimethyl sulfide (DMS) levels were identified in ocean water (up to 75 nM) and the overlying atmosphere (up to 1 ppbv) in the Canadian Arctic Archipelago (CAA). Furthermore, melt ponds, which are widely prevalent, were identified as an important DMS source (with DMS concentrations of up to 6 nM and a potential contribution to atmospheric DMS of 20 % in the study area). (2) Evidence of widespread particle nucleation and growth in the marine boundary layer was found in the CAA in the summertime, with these events observed on 41 % of days in a 2016 cruise. As well, at Alert, Nunavut, particles that are newly formed and grown under conditions of minimal anthropogenic influence during the months of July and August are estimated to contribute 20 % to 80 % of the 30–50 nm particle number density. DMS-oxidation-driven nucleation is facilitated by the presence of atmospheric ammonia arising from seabird-colony emissions, and potentially also from coastal regions, tundra, and biomass burning. Via accumulation of secondary organic aerosol (SOA), a significant fraction of the new particles grow to sizes that are active in cloud droplet formation. Although the gaseous precursors to Arctic marine SOA remain poorly defined, the measured levels of common continental SOA precursors (isoprene and monoterpenes) were low, whereas elevated mixing ratios of oxygenated volatile organic compounds (OVOCs) were inferred to arise via processes involving the sea surface microlayer. (3) The variability in the vertical distribution of black carbon (BC) under both springtime Arctic haze and more pristine summertime aerosol conditions was observed. Measured particle size distributions and mixing states were used to constrain, for the first time, calculations of aerosol–climate interactions under Arctic conditions. Aircraft- and ground-based measurements were used to better establish the BC source regions that supply the Arctic via long-range transport mechanisms, with evidence for a dominant springtime contribution from eastern and southern Asia to the middle troposphere, and a major contribution from northern Asia to the surface. (4) Measurements of ice nucleating particles (INPs) in the Arctic indicate that a major source of these particles is mineral dust, likely derived from local sources in the summer and long-range transport in the spring. In addition, INPs are abundant in the sea surface microlayer in the Arctic, and possibly play a role in ice nucleation in the atmosphere when mineral dust concentrations are low. (5) Amongst multiple aerosol components, BC was observed to have the smallest effective deposition velocities to high Arctic snow (0.03 cm s⁻¹).

Recent observational and modeling studies have demonstrated a link between eastern tropical Pacific Ocean (TPO) warming associated with the El Niño–Southern Oscillation (ENSO) and the negative phase of the wintertime northern annular mode (NAM). The TPO–NAM link involves a Rossby wave teleconnection from the tropics to the extratropics, and an increase in polar stratospheric wave driving that in turn induces a negative NAM anomaly in the stratosphere and troposphere. Previous work further suggests that tropical Indian Ocean (TIO) warming is associated with a positive NAM anomaly, which is of opposite sign to the TPO case. The TIO case is, however, difficult to interpret because the TPO and TIO warmings are not independent. To better understand the dynamics of tropical influences on the NAM, the current study investigates the NAM response to imposed TPO and TIO warmings in a general circulation model. The NAM responses to the two warmings have opposite sign and can be of surprisingly similar amplitude even though the TIO forcing is relatively weak. It is shown that the sign and strength of the NAM response is often simply related to the phasing, and hence the linear interference, between the Rossby wave response and the climatological stationary wave. The TPO (TIO) wave response reinforces (attenuates) the climatological wave and therefore weakens (strengthens) the stratospheric jet and leads to a negative (positive) NAM response. In additional simulations, it is shown that decreasing the strength of the climatological stationary wave reduces the importance of linear interference and increases the importance of nonlinearity. This work demonstrates that the simulated extratropical annular mode response to climate forcings can depend sensitively on the amplitude and phase of the climatological stationary wave and the wave response.

Variability in the extent of fall season snow cover over the Eurasian sector has been linked in observations to a teleconnection with the winter northern annular mode pattern. Here, the dynamics of this teleconnection are investigated using a 100-member ensemble of transient integrations of the GFDL atmospheric general circulation model (AM2). The model is perturbed with a simple persisted snow anomaly over Siberia and is integrated from October through December. Strong surface cooling occurs above the anomalous Siberian snow cover, which produces a tropospheric form stress anomaly associated with the vertical propagation of wave activity. This wave activity response drives wave–mean flow interaction in the lower stratosphere and subsequent downward propagation of a negative-phase northern annular mode response back into the troposphere. A wintertime coupled stratosphere–troposphere response to fall season snow forcing is also found to occur even when the snow forcing itself does not persist into winter. Finally, the response to snow forcing is compared in versions of the same model with and without a well-resolved stratosphere. The version with the well-resolved stratosphere exhibits a faster and weaker response to snow forcing, and this difference is tied to the unrealistic representation of the unforced lower-stratospheric circulation in that model.

The classical problem of predicting the atmospheric circulation response to extratropical surface forcing is revisited in the context of the observed connection between autumnal snow cover anomalies over Siberia and wintertime anomalies of the northern annular mode (NAM). Previous work has shown that in general circulation model (GCM) simulations in which autumnal Siberian snow forcing is prescribed, a vertically propagating Rossby wave train is generated that propagates into the stratosphere, drives dynamical stratospheric warming, and induces a negative NAM response that couples to the troposphere. Important questions remain regarding the dynamics of the response to this surface cooling. It is shown that previously unexplained aspects of the evolution of the response in a comprehensive GCM can be explained by examining the time evolution of the phasing, and hence the linear interference, between the Rossby wave response and the background climatological stationary wave. When the wave response and background wave are in phase, wave activity into the stratosphere is amplified and the zonal-mean stratosphere–troposphere NAM response displays a negative tendency; when they are out of phase, wave activity into the stratosphere is reduced and the NAM response displays a positive tendency. The effects of linear interference are probed further in a simplified GCM, where an imposed lower tropospheric cooling is varied in position, strength, and sign. As in the comprehensive GCM, linear interference strongly influences the response over a realistic range of forcing strengths. The transition from linear to nonlinear behavior is shown to depend simply on forcing strength.

A statistical forecast model, referred to as the snow-cast (sCast) model, has been developed using observed October mean snow cover and sea level pressure anomalies to predict upcoming winter land surface temperatures for the extratropical Northern Hemisphere. In operational forecasts since 1999, snow cover has been used for seven winters, and sea level pressure anomalies for three winters. Presented are skill scores for these seven real-time forecasts and also for 33 winter hindcasts (1972/73–2004/05). The model demonstrates positive skill over much of the eastern United States and northern Eurasia—regions that have eluded skillful predictions among the existing major seasonal forecast centers. Comparison with three leading dynamical forecast systems shows that the statistical model produces superior skill for the same regions. Despite the increasing complexity of the dynamical models, they continue to derive their forecast skill predominantly from tropical atmosphere–ocean coupling, in particular from ENSO. Therefore, in the Northern Hemisphere extratropics, away from the influence of ENSO, the sCast model is expected to outperform the dynamical models into the foreseeable future.