ALBERT

Description: Approximately 1700 Pg of soil carbon (C) are stored in the northern circumpolar permafrost zone, more than twice as much C than in the atmosphere. The overall amount, rate, and form of C released to the atmosphere in a warmer world will influence the strength of the permafrost C feedback to climate change. We used a survey to quantify variability in the perception of the vulnerability of permafrost C to climate change. Experts were asked to provide quantitative estimates of permafrost change in response to four scenarios of warming. For the highest warming scenario (RCP 8.5), experts hypothesized that C release from permafrost zone soils could be 19–45 Pg C by 2040, 162–288 Pg C by 2100, and 381–616 Pg C by 2300 in CO2 equivalent using 100-year CH4 global warming potential (GWP). These values become 50 % larger using 20-year CH4 GWP, with a third to a half of expected climate forcing coming from CH4 even though CH4 was only 2.3 % of the expected C release. Experts projected that two-thirds of this release could be avoided under the lowest warming scenario (RCP 2.6). These results highlight the potential risk from permafrost thaw and serve to frame a hypothesis about the magnitude of this feedback to climate change. However, the level of emissions proposed here are unlikely to overshadow the impact of fossil fuel burning, which will continue to be the main source of C emissions and climate forcing.

Description: High-resolution predictions of land surface hydrological dynamics are desirable for improved investigations of regional- and watershed-scale processes. Direct deterministic simulations of fine-resolution land surface variables present many challenges, including high computational cost. We therefore propose the use of reduced-order modeling techniques to facilitate emulation of fine-resolution simulations. We use an emulator, Gaussian process regression, to approximate fine-resolution four-dimensional soil moisture fields predicted using a three-dimensional surface-subsurface hydrological simulator (PFLOTRAN). A dimension-reduction technique known as "proper orthogonal decomposition" is further used to improve the efficiency of the resulting reduced-order model (ROM). The ROM reduces simulation computational demand to negligible levels compared to the underlying fine-resolution model. In addition, the ROM that we constructed is equipped with an uncertainty estimate, allowing modelers to construct a ROM consistent with uncertainty in the measured data. The ROM is also capable of constructing statistically equivalent analogs that can be used in uncertainty and sensitivity analyses. We apply the technique to four polygonal tundra sites near Barrow, Alaska that are part of the Department of Energy’s Next-Generation Ecosystem Experiments (NGEE)–Arctic project. The ROM is trained for each site using simulated soil moisture from 1998–2000 and validated using the simulated data for 2002 and 2006. The average relative RMSEs of the ROMs are under 1%.

Description: Permafrost soils contain enormous amounts of organic carbon whose stability is contingent on remaining frozen. With future warming, these soils may release carbon to the atmosphere and act as a positive feedback to climate change. Significant uncertainty remains on the postthaw carbon dynamics of permafrost-affected ecosystems, in particular since most...

Description: This paper reexamines evidence for systematic errors in atmospheric transport models, in terms of the diagnostics used to infer vertical mixing rates from models and observations. Different diagnostics support different conclusions about transport model errors that could imply either stronger or weaker northern terrestrial carbon sinks. Conventional mixing diagnostics are compared to analyzed vertical mixing rates using data from the US Southern Great Plains Atmospheric Radiation Measurement Climate Research Facility, the CarbonTracker data assimilation system based on Transport Model version 5 (TM5), and atmospheric reanalyses. The results demonstrate that diagnostics based on boundary layer depth and vertical concentration gradients do not always indicate the vertical mixing strength. Vertical mixing rates are anti-correlated with boundary layer depth at some sites, diminishing in summer when the boundary layer is deepest. Boundary layer equilibrium concepts predict an inverse proportionality between CO2 vertical gradients and vertical mixing strength, such that previously reported discrepancies between observations and models most likely reflect overestimated as opposed to underestimated vertical mixing. However, errors in seasonal concentration gradients can also result from errors in modeled surface fluxes. This study proposes using the timescale for approach to boundary layer equilibrium to diagnose vertical mixing independently of seasonal surface fluxes, with applications to observations and model simulations of CO2 or other conserved boundary layer tracers with surface sources and sinks. Results indicate that frequently cited discrepancies between observations and inverse estimates do not provide sufficient proof of systematic errors in atmospheric transport models. Some previously hypothesized transport model biases, if found and corrected, could cause inverse estimates to further diverge from carbon inventory estimates of terrestrial sinks.

Description: Terrestrial net CH4 surface fluxes often represent the difference between much larger gross production and consumption fluxes and depend on multiple physical, biological, and chemical mechanisms that are poorly understood and represented in regional- and global-scale biogeochemical models. To characterize uncertainties, study feedbacks between CH4 fluxes and climate, and to guide future model development and experimentation, we developed and tested a new CH4 biogeochemistry model (CLM4Me) integrated in the land component (Community Land Model; CLM4) of the Community Earth System Model (CESM1). CLM4Me includes representations of CH4 production, oxidation, aerenchymous transport, ebullition, aqueous and gaseous diffusion, and fractional inundation. As with most global models, CLM4Me lacks important features for predicting current and future CH4 fluxes, including: vertical representation of soil organic matter, accurate subgrid scale hydrology, realistic representation of inundated system vegetation, anaerobic decomposition, thermokarst dynamics, and aqueous chemistry. We compared the seasonality and magnitude of predicted CH4 emissions to observations from 18 sites and three global atmospheric inversions. Simulated net CH4 emissions using our baseline parameter set were 270, 160, 50, and 70 Tg CH4 m−2 yr−1 globally, in the tropics, temperate zone, and north of 45° N, respectively; these values are within the range of previous estimates. We then used the model to characterize the sensitivity of regional and global CH4 emission estimates to uncertainties in model parameterizations. Of the parameters we tested, the temperature sensitivity of CH4 production, oxidation parameters, and aerenchyma properties had the largest impacts on net CH4 emissions, up to a factor of 4 and 10 at the regional and gridcell scales, respectively. In spite of these uncertainties, we were able to demonstrate that emissions from dissolved CH4 in the transpiration stream are small (

Description: We conducted high frequency measurements of the δ18O value of atmospheric CO2 from a juniper (Juniperus monosperma) woodland in New Mexico, USA, over a four-year period to investigate climatic and physiological regulation of the δ18O value of ecosystem respiration (δR). Rain pulses reset δR with the dominant water source isotope composition, followed by progressive enrichment of δR. Transpiration (ET) was significantly related to post-pulse δR enrichment because leaf water δ18O value showed strong enrichment with increasing vapor pressure deficit that occurs following rain. Post-pulse δR enrichment was correlated with both ET and the ratio of ET to soil evaporation (ET / ES). In contrast, soil water δ18O value was relatively stable and δR enrichment was not correlated with ES. Model simulations captured the large post-pulse δR enrichments only when the offset between xylem and leaf water δ18O value was modeled explicitly and when a gross flux model for CO2 retro-diffusion was included. Drought impacts δR through the balance between evaporative demand, which enriches δR, and low soil moisture availability, which attenuates δR enrichment through reduced ET. The net result, observed throughout all four years of our study, was a negative correlation of post-precipitation δR enrichment with increasing drought.

Description: Representation of gaseous diffusion in variably saturated near-surface soils is becoming more common in land biogeochemical models, yet the formulations and numerical solution algorithms applied vary widely. We present three different but equivalent formulations of the dual-phase (gaseous and aqueous) tracer diffusion transport problem that is relevant to a wide class of volatile tracers in land biogeochemical models. Of these three formulations (i.e., the gas-primary, aqueous-primary, and bulk tracer based formulations), we contend the gas-primary formulation is the most convenient for modeling tracer dynamics in biogeochemical models. We then provide finite volume approximation to the gas-primary equation and evaluate its accuracy against three analytical models: one for steady-state soil CO2 dynamics, one for steady-state soil CO2 dynamics, and one for transient tracer diffusion from a constant point source into two different sequentially aligned medias. All evaluations demonstrated good accuracy of the numerical approximation. We expect our result will standardize an efficient mechanistic numerical method for solving relatively simple, multi-phase, one-dimensional diffusion problems in land models.

Description: To better understand sources of uncertainty in projections of terrestrial carbon cycle feedbacks, we present an approach to separate the controls on modeled carbon changes. We separate carbon changes into 4 categories using a linearized, equilibrium approach: those arising from changed inputs (productivity-driven changes), and outputs (turnover-driven changes), and apply the analysis separately to the live and dead carbon pools. Using Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations for 5 models, we find that changes to the live pools are primarily explained by productivity-driven changes, with only one model showing large compensating changes to live carbon turnover times. For dead carbon pools, the situation is more complex as all models predict a large reduction in turnover times in response to increases in productivity. This responses arises from the common representation of a broad spectrum of decomposition turnover times via a multi-pool approach, in which flux-weighted turnover times are faster than mass-weighted turnover times. This leads to a shift in the distribution of carbon among dead pools in response to changes in inputs, and therefore a transient but long-lived reduction in turnover times in response to increases in productivity. Since this behavior, a reduction in inferred turnover times resulting from an increase in inputs, is superficially similar to priming processes, but occurring without the mechanisms responsible for priming, we call the phenomenon "false priming", and show that it masks much of the intrinsic changes to dead carbon turnover times as a result of changing climate. These patterns hold across the fully-coupled, biogeochemically-coupled, and radiatively-coupled 1% yr−1 increasing CO2 experiments. We disaggregate inter-model uncertainty in the globally-integrated equilibrium carbon responses to initial turnover times, inital productivity, fractional changes in turnover, and fractional changes in productivity. For both the live and dead carbon pools, inter-model spread in carbon changes arising from initial conditions is dominated by model disagreement on turnover times, whereas inter-model spread in carbon changes from fractional changes to these terms is dominated by model disagreement on changes to productivity in response to both warming and CO2 fertilization. However, the lack of changing turnover time control on carbon responses, for both live and dead carbon pools, in response to the imposed forcings may indicate a common lack of process representation behind changing turnover times (e.g., allocation and mortality for live carbon; permafrost, microbial dynamics, and mineral stabilization for dead carbon), rather than a true estimate of the uncertainty in these processes.

Description: We present a generic flux limiter to account for mass limitations from an arbitrary number of substrates in a biogeochemical reaction network. The flux limiter is based on the observation that substrate (e.g., nitrogen, phosphorus) limitation in biogeochemical models can be represented as to ensure mass conservative and non-negative numerical solutions to the governing ordinary differential equations. Application of the flux limiter includes two steps: (1) formulate the biogeochemical processes with a matrix of stoichiometric coefficients and (2) apply Liebig's law of the minimum using the dynamic stoichiometric relationship of the reactants. This approach contrasts with the ad hoc down-regulation approaches that are implemented in many existing models (such as CLM4.5 and the ACME (Accelerated Climate Modeling for Energy) Land Model (ALM)) of carbon and nutrient interactions, which are error prone when adding new processes, even for experienced modelers. Through an example implementation with a Century-like decomposition model that includes carbon, nitrogen, and phosphorus, we show that our approach (1) produced almost identical results to that from the ad hoc down-regulation approaches under non-limiting nutrient conditions; and (2) properly resolved the negative solutions under substrate-limited conditions where the simple clipping approach failed; and (3) successfully avoided the potential conceptual ambiguities that are implied by those ad hoc down-regulation approaches. We expect our approach will make future biogeochemical models easier to improve and more robust.