CGD's Dr. David Schimel

Abstract

Over a range of geological and historical timescales, warmer climate conditions are associated with higher atmospheric levels of CO₂, an important climate-modulating greenhouse gas. Coupled carbon-climate interactions have the potential to introduce both stabilizing and destabilizing feedback loops into Earth's system. Here we bring together evidence on the dominant climate, biogeochemical and geological processes organized by timescale, spanning interannual to centennial climate variability, Holocene millennial variations and Pleistocene glacial-interglacial cycles, and million-year and longer variations over the Precambrian and Phanerozoic. Our focus is characterizing, and where possible quantifying, internal coupled carbon-cliamte system dynamics and responses to external forcing from tectonics, orbital dynamics, catastrophic events, and anthropogenic fossil-fuel emissions. One emergent property is clear across timescales; atmospheric CO₂ can increase quickly, but the return to lower levels through natural processes is much slower. The consequences of human carbon cycle perturbations will far outlive the emissions that caused them.

Figure caption: Schematic introducing the magnitude of atmospheric CO₂ perturbations (ppm) against approximate timescale (years) for various climate process. The axes are plotted on a logarithmic scale. Abbreviation: ENSO, el Ni&n241;o-Southern Oscillation.

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Zobitz, J.M., D. Moore, W.J. Sacks, R.K. Monson, D.R. Bowling, and D.S. Schimel, 2007: Integration of process-based soil respiration models with whole-ecosystem CO₂ measurements. ? in review.

Abstract

We integrated soil models with an established ecosystem process model (SIPNET, simplified photosynthesis and evapotranspiration model) to investigate the influence of soil processes on modeled values of soil CO₂ fluxes (R_soil). Model parameters were determined from literature values and a data assimilation routine that utilized a seven-year record of the net ecosystem exchange of CO₂ and environmental variables collected at a high-elevation subalpine forest (the Niwot Ridge AmeriFlux site). These soil models were subsequently evaluated in how they estimated the seasonal contribution of R_soil to total ecosystem respiration (TER) and the seasonal contribution of root respiration (R_root) to R_soil. Additionally, these soil models were compared to data assimilation output of empirical (non-biological) models of soil heterotrphic respiration.

Explicit modeling of root dynamics led to better agreement with literature values of the contribution of R_soil to TER. Estimates of R_soil/TER when root dynamics were considered ranged from 0.3-0.6; without modeling root biomass dynamics these values were 0.1-0.3. Hence we conclude that modeling of root biomass dynamics is critically important to model the R_soil/TER ratio correctly. When soil heterotrophic respiration was dependent on simplistic functions of temperature and moisture independent of soil carbon pool size, worse model-data fits were produced. This justifies the choice of biological, rather than empirical, models of soil processes.

Adding additional complexity to the soil pool improved the model-data fit from the base model, but issues remained. The soil models wre not successful in modeling R_root/R_soil. This is partially attributable to estimated turnover parameters of soil carbon pools not agreeing with expected values from literature and being poorly constrained by the parameter estimation routine. We conclude that net ecosystem exchange of CO₂ alone cannot constrain specific rhizospheric and microbial components of soil respiration. Reasons for this include inability of the data assimilation routine to constrain soil parameters using ecosystem CO₂ flux measurements and not considering the effect of other resource limitations (e.g., nitrogen) on the microbe biomass. Future data assimilation studies with these models should include ecosystem-scale measurements of R_soil in the parameter estimation routine and experimentally determine soil model parameters not constrained by the parameter estimation routine.

Figure caption: Comparisons of measured and modeled cumulative NEE. Panel a) shows comparison among twice-daily values of measured NEE and modeled NEE for the Roots model. Simlar results for the other model variants were obtained. Panel b) shows the difference between measured and modeled values of cumulative NEE for each of the model variants. Gray-shaded panels in both plots represent the optimization period of fluxes used to estimate model parameters. Positive values indicate that the model is producing more negative values of NEE than measurements.

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Ammann, C.M., F. Joos, D.S. Schimel, B.L. Otto-Bliesner, and R.A. Tomas, 2007: Solar influence on climate during the past millennium: results from transient simulations with the NCAR Climate System Model, Proc. National Academy Sci., 104, 3713-3718.

Abstract

The potential role of solar variations in modulating recent climate has been debated for many decades and recent papers suggest that solar forcing may be less than previously believed. Because solar variability before the satellite period must be scaled from proxy data, large uncertainty exists about phase and magnitude of the forcing. We used a coupled climate system model to determine whether proxy-based irradiance series are capable of inducing climatic variations that resemble variations found in climate reconstructions, and if part of the previously estimated large range of past solar irradiance changes could be excluded. Transient simulations, covering the published range of solar irradiance estimates, were integrated from 850 AD to the present. Solar forcing as well as volcanic and anthropogenic forcing are detectable in the model results despite internal variability. The resulting climates are generally consistent with temperature reconstructions. Smaller, rather than larger, long-term trends in solar irradiance appear more plausible and produced modeled climates in better agreement with the range of Northern Hemisphere temperature proxy records both with respect to phase and magnitude. Despite the direct response of the model to solar forcing, even large solar irradiance change combined with realistic volcanic forcing over past centuries could not explain the late 20th century warming without inclusion of greenhouse gas forcing. Although solar and volcanic effects appear to dominate most of the slow climate variations within the past thousand years, the impacts of greenhouse gases have dominated since the second half of the last century

Figure caption: Comparison of NCAR CSM simulations with proxy reconstructions and instrumental data. (a) Reconstructed NH average surface temperature anomalies over the past millennium. All series are as published originally and no additional scaling has been performed, but annual records have been smoothed with a 50-year-long Gaussian filter. All series are relative to 1901-1960 averages computed from original data. (b) Northern hemisphere surface temperature from the low- (green), medium- (red), and high-scaled (blue) solar forcing simulations compared with the range spanned by the annual proxy-based reconstructions. This range does not include a systematic error analysis, it only illustrates the current debate regarding the amplitude of hemispheric multidecadal to century-scale temperature variations of the past. (c) Simulated versus the instrumental (gray) record of global average surface temperature (gray, thick solid line). The time series of the low (green), medium (red), and high (blue) solar forcing experiments were smoothed by using an 11-year Gaussian filter. Anthropogenic forcings were included in the primary experiments (solid lines) but held at 1870 AD conditions in 1870-2000 AD branch experiments (dashed lines). See publication for references.