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At least 1,027 records · Page 57

Characterizing the Influence of Fracture Density on Network Scale Transport

The topology of natural fracture networks is inherently linked to the structure of the fluid velocity field and transport therein. Here we study the impact of network density on flow and transport behaviors. We stochastically generate fracture networks of varying density and simulate flow and transport with a discrete fracture network model, which fully resolves network topology at the fracture scale. We study conservative solute trajectories with Lagrangian particle tracking and find that as fracture density decreases, solute channelization to large local fractures increases, thereby reducing plume spreading. Furthermore, in sparse networks mean particle travel distance increases and local network features, such as velocity zones where flow is counter to the primary pressure gradient, become increasingly important for transport. As the network density increases, network statistics homogenize and such local features have a reduced impact. We quantify local topological influence on transport behavior with an effective tortuosity parameter, which measures the ratio of total advective distance to linear distance at the fracture scale; large tortuosity values are correlated to slow-velocity regions. Additionally, these large tortuosity, slow-velocity regions delay downstream transport and enhance tailing on particle breakthrough curves. Finally, we predict transport with an upscaled, Bernoulli spatial Markov random walk model and parameterize local topological influences with a novel tortuosity parameter. Furthermore, Bernoulli model predictions improve when sampling from a tortuosity distribution, as opposed to a fixed value as has previously been done, suggesting that local network topological features must be carefully considered in upscaled modeling efforts of fracture network systems.

58 GEOSCIENCES↗

Topographical Controls on Hillslope-Scale Hydrology Drive Shrub Distributions on the Seward Peninsula, Alaska

Observations indicate shrubs are expanding across the Arctic tundra, mainly on hillslopes and primarily in response to climate warming. However, the impact topography exerts on hydrology, nutrient dynamics, and plant growth can make untangling the mechanisms behind shrub expansion difficult. We examined the role topography plays in determining shrub expansion by applying a coupled transect version of a mechanistic ecosystem model (ecosys) in a tundra hillslope site in the Seward Peninsula, Alaska. Modeled biomass of the dominant plant functional types agreed well with field measurements (R 2 = 0.89) and accurately represented shrub expansion over the past 30 years inferred from satellite observations. In the well-drained crest position, canopy water potential and plant nitrogen (N) uptake was modeled to be low from plant and microbial water stress. Intermediate soil water content in the mid-slope position enhanced mineralization and plant N uptake, increasing shrub biomass. The deciduous shrub growth in the mid-slope position was further enhanced by symbiotic N 2 fixation primed by increased root carbon allocation. The gentle slope in the poorly drained lower-slope position resulted in saturated soil conditions that reduced soil O 2 concentrations, leading to lower root O 2 uptake and lower nutrient uptake and plant biomass. Additionally, a simulation that removed topographical interconnectivity between grid cells resulted in (1) a 28% underestimate of mean shrub biomass and (2) over or underestimated shrub productivity at the various hillslope positions. Our results indicate that land models need to account for hillslope-scale coupled surface and subsurface hydrology to accurately predict current plant distributions and future trajectories in Arctic ecosystems.

54 ENVIRONMENTAL SCIENCES↗

Reservoir Computing as a Tool for Climate Predictability Studies

Reduced-order dynamical models play a central role in developing our understanding of predictability of climate irrespective of whether we are dealing with the actual climate system or surrogate climate models. In this context, the linear inverse modeling (LIM) approach, by capturing a few essential interactions between dynamical components of the full system, has proven valuable in providing insights into predictability of the full system. We demonstrate that reservoir computing (RC), a form of learning suitable for systems with chaotic dynamics, provides an alternative nonlinear approach that improves on the predictive skill of the LIM approach. We do this in the example setting of predicting sea surface temperature in the North Atlantic in the preindustrial control simulation of a popular earth system model, the Community Earth System Model so that we can compare the performance of the new RC-based approach with the traditional LIM approach both when learning data are plentiful and when such data are more limited. The improved predictive skill of the RC approach over a wide range of conditions—larger number of retained EOF coefficients, extending well into the limited data regime, etc.—suggests that this machine-learning technique may have a use in climate predictability studies. While the possibility of developing a climate emulator—the ability to continue the evolution of the system on the attractor long after failing to be able to track the reference trajectory—is demonstrated in the Lorenz-63 system, it is suggested that further development of the RC approach may permit such uses of the new approach in more realistic predictability studies.

54 ENVIRONMENTAL SCIENCES↗

Subduction, Underplating, and Return Flow Recorded in the Cycladic Blueschist Unit Exposed on Syros, Greece

Exhumed high-pressure/low-temperature (HP/LT) metamorphic rocks provide insights into deep (~20–70 km) subduction interface dynamics. On Syros Island (Cyclades, Greece), the Cycladic Blueschist Unit preserves blueschist-to-eclogite facies oceanic- and continental-affinity rocks that record the structural and thermal evolution linked to Eocene subduction. Despite decades of research, the metamorphic and deformation history (P-T-D) and timing of subduction and exhumation are matters of ongoing discussion. We suggest that Syros comprises three coherent tectonic slices and that each slice underwent subduction, underplating, and syn-subduction return flow along similar P-T trajectories, but at progressively younger times. Subduction and exhumation are distinguished by lineations and ductile fold axis orientations, and are kinematically consistent with previous studies that document top-to-the-S-SW shear (prograde-to-peak subduction), top-to-the-NE shear (blueschist facies exhumation), and then E-W coaxial stretching (greenschist facies exhumation). Amphibole zonations record cooling during decompression, indicating return flow above a cold slab. Multi-mineral Rb-Sr isochrons and compiled metamorphic geochronology show that the three slices record distinct stages of peak subduction (53–52, ~50, and 45 Ma) that young with structural depth. Retrograde blueschist and greenschist facies fabrics span ~50–40 and ~43–20 Ma, respectively, and also young with structural depth. Synthesized data sets support a revised tectonic framework for Syros, involving subduction of structurally distinct coherent slices and simultaneous return flow of previously accreted tectonic slices in the subduction channel shear zone. Distributed, ductile, dominantly coaxial return flow in an Eocene-Oligocene subduction channel proceeded at rates of ~1.5–5 mm/yr and accommodated ~80% of the total exhumation of this HP/LT complex.

58 GEOSCIENCES↗

A Typology for Characterizing Human Action in MultiSector Dynamics Models

The role of individual and collective human agency is increasingly recognized as a prominent and arguably paramount determinant in shaping the behavior, trajectory, and vulnerability of multisector systems. This human influence operates at multiple scales: from short-term (hourly to daily) to long-term (annually to centennial) timescales, and from the local to the global, pushing systems towards either desirable or undesirable outcomes. However, the effort to represent human systems in multisector models has been fragmented across philosophical, methodological, and disciplinary lines. To cohere insights across diverse modeling approaches, we present a new typology for classifying how human actors are represented in the broad suite of coupled human-natural system models that are applied in MultiSector Dynamics (MSD) research. The typology conceptualizes a “sector” as a system-of-systems that includes a diverse group of human actors, defined across individual to collective social levels, involved in governing, provisioning, and utilizing products, goods, or services towards some human end. We trace the salient features of modeled representations of human systems by organizing the typology around three key questions: 1) Who are the modeled actors in MSD systems? 2) What are their modeled actions? 3) How and for what purpose are these actors and actions operationalized in a computational model? The typology is used to critically examine existing models and chart the frontier of future human systems modeling for MSD research.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Upper-Hybrid Waves Driven by Meandering Electrons Around Magnetic Reconnection X Line

Magnetic reconnection is a fundamental process in collisionless space plasma environment, and plasma waves relevant to the kinetic interactions can have a significant impact on the multiscale behavior of reconnection. Here, we present Magnetospheric Multiscale (MMS) observations during an encounter of an X line of symmetric magnetic reconnection in the magnetotail. The X line is characterized by reversals of ion and electron jets and electromagnetic fields, agyrotropic electron velocity distribution functions (VDFs), and an electron-scale current sheet. MMS observe large-amplitude nonlinear upper-hybrid (UH) waves on both sides of the neutral line, and the wave amplitudes have highly localized distribution along the normal direction. Here, the inbound meandering electrons drive the UH waves, releasing the free energy stored from the reconnection electric field along the meandering trajectories. The interaction between the meandering electrons and the UH waves may modify the balance of the reconnection electric field around the X line.

58 GEOSCIENCES↗

Solar Energetic Proton Access to the Inner Magnetosphere During the September 7–8, 2017 Event

Here, the access of solar energetic protons into the inner magnetosphere on September 7–8, 2017 is investigated by following reversed proton trajectories to compute the proton cutoff energy using the Dartmouth geomagnetic cutoff code (Kress et al., 2010, https://doi.org/10.1029/2009sw000488). The cutoff energies for protons coming from the west and east direction, the minimum and maximum cutoff energy respectively, are calculated every 5 min along the orbit of Van Allen Probes using TS07 and the Lyon-Fedder-Mobarry (LFM) MHD magnetic field model. The result shows that the cutoff energy increases significantly as the radial distance decreases, and that the cutoff energy decreases with the building up of the ring current during magnetic storms. Solar wind dynamic pressure also affects cutoff suppression (Kress et al., 2004, https://doi.org/10.1029/2003gl018599). The LFM-RCM model shows stronger suppression of cutoff energy than TS07 during strong solar wind driving conditions. The simulation result is compared with proton flux measurements, showing consistent variation of the cutoff location during the September 7–8, 2017 geomagnetic storm.

79 ASTRONOMY AND ASTROPHYSICS↗

Astrophysical Explosions Revisited: Collisionless Coupling of Debris to Magnetized Plasma

The coupling between a rapidly expanding cloud of ionized debris and an ambient magnetized plasma is revisited with a hybrid (kinetic ion/fluid electron) simulation code that allows a study over a wide range of plasma parameters. Over a specified range of hypothetical conditions, simple scaling laws in terms of the total debris mass and explosion speed are derived and verified for the maximal size of the debris cloud and the fraction of debris that free-streams from the burst along the magnetic field. Furthermore, the amount of debris that escapes from the burst with minimal coupling to the background magnetic field increases with the debris gyroradius. Test cases with two different debris species—including a heavy minority species with a relatively large gyroradius—highlight how the collisionless coupling of the debris depends on the single particle trajectories as well as the overall conservation of energy and momentum.

79 ASTRONOMY AND ASTROPHYSICS↗

Modification of the Loss Cone for Energetic Particles in the Earth's Inner Magnetosphere

The behavior of energetic particles in the Earth's dipole and stretched magnetic-field models is explored with a focus on the shift of the atmospheric loss cone away from the magnetic-field direction and on non-adiabatic behavior occurring when the particle gyroradius becomes comparable with the gradient scale length of the local magnetic field. It is shown that the equatorial loss cone is aberrated away from the magnetic-field direction (pitch angle of 0°) by the perpendicular drift of a charged particle (which is referred to as the “Mozer transform” described in Mozer (1966, https://doi.org/10.1029/JZ071i011p02701). It is found that the Mozer coordinate transformation in pitch-angle/gyrophase-angle space better organizes the behavior of bounce times, mirror altitudes, drift speeds, and first adiabatic invariant. It also describes the loss-cone shift accurately for a certain range of values of the adiabaticity parameter ϵ, defined by the ratio of the particle gyroradius to the local radius of curvature of the magnetic field. For particles with larger ϵ, the Mozer transform (evaluated with the standard gradient-curvature drift) breaks down and the “central trajectory” theory can be used to calculate the angular shift of the loss cone, which now includes an Earthward shift. When ϵ becomes relatively large, stochastic field line curvature (FLC) scattering occurs: we show the intimate connection between the strength of FLC scattering and the loss-cone shift. Finally, by comparing ion orbits in the dipole and Tsyganenko (Ts89 and Ts04) magnetic fields, we conclude that the loss cone of ring-current ions is significantly modified during geomagnetically active times.

79 ASTRONOMY AND ASTROPHYSICS↗

Shift in Peaks of PAH-Associated Health Risks From East Asia to South Asia and Africa in the Future

Lung cancer risk from exposure to ambient polycyclic aromatic hydrocarbons (PAHs) is expected to change significantly by 2050 compared to 2008 due to changes in climate and emissions. Integrating a global atmospheric chemistry model, a lung cancer risk model, and plausible future emissions trajectories of PAHs, we assess how global PAHs and their associated lung cancer risk will likely change in the future. Benzo(a)pyrene (BaP) is used as an indicator of cancer risk from PAH mixtures. From 2008 to 2050, the population-weighted global average BaP concentrations under all RCPs consistently exceeded the WHO-recommended limits, primarily attributed to residential biofuel use. Peaks in PAH-associated incremental lifetime cancer risk shift from East Asia (4 × 10 –5 ) in 2008 to South Asia (mostly India, 2–4 × 10 –5 ) and Africa (1–2 × 10 –5 ) by 2050. In the developing regions of Africa and South Asia, PAH-associated lung cancer risk increased by 30–64% from 2008 to 2050, due to increasing residential energy demand in households for cooking, heating, and lighting, the continued use of traditional biomass use, increases in agricultural waste burning, and forest fires, accompanied by rapid population growth in these regions. Due to more stringent air quality policies in developed countries, their PAH lung cancer risk substantially decreased by ~80% from 2008 to 2050. Climate change is likely to have minor effects on PAH lung cancer risk compared to the impact of emissions. Future policies, therefore, need to consider efficient combustion technologies that reduce air pollutant emissions, including incomplete combustion products such as PAH.

54 ENVIRONMENTAL SCIENCES↗

Forming the Future of Agrohydrology

Agricultural water management is increasingly prioritized throughout the world as producers are tasked with meeting growing crop demand while also managing environmental resources more sustainably. Likewise, agriculture is increasingly modifying the terrestrial water cycle. In response to these dynamics, the informal research discipline of agrohydrology continues to grow, fueled by a new era of rapidly evolving research tools and big data availability. While many researchers are actively invested in agrohydrology as a research topic, there remains a gap in formalizing this valuable discipline. This article aims to: (a) identify key research themes in agrohydrology, (b) conceptualize future research topics within each theme, and (c) estimate a timeframe before topics become pressing (i.e., before a topic becomes a limiting factor in advancing water management in an agricultural context). This commentary is meant to guide the trajectory of an evolving discipline of agrohydrology, the practice of agricultural water management at multiple nested scales, and the conversation of the invested public.

54 ENVIRONMENTAL SCIENCES↗

Scenario Discovery Analysis of Drivers of Solar and Wind Energy Transitions Through 2050

Deep human-Earth system uncertainties and strong multi-sector dynamics make it difficult to anticipate which conditions are most likely to lead to higher or lower adoption of renewable energy, and models project a broad range of future solar and wind energy shares across future scenarios. To elucidate these dynamics, we explore a large data set of scenarios simulated from the Global Change Analysis Model (GCAM) and use scenario discovery to identify the most significant factors affecting solar and wind adoption by mid-century. We generated a data set of over 4,000 scenarios from GCAM by varying 12 different socioeconomic factors at high and low levels, including assumptions about future energy demand, resource costs, and fossil fuel emissions paths, as well as specific technology assumptions including wind and solar backup requirements and storage costs. Using scenario discovery, we assess the most important factors globally and regionally in creating high fractions of solar and wind energy and explore interconnected effects on other systems including water and non-CO 2 emissions. Globally and regionally, we found that solar and wind-related technology costs were the primary drivers of high wind and solar energy adoption, though a few regions depend heavily on other parameters like carbon capture and storage costs, population and gross domestic product trajectories, and fossil fuel costs. We also identify four key paths to high solar and wind energy by mid-century and discuss their tradeoffs in terms of other outcomes.

14 SOLAR ENERGY↗

Energy Surplus and an Atmosphere‐Land‐Surface “Tug of War” Control Future Evapotranspiration

Abstract The 21st century evapotranspiration (ET) trends over the continental U.S. are assessed using innovative, energy‐based principles. Annual ET is projected to increase with high confidence at the rate of 20 mm for every 1℃ of rise in near‐surface air temperature, or 0.45 or 0.98 mm/year/year, depending on the emission scenario. The ET trajectory is dominated (58%) by the increase of land‐surface net radiative energy. An enhancement of the fraction of energy taken up by ET becomes a more important controller (53%) in late 21st century, under the high emission scenario. This increase is explained by the “tug of war” between atmospheric vapor demand and land‐surface ability to supply water. An assessment of future water availability (precipitation minus ET) shows no significant changes at the continental scale. This outcome nevertheless hides strong spatial variability, emphasizing the role of ET in shaping the distribution of water availability among human populations.

Xu, Donghui↗

Understanding Precipitation Bias Sensitivities in E3SM-Multi-Scale Modeling Framework From a Dilution Framework

We investigate a set of Energy Exascale Earth System Model Multi-scale modeling framework (MMF) (E3SM-MMF) simulations that vary the dimensionality and momentum transport configurations of the embedded cloud-resolving models (CRMs), including unusually ambitious 3D configurations. Issues endemic to all MMF simulations include too much Intertropical Convergence Zone rainfall and too little over the Amazon. Systematic MMF improvements include more on-equatorial rainfall across the Warm Pool. Interesting sensitivities to the CRM domain are found in the regional time-mean precipitation pattern over the tropics. The 2D E3SM-MMF produces an unrealistically rainy region over the northwestern tropical Pacific; this is reduced in computationally ambitious 3D configurations that use 1,024 embedded CRM grid columns per host cell. Trajectory analysis indicates that these regional improvements are associated with desirably fewer tropical cyclones and less extreme precipitation rates. To understand why and how the representation of precipitation improved in 3D, we propose a framework that dilution is stronger in 3D. This viewpoint is supported by multiple indirect lines of evidence, including a delayed moisture-precipitation pickup, smaller precipitation efficiency, and amplified convective mass flux profiles and more high clouds. We also demonstrate that the effects of varying embedded CRM dimensionality and momentum transport on precipitation can be identified during the first few simulated days, providing an opportunity for rapid model tuning without high computational cost. Meanwhile the results imply that other less computationally intensive ways to enhance dilution within MMF CRMs may also be strategic tuning targets.

54 ENVIRONMENTAL SCIENCES↗

Evaporation and Transpiration From Multiple Proximal Forests and Wetlands

Abstract Climate change is intensifying the hydrologic cycle and altering ecosystem function, including water flux to the atmosphere through evapotranspiration (ET). ET is made up of evaporation (E) via non‐stomatal surfaces, and transpiration (T) through plant stomata which are impacted by global changes in different ways. E and T are difficult to measure independently at the ecosystem scale, especially across multiple sites that represent different land use and land management strategies. To address this gap in understanding, we applied flux variance similarity (FVS) to quantify how E and T differ across 13 different ecosystems measured using eddy covariance in a 10 × 10 km area from the CHEESEHEAD19 experiment in northern Wisconsin, USA. The study sites included eight forests with a large deciduous broadleaf component, three evergreen needleleaf forests, and two wetlands. Average T/ET for the study period averaged nearly 52% in forested sites and 45% in wetlands, with larger values after excluding periods following rain events when evaporation from canopy interception may be expected. A dominance analysis revealed that environmental variables explained on average 69% of the variance of half‐hourly T, which decreased from summer to autumn. Deciduous and evergreen forests showed similar E trajectories over time despite differences in vegetation phenology, and vapor pressure deficit explained some 13% of the variance E in wetlands but only 5% or less in forests. Retrieval of E and T within a dense network of flux towers lends confidence that FVS is a promising approach for comparing ecosystem hydrology across multiple sites to improve our process‐based understanding of ecosystem water fluxes.

Environmental Sciences & Ecology↗

Revealing the Statistics of Extreme Events Hidden in Short Weather Forecast Data

Extreme weather events have significant consequences, dominating the impact of climate on society. While high-resolution weather models can forecast many types of extreme events on synoptic timescales, long-term climatological risk assessment is an altogether different problem. A once-in-a-century event takes, on average, 100 years of simulation time to appear just once, far beyond the typical integration length of a weather forecast model. Therefore, this task is left to cheaper, but less accurate, low-resolution or statistical models. But there is untapped potential in weather model output: despite being short in duration, weather forecast ensembles are produced multiple times a week. Integrations are launched with independent perturbations, causing them to spread apart over time and broadly sample phase space. Collectively, these integrations add up to thousands of years of data. We establish methods to extract climatological information from these short weather simulations. Using ensemble hindcasts by the European Center for Medium-range Weather Forecasting archived in the subseasonal-to-seasonal (S2S) database, we characterize sudden stratospheric warming (SSW) events with multi-centennial return times. Consistent results are found between alternative methods, including basic counting strategies and Markov state modeling. By carefully combining trajectories together, we obtain estimates of SSW frequencies and their seasonal distributions that are consistent with reanalysis-derived estimates for moderately rare events, but with much tighter uncertainty bounds, and which can be extended to events of unprecedented severity that have not yet been observed historically. These methods hold potential for assessing extreme events throughout the climate system, beyond this example of stratospheric extremes.

58 GEOSCIENCES↗

Forest Carbon Storage in the Western United States: Distribution, Drivers, and Trends

Abstract Forests are a large carbon sink and could serve as natural climate solutions that help moderate future warming. Thus, establishing forest carbon baselines is essential for tracking climate‐mitigation targets. Western US forests are natural climate solution hotspots but are profoundly threatened by drought and altered disturbance regimes. How these factors shape spatial patterns of carbon storage and carbon change over time is poorly resolved. Here, we estimate live and dead forest carbon density in 19 forested western US ecoregions with national inventory data (2005–2019) to determine: (a) current carbon distributions, (b) underpinning drivers, and (c) recent trends. Potential drivers of current carbon included harvest, wildfire, insect and disease, topography, and climate. Using random forests, we evaluated driver importance and relationships with current live and dead carbon within ecoregions. We assessed trends using linear models. Pacific Northwest (PNW) and Southwest (SW) ecoregions were most and least carbon dense, respectively. Climate was an important carbon driver in the SW and Lower Rockies. Fire reduced live and increased dead carbon, and was most important in the Upper Rockies and California. No ecoregion was unaffected by fire. Harvest and private ownership reduced carbon, particularly in the PNW. Since 2005, live carbon declined across much of the western US, likely from drought and fire. Carbon has increased in PNW ecoregions, likely recovering from past harvest, but recent record fire years may alter trajectories. Our results provide insight into western US forest carbon function and future vulnerabilities, which is vital for effective climate change mitigation strategies.

Environmental Sciences & Ecology↗