The Community Earth System Model (CESM) is a flexible and extensible community tool used to investigate a diverse set of Earth system interactions across multiple time and space scales. This global coupled model significantly extends its predecessor, the Community Climate System Model, by incorporating new Earth system simulation capabilities. These comprise the ability to simulate biogeochemical cycles, including those of carbon and nitrogen, a variety of atmospheric chemistry options, the Greenland Ice Sheet, and an atmosphere that extends to the lower thermosphere. These and other new model capabilities are enabling investigations into a wide range of pressing scientific questions, providing new foresight into possible future climates and increasing our collective knowledge about the behavior and interactions of the Earth system. Simulations with numerous configurations of the CESM have been provided to phase 5 of the Coupled Model Intercomparison Project (CMIP5) and are being analyzed by the broad com...

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The Community Earth System Model: A Framework for Collaborative Research

Global environmental change is rapidly altering the dynamics of terrestrial vegetation, with consequences for the functioning of the Earth system and provision of ecosystem services(1,2). Yet how global vegetation is responding to the changing environment is not well established. Here we use three long-term satellite leaf area index (LAI) records and ten global ecosystem models to investigate four key drivers of LAI trends during 1982-2009. We show a persistent and widespread increase of growing season integrated LAI (greening) over 25% to 50% of the global vegetated area, whereas less than 4% of the globe shows decreasing LAI (browning). Factorial simulations with multiple global ecosystem models suggest that CO2 fertilization effects explain 70% of the observed greening trend, followed by nitrogen deposition (9%), climate change (8%) and land cover change (LCC) (4%). CO2 fertilization effects explain most of the greening trends in the tropics, whereas climate change resulted in greening of the high latitudes and the Tibetan Plateau. LCC contributed most to the regional greening observed in southeast China and the eastern United States. The regional effects of unexplained factors suggest that the next generation of ecosystem models will need to explore the impacts of forest demography, differences in regional management intensities for cropland and pastures, and other emerging productivity constraints such as phosphorus availability.

/pdf/greening-of-the-earth-and-its-drivers-1ksndek8nh.pdf

Greening of the Earth and its drivers

. Accurate assessment of anthropogenic carbon dioxide (CO2) 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 all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates and consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (ELUC), mainly deforestation, are based on combined evidence from land-cover change data, fire activity associated with deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The mean ocean CO2 sink (SOCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in SOCEAN is evaluated with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models. We compare the mean land and ocean fluxes and their variability to estimates from three atmospheric inverse methods for three broad latitude bands. All uncertainties are reported as ±1σ, reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2006–2015), EFF was 9.3 ± 0.5 GtC yr−1, ELUC 1.0 ± 0.5 GtC yr−1, GATM 4.5 ± 0.1 GtC yr−1, SOCEAN 2.6 ± 0.5 GtC yr−1, and SLAND 3.1 ± 0.9 GtC yr−1. For year 2015 alone, the growth in EFF was approximately zero and emissions remained at 9.9 ± 0.5 GtC yr−1, showing a slowdown in growth of these emissions compared to the average growth of 1.8 % yr−1 that took place during 2006–2015. Also, for 2015, ELUC was 1.3 ± 0.5 GtC yr−1, GATM was 6.3 ± 0.2 GtC yr−1, SOCEAN was 3.0 ± 0.5 GtC yr−1, and SLAND was 1.9 ± 0.9 GtC yr−1. GATM was higher in 2015 compared to the past decade (2006–2015), reflecting a smaller SLAND for that year. The global atmospheric CO2 concentration reached 399.4 ± 0.1 ppm averaged over 2015. For 2016, preliminary data indicate the continuation of low growth in EFF with +0.2 % (range of −1.0 to +1.8 %) based on national emissions projections for China and USA, and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. In spite of the low growth of EFF in 2016, the growth rate in atmospheric CO2 concentration is expected to be relatively high because of the persistence of the smaller residual terrestrial sink (SLAND) in response to El Nino conditions of 2015–2016. From this projection of EFF and assumed constant ELUC for 2016, cumulative emissions of CO2 will reach 565 ± 55 GtC (2075 ± 205 GtCO2) for 1870–2016, about 75 % from EFF and 25 % from ELUC. This living data update documents changes in the methods and data sets used in this new carbon budget compared with previous publications of this data set (Le Quere et al., 2015b, a, 2014, 2013). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center ( doi:10.3334/CDIAC/GCP_2016 ).

/pdf/global-carbon-budget-2016-5acbzpsjhs.pdf

Global Carbon Budget 2016

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.

The Community Land Model version 5 : description of new features, benchmarking, and impact of forcing uncertainty

[1] The Community Land Model is the land component of the Community Climate System Model. Here, we describe a broad set of model improvements and additions that have been provided through the CLM development community to create CLM4. The model is extended with a carbon-nitrogen (CN) biogeochemical model that is prognostic with respect to vegetation, litter, and soil carbon and nitrogen states and vegetation phenology. An urban canyon model is added and a transient land cover and land use change (LCLUC) capability, including wood harvest, is introduced, enabling study of historic and future LCLUC on energy, water, momentum, carbon, and nitrogen fluxes. The hydrology scheme is modified with a revised numerical solution of the Richards equation and a revised ground evaporation parameterization that accounts for litter and within-canopy stability. The new snow model incorporates the SNow and Ice Aerosol Radiation model (SNICAR) - which includes aerosol deposition, grain-size dependent snow aging, and vertically-resolved snowpack heating – as well as new snow cover and snow burial fraction parameterizations. The thermal and hydrologic properties of organic soil are accounted for and the ground column is extended to ∼50-m depth. Several other minor modifications to the land surface types dataset, grass and crop optical properties, surface layer thickness, roughness length and displacement height, and the disposition of snow-capped runoff are also incorporated. The new model exhibits higher snow cover, cooler soil temperatures in organic-rich soils, greater global river discharge, and lower albedos over forests and grasslands, all of which are improvements compared to CLM3.5. When CLM4 is run with CN, the mean biogeophysical simulation is degraded because the vegetation structure is prognostic rather than prescribed, though running in this mode also allows more complex terrestrial interactions with climate and climate change.

/pdf/parameterization-improvements-and-functional-and-structural-4uhk3hsygs.pdf

Parameterization improvements and functional and structural advances in version 4 of the Community Land Model

/pdf/technical-description-of-version-4-5-of-the-community-land-5dbe09n7u7.pdf

Technical description of version 4.5 of the Community Land Model (CLM)

/pdf/technical-description-of-version-4-0-of-the-community-land-4j0ebbbp74.pdf

Technical Description of version 4.0 of the Community Land Model (CLM)

Modeling land use and land management with the Community Land Model

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Technical description of version 4.5 of the Community Land Model (CLM)

Technical Description of version 4.0 of the Community Land Model (CLM)

Modeling land use and land management with the Community Land Model