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At least 109 records · Page 6

Revisiting particle dry deposition and its role in radiative effect estimates

Wet and dry deposition remove aerosols from the atmosphere, and these processes control aerosol lifetime and thus impact climate and air quality. Dry deposition is a significant source of aerosol uncertainty in global chemical transport and climate models. Dry deposition parameterizations in most global models were developed when few particle deposition measurements were available. However, new measurement techniques have enabled more size-resolved particle flux observations. We combined literature measurements with data that we collected over a grassland in Oklahoma and a pine forest in Colorado to develop a dry deposition parameterization. We find that relative to observations, previous parameterizations overestimated deposition of the accumulation and Aitken mode particles, and underestimated in the coarse mode. These systematic differences in observed and modeled accumulation mode particle deposition velocities are as large as an order of magnitude over terrestrial ecosystems. As accumulation mode particles form most of the cloud condensation nuclei (CCN) that influence the indirect radiative effect, this model-measurement discrepancy in dry deposition alters modeled CCN and radiative forcing. We present a revised observationally driven parameterization for regional and global aerosol models. Using this revised dry deposition scheme in the Goddard Earth Observing System (GEOS)-Chem chemical transport model, we find that global surface accumulation-mode number concentrations increase by 62% and enhance the global combined anthropogenic and natural aerosol indirect effect by −0.63 W m −2 . Our observationally constrained approach should reduce the uncertainty of particle dry deposition in global chemical transport models.

54 ENVIRONMENTAL SCIENCES↗

Analytical models of hydrogen transport in graphite

The importance of graphite-hydrogen chemical reactions to fusion, fission, and hydrogen storage applications, combined with the rapidly evolving knowledge on the underlying mechanisms, has led to the development of multiple models to describe hydrogen transport in graphite. Significant differences exist among these models, resulting from discrepancies in the modeling assumptions, intended degree of fidelity, and conditions of applicability. This paper attempts at reconciling these apparent differences by providing a comprehensive description of the constitutive equations governing hydrogen transport in graphite at high-temperature, identifying outstanding gaps in knowledge, illustrating how these different models approach them, and proposing alternative analytical formulations grounded on experimental results from hydrogen-graphite studies. Governing equations, closing relations, and simplifying assumptions are discussed for hydrogen transport at the inter-granular and intra-granular level, accompanied by compiled experimental data and illustrated energy diagrams associated to the proposed transport mechanisms. Analytical formulations are provided to reproduce competing hypotheses on the mechanisms, supporting the development of a range of computational models that can enable resolution of outstanding knowledge gaps through comparative testing against experimental data.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Biased Estimates of Equilibrium Climate Sensitivity and Transient Climate Response Derived From Historical CMIP6 Simulations

Abstract This study assesses the effective climate sensitivity (EffCS) and transient climate response (TCR) derived from global energy budget constraints within historical simulations of eight CMIP6 global climate models (GCMs). These calculations are enabled by use of the Radiative Forcing Model Intercomparison Project (RFMIP) simulations, which permit accurate quantification of the radiative forcing. Long‐term historical energy budget constraints generally underestimate EffCS from CO 2 quadrupling and TCR from CO 2 ramping, owing to changes in radiative feedbacks and changes in ocean heat uptake efficiency. Atmospheric GCMs forced by observed warming patterns produce lower values of EffCS that are more in line with those inferred from observed historical energy budget changes. The differences in the EffCS estimates from historical energy budget constraints of models and observations are traced to discrepancies between modeled and observed historical surface warming patterns.

Dong, Yue↗

Measurement of the sound velocity and Grüneisen parameter of polystyrene at inertial confinement fusion conditions

The principal Hugoniot, sound velocity, and Grüneisen parameter of polystyrene were measured at conditions relevant to shocks in inertial confinement fusion implosions, from 100 to 1000 GPa. The sound velocity is in good agreement with quantum molecular dynamics calculations and all tabular equation of state models at pressures below 200 GPa. Above 200 GPa, the experimental results agree with two of the examined tables, but do not agree with the most recent table developed for design of ICF experiments. The Grüneisen parameter increases with density below ~3.1 g/cm 3 and approaches the asymptotic value for an ideal gas after complete dissociation. This behavior is in good agreement with quantum molecular dynamics results and previous work but is not represented by any of the tabular models. Finally, the discrepancy between tabular models and experimental measurement of the sound velocity and Grüneisen parameter is sufficient to impact simulations of ICF experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Bayesian mixture model approach to quantifying the empirical nuclear saturation point

The equation of state (EOS) in the limit of infinite symmetric nuclear matter exhibits an equilibrium density, $n_0 \approx 0.16 \, \mathrm{fm}^{-3}$, at which the pressure vanishes and the energy per particle attains its minimum, $E_0 \approx -16 \, \mathrm{MeV}$. Although not directly measurable, the nuclear saturation point $(n_0,E_0)$ can be extrapolated by density functional theory (DFT), providing tight constraints for microscopic interactions derived from chiral effective field theory (EFT). However, when considering several DFT predictions for $(n_0,E_0)$ from Skyrme and Relativistic Mean Field (RMF) models together, a discrepancy between these model classes emerges at high confidence levels that each model prediction's uncertainty cannot explain. How can we leverage these DFT constraints to rigorously benchmark nuclear saturation properties of chiral interactions? To address this question, we present a Bayesian mixture model that combines multiple DFT predictions for $(n_0,E_0)$ using an efficient conjugate prior approach. The inferred posterior distribution for the saturation point's mean and covariance matrix follows a Normal-inverse-Wishart class, resulting in posterior predictives in the form of correlated, bivariate $t$-distributions. The DFT uncertainty reports are then used to mix these posteriors using an ordinary Monte Carlo approach. At the 95\% credibility level, we estimate $n_0 \approx 0.157 \pm 0.010 \, \mathrm{fm}^{-3}$ and $E_0 \approx -15.97 \pm 0.40 \, \mathrm{MeV}$ for the marginal (univariate) $t$-distributions. Combined with chiral EFT calculations of the pure neutron matter EOS, we obtain bivariate normal distributions for the nuclear symmetry energy and its slope parameter evaluated at $n_0$: $S_v \approx 32.0 \pm 1.1 \, \mathrm{MeV}$ and $L\approx 52.6\pm 8.1 \, \mathrm{MeV}$ (95\%), respectively. Furthermore, our Bayesian framework is publicly available, so practitioners can readily use and extend our results.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Core-corona hadronization model and muon puzzle in extensive air showers

The discrepancy between models and measurements concerning the muon content in air showers produced by ultra-high energy cosmic rays, the so-called muon puzzle, remains unsolved. String fragmentation models currently used in hadronic interactions fail to reproduce the observations, while recent measurements at the LHC hint towards the existence of production mechanisms, such as collective statistical hadronization, which lead to an increase in the muon production after a hadronic interaction. The core-corona model of heavy ions implements both production mechanisms, where the large-density region of interaction (core) hadronizes statistically, while the low-density (corona) hadronizes following string fragmentation. In this contribution, we present a modification of the CONEX framework to implement the core-corona model in air shower simulations. We demonstrate a significant impact of the core effect, as observed at the LHC, on the muon content in air showers produced by ultra-high energy cosmic rays.

79 ASTRONOMY AND ASTROPHYSICS↗

Constraining long‐term model predictions for woody growth using tropical tree rings

The strength and persistence of the tropical carbon sink hinges on the long-term responses of woody growth to climatic variations and increasing CO 2 . However, the sensitivity of tropical woody growth to these environmental changes is poorly understood, leading to large uncertainties in growth predictions. Here, we used tree ring records from a Southeast Asian tropical forest to constrain ED2.2-hydro, a terrestrial biosphere model with explicit vegetation demography. Specifically, we assessed individual-level woody growth responses to historical climate variability and increases in atmospheric CO 2 (C a ). When forced with historical C a , ED2.2-hydro reproduced the magnitude of increases in intercellular CO 2 concentration (a major determinant of photosynthesis) estimated from tree ring carbon isotope records. In contrast, simulated growth trends were considerably larger than those obtained from tree rings, suggesting that woody biomass production efficiency (WBPE = woody biomass production:gross primary productivity) was overestimated by the model. The estimated WBPE decline under increasing C a based on model-data discrepancy was comparable to or stronger than (depending on tree species and size) the observed WBPE changes from a multi-year mature-forest CO 2 fertilization experiment. In addition, we found that ED2.2-hydro generally overestimated climatic sensitivity of woody growth, especially for late-successional plant functional types. The model-data discrepancy in growth sensitivity to climate was likely caused by underestimating WBPE in hot and dry years due to commonly used model assumptions on carbon use efficiency and allocation. To our knowledge, this is the first study to constrain model predictions of individual tree-level growth sensitivity to C a and climate against tropical tree-ring data. Our results suggest that improving model processes related to WBPE is crucial to obtain better predictions of tropical forest responses to droughts and increasing C a . Finally, more accurate parameterization of WBPE will likely reduce the stimulation of woody growth by C a rise predicted by biosphere models.

54 ENVIRONMENTAL SCIENCES↗

Investigating the Tropospheric Chemistry of Acetic Acid Using the Global 3‐D Chemistry Transport Model, STOCHEM‐CRI

Abstract Acetic acid (CH 3 COOH) is one of the most abundant carboxylic acids in the troposphere. In the study, the tropospheric chemistry of CH 3 COOH is investigated using the 3‐D global chemistry transport model, STOCHEM‐CRI. The highest mixing ratios of surface CH 3 COOH are found in the tropics by as much as 1.6 ppb in South America. The model predicts the seasonality of CH 3 COOH reasonably well and correlates with some surface and flight measurement sites, but the model drastically underpredicts levels in urban and midlatitudinal regions. The possible reasons for the underprediction are discussed. The simulations show that the lifetime and global burden of CH 3 COOH are 1.6–1.8 days and 0.45–0.61 Tg, respectively. The reactions of the peroxyacetyl radical (CH 3 CO 3 ) with the hydroperoxyl radical (HO 2 ) and other organic peroxy radicals (RO 2 ) are found to be the principal sources of tropospheric CH 3 COOH in the model, but the model‐measurement discrepancies suggest the possible unknown or underestimated sources which can contribute large fractions of the CH 3 COOH burden. The major sinks of CH 3 COOH in the troposphere are wet deposition, dry deposition, and OH loss. However, the reaction of CH 3 COOH with Criegee intermediates is proposed to be a potentially significant chemical loss process of tropospheric CH 3 COOH that has not been previously accounted for in global modeling studies. Inclusion of this loss process reduces the tropospheric CH 3 COOH level significantly which can give even larger discrepancies between model and measurement data, suggesting that the emissions inventory and the chemical production sources of CH 3 COOH are underpredicted even more so in current global models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Iron and nickel isotope compositions of presolar silicon carbide grains from supernovae

Here we report the carbon, silicon, iron, and nickel isotope compositions of twenty-five presolar SiC grains of mostly supernova (SN) origin. The iron and nickel isotope compositions were measured with the new Chicago Instrument for Laser Ionization, CHILI, which allows the analysis of all iron and nickel isotopes without the isobaric interferences that plagued previous measurements with the NanoSIMS. Despite terrestrial iron and nickel contamination, significant isotopic anomalies in 54 Fe/ 56 Fe, 57 Fe/ 56 Fe, 60 Ni/ 58 Ni, 61 Ni/ 58 Ni, 62 Ni/ 58 Ni, and 64 Ni/ 58 Ni were detected in nine SN grains (of type X). Combined multi-isotope data of three grains with the largest nickel isotope anomalies (>100% or <-100% in at least one isotope ratio, when expressed as deviation from the solar value) are compared with the predictions of two SN models, one with and one without hydrogen ingestion in the He shell prior to SN explosion. One grain's carbon-silicon-iron-nickel isotope composition is consistent with the prediction of the model without hydrogen ingestion, whereas the other two grains' isotope anomalies could not be reproduced using either SN models. The discrepancies between the measured isotope compositions and model predictions may indicate element fractionation in the SN ejecta prior to or during grain condensation, and reiterate the need for three-dimensional SN models.

79 ASTRONOMY AND ASTROPHYSICS↗

Cosmogenic neutron production in water at SNO+

Accurate measurement of the cosmogenic muon-induced neutron yield is crucial for constraining a significant background in a wide range of low-energy physics searches. Although previous underground experiments have measured this yield across various cosmogenic muon energies, SNO+ is uniquely positioned due to its exposure to one of the highest average cosmogenic muon energies at 364 GeV. Using ultrapure water, we have determined a neutron yield of 𝑌 𝑛 = (3.3⁢8$^{+0.23}_{−0.30}$) × 10 −4 cm 2 g −1 𝜇 −1 at SNO+. Comparison with simulations demonstrates clear agreement with the FLUKA neutron production model, highlighting discrepancies with the widely used GEANT 4 model. Furthermore, this measurement reveals a lower cosmogenic neutron yield than that observed by the SNO experiment, which used heavy water under identical muon flux conditions. This result provides new evidence that nuclear structure and target material composition significantly influence neutron production by cosmogenic muons, offering fresh insight with important implications for the design and background modeling of future underground experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Vertical profiles of light absorption and scattering associated with black carbon particle fractions in the springtime Arctic above 79° N

Despite the potential importance of black carbon (BC) for radiative forcing of the Arctic atmosphere, vertically resolved measurements of the particle light scattering coefficient (σ sp ) and light absorption coefficient (σ ap ) in the springtime Arctic atmosphere are infrequent, especially measurements at latitudes at or above 80° N. Here, relationships among vertically distributed aerosol optical properties (σap, σsp and single scattering albedo or SSA), particle microphysics and particle chemistry are examined for a region of the Canadian archipelago between 79.9 and 83.4° N from near the surface to 50 hPa. Airborne data collected during April 2015 are combined with ground-based observations from the observatory at Alert, Nunavut and simulations from the Goddard Earth Observing System (GEOS) model, GEOS-Chem, coupled with the TwO-Moment Aerosol Sectional (TOMAS) model (collectively GEOS-Chem–TOMAS; Kodros et al., 2018) to further our knowledge of the effects of BC on light absorption in the Arctic troposphere. The results are constrained for σsp less than 15 Mm -1 , which represent 98% of the observed σsp, because the single scattering albedo (SSA) has a tendency to be lower at lower σsp, resulting in a larger relative contribution to Arctic warming. At 18.4 m 2 g -1 , the average BC mass absorption coefficient (MAC) from the combined airborne and Alert observations is substantially higher than the two averaged modelled MAC values (13.6 and 9.1 m2 g -1 ) for two different internal mixing assumptions, the latter of which is based on previous observations. The higher observed MAC value may be explained by an underestimation of BC, the presence of small amounts of dust and/or possible differences in BC microphysics and morphologies between the observations and model. In comparing the observations and simulations, we present σap and SSA, as measured, and σ ap 2 and the corresponding SSA to encompass the lower modelled MAC that is more consistent with accepted MAC values. Median values of the measured σap, rBC and the organic component of particles all increase by a factor of 1.8±0.1, going from near-surface to 750 hPa, and values higher than the surface persist to 600 hPa. Modelled BC, organics and σap agree with the near-surface measurements but do not reproduce the higher values observed between 900 and 600 hPa. The differences between modelled and observed optical properties follow the same trend as the differences between the modelled and observed concentrations of the carbonaceous components (black and organic). Model-observation discrepancies may be mostly due to the modelled ejection of biomass burning particles only into the boundary layer at the sources. For the assumption of the observed MAC value, the SSA range between 0.88 and 0.94, which is significantly lower than other recent estimates for the Arctic, in part reflecting the constraint of σsp<15 Mm -1 . The large uncertainties in measuring optical properties and BC, and the large differences between measured and modelled values here and in the literature, argue for improved measurements of BC and light absorption by BC and more vertical profiles of aerosol chemistry, microphysics and other optical properties in the Arctic.

54 ENVIRONMENTAL SCIENCES↗

Investigating calcite growth rates using a quartz crystal microbalance with dissipation (QCM-D)

Calcite precipitation plays a significant role in processes such as geological carbon sequestration and toxic metal sequestration and, yet, the rates and mechanisms of calcite growth under close to equilibrium conditions are far from well understood. In this study, a quartz crystal microbalance with dissipation (QCM-D) was used for the first time to measure macroscopic calcite growth rates. Calcite seed crystals were first nucleated and grown on sensors, then growth rates of calcite seed crystals were measured in real-time under close to equilibrium conditions (saturation index, SI = log ({Ca 2+ }/{CO 3 2– }/ K sp ) = 0.01–0.7, where {i} represent ion activities and K sp = 10 –8.48 is the calcite thermodynamic solubility constant). At the end of the experiments, total masses of calcite crystals on sensors measured by QCM-D and inductively coupled plasma mass spectrometry (ICP-MS) were consistent, validating the QCM-D measurements. Calcite growth rates measured by QCM-D were compared with reported macroscopic growth rates measured with auto-titration, ICP-MS, and microbalance. Calcite growth rates measured by QCM-D were also compared with microscopic growth rates measured by atomic force microscopy (AFM) and with rates predicted by two process-based crystal growth models. The discrepancies in growth rates among AFM measurements and model predictions appear to mainly arise from differences in step densities, and the step velocities were consistent among the AFM measurements as well as with both model predictions. Using the predicted steady-state step velocity and the measured step densities, both models predict well the growth rates measured using QCM-D and AFM. Furthermore, this study provides valuable insights into the effects of reactive site densities on calcite growth rate, which may help design future growth models to predict transient-state step densities.

58 GEOSCIENCES↗

Modeling and Calibration of Supplier Selection Problem in Freight Agent-Based Simulations

Freight transportation modeling often struggles with data limitations, especially in accurately representing complex supplier selection processes and their impact on network flows. This research addresses this critical gap by developing a large-scale, calibrated agent-based model for supplier selection, complemented by a probabilistic heuristic for international shipments. Our approach integrates trade relationships between industry sectors, transportation costs, and a supplier-rating model adapted from existing literature. The model’s core objective is to minimize the discrepancy between modeled and observed commodity flows while ensuring a close match to regional shipping distance distributions. Implemented and tested across four major U.S. metropolitan areas—Atlanta, Chicago, Dallas–Fort Worth, and Los Angeles—the model demonstrates high fidelity in replicating observed freight patterns. Key findings reveal consistent alignment with national shipping distance trends and highlight significant spatial variations in commodity trade assignments and demand across the study regions. This behaviorally informed and transport-sensitive framework is designed to approximate real-world decision making, providing a robust tool for policymakers and planners to evaluate targeted interventions, assess infrastructure investments, and enhance supply chain resilience in the face of disruptions.

Ismael, Abdelrahman (ORCID:0000000303712110)↗

Divergent controls of soil organic carbon between observations and process-based models

Abstract The storage and cycling of soil organic carbon (SOC) are governed by multiple co-varying factors, including climate, plant productivity, edaphic properties, and disturbance history. Yet, it remains unclear which of these factors are the dominant predictors of observed SOC stocks, globally and within biomes, and how the role of these predictors varies between observations and process-based models. Here we use global observations and an ensemble of soil biogeochemical models to quantify the emergent importance of key state factors – namely, mean annual temperature, net primary productivity, and soil mineralogy – in explaining biome- to global-scale variation in SOC stocks. We use a machine-learning approach to disentangle the role of covariates and elucidate individual relationships with SOC, without imposing expected relationships a priori . While we observe qualitatively similar relationships between SOC and covariates in observations and models, the magnitude and degree of non-linearity vary substantially among the models and observations. Models appear to overemphasize the importance of temperature and primary productivity (especially in forests and herbaceous biomes, respectively), while observations suggest a greater relative importance of soil minerals. This mismatch is also evident globally. However, we observe agreement between observations and model outputs in select individual biomes – namely, temperate deciduous forests and grasslands, which both show stronger relationships of SOC stocks with temperature and productivity, respectively. This approach highlights biomes with the largest uncertainty and mismatch with observations for targeted model improvements. Understanding the role of dominant SOC controls, and the discrepancies between models and observations, globally and across biomes, is essential for improving and validating process representations in soil and ecosystem models for projections under novel future conditions.

58 GEOSCIENCES↗

High-precision radio and infrared astrometry of LSPM J1314+1320AB. II. Testing pre-main-sequence models at the lithium depletion boundary with dynamical masses

We present novel tests of pre-main-sequence models based on individual dynamical masses for the M7 binary LSPM J1314+1320AB. Joint analysis of Keck adaptive optics astrometric monitoring along with Very Long Baseline Array radio data from a companion paper yield component masses of 92.8 ± 0.6 M {sub Jup} (0.0885 ± 0.0006 M {sub ☉}) and 91.7 ± 1.0 M {sub Jup} (0.0875 ± 0.0010 M {sub ☉}) and a parallactic distance of 17.249 ± 0.013 pc. We find component luminosities consistent with the system being coeval at 80.8 ± 2.5 Myr, according to BHAC15 evolutionary models. The presence of lithium is consistent with model predictions, marking the first test of the theoretical lithium depletion boundary using ultracool dwarfs of known mass. However, we find that the evolutionary model-derived average effective temperature (2950 ± 5 K) is 180 K hotter than that given by a spectral type–T{sub eff} relation based on BT-Settl models (2770 ± 100 K). We suggest that the dominant source of this discrepancy is model radii being too small by ≈13%. In a test mimicking the typical application of models by observers, we derive masses on the H-R diagram using luminosity and BT-Settl temperature. The estimated masses are lower by 46{sub −19}{sup +16}% (2.0σ) than we measure dynamically and would imply that this is a system of ≈50 M {sub Jup} brown dwarfs, highlighting the large systematic errors possible in H-R diagram properties. This is the first time masses have been measured for ultracool (≥M6) dwarfs displaying spectral signatures of low gravity. Based on features in the infrared, LSPM J1314+1320AB appears to have higher gravity than typical Pleiades and AB Dor members, opposite the expectation given its younger age. The components of LSPM J1314+1320AB are now the nearest, lowest mass pre-main-sequence stars with direct mass measurements.

79 ASTRONOMY AND ASTROPHYSICS↗

Discovery of the First Quadruple Gravitationally Lensed Quasar Candidate with Pan-STARRS

We report the serendipitous discovery of the first gravitationally lensed quasar candidate from Pan-STARRS. The grizy images reveal four point-like images with magnitudes between 14.9 and 18.1 mag. The colors of the point sources are similar, and they are more consistent with quasars than with stars or galaxies. The lensing galaxy is detected in the izy bands, with an inferred photometric redshift of ∼0.6, lower than that of the point sources. We successfully model the system with a singular isothermal ellipsoid with shear, using the relative positions of the five objects as constraints. While the brightness ranking of the point sources is consistent with that of the model, we find discrepancies between the model-predicted and observed fluxes, likely due to microlensing by stars and millilensing due to the dark matter substructure. In order to fully confirm the gravitational lens nature of this system and add it to the small but growing number of the powerful probes of cosmology and astrophysics represented by quadruply lensed quasars, we require further spectroscopy and high-resolution imaging.

79 ASTRONOMY AND ASTROPHYSICS↗

Uncertainty quantification in LES of channel flow

Here, in this paper, we present a Bayesian framework for estimating joint densities for large eddy simulation (LES) sub-grid scale model parameters based on canonical forced isotropic turbulence direct numerical simulation (DNS) data. The framework accounts for noise in the independent variables, and we present alternative formulations for accounting for discrepancies between model and data. To generate probability densities for flow characteristics, posterior densities for sub-grid scale model parameters are propagated forward through LES of channel flow and compared with DNS data. Synthesis of the calibration and prediction results demonstrates that model parameters have an explicit filter width dependence and are highly correlated. Discrepancies between DNS and calibrated LES results point to additional model form inadequacies that need to be accounted for.

97 MATHEMATICS AND COMPUTING↗

Terrestrial ecosystem model performance in simulating productivity and its vulnerability to climate change in the northern permafrost region: Modeled Productivity in Permafrost Regions

Realistic projection of future climate-carbon (C) cycle feedbacks requires better understanding and an improved representation of the C cycle in permafrost regions in the current generation of Earth system models. Here we evaluated 10 terrestrial ecosystem models for their estimates of net primary productivity (NPP) and responses to historical climate change in permafrost regions in the Northern Hemisphere. In comparison with the satellite estimate from the Moderate Resolution Imaging Spectroradiometer (MODIS; 246 ± 6 g C m -2 yr -1 ), most models produced higher NPP (309 ± 12 g C m -2 yr -1 ) over the permafrost region during 2000–2009. By comparing the simulated gross primary productivity (GPP) with a flux tower-based database, we found that although mean GPP among the models was only overestimated by 10% over 1982–2009, there was a twofold discrepancy among models (380 to 800 g C m -2 yr -1 ), which mainly resulted from differences in simulated maximum monthly GPP (GPP max ). Most models overestimated C use efficiency (CUE) as compared to observations at both regional and site levels. Further analysis shows that model variability of GPP and CUE are nonlinearly correlated to variability in specific leaf area and the maximum rate of carboxylation by the enzyme Rubisco at 25°C (Vc max_25 ), respectively. The models also varied in their sensitivities of NPP, GPP, and CUE to historical changes in climate and atmospheric CO 2 concentration. In conclusion, these results indicate that model predictive ability of the C cycle in permafrost regions can be improved by better representation of the processes controlling CUE and GPP max as well as their sensitivity to climate change.

54 ENVIRONMENTAL SCIENCES↗