Forrest M. Hoffman

The Community Land Model and Its Climate Statistics as a Component of the Community Climate System Model

Abstract Several multidecadal simulations have been carried out with the new version of the Community Climate System Model (CCSM). This paper reports an analysis of the land component of these simulations. Global annual averages over land appear to be within the uncertainty of observational datasets, but the seasonal cycle over land of temperature and precipitation appears to be too weak. These departures from observations appear to be primarily a consequence of deficiencies in the simulation of the atmospheric model rather than of the land processes. High latitudes of northern winter are biased sufficiently warm to have a significant impact on the simulated value of global land temperature. The precipitation is approximately doubled from what it should be at some locations, and the snowpack and spring runoff are also excessive. The winter precipitation over Tibet is larger than observed. About two-thirds of this precipitation is sublimated during the winter, but what remains still produces a snowpack tha...

A continental strategy for the national ecological observatory network

O ne of the great realizations of the past half-century in both biological and Earth sciences is that, throughout geologic time, life has been shaping the Earths surface and regulating the chemistry of its oceans and atmosphere (eg Berkner and Marshall 1964). In the present Anthropocene Era (Crutzen and Steffen 2003; Ruddiman 2003), humanity is directly shaping the bios-phere and physical environment, triggering potentially devastating and currently unpredictable consequences (Doney and Schimel 2007). While subtle interactions between the Earths orbit, ocean circulation, and the biosphere have dominated climate feedbacks for eons, now human perturbations to the cycles of CO 2 , other trace gases, and aerosols regulate the pace of climate change. Accompanying the biogeochemical perturbations are the vast changes resulting from biodiversity loss and a profound rearrangement of the biosphere due to species movements and invasions. Scientists and managers of biological resources require a stronger basis for forecasting the consequences of such changes. In this Special Issue of Frontiers, the scientific community confronts the challenge of research and environmental management in a human-dominated, increasingly connected world (Peters et al. p 229). Carbon dioxide, a key driver of climate change produced by a host of local and small-scale processes (eg clearing of forests, extraction and use of fossil fuels), affects the global energy balance (Marshall et al. p 273). Invasive species, though small from a large-scale perspective, nonetheless modify the continental biosphere (Crowl et al. p 238). Aquatic systems are tightly coupled to both terrestrial systems and the marine environment (Hopkinson et al. p 255). Flowing water not only intrinsically creates a highly connected system, but acts a transducer of climate, land-use, and invasive species effects, spreading their impacts from terrestrial and upstream centers of action downstream and into distant systems (Williamson et al. p 247). Human activities such as urbanization create new connections; materials, organisms, and energy flow into cities from globally distributed sources and waste products are exported back into the environment (Grimm et al. p 264). All of the papers in this issue of Frontiers conclude that a new approach to studying the biosphere is required in the present era. In response to this challenge, with the support of the National Science Foundation (NSF), ecologists in the US are planning a National Ecological Observatory Network (NEON). The conceptual design of this network (Field et al. 2006) gives rise to several general questions: (1) How will the ecosystems …

Photoperiodic regulation of the seasonal pattern of photosynthetic capacity and the implications for carbon cycling

Although temperature is an important driver of seasonal changes in photosynthetic physiology, photoperiod also regulates leaf activity. Climate change will extend growing seasons if temperature cues predominate, but photoperiod-controlled species will show limited responsiveness to warming. We show that photoperiod explains more seasonal variation in photosynthetic activity across 23 tree species than temperature. Although leaves remain green, photosynthetic capacity peaks just after summer solstice and declines with decreasing photoperiod, before air temperatures peak. In support of these findings, saplings grown at constant temperature but exposed to an extended photoperiod maintained high photosynthetic capacity, but photosynthetic activity declined in saplings experiencing a naturally shortening photoperiod; leaves remained equally green in both treatments. Incorporating a photoperiodic correction of photosynthetic physiology into a global-scale terrestrial carbon-cycle model significantly improves predictions of seasonal atmospheric CO2 cycling, demonstrating the benefit of such a function in coupled climate system models. Accounting for photoperiod-induced seasonality in photosynthetic parameters reduces modeled global gross primary production 2.5% (∼4 PgC y−1), resulting in a >3% (∼2 PgC y−1) decrease of net primary production. Such a correction is also needed in models estimating current carbon uptake based on remotely sensed greenness. Photoperiod-associated declines in photosynthetic capacity could limit autumn carbon gain in forests, even if warming delays leaf senescence.

Using multivariate clustering to characterize ecoregion borders

The authors present a geographic clustering technique which unambiguously locates, characterizes, and visualizes ecoregions and their borders. When coded with similarity colors, it can produce planar map views with sharpness contours that are visually rich in ecological information and represent integrated visualizations of complex and massive environmental data sets.

Preindustrial-Control and Twentieth-Century Carbon Cycle Experiments with the Earth System Model CESM1(BGC)

Version1oftheCommunityEarth SystemModel, in theconfigurationwhereitsfullcarboncycleis enabled, is introduced and documented. In this configuration, the terrestrial biogeochemical model, which includes carbon‐ nitrogen dynamics and is present in earlier model versions, is coupled to an ocean biogeochemical model and atmospheric CO2 tracers. The authors provide a description of the model, detail how preindustrial-control and twentieth-century experimentswere initialized andforced, and examine thebehavior of the carbon cyclein those experiments. They examinehow sea- and land-to-air CO2fluxescontributetotheincreaseofatmosphericCO2in the twentieth century, analyze how atmospheric CO2 and its surface fluxes vary on interannual time scales, including how they respond to ENSO, and describe the seasonal cycle of atmospheric CO2 and its surfacefluxes. While the model broadly reproduces observed aspects of the carbon cycle, there are several notable biases, including having too large of an increase in atmospheric CO2 over the twentieth century and too small of a seasonal cycle of atmospheric CO2 in the Northern Hemisphere. The biases are related to a weak response of the carbon cycle to climatic variations on interannual and seasonal time scales and to twentieth-century anthropogenic forcings, including rising CO2, land-use change, and atmospheric deposition of nitrogen.

Global Latitudinal-Asymmetric Vegetation Growth Trends and Their Driving Mechanisms: 1982–2009

Using a recent Leaf Area Index (LAI) dataset and the Community Land Model version 4 (CLM4), we investigated percent changes and controlling factors of global vegetation growth for the period 1982 to 2009. Over that 28-year period, both the remote-sensing estimate and model simulation show a significant increasing trend in annual vegetation growth. Latitudinal asymmetry appeared in both products, with small increases in the Southern Hemisphere (SH) and larger increases at high latitudes in the Northern Hemisphere (NH). The south-to-north asymmetric land surface warming was assessed to be the principal driver of this latitudinal asymmetry of LAI trend. Heterogeneous precipitation functioned to decrease this latitudinal LAI gradient, and considerably regulated the local LAI change. A series of factorial experiments were specially-designed to isolate and quantify contributions to LAI trend from different external forcings such as climate variation, CO2, nitrogen deposition and land use and land cover change. The climate-only simulation confirms that climate change, particularly the asymmetry of land temperature variation, can explain the latitudinal pattern of LAI change. CO2 fertilization during the last three decades was simulated to be the dominant cause for the enhanced vegetation growth. Our study, though limited by observational and modeling uncertainties, adds further insight into vegetation growth trends and environmental correlations. These validation exercises also provide new quantitative and objective metrics for evaluation of land ecosystem process models at multiple spatio-temporal scales.

A Fractal Landscape Realizer for Generating Synthetic Maps

A fractal landscape realizer has been developed that generates synthetic landscape maps to user specifications. The alternative landscape realizations are not identical to the actual maps after which they are patterned, but are similar statistically (i.e., the areas and fractal character of each category are replicated). A fractal or self-affine pattern generator is used to provide a spatial probability surface for each category in the synthetic map. The Fractal Realizer arbitrates contentions among categories in a way that makes it possible to preserve the fractal patterns of all the categories in the resulting synthetic landscape. Each synthetic landscape is one equally likely realization from among an infinite ensemble of possible fractal landscape combinations. Synthetic landscapes produced by the Fractal Realizer have been tested using a variant of the Turing Test. More than 100 map experts were presented with a series of 20 selections of paired maps, and asked to distinguish the real map from the synthetic realization. The resulting population of scores was not significantly different from a random binomial, suggesting that the experts were unable to discern the synthetic maps from the actual ones. Statistical landscape indices computed for 25 different synthetic realizations are compared with the values computed for the actual maps. The Fractal Realizer can be used as a stochastic generator of synthetic input maps to a spatially explicit simulation model to test the effects of landscape rearrangement on the uncertainty of model parameter estimates. The sensitivity of stochastic spatial simulations to prescribed input landscapes can be evaluated by supplying them with a series of synthetic maps that obey particular statistical characteristics and by monitoring changes in selected output responses. Statistically similar input landscapes with different spatial arrangements can be generated and supplied to spatial models as a hedge against pseudoreplication.

Causes and implications of persistent atmospheric carbon dioxide biases in Earth System Models

The strength of feedbacks between a changing climate and future CO2 concentrations is uncertain and difficult to predict using Earth System Models (ESMs). We analyzed emission-driven simulations—in which atmospheric CO2levels were computed prognostically—for historical (1850–2005) and future periods (Representative Concentration Pathway (RCP) 8.5 for 2006–2100) produced by 15 ESMs for the Fifth Phase of the Coupled Model Intercomparison Project (CMIP5). Comparison of ESM prognostic atmospheric CO2 over the historical period with observations indicated that ESMs, on average, had a small positive bias in predictions of contemporary atmospheric CO2. Weak ocean carbon uptake in many ESMs contributed to this bias, based on comparisons with observations of ocean and atmospheric anthropogenic carbon inventories. We found a significant linear relationship between contemporary atmospheric CO2 biases and future CO2levels for the multimodel ensemble. We used this relationship to create a contemporary CO2 tuned model (CCTM) estimate of the atmospheric CO2 trajectory for the 21st century. The CCTM yielded CO2estimates of 600±14 ppm at 2060 and 947±35 ppm at 2100, which were 21 ppm and 32 ppm below the multimodel mean during these two time periods. Using this emergent constraint approach, the likely ranges of future atmospheric CO2, CO2-induced radiative forcing, and CO2-induced temperature increases for the RCP 8.5 scenario were considerably narrowed compared to estimates from the full ESM ensemble. Our analysis provided evidence that much of the model-to-model variation in projected CO2 during the 21st century was tied to biases that existed during the observational era and that model differences in the representation of concentration-carbon feedbacks and other slowly changing carbon cycle processes appear to be the primary driver of this variability. By improving models to more closely match the long-term time series of CO2from Mauna Loa, our analysis suggests that uncertainties in future climate projections can be reduced.

Plant responses to increasing CO2 reduce estimates of climate impacts on drought severity

Significance We show that the water savings that plants experience under high CO2 conditions compensate for much of the effect of warmer temperatures, keeping the amount of water on land, on average, higher than we would predict with common drought metrics, and with a different spatial pattern. The implications of plants needing less water under high CO2 reaches beyond drought prediction to the assessment of climate change impacts on agriculture, water resources, wildfire risk, and vegetation dynamics. Rising atmospheric CO2 will make Earth warmer, and many studies have inferred that this warming will cause droughts to become more widespread and severe. However, rising atmospheric CO2 also modifies stomatal conductance and plant water use, processes that are often are overlooked in impact analysis. We find that plant physiological responses to CO2 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 CO2 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 CO2, including direct use of P-E and soil moisture from ESMs, is needed to reduce uncertainties in future assessment.

New analysis reveals representativeness of the AmeriFlux network

The AmeriFlux network of eddy flux covariance towers was established to quantify variation in carbon dioxide and water vapor exchange between terrestrial ecosystems and the atmosphere, and to understand the underlying mechanisms responsible for observed fluxes and carbon pools. The network is primarily funded by the U.S. Department of Energy, NASA, the National Oceanic and Atmospheric Administration, and the National Science Foundation. Similar regional networks elsewhere in the world—for example, CarboEurope, AsiaFlux, OzFlux, and Fluxnet Canada—participate in synthesis activities across larger geographic areas [Baldocchi et al., 2001; Law et al., 2002].