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At least 1,369 records · Page 76

Tracking Aerosol Convection Interactions Experiment (TRACER) Field Campaign Report

Convective clouds serve a critical role in the Earth’s energy and water cycles through their transport of heat, moisture, momentum, and chemical species through the troposphere driving the global circulation (e.g., Hartmann et al. 1984, Del Genio et al. 2012, Su et al. 2014). On more local scales, convective clouds impact the atmospheric heating profile through diabatic heating effects, removal of water from the atmospheric column through precipitation, and conditioning of the local environment impacting further development of clouds (e.g., Sullivan and Voigt 2021). These critical roles underscore the importance of realistic representation of convective processes across scales of models from large-eddy simulation (LES), to convection-permitting models (CPM; e.g., Kendon et al. 2020, Marinescu et al. 2021), to numerical weather prediction (NWP) models used for operational weather forecasting, to Earth system models used to predict climate sensitivity (Sanderson et al. 2011, Sherwood et al. 2014, Tomassini et al. 2014, Zhao et al. 2016, Cronin et al. 2017). A key component of improving model representation of convective clouds is better quantification and parameterization of updraft microphysics and dynamics, including their interactions with the surrounding environment and storm organization (Bony et al. 2015, Hagos and Houze 2016, Donner et al. 2016, Morrison et al. 2020). Aerosol is an important environmental factor that could affect convective clouds and precipitation since cloud droplet and ice formation processes are initiated by it. Andrae et al. (2004) hypothesized that aerosols associated with increased biomass burning particles acting as cloud condensation nuclei (CCN) result in smaller and more monodisperse cloud droplets leading to suppression of warm rain formation, ultimately leading to more cloud water being lofted above the freezing level based on observations in the Amazon region. The subsequent increase in latent heat release increases the buoyancy of rising convective parcels invigorating the deep convection. This work was followed by a description of the theoretical basis for this “cold-phase invigoration” by Rosenfeld et al. (2008), who argued that it could have a significant effect for deep convective clouds with warm cloud-bases. Several modeling studies (e.g., Khain et al. 2005, 2009, van den Heever et al. 2006, Fan et al. 2007, 2009, 2012, Lee et al. 2008, Storer et al. 2010, Lebo et al. 2012, Storer and van den Heever 2013, Chen et al. 2020, Dagan et al. 2022) have investigated these aerosol-convection interactions and the environmental factors that influence their relative importance and magnitude. More recently, several studies have indicated that “warm-phase invigoration”, the enhancement of convection through condensational heating, also appears to play a role in enhancing both shallow cumuli (Seiki and Nakajima 2014, Saleeby et al 2015) and deeper tropical convection (Lebo and Seinfeld 2011, Khain et al. 2012, Sheffield et al 2015, Fan et al. 2018, Igel and van den Heever 2021), as well as Houston thunderstorms (Fan et al. 2007, 2020). However, still other studies have provided additional evidence of systematic biases in simulated convective outflow ice size distribution properties, which are consistent with a lack of poorly understood secondary ice production within convective updrafts (e.g., Fridlind et al. 2017). To help address these critical gaps in our understanding of cloud processes, aerosol processes and aerosol-cloud interactions, the Tracking Aerosol Convection Interactions Experiment was designed building upon efforts by the Aerosol, Cloud, Precipitation and Climate (ACPC) Initiative (http://acpcintiative.org/), a joint effort of the International Geosphere-Biosphere Programme (IGBP) and the World Climate Research Program (WCRP) that focused on resolving uncertainties in the interactions between aerosol and clouds towards better understanding the role that these interactions play in the climate system. The TRACER campaign was motivated by recommendations from a number of pilot studies undertaken by ACPC (van den Heever et al. 2017, Fridlind et al. 2019, Hu et al. 2019, Fan et al. 2020, Marinescu et al. 2021, Hernandez-Deckers et al. 2022) that pointed towards the southeastern Texas region as a locale where aerosol-convection interactions could be studied owing to the copious occurrence of isolated convection during the summer months accompanied by diverse and significant sources of aerosols from both anthropogenic and natural sources. The TRACER campaign began on 01 October 2021 and extended through 30 September 2022 with an intensive operational period (IOP) during June-September 2022. Three main sites (Table 1) were managed by the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility.

54 ENVIRONMENTAL SCIENCES↗

The Sensitivity of GPz Estimates of Photo-z Posterior PDFs to Realistically Complex Training Set Imperfections

The accurate estimation of photometric redshifts is crucial to many upcoming galaxy surveys, for example, the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). Almost all Rubin extragalactic and cosmological science requires accurate and precise calculation of photometric redshifts; many diverse approaches to this problem are currently in the process of being developed, validated, and tested. In this work, we use the photometric redshift code GPz to examine two realistically complex training set imperfections scenarios for machine learning based photometric redshift calculation: (i) where the spectroscopic training set has a very different distribution in color–magnitude space to the test set, and (ii) where the effect of emission line confusion causes a fraction of the training spectroscopic sample to not have the true redshift. By evaluating the sensitivity of GPz to a range of increasingly severe imperfections, with a range of metrics (both of photo-z point estimates as well as posterior probability distribution functions, PDFs), we quantify the degree to which predictions get worse with higher degrees of degradation. In particular, we find that there is a substantial drop-off in photo-z quality when line-confusion goes above ~1%, and sample incompleteness below a redshift of 1.5, for an experimental setup using data from the Buzzard Flock synthetic sky catalogs.

79 ASTRONOMY AND ASTROPHYSICS↗

Ultrafast population and structural dynamics of a Ni-bipyridine photoredox catalyst reveal a significant deactivation pathway

The ultrafast excited state pathways and dynamics of NiII-bipyridine complexes influence the yield of photochemical processes involved in their catalytic cross-coupling reactions. Here we present ultrafast Ni K x-ray emission spectroscopy (XES) and x-ray solution scattering (XSS) of a NiII-bipyridine aryl halide complex, [Ni(t-Bubpy)(o-tol)Br], to quantify the excited state population dynamics and structural changes of the pre-catalyst. Due to the local spin-sensitivity of XES, the population dynamics of metal-to-ligand charge transfer (MLCT) and metal-centered (MC) excited states is established. A rapid ground state recovery pathway is newly identified, representing a significant deactivation pathway during photocatalysis. Furthermore, the pseudotetrahedral structure of the long-lived MC excited state is unambiguously identified and refined by XSS. The results advance our understanding of the ultrafast relaxation mechanisms that impact the photocatalytic mechanism and yield for NiII-bipyridine aryl halide cross-coupling catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

In situ liquid SIMS analysis of uranium oxide

Trace analysis of nuclear materials in solid particles collected in the environment or particles in liquid slurry generated in nuclear material manufacturing processes can pinpoint elemental, organic, and isotopic signatures of nuclear fuel cycle activities and processes. Such information can support nuclear safeguards programs by increasing our ability to detect undeclared nuclear materials, routine activities for safeguarding at declared facilities, and illicit activities. However, trace radioactive material analysis in liquids and slurries is challenging using bulk approaches. For example, one drawback of sensitive analysis such as inductively coupled plasma mass spectrometry (ICP-MS) is that sample is consumed or destroyed as a result of the technical approach. We developed a vacuum compatible microfluidic interface to enable surface analysis of liquids and liquid-solid interactions using time-of-flight secondary ion mass spectrometry (ToF-SIMS). In this work, we illustrate initial results of liquid standards containing uranium using in situ liquid SIMS. Specifically a series of diluted uranium standards used for ICPMS analysis were studied and the limit of detection was estimated. Since the liquid SIMS analysis is almost nondestructive, the same sample can be analyzed by other more destructive approaches afterwards or saved for future references. Consequently, multimodal analysis is possible. Our results demonstrate that in situ liquid SIMS can be used as a new approach to analyze radioactive materials in liquid and slurry forms of relevance to the IAEA safeguards missions.

In situ liquid ToF-SIMS, uranium, limit of detecti↗

Voltammetry measurements in lithium chloride-lithium oxide (LiCl–Li 2 O) salt: An evaluation of working electrode materials

Instrumentation to provide process monitoring (PM) and safeguards for the oxide reduction (OR) step in the electrochemical processing of used oxide nuclear fuel is necessary to ensure equipment is operated as declared. Cyclic voltammetry (CV) has been proposed for real-time monitoring of the operation of an OR process for safeguards purposes. In this study, different materials including 316 stainless steel (SS), tantalum (Ta), molybdenum (Mo), tungsten (W), platinum (Pt), and iridium (Ir) were evaluated as potential working electrode (WE) materials based on their chemical inertness, corrosion resistance, and sensitivity in detecting Li 2 O and other chloride salts in the OR electrolyte. Of the electrodes evaluated, 316 SS, Ir, and Pt all performed reasonably well in the LiCl-Li 2 O electrolyte. Here, stainless steel was operated in the cathodic potential and had reasonable corrosion resistance and is relatively inexpensive. Iridium could be operated in both the cathodic and anodic potentials and was the most corrosion resistant of those evaluated. Platinum is limited to the anodic potential range, had reasonable corrosion resistance, and was the most sensitive to Li 2 O concentrations in the salt. In the development of a stand-alone safeguards instrumentation, our recommendation is a CV sensor fitted with both Ir and Pt WEs. The results in this study may also be helpful for anode material selection in other electrometallurgy industries, such as molten salt electrolysis.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Using Best Basis Inventory Data to Direct Strategies for Real Time Monitoring of Hanford High Level Waste – 26226

The potential to accelerate the processing of low- and high-level tank waste by applying real-time monitoring (RTM) of chemical and physical properties has prompted research into the suitability of multiple analytical methods for that purpose. The broad variety of waste stream properties and the large number of analytes of interest (as evidenced by Waste Acceptance Criteria (WAC) and Process Control Limit (PCL) lists) lead to an overwhelming set of possible analytical scenarios. This report describes the use of Best Basis Inventory (BBI) data to find the most relevant analytical targets for the specific case of monitoring the blending of High Level Waste from multiple tanks prior to introduction into a vitrification facility. Campaigns for blending this waste to minimize the risk of exceeding WACs and PCLs have been proposed. However, the predicted compositions of the blended materials do not incorporate any uncertainties that may be associated with the representativeness of the waste layer samples or the laboratory analyses that generated the BBI data. Also, they do not include any uncertainty associated with the precision of collecting highly specific fractions of the layers during a blending campaign or any inhomogeneities that may exist in those layers. Monte Carlo methods are used to apply uncertainties to the compositions of the individual layers specified in the campaign recipes. The resulting variations in the compositions of the blended materials allow estimation of the risks of exceeding WACs and PCLs for each campaign. A critical subset of WACs/PCLs – NOx, NaK, AlFeZr, and S – are especially at risk of being exceeded in multiple campaigns. These analytes should be the focus of instrument development. We also have extracted the expected solid/supernate distribution for these analytes, which establishes important performance criteria for individual analytical methods. The BBI data also permits an understanding of the different chemical forms in which the analytes appear. Thus, the need to establish instrumental sensitivity to these forms can be gainfully addressed. Although concentrating on one specific application – the blending of tank waste - this approach should be generalizable for the analysis of other possible RTM applications for waste processing.

Lascola, Robert [Savannah River National Laborator↗

Fluor Solvent Evaluation and Testing New Scope: Techno-economic Assessment of EEMPA Solvent for CO 2 Separations from Natural Gas Combined Cycle Power Plant

In this project, a techno-economic analysis (TEA) and sensitivity studies were conducted to assess the PNNL’s leading water-lean CO 2 capture solvent, EEMPA, for capture CO 2 from a natural gas combined cycle (NGCC) power plant at different levels of capture rate. Process models for the NGCC power plant, integrated with EEMPA carbon capture processes, were developed in Aspen Plus V14 using the most up-to-date property package for EEMPA-H 2 O-CO 2 system. The TEA evaluated EEMPA carbon capture process at normal capture rates (90%, 95% and 97%) against Case B32B (Cansolv) described in NETL Rev4a baseline report, and at higher capture rates aimed at achieving zero or negative emissions from the power plant (400 ppmv, 200 ppmv, and 100 ppmv CO 2 in exhaust gas), compared to typical Direct Air Capture (DAC) technologies. A manuscript was drafted for peer-reviewed publication. The results suggested that the carbon capture cost reaches a minimum of $\$$53.7/tonne CO 2 at 90% capture rate. Compared to Cansolv, one of the industrial benchmarks, EEMPA demonstrates 2-4% cost savings at capture rates up to 95%, but minimal savings at higher capture rate. The water lean-solvent system proves economically attractive for achieving moderate negative emissions (about 200 ppmv CO 2 in exhaust gas, and equivalent to 50% CO 2 removal from air) for NGCC flue gas, with marginal capture costs comparable to direct air capture (DAC) technologies. A sensitivity analysis results reveal that its economic advantage, unaffected by EEMPA price due to low solvent loss and degradation rate. However, the marginal carbon capture cost exceeds $\$$1,000/tonne CO 2 when transitioning from moderate to extreme negative emissions (100 ppmv CO 2 in exhaust gas), suggesting that water-lean solvents may not be economically competitive with other DAC technologies for removing more than 75% CO 2 from air. In addition, initial connection was established with Technology Center Mongstad (TCM) for a potential pilot testing proposal. However, detailed modeling and proposal preparation was not conducted due to the delay of non-disclosure agreement.

20 FOSSIL-FUELED POWER PLANTS↗

Ignition delay times of NH 3 /DME blends at high pressure and low DME fraction: RCM experiments and simulations

Here, autoignition delay times of ammonia/dimethyl ether (NH 3 /DME) mixtures were measured in a rapid compression machine with DME fractions of 0, 2 and 5 and 100% in the fuel. The measurements were performed at equivalence ratios $\varphi$= 0.5, 1.0 and 2.0 and pressures in the range 10–70 bar; depending on the fuel composition, the temperatures after compression varied from 610 K to 1180 K. Admixture of DME is seen to have a dramatic effect on the ignition delay time, effectively shifting the curves of ignition delay vs. temperature to lower temperatures, up to ~250 K compared to pure ammonia. Two-stage ignition is observed at $\varphi$= 1.0 and 2.0 with 2% and 5% DME in the fuel, despite the pressure being higher than that at which pure DME shows two-stage ignition. At $\varphi$= 0.5, a reproducible pre-ignition pressure rise is observed for both DME fractions, which is not observed in the pure fuel components. A novel NH 3 /DME mechanism was developed, including modifications in the NH 3 subset and addition of the NH 2 + CH 3 OCH 3 reaction, with rate coefficients calculated from ab initio theory. Simulations faithfully reproduce the observed pre- ignition pressure rise. While the mechanism also exhibits two-stage ignition for NH 3 /DME mixtures, both qualitative and quantitative improvement is recommended. The overall ignition delay times for ammonia/DME mixtures are predicted well, generally being within 50% of the experimental values, although reduced performance is observed for pure ammonia at $\varphi$= 2.0. Simulating the ignition process, we observe that the DME is oxidized much more rapidly than ammonia. Analysis of the mechanism indicates that this ‘early DME oxidation’ generates reactive species that initiate the oxidation of ammonia, which in turn begins heat release that raises the temperature and accelerates the oxidation process towards ignition. The reaction path analysis shows that the low-temperature chain-branching reactions of DME are important in the early oxidation of the fuel, while the sensitivity analysis indicates that several reactions in the oxidation of DME, including cross reactions between DME and NH 3 species presented here, are critical to ignition, even at fractions of 2% DME in the fuel.

10 SYNTHETIC FUELS↗

Automated descriptor selection, volcano curve generation, and active site determination using the DescMAP software

The material space for catalyst discovery is expansive. Volcano curves are traditionally employed to provide physical insights into optimal catalyst characteristics for new material selection. Their generation lies on a single descriptor picked using expert knowledge. Here we present DescMAP, a Python-based software, to automate the selection of descriptors, the generation of volcano maps, and the identification of active sites for structure-sensitive reactions. Here, we consider traditional energy-based and geometric descriptors for structure-sensitive reactions. DescMAP is integrated with the Virtual Kinetic Laboratory (VLab) to provide multiple functionalities. It inputs spreadsheets or template files for flexibility and outputs interactive graphs for post-processing. We demonstrate its features using the non-oxidative dehydrogenation of ethane to ethylene over (111) closed-packed surfaces and the methane total oxidation over various Pt facets. It can be easily applied to other complex chemistries and achieves quick screening of potential catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Isotope dependence of muon-to-electron conversion

The lepton-flavor-violating conversion of a muon into an electron in the field of a nucleus is one of the most sensitive probes of physics beyond the Standard Model and the experiments Mu2e, COMET, and DeeMe will explore uncharted terrain in the near future. An observation of this μ - → e - conversion process opens up the possibility to distinguish the underlying operator or new-physics model by exploiting the target-nucleus dependence of the conversion rate. To facilitate the choice of optimal targets we provide μ - → e - conversion rates for all stable isotopes and estimate nuclear-structure uncertainties. Our results enable studies of mixed or enriched target materials that are particularly promising for distinguishing scenarios in which the muon converts either on protons or neutrons.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

How Bulk Sensitive is Hard X-ray Photoelectron Spectroscopy: Accounting for the Cathode–Electrolyte Interface when Addressing Oxygen Redox

Sensitivity to the `bulk' oxygen core orbital makes hard X-ray photoelectron spectroscopy (HAXPES) an appealing technique for studying oxygen redox candidates. Various studies have reported an additional O 1s peak (530-531 eV) at high voltages, which has been considered a direct signature of the bulk oxygen redox process. Here, we find the emergence of a 530.4 eV O 1s HAXPES peak for three model cathodes, Li 2 MnO 3 , Li-rich NMC, and NMC 442, that shows no clear link to oxygen redox. Instead, the 530.4 eV peak for these three systems is attributed to transition metal reduction and electrolyte decomposition in the near-surface region. Claims of oxygen redox relying on photoelectron spectroscopy must explicitly account for the surface sensitivity of this technique and the extent of the cathode degradation layer.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Advancing Diagnostic Model Evaluation to Better Understand Water Shortage Mechanisms in Institutionally Complex River Basins

Abstract Water resources systems models enable valuable inferences on consequential system stressors by representing both the geophysical processes determining the movement of water and the human elements distributing it to its various competing uses. This study contributes a diagnostic evaluation framework that pairs exploratory modeling with global sensitivity analysis to enhance our ability to make inferences on water scarcity vulnerabilities in institutionally complex river basins. Diagnostic evaluation of models representing institutionally complex river basins with many stakeholders poses significant challenges. First, it needs to exploit a large and diverse suite of simulations to capture important human‐natural system interactions as well as institutionally aware behavioral mechanisms. Second, it needs to have performance metrics that are consequential and draw on decision‐relevant model outputs that adequately capture the multisector concerns that emerge from diverse basin stakeholders. We demonstrate the proposed model diagnostic framework by evaluating how potential interactions between changing hydrologic conditions and human demands influence the frequencies and durations of water shortages of varying magnitudes experienced by hundreds of users in a subbasin of the Colorado River. We show that the dominant factors shaping these effects vary both across users and, for an individual user, across percentiles of shortage magnitude. These differences hold even for users sharing diversion locations, demand levels or water right seniority. Our findings underline the importance of detailed institutional representation for such basins, as institutions strongly shape how dominant factors of stakeholder vulnerabilities propagate through the complex network of users.

Hadjimichael, Antonia↗

Assessing Clouds Using Satellite Observations Through Three Generations of Global Atmosphere Models

Abstract Clouds are parameterized in climate models using quantities on the model grid‐scale to approximate the cloud cover and impact on radiation. Because of the complexity of processes involved with clouds, these parameterizations are one of the key challenges in climate modeling. Differences in parameterizations of clouds are among the main contributors to the spread in climate sensitivity across models. In this work, the clouds in three generations of an atmosphere model lineage are evaluated against satellite observations. Satellite simulators are used within the model to provide an appropriate comparison with individual satellite products. In some respects, especially the top‐of‐atmosphere cloud radiative effect, the models show generational improvements. The most recent generation, represented by two distinct branches of development, exhibits some regional regressions in the cloud representation; in particular the southern ocean shows a positive bias in cloud cover. The two branches of model development show how choices during model development, both structural and parametric, lead to different cloud climatologies. Several evaluation strategies are used to quantify the spatial errors in terms of the large‐scale circulation and the cloud structure. The Earth mover's distance is proposed as a useful error metric for the passive satellite data products that provide cloud‐top pressure‐optical depth histograms. The cloud errors identified here may contribute to the high climate sensitivity in the Community Earth System Model, version 2 and in the Energy Exascale Earth System Model, version 1.

54 ENVIRONMENTAL SCIENCES↗

LHC physics dataset for unsupervised New Physics detection at 40 MHz

In the particle detectors at the Large Hadron Collider, hundreds of millions of proton-proton collisions are produced every second. If one could store the whole data stream produced in these collisions, tens of terabytes of data would be written to disk every second. The general-purpose experiments ATLAS and CMS reduce this overwhelming data volume to a sustainable level, by deciding in real-time whether each collision event should be kept for further analysis or be discarded. We introduce a dataset of proton collision events that emulates a typical data stream collected by such a real-time processing system, pre-filtered by requiring the presence of at least one electron or muon. This dataset could be used to develop novel event selection strategies and assess their sensitivity to new phenomena. In particular, we intend to stimulate a community-based effort towards the design of novel algorithms for performing unsupervised new physics detection, customized to fit the bandwidth, latency and computational resource constraints of the real-time event selection system of a typical particle detector.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Manipulating meso-scale solvent structure from Pd nanoparticle deposits in deep eutectic solvents

Deep Eutectic Solvents (DESs) are complex solutions that present unique challenges compared to traditional electrolytes. Unlike most electrolytes and ionic liquids, DESs have delicate hydrogen bond networks that are responsible for their highly sensitive compositional dependence on the melting point. Prior work has demonstrated unique nanoscale structure both experimentally and theoretically that brings both challenges and opportunities to their adoption in traditional electrochemical processes. In this study, we use in-situ sample-rotated ultra-small angle X-ray scattering to resolve the near-interface solvent structure after electrodepositing Pd nanoparticles onto a glassy carbon electrode in choline chloride:urea and choline chloride:ethylene glycol DESs. Our results indicate that solvent structure can be observed on the meso-scale in the choline chloride:urea and choline chloride:ethylene glycol systems. Importantly, this extended solvent structure peaks at -0.5 V (vs. Ag/AgCl) and decreases slightly with higher overpotentials during Pd electrodeposition. Experimentally, the nature of this structure is more pronounced in the ethylene glycol system, as evidenced by both the X-ray scattering as well as the electrochemical impedance spectroscopy (EIS). Here, molecular dynamics simulations and dipolar orientation analysis reveal that chloride delocalization near the Pd interface and long-range interactions between the choline and each hydrogen bond donor are very different and qualitatively consistent with the experimental data. These results show how the long-range solvent-deposit interactions can be tuned by changing the hydrogen bond donor in the DES and the applied potential.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Evaluating the impact of peat soils and snow schemes on simulated active layer thickness at pan-Arctic permafrost sites

Abstract Permafrost stability is significantly influenced by the thermal buffering effects of snow and active-layer peat soils. In the warm season, peat soils act as a barrier to downward heat transfer mainly due to their low thermal conductivity. In the cold season, the snowpack serves as a thermal insulator, retarding the release of heat from the soil to the atmosphere. Currently, many global land models overestimate permafrost soil temperature and active layer thickness (ALT), partially due to inaccurate representations of soil organic matter (SOM) density profiles and snow thermal insulation. In this study, we evaluated the impacts of SOM and snow schemes on ALT simulations at pan-Arctic permafrost sites using the Energy Exascale Earth System Model (E3SM) land model (ELM). We conducted simulations at the Circumpolar Active Layer Monitoring (CALM) sites across the pan-Arctic domain. We improved ELM-simulated site-level ALT using a knowledge-based hierarchical optimization procedure and examined the effects of precipitation-phase partitioning methods (PPMs), snow compaction schemes, and snow thermal conductivity schemes on simulated snow depth, soil temperature, ALT, and CO 2 fluxes. Results showed that the optimized ELM significantly improved agreement with observed ALT (e.g. RMSE decreased from 0.83 m to 0.15 m). Our sensitivity analysis revealed that snow-related schemes significantly impact simulated snow thermal insulation levels, soil temperature, and ALT. For example, one of the commonly used snow thermal conductivity schemes (quadratic Sturm or SturmQua) generally produced warmer soil temperatures and larger ALT compared to the other two tested schemes. The SturmQua scheme also amplified the model’s sensitivity to PPMs and predicted deeper ALTs than the other two snow schemes under both current and future climates. The study highlights the importance of accurately representing snow-related processes and peat soils in land models to enhance permafrost dynamics simulations.

54 ENVIRONMENTAL SCIENCES↗

Forecasting constraints on the high-z IGM thermal state from the Lyman-α forest flux autocorrelation function

ABSTRACT The autocorrelation function of the Lyman-$\alpha$ (Ly $\alpha$) forest flux from high-z quasars probes the small-scale structure of the intergalactic medium (IGM). The thermal state of the IGM, determined by the physics of reionization, sets the small-scale power observed in the Ly $\alpha$ forest. To explore the sensitivity of the autocorrelation function to the IGM’s thermal state, we compute the autocorrelation function from a cosmological hydrodynamical simulation with an instantaneous reionization model and 135 post-processed thermal states. Using mock data sets of 20 quasars, we forecast constraints on $T_0$ and $\gamma$, which characterize the post-processed IGM thermal state, at $5.4 \le z \le 6$. While this model simplifies the IGM’s thermal state, it serves as a key first step in assessing future observational prospects. We also perform an inference test on mocks and re-weight out posterior distributions to guarantee that they exhibit statistically correct behaviour. At $z = 5.4$, we find that an idealized data set constrains $T_0$ to 59 per cent and $\gamma$ to 16 per cent at the 1$\sigma$ equivalent confidence level. To explore more realistic, non-instantaneous reionization scenarios, we analyse four models combining temperature and ultraviolet background (UVB) fluctuations at $z = 5.8$. We find that mock data generated from a model with both temperature and UVB fluctuations can rule out a model with only temperature fluctuations at the $> 1\sigma$ level 73.9 per cent of the time.

Wolfson, Molly↗

Sensitivity to longitudinal vector boson scattering and doubly charged Higgs boson production in $W^± W^± jj$ at future hadron colliders

We study the sensitivity to longitudinal vector boson scattering at a 27-, 50-, and 100-TeV pp collider using events containing two leptonically decaying same-electric-charge 𝑊 bosons produced in association with two jets. The baseline FCC-hh detector parametrization within the D ELPHES framework is used under the assumption of fully efficient pileup mitigation. A tightly constrained phase space with a dijet mass greater than 2 TeV is considered in order to suppress the impact of potential instrumental backgrounds. Based on this setup, the expected sensitivity to the production of longitudinally polarized same-sign 𝑊 boson pairs is evaluated. Additionally, expected limits are set on doubly charged Higgs bosons produced via vector boson fusion processes and decaying to same-sign 𝑊 boson pairs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗