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Abstract Land‐atmosphere interactions are central to the evolution of the atmospheric boundary layer and the subsequent formation of clouds and precipitation. Existing global climate models represent these connections with bulk approximations on coarse spatial scales, but observations suggest that small‐scale variations in surface characteristics and co‐located turbulent and momentum fluxes can significantly impact the atmosphere. Recent model development efforts have attempted to capture this phenomenon by coupling existing representations of subgrid‐scale (SGS) heterogeneity between land and atmosphere models. Such approaches are in their infancy and it is not yet clear if they can produce a realistic atmospheric response to surface heterogeneity. Here, we implement a parameterization to capture the effects of SGS heterogeneity in the Community Earth System Model (CESM2), and compare single‐column simulations against high‐resolution Weather Research and Forecasting (WRF) large‐eddy simulations (LESs), which we use as a proxy for observations. The CESM2 experiments increase the temperature and humidity variances in the lowest atmospheric levels, but the response is weaker than in WRF‐LES. In part, this is attributed to an underestimate of surface heterogeneity in the land model due to a lack of SGS meteorology, a separation between deep and shallow convection schemes in the atmosphere, and a lack of explicitly represented mesoscale secondary circulations. These results highlight the complex processes involved in capturing the effects of SGS heterogeneity and suggest the need for parameterizations that communicate their influence not only at the surface but also vertically.

Abstract We enhance the Community Land Model (CLM) snow albedo modeling by implementing several new features with more realistic and physical representations of snow‐aerosol‐radiation interactions. Specifically, we incorporate the following model enhancements: (a) updating ice and aerosol optical properties with more realistic and accurate data sets, (b) adding multiple dust types, (c) adding multiple surface downward solar spectra to account for different atmospheric conditions, (d) incorporating a more accurate adding‐doubling radiative transfer solver, (e) adding nonspherical snow grain representations, (f) adding black carbon‐snow and dust‐snow internal mixing representations, and (g) adding a hyperspectral (480‐band vs. the default 5‐band) modeling capability. These model features/enhancements are included as new CLM physics/namelist options, which allows for quantification of model sensitivity to snow albedo processes and for multi‐physics model ensemble analyses for uncertainty assessment. The model updates have been included in the latest released CLM version. Sensitivity analyses reveal strong impacts of using the new adding‐doubling solver, nonspherical snow grains, aerosol‐snow internal mixing, updated aerosol optics, and different dust types. These enhanced snow albedo representations improve the CLM simulated global snowpack evolution and land surface conditions, with reduced biases in simulated snow surface albedo, snow cover, snow water equivalent, snow depth, and surface (2‐m) air temperature over many mid‐latitude mountainous regions and seasonal snowpacks but degraded performance in some northern high‐latitude regions.

Abstract Numerical models have been developed to investigate and understand responses of biogeochemical cycle to global changes. Steady state, when a system is in dynamic equilibrium, is generally required to initialize these model simulations. However, the spin‐up process that is used to achieve steady state pose a great burden to computational resources, limiting the efficiency of global modeling analysis on biogeochemical cycles. This study introduces a new Semi‐Analytical Spin‐Up (SASU) to tackle this grand challenge. We applied SASU to Community Land Model version 5 and examined its computational efficiency and accuracy. At the Brazil site, SASU is computationally 7 times more efficient than (or saved up to 86% computational cost in comparison with) the traditional native dynamics (ND) spin‐up to reach the same steady state. Globally, SASU is computationally 8 times more efficient than the accelerated decomposition spin‐up and 50 times more efficient than ND. In summary, SASU achieves the highest computational efficiency for spin‐up on site and globally in comparison with other spin‐up methods. It is generalizable to wide biogeochemical models and thus makes computationally costly studies (e.g., parameter perturbation ensemble analysis and data assimilation) possible for a better understanding of biogeochemical cycle under climate change.

Warming and drying from deforestation could amplify carbon storage losses in tropical remaining forests. Here the authors report this value to be extra 5.1% in the Amazon and 3.8% in Congo as compared to the direct biomass loss from deforestation.

Abstract Stratospheric aerosol injection (SAI) has been shown in climate models to reduce some impacts of global warming in the Arctic, including the loss of sea ice, permafrost thaw, and reduction of Greenland Ice Sheet (GrIS) mass; SAI at high latitudes could preferentially target these impacts. In this study, we use the Community Earth System Model to simulate two Arctic‐focused SAI strategies, which inject at 60°N latitude each spring with injection rates adjusted to either maintain September Arctic sea ice at 2030 levels (“Arctic Low”) or restore it to 2010 levels (“Arctic High”). Both simulations maintain or restore September sea ice to within 10% of their respective targets, reduce permafrost thaw, and increase GrIS surface mass balance by reducing runoff. Arctic High reduces these impacts more effectively than a globally focused SAI strategy that injects similar quantities of SO2 at lower latitudes. However, Arctic‐focused SAI is not merely a “reset button” for the Arctic climate, but brings about a novel climate state, including changes to the seasonal cycles of Northern Hemisphere temperature and sea ice and less high‐latitude carbon uptake relative to SSP2‐4.5. Additionally, while Arctic‐focused SAI produces the most cooling near the pole, its effects are not confined to the Arctic, including detectable cooling throughout most of the northern hemisphere for both simulations, increased mid‐latitude sulfur deposition, and a southward shift of the location of the Intertropical Convergence Zone. For these reasons, it would be incorrect to consider Arctic‐focused SAI as “local” geoengineering, even when compared to a globally focused strategy.

Abstract Soil moisture predictability on seasonal to decadal (S2D) continuum timescales over North America is examined from the Community Earth System Modeling (CESM) experiments. The effects of ocean and land initializations are disentangled using two large ensemble datasets—initialized and uninitialized experiments from the CESM. We find that soil moisture has significant predictability on S2D timescales despite limited predictability in precipitation. On sub-seasonal to seasonal timescales, precipitation variability is an order of magnitude greater than soil moisture, suggesting land surface processes, including soil moisture memory, reemergence, land–atmosphere interactions, transform a less predictable precipitation signal into a more predictable soil moisture signal.

Abstract The Community Earth System Model (CESM) is widely used for the prediction and understanding of climate variability and change. Accurate simulation of the behavior of near surface air temperature (T2m) is critical in such a model for addressing societally relevant problems. However, previous versions of CESM suffered from an overestimation of wintertime T2m variability in Northern Hemisphere (NH) land regions. Here, it is shown that the latest version of CESM (CESM2) exhibits a much improved representation of wintertime T2m variability compared to its predecessor and it now compares well with observations. A series of targeted experiments reveal that an important contributor to this improvement is the local effects of changes to the representation of snow density within the land surface component. Increased snow densities in CESM2 lead to enhanced conductance of the snow layer. As a result, larger heat fluxes across the snow layer are induced in the presence of T2m anomalies, leading to a greater dampening of surface and near surface atmospheric temperature anomalies. The implications for future projections with CESM2 are also considered through comparison of the CESM1 and CESM2 large ensembles. Aligned with the reduction in surface temperature variability, compared to CESM1, CESM2 exhibits reduced ensemble spread in future projections of NH winter mean temperature and a smaller decline in daily wintertime T2m variability under climate change. Overall, this improvement has increased the accuracy of CESM2 as a tool for the study of wintertime T2m variability and change.

How the effects of irrigation on the climate conditions compare to other anthropogenic forcings is not well known. Observational and model evidence show that expanding irrigation has dampened historical anthropogenic warming during hot days, an effect that is particularly strong over South Asia.

Abstract The concept of using representative hillslopes to simulate hydrologically similar areas of a catchment has been incorporated in many hydrologic models but few Earth system models. Here we describe a configuration of the Community Land Model version 5 in which each grid cell is decomposed into one or more multicolumn hillslopes. Within each hillslope, the intercolumn connectivity is specified, and the lateral saturated subsurface flow from each column is passed to its downslope neighbor. We first apply the model to simulate a headwater catchment and assess the results against runoff and evapotranspiration flux measurements. By redistributing soil water within the catchment, the model is able to reproduce the observed difference between evapotranspiration in the upland and lowland portions of the catchment. Next, global simulations based on hypothetical hillslope geomorphic parameters are used to show the model's sensitivity to differences in hillslope shape and discretization. Differences in evapotranspiration between upland and lowland hillslope columns are found to be largest in arid and semiarid regions, while humid tropical and high‐latitude regions show limited evapotranspiration increases in lowlands relative to uplands.

Abstract 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.

Abstract Future projections of land carbon uptake in Earth System Models are affected by land surface model responses to both CO2 and nitrogen fertilization. The Community Land Model, Version 5 (CLM5), contains a suite of modifications to carbon and nitrogen cycle representation. Globally, the CLM5 has a larger CO2 response and smaller nitrogen response than its predecessors. To improve our understanding of the controls over the fertilization responses of the new model, we assess sensitivity to eight parameters pertinent to the cycling of carbon and nitrogen by vegetation, both under present‐day conditions and with CO2 and nitrogen fertilization. The impact of fertilization varies with both model parameters and with the balance of limiting factors (water, temperature, nutrients, and light) in the pre‐fertilization model state. The model parameters that impact the pre‐fertilization state are in general not the same as those that control fertilization responses, meaning that goodness of fit to present‐day conditions does not necessarily imply a constraint on future transient projections. Where pre‐fertilization state has low leaf area, fertilization‐induced increases in leaf production amplify the model response to the initial fertilization via further increases in photosynthesis. Model responses to CO2 and N fertilization are strongly impacted by how much plant communities can increase their rates of nitrogen fixation and also directly affected by costs of N extraction from soil and stoichiometric flexibility. Illustration of how parametric flexibility impacts model outputs should help inform the interpretation of carbon‐climate feedbacks estimated by in fully coupled Earth system model simulations.

Abstract Climate engineering arises as one of the potential methods that could contribute to meeting the 1.5 °C global warming target agreed under the Paris Agreement. We examine how permafrost and high‐latitude vegetation respond to the large‐scale implementation of climate engineering. Specifically, we explore the impacts of applying the solar radiation management method of stratospheric aerosol injections (SAI) on permafrost temperature and the global extent of near‐surface permafrost area. We compare the RCP8.5 and RCP4.5 scenarios to several SAI deployment scenarios using the Norwegian Earth System Model (CE1 = moderate SAI scenario to bring down the global mean warming in RCP8.5 to the RCP4.5 level, CE2 = aggresive SAI scenario to maintain the global mean temperature toward the preindustrial level). We show that large‐scale application of SAI may help slow down the current rate of permafrost degradation for a wide range of emission scenarios. Between the RCP4.5 and CE1 simulations, the differences in the permafrost degradation may be attributed to the spatial variations in surface air temperature, rainfall, and snowfall, which lead to the differences in the timing of permafrost degradation up to 40 years. Although atmospheric temperatures in CE1 and RCP4.5 simulations are similar, net primary production is higher in CE1 due to CO2 fertilization. Our investigation of permafrost extent under large‐scale SAI application scenarios suggests that circum‐Arctic permafrost area and extent is rather sensitive to temperature changes created under such SAI application. Our results highlight the importance of investigating the regional effects of climate engineering, particularly in high‐latitude ecosystems.

Abstract Atmospheric models used for weather prediction and future climate projections rely on land models to calculate surface boundary conditions. Observations of near‐surface states and fluxes made at flux measurement sites provide valuable data with which to assess the quality of simulated lower boundary conditions. A previous assessment of the Community Land Model version 4.5 using data from the Niwot Ridge Subalpine Forest AmeriFlux tower showed that simulated latent heat fluxes could be improved by adjusting a parameter describing the maximum leaf wetted area, but biases in midday sensible heat flux and nighttime momentum flux were generally not reduced by model parameter perturbations. These biases are related to the model's lack of heat storage in vegetation biomass. A biomass heat capacity is parameterized in Community Land Model version 5 with measurable quantities such as canopy height, diameter at breast height, and tree number density. After implementing a parameterization describing the heat transfer between the forest biomass and the canopy air space, the biases in the mean midday sensible heat and mean nighttime momentum fluxes at Niwot Ridge are reduced from 47 to 13 W/m2 and from 0.12 to −0.03 m/s, respectively. The bias in the mean nighttime canopy air temperature was reduced from −5.9 to 0.4 °C. Additional simulations at other flux tower sites demonstrate a consistent reduction in midday sensible heat flux, a lower ratio of the sum of sensible and latent heat flux to net radiation, and an increase in nighttime canopy temperatures.

Abstract Aerosols can enhance terrestrial productivity through increased absorption of solar radiation by the shaded portion of the plant canopy—the diffuse radiation fertilization effect. Although this process can, in principle, alter surface evaporation due to the coupling between plant water loss and carbon uptake, with the potential to change the surface temperature, aerosol‐climate interactions have been traditionally viewed in light of the radiative effects within the atmosphere. Here, we develop a modeling framework that combines global atmosphere and land model simulations with a conceptual diagnostic tool to investigate these interactions from a surface energy budget perspective. Aerosols increase the terrestrial evaporative fraction, or the portion of net incoming energy consumed by evaporation, by over 4% globally and as much as ∼40% regionally. The main mechanism for this is the increase in energy allocation from sensible to latent heat due to global dimming (reduction in global shortwave radiation) and slightly augmented by diffuse radiation fertilization. In regions with moderately dense vegetation (leaf area index >2), the local surface cooling response to aerosols is dominated by this evaporative pathway, not the reduction in incident radiation. Diffuse radiation fertilization alone has a stronger impact on gross primary productivity (+2.18 Pg C y−1 or +1.8%) than on land evaporation (+0.18 W m−2 or +0.48%) and surface temperature (−0.01 K). Our results suggest that it is important for land surface models to distinguish between quantity (change in total magnitude) and quality (change in diffuse fraction) of radiative forcing for properly simulating surface climate.

Abstract Plants are expected to face increasing water stress under future climate change. Most land surface models, including Noah‐MP, employ an idealized “big‐leaf” concept to regulate water and carbon fluxes in response to soil moisture stress through empirical soil hydraulics schemes (SHSs). However, such schemes have been shown to cause significant uncertainties in carbon and water simulations. In this paper, we present a novel plant hydraulics scheme (PHS) for Noah‐MP (hereafter, Noah‐MP‐PHS), which employs a big‐tree rather than big‐leaf concept, wherein the whole‐plant hydraulic strategy is considered, including root‐level soil water acquisition, stem‐level hydraulic conductance and capacitance, and leaf‐level anisohydricity and hydraulic capacitance. Evaluated against plot‐level observations from a mature, mixed hardwood forest at the University of Michigan Biological Station and compared with the default Noah‐MP, Noah‐MP‐PHS better represents plant water stress and improves water and carbon simulations, especially during periods of dry soil conditions. Noah‐MP‐PHS also improves the asymmetrical diel simulation of gross primary production under low soil moisture conditions. Noah‐MP‐PHS is able to reproduce different patterns of transpiration, stem water storage and root water uptake during a 2‐week dry‐down period for two species with contrasting plant hydraulic behaviors, i.e., the “cavitation risk‐averse” red maple and the “cavitation risk‐prone” red oak. Sensitivity experiments with plant hydraulic capacitance show that the stem water storage enables nocturnal plant water recharge, affects plant water use efficiency, and provides an important buffer to relieve xylem hydraulic stress during dry soil conditions.

Abstract Prior research indicates that land use and land cover change (LULCC) in the central United States has led to significant changes in surface climate. The spatial resolution of simulations is particularly relevant in this region due to its influence on model skill in capturing mesoscale convective systems (MCSs) and on representing the spatial heterogeneity. Recent advances in Earth system models (ESMs) make it feasible to use variable resolution (VR) meshes to study regional impacts of LULCC while avoiding inconsistencies introduced by lateral boundary conditions typically seen in limited area models. Here, we present numerical experiments using the Community Earth System Model version 2–VR to evaluate (1) the influence of resolution and land use on model skill and (2) impacts of LULCC over the central United States at different resolutions. These simulations are configured either on the 1° grid or a VR grid with grid refinement to 1/8° over the contiguous United States for the period of 1984–2010 with two alternative land use data sets corresponding to the preindustrial and present day states. Our results show that skill in simulating precipitation over the central United States is primarily dependent on resolution, whereas skill in simulating 2‐m temperature is more dependent on accurate land use. The VR experiments show stronger LULCC‐induced precipitation increases over the Midwest in May and June, corresponding to an increase in the number of MCS‐like features and a more conductive thermodynamic environment for convection. Our study demonstrates the potential of using VR ESMs for hydroclimatic simulations in regions with significant LULCC.

Abstract Plant response to elevated CO2 concentration is known to increase leaf‐level water‐use efficiency through a reduction in stomatal opening. Recent studies have emphasized that increased plant water‐use efficiency can ameliorate the impact of drought due to climate change. However, there is a potentially counterbalancing impact due to the increased leaf area. We investigate long‐term trends (1951 to 2015) of observed streamflow in the Southeastern United States (SE US) and quantify the contribution of major drivers of streamflow changes using single factor climate modeling experiments from Community Land Model Version 5 (CLM5). The SE US streamflow observations do not exhibit a trend, which is in agreement with the CLM5 control experiment. Using the factorial set of CLM5 experiments, we find that increased leaf area under elevated CO2 leads to decreased runoff and completely counteracts increased runoff due to water‐use efficiency gains under elevated CO2 and land‐use change.

Multiple myeloma (MM) is a hematological malignancy resulting from the uncontrolled proliferation of antibody-producing plasma cells in the bone marrow. At diagnosis, independent plasma cell tumors are found throughout the skeleton. The recirculation of mutant plasma cells from the initial lesion and their recolonization of distant marrow sites are thought to occur by a process similar to solid tumor metastasis. However, the efficiency of this bone marrow homing process and the proportion of disseminated cells that actively divide and contribute to new tumor growth in MM are both unknown. We used the C57BL/KaLwRij mouse model of myeloma, lentiviral-mediated DNA barcoding of 5TGM1 myeloma cells, and next-generation sequencing to investigate the relative efficiency of plasma cell migration to, and growth within, the bone marrow. This approach revealed three major findings: firstly, establishment of metastasis within the bone marrow was extremely inefficient, with approximately 0.01% of circulating myeloma cells becoming resident long term in the bone marrow of each long bone; secondly, the individual cells of each metastasis exhibited marked differences in their proliferative fates, with the majority of final tumor burden within a bone being attributable to the progeny of between 1 and 8 cells; and, thirdly, the proliferative fate of individual clonal plasma cells differed at each bone marrow site in which the cells “landed.” These findings suggest that individual myeloma plasma cells are subjected to vastly different selection pressures within the bone marrow microenvironment, highlighting the importance of niche-driven factors, which determine the disease course and outcome.

Infiltration in soils is a key process that partitions precipitation at the land surface into surface runoff and water that enters the soil profile. We reviewed the basic principles of water infiltration in soils and we analyzed approaches commonly used in land surface models (LSMs) to quantify infiltration as well as its numerical implementation and sensitivity to model parameters. We reviewed methods to upscale infiltration from the point to the field, hillslope, and grid cell scales of LSMs. Despite the progress that has been made, upscaling of local-scale infiltration processes to the grid scale used in LSMs is still far from being treated rigorously. We still lack a consistent theoretical framework to predict effective fluxes and parameters that control infiltration in LSMs. Our analysis shows that there is a large variety of approaches used to estimate soil hydraulic properties. Novel, highly resolved soil information at higher resolutions than the grid scale of LSMs may help in better quantifying subgrid variability of key infiltration parameters. Currently, only a few LSMs consider the impact of soil structure on soil hydraulic properties. Finally, we identified several processes not yet considered in LSMs that are known to strongly influence infiltration. Especially, the impact of soil structure on infiltration requires further research. To tackle these challenges and integrate current knowledge on soil processes affecting infiltration processes into LSMs, we advocate a stronger exchange and scientific interaction between the soil and the land surface modeling communities.