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...

Earth System Models (ESMs) are essential tools for understanding and predicting global change, but they cannot explicitly resolve hillslope-scale terrain structures that fundamentally organize water, energy, and biogeochemical stores and fluxes at subgrid scales. Here we bring together hydrologists, Critical Zone scientists, and ESM developers, to explore how hillslope structures may modulate ESM grid-level water, energy, and biogeochemical fluxes. In contrast to the one-dimensional (1-D), 2-to 3-m deep, and free-draining soil hydrology in most ESM land models, we hypothesize that 3-D, lateral ridge-to-valley flow through shallow and deep paths and insolation contrasts between sunny and shady slopes are the top two globally quantifiable organizers of water and energy (and vegetation) within an ESM grid cell. We hypothesize that these two processes are likely to impact ESM predictions where (and when) water and/or energy are limiting. We further hypothesize that, if implemented in ESM land models, these processes will increase simulated continental water storage and residence time, buffering terrestrial ecosystems against seasonal and interannual droughts. We explore efficient ways to capture these mechanisms in ESMs and identify critical knowledge gaps preventing us from scaling up hillslope to global processes. One such gap is our extremely limited knowledge of the subsurface, where water is stored (supporting vegetation) and released to stream baseflow (supporting aquatic ecosystems). We conclude with a set of organizing

Abstract. We implement and analyze 13 different metrics (4 moist thermodynamic quantities and 9 heat stress metrics) in the Community Land Model (CLM4.5), the land surface component of the Community Earth System Model (CESM). We call these routines the HumanIndexMod. We limit the algorithms of the HumanIndexMod to meteorological inputs of temperature, moisture, and pressure for their calculation. All metrics assume no direct sunlight exposure. The goal of this project is to implement a common framework for calculating operationally used heat stress metrics, in climate models, offline output, and locally sourced weather data sets, with the intent that the HumanIndexMod may be used with the broadest of applications. The thermodynamic quantities use the latest, most accurate and efficient algorithms available, which in turn are used as inputs to the heat stress metrics. There are three advantages of adding these metrics to CLM4.5: (1) improved moist thermodynamic quantities; (2) quantifying heat stress in every available environment within CLM4.5; and (3) these metrics may be used with human, animal, and industrial applications.We demonstrate the capabilities of the HumanIndexMod in a default configuration simulation using CLM4.5. We output 4× daily temporal resolution globally. We show that the advantage of implementing these routines into CLM4.5 is capturing the nonlinearity of the covariation of temperature and moisture conditions. For example, we show that there are systematic biases of up to 1.5 • C between monthly and ±0.5 • C between 4× daily offline calculations and the online instantaneous calculation, respectively. Additionally, we show that the differences between an inaccurate wet bulb calculation and the improved wet bulb calculation are ±1.5 • C. These differences are important due to human responses to heat stress being nonlinear. Furthermore, we show heat stress has unique regional characteristics. Some metrics have a strong dependency on regionally extreme moisture, while others have a strong dependency on regionally extreme temperature.

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As the world overheats—potentially to conditions warmer than during the three million years over which modern humans evolved—suffering from heat stress will become widespread. Fundamental questions about humans’ thermal tolerance limits are pressing. Understanding heat stress as a process requires linking a network of disciplines, from human health and evolutionary theory to planetary atmospheres and economic modeling. The practical implications of heat stress are equally transdisciplinary, requiring technological, engineering, social, and political decisions to be made in the coming century. Yet relative to the importance of the issue, many of heat stress's crucial aspects, including the relationship between its underlying atmospheric drivers—temperature, moisture, and radiation—remain poorly understood. This review focuses on moist heat stress, describing a theoretical and modeling framework that enables robust prediction of the averaged properties of moist heat stress extremes and their spatial distribution in the future, and draws some implications for human and natural systems from this framework. ▪  Moist heat stress affects society; we summarize drivers of moist heat stress and assess future impacts on societal and global scales. ▪  Moist heat stress pattern scaling of climate models allows research on future heat waves, infrastructure planning, and economic productivity.

Abstract. We describe a set of early Eocene (~ 55 Ma) climate model boundary conditions constructed in a self-consistent reference frame and incorporating recent data and methodologies. Given the growing need for uniform experimental design within the Eocene climate modelling community and the challenges faced in simulating the prominent features of Eocene climate, we make publicly available our data sets of Eocene topography, bathymetry, tidal dissipation, vegetation, aerosol distributions and river runoff. Major improvements in our boundary conditions over previous efforts include the implementation of the ANTscape palaeotopography of Antarctica, more accurate representations of the Drake Passage and Tasman Gateway, as well as an approximation of sub grid cell topographic variability. Our boundary conditions also include for the first time modelled estimates of Eocene aerosol distributions and tidal dissipation, both consistent with our palaeotopography and palaeobathymetry. The resolution of our data sets is unprecedented and will facilitate high resolution climate simulations. In light of the inherent uncertainties involved in reconstructing global boundary conditions for past time periods these data sets should be considered as one interpretation of the available data and users are encouraged to modify them according to their needs and interpretations. This paper marks the beginning of a process for reconstructing a set of accurate, open-access Eocene boundary conditions for use in climate models.

As is true in many regions, India experiences surface Urban Heat Island (UHI) effect that is well understood, but the causes of the more recently discovered Urban Cool Island (UCI) effect remain poorly constrained. This raises questions about our fundamental understanding of the drivers of rural-urban environmental gradients and hinders development of effective strategies for mitigation and adaptation to projected heat stress increases in rapidly urbanizing India. Here we show that more than 60% of Indian urban areas are observed to experience a day-time UCI. We use satellite observations and the Community Land Model (CLM) to identify the impact of irrigation and prove for the first time that UCI is caused by lack of vegetation and moisture in non-urban areas relative to cities. In contrast, urban areas in extensively irrigated landscapes generally experience the expected positive UHI effect. At night, UHI warming intensifies, occurring across a majority (90%) of India’s urban areas. The magnitude of rural-urban temperature contrasts is largely controlled by agriculture and moisture availability from irrigation, but further analysis of model results indicate an important role for atmospheric aerosols. Thus both land-use decisions and aerosols are important factors governing, modulating, and even reversing the expected urban-rural temperature gradients.