The Community Land Model (CLM) is the land component of the Community Earth System Model (CESM) and is used in several global and regional modeling systems. In this paper, we introduce model developments included in CLM version 5 (CLM5), which is the default land component for CESM2. We assess an ensemble of simulations, including prescribed and prognostic vegetation state, multiple forcing data sets, and CLM4, CLM4.5, and CLM5, against a range of metrics including from the International Land Model Benchmarking (ILAMBv2) package. CLM5 includes new and updated processes and parameterizations: (1) dynamic land units, (2) updated parameterizations and structure for hydrology and snow (spatially explicit soil depth, dry surface layer, revised groundwater scheme, revised canopy interception and canopy snow processes, updated fresh snow density, simple firn model, and Model for Scale Adaptive River Transport), (3) plant hydraulics and hydraulic redistribution, (4) revised nitrogen cycling (flexible leaf stoichiometry, leaf N optimization for photosynthesis, and carbon costs for plant nitrogen uptake), (5) global crop model with six crop types and time‐evolving irrigated areas and fertilization rates, (6) updated urban building energy, (7) carbon isotopes, and (8) updated stomatal physiology. New optional features include demographically structured dynamic vegetation model (Functionally Assembled Terrestrial Ecosystem Simulator), ozone damage to plants, and fire trace gas emissions coupling to the atmosphere. Conclusive establishment of improvement or degradation of individual variables or metrics is challenged by forcing uncertainty, parametric uncertainty, and model structural complexity, but the multivariate metrics presented here suggest a general broad improvement from CLM4 to CLM5.

This study shows that climate change has the potential to substantially increase undernourishment rates and threaten food security in developing countries through crop damage, but that ozone regulation can significantly offset climate impacts, depending on the scenario. The findings should help policymakers devise optimal strategies for food production under global climate change. Future food production is highly vulnerable to both climate change and air pollution with implications for global food security1,2,3,4. Climate change adaptation and ozone regulation have been identified as important strategies to safeguard food production5,6, but little is known about how climate and ozone pollution interact to affect agriculture, nor the relative effectiveness of these two strategies for different crops and regions. Here we present an integrated analysis of the individual and combined effects of 2000–2050 climate change and ozone trends on the production of four major crops (wheat, rice, maize and soybean) worldwide based on historical observations and model projections, specifically accounting for ozone–temperature co-variation. The projections exclude the effect of rising CO2, which has complex and potentially offsetting impacts on global food supply7,8,9,10. We show that warming reduces global crop production by >10% by 2050 with a potential to substantially worsen global malnutrition in all scenarios considered. Ozone trends either exacerbate or offset a substantial fraction of climate impacts depending on the scenario, suggesting the importance of air quality management in agricultural planning. Furthermore, we find that depending on region some crops are primarily sensitive to either ozone (for example, wheat) or heat (for example, maize) alone, providing a measure of relative benefits of climate adaptation versus ozone regulation for food security in different regions.

We analyze an extensive record of aerosol smoke plume heights derived from observations over North America for the fire seasons of 2002 and 2004–2007 made by the Multi-angle Imaging SpectroRadiometer (MISR) instrument on board the NASA Earth Observing System Terra satellite. We characterize the magnitude and variability of smoke plume heights for various biomes, and assess the contribution of local atmospheric and fire conditions to this variability. Plume heights are highly variable, ranging from a few hundred meters up to 5000 m above the terrain at the Terra overpass time (11:00–14:00 local time). The largest plumes are found over the boreal region (median values of ~850 m height, 24 km length and 940 m thickness), whereas the smallest plumes are found over cropland and grassland fires in the contiguous US (median values of ~530 m height, 12 km length and 550–640 m thickness). The analysis of plume heights in combination with assimilated meteorological observations from the NASA Goddard Earth Observing System indicates that a significant fraction (4–12%) of plumes from fires are injected above the boundary layer (BL), consistent with earlier results for Alaska and the Yukon Territories during summer 2004. Most of the plumes located above the BL (>83%) are trapped within stable atmospheric layers. We find a correlation between plume height and the MODerate resolution Imaging Spectroradiometer (MODIS) fire radiative power (FRP) thermal anomalies associated with each plume. Smoke plumes located in the free troposphere (FT) exhibit larger FRP values (1620–1640 MW) than those remaining within the BL (174–465 MW). Plumes located in the FT without a stable layer reach higher altitudes and are more spread-out vertically than those associated with distinct stable layers (2490 m height and 2790 m thickness versus 1880 m height and 1800 m thickness). The MISR plume climatology exhibits a well-defined seasonal cycle of plume heights in boreal and temperate biomes, with greater heights during June–July. MODIS FRP measurements indicate that larger summertime heights are the result of higher fire intensity, likely due to more severe fire weather during these months. This work demonstrates the significant effect of fire intensity and atmospheric structure on the ultimate rise of fire emissions, and underlines the importance of considering such physical processes in modeling smoke dispersion.

Fine particulate matter (PM_2.5) from U.S. anthropogenic sources is decreasing. However, previous studies have predicted that PM_2.5 emissions from wildfires will increase in the midcentury to next century, potentially offsetting improvements gained by continued reductions in anthropogenic emissions. Therefore, some regions could experience worse air quality, degraded visibility, and increases in population‐level exposure. We use global climate model simulations to estimate the impacts of changing fire emissions on air quality, visibility, and premature deaths in the middle and late 21st century. We find that PM_2.5 concentrations will decrease overall in the contiguous United States (CONUS) due to decreasing anthropogenic emissions (total PM_2.5 decreases by 3% in Representative Concentration Pathway [RCP] 8.5 and 34% in RCP4.5 by 2100), but increasing fire‐related PM_2.5 (fire‐related PM_2.5 increases by 55% in RCP4.5 and 190% in RCP8.5 by 2100) offsets these benefits and causes increases in total PM_2.5 in some regions. We predict that the average visibility will improve across the CONUS, but fire‐related PM_2.5 will reduce visibility on the worst days in western and southeastern U.S. regions. We estimate that the number of deaths attributable to total PM_2.5 will decrease in both the RCP4.5 and RCP8.5 scenarios (from 6% to 4–5%), but the absolute number of premature deaths attributable to fire‐related PM_2.5 will double compared to early 21st century. We provide the first estimates of future smoke health and visibility impacts using a prognostic land‐fire model. Our results suggest the importance of using realistic fire emissions in future air quality projections.

The Community Atmosphere Model (CAM), version 5, is now coupled to extensive tropospheric and stratospheric chemistry, called CAM5-chem, and is available in addition to CAM4-chem in the Community Earth System Model (CESM) version 1.2. The main focus of this paper is to compare the performance of configurations with internally derived "free running" (FR) meteorology and "specified dynamics" (SD) against observations from surface, aircraft, and satellite, as well as understand the origin of the identified differences. We focus on the representation of aerosols and chemistry. All model configurations reproduce tropospheric ozone for most regions based on in situ and satellite observations. However, shortcomings exist in the representation of ozone precursors and aerosols. Tropospheric ozone in all model configurations agrees for the most part with ozonesondes and satellite observations in the tropics and the Northern Hemisphere within the variability of the observations. Southern hemispheric tropospheric ozone is consistently underestimated by up to 25%. Differences in convection and stratosphere to troposphere exchange processes are mostly responsible for differences in ozone in the different model configurations. Carbon monoxide (CO) and other volatile organic compounds are largely underestimated in Northern Hemisphere mid-latitudes based on satellite and aircraft observations. Nitrogen oxides (NO_x) are biased low in the free tropical troposphere, whereas peroxyacetyl nitrate (PAN) is overestimated in particular in high northern latitudes. The present-day methane lifetime estimates are compared among the different model configurations. These range between 7.8 years in the SD configuration of CAM5-chem and 8.8 years in the FR configuration of CAM4-chem and are therefore underestimated compared to observational estimations. We find that differences in tropospheric aerosol surface area between CAM4 and CAM5 play an important role in controlling the burden of the tropical tropospheric hydroxyl radical (OH), which causes differences in tropical methane lifetime of about half a year between CAM4-chem and CAM5-chem. In addition, different distributions of NO_x from lightning explain about half of the difference between SD and FR model versions in both CAM4-chem and CAM5-chem. Remaining differences in the tropical OH burden are due to enhanced tropical ozone burden in SD configurations compared to the FR versions, which are not only caused by differences in chemical production or loss but also by transport and mixing. For future studies, we recommend the use of CAM5-chem configurations, due to improved aerosol description and inclusion of aerosol–cloud interactions. However, smaller tropospheric surface area density in the current version of CAM5-chem compared to CAM4-chem results in larger oxidizing capacity in the troposphere and therefore a shorter methane lifetime.

The Community Earth System Model (CESM1) CAM4-chem has been used to perform the Chemistry Climate Model Initiative (CCMI) reference and sensitivity simulations. In this model, the Community Atmospheric Model version 4 (CAM4) is fully coupled to tropospheric and stratospheric chemistry. Details and specifics of each configuration, including new developments and improvements are described. CESM1 CAM4-chem is a low-top model that reaches up to approximately 40 km and uses a horizontal resolution of 1.9° latitude and 2.5° longitude. For the specified dynamics experiments, the model is nudged to Modern-Era Retrospective Analysis for Research and Applications (MERRA) reanalysis. We summarize the performance of the three reference simulations suggested by CCMI, with a focus on the last 15 years of the simulation when most observations are available. Comparisons with selected data sets are employed to demonstrate the general performance of the model. We highlight new data sets that are suited for multi-model evaluation studies. Most important improvements of the model are the treatment of stratospheric aerosols and the corresponding adjustments for radiation and optics, the updated chemistry scheme including improved polar chemistry and stratospheric dynamics and improved dry deposition rates. These updates lead to a very good representation of tropospheric ozone within 20 % of values from available observations for most regions. In particular, the trend and magnitude of surface ozone is much improved compared to earlier versions of the model. Furthermore, stratospheric column ozone of the Southern Hemisphere in winter and spring is reasonably well represented. All experiments still underestimate CO most significantly in Northern Hemisphere spring and show a significant underestimation of hydrocarbons based on surface observations.