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Peter E. Thornton and Niklaus E. Zimmermann

Abstract

A new logical framework relating the structural and functional characteristics of a vegetation canopy is presented, based on the hypothesis that the ratio of leaf area to leaf mass (specific leaf area) varies linearly with overlying leaf area index within the canopy. Measurements of vertical gradients in specific leaf area and leaf carbon:nitrogen ratio for five species (two deciduous and three evergreen) in a temperate climate support this hypothesis. This new logic is combined with a two-leaf (sunlit and shaded) canopy model to arrive at a new canopy integration scheme for use in the land surface component of a climate system model. An inconsistency in the released model radiation code is identified and corrected. Also introduced here is a prognostic canopy model with coupled carbon and nitrogen cycle dynamics. The new scheme is implemented within the Community Land Model and tested in both diagnostic and prognostic canopy modes. The new scheme increases global gross primary production by 66% (from 65 to 108 Pg carbon yr−1) for diagnostic model simulations driven with reanalysis surface weather, with similar results (117 PgC yr−1) for the new prognostic model. Comparison of model predictions to global syntheses of observations shows generally good agreement for net primary productivity (NPP) across a range of vegetation types, with likely underestimation of NPP in tundra and larch communities. Vegetation carbon stocks are higher than observed in forest systems, but the ranking of stocks by vegetation type is accurately captured.

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Jiafu Mao, Xiaoying Shi, Lijuan Ma, Dale P. Kaiser, Qingxiang Li, and Peter E. Thornton

Abstract

Using a recently homogenized observational daily maximum (T MAX) and minimum temperature (T MIN) dataset for China, the extreme temperatures from the 40-yr ECMWF Re-Analysis (ERA-40), the Japanese 25-year Reanalysis (JRA-25), the NCEP/Department of Energy Global Reanalysis 2 (NCEP-2), and the ECMWF’s ERA-Interim (ERAIn) reanalyses for summer (June–August) and winter (December–February) are assessed by probability density functions for the periods 1979–2001 and 1990–2001. For 1979–2001, no single reanalysis appears to be consistently accurate across eight areas examined over China. The ERA-40 and JRA-25 reanalyses show similar representations and close skill scores over most of the regions of China for both seasons. NCEP-2 generally has lower skill scores, especially over regions with complex topography. The regional and seasonal differences identified are commonly associated with different geographical locations and the methods used to diagnose these quantities. All the selected reanalysis products exhibit better performance for winter compared to summer over most regions of China. The T MAX values from the reanalysis tend to be systematically underestimated, while T MIN is systematically closer to observed values than T MAX. Comparisons of the reanalyses to reproduce the 99.7 percentiles for T MAX and 0.3 percentiles for T MIN show that most reanalyses tend to underestimate the 99.7 percentiles in maximum temperature both in summer and winter. For the 0.3 percentiles in T MIN, NCEP-2 is relatively inaccurate with a −12°C cold bias over the Qinghai–Tibetan Plateau in winter. ERA-40 and JRA-25 generally overestimate the extreme T MIN, and the extreme percentage differences of ERA-40 and JRA-25 are quite similar over all of the regions. The results are generally similar for 1990–2001, but in contrast to the other three reanalysis products the newly released ERAIn is very reasonable, especially for wintertime T MIN, with a skill score greater than 0.83 for each region of China. This demonstrates the great potential of this product for use in future impact assessments on continental scales where those impacts are based on extreme temperatures.

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Michael A. White, Peter E. Thornton, Steven W. Running, and Ramakrishna R. Nemani

Abstract

Ecosystem simulation models use descriptive input parameters to establish the physiology, biochemistry, structure, and allocation patterns of vegetation functional types, or biomes. For single-stand simulations it is possible to measure required data, but as spatial resolution increases, so too does data unavailability. Generalized biome parameterizations are then required. Undocumented parameter selection and unknown model sensitivity to parameter variation for larger-resolution simulations are currently the major limitations to global and regional modeling. The authors present documented input parameters for a process-based ecosystem simulation model, BIOME–BGC, for major natural temperate biomes. Parameter groups include the following: turnover and mortality; allocation; carbon to nitrogen ratios (C:N); the percent of plant material in labile, cellulose, and lignin pools; leaf morphology; leaf conductance rates and limitations; canopy water interception and light extinction; and the percent of leaf nitrogen in Rubisco (ribulose bisphosphate-1,5-carboxylase/oxygenase) (PLNR). Using climatic and site description data from the Vegetation/Ecosystem Modeling and Analysis Project, the sensitivity of predicted annual net primary production (NPP) to variations in parameter level of ± 20% of the mean value was tested. For parameters exhibiting a strong control on NPP, a factorial analysis was conducted to test for interaction effects. All biomes were affected by variation in leaf and fine root C:N. Woody biomes were additionally strongly controlled by PLNR, maximum stomatal conductance, and specific leaf area while nonwoody biomes were sensitive to fire mortality and litter quality. None of the critical parameters demonstrated strong interaction effects. An alternative parameterization scheme is presented to better represent the spatial variability in several of these critical parameters. Patterns of general ecological function drawn from the sensitivity analysis are discussed.

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David M. Lawrence, Peter E. Thornton, Keith W. Oleson, and Gordon B. Bonan

Abstract

Although the global partitioning of evapotranspiration (ET) into transpiration, soil evaporation, and canopy evaporation is not well known, most current land surface schemes and the few available observations indicate that transpiration is the dominant component on the global scale, followed by soil evaporation and canopy evaporation. The Community Land Model version 3 (CLM3), however, does not reflect this global view of ET partitioning, with soil evaporation and canopy evaporation far outweighing transpiration. One consequence of this unrealistic ET partitioning in CLM3 is that photosynthesis, which is linked to transpiration through stomatal conductance, is significantly underestimated on a global basis. A number of modifications to CLM3 vegetation and soil hydrology parameterizations are described that improve ET partitioning and reduce an apparent dry soil bias in CLM3. The modifications reduce canopy interception and evaporation, reduce soil moisture stress on transpiration, increase transpiration through a more realistic canopy integration scheme, reduce within-canopy soil evaporation, eliminate lateral drainage of soil water, increase infiltration of water into the soil, and increase the vertical redistribution of soil water. The partitioning of ET is improved, with notable increases seen in transpiration (13%–41% of global ET) and photosynthesis (65–148 Pg C yr−1). Soils are wetter and exhibit a far more distinct soil moisture annual cycle and greater interseasonal soil water storage, which permits plants to sustain transpiration through the dry season.

The broader influences of improved ET partitioning on land–atmosphere interaction are diverse. Stronger transpiration and reduced canopy evaporation yield an extended ET response to rain events and a shift in the precipitation distribution toward more frequent small- to medium-size rain events. Soil moisture memory time scales decrease particularly at deeper soil levels. Subsurface soil moisture exerts a slightly greater influence on precipitation. These results indicate that partitioning of ET is an important responsibility for land surface schemes, a responsibility that will gain in relevance as GCMs evolve to incorporate ever more complex treatments of the earth’s carbon and hydrologic cycles.

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Jiafu Mao, Peter E. Thornton, Xiaoying Shi, Maosheng Zhao, and Wilfred M. Post

Abstract

Remote sensing can provide long-term and large-scale products helpful for ecosystem model evaluation. The authors compare monthly gross primary production (GPP) simulated by the Community Land Model, version 4 (CLM4) at a half-degree resolution with satellite estimates of GPP from the Moderate Resolution Imaging Spectroradiometer (MODIS) GPP product (MOD17) for the 10-yr period January 2000–December 2009. The assessment is presented in terms of long-term mean carbon assimilation, seasonal mean distributions, amplitude and phase of the annual cycle, and intraannual and interannual GPP variability and their responses to climate variables. For the long-term annual and seasonal means, major GPP patterns are clearly demonstrated by both products. Compared to the MODIS product, CLM4 overestimates the magnitude of GPP for tropical evergreen forests. CLM4 has a longer carbon uptake period than MODIS for most plant functional types (PFTs) with an earlier onset of GPP in spring and a later decline of GPP in autumn. Empirical orthogonal function analysis of the monthly GPP changes indicates that, on the intraannual scale, both CLM4 and MODIS display similar spatial representations and temporal patterns for most terrestrial ecosystems except in northeast Russia and in the very dry region of central Australia. For 2000–09, CLM4 simulated increases in annual averaged GPP over both hemispheres; however, estimates from MODIS suggest a reduction in the Southern Hemisphere (−0.2173 PgC yr−1), balancing the significant increase over the Northern Hemisphere (0.2157 PgC yr−1). The evaluations highlight strengths and weaknesses of the CLM4 primary production and illuminate potential improvements and developments.

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Robert E. Dickinson, Keith W. Oleson, Gordon Bonan, Forrest Hoffman, Peter Thornton, Mariana Vertenstein, Zong-Liang Yang, and Xubin Zeng

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 that is very large compared to that observed with correspondingly excessive spring runoff. A large cold anomaly over the Sahara Desert and Sahel also appears to be a consequence of a large anomaly in downward longwave radiation; low column water vapor appears to be most responsible. The modeled precipitation over the Amazon basin is low compared to that observed, the soil becomes too dry, and the temperature is too warm during the dry season.

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Samuel Levis, Gordon B. Bonan, Erik Kluzek, Peter E. Thornton, Andrew Jones, William J. Sacks, and Christopher J. Kucharik

Abstract

The Community Earth System Model, version 1 (CESM1) is evaluated with two coupled atmosphere–land simulations. The CTRL (control) simulation represents crops as unmanaged grasses, while CROP represents a crop managed simulation that includes special algorithms for midlatitude corn, soybean, and cereal phenology and carbon allocation. CROP has a more realistic leaf area index (LAI) for crops than CTRL. CROP reduces winter LAI and represents the spring planting and fall harvest explicitly. At the peak of the growing season, CROP simulates higher crop LAI. These changes generally reduce the latent heat flux but not around peak LAI (late spring/early summer). In midwestern North America, where corn, soybean, and cereal abundance is high, simulated peak summer precipitation declines and agrees better with observations, particularly when crops emerge late as is found from a late planting sensitivity simulation (LateP). Differences between the CROP and LateP simulations underscore the importance of simulating crop planting and harvest dates correctly. On the biogeochemistry side, the annual cycle of net ecosystem exchange (NEE) also improves in CROP relative to Ameriflux site observations. For a global perspective, the authors diagnose annual cycles of CO2 from the simulated NEE (CO2 is not prognostic in these simulations) and compare against representative GLOBALVIEW monitoring stations. The authors find an increased (thus also improved) amplitude of the annual cycle in CROP. These regional and global-scale refinements from improvements in the simulated plant phenology have promising implications for the development of the CESM and particularly for simulations with prognostic atmospheric CO2.

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Peter J. Lawrence, Johannes J. Feddema, Gordon B. Bonan, Gerald A. Meehl, Brian C. O’Neill, Keith W. Oleson, Samuel Levis, David M. Lawrence, Erik Kluzek, Keith Lindsay, and Peter E. Thornton

Abstract

To assess the climate impacts of historical and projected land cover change in the Community Climate System Model, version 4 (CCSM4), new time series of transient Community Land Model, version 4 (CLM4) plant functional type (PFT) and wood harvest parameters have been developed. The new parameters capture the dynamics of the Coupled Model Intercomparison Project phase 5 (CMIP5) land cover change and wood harvest trajectories for the historical period from 1850 to 2005 and for the four representative concentration pathway (RCP) scenarios from 2006 to 2100. Analysis of the biogeochemical impacts of land cover change in CCSM4 reveals that the model produced a historical cumulative land use flux of 127.7 PgC from 1850 to 2005, which is in general agreement with other global estimates of 156 PgC for the same period. The biogeophysical impacts of the transient land cover change parameters were cooling of the near-surface atmosphere over land by −0.1°C, through increased surface albedo and reduced shortwave radiation absorption. When combined with other transient climate forcings, the higher albedo from land cover change was counteracted by decreasing snow albedo from black carbon deposition and high-latitude warming. The future CCSM4 RCP simulations showed that the CLM4 transient PFT parameters can be used to represent a wide range of land cover change scenarios. In the reforestation scenario of RCP 4.5, CCSM4 simulated a drawdown of 67.3 PgC from the atmosphere into the terrestrial ecosystem and product pools. By contrast the RCP 8.5 scenario with deforestation and high wood harvest resulted in the release of 30.3 PgC currently stored in the ecosystem.

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Keith Lindsay, Gordon B. Bonan, Scott C. Doney, Forrest M. Hoffman, David M. Lawrence, Matthew C. Long, Natalie M. Mahowald, J. Keith Moore, James T. Randerson, and Peter E. Thornton

Abstract

Version 1 of the Community Earth System Model, in the configuration where its full carbon cycle is 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 experiments were initialized and forced, and examine the behavior of the carbon cycle in those experiments. They examine how sea- and land-to-air CO2 fluxes contribute to the increase of atmospheric CO2 in 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 surface fluxes. 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.

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Gretchen Keppel-Aleks, James T. Randerson, Keith Lindsay, Britton B. Stephens, J. Keith Moore, Scott C. Doney, Peter E. Thornton, Natalie M. Mahowald, Forrest M. Hoffman, Colm Sweeney, Pieter P. Tans, Paul O. Wennberg, and Steven C. Wofsy

Abstract

Changes in atmospheric CO2 variability during the twenty-first century may provide insight about ecosystem responses to climate change and have implications for the design of carbon monitoring programs. This paper describes changes in the three-dimensional structure of atmospheric CO2 for several representative concentration pathways (RCPs 4.5 and 8.5) using the Community Earth System Model–Biogeochemistry (CESM1-BGC). CO2 simulated for the historical period was first compared to surface, aircraft, and column observations. In a second step, the evolution of spatial and temporal gradients during the twenty-first century was examined. The mean annual cycle in atmospheric CO2 was underestimated for the historical period throughout the Northern Hemisphere, suggesting that the growing season net flux in the Community Land Model (the land component of CESM) was too weak. Consistent with weak summer drawdown in Northern Hemisphere high latitudes, simulated CO2 showed correspondingly weak north–south and vertical gradients during the summer. In the simulations of the twenty-first century, CESM predicted increases in the mean annual cycle of atmospheric CO2 and larger horizontal gradients. Not only did the mean north–south gradient increase due to fossil fuel emissions, but east–west contrasts in CO2 also strengthened because of changing patterns in fossil fuel emissions and terrestrial carbon exchange. In the RCP8.5 simulation, where CO2 increased to 1150 ppm by 2100, the CESM predicted increases in interannual variability in the Northern Hemisphere midlatitudes of up to 60% relative to present variability for time series filtered with a 2–10-yr bandpass. Such an increase in variability may impact detection of changing surface fluxes from atmospheric observations.

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