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 Key Points: • Updated Community Land Model has more hydrological and ecological process fidelity and more comprehensive representation of land management. • The model is systematically evaluated using International Land Model Benchmarking system and shows marked improvement over prior versions. 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. Plain Language Summary The Community Land Model (CLM) is the land component of the widely used Community Earth System Model (CESM). Here, we introduce model developments included in CLM version 5 (CLM5), the default land component for CESM2 which will be used for the Coupled Model Intercomparison Project (CMIP6). CLM5 includes many new and updated processes including (1) hydrology and snow features such as spatially explicit soil depth, canopy snow processes, a simple firn model, and a more mechanistic river model, (2) plant hydraulics and hydraulic redistribution, (3) revised nitrogen cycling with flexible leaf stoichiometry, leaf N optimization for photosynthesis, and carbon costs for plant nitrogen uptake, (4) expansion to six crop types (global) and time-evolving irrigated areas and fertilization rates, (5) improved urban building energy model, and (6) carbon isotopes. New optional features include a demographically structured dynamic vegetat...

Abstract. This paper describes the operational methods to achieve and measure both deep-soil heating (0–3 m) and whole-ecosystem warming (WEW) appropriate to the scale of tall-stature, high-carbon, boreal forest peatlands. The methods were developed to allow scientists to provide a plausible set of ecosystem-warming scenarios within which immediate and longer-term (1 decade) responses of organisms (microbes to trees) and ecosystem functions (carbon, water and nutrient cycles) could be measured. Elevated CO2 was also incorporated to test how temperature responses may be modified by atmospheric CO2 effects on carbon cycle processes. The WEW approach was successful in sustaining a wide range of aboveground and belowground temperature treatments (+0, +2.25, +4.5, +6.75 and +9 °C) in large 115 m2 open-topped enclosures with elevated CO2 treatments (+0 to +500 ppm). Air warming across the entire 10 enclosure study required  ∼  90 % of the total energy for WEW ranging from 64 283 mega Joules (MJ) d−1 during the warm season to 80 102 MJ d−1 during cold months. Soil warming across the study required only 1.3 to 1.9 % of the energy used ranging from 954 to 1782 MJ d−1 of energy in the warm and cold seasons, respectively. The residual energy was consumed by measurement and communication systems. Sustained temperature and elevated CO2 treatments were only constrained by occasional high external winds. This paper contrasts the in situ WEW method with closely related field-warming approaches using both aboveground (air or infrared heating) and belowground-warming methods. It also includes a full discussion of confounding factors that need to be considered carefully in the interpretation of experimental results. The WEW method combining aboveground and deep-soil heating approaches enables observations of future temperature conditions not available in the current observational record, and therefore provides a plausible glimpse of future environmental conditions.

Terrestrial ecosystems play a vital role in regulating the accumulation of carbon (C) in the atmosphere. Understanding the factors controlling land C uptake is critical for reducing uncertainties in projections of future climate. The relative importance of changing climate, rising atmospheric CO2, and other factors, however, remains unclear despite decades of research. Here, we use an ensemble of land models to show that models disagree on the primary driver of cumulative C uptake for 85% of vegetated land area. Disagreement is largest in model sensitivity to rising atmospheric CO2 which shows almost twice the variability in cumulative land uptake since 1901 (1 s.d. of 212.8 PgC vs. 138.5 PgC, respectively). We find that variability in CO2 and temperature sensitivity is attributable, in part, to their compensatory effects on C uptake, whereby comparable estimates of C uptake can arise by invoking different sensitivities to key environmental conditions. Conversely, divergent estimates of C uptake can occur despite being based on the same environmental sensitivities. Together, these findings imply an important limitation to the predictability of C cycling and climate under unprecedented environmental conditions. We suggest that the carbon modeling community prioritize a probabilistic multi-model approach to generate more robust C cycle projections.

To evaluate boreal peatland C losses from warming, novel technologies were used to expose intact bog plots in northern Minnesota to a range of future temperatures (+0°C to +9°C) with and without elevated CO 2 (eCO 2). After 3 years, warming linearly increased net C loss at a rate of 31.3 g C•m −2 •year −1 •°C −1. Increasing losses were associated with increased decomposition and corroborated by measures of declining peat elevation. Effects of eCO 2 were minor. Results indicate a range of C losses from boreal peatlands 4.5 to 18 times faster than historical rates of accumulation, with substantial emissions of CO 2 and CH 4 to the atmosphere. A model of peatland C cycle captured the temperature response dominated by peat decomposition under ambient CO 2 , but improvements will be needed to predict the lack of observable responses to elevated CO 2 concentrations thus far. Plain Language Summary Northern bogs and fens have accumulated carbon in deep deposits of peat-dead and decaying plant material high in carbon content-for millennia under wet, cold, and acidic conditions. We experimentally warmed and added CO 2 to a series of bog plots in northern Minnesota to investigate whether warming and drying would lead to the increased decomposition and loss of carbon from bogs to the atmosphere, where it would contribute further to warming. We found that warming changed the nature of these bogs from carbon accumulators to carbon emitters-where carbon was increasingly lost to the atmosphere in the form of greenhouse gases CO 2 and CH 4 as the level of warming increased. This carbon loss was faster than historical rates of carbon accumulation, demonstrating the significant impact of global warming on naturally stored carbon. Improved peatland ecosystem models are capable of capturing the temperature responses but overpredict responses to the elevated CO 2 treatments.

Significant land greening in the northern extratropical latitudes (NEL) has been documented through satellite observations during the past three decades 1-5 . This enhanced vegetation growth has broad implications for surface energy, water and carbon budgets, and ecosystem services across multiple scales 6-8 . Discernible human impacts on the Earth's climate system have been revealed by using statistical frameworks of detection-attribution 9-11 . These impacts, however, were not previously identified on the NEL greening signal, owing to the lack of long-term observational records, possible bias of satellite data, di erent algorithms used to calculate vegetation greenness, and the lack of suitable simulations from coupled Earth system models (ESMs). Here we have overcome these challenges to attribute recent changes in NEL vegetation activity. We used two 30-year-long remote-sensing-based leaf area index (LAI) data sets 12,13 , simulations from 19 coupled ESMs with interactive vegetation, and a formal detection and attribution algorithm 14,15 . Our findings reveal that the observed greening record is consistent with an assumption of anthropogenic forcings, where greenhouse gases play a dominant role, but is not consistent with simulations that include only natural forcings and internal climate variability. These results provide the first clear evidence of a discernible human fingerprint on physiological vegetation changes other than phenology and range shifts 11 .This study examines the growing season LAI over the NEL (30-75 • N). The LAI is a measurable biophysical parameter using satellite observation, an archived prognostic variable of the Coupled Model Intercomparison Project Phase 5 (CMIP5) ESMs, and a direct indicator of the leaf surface per unit ground area that exchanges energy, water, carbon dioxide and momentum with the planetary boundary layer. We employed the recently published LAI3g data set 12 and the GEOLAND2 LAI data 13 , both of which were quality-controlled over the NEL region for the 1982-2011 period ( Supplementary Information 1). We compared the observed changes of LAI to simulated variations from multi-model results obtained from the CMIP5 archive (Supplementary Information 2 and Supplementary Table 1). These ensemble simulations comprise ALL, with historical anthropogenic and natural forcings, GHG, with greenhouse gases forcing only, NAT, with natural forcing only, CTL, with internal variability (IV) only, esmFixClim2, with CO 2 physiological effects, and esmFdbk2, with greenhouse gases radiative effects. Beyond the standard comparison of time series and patterns of trends, two methods were applied to detect and attribute changes in observed LAI, including a formal 'optimal fingerprint' analysis (Methods).From 1982 to 2011, LAI3g, GEOLAND2 and their mean exhibited greening trends over the NEL vegetated area (85.3%, 69.5% and 80.6%, respectively), except across a narrow latitudinal band over Canada and Alaska, and in a few spots over Eurasia (Fig. 1a-c). The largest positive increase is observ...