Modeling canopy-induced turbulence in the Earth system: a unified parameterization of turbulent exchange within plant canopies and the roughness sublayer (CLM-ml v0)

Land surface models used in climate models neglect the roughness sublayer and parameterize within-canopy turbulence in an ad hoc manner. We implemented a roughness sublayer turbulence parameterization in a multilayer canopy model (CLM-ml v0) to test if this theory provides a tractable parameterization extending from the ground through the canopy and the roughness sublayer. We compared the canopy model with the Community Land Model (CLM4.5) at seven forest, two grassland, and three cropland AmeriFlux sites over a range of canopy heights, leaf area indexes, and climates. CLM4.5 has pronounced biases during summer months at forest sites in midday latent heat flux, sensible heat flux, gross primary production, nighttime friction velocity, and the radiative temperature diurnal range. The new canopy model reduces these biases by introducing new physics. Advances in modeling stomatal conductance and canopy physiology beyond what is in CLM4.5 substantially improve model performance at the forest sites. The signature of the roughness sublayer is most evident in nighttime friction velocity and the diurnal cycle of radiative temperature, but is also seen in sensible heat flux. Within-canopy temperature profiles are markedly different compared with profiles obtained using Monin–Obukhov similarity theory, and the roughness sublayer produces cooler daytime and warmer nighttime temperatures. The herbaceous sites also show model improvements, but the improvements are related less systematically to the roughness sublayer parameterization in these canopies. The multilayer canopy with the roughness sublayer turbulence improves simulations compared with CLM4.5 while also advancing the theoretical basis for surface flux parameterizations

Influence of Vertical Heterogeneities in the Canopy Microenvironment on Interannual Variability of Carbon Uptake in Temperate Deciduous Forests

Vegetation structure and function are key design choices in terrestrial models that affect the relationship between carbon uptake and environmental drivers. Here, we investigate how representing canopy vertical structure in a terrestrial biosphere model- that is, micrometeorological, leaf area, and leaf water profiles- influences carbon uptake at five U.S. temperate deciduous forest sites in July. Specifically, we test whether the interannual variability (IAV) of gross primary productivity (GPP) responds differently to four abiotic environmental drivers- air temperature, relative humidity, incoming shortwave radiation, and soil moisture- using either a Community Land Model multilayer canopy model (CLM- ml) or a big- leaf model (CLM4.5/CLM5). We conclude that vertical leaf area and microclimatic profiles (temperature, humidity, and wind) do not impact GPP IAV compared to a single- layer model when plant hydraulics is excluded. However, with a mechanistic representation of plant hydraulics there is vertically varying water stress in CLM- ml, and the sensitivity of carbon uptake to particular climate variables changes with height, resulting in dampened canopy- scale GPP IAV relative to CLM4.5. Dampening is due to both a reduced dependence on soil moisture and opposing climatic forcing on different leaf layers. Such dampening is not evident in the single- layer representation of plant hydraulic water stress implemented in the recently released CLM5. Overall, both model representations of the canopy fail to accurately simulate observed GPP IAV and this may be related by their inability to capture the upper range of observed hourly GPP and diffuse light- GPP relationships that cannot be resolved by canopy structure alone.Key PointsExplicitly simulated leaf area and microclimatic profiles do not affect gross primary productivity (GPP) interannual variability compared to a - big- leaf- simplificationMultilayer plant hydraulics lead to vertically varying water stress, altering leaf- layer responses to interannual climate variationsAll model simulations underestimate hourly GPP compared to FLUXNET estimates, adversely impacting simulated GPP interannual variabilityPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/156484/2/jgrg21710_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/156484/1/jgrg21710.pd

Self-Duality in D <= 8-dimensional Euclidean Gravity

In the context of D-dimensional Euclidean gravity, we define the natural generalisation to D-dimensions of the self-dual Yang-Mills equations, as duality conditions on the curvature 2-form of a Riemannian manifold. Solutions to these self-duality equations are provided by manifolds of SU(2), SU(3), G_2 and Spin(7) holonomy. The equations in eight dimensions are a master set for those in lower dimensions. By considering gauge fields propagating on these self-dual manifolds and embedding the spin connection in the gauge connection, solutions to the D-dimensional equations for self-dual Yang-Mills fields are found. We show that the Yang-Mills action on such manifolds is topologically bounded from below, with the bound saturated precisely when the Yang-Mills field is self-dual. These results have a natural interpretation in supersymmetric string theory.Comment: 9 pages, Latex, factors in eqn. (6) corrected, acknowledgement and reference added, typos fixe

Climate Change Impacts on Freshwater Wetland Hydrology and Vegetation Cover Cycling Along a Regional Aridity Gradient

Global mean temperature may increase up to 6°C by the end of this century and together with precipitation change may steepen regional aridity gradients. The hydrology, productivity, and ecosystem services from freshwater wetlands depend on their future water balance. We simulated the hydrology and vegetation dynamics of wetland complexes in the North American Prairie Pothole Region with the WETLANDSCAPE model. Simulations for 63 precipitation × temperature combinations spanning 6°C warming and −20% to +20% annual precipitation change at 19 locations along a mid-continental aridity gradient showed that aridity explained up to 99% of the variation in wetland stage and hydroperiod for all wetland permanence types, and in vegetation cycling for semipermanent wetlands. The magnitude and direction of hydrologic responses depended on whether climate changes increased or decreased water deficits. Warming to 6°C and 20% less precipitation increased wetland water deficits and more strongly decreased wetland stage and hydroperiod from historic levels at low aridity, especially in semipermanent wetlands, where peak vegetation cycling (Cover Cycle Index, CCI) also shifted to lower aridity. In contrast, 20% more precipitation decreased water deficits, increasing wetland stage and hydroperiod most strongly in shallow wetlands at high aridity, but filling semipermanent wetlands and reducing CCI at low aridity. All climate changes narrowed the range of aridity favorable to high productivity. Climate changes that reduce water deficits may help maintain wetlands at high aridity at the expense of those at low aridity, but with warming certain, increased deficits are more likely and will help maintain wetlands at lower aridity but exacerbate loss of wetlands at high aridity. Thus, there is likely not a universally applicable approach to mitigating climate change impacts on freshwater wetlands across regional aridity gradients. Conservation strategies need to account for aridity-specific effects of climate change on freshwater wetland ecosystems

Two-band random matrices

Spectral correlations in unitary invariant, non-Gaussian ensembles of large random matrices possessing an eigenvalue gap are studied within the framework of the orthogonal polynomial technique. Both local and global characteristics of spectra are directly reconstructed from the recurrence equation for orthogonal polynomials associated with a given random matrix ensemble. It is established that an eigenvalue gap does not affect the local eigenvalue correlations which follow the universal sine and the universal multicritical laws in the bulk and soft-edge scaling limits, respectively. By contrast, global smoothed eigenvalue correlations do reflect the presence of a gap, and are shown to satisfy a new universal law exhibiting a sharp dependence on the odd/even dimension of random matrices whose spectra are bounded. In the case of unbounded spectrum, the corresponding universal `density-density' correlator is conjectured to be generic for chaotic systems with a forbidden gap and broken time reversal symmetry.Comment: 12 pages (latex), references added, discussion enlarge

Active Amplification of the Terrestrial Albedo to Mitigate Climate Change: An Exploratory Study

This study explores the potential to enhance the reflectance of solar insolation by the human settlement and grassland components of the Earth's terrestrial surface as a climate change mitigation measure. Preliminary estimates derived using a static radiative transfer model indicate that such efforts could amplify the planetary albedo enough to offset the current global annual average level of radiative forcing caused by anthropogenic greenhouse gases by as much as 30 percent or 0.76 W/m2. Terrestrial albedo amplification may thus extend, by about 25 years, the time available to advance the development and use of low-emission energy conversion technologies which ultimately remain essential to mitigate long-term climate change. However, additional study is needed to confirm the estimates reported here and to assess the economic and environmental impacts of active land-surface albedo amplification as a climate change mitigation measure.Comment: 21 pages, 3 figures. In press with Mitigation and Adaptation Strategies for Global Change, Springer, N

The soil and plant biogeochemistry sampling design for The National Ecological Observatory Network

Human impacts on biogeochemical cycles are evident around the world, from changes to forest structure and function due to atmospheric deposition, to eutrophication of surface waters from agricultural effluent, and increasing concentrations of carbon dioxide (CO2) in the atmosphere. The National Ecological Observatory Network (NEON) will contribute to understanding human effects on biogeochemical cycles from local to continental scales. The broad NEON biogeochemistry measurement design focuses on measuring atmospheric deposition of reactive mineral compounds and CO2 fluxes, ecosystem carbon (C) and nutrient stocks, and surface water chemistry across 20 eco‐climatic domains within the United States for 30 yr. Herein, we present the rationale and plan for the ground‐based measurements of C and nutrients in soils and plants based on overarching or “high‐level” requirements agreed upon by the National Science Foundation and NEON. The resulting design incorporates early recommendations by expert review teams, as well as recent input from the larger natural sciences community that went into the formation and interpretation of the requirements, respectively. NEON\u27s efforts will focus on a suite of data streams that will enable end‐users to study and predict changes to biogeochemical cycling and transfers within and across air, land, and water systems at regional to continental scales. At each NEON site, there will be an initial, one‐time effort to survey soil properties to 1 m (including soil texture, bulk density, pH, baseline chemistry) and vegetation community structure and diversity. A sampling program will follow, focused on capturing long‐term trends in soil C, nitrogen (N), and sulfur stocks, isotopic composition (of C and N), soil N transformation rates, phosphorus pools, and plant tissue chemistry and isotopic composition (of C and N). To this end, NEON will conduct extensive measurements of soils and plants within stratified random plots distributed across each site. The resulting data will be a new resource for members of the scientific community interested in addressing questions about long‐term changes in continental‐scale biogeochemical cycles, and is predicted to inspire further process‐based research

Use of FLUXNET in the Community Land Model development

The Community Land Model version 3 (CLM3.0) simulates land-atmosphere exchanges in response to climatic forcings. CLM3.0 has known biases in the surface energy partitioning as a result of deficiencies in its hydrological and biophysical parameterizations. Such models, however, need to be robust for multidecadal global climate simulations. FLUXNET now provides an extensive data source of carbon, water and energy exchanges for investigating land processes, and it encompasses a global range of ecosystem-climate interactions. Data from 15 FLUXNET sites are used to identify and improve model deficiencies. Including a prognostic aquifer, a bare soil evaporation resistance formulation and numerous other changes in the model result in a significantly improved soil hydrology and energy partitioning. Terrestrial water storage increased by up to 300 mm in warm climates and decreased in cold climates. Nitrogen control of photosynthesis is revealed as another missing process in the model. These improvements increase the correlation coefficient of hourly and monthly latent heat fluxes from a range of 0.5–0.6 to the range of 0.7–0.9. RMSE of the simulated sensible heat fluxes decrease by 20–50%. Primary production is overestimated during the wet season in mediterranean and tropical ecosystems. This might be related to missing carbon-nitrogen dynamics as well as to site-specific parameters. The new model (CLM3.5) with an improved terrestrial water cycle should lead to more realistic land-atmosphere exchanges in coupled simulations. FLUXNET is found to be a valuable tool to develop and validate land surface models prior to their application in computationally expensive global simulations

Integrating microbial physiology and physio-chemical principles in soils with the MIcrobial-MIneral Carbon Stabilization (MIMICS) model

A growing body of literature documents the pressing need to develop soil biogeochemistry models that more accurately reflect contemporary understanding of soil processes and better capture soil carbon (C) responses to environmental perturbations. Models that explicitly represent microbial activity offer inroads to improve representations of soil biogeochemical processes, but have yet to consider relationships between litter quality, functional differences in microbial physiology, and the physical protection of microbial byproducts in forming stable soil organic matter (SOM). To address these limitations, we introduce the MIcrobial-MIneral Carbon Stabilization (MIMICS) model, and evaluate it by comparing site-level soil C projections with observations from a long-term litter decomposition study and soil warming experiment. In MIMICS, the turnover of litter and SOM pools is governed by temperature-sensitive Michaelis–Menten kinetics and the activity of two physiologically distinct microbial functional types. The production of microbial residues through microbial turnover provides inputs to SOM pools that are considered physically or chemically protected. Soil clay content determines the physical protection of SOM in different soil environments. MIMICS adequately simulates the mean rate of leaf litter decomposition observed at temperate and boreal forest sites, and captures observed effects of litter quality on decomposition rates. Moreover, MIMICS better captures the response of SOM pools to experimental warming, with rapid SOM losses but declining temperature sensitivity to long-term warming, compared with a more conventional model structure. MIMICS incorporates current microbial theory to explore the mechanisms by which litter C is converted to stable SOM, and to improve predictions of soil C responses to environmental change

Protecting climate with forests

Policies for climate mitigation on land rarely acknowledge biophysical factors, such as reflectivity, evaporation, and surface roughness. Yet such factors can alter temperatures much more than carbon sequestration does, and often in a conflicting way. We outline a framework for examining biophysical factors in mitigation policies and provide some best-practice recommendations based on that framework. Tropical projects-avoided deforestation, forest restoration, and afforestation-provide the greatest climate value, because carbon storage and biophysics align to cool the Earth. In contrast, the climate benefits of carbon storage are often counteracted in boreal and other snow-covered regions, where darker trees trap more heat than snow does. Managers can increase the climate benefit of some forest projects by using more reflective and deciduous species and through urban forestry projects that reduce energy use. Ignoring biophysical interactions could result in millions of dollars being invested in some mitigation projects that provide little climate benefit or, worse, are counter-productive