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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Bioremediation of copper in sediments from a constructed wetland ex situ with the novel bacterium Cupriavidus basilensis SRS

The H-02 constructed wetland was designed to remove metals (primarily copper and zinc) to treat building process water and storm water runoff from multiple sources associated with the Tritium Facility at the DOE-Savannah River Site, Aiken, SC. The concentration of Cu and Zn in the sediments has increased over the lifetime of the wetland and is a concern. A bioremediation option was investigated at the laboratory scale utilizing a newly isolated bacterium of the copper metabolizing genus Cupriavidus isolated from Tim’s Branch Creek, a second-order stream that eventually serves as a tributary to the Savannah River, contaminated with uranium and other metals including copper, nickel, and mercury. Cupriavidus basilensis SRS is a rod-shaped, gram-negative bacterium which has been shown to have predatory tendencies. The isolate displayed resistance to the antibiotics ofloxacin, tetracycline, ciprofloxacin, select fungi, as well as Cu 2+ and Zn 2+ . Subsequent ribosomal sequencing demonstrated a 100% confidence for placement in the genus Cupriavidus and a 99.014% match to the C. basilensis type strain. When H-02 wetland samples were inoculated with Cupriavidus basilensis SRS samples showed significant (p < 0.05) decrease in Cu 2+ concentrations and variability in Zn 2+ concentrations. Over the 72-h incubation there were no significant changes in the inoculate densities (10 6 –10 8 cells/ML) indicating Cupriavidus basilensis SRS resiliency in this environment. This research expands our understanding of the Cupriavidus genus and demonstrates the potential for Cupriavidus basilensis SRS to bioremediate sites impacted with heavy metals, most notably copper.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Tunable internal quantum well alignment in rationally designed oligomer-based perovskite films deposited by resonant infrared matrix-assisted pulsed laser evaporation

Hybrid perovskites incorporating conjugated organic cations enable unusual charge carrier interactions among organic and inorganic structural components, but are difficult to prepare as films due to disparate component chemical/physical characteristics (e.g., solubility, thermal stability). In this work, we demonstrate that resonant infrared matrix-assisted pulsed laser evaporation (RIR-MAPLE) mitigates these challenges, enabling facile deposition of lead-halide-based perovskite films incorporating variable-length oligothiophene cations. Density functional theory (DFT) predicts suitable organic and inorganic moieties that form quantum-well-like structures with targeted luminescence or exciton separation/quenching. RIR-MAPLE-deposited films enable confirmation of these predictions by optical measurements, which further display excited state behavior transcending traditional quantum-well models—i.e., with appropriate selection of specially synthesized organic/inorganic moieties, intercomponent carrier transfer efficiently converts excitons from singlet to triplet states in organics for which intersystem crossing cannot ordinarily compete with recombination. These observations demonstrate the uniquely versatile excited-state behavior in hybrid perovskite quantum wells, and the value of integrating DFT, organic synthesis, RIR-MAPLE and spectroscopy for screening/preparing rationally devised complex structures.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Exponential time differencing scheme for mass transport and depletion in molten salt reactors

This work extends the capability previously shown for addressing the problem of computing depletion and mass transport calculations in molten salt reactors (MSRs) by calculating matrix exponentials. Additional algorithms are implemented to compute the matrix exponential and the action of the matrix exponential on a matrix. These algorithms include two methods based on the Pade approximation, a Taylor series method, and three methods based on Cauchy's integral formula. In addition to the added matrix exponential solvers, a variable-order total variation diminishing scheme is applied to the convective flux approximation to provide enhanced accuracy. Finally, a simplified MSR problem is shown for each of the exponential time differencing solvers along with classical backwards differencing integrators. The results show excellent convergence for exponential time differencing methods. Computation time is a key element for selecting the optimal solver in these problems, and this work shows that Pade and Cauchy-based solvers may provided the fastest and most accurate solutions. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2019

Engineering Accessible Adsorption Sites in MOFs for CO 2 Capture (Final Report)

The overall goal of this project was to synthesize metal-organic frameworks (MOFs) with improved CO 2 adsorption and selectivity properties for potential application in removing this greenhouse gas from flue gas streams during fossil fuel processing. MOFs are an important class of 2-dimensional (2D) and 3D supramolecular coordination polymer networks that are comprised of organic linkers (ligands) and metal ion-units or clusters. They generally possess very high surface area, porosity, variable thermal stability and tunable chemistry, which make them potentially candidates CO 2 adsorption. The three specific objectives of this project were as follows: 1) To synthesize MOFs with metal ions adsorption sites in more accessible locations within the structures (towards the center of the organic linkers) in order to enhance their CO 2 adsorption characteristics; 2) To investigate the CO 2 adsorption properties of new MOFs containing pyrazine- and other nitrogen containing ligands as possible improved alternatives to known amine-functionalized MOFs; and 3) To investigate the nature of the adsorption sites and mechanism(s) by conducting computational studies on CO 2 adsorption within the MOF structures and compare the results with experimental observations. The main outcomes of this research are as follows. Nitrogen-containing ligands that possesses a diaza-12-crown-4-ether moiety at the center of two phenylcarboxylic acid groups was utilized to synthesize 3D MOFs in which the added transition metal ions (i.e.CO 2 + and Mn2+) were coordinated within the crown moieties. Therefore, the structures had the metal ions in more accessible locations. The new 3D structures, being non-porous however, showed negligible adsorption capacity for CO 2 . The ligand 2,3,5,6,-pyrazinetetracarboxylic acid (PZTC) was successfully used to synthesize four new MOFs, each with one of the following metal ion; Ca2+(1D), Zn2+(2D), Mn2+ (3D) and Gd3+(3D), and with the dimensionality (D) indicated. The Ca-, Zn- and Mn- PZTC-based MOFs had no obvious accessible pores and showed no adsorption capacity for CO 2 . Gd-PZTC structure however, showed promising capacities of 1.0 mmol/g and 0.6 mmol/g at 273K and 298 K respectively. Another nitrogen-containing ligand explored was 2,2’-dinitro- trans-4,4’- stilbenedicarboxylic acid (DNSDC) and in combination with a co-ligand, 2,2’-bipyridine (2,2’-BPY). The combination of DNSDC with CO 2 + and Mn2+ yielded four new thermally stable MOFs that showed significant CO 2 absorption capacities. The experimental CO 2 adsorption capacities varied among the structures, ranging between 1.8 mmol/g at 256 K and 0.8 mmol/g at 298K. The DNSDC-based structures maintained significant stability and capacities over many adsorption cycles at 298K. With 2,2’-diamino- trans-4,4’-stillbene dicarboxylic acid (DASDC) as ligand instead of DNSDC, new 3D MOF structures were also synthesized. The structures however were less stable, and decomposed on activation (exposure to vacuum and or solvents) and therefore showed negligible CO 2 adsorption capacities. The dinitro-stilbene based MOFs showed promising CO 2 adsorption capacities, thermal stabilities and recyclability, and therefore showed potential for application in CO 2 removal from flue gas. The research accomplishments presented herein supports the Department of Energy’s (DOE) Office of Fossil Energy and the National Energy Technology Laboratory (NETL) mission in the area of research that advances the science of coal technologies, specifically carbon capture and storage. The research outcomes can guide rational design/synthesis strategies towards producing advanced materials for CO 2 capture. However, further research is needed in order to develop the materials to meet or exceed capacities and stabilities that are reported for their counterparts.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2019

Integrated Electric Drive with HV 2 Modular Electric Machine and SiC Based Power Converters (Final Report)

An innovative high performance, high speed electric drive is designed, fabricated and tested. The drive is based on the modular multilevel converter (MMC) topology and is synthesized using power electronic building blocks (submodules) that utilize the newest generation of silicon-carbide (SiC) semiconductors. Power modules from two suppliers are investigated, characterized and the one showing better performance selected. A prototype MMC submodule is designed, built and tested in the lab. Simultaneously, control hardware and software are implemented and tested using real-time simulators. After verification of each of the subsystems, all subsystems are integrated to form a DC/AC converter-based drive. Multiple configurations are assembled and tested, and operation in variable voltages and frequencies, up to 4,160 V (line-to-line, rms), 140 A (rms) and 0-1,000 Hz is achieved. The efficiency of the drive system accomplished in the project is higher than 99.2% and the volume is 70% smaller than that of state-of-the art drives made using conventional technologies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Engineering Accessible Adsorption Sites in MOFs for CO 2 Capture

The overall goal of this project was to synthesize metal-organic frameworks (MOFs) with improved CO 2 adsorption and selectivity properties for potential application in removing this greenhouse gas from flue gas streams during fossil fuel processing. MOFs are an important class of 2-dimensional (2D) and 3D supramolecular coordination polymer networks that are comprised of organic linkers (ligands) and metal ion-units or clusters. They generally possess very high surface area, porosity, variable thermal stability and tunable chemistry, which make them potential candidates for CO 2 adsorption. The three specific objectives of this project were as follows: 1) To synthesize MOFs with metal ion adsorption sites in more accessible locations within the structures (towards the center of the organic linkers) in order to enhance their CO 2 adsorption characteristics; 2) To investigate the CO 2 adsorption properties of new MOFs containing pyrazine- and other nitrogen containing ligands as possible improved alternatives to known amine-functionalized MOFs; and 3) To investigate the nature of the adsorption sites and mechanism(s) by conducting computational studies on CO 2 adsorption within the MOF structures and compare the results with experimental observations. The main outcomes of this research are as follows: Nitrogen-containing ligands that possess a diaza-12-crown-4-ether moiety at the center of two phenylcarboxylic acid groups were utilized to synthesize 3D MOFs in which the added transition metal ions (i.e. Co 2+ and Mn 2+ ) were coordinated within the crown moieties. Therefore, the structures had the metal ions in more accessible locations. The new 3D structures, being non-porous however, showed negligible adsorption capacity for CO 2 . The ligand 2,3,5,6,-pyrazinetetracarboxylic acid (PZTC) was successfully used to synthesize four new MOFs, each with one of the following metal ions; Ca 2+ (1D), Zn 2+ (2D), Mn 2+ (3D) and Gd 3+ (3D), and with the dimensionality (D) indicated. The Ca-, Zn- and Mn- PZTC-based MOFs had no obvious accessible pores and showed no adsorption capacity for CO 2 . Gd-PZTC structure however, showed promising capacities of 1.0 mmol/g and 0.6 mmol/g at 273K and 298 K respectively. Another nitrogen-containing ligand explored was 2,2’-dinitro- trans-4,4’- stilbenedicarboxylic acid (DNSDC) and in combination with a co-ligand, 2,2’-bipyridine (2,2’-BPY). The combination of DNSDC with Co 2+ and Mn 2+ yielded four new thermally stable MOFs that showed significant CO 2 absorption capacities. The experimental CO 2 adsorption capacities varied among the structures, ranging between 1.8 mmol/g at 256 K and 0.8 mmol/g at 298K. The DNSDC-based structures maintained significant stability and capacities over many adsorption cycles at 298K. With 2,2’-diamino- trans-4,4’-stillbene dicarboxylic acid (DASDC) as ligand instead of DNSDC, new 3D MOF structures were also synthesized. The structures, however, were less stable, and decomposed on activation (exposure to vacuum and or solvents) and therefore showed negligible CO 2 adsorption capacities. The dinitro-stilbene based MOFs showed promising CO 2 adsorption capacities, thermal stabilities and recyclability, and therefore showed potential for application in CO 2 removal from flue gas. The research accomplishments presented herein support the Department of Energy’s (DOE) Office of Fossil Energy and the National Energy Technology Laboratory (NETL) mission in the area of research that advances the science of coal technologies, specifically carbon capture and storage. The research outcomes can guide rational design/synthesis strategies towards producing advanced materials for CO 2 capture. However, further research is needed in order to develop the materials to meet or exceed capacities and stabilities that are reported for their counterparts.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2021

An optimization-based approach to parameter learning for fractional type nonlocal models

Nonlocal operators of fractional type are a popular modeling choice for applications that do not adhere to classical diffusive behavior; however, one major challenge in nonlocal simulations is the selection of model parameters. In this study we propose an optimization-based approach to parameter identification for fractional models with an optional truncation radius. We formulate the inference problem as an optimal control problem where the objective is to minimize the discrepancy between observed data and an approximate solution of the model, and the control variables are the fractional order and the truncation length. For the numerical solution of the minimization problem we propose a gradient-based approach, where we enhance the numerical performance by an approximation of the bilinear form of the state equation and its derivative with respect to the fractional order. Several numerical tests in one and two dimensions illustrate the theoretical results and show the robustness and applicability of our method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Determining Spatial Scales of Soil Moisture—Cloud Coupling Pathways Using Semi-Idealized Simulations

The spatial scales of land-atmosphere interactions over heterogeneous, realistic soil moisture patterns are critical to improve our understanding of land-atmosphere interactions. However, these scales are poorly quantified. We use high-resolution numerical experiments to quantify the spatial scales for a selected day during the Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems (HI-SCALE) campaign in Oklahoma. A semi-idealized approach (removing background winds and surface topography while retaining the real-world data for other boundary conditions) enables examination of the local influence from the surface. Simulations that apply uniform surface, variable land cover with uniform soil moisture, and variable land cover with variable soil moisture are then compared. Land cover variations, especially water and urban surfaces, create two variance peaks in the surface sensible heat flux in the scales >10 km (meso-β) and <6 km (meso-γ). Both peaks are enhanced by the observation-based soil moisture distribution that has most of its variance in the meso-β scale. Atmospheric response in the meso-β scale is hydrostatic with weak vertical motion. The land cover variations induce secondary circulations in the scales of 2.5–6 km. The additional soil moisture variability intensifies extreme circulations over dry soil patches and sharp sensible heat flux gradients, slightly extending the characteristic scales to 2.5–9 km. While their areal coverage is small, soil moisture variations on such “hotspots” lead to substantially larger convective cloud structure and domain-mean rainfall, calling for a consideration of their non-linear effect in large-scale models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Recovering hidden dynamical modes from the generalized Langevin equation

In studying large molecular systems, insights can better be extracted by selecting a limited number of physical quantities for analysis rather than treating every atomic coordinate in detail. Some information may, however, be lost by projecting the total system onto a small number of coordinates. For such problems, the generalized Langevin equation (GLE) is shown to provide a useful framework to examine the interaction between the observed variables and their environment. Starting with the GLE obtained from the time series of the observed quantity, we perform a transformation to introduce a set of variables that describe dynamical modes existing in the environment. The introduced variables are shown to effectively recover the essential information of the total system that appeared to be lost by the projection.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Evaluating the active site-substrate interplay between x-ray crystal structure and molecular dynamics in chorismate mutase

Designing realistic quantum mechanical (QM) models of enzymes is dependent on reliably discerning and modeling residues, solvents, and cofactors important in crafting the active site microenvironment. Interatomic van der Waals contacts have previously demonstrated usefulness toward designing QM-models, but their measured values (and subsequent residue importance rankings) are expected to be influenceable by subtle changes in protein structure. Using chorismate mutase as a case study, this work examines the differences in ligand-residue interatomic contacts between an x-ray crystal structure and structures from a molecular dynamics simulation. Select structures are further analyzed using symmetry adapted perturbation theory to compute ab initio ligand-residue interaction energies. The findings of this study show that ligand-residue interatomic contacts measured for an x-ray crystal structure are not predictive of active site contacts from a sampling of molecular dynamics frames. In addition, the variability in interatomic contacts among structures is not correlated with variability in interaction energies. However, the results spotlight using interaction energies to characterize and rank residue importance in future computational enzymology workflows.

Chemistry↗
DOE OSTI2025

Systematic characterization of unknown compounds via dimensionality reduction of time series

Analysis of ambient aerosols provides valuable insight into particle sources and formation chemistry. However, due to the complexity of atmospheric data and the dynamic nature of aerosol composition, a substantial fraction of data often become discarded by conventional analysis methods. Furthermore, a large fraction of chemical species within those data are unidentifiable due to a lack of matching spectral information, resulting in suboptimal characterization of chemical composition. Previous work has demonstrated techniques for cataloging analytes in a chromatographic dataset by deconvolution of mass spectra, but integration of these analytes throughout a large dataset remains time consuming. Here, we present a method to automatically identify an ion for quantitation for single-ion chromatogram based peak fitting and integration, enabling comprehensive integration of analytes with minimal user interaction. The resulting time series are clustered with a machine-learning based dimensionality reduction technique to systematically investigate the underlying characteristics of the categorized analytes and gain new insights into the chemical composition and physicochemical properties of the unidentifiable analytes. We apply these methods to existing atmospheric datasets collected in Manacapuru, Brazil during the GoAmazon2014/5 campaign to identify new analytes and interpret their variability and transformations in the atmosphere. The analysis results generate 408 time series from cataloged analytes of interest, and the clustering of those time series with spherical k-means results in 8 distinct clusters. We find the analytes form clusters based on their distinct physicochemical properties, demonstrating the method’s ability to systematically identify and selectively filter contaminants and instrumental analytes and characterize the unidentifiable analytes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Emitter-site-selective photoelectron circular dichroism of trifluoromethyloxirane

The angle-resolved inner-shell photoionization of R-trifluoromethyloxirane, C 3 H 3 F 3 O, is studied experimentally and theoretically. Thereby, we investigate the photoelectron circular dichroism (PECD) for nearly symmetric O 1s and F 1s electronic orbitals, which are localized on different molecular sites. The respective dichroic β 1 and angular distribution β 2 parameters are measured at the photoelectron kinetic energies from 1 to 16 eV by using variably polarized synchrotron radiation and velocity map imaging spectroscopy. The present experimental results are in good agreement with the outcome of ab initio electronic structure calculations. We report a sizable chiral asymmetry β 1 of up to about 9% for the K -shell photoionization of oxygen atom. For the individual fluorine atoms, the present calculations predict asymmetries of similar size. However, being averaged over all fluorine atoms, it drops down to about 2%, as also observed in the present experiment. Our study demonstrates a strong emitter and site sensitivity of PECD in the one-photon inner-shell ionization of this chiral molecule.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Explosive Yield Estimation Using Regional Seismic Moment Tensors

Here, we use the Pasyanos and Chiang (2022) data set to calculate the seismic moment M 0 for each explosion and use the measured explosive yield W to validate the W~M 0 relationship in Denny and Johnson (1991; hereafter, DJ91). The M 0 is corrected by transforming to a potency tensor and applying more appropriate near-source geophysical parameter values in the moment estimate. The mean residual between observed and predicted yield is near zero; however, the standard deviation of the residuals results in an F-value (a 95% confidence factor) of about 5. We re-estimate the coefficients in the DJ91 model and find similar values and only a slight improvement in the F-value. Next, we embark on a similar model selection process as DJ91, allowing for non-cube-root yield scaling and other plausible near-source elastic moduli. As was found by DJ91, the yield dependence is not significantly different from unity, and a cube root assumption is valid. Therefore, we yield scale the seismic moment and test the significance of all plausible explanatory variables. Isotropic moment performs better in the response variable than total moment. The preference for isotropic moment could be due to its relationship to volume change, which would be more directly affected by explosive yield. Surprisingly, we find that the overburden pressure, which is a function of depth, is not a significant parameter in the model. We hypothesize that this is due to the competing depth effects on source asymmetry and the incorporation of depth in the Green’s functions used to calculate the seismic moment tensors. Importantly, this emphasizes that only seismic moment tensor-derived moments should be used in these models. After removing insignificant model parameters, we are left with a simple model to predict explosive yield $\widehat{W}$ in kt from isotropic moment M I in N·m, $\widehat{W}$=κ –1.4132 10 0.035626GP M I , in which κ and GP are the near-source bulk modulus and gas porosity in Pa and %, respectively. The F-value for this model is approximately 3.

58 GEOSCIENCES↗
DOE OSTI2020

An optimization-based approach to parameter learning for fractional type nonlocal models

Nonlocal operators of fractional type are a popular modeling choice for applications that do not adhere to classical diffusive behavior; however, one major challenge in nonlocal simulations is the selection of model parameters. In this work we propose an optimization-based approach to parameter identification for fractional models with an optional truncation radius. We formulate the inference problem as an optimal control problem where the objective is to minimize the discrepancy between observed data and an approximate solution of the model, and the control variables are the fractional order and the truncation length. For the numerical solution of the minimization problem we propose a gradient-based approach, where we enhance the numerical performance by an approximation of the bilinear form of the state equation and its derivative with respect to the fractional order. Several numerical tests in one and two dimensions illustrate the theoretical results and show the robustness and applicability of our method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

M DWARF ACTIVITY IN THE PAN-STARRS1 MEDIUM-DEEP SURVEY: FIRST CATALOG AND ROTATION PERIODS

We report on an ongoing project to investigate activity in the M dwarf stellar population observed by the Pan-STARRS1 Medium-Deep Survey (PS1-MDS). Using a custom-built pipeline, we refine an initial sample of ∼4 million sources in PS1-MDS to a sample of 184,148 candidate cool stars using color cuts. Motivated by the well-known relationship between rotation and stellar activity, we use a multiband periodogram analysis and visual vetting to identify 270 sources that are likely rotating M dwarfs. We derive a new set of polynomials relating M dwarf PS1 colors to fundamental stellar parameters and use them to estimate the masses, distances, effective temperatures, and bolometric luminosities of our sample. We present a catalog containing these values, our measured rotation periods, and cross-matches to other surveys. Our final sample spans periods of ≲1–130 days in stars with estimated effective temperatures of ∼2700–4000 K. Twenty-two of our sources have X-ray cross-matches, and they are found to be relatively X-ray bright as would be expected from selection effects. Our data set provides evidence that Kepler -based searches have not been sensitive to very slowly rotating stars ( P {sub rot} ≳ 70 day), implying that the observed emergence of very slow rotators in studies of low-mass stars may be a systematic effect. We also see a lack of low-amplitude (<2%) variability in objects with intermediate (10–40 day) rotation periods, which, considered in conjunction with other observational results, may be a signpost of a loss of magnetic complexity associated with a phase of rapid spin-down in intermediate-age M dwarfs. This work represents just a first step in exploring stellar variability in data from the PS1-MDS and, in the farther future, Large Synoptic Survey Telescope.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Climate Services for Agriculture: Tools for Informing Decisions Relating to Climate Change and Climate Variability in the Wine Industry

Australia’s changing climate is already impacting the agriculture sector and will continue to do so in the future. To help respond to these impacts, the Climate Services for Agriculture (CSA) platform presents readily accessible climate data, including future climate projections, relevant to specific agricultural commodities. This wine industry example aims to demonstrate the functionality and utility of the CSA for national use across a broad range of commodities. Methods and Results. The platform includes commodity-relevant climate indices designed in consultation with experts to ensure that they are as salient to producers as possible; the wine-grape specific indices include measures of growing season temperature, rainfall, extreme heat, and frost. Here, we describe the research behind the wine-grape specific indices and present sample outputs from the CSA platform for a site within a selected winegrowing region. We note the CSA platform has been developed through an extensive and continuing user engagement initiative, ensuring it meets the needs of the agriculture community as they grapple with how to make decisions based on longer term climate projections. Conclusions. Provision of past, seasonal outlook, and future climate information for Australia and for a range of important agricultural commodities can help improve on-farm planning and decision-making to respond to climate risks. The wine industry provides a leading example of how to use these data for decision-making, noting ongoing adjustments will be needed. Significance of the Study. The CSA platform brings together historical climate data, seasonal climate outlooks, and future climate projections to assist agricultural producers to better manage climate variability and climate change. It aims to nationalise this information for all major agricultural commodities in Australia. We use wine production as a demonstration case here.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

The Atmospheric River Tracking Method Intercomparison Project (ARTMIP): Quantifying Uncertainties in Atmospheric River Climatology

Atmospheric rivers (ARs) are now widely known for their association with high-impact weather events and long-term water supply in many regions. Researchers within the scientific community have developed numerous methods to identify and track of ARs—a necessary step for analyses on gridded data sets, and objective attribution of impacts to ARs. These different methods have been developed to answer specific research questions and hence use different criteria (e.g., geometry, threshold values of key variables, and time dependence). Furthermore, these methods are often employed using different reanalysis data sets, time periods, and regions of interest. The goal of the Atmospheric River Tracking Method Intercomparison Project (ARTMIP) is to understand and quantify uncertainties in AR science that arise due to differences in these methods. This paper presents results for key AR-related metrics based on 20+ different AR identification and tracking methods applied to Modern-Era Retrospective Analysis for Research and Applications Version 2 reanalysis data from January 1980 through June 2017. We show that AR frequency, duration, and seasonality exhibit a wide range of results, while the meridional distribution of these metrics along selected coastal (but not interior) transects are quite similar across methods. Furthermore, methods are grouped into criteria-based clusters, within which the range of results is reduced. AR case studies and an evaluation of individual method deviation from an all-method mean highlight advantages/disadvantages of certain approaches. For example, methods with less (more) restrictive criteria identify more (less) ARs and AR-related impacts. Finally, this paper concludes with a discussion and recommendations for those conducting AR-related research to consider.

Rutz, Jonathan J.↗