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At least 19 records

Coastal typologies and surface and subsurface characteristics of the Alaskan Beaufort Sea Coast

This dataset was generated to classify the Alaskan Beaufort Sea Coast (ABSC) into a set of distinct coastal typologies, to understand the surface and subsurface characteristics and variability of the ABSC, and to quantify relationships between these characteristics and historical rates of shoreline change. This geospatial dataset contains two csv files of points along the ABSC at a 50 m spacing, one for points sheltered by a barrier island and one for points exposed to the open ocean. Each point has a lat/lon location, and we have attributed to each point average values for elevation, historical long-term shoreline change rates, shoreline orientation, landcover, mean annual ground temperature, geomorphic unit, lithology, geology, ecological landscape unit, maximum thaw settlement potential, massive ice content, and segregated ice content. Each point is also assigned to one of 16 coastal typologies, determined by a hierarchical clustering algorithm on the elevation, shoreline change, orientation, and ground temperature data. There are 9 sheltered typologies and 7 exposed typologies, identified by an integer label in the last column of each csv file. The other two csv files contain the integer IDs and classes for the landcover and geomorphology datasets.

54 ENVIRONMENTAL SCIENCES↗

Steady global surface warming from 1973 to 2022 but increased warming rate after 1990

The change in global mean surface temperature is a crucial and broadly used indicator of the evolution of climate change. Any decadal scale changes in warming rate are however obfuscated by internal variability. Here we show that the surface temperature increase through the recent La Nina influenced years (2022) is consistent with the 50-year trend of 0.18 °C/decade. We use an Earth System Model based tool to filter out modulations to the warming rate by sea-surface temperature patterns and find consistent warming rates in four major global temperature data series. However, we also find clear indications, in all observational series, of a step-up in warming rate since around 1990. CMIP6 models generally do not capture this observed combination of long-term warming rate and recent increase.

58 GEOSCIENCES↗

Utah FORGE: Phase 3 InSAR Study Results

Ground movement is evaluated through analysis of Interferometric Synthetic Aperture Radar (InSAR) interferograms. Results indicate there has been no detectable ground movement at millimeter scale. The zipped file in this submission contains a report, maps, and results from the InSAR Phase 3 study done to determine ground crustal deformation, if any, in the Utah FORGE area. The data used to facilitate this study included synthetic aperture radar data acquired by the TerraSAR-X and TanDEM-X satellite missions operated by the German Space Agency (DLR). It is accompanied by a README.txt file which further describes each included dataset.

15 GEOTHERMAL ENERGY↗

Near Detector Selection for Neutral Current Disappearance Search at the Short-Baseline Neutrino Program

Various short baseline neutrino experiments observe anomalies that challenge the three-flavor neutrino oscillation model, consistent with a hypothetical “sterile” neutrino that does not interact via the weak force. This poster presents a near detector event selection at the Short-Baseline Near Detector (SBND), developed for the first search for neutral current (NC) disappearance at short-baseline experiments. NC disappearance provides ``smoking gun” insight into the sterile neutrino question because NC interactions are equally sensitive to all three active neutrinos, meaning any change in the NC interaction rate between near and far detectors cannot be explained by oscillations among known flavor states. This analysis focuses on the NC1p topology, the most common NC interaction type at the Short-Baseline Neutrino (SBN) Program. NC topologies are inherently challenging due to their low light yield and the absence of an outgoing charged lepton, which complicates identification and leads to poor energy reconstruction as the outgoing neutrino carries away a large portion of the neutrino’s initial energy. This work presents an NC1p event selection at the near detector, highlighting SBND’s impressive detector capabilities, including trigger efficiency studies. Combined with a novel kinematic energy reconstruction technique leveraging the detector’s outstanding hadronic detail, this analysis establishes a robust near detector foundation to target an NC disappearance measurement consistent with the 3$+$1 sterile neutrino model. This SBND selection will soon be combined with the far detector to conduct an NC disappearance search, providing unique insight and complementary information to traditional charged current searches and advancing the SBN Program’s goal to resolve the sterile neutrino question, including 3$+$1 searches and beyond.

Nicole Pallat, Nicole Pallat [Minnesota U.] (ORCID↗

A storyline analysis of Hurricane Irma’s precipitation under various levels of climate warming

Abstract Understanding how extreme weather, such as tropical cyclones, will change with future climate warming is an interesting computational challenge. Here, the hindcast approach is used to create different storylines of a particular tropical cyclone, Hurricane Irma (2017). Using the community atmosphere model, we explore how Irma’s precipitation would change under various levels of climate warming. Analysis is focused on a 48 h period where the simulated hurricane tracks reasonably represent Irma’s observed track. Under future scenarios of 2 K, 3 K, and 4 K global average surface temperature increase above pre-industrial levels, the mean 3-hourly rainfall rates in the simulated storms increase by 3–7% K −1 compared to present. This change increases in magnitude for the 95th and 99th percentile 3-hourly rates, which intensify by 10–13% K −1 and 17–21% K −1 , respectively. Over Florida, the simulated mean rainfall accumulations increase by 16–26% K −1 , with local maxima increasing by 18–43% K −1 . All percent changes increase monotonically with warming level.

Environmental Sciences & Ecology↗

Droplet Growth or Evaporation Does Not Buffer the Variability in Supersaturation in Clean Clouds

Abstract Water vapor supersaturation in clouds is a random variable that drives activation and growth of cloud droplets. The Pi Convection–Cloud Chamber generates a turbulent cloud with a microphysical steady state that can be varied from clean to polluted by adjusting the aerosol injection rate. The supersaturation distribution and its moments, e.g., mean and variance, are investigated for varying cloud microphysical conditions. High-speed and collocated Eulerian measurements of temperature and water vapor concentration are combined to obtain the temporally resolved supersaturation distribution. This allows quantification of the contributions of variances and covariances between water vapor and temperature. Results are consistent with expectations for a convection chamber, with strong correlation between water vapor and temperature; departures from ideal behavior can be explained as resulting from dry regions on the warm boundary, analogous to entrainment. The saturation ratio distribution is measured under conditions that show monotonic increase of liquid water content and decrease of mean droplet diameter with increasing aerosol injection rate. The change in liquid water content is proportional to the change in water vapor concentration between no-cloud and cloudy conditions. Variability in the supersaturation remains even after cloud droplets are formed, and no significant buffering is observed. Results are interpreted in terms of a cloud microphysical Damköhler number (Da), under conditions corresponding to , i.e., the slow-microphysics regime. This implies that clouds with very clean regions, such that is satisfied, will experience supersaturation fluctuations without them being buffered by cloud droplet growth. Significance Statement The saturation ratio (humidity) in clouds controls the growth rate and formation of cloud droplets. When air in a turbulent cloud mixes, the humidity varies in space and time throughout the cloud. This is important because it means cloud droplets experience different growth histories, thereby resulting in broader size distributions. It is often assumed that growth and evaporation of cloud droplets buffers out some of the humidity variations. Measuring these variations has been difficult, especially in the field. The purpose of this study is to measure the saturation ratio distribution in clouds with a range of conditions. We measure the in-cloud saturation ratio using a convection cloud chamber with clean to polluted cloud properties. We found in clouds with low concentrations of droplets that the variations in the saturation ratio are not suppressed.

54 ENVIRONMENTAL SCIENCES↗

Ocean Variability Beneath the Filchner-Ronne Ice Shelf Inferred From Basal Melt Rate Time Series

Fourteen phase-sensitive radars (ApRES) were deployed on the Filchner-Ronne Ice Shelf (FRIS) to measure variability in its basal melt rate. Melt rates from sites along the Ronne Depression vary seasonally, consistent with the dynamics of the propagation of seasonal dense water from the western ice front into the cavity. Several sites at the back of the FRIS cavity feature a signal with two seasonal maxima. Sub-ice shelf oceanographic data available from one of the sites indicate that this signal is caused by two different pathways followed by the same source water. Inter-annual variability is strongest along a direct flow pathway between western Ronne Ice Front and western Berkner Island. Highest melting occurred in 1999 and 2018, following anomalously low summer sea-ice concentrations in front of the ice shelf. Inter-annual melt rate variability at the back of the FRIS cavity is limited. If present, it is expressed as a suppression or delay in the arrival of the seasonal melt rate minimum, which can be understood in terms of inter-annual stratification changes and variable inflow pathways toward the sites. Long term mean ApRES melt rates agree with estimates from satellite data over eastern FRIS. However, the satellite estimates overstate the area of active basal freezing in the western part of the ice shelf. Furthermore, the temporal melt rate variability from the satellite estimates exaggerates the range of variability at both seasonal and inter-annual time scales with any correspondence between the in-situ and remotely derived inter-annual variability being limited to a single site.

54 ENVIRONMENTAL SCIENCES↗

Initial soil organic carbon stocks govern changes in soil carbon: Reality or artifact?

Abstract Changes in soil organic carbon (SOC) storage have the potential to affect global climate; hence identifying environments with a high capacity to gain or lose SOC is of broad interest. Many cross‐site studies have found that SOC‐poor soils tend to gain or retain carbon more readily than SOC‐rich soils. While this pattern may partly reflect reality, here we argue that it can also be created by a pair of statistical artifacts. First, soils that appear SOC‐poor purely due to random variation will tend to yield more moderate SOC estimates upon resampling and hence will appear to accrue or retain more SOC than SOC‐rich soils. This phenomenon is an example of regression to the mean. Second, normalized metrics of SOC change—such as relative rates and response ratios—will by definition show larger changes in SOC at lower initial SOC levels, even when the absolute change in SOC does not depend on initial SOC. These two artifacts create an exaggerated impression that initial SOC stocks are a major control on SOC dynamics. To address this problem, we recommend applying statistical corrections to eliminate the effect of regression to the mean, and avoiding normalized metrics when testing relationships between SOC change and initial SOC. Careful consideration of these issues in future cross‐site studies will support clearer scientific inference that can better inform environmental management.

54 ENVIRONMENTAL SCIENCES↗

Divergent urbanization-induced impacts on global surface urban heat island trends since 1980s

Urbanization experiences different speeds and forms under diverse development stages across the globe. However, urbanization-induced impacts on long-term surface urban heat island intensity (I s ) trends across global cities and the regulators of such impacts remain understudied. Here we estimate interannual trends in daytime I s (i.e., urban-rural differences in surface temperatures) across 511 major cities for 1985 –2020 using annual averages calculated by using reconstructed land surface temperature data derived from more than >250,000 Landsat thermal images. Our study reveals that the global mean I s growth rate is 0.156 °C/decade. We further examine I s change associated with per 1% impervious land growth (denoted as ß) in each city throughout the research period and during different periods. The global mean ß is 0.018 ± 0.025 °C/% (mean ± 1 standard deviation) for the whole period, with greater values in humid than in arid climates; and the ß may change during different periods, e.g., it has more than tripled when urban impervious land exceeds 30%, indicating the spatiotemporally divergent impacts of urbanization on Is trends across global cities. The spatial variations in ß across global cities are well correlated with rural vegetation abundance and precipitation but not with urban population. Among these three factors, rural vegetation abundance possesses the greatest standardized regression coefficient of partial least-squares model, signifying the critical role of biome background in regulating ß. Furthermore, the finding implies that future urbanization over densely vegetated regions should be more carefully and strategically planned due to the greater urbanization-induced surface warming effect.

54 ENVIRONMENTAL SCIENCES↗

Topography Controls Variability in Circumpolar Permafrost Thaw Pond Expansion

Abstract One of the most conspicuous signals of climate change in high‐latitude tundra is the expansion of ice wedge thermokarst pools. These small but abundant water features form rapidly in depressions caused by the melting of ice wedges (i.e., meter‐scale bodies of ice embedded within the top of the permafrost). Pool expansion impacts subsequent thaw rates through a series of complex positive and negative feedbacks which play out over timescales of decades and may accelerate carbon release from the underlying sediments. Although many local observations of ice wedge thermokarst pool expansion have been documented, analyses at continental to pan‐Arctic scales have been rare, hindering efforts to project how strongly this process may impact the global carbon cycle. Here we present one of the most geographically extensive and temporally dense records yet compiled of recent pool expansion, in which changes to pool area from 2008 to 2020 were quantified through satellite‐image analysis at 27 survey areas (measuring 10–35 km 2 each, or 400 km 2 in total) dispersed throughout the circumpolar tundra. The results revealed instances of rapid expansion at 44% (15%) of survey areas. Considered alone, the extent of departures from historical mean air temperatures did not account for between site variation in rates of change to pool area. Pool growth was most clearly associated with upland (i.e., hilly) terrain and elevated silt content at soil depths greater than one meter. These findings suggest that, at short time scales, pedologic and geomorphologic conditions may exert greater control on pool dynamics in the warming Arctic than spatial variability in the rate of air temperature increases.

Abolt, C. J.↗

Feedback regulation of crystal growth by buffering monomer concentration

Abstract Crystallization is a ubiquitous means of self-assembly that can organize matter over length scales orders of magnitude larger than those of the monomer units. Yet crystallization is notoriously difficult to control because it is exquisitely sensitive to monomer concentration, which changes as monomers are depleted during growth. Living cells control crystallization using chemical reaction networks that offset depletion by synthesizing or activating monomers to regulate monomer concentration, stabilizing growth conditions even as depletion rates change, and thus reliably yielding desired products. Using DNA nanotubes as a model system, here we show that coupling a generic reversible bimolecular monomer buffering reaction to a crystallization process leads to reliable growth of large, uniformly sized crystals even when crystal growth rates change over time. Buffering could be applied broadly as a simple means to regulate and sustain batch crystallization and could facilitate the self-assembly of complex, hierarchical synthetic structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A decreasing carbon allocation to belowground autotrophic respiration in global forest ecosystems

Belowground autotrophic respiration (RAsoil) depends on carbohydrates from photosynthesis flowing to roots and rhizospheres, and is one of the most important but least understood components in forest carbon cycling. Carbon allocation plays an important role in forest carbon cycling and reflects forest adaptation to changing environmental conditions. However, carbon allocation to RAsoil has not been fully examined at the global scale. To fill this knowledge gap, first, the spatio-temporal patterns of RAsoil from 1981 to 2017 were predicted by a Random Forest (RF) algorithm using the most updated Global Soil Respiration Database (v5) with global environmental variables; second, carbon allocation from photosynthesis to RAsoil (CAB), was calculated as the ratio of RAsoil to gross primary production; and its temporal and spatial patterns were assessed in global forest ecosystems. . Globally, mean RAsoil from forests was 8.9 ± 0.08 Pg C yr-1 (mean ± standard deviation) from 1981 to 2017 with strong spatial variabilities. Temporally, RAsoil increased at a rate of 0.0059 Pg C yr-2, paralleling broader soil respiration changes and indicating increasing carbon respired by roots. Mean CAB was 0.243 ± 0.016 and decreased over time. The temporal trend of CAB varied greatly in space, reflecting uneven responses of CAB to environmental changes. This study is the first attempt to predict global CAB and analyze its temporal and spatial patterns. With the linkage of carbon use efficiency, the developed CAB offers an completely independent approach to quantify global aboveground autotropic respiration spatially and temporally, which could provide crucial insights into carbon flux partition and global carbon cycling under climate change.

Tang, Xiaolu↗

Ocean Surface Flux Algorithm Effects on Earth System Model Energy and Water Cycles

Earth system models parameterize ocean surface fluxes of heat, moisture, and momentum with empirical bulk flux algorithms, which introduce biases and uncertainties into simulations. We investigate the atmosphere and ocean model sensitivity to algorithm choice in the Energy Exascale Earth System Model (E3SM). Flux differences between algorithms are larger in atmosphere simulations (where wind speeds can vary) than ocean simulations (where wind speeds are fixed by forcing data). Surface flux changes lead to global scale changes in the energy and water cycles, notably including ocean heat uptake and global mean precipitation rates. Compared to the control algorithm, both COARE and University of Arizona (UA) algorithms reduce global mean precipitation and top of atmosphere radiative biases. Further, UA may slightly reduce biases in ocean meridional heat transport. We speculate that changes seen here, especially in the ocean, could be even larger in coupled simulations.

54 ENVIRONMENTAL SCIENCES↗

Frequency Resilience Enhancement for Power Systems with High Penetration of Grid-Forming Inverters

Abstract—Grid following inverter-based renewable generation has replaced conventional generation in recent years, resulting in lower system inertia. The frequency resilience in such a lower inertia system is critical for emergency mitigation. In this paper, we propose a resilience metric based on frequency recovery to quantitatively represent system resilience in terms of the rate of change of frequency. Application of grid-forming converters provides a means to improve system resilience by providing virtual inertia. An under-frequency load shedding strategy is applied to further support frequency recovery in cases with high penetration of grid-forming inverters. Case studies are designed and performed in a modified IEEE 9-bus test system using the PSCAD/EMTDC platform. Simulation results demonstrate the validity of the proposed resilience metric and the effectiveness of the strategy for reducing frequency excursion in inverter-based power systems. citation: J. Gui, H. Lei, T. R. McJunkin and B. K. Johnson, "Frequency Resilience Enhancement for Power Systems with High Penetration of Grid-Forming Inverters," 2023 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), Washington, DC, USA, 2023, pp. 1-5, doi: 10.1109/ISGT51731.2023.10066357.

14 SOLAR ENERGY↗

Structural complexity and primary production resistance are coupled in a temperate forest

The capacity of forests to resist structural change and retain material legacies–the biotic and abiotic resources that persist through disturbance–is crucial to sustaining ecosystem function after disturbance. However, the role of forest structure as both a material legacy and feature supporting carbon (C) cycling stability following disturbance has not been widely investigated. We used a large-scale disturbance manipulation to ask whether legacies of lidar-derived canopy structures drive 3-year primary production responses to disturbance. As part of the Forest Resilience Threshold Experiment (FoRTE) in northern Michigan, USA we simulated phloem-disrupting disturbances producing a range of severities and affecting canopy trees of different sizes. We quantified the legacies of forest structure using two approaches: one measuring the change in structure and primary production from pre-to post-disturbance and the second estimating resistance as log transformed ratios of control and treatment values. We found that total aboveground wood net primary production (ANPP w ) was similar across disturbance severities as legacy trees rapidly increased rates of primary production. Experiment-wide, the disturbance had limited effects on change in mean structural complexity values; however, high variance underscored large differences in the magnitude and direction of complexity's response at the plot-scale. Plot-scale structural complexity, but not vegetation area index (VAI), resistance strongly predicted ANPP w resistance while temporal VAI and structural complexity changes did not. We conclude that the presence of material legacies in the form of forest structure may affect primary production stability following disturbance and that how legacies are quantified may affect the interpretation of disturbance response.

lidar—remote sensing↗

Deep Deception: Exemplars of Adversarial Machine Learning and Countermeasures Applicable to International Safeguards

As a follow-up to our more comprehensive report on Adversarial Machine Learning (AML), here we provide demonstrations of AML attacks against the Limbo image database of UF6 cylinders in a variety of orientations and amongst a variety of distractor images. We demonstrate the Carlini & Wagner AML attack against a subset of Limbo images, with 100% attack success rate; meaning all attacked images were misclassified by a highly accurate trained model, yet the image changes were imperceptible to the human eye. We also demonstrate successful attacks against segmented images (images with more than one targeted object). Finally, we demonstrated the Fast Fourier Transform countermeasure that can be used to detect AML attacks on images. The intent of this and our previous report is to inform the IAEA and stakeholders of both the promise of machine learning, which could greatly improve the efficiency of surveillance monitoring, but also of the real threat of AML and potential defenses.

97 MATHEMATICS AND COMPUTING↗

Long-term patterns of post-fire harvest diverge among ownerships in the Pacific West, U.S.A.

Abstract Post-fire harvest (PFH) is a forest management practice designed to salvage value from burned timber, mitigate safety hazards from dead trees, reduce long-term fuels, and prepare sites for replanting. Despite public controversy and extensive ecological research, little is known about how much PFH occurs on private and public lands in the U.S. Pacific West, or how practices changed with shifting forest policy and increasing area burned over the last three decades. We mapped PFH across 2.2M burned hectares in California, Oregon, and Washington between 1986-2017 and used time series intervention analysis to compare trends in area, rate (% of burned area harvested), and mean patch size between private (0.5M ha) and federal (1.6M ha) forest land and across a gradient of burn severity. Harvest rates varied by ownership (4.9% federal, 18.6% private, 8.0% overall), and practices evolved and diverged over the study period. PFH area and rate declined across all ownerships in the mid-1990s during a period of reduced fire activity. As area burned increased between the early 2000s and late 2010s, PFH area rebounded and surpassed late-1980s levels, while rates remained relatively low. On federal lands, PFH practices shifted in the early-to-mid 1990s towards lower rates (10.3% to 3.8%) and smaller patches (6.0 to 3.3 ha), following policy changes and increased litigation. PFH rates on federal lands decreased at all levels of burn severity, with the largest decreases (6.2% to 1.2%) in forests with low tree mortality (i.e. fire refugia). Conversely, private PFH rates and mean patch sizes more than doubled in forests burned at very low-to-moderate severity. Our results highlight how PFH practices have shifted with policy, socio-economic pressure, and increasing area burned over 31 years in the Pacific West. A similar area of post-fire harvest is now dispersed over larger fires, with practices diverging substantially between ownerships.

Zuspan, Aaron (ORCID:0000000315833710)↗

Sensitivity of tropical orographic precipitation to wind speed with implications for future projections

Abstract. Some of the rainiest regions on Earth lie upstream of tropical mountains, where the interaction of prevailing winds with orography produces frequent precipitating convection. Yet the response of tropical orographic precipitation to the large-scale wind and temperature variations induced by anthropogenic climate change remains largely unconstrained. Here, we quantify the sensitivity of tropical orographic precipitation to background cross-slope wind using theory, idealized simulations, and observations. We build on a recently developed theoretical framework that characterizes the orographic enhancement of seasonal mean precipitation, relative to upstream regions, as a response of convection to cooling and moistening of the lower free troposphere by stationary orographic gravity waves. Using this framework and convection-permitting simulations, we show that higher cross-slope wind speeds deepen the penetration of the cool and moist gravity wave perturbation upstream of orography, resulting in a mean rainfall increase of 20 % (m s−1)−1 to 30 % (m s−1)−1 increase in cross-slope wind speed. Additionally, we show that orographic precipitation in five tropical regions exhibits a similar dependence on changes in cross-slope wind at both seasonal and daily timescales. Given next-century changes in large-scale winds around tropical orography projected by global climate models, this strong scaling rate implies wind-induced changes in some of Earth's rainiest regions that are comparable with any produced directly by increases in global mean temperature and humidity.

Nicolas, Quentin (ORCID:000000024116973X)↗