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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,081 records · Page 60

On the importance of three-dimensional modeling for high-energy-density physics experiments

Laser-driven cylindrical implosion experiments enable direct measurements of hydrodynamic instability growth in convergent geometries, providing a wealth of validation data in the high-energy-density regime. These experiments are designed to be nearly axially invariant, allowing for modeling with complementary two-dimensional slices of the cylinder. Two distinct hydrodynamics codes are employed to model a subset of these experiments, and the results are shown to be in very good agreement with each other and the available experimental data. While this 2D modeling approach adequately captures most of the physics of the implosion and ensuing instability growth, there are crucial aspects from the three-dimensional nature of the experiments that are missed in 2D. The first fully 3D simulations of these experiments are presented, and small but significant differences are found to arise from both the axial and azimuthal non-uniformity in the laser drive. Recent experimental results confirming the drive asymmetry are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Modeling Plant Metabolism: From Network Reconstruction to Mechanistic Models

Mathematical modeling of plant metabolism allows the plant science community to understand the organization of plant metabolism, obtain quantitative insights into metabolic functions, and derive engineering strategies for manipulation of metabolism. Among the various modeling approaches, metabolic pathway analysis can dissect the basic functional modes of subsections of core metabolism, such as photorespiration, and reveal how classical definitions of metabolic pathways have overlapping functionality. In current research using constraint-based modeling in plants, numerous computational tools are currently available to analyze large-scale and genome-scale metabolic networks. For 13 C-metabolic flux analysis, principles of isotopic steady state have been used to study heterotrophic plant tissues, while nonstationary isotope labeling approaches are amenable to the study of photoautotrophic and secondary metabolism. Enzyme kinetic models explore pathways in mechanistic detail, and we discuss different approaches to determine or estimate kinetic parameters. In this review, we describe recent advances and challenges in modeling plant metabolism.

59 BASIC BIOLOGICAL SCIENCES↗

Experimental Testing of Particle Erosion and Attrition in CSP Systems

In CSP systems using solid particles for heat transfer, erosion from the falling particles can damage the system components upon impact, and from sliding against the component walls. Furthermore, the resulting attrition of particles can change the thermal performance due to alterations in particle morphology. The research on these issues has been limited to industrial applications, and don’t necessarily coincide with the operating conditions in CSP systems. In this work, we investigated the durability of the particles selected as the heat transfer media, as well as special substrate materials that are of interest as lining materials to the particle storage tanks and hoppers. Three different erosion phenomena were studied: impact, abrasion, and attrition erosion. The low-temperature experiments revealed negligible losses from attrition and abrasion erosion. Although the substrates indicated visible surface damage from impact erosion, the actual material mass loss was small even after a throughput of 500kg of particles 63 days of 1MW CSP plant operation assuming 14 hours per day of operation. Erosion is typically classified as impact, abrasion, or attrition erosion. For example, the CSP systems utilizing solid particles as heat transfer media will likely experience impact erosion on the receiver hopper and heat exchanger walls as the solid particles fall from the reservoir. Additionally, there will be sliding erosion along the receiver walls as particles move through the hopper, and lastly, there will also be attrition erosion as the particles rub against each other. The extent of erosion depends on many factors including but not limited to particle shape and size, material hardness/brittleness and ductility, and particle impact speed and angle. Mechanistic erosion equations that are available in the literature are mostly derived from data pertaining to specific experiments and therefore can’t be applied to all applications without suitable adjustments. Survey of the literature relating to particle-based receivers revealed that the most prevalent approach has been to choose low velocities to limit erosion, but to our knowledge, little effort has been put in to fully characterize erosion at the expected operating conditions. A relatively recent work investigated the erosion of wire mesh proposed for use in a particle receiver, where the results actually showed an increase in mass as oxidation occurred on the mesh surface but the work did not investigate the particle attrition rate, and the erosion rate of a solid substrate. The end goal of this work is to develop a comprehensive particle and substrate durability model that will allow a comprehensive understanding of particle-based CSP operating conditions on component durability.

14 SOLAR ENERGY↗

NSUF University Research Reactor Fitness Workshop

University research reactors have been a cornerstone of nuclear engineering research and education since the first reactor was deployed at North Carolina State University in the 1950s. The population of university reactors grew to a high of almost 80 in 1970 but has dropped to 25 operating today, also shrinking the community, availability of vendors and the talent pipeline. The nation’s fleet of TRTRs serves as a vital resource for educating the next generation of nuclear engineers and as a flexible testbed for innovative reactor technologies. Typically, the reactors have a very small staff with responsibilities ranging through research and operations, isotope production, regulatory compliance, facility maintenance, and university teaching obligations. Knowledge transfer and staffing were identified as critical areas in a recent study of US university research reactor fitness. This panel discusses the unique challenges and potential solutions to these issues.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Lessons Learned and Scalability Achieved When Porting Uintah to DOE Exascale Systems

A key challenge faced when preparing codes for Department of Energy (DOE) exascale systems was designing scalable applications for systems featuring hardware and software not yet available at leadership-class scale. With such systems now available, it is important to evaluate scalability of the resulting software solutions on these target systems. One such code designed with the exascale DOE Aurora and DOE Frontier systems in mind is the Uintah Computational Framework, an open-source asynchronous many-task (AMT) runtime system. To prepare for exascale, Uintah adopted a portable MPI+X hybrid parallelism approach using the Kokkos performance portability library (i.e., MPI+Kokkos). This paper complements recent work with additional details and an evaluation of the resulting approach on Aurora and Frontier. Results are shown for a challenging benchmark demonstrating interoperability of 3 portable codes essential to Uintah-related combustion research. These results demonstrate single-source portability across Aurora and Frontier with scaling characteristics shown to 3,072 Aurora nodes and 9,216 Frontier nodes. In addition to showing results run to new scales on new systems, this paper also discusses lessons learned through efforts preparing Uintah for exascale systems.

Holmen, John [ORNL] (ORCID:0000000259342641)↗

Insights into Methodologies and Operational Details of Resource Adequacy Assessment: A Case Study with Application to a Broader Flexibility Framework

Assessing and maintaining resource adequacy (RA) is a core pillar of power systems. However, recent changes in the physical makeup of these systems and the conditions under which these systems must operate have yielded a renewed interest in the methods, metrics, and assumptions that underpin RA assessments. In this paper, we systematically explore a wide range of RA modeling dimensions, including: the objective function and level of operational detail in the underlying model formulation; the quantity (look-ahead) and quality (accuracy) of data that is available for making operational decisions within those models; and the physical configuration of solar photovoltaics (PV) with battery storage hybrid resources. We apply a set of probabilistic RA tools and production cost modeling tools to a realistic test system based loosely on a future Electric Reliability Council of Texas power system dominated by solar PV resources. Under the assumptions of our system and models, we find that multi-stage probabilistic assessments may provide a more robust evaluation of RA by capturing a wider range of operational and system interactions, but this comes at a computational cost of 1-2 orders of magnitude longer run time depending on the specific configuration. In addition, the information on thermal generator availability impacts RA performance by an order of magnitude more than solar resource forecasts, which is driven by the comparatively larger magnitude of thermal outages than solar forecast errors within our test system. Lastly, the flexibility provided by hybrid and other resources can help reduce system load-shedding event frequencies and enable the system to be more robust to inaccurate forecast information, and alternative hybrid inverter sizes can impact RA levels by 1-2 orders of magnitude. Our results point to the importance of a broader flexibility framework to describe the interaction between (1) flexibility "supply" from both physical resource capabilities and operational constraints considered in the modeling, and (2) flexibility "demand" from forecast errors, thermal generator outages, and other sources of uncertainty, as well as their RA impacts. Results are likely sensitive to the system buildout explored; future work could consider additional system configurations and conditions.

ENERGY PLANNING, POLICY, AND ECONOMY,POWER TRANSMI↗

Antimony redox processes in the environment: A critical review of associated oxidants and reductants

The environmental behavior of antimony (Sb) has recently received greater attention due to the increasing global use of Sb in a range of industrial applications. Although present at trace levels in most natural systems, elevated Sb concentrations in aquatic and terrestrial environments may result from anthropogenic activities. The mobility and toxicity of Sb largely depend on its speciation, which is dependent to a large extent on its oxidation state. To a certain extent, our understanding of the environmental behavior of Sb has been informed by studies of the environmental behavior of arsenic (As), as Sb and As have somewhat similar chemical properties. However, recently it has become evident that the speciation of Sb and As, especially in the context of redox reactions, may be fundamentally different. Therefore, it is crucial to study the biogeochemical processes impacting Sb redox transformations to understand the behavior of Sb in natural and engineered environments. Currently, there is a growing body of literature involving the speciation, mobility, toxicity, and remediation of Sb, and several reviews on these general topics are available; however, a comprehensive review focused on Sb environmental redox chemistry is lacking. Herein, we provide a review of research conducted within the past two decades examining the redox chemistry of Sb in aquatic and terrestrial environments and identifies knowledge gaps that need to be addressed to develop a better understanding of Sb biogeochemistry for improved management of Sb in natural and engineered systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Literature Review of Documented Persistent Secondary Uranium Sources at DOE LM Sites

The U.S. Department of Energy Office of Legacy Management (LM) has the responsibility to protect human health and the environment at 101 legacy uranium sites across the nation by implementing long-term surveillance and maintenance requirements. Included in these responsibilities is to provide for the safe and environmentally sound disposal, long-term stabilization, and control of uranium mill tailings in a manner that minimizes or eliminates radiation health hazards to the public at 21 Uranium Mill Tailings Radiation Control Act (UMTRCA) Title I sites; 6 UMTRCA Title II sites; and 9 Comprehensive Environmental Response, Compensation, and Liability Act/Resource Conservation and Recovery Act sites. These sites are former uranium mills (processing sites), or sites with wastes from processing sites encapsulated in engineered disposal cells (disposal sites), or sites where components of atomic weapons were manufactured. During site characterization, groundwater contamination was often discovered and evaluated or modeled for future movement with the inclusion of uranium sorption in the groundwater plume. Much of this original work did identify uranium processing wastes as the original contaminant source. However, more recent work has identified the existence and influence of persistent secondary uranium sources that may prevent uranium in groundwater from attenuating as quickly as initial evaluations or modeling indicated. By understanding these processes, better decisions can be made to choose the appropriate remediation and closure strategies, identify long-term surveillance and maintenance activities, and more accurately estimate life-cycle costs. The purpose of this report is to summarize the literature available on documented persistence secondary uranium sources at LM sites as part of the Applied Studies and Technology Persistent Secondary Contaminant Sources Project.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

VTO_2021_APR_LLNL_Ye

Traditional batteries are composed of two-dimensional films that are stacked and/or rolled. Thin film batteries display high power density while their thick film counterparts show good energy density, but it has proven difficult to concurrently achieve both within these planar form factors. In addition, conventional Li-ion batteries based on liquid organic electrolytes or gel polymer electrolytes have raised severe safety concerns due to the intrinsic flammable properties of the organic electrolytes. They are also not ideal for the use of high energy density metallic lithium (Li) anodes due to Li dendrite growth, or sulfur cathodes due to shuttling effects that result in fast capacity fade. There is an urgent need to develop safe, high-performance solid-state batteries (SSBs) with advanced electrolyte and separator technologies. Although in recent years a series of superionic conductors have been developed for electrolytes and separators, their performance does not satisfy demanding criteria due to large impedance from poor solid electrolyte-electrode contact and questionable electrochemical and mechanical stability. Unlike the well-established roll-to-roll fabrication of conventional Li-ion batteries, the processing of SSBs is unique due to the brittleness of solid-state electrolytes (SSEs). The commercially available or lab-developed SSE discs are usually very thick (hundreds of micrometers to millimeters) to overcome their brittle nature, which unfortunately increases the cell impedance and accounts for the majority of the overall cell weight and volume, leading to dramatically decreased power and energy densities. In this project, we will investigate 3D printing techniques to overcome safety, fabrication, mechanical, and electrochemical issues in SSBs. 3D printing builds complex structures in a layer-by-layer fashion, which allows rapid production of hierarchical architectures, gradient and multi-material structures, and multi-component assemblies. 3D printing is an emerging area that could fundamentally transform energy storage devices. For example, 3D printing can produce batteries with arbitrary form factors to fit a product’s specific volume requirements and can create interwoven electrode arrangements over a wide range of length scales to improve transport and increase power density for a given energy density. For SSBs, 3D printing may dramatically reduce the separator thickness from ~1 mm (by hydraulic pressing) to tens of micrometers or less. In addition, the interfacial contact area between the electrolyte and the electrode may be increased via 3D interdigitated designs. Hence, we expect a significant reduction of the overall cell impedance and enhancement of both energy and power densities of SSBs by harnessing an array of 3D printing technologies being developed at Lawrence Livermore National Laboratory (LLNL).

25 ENERGY STORAGE↗

Materials Science of the Interstitial Doping Process

Particle accelerators are an increasingly important tool for frontier science. Growing initial and operating costs are a significant barrier for upgrades and for new machines. While everything matters, the major cost contributor is the SRF cavities and their ancillary facilities (e.g., cryoplant). Accordingly, the accelerator science community devotes much R&D effort to improving their energy efficiency (increased Q o ) and gradient (E acc ). While improved gradient is at the forefront for certain machines (ILC), improved quality factor has broader impact, benefitting all SRF applications. An important opportunity for accelerator science and technology to move forward arose in the course of building the LCLS-II, the second generation Linac Coherent Light Source at SLAC. At more or less the same time, researchers at Fermilab discovered that introducing a small amount of nitrogen to the niobium surface could improve the mid-range quality factor as much as three-fold. A firm resolution of how nitrogen confers its benefit attracts much current research interest. The key elements of the “nitrogen doping” process were vacuum bake at 800 °C, brief exposure to mTorr of nitrogen at several hundred degrees followed by electropolish (EP) to remove several microns from the surface to eliminate unwanted nitrides: While the process as a whole was novel, the comprising unit operations are familiar to the accelerator community. It was judged reasonable to adopt it as a cost-reduction technology for LCLS-II. Researchers carried out a program of varying process parameters and measuring performance in single-cell cavities, leading to a consensus stable protocol for the project. The transition to vendor fabrication and multiple niobium sources has presented unforeseen challenges of performance variation evidently not connected to anything that could be incorporated in a purchase specification. Moving beyond the high temperature N-doping process above, researchers reported a simplified process consisting entirely of tens of hours anneal in a N atmosphere at low temperatures (~120°C – 160°C) after 800 °C UHV bake. These processes typically yield a few-nm doped layer while the high temperature process yields at least a few to many micron doped layer. Even more recently, oxygen has been used to dope instead of nitrogen which leaves a few-µm O-alloyed layer upon vacuum annealing for 300 °C for ~3 hours. The investigation of these materials is just beginning, but the process simplification they may offer is surely attractive. The very low quantity of material that appears to be significant in the “infusion” process indicates the need for very careful control of gas species available for diffusion into the surface during low temperature treatment, both for process control and research to characterize the underlying dynamics. Oxygen alloying offers the further opportunity to utilize the decomposition of the surface native oxide as the dopant source. It is necessary to understand and (thus) manage this process. We have been supported by the Department of Energy Offices of High Energy Physics and Nuclear Physics to pursue this goal.

36 MATERIALS SCIENCE↗

Evaluation of Multi-Fidelity Soil Moisture Products Across the Continental United States

We have aggregated the most recent soil moisture datasets from a diverse range of sources, encompassing the Continental United States (CONUS). These sources encompass gridded data from remote sensing products, reanalysis products, machine learning-based projects, and land surface modeling products. Additionally, we have obtained and processed in-situ soil moisture observations from the International Soil Moisture Network. The collected datasets exhibit variations in both temporal and spatial resolutions. Among the 20 datasets, six are available at a spatial resolution of 0.25 degrees, while three are at a coarser spatial resolution of 25 km. To minimize spatial interpolation, we conducted data uncertainty evaluations at the 0.25-degree spatial resolution. For our data evaluations, we maintained a monthly temporal resolution, which effectively captures soil moisture seasonality and interannual variability. Our data processing strategy preserves the raw data and interpolated data at their original temporal resolutions. Datasets with higher temporal resolutions, including daily, three-hourly, and hourly datasets, are set aside for subsequent analyses. These analyses will delve into topics such as soil moisture changes and recovery during extreme weather events. Furthermore, we have processed auxiliary data to enhance our evaluation, leveraging tools such as Google Earth Engine. This includes incorporating topography data, land use land cover data, Köppen-Geiger climate classification, and more to provide a comprehensive assessment from multiple sources.

Li, Lingcheng↗

Combustion studies of n-butyl acetate synthesized by a new biological process and comparisons with neat n-butyl acetate

Blending petroleum fuels with biofuels is a common approach for stemming the depletion of crude oil while also mitigating the impact of their combustion on the environment. It has recently been considered that n-butyl acetate (BA, C6H12O2, boiling point of 399K) could be a viable biofuel additive to diesel fuel. This paper reports the combustion dynamics of BA droplets in the absence of external convection. Two grades of BA were examined: one synthesized by a new process that uses a solventogenic Clostridium strain through an extractive fermentation process using n-hexadecane as the extractant (SBA); the other commercially available as a high-purity (99.9%) 'neat' BA grade produced by Fischer esterification (NBA). The mass concentration of by-products from the synthesis process amounted to approximately 6% of the total composition and included n-butanol, n-hexadecane, iso-propyl alcohol and ethyl acetate. The platform used to study the combustion of commercial and synthesized BA was an isolated droplet burning with spherical symmetry. Initial droplet diameters were fixed at 0.6 mm. Experiments were carried out in a drop tower to promote one-dimensional transport dynamics, in the standard atmosphere, and with ignition accomplished by spark discharge. Differences in droplet burning rates and flame structures were undetectable between NBA and SBA, despite the differences in burning among the SBA components individually. The results presented show that the new synthesis process for butyl acetate yields a sustainable alternative to conventional methodologies with burning characteristics that are identical to NBA in stagnant gas transport fields.

Wang, Yujie↗

Recent Developments in Femtosecond Laser-Enabled TriBeam Systems

Streams of multimodal three-dimensional (3D) and four-dimensional (4D) data are revolutionizing our ability to design and predict the behavior of a broad array of advanced materials systems. Over the last 10 years, a new 3D imaging platform consisting of a femtosecond (fs) pulsed laser coupled with a focused ion beam scanning electron microscope (FIB SEM) has been developed by UC Santa Barbara in collaboration with Thermo Fisher Scientific (formerly FEI). The femtosecond-laser-enabled FIB SEM, called the TriBeam, has become one of the only 3D serial sectioning methods available that can gather millimeter-scaled multimodal datasets at sub-μm voxel resolutions; these length scales are critical for many materials problems. Multimodal chemical, crystallographic, and morphological information can be gathered rapidly on a layer-by-layer basis and reconstructed in 3D. Large (gigabyte to terabyte scale) 3D datasets have been generated for a broad array of materials systems, including metallic alloys, ceramics, biomaterials, polymer- and ceramic-matrix composites, and semiconductors. The research tasks conducted have resulted in a completely new design, operating with a dual-wavelength femtosecond-pulsed laser on a plasma focused ion beam (PFIB) platform.

36 MATERIALS SCIENCE↗

A human cell type similar to murine central nervous system perivascular fibroblasts

Highlights: • Human diploid cell lines were established from tumor and non-tumor brain tissue. • Human cells share a common transcriptomic profile with murine perivascular fibroblasts. • Human cells resemble commercially available cell of presumed pericyte origin. The brain vasculature has several specific features, one of them being the blood-brain barrier (BBB), which supports and protects the brain by allowing for the passage of oxygen and nutrients, while at the same time preventing passage of pathogens and toxins. The BBB also prevents efficient delivery of drugs to the brain, e.g. for treatment of brain tumors. In the murine brain, perivascular fibroblasts were recently identified as a novel potential constituent of the BBB. Here we present the existence of human cells that could be the equivalent to the murine brain perivascular fibroblasts. Using RNA sequencing, we show a similar transcriptomic profile of cultured human brain cells and murine perivascular fibroblasts. These data open up a window for new hypotheses on cell types involved in human CNS diseases.

60 APPLIED LIFE SCIENCES↗

Preserving isohydricity: vertical environmental variability explains Amazon forest water-use strategies

Abstract Increases in hydrological extremes, including drought, are expected for Amazon forests. A fundamental challenge for predicting forest responses lies in identifying ecological strategies which underlie such responses. Characterization of species-specific hydraulic strategies for regulating water-use, thought to be arrayed along an ‘isohydric–anisohydric’ spectrum, is a widely used approach. However, recent studies have questioned the usefulness of this classification scheme, because its metrics are strongly influenced by environments, and hence can lead to divergent classifications even within the same species. Here, we propose an alternative approach positing that individual hydraulic regulation strategies emerge from the interaction of environments with traits. Specifically, we hypothesize that the vertical forest profile represents a key gradient in drought-related environments (atmospheric vapor pressure deficit, soil water availability) that drives divergent tree water-use strategies for coordinated regulation of stomatal conductance (gs) and leaf water potentials (ΨL) with tree rooting depth, a proxy for water availability. Testing this hypothesis in a seasonal eastern Amazon forest in Brazil, we found that hydraulic strategies indeed depend on height-associated environments. Upper canopy trees, experiencing high vapor pressure deficit (VPD), but stable soil water access through deep rooting, exhibited isohydric strategies, defined by little seasonal change in the diurnal pattern of gs and steady seasonal minimum ΨL. In contrast, understory trees, exposed to less variable VPD but highly variable soil water availability, exhibited anisohydric strategies, with fluctuations in diurnal gs that increased in the dry season along with increasing variation in ΨL. Our finding that canopy height structures the coordination between drought-related environmental stressors and hydraulic traits provides a basis for preserving the applicability of the isohydric-to-anisohydric spectrum, which we show here may consistently emerge from environmental context. Our work highlights the importance of understanding how environmental heterogeneity structures forest responses to climate change, providing a mechanistic basis for improving models of tropical ecosystems.

Forestry↗

Explaining machine-learning models for gamma-ray detection and identification

As more complex predictive models are used for gamma-ray spectral analysis, methods are needed to probe and understand their predictions and behavior. Recent work has begun to bring the latest techniques from the field of Explainable Artificial Intelligence (XAI) into the applications of gamma-ray spectroscopy, including the introduction of gradient-based methods like saliency mapping and Gradient-weighted Class Activation Mapping (Grad-CAM), and black box methods like Local Interpretable Model-agnostic Explanations (LIME) and SHapley Additive exPlanations (SHAP). In addition, new sources of synthetic radiological data are becoming available, and these new data sets present opportunities to train models using more data than ever before. In this work, we use a neural network model trained on synthetic NaI(Tl) urban search data to compare some of these explanation methods and identify modifications that need to be applied to adapt the methods to gamma-ray spectral data. We find that the black box methods LIME and SHAP are especially accurate in their results, and recommend SHAP since it requires little hyperparameter tuning. We also propose and demonstrate a technique for generating counterfactual explanations using orthogonal projections of LIME and SHAP explanations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Estimating Large Global Significances with a New Monte Carlo Extrapolation Method

In particle physics, it is needed to evaluate the possibility that excesses of events in mass spectra are due to statistical fluctuations as quantified by the standards of local and global significances. Without prior knowledge of a particle’s mass, it is especially critical to estimate its global significance. The usual approach is to count the number of times a significance limit is exceeded in a collection of simulated Monte Carlo (MC) “toy experiments”. To demonstrate this conventional method for global significance, we performed simulation studies according to a recent Compact Muon Solenoid (CMS) result to show its effectiveness. However, this counting method is not practical for computing large global significances. To address this problem, we developed a new “extrapolation” method to evaluate the global significance. We compared the global significance estimated by our new method with that of the conventional approach, and verified its feasibility and effectiveness. This method is also applicable for cases where only small toy MC samples are available. In this approach, the significance is calculated based on p-values, assuming symmetrical Gaussian distributions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Water isotopes, climate variability, and the hydrological cycle: recent advances and new frontiers

Abstract The hydrologic cycle is a fundamental component of the climate system with critical societal and ecological relevance. Yet gaps persist in our understanding of water fluxes and their response to increased greenhouse gas forcing. The stable isotope ratios of oxygen and hydrogen in water provide a unique opportunity to evaluate hydrological processes and investigate their role in the variability of the climate system and its sensitivity to change. Water isotopes also form the basis of many paleoclimate proxies in a variety of archives, including ice cores, lake and marine sediments, corals, and speleothems. These records hold most of the available information about past hydrologic variability prior to instrumental observations. Water isotopes thus provide a ‘common currency’ that links paleoclimate archives to modern observations, allowing us to evaluate hydrologic processes and their effects on climate variability on a wide range of time and length scales. Building on previous literature summarizing advancements in water isotopic measurements and modeling and describe water isotopic applications for understanding hydrological processes, this topical review reflects on new insights about climate variability from isotopic studies. We highlight new work and opportunities to enhance our understanding and predictive skill and offer a set of recommendations to advance observational and model-based tools for climate research. Finally, we highlight opportunities to better constrain climate sensitivity and identify anthropogenically-driven hydrologic changes within the inherently noisy background of natural climate variability.

Dee, Sylvia (ORCID:000000022140785X)↗