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: 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: We describe a new top boundary condition (TBC) for representing the air–soil diffusive exchange of a generic volatile tracer. This new TBC (1) accounts for the multi-phase flow of a generic tracer; (2) accounts for effects of soil temperature, pH, solubility, sorption, and desorption processes; (3) enables a smooth transition between wet and dry soil conditions; (4) is compatible with the conductance formulation for modeling air–water volatile tracer exchange; and (5) is applicable to site, regional, and global land models. Based on the new TBC, we developed new formulations for bare-soil resistance and corresponding soil evaporation efficiency. The new soil resistance is predicted as the reciprocal of the harmonic sum of two resistances: (1) gaseous and aqueous molecular diffusion and (2) liquid mass flow resulting from the hydraulic pressure gradient between the soil surface and center of the topsoil control volume. We compared the predicted soil evaporation efficiency with those from several field and laboratory soil evaporation measurements and found good agreement with the typically observed two-stage soil evaporation curves. Comparison with the soil evaporation efficiency equation of Lee and Pielke (1992; hereafter LP92) indicates that their equation can overestimate soil evaporation when the atmospheric resistance is low and underestimate soil evaporation when the soil is dry. Using a synthetic inversion experiment, we demonstrated that using inverted soil resistance data from field measurements to derive empirical soil resistance formulations resulted in large uncertainty because (1) the inverted soil resistance data are always severely impacted by measurement error and (2) the derived empirical equation is very sensitive to the number of data points and the assumed functional form of the resistance. We expect the application of our new TBC in land models will provide a consistent representation for the diffusive tracer exchange at the soil–air interface.

Description: Watershed-scale hydrological and biogeochemical models are usually discretized at resolutions coarser than where significant heterogeneities in topography, abiotic factors (e.g., soil properties), and biotic (e.g., vegetation) factors exist. Here we report on a method to use fine-scale (220 m grid cells) hydrological model predictions to build reduced-order models of the statistical properties of near-surface soil moisture at coarse resolution (25 times coarser, ~7 km). We applied a watershed-scale hydrological model (PAWS-CLM4) that has been previously tested in several watersheds. Using these simulations, we developed simple, relatively accurate (R2 ~0.7–0.8), reduced-order models for the relationship between mean and higher-order moments of near-surface soil moisture during the nonfrozen periods over five years. When applied to transient predictions, soil moisture variance and skewness were relatively accurately predicted (R2 0.7–0.8), while the kurtosis was less accurately predicted (R2 ~0.5). We also tested 16 system attributes hypothesized to explain the negative relationship between soil moisture mean and variance toward the wetter end of the distribution and found that, in the model, 59% of the variance of this relationship can be explained by the elevation gradient convolved with mean evapotranspiration. We did not find significant relationships between the time rate of change of soil moisture variance and covariances between mean moisture and evapotranspiration, drainage, or soil properties, as has been reported in other modeling studies. As seen in previous observational studies, the predicted soil moisture skewness was predominantly positive and negative in drier and wetter regions, respectively. In individual coarse-resolution grid cells, the transition between positive and negative skewness occurred at a mean soil moisture of ~0.25–0.3. The type of numerical modeling experiments presented here can improve understanding of the causes of soil moisture heterogeneity across scales, and inform the types of observations required to more accurately represent what is often unresolved spatial heterogeneity in regional and global hydrological models.

Description: We describe a new top boundary condition (TBC) for representing the air-soil diffusive exchange of a generic volatile tracer. This new TBC (1) accounts for the multi-phase flow of a generic tracer; (2) accounts for effects of soil temperature, pH, solubility, sorption, and desorption processes; (3) enables a smooth transition between wet and dry soil conditions; (4) is compatible with the conductance formulation for modeling air-water volatile tracer exchange; and (5) is applicable to site, regional, and global land models. Based on the new TBC, we developed new formulations for bare-soil resistance and corresponding soil evaporation efficiency. The new soil resistance is predicted as the reciprocal of the harmonic sum of two resistances: (1) gaseous and aqueous molecular diffusion and (2) liquid mass flow resulting from the hydraulic pressure gradient between the soil surface and center of the topsoil control volume. The resulting soil evaporation efficiency reasonably explains the two-stage soil evaporation curves typically observed in field and laboratory soil evaporation measurements. Comparison with the soil evaporation efficiency equation of Lee and Pielke (1992; hereafter LP92) indicates that their equation can overestimate soil evaporation when the atmospheric resistance is low and underestimate soil evaporation when the soil is dry. Using a synthetic inversion experiment, we demonstrated that using inverted soil resistance data from field measurements to derive empirical soil resistance formulations resulted in large uncertainty because (1) the inverted soil resistance data is always severely impacted by measurement error and (2) the derived empirical equation is very sensitive to the number of data points and the assumed functional form of the resistance. We expect the application of our new TBC in land models will provide a consistent representation for the diffusive tracer exchange at the soil–air interface.

Description: Watershed-scale hydrological and biogeochemical models are usually discretized at resolutions coarser than where significant heterogeneities in topographic, subsurface abiotic and biotic, and surface vegetation exist. Here we report on a method to use fine-resolution (220 m gridcells) hydrological model predictions to build reduced order models of the statistical properties of near-surface soil moisture at coarse-resolution (25 times coarser; ~7 km). We applied a watershed-scale hydrological model (PAWS+CLM) that has been previously tested in several watersheds and developed simple, relatively accurate (R2 ~ 0.7–0.8) reduced order models for the relationship between mean and higher-order moments of near-surface soil moisture during the non-frozen periods over five years. When applied to transient predictions, soil moisture variance and skewness were relatively accurately predicted (R2 ~ 0.7–0.8), while the kurtosis was less accurately predicted (R2 ~ 0.5). We tested sixteen system attributes hypothesized to explain the negative relationship between soil moisture mean and variance toward the wetter end of the distribution and found that, in the model, 59% of the variance of this relationship can be explained by the elevation gradient convolved with mean evapotranspiration. We did not find significant relationships between the time rate of change of soil moisture variance and covariances between mean moisture and evapotranspiration, drainage, or soil properties, as has been reported in other modeling studies. As seen in previous observational studies, the predicted soil moisture skewness was predominantly positive and negative in drier and wetter regions, respectively. In individual coarse-resolution gridcells, the transition between positive and negative skewness occurred at a mean soil moisture of ~0.25–0.3. The type of numerical modeling experiments presented here can improve understanding of the causes of soil moisture heterogeneity across scales, and inform the types of observations required to more accurately represent unresolved spatial heterogeneity in regional and global hydrological models.