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...

Accurate assessment of anthropogenic carbon dioxide (CO 2 ) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere -the "global carbon budget" -is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO 2 emissions (E FF ) are based on energy statistics and cement production data, while emissions from land use and land-use change (E LUC ), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO 2 concentration is measured directly and its growth rate (G ATM ) is computed from the annual changes in concentration. The ocean CO 2 sink (S OCEAN ) and terrestrial CO 2 sink (S LAND ) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (B IM ), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ . For the last decade available (2008-2017), E FF was 9.4 ± 0.5 GtC yr −1 , E LUC 1.5 ± 0.7 GtC yr −1 , G ATM 4.7 ± 0.02 GtC yr −1 , S OCEAN 2.4 ± 0.5 GtC yr −1 , and S LAND 3.2 ± 0.8 GtC yr −1 , with a budget imbalance B IM of 0.5 GtC yr −1 indicating overestimated emissions and/or underestimated sinks. For the year 2017 alone, the growth in E FF was about 1.6 % and emissions increased to 9.9 ± 0.5 GtC yr −1 . Also for 2017, E LUC was 1.4 ± 0.7 GtC yr −1 , G ATM was 4.6 ± 0.2 GtC yr −1 , S OCEAN was 2.5 ± 0.5 GtC yr −1 , and S LAND was 3.8 ± 0.8 GtC yr −1 , with a B IM of 0.3 GtC. The global atmospheric CO 2 concentration reached 405.0 ± 0.1 ppm averaged over 2017. For 2018, preliminary data for the first 6-9 months indicate a renewed growth in E FF of +2.7 % (range of 1.8 % to 3.7 %) based on national emission projections for China, the US, the EU, and India and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. The analysis presented here shows that the mean and trend in the five components of the global carbon budget are consistently estimated over the period of 1959-2017, but discrepancies of up to 1 GtC yr −1 persist for the representation of semi-decadal variability in CO 2 fluxes. A detailed comparison among individual estimates and the introduction of a broad range of observations show (1) no consensus in the mean and trend in land-use change emissions, (2) a persistent low agreement among the different methods on the magnitude of the land CO 2 flux in the northern extra-tropics, and (3) an apparent underestimation of the CO 2 variability by ocean models, originating outside the tropics. This living data update documents changes in the methods and data sets used in this new global c...

Stocks of soil organic carbon represent a large component of the carbon cycle that may participate in climate change feedbacks, particularly on decadal and centennial timescales. For Earth system models (ESMs), the ability to accurately represent the global distribution of existing soil carbon stocks is a prerequisite for accurately predicting future carbon–climate feedbacks. We compared soil carbon simulations from 11 model centers to empirical data from the Harmonized World Soil Database (HWSD) and the Northern Circumpolar Soil Carbon Database (NCSCD). Model estimates of global soil carbon stocks ranged from 510 to 3040 Pg C, compared to an estimate of 1260 Pg C (with a 95% confidence interval of 890–1660 Pg C) from the HWSD. Model simulations for the high northern latitudes fell between 60 and 820 Pg C, compared to 500 Pg C (with a 95% confidence interval of 380–620 Pg C) for the NCSCD and 290 Pg C for the HWSD. Global soil carbon varied 5.9 fold across models in response to a 2.6-fold variation in global net primary productivity (NPP) and a 3.6-fold variation in global soil carbon turnover times. Model–data agreement was moderate at the biome level (R² values ranged from 0.38 to 0.97 with a mean of 0.75); however, the spatial distribution of soil carbon simulated by the ESMs at the 1° scale was not well correlated with the HWSD (Pearson correlation coefficients less than 0.4 and root mean square errors from 9.4 to 20.8 kg C m⁻²). In northern latitudes where the two data sets overlapped, agreement between the HWSD and the NCSCD was poor (Pearson correlation coefficient 0.33), indicating uncertainty in empirical estimates of soil carbon. We found that a reduced complexity model dependent on NPP and soil temperature explained much of the 1° spatial variation in soil carbon within most ESMs (R² values between 0.62 and 0.93 for 9 of 11 model centers). However, the same reduced complexity model only explained 10% of the spatial variation in HWSD soil carbon when driven by observations of NPP and temperature, implying that other drivers or processes may be more important in explaining observed soil carbon distributions. The reduced complexity model also showed that differences in simulated soil carbon across ESMs were driven by differences in simulated NPP and the parameterization of soil heterotrophic respiration (inter-model R² = 0.93), not by structural differences between the models. Overall, our results suggest that despite fair global-scale agreement with observational data and moderate agreement at the biome scale, most ESMs cannot reproduce grid-scale variation in soil carbon and may be missing key processes. Future work should focus on improving the simulation of driving variables for soil carbon stocks and modifying model structures to include additional processes

Rising atmospheric CO 2 will make Earth warmer, and many studies have inferred that this warming will cause droughts to become more widespread and severe. However, rising atmospheric CO 2 also modifies stomatal conductance and plant water use, processes that are often are overlooked in impact analysis. We find that plant physiological responses to CO 2 reduce predictions of future drought stress, and that this reduction is captured by using plant-centric rather than atmosphere-centric metrics from Earth system models (ESMs). The atmosphere-centric Palmer Drought Severity Index predicts future increases in drought stress for more than 70% of global land area. This area drops to 37% with the use of precipitation minus evapotranspiration (P-E), a measure that represents the water flux available to downstream ecosystems and humans. The two metrics yield consistent estimates of increasing stress in regions where precipitation decreases are more robust (southern North America, northeastern South America, and southern Europe). The metrics produce diverging estimates elsewhere, with P-E predicting decreasing stress across temperate Asia and central Africa. The differing sensitivity of drought metrics to radiative and physiological aspects of increasing CO 2 partly explains the divergent estimates of future drought reported in recent studies. Further, use of ESM output in offline models may double-count plant feedbacks on relative humidity and other surface variables, leading to overestimates of future stress. The use of drought metrics that account for the response of plant transpiration to changing CO 2 , including direct use of P-E and soil moisture from ESMs, is needed to reduce uncertainties in future assessment.T he demand for water by the atmosphere is widely predicted to increase due to climate change (1). It is commonly inferred that this will cause droughts to become more widespread and severe (2). Many recent studies, however, ignore the impact of rising atmospheric CO 2 on plant water use (3-11). Plants absorb CO 2 through stomates in their leaves, and simultaneously lose water to the atmosphere by means of transpiration through the same pathway. Higher atmospheric CO 2 concentrations allow plants to reduce water losses per unit of carbon gain (12), in part by reducing stomatal conductance when the gradient of CO 2 between the atmosphere and the leaf interior increases. If leaf area stays the same, this physiological response has the potential to reduce water losses from the land surface, increase soil moisture, and reduce plant water stress (13)-the opposite effect of an increase in drought stress and aridity as predicted by many drought metrics (3,14,15). A plant-centric view may therefore suggest that ecosystem-level tradeoffs between water loss and photosynthesis under increasing CO 2 are potentially large enough to reduce drought, despite the large projected increases in water demand from a warmer atmosphere.Drought indices, river routing schemes, and water balance models frequently use potential evapotr...

Global change is impacting forests worldwide, threatening biodiversity and ecosystem services including climate regulation. Understanding how forests respond is critical to forest conservation and climate protection. This review describes an international network of 59 long-term forest dynamics research sites (CTFS-ForestGEO) useful for characterizing forest responses to global change. Within very large plots (median size 25 ha), all stems ≥1 cm diameter are identified to species, mapped, and regularly recensused according to standardized protocols. CTFS-ForestGEO spans 25°S-61°N latitude, is generally representative of the range of bioclimatic, edaphic, and topographic conditions experienced by forests worldwide, and is the only forest monitoring network that applies a standardized protocol to each of the world's major forest biomes. Supplementary standardized measurements at subsets of the sites provide additional information on plants, animals, and ecosystem and environmental variables. CTFS-ForestGEO sites are experiencing multifaceted anthropogenic global change pressures including warming (average 0.61°C), changes in precipitation (up to AE30% change), atmospheric deposition of nitrogen and sulfur compounds (up to 3.8 g N m À2 yr À1 and 3.1 g S m À2 yr À1), and forest fragmentation in the surrounding landscape (up to 88% reduced tree cover within 5 km). The broad suite of measurements made at CTFS-ForestGEO sites makes it possible to investigate the complex ways in which global change is impacting forest dynamics. Ongoing research across the CTFSForestGEO network is yielding insights into how and why the forests are changing, and continued monitoring will provide vital contributions to understanding worldwide forest diversity and dynamics in an era of global change.

Abstract.Fire is an integral Earth System process that interacts with climate in multiple ways. Here we assessed the parametrization of fires in the Community Land Model (CLM-CN) and improved the ability of the model to reproduce contemporary global patterns of burned areas and fire emissions. In addition to wildfires we extended CLM-CN to account for fires related to deforestation. We compared contemporary fire carbon emissions predicted by the model to satellite-based estimates in terms of magnitude and spatial extent as well as interannual and seasonal variability. Long-term trends during the 20th century were compared with historical estimates. Overall we found the best agreement between simulation and observations for the fire parametrization based on the work by Arora and Boer (2005). We obtained substantial improvement when we explicitly considered human caused ignition and fire suppression as a function of population density. Simulated fire carbon emissions ranged between 2.0 and 2.4 Pg C/year for the period 1997-2004. Regionally the simulations had a low bias over Africa and a high bias over South America when compared to satellite-based products. The net terrestrial carbon source due to land use change for the 1990s was 1.2 Pg C/year with 11% stemming from deforestation fires. During 2000-2004 this flux decreased to 0.85 Pg C/year with a similar relative contribution from deforestation fires. Between 1900 and 1960 we predicted a slight downward trend in global Correspondence to: S. Kloster (silvia.kloster@zmaw.de) fire emissions caused by reduced fuels as a consequence of wood harvesting and also by increases in fire suppression. The model predicted an upward trend during the last three decades of the 20th century as a result of climate variations and large burning events associated with ENSOinduced drought conditions.

Earth system models are complex and represent a large number of processes, resulting in a persistent spread across climate projections for a given future scenario. Owing to different model performances against observations and the lack of independence among models, there is now evidence that giving equal weight to each available model projection is suboptimal. This Perspective discusses newly developed tools that facilitate a more rapid and comprehensive evaluation of model simulations with observations, process-based emergent constraints that are a promising way to focus evaluation on the observations most relevant to climate projections, and advanced methods for model weighting. These approaches are needed to distil the most credible information on regional climate changes, impacts, and risks for stakeholders and policy-makers.

Abstract. Desert dust perturbs climate by directly and indirectly interacting with incoming solar and outgoing long wave radiation, thereby changing precipitation and temperature, in addition to modifying ocean and land biogeochemistry. While we know that desert dust is sensitive to perturbations in climate and human land use, previous studies have been unable to determine whether humans were increasing or decreasing desert dust in the global average. Here we present observational estimates of desert dust based on paleodata proxies showing a doubling of desert dust during the 20th century over much, but not all the globe. Large uncertainties remain in estimates of desert dust variability over 20th century due to limited data. Using these observational estimates of desert dust change in combination with ocean, atmosphere and land models, we calculate the net radiative effect of these observed changes (top of atmosphere) over the 20th century to be −0.14 ± 0.11 W/m 2 (1990-1999 vs. 1905-1914). The estimated radiative changeCorrespondence to: N. M. Mahowald (mahowald@cornell.edu) due to dust is especially strong between the heavily loaded 1980-1989 and the less heavily loaded 1955-1964 time periods (−0.57 ± 0.46 W/m 2 ), which model simulations suggest may have reduced the rate of temperature increase between these time periods by 0.11 • C. Model simulations also indicate strong regional shifts in precipitation and temperature from desert dust changes, causing 6 ppm (12 PgC) reduction in model carbon uptake by the terrestrial biosphere over the 20th century. Desert dust carries iron, an important micronutrient for ocean biogeochemistry that can modulate ocean carbon storage; here we show that dust deposition trends increase ocean productivity by an estimated 6% over the 20th century, drawing down an additional 4 ppm (8 PgC) of carbon dioxide into the oceans. Thus, perturbations to desert dust over the 20th century inferred from observations are potentially important for climate and biogeochemistry, and our understanding of these changes and their impacts should continue to be refined.