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At least 1,099 records · Page 61

Data-Driven Modeling and Control of Systems with Plasma-Surface Interactions (Final Technical Report)

This final technical report summarizes the activities and accomplishments in the period from February 2023 thru January 2026. The objective of the proposed research is to investigate the physical mechanisms and processes underlying the formation of structures and patterns in systems with plasma-surface interactions. In the past decades, there have been extensive studies on the interaction of glow discharges, dielectric barrier discharges, and arc discharges with confining or intervening surfaces. The advancement of the understanding of these phenomena is not only of fundamental scientific interest and relevance to the knowledge of the plasma state, but also with profound implications in various technological applications. The research will integrate theoretical, computational, and experimental work within an innovative framework of data assimilation, i.e., optimally combining model predictions with measurements. The scientific merit of this research has three aspects. Firstly, it extends the studies of plasma-surface interactions to systems with insulator surfaces and multi-layer systems, while existing studies are predominantly on electrode surfaces. Secondly, it expects to develop a novel data-driven modeling approach based on data assimilation to enhance the predictive and control capabilities, which could make transformative contributions to basic plasma research. Thirdly, it will shed new light on outstanding problems related to formation of patterns interfacing plasmas. This project also aims to launch an education and outreach initiative at Texas A&M University-Kingsville, a non-R1, minority-serving institution in South Texas. The initiative is structured as a four-tier pyramid. Tier one will be a webinar series for culture and capacity building to inform broader audience in the region about the research fields of plasma science and engineering. Tier two will be the creation and offering of an upper-level undergraduate course on introductory plasma physics, which will help with the recruitment for the upper tiers. On tier three, we will engage and mentor senior design students to conduct work toward the research goal of this project. There will also be a certificate program on general plasma science for undergrad and graduate students, part of which will be lab training at Princeton University. Tier four will be the supervision and mentoring of Ph.D. students. Therefore, this project will systematically expand the talent pipeline, broaden participation from communities historically and geographically underrepresented in DOE SC research portfolio, significantly improve the research and education capacity at the PI’s institution, and contribute to developing a diverse workforce in plasma science and engineering.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Numerical challenges in modeling gravothermal collapse in Self-Interacting Dark Matter halos

When dark matter has a large cross section for self scattering, halos can undergo a process known as gravothermal core collapse, where the inner core rapidly increases in density and temperature. To date, several methods have been used to implement Self-Interacting Dark Matter (SIDM) in N-body codes, but there has been no systematic study of these different methods or their accuracy in the core-collapse phase. In this paper, we compare three different numerical implementations of SIDM, including the standard methods from the GIZMO and Arepo codes, by simulating idealized dwarf halos undergoing significant dark matter self interactions (σ/m = 50 cm 2 /g). When simulating these halos, we also vary the mass resolution, time-stepping criteria, and gravitational force-softening scheme. The various SIDM methods lead to distinct differences in a halo's evolution during the core-collapse phase, as each results in spurious scattering rate differences and energy gains/losses. The use of adaptive force softening for gravity can lead to numerical heating that artificially accelerates core collapse, while an insufficiently small simulation time step can cause core evolution to stall or completely reverse. Additionally, particle numbers must be large enough to ensure that the simulated halos are not sensitive to noise in the initial conditions. Even for the highest-resolution simulations tested in this study (10 6 particles per halo), we find that variations of order 10% in collapse time are still present. Here, the results of this work underscore the sensitivity of SIDM modeling on the choice of numerical implementation and motivate a careful study of how these results generalize to halos in a cosmological context.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Weak influence of anthropogenic emissions on aerosol, cloud, and rain in the wet season of the Amazon rainforest

Anthropogenic emissions have been shown to affect new particle formation, aerosol concentrations, and clouds. Such effects vary with region, environmental conditions, and cloud types. In the wet season of Amazonia, anthropogenic emissions emitted from Manaus, Brazil, can significantly increase the cloud condensation nuclei (CCN) concentrations compared to the background of mainly natural aerosols. However, the regional response of cloud and rain to anthropogenic emissions in Amazonia remains very uncertain. Here, we aim to quantify how aerosol concentration, cloud, and rain respond to changes in anthropogenic emissions through parameterized new particle formation and primary aerosol emission in the Manaus region and to understand the underlying mechanisms. We ran the atmosphere-only configuration of the HadGEM3 climate model with a nested regional domain that covers most of the rainforest region (720 km by 1200 km with 3 km resolution) under scaled regional emissions. The 7 d simulations show that, in the areas that are affected by anthropogenic emissions, when aerosol and precursor gas emissions are doubled from the baseline emission inventories, aerosol number concentrations increase by 13 %. The nucleation rate that involves sulfuric acid and biogenic compounds generally increases with pollution levels. However, nucleation is suppressed very close to the pollution source, resulting in lower nucleation and soluble Aitken mode aerosol number concentrations. We also found that doubling the anthropogenic emission can increase the cloud droplet number concentrations ( N d ) by 9 %, but cloud water and rain mass mixing ratios do not change significantly. Even very strong reductions in aerosol number concentrations by a factor of 4, which is an unrealistic condition, cause only a 4 % increase in rain over the domain. If we assume our simulation has a fine enough grid resolution and an accurate representation of the relevant atmospheric processes, the simulated weak and non-linear response of cloud and rain properties to linearly scaled anthropogenic emissions suggests that the interactions among aerosol, cloud, and precipitation in the Amazonian convective environment are buffered by microphysical processes. It also implies that the convective environment is resilient to the changes in Nd that occur in response to localized anthropogenic aerosol perturbations.

Wang, Xuemei [University of Leeds (United Kingdom)↗

A Self Consistent 2D Simulation of Coherent Synchrotron Radiation Effects on Beam Dynamics

An increasing interest in high quality and high current electron beams necessitates a thorough understanding and prediction of coherent synchrotron radiation effects. The self-interaction of charged particles in a beam undergoing synchrotron motion is a physically significant process that is all too often computationally intensive with very little analytical results to rely on for the general case. The coherent spectrum of this interaction is of utmost importance to the design of free electron lasers (FELs) and an accurate assessment is imperative for their design. This work presents a novel implementation to the numerical simulation of charged particle beams. The simulation is a self-consistent approach including the self-fields generated by the beam of which coherent synchrotron radiation effects are of primary interest. A particle-in-cell model is used where a planar beam sampled by point particles is deposited on an encompassing grid at each timestep. The electromagnetic fields are calculated on the grid using the retarded potentials according to causality. The electromagnetic forces from the fields are interpolated on each particle which in turn advance in time. The simulation is benchmarked against well-established results for coherent synchrotron radiation effects. In addition, studies are provided that show the convergence of simulation results for increasing resolution. A study into the transverse beam size effects on beam dynamics is performed as well as a proof of concept where the simulation is used by a genetic algorithm to optimize the design parameters of a beam lattice. The results of these studies in tandem verify the efficacy of the simulation for its practical use in accelerator design or the study of synchrotron radiation effects

Duffin, Dallan [Old Dominion Univ., Norfolk, VA (U↗

Snowmass 2021 LoI: Neutrino-induced Shallow- and Deep-Inelastic Scattering

In neutrino interactions with nucleons and nuclei, Shallow Inelastic Scattering (SIS) refers to processes, dominated by non-resonant contributions, in the kinematic region where $Q^2$ is small and the invariant mass of the hadronic system, $W$, is above the pion production threshold. The extremely rich science of this complex region, poorly understood both theoretically and experimentally, encompasses the transition from interactions described in terms of hadronic degrees of freedom to interactions with quarks and gluons described by perturbative QCD. Since a large fraction of events in NOvA and DUNE, and in atmospheric neutrino measurements such as IceCube-Upgrade, KM3NeT, Super- and Hyper-Kamiokande, are from this SIS region, there is a definite need to improve our knowledge of this physics. This LoI summarizes the current understandings of the SIS physics and a series of proposals for the path to forward.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Effect of Phosphorus Modulation in Iron Single‐Atom Catalysts for Peroxidase Mimicking

Abstract Fe–N–C single‐atom catalysts (SACs) exhibit excellent peroxidase (POD)‐like catalytic activity, owing to their well‐defined isolated iron active sites on the carbon substrate, which effectively mimic the structure of natural peroxidase's active center. To further meet the requirements of diverse biosensing applications, SAC POD‐like activity still needs to be continuously enhanced. Herein, a phosphorus (P) heteroatom is introduced to boost the POD‐like activity of Fe–N–C SACs. A 1D carbon nanowire (FeNCP/NW) catalyst with enriched Fe–N 4 active sites is designed and synthesized, and P atoms are doped in the carbon matrix to affect the Fe center through long‐range interaction. The experimental results show that the P‐doping process can boost the POD‐like activity more than the non‐P‐doped one, with excellent selectivity and stability. The mechanism analysis results show that the introduction of P into SAC can greatly enhance POD‐like activity initially, but its effect becomes insignificant with increasing amount of P. As a proof of concept, FeNCP/NW is employed in an enzyme cascade platform for highly sensitive colorimetric detection of the neurotransmitter acetylcholine.

Ding, Shichao↗

A Bioinspired Artificial Injury Response System Based on a Robust Polymer Memristor to Mimic a Sense of Pain, Sign of Injury, and Healing

Abstract Flexible electronic skin with features that include sensing, processing, and responding to stimuli have transformed human–robot interactions. However, more advanced capabilities, such as human‐like self‐protection modalities with a sense of pain, sign of injury, and healing, are more challenging. Herein, a novel, flexible, and robust diffusive memristor based on a copolymer of chlorotrifluoroethylene and vinylidene fluoride (FK‐800) as an artificial nociceptor (pain sensor) is reported. Devices composed of Ag/FK‐800/Pt have outstanding switching endurance >10 6 cycles, orders of magnitude higher than any other two‐terminal polymer/organic memristors in literature (typically 10 2 –10 3 cycles). In situ conductive atomic force microscopy is employed to dynamically switch individual filaments, which demonstrates that conductive filaments correlate with polymer grain boundaries and FK‐800 has superior morphological stability under repeated switching cycles. It is hypothesized that the high thermal stability and high elasticity of FK‐800 contribute to the stability under local Joule heating associated with electrical switching. To mimic biological nociceptors, four signature nociceptive characteristics are demonstrated: threshold triggering, no adaptation, relaxation, and sensitization. Lastly, by integrating a triboelectric generator (artificial mechanoreceptor), memristor (artificial nociceptor), and light emitting diode (artificial bruise), the first bioinspired injury response system capable of sensing pain, showing signs of injury, and healing, is demonstrated.

36 MATERIALS SCIENCE↗

Probing extended scalar sectors with precision e + e - → Zh and Higgs diphoton studies

We compute the one-loop corrections to σ(e + e - → Zh) arising from representative extended Standard Model scalar sector scenarios. According to the new scalar SU(2)L representations, we consider the inert doublet, real and complex triplet, quintuplet, and septuplet models. With the sub-percent level precision expected for prospective future e + e - collider measurements of σ(e + e - → Zh), studies of the Higgsstrahlung process will probe extended scalar sector particle spectrum and interactions in a manner complementary to direct searches at the Large Hadron Collider and possible future pp colliders. We also compare with the sensitivity of future Higgs diphoton decay rate measurements. We find that the σ(e + e - → Zh) and Γ(h → γγ) complementarity is particularly pronounced for the complex triplet model.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Statistical framework to assess long-term spatio-temporal climate changes: East River mountainous watershed case study

Abstract Evaluation of long-term temporal and spatial climatic change in mountainous regions is a critical challenge because of the interactive effects of multiple land and climatic factors and processes. Here we present the application of the statistical framework to the assessment of changes of climatic conditions, using data from 17 meteorological stations across the East River watershed near Crested Butte, Colorado, USA, and spanning the period from 1966 to 2021. The framework is developed based on (1) a time-series analysis of daily, monthly, and yearly averaged meteorological parameters (temperature, relative humidity, precipitation, wind speed, etc.), (2) evaluation and time series analysis of potential evapotranspiration (ET o ), actual evapotranspiration (ET), aridity index (AI), standard precipitation index (SPI) and standard precipitation-evapotranspiration index (SPEI), and (3) a temporal-spatial climatic zonation of the studied area based on the hierarchical clustering and PCA analysis of the SPEI, because the SPEI can be considered an integrative characteristic of the changes of climatic conditions. The Budyko model, with the application of the Penman–Monteith equation for the estimation of ET o , was used to determine the ET. The time series analysis of the AI is used to identify the periods with energy limited and water limited conditions. Hierarchical clustering of site locations for the three temporal segments of the SPEI showed a significant temporal-spatial shifts, indicating that dynamic climatic processes drive zonation patterns. Therefore, the watershed climatic zonation requires periodic re-evaluation based on the structural time series analysis of meteorological and water balance data.

54 ENVIRONMENTAL SCIENCES↗

Direct root contact among neighboring plants influences activity of soil extracellular enzymes

Composition and diversity of vegetation systems can influence soil microbial activity and extracellular enzyme (EE) dynamics, which are crucial for soil carbon (C) accrual and nutrient cycling. Yet, the impact of plant interactions and competition on EE activities remains a notable knowledge gap. This study examines how direct root contact and neighboring plant identity affect the activity and spatial distribution of four key soil EEs: β-glucosidase (BGlu), chitinase, acid phosphatase (AcidP), and alkaline phosphatase (AlkP). Using three-compartment rhizoboxes with switchgrass (Panicum virgatum L.) grown alongside bush clover (Lespedeza capitata Michx.), and black-eyed Susan (Rudbeckia hirta L.), we assessed enzyme activities using zymography under conditions that either allowed or restricted direct root contact by root barriers. Results show that root proliferation and species interactions significantly influenced EE activity. While BGlu and AcidP activities were strongly correlated with root biomass, AlkP activity was consistently higher in the absence of root barriers, indicating a pronounced microbial response to plant interactions via direct/close root contacts. Additionally, soil phosphorus availability modulated enzyme activity, with higher phosphatase activities in low-P soils. Furthermore, these findings highlight the importance of root-root interactions and plant species composition in shaping soil biochemical processes.

enyzme activity↗

Temperature effects on cobalt hydroxide–cobalt carbonate competitive growth on carbonate surfaces

Cobalt (Co), a critical metal essential for various environmental and industrial processes, undergoes speciation and immobilization in natural systems, primarily interacting with existing mineral surfaces. Understanding the underlying mechanisms of Co immobilization on abundant carbonate surfaces under different environmental conditions is critical for predicting Co mobility, availability, and recovery. In this study, we investigated the temperature-dependent competition between CoCO 3 and Co(OH) 2 formation on calcite (CaCO 3 ) and magnesite (MgCO 3 ) surfaces. Using X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), and energy-dispersive X-ray spectroscopy (EDS), we analyzed carbonate substrates exposed to CoCl 2 solutions at varying concentrations (0–500 μM) and temperatures (22, 50, and 80 °C). Magnesite surfaces promoted CoCO 3 formation due to its low lattice mismatch with sphaerocobaltite (CoCO 3 ). However, this slow-growing CoCO 3 component was progressively outcompeted by Co(OH) 2 formation as the temperature and/or initial Co concentration increased. On calcite surfaces, the poor lattice mismatch between calcite and sphaerocobaltite led to Co(OH) 2 outcompeting CoCO 3 formation at all three temperatures. These findings provide critical insights into the roles of substrate composition, solution chemistry, and temperature in controlling Co speciation and mobility. They carry important implications for environmental transport, geochemical cycling, and industrial recovery of cobalt in carbonate-rich systems.

Calcite↗

Decrease in multiple complement proteins associated with development of islet autoimmunity and type 1 diabetes

Type 1 diabetes (T1D) is a chronic condition caused by autoimmune destruction of the insulin-producing pancreatic ß-cells. While it is known that gene-environment interactions play a key role in triggering the autoimmune process leading to T1D, the pathogenic mechanism leading to the appearance of islet autoantibodies - biomarkers of autoimmunity – is poorly understood. Here we show that disruption of the complement system precedes the detection of islet autoantibodies and persists through diagnosis. Our results suggest that children who exhibit islet autoimmunity and progress to clinical T1D are complement deficient relative to those who do not progress within a similar timeframe. Thus, the complement pathway, an understudied mechanistic and therapeutic target in T1D, merits increased attention for use as protein biomarkers of prediction and potentially prevention of T1D.

59 BASIC BIOLOGICAL SCIENCES↗

Using a coupled dispersion model to estimate depletion of a tritium oxide plume by a forest

Tritium processing facilities may release tritium oxide (HTO) to the atmosphere which poses potential health risks to exposed co-located workers and to offsite individuals. Most radiological consequence analyses determine HTO dose by applying Gaussian plume models to simulate the transport of HTO. Within these models, deposition velocity is used to assess the sum of all deposition processes acting on the plume. While this may account for vegetative and soil uptake or respiration processes, it may currently lack inclusion of the complex interactions within heterogeneous forested environments. In this complex morphology, dispersion patterns are significantly altered by changing flow regimes above and below the forest canopy and by the transfer of plume material across the canopy boundary. To determine the effects of a heterogeneous forest canopy on an airborne HTO plume, a Gaussian plume model coupled with an advection-diffusion plume model was applied to estimate transport in the free atmosphere above the forest and within the forest canopy and understory. During 2012, wind speed and wind direction measurements taken at 5 heights, ranging from 2-m to 28-m, on an instrumented meteorological tower located in a loblolly pine forest at the Department of Energy (DOE) Savannah River Site (SRS), near Aiken, SC. From these measurements, model predictions were made over a full spectrum of meteorological conditions. Deposition and resuspension velocities were calculated based on the model-predicted flux of plume material across the top of the forest canopy. Additionally, net deposition velocity of the plume material was calculated as the difference between the deposition and resuspension velocities. The 1st and 5th percentile net deposition velocities were estimated to be 0.7 cm s-1 and 1.2 cm s-1, respectively.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

A first principles study on the adsorbate-adsorbate interactions on the CdTe(111) surface with Cd, Te, Zn, and Se adatoms

The study of adsorbate-adsorbate interactions is essential to understanding early crystal growth dynamics. Here, we employ planewave density functional theory to study the binary adatom pair interactions between Cd-Cd, Te-Te, Zn-Zn, Se-Se, Cd-Te, Cd-Se, Cd-Zn, Te-Se, Te-Zn, and Se-Zn adatom pairs on two CdTe(111) surfaces. An analysis of the interaction energies between binary adatom pairs suggests repulsive interactions are common regardless of the relative distance between adatoms. For the CdTe(111)A surface, attractive interactions occur between neighboring chalcogen (i.e., Te and Se) and Group 12 (i.e., Cd and Zn) adatom pairs. For the CdTe(111)B surface, attractive interactions occur between neighboring Group 12 adatoms forming a surface dimer configuration. Furthermore, the formation energy of an adatom pair is decomposed in terms of the electronic, elastic, and adatom binding contributions. For smaller interatomic distances between the adatoms, the formation energy is primarily a function of the electronic interactions, with null contributions from the elastic and adatom binding interactions for Group 12-containing pairs. Because of the less favorable electronic interactions for larger interatomic distances between the adatoms, the formation energies are typically more positive. Lastly, neighboring adatoms significantly increase the barriers of migration on the CdTe(111)A surface relative to unary adatoms for the top-to-fcc and fcc-to-fcc sites, while the migration barriers on the CdTe(111)B surface only increases for the fcc-to-fcc migration of chalcogen species. From this analysis, we illustrate the role of adatom interactions during the early stages of the surface nucleation processes on CdTe(111) thin films.

CdTe↗

miR-23b Ameliorates nonalcoholic steatohepatitis by targeting Acyl-CoA thioesterases 4

Non-alcoholic fatty liver disease (NAFLD) and its more advanced stages, Non-alcoholic steatohepatitis and Cirrhosis, are the most common liver diseases in the worldwide, especially in developing countries. NAFLD is distinguished by the accumulation of triglycerides within hepatocytes. An increasing body of evidence suggests that hepatic MicroRNAs play an important role in NAFLD by controlling lipid metabolism, inflammation, and fibrosis. However, the precise causative functions of miRNA in NAFLD remain unknown. Here, we discovered that mice lacking MicroRNA-23b developed NAFLD-like phenotypes such as increased serum triglyceride and lipid droplet accumulation. In db/db mice fed a high fat diet, MicroRNA-23b overexpression reduced liver weight and alleviated liver inflammation, apoptosis, and fibrosis. MicroRNA-23b regulates the acyl-CoA metabolic process via Acyl-CoA thioesterase 4 (Acot4), which interacts with Acetyl CoA Carboxylase (ACC), according to the RNA-seq analysis.

60 APPLIED LIFE SCIENCES↗

Pitch Angle Dependence of Electron and Ion Flux Changes During Local Magnetic Dipolarization Inside Geosynchronous Orbit

In this study we have statistically examined flux changes of 1–1,000-keV electrons, and hydrogen, helium, and oxygen ions during local magnetic dipolarization inside geosynchronous orbit, with a focus on their pitch angle dependence. Here, using 144 dipolarization events that were selected in a previous study with Van Allen Probes observations in 2012–2016, we have performed a superposed epoch analysis of differential flux changes after the dipolarization onset for each species. On average the electron flux increases primarily around pitch angle (α) = 90° at >80 keV and almost isotropically at 10–50 keV. The electron flux at <5 keV increases at α = 0° and 180° but slightly decreases (or remains unchanged) at α = 90°. On the other hand, the ion flux at >80 keV increases around α = 90°, while at <30 keV it decreases nearly independent of pitch angle. Only the low-energy (<5 keV) helium and oxygen ion flux changes indicate a strong field-aligned enhancement, which could be attributed to their outflows from the topside ionosphere. After the dipolarization onset, >5-keV electron and >30-keV ion fluxes exhibit a perpendicular anisotropy, which is most pronounced for 50–200-keV electrons. Both distributions become more isotropic with decreasing energy. A noticeable field-aligned anisotropy is seen for <5-keV ion fluxes. These statistical pitch angle-dependent electron and ion properties during dipolarizations may be explained by combining various processes, including adiabatic acceleration and/or transport, wave-particle interactions, and ion outflow.

79 ASTRONOMY AND ASTROPHYSICS↗

A Baseline for Global Weather and Climate Simulations at 1 km Resolution

In an attempt to advance the understanding of the Earth's weather and climate by representing deep convection explicitly, we present a global, four-month simulation (November 2018 to February 2019) with ECMWF's hydrostatic Integrated Forecasting System (IFS) at an average grid spacing of 1.4 km. The impact of explicitly simulating deep convection on the atmospheric circulation and its variability is assessed by comparing the 1.4 km simulation to the equivalent well-tested and calibrated global simulations at 9 km grid spacing with and without parametrized deep convection. The explicit simulation of deep convection at 1.4 km results in a realistic large-scale circulation, better representation of convective storm activity, and stronger convective gravity wave activity when compared to the 9 km simulation with parametrized deep convection. Comparison of the 1.4 km simulation to the 9 km simulation without parametrized deep convection shows that switching off deep convection parametrization at a too coarse resolution (i.e., 9 km) generates too strong convective gravity waves. Based on the limited statistics available, improvements to the Madden-Julian Oscillation or tropical precipitation are not observed at 1.4 km, suggesting that other Earth system model components and/or their interaction are important for an accurate representation of these processes and may well need adjusting at deep convection resolving resolutions. Overall, the good agreement of the 1.4 km simulation with the 9 km simulation with parametrized deep convection is remarkable, despite one of the most fundamental parametrizations being turned off at 1.4 km resolution and despite no adjustments being made to the remaining parametrizations.

54 ENVIRONMENTAL SCIENCES↗

Accurate Simulation of Both Sensitivity and Variability for Amazonian Photosynthesis: Is It Too Much to Ask?

Abstract Estimates of Amazon rainforest gross primary productivity (GPP) differ by a factor of 2 across a suite of three statistical and 18 process models. This wide spread contributes uncertainty to predictions of future climate. We compare the mean and variance of GPP from these models to that of GPP at six eddy covariance (EC) towers. Only one model's mean GPP across all sites falls within a 99% confidence interval for EC GPP, and only one model matches EC variance. The strength of model response to climate drivers is related to model ability to match the seasonal pattern of the EC GPP. Models with stronger seasonal swings in GPP have stronger responses to rain, light, and temperature than does EC GPP. The model to data comparison illustrates a trade‐off inherent to deterministic models between accurate simulation of a mean (average) and accurate responsiveness to drivers. The trade‐off exists because all deterministic models simplify processes and lack at least some consequential driver or interaction. If a model's sensitivities to included drivers and their interactions are accurate, then deterministically predicted outcomes have less variability than is realistic. If a GPP model has stronger responses to climate drivers than found in data, model predictions may match the observed variance and seasonal pattern but are likely to overpredict GPP response to climate change. High or realistic variability of model estimates relative to reference data indicate that the model is hypersensitive to one or more drivers.

54 ENVIRONMENTAL SCIENCES↗