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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

PROTOTYPING NON-EQUILIBRIUM VISCOUS-TIMESCALE ACCRETION THEORY USING LMC X-3

Explaining variability observed in the accretion flows of black hole X-ray binary systems remains challenging, especially concerning timescales less than, or comparable to, the viscous timescale but much larger than the inner orbital period despite decades of research identifying numerous relevant physical mechanisms. We take a simplified but broad approach to study several mechanisms likely relevant to patterns of variability observed in the persistently high-soft Roche-lobe overflow system LMC X-3. Based on simple estimates and upper bounds, we find that physics beyond varying disk/corona bifurcation at the disk edge, Compton-heated winds, modulation of total supply rate via irradiation of the companion, and the likely extent of the partial hydrogen ionization instability is needed to explain the degree, and especially the pattern, of variability in LMC X-3 largely due to viscous dampening. We then show how evaporation-condensation may resolve or compound the problem given the uncertainties associated with this complex mechanism and our current implementation. We briefly mention our plans to resolve the question, refine and extend our model, and alternatives we have not yet explored.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

The quiescent counterpart of the peculiar X-ray burster SAX J2224.9+5421

SAX J2224.9+5421 is an extraordinary neutron star low-mass X-ray binary. It was discovered when it was exhibiting a ≅ 10 s long thermonuclear X-ray burst, but it had faded to a 0.5-10 keV luminosity of L {sub X} ≲ 8 × 10{sup 32}(D/7.1 kpc){sup 2} erg s{sup –1} only ≅ 8 hr later. It is generally assumed that neutron stars are quiescent (i.e., not accreting) at such intensity, raising questions about the trigger conditions of the X-ray burst and the origin of the faint persistent emission. We report on a ≅51 ks XMM-Newton observation aimed at finding clues explaining the unusual behavior of SAX J2224.9+5421. We identify a likely counterpart that is detected at L {sub X} ≅ 5 × 10{sup 31}(D/7.1 kpc){sup 2} erg s{sup –1} (0.5-10 keV) and has a soft X-ray spectrum that can be described by a neutron star atmosphere model with a temperature of kT {sup ∞} ≅ 50 eV. This would suggest that SAX J2224.9+5421 is a transient source that was in quiescence during our XMM-Newton observation and experienced a very faint (ceasing) accretion outburst at the time of the X-ray burst detection. We consider one other potential counterpart that is detected at L {sub X} ≅ 5 × 10{sup 32}(D/7.1 kpc){sup 2} erg s{sup –1} and displays an X-ray spectrum that is best described by a power law with a photon index of Γ ≅ 1.7. Similarly hard X-ray spectra are seen for a few quiescent neutron stars and may be indicative of a relatively strong magnetic field or the occurrence of low-level accretion.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Rapid changes in coastal ocean microbiomes uncoupled with shifts in environmental variables

Disturbances, here defined as events that directly alter microbial community composition, are commonly studied in host–associated and engineered systems. Notably, in spite of global change both altering environmental averages and increasing extreme events, there has been relatively little research into the causes, persistence and population–level impacts of disturbance in the dynamic coastal ocean. Here, we utilize 3 years of observations from a coastal time series to identify disturbances based on the largest week–over–week changes in the microbiome (i.e. identifying disturbance as events that alter the community composition). In general, these microbiome disturbances were not clearly linked to specific environmental factors and responsive taxa largely differed, aside from SAR11, which generally declined. However, several disturbance metagenomes identified increased phage–associated genes, suggesting that unexplained community shifts might be caused by increased mortality. Furthermore, a category 1 hurricane, the only event that would likely be classified a priori as an environmental disturbance, was not an outlier in microbiome composition, but did enhance a bloom in seasonally abundant phytoplankton. Thus, as extreme environmental changes intensify, assumptions of what constitutes a disturbance should be re–examined in the context of ecological history and microbiome responses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Application of Hybrid Geo-Spatially Granular Fragility Curves to Improve Power Outage Predictions

Fragility curves depict the relationship between a weather variable (wind speed, gust speed, ice accumulation, precipitation rate) and the observed outages for a targeted infrastructure network. This paper describes an empirical study of the county by county distribution of power outages and one minute weather variables during Hurricane Irene with the objective of comparing 1) as built fragility curves (statistical approach) to engineering as designed (bottom up) fragility curves for skill in forecasting outages during future hurricanes; 2) county specific fragility curves to find examples of significant deviation from average behavior; and 3) the engineering practices of outlier counties to suggest future engineering studies of robustness. Outages in more than 90% of the impacted counties could be anticipated through an average or generic fragility curve. The remaining counties could be identified and handled as exceptions through geographic data sets. The counties with increased or decreased robustness were characterized by terrain more or less susceptible to persistent flooding in areas where above ground poles located their foundations. Land use characteristics of the area served by the power distribution system can suggest trends in the as built power grid vulnerabilities to extreme weather events that would be subjects for site specific studies.

classification of impacted areas↗
DOE OSTI2021

Evaluation of overtime phenotypic variation of yeasts in chronic vulvovaginal candidosis cases

Abstract Chronic vulvovaginal candidosis results either from reinfection or from the ability of Candida spp. to persist in the vulva and/or vagina. Persistence is usually associated with increased antifungal (mainly azoles) resistance rates, which can explain treatment failure, and/or increased expression of virulence factors by Candida spp. The aim of this study was to assess the mechanisms leading to Candida spp persistence, by studying sequential isolates from women with chronic vulvovaginal candidosis, focusing on strains genotypes, azole resistance, and ability to form biofilms along the period of clinical evaluation. The strains were identified at species level by automated analysis of biochemical profiles and molecular typing evaluated by polymorphic DNA analysis. The capacity to form biofilm was assessed with a microtiter plate assay. Fluconazole susceptibility was determined by the microdilution broth assay at both pH 7 (following the recommended guideline) and pH 4.5 (as representative of vaginal pH). We studied samples from 17 clinically recurrent cases. In 53% of the chronic cases there were two or more isolates that had a phylogenetic relationship while the remaining (47%) were caused by different species. In those cases where related strains were involved in recurrence, we verified an increase in MIC at pH 7 and also an increased capacity to form biofilms over time. Significant correlation between these two parameters was observed only in cases caused by C. glabrata, evidencing the importance of these two factors to enhance persistence in the vaginal mucosa for this particular species.

Faria-Gonçalves, Paula↗
DOE OSTI2025

Phosphate amendment drives bloom of RNA viruses after soil wet-up

Soil rewetting after a dry period results in a surge of activity and succession in both microbial and DNA virus communities. Less is known about the response of RNA viruses to soil rewetting—while they are highly diverse and widely distributed in soil, they remain understudied. We hypothesized that RNA viruses would show temporal succession following rewetting and that phosphate amendment would influence their trajectory, as viral proliferation may cause phosphorus limitation. Using 39 time-resolved metatranscriptomes and amplicon data, 2190 RNA viral populations were identified across five phyla, with 26 % of these predicted to infect bacteria, and 11 % fungi. Only 1.2 % of viral populations had annotated capsid genes, suggesting most persist via intracellular replication without a free virion phase. Phosphate amendment altered RNA viral community composition within the first week and amended vs. unamended communities remained distinguishable for up to three weeks. While the overall host community remained stable, certain bacterial populations showed reduced abundance in phosphate-amended soils, likely due to increased viral lysis, as RNA bacteriophages proliferated significantly. Notably, 60 % of the viruses with increased abundance under phosphate amendment belonged to basal Lenarviricota clades rather than well-known groups like Leviviricetes. We estimate RNA bacteriophage infections may affect 10 7 –10 9 bacteria per gram of soil, aligning with the total bacterial population (10 7 –10 10 g -1 soil), suggesting that RNA phages significantly influence bacterial communities post-wet-up, with phosphorus availability modulating this effect.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Quarkonium Spectroscopy in the Quark-Gluon Plasma

The properties of bound states are fundamental to hadronic spectroscopy and play a central role in the transition from hadronic matter to a quark-gluon plasma (QGP). In a strongly coupled QGP (sQGP), the interplay of temperature, binding energy, and large collisional widths of the partons poses formidable challenges in evaluating the in-medium properties of hadronic states and their eventual melting. In particular, the existence of heavy quarkonia in the QGP is a long-standing problem that is hard to solve by considering their spectral properties on the real-energy axis. Here, we address this problem by analyzing in-medium thermodynamic quarkonium 𝑇 matrices in the complex energy plane. We first validate this method in vacuum, where the 𝑇-matrix poles of observed states are readily identified. When deploying this approach to recent self-consistently calculated 𝑇 matrices in the QGP, we find that poles in the complex energy plane can persist to surprisingly large temperatures, depending on the strength of the in-medium interactions. While the masses and widths of the pole positions are precisely defined, the notion of a binding energy is not due to the absence of thresholds caused by the (large) widths of the underlying quark or anti-quark spectral functions. Our method thus provides a new and definitive quantum-mechanical criterion to determine the melting temperature of hadronic states in the sQGP while increasing the accuracy in the theoretical determination of transport parameters.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

A highly ordered, nonprotective MALAT1 ENE structure is adopted prior to triplex formation

The 3' end of the ~7 kb lncRNA MALAT1 contains an evolutionarily and structurally conserved element for nuclear expression (ENE) which confers protection from cellular degradation pathways. Formation of an ENE triple helix is required to support transcript accumulation, leading to persistent oncogenic activity of MALAT1 in multiple cancer types. Though the specific mechanism of triplex-mediated protection remains unknown, the MALAT1 ENE triplex has been identified as a promising target for therapeutic intervention. Interestingly, a maturation step of the nascent lncRNA 3' end is required prior to triplex formation. We hypothesize that disruption of the maturation or folding process may be a viable mechanism of inhibition. To assess putative cotranscriptional ENE conformations prior to triplex formation, we perform microsecond MD simulations of a partially folded ENE conformation and the ENE triplex. Herein, we identify a highly ordered ENE structure prior to triplex formation. Extensive formation of U•U base pairs within the large U-rich internal loops produces a global rod-like architecture. We present a three-dimensional structure of the isolated ENE motif, the global features of which are consistent with small angle X-ray scattering (SAXS) experiments. Our structural model represents a nonprotective conformation of the MALAT1 ENE, providing a molecular description useful for future mechanistic and inhibition studies. We anticipate that targeting stretches of U•U pairs within the ENE motif will prove advantageous for the design of therapeutics targeting this oncogenic lncRNA.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

A Passive Network Cyber Threat Intelligence Framework for Legacy Critical Control Systems using Machine Learning

The importance of Internet and communication networks in our daily life and in any organization’s daily operations is well known and cannot be overstressed. A nation’s economy is fully reliant on its critical infrastructure. Energy sector is one of the 16 Critical Infrastructure Sectors identified by the Department of Homeland Security. Securing these critical infrastructure sectors is challenging but is also of utmost priority in this day of constant and persistent cyber threats. Threat is any circumstance or event that has the potential to adversely impact an agency's assets and operations. Cyber Threat Intelligence (CTI) is the process of collection, analysis, and identification of potential cyber threats to the organization. This goal of current research performed at the Savannah River National Laboratory (SRNL), Aiken, SC, is to develop a Cyber Threat Intelligence framework for gathering Threat Intelligence passively from the network traffic from and to a real or simulated Critical Control Systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

In Situ Monitoring of H 2 -Induced Nonstoichiometry in Cu 2 O

Nonstoichiometry plays a pivotal role in the functioning of oxide materials, but it is challenging to measure the non-stoichiometric formation and the resulting charge redistribution around the point defects. Using ambient-pressure X-ray photoelectron spectroscopy and Auger electron spectroscopy to monitor the reduction of Cu 2 O in H 2 , we identify the formation of an intermediate, oxygen-deficient Cu 2 O phase and its progressive inward growth into the deeper region of the oxide. Complemented by DFT modeling, we show that the oxygen-deficient Cu 2 O formation occurs via molecular H 2 adsorption at the Cu 2 O surface, which results in the loss of lattice O from the formation of H 2 O molecules that desorb spontaneously from the oxide surface. The resulting oxy-gen-deficient Cu 2 O is a stable intermediate that persists before the Cu 2 O is fully reduced to metallic Cu. The O vacancy induced charge redistribution of the coordinating Cu atoms results in a satellite feature in Cu LMM, which can be used a fingerprint to identify the nonstoichiometry and local charge transfer in non-stoichiometric oxides.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2011

The Min Oscillator Uses MinD-Dependent Conformational Changes in MinE to Spatially Regulate Cytokinesis.

In E. coli, MinD recruits MinE to the membrane, leading to a coupled oscillation required for spatial regulation of the cytokinetic Z ring. How these proteins interact, however, is not clear because the MinD-binding regions of MinE are sequestered within a six-stranded {beta} sheet and masked by N-terminal helices. minE mutations that restore interaction between some MinD and MinE mutants were isolated. These mutations alter the MinE structure leading to release of the MinD-binding regions and the N-terminal helices that bind the membrane. Crystallization of MinD-MinE complexes revealed a four-stranded {beta} sheet MinE dimer with the released {beta} strands (MinD-binding regions) converted to {alpha} helices bound to MinD dimers. These results identify the MinD-dependent conformational changes in MinE that convert it from a latent to an active form and lead to a model of how MinE persists at the MinD-membrane surface.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Interaction of NaOH solutions with silica surfaces

Sodium adsorption on silica surfaces depends on the solution counter-ion. Here, we use NaOH solutions to investigate basic environments. Sodium adsorption on hydroxylated silica surfaces from NaOH solutions were investigated through molecular dynamics with a dissociative force field, allowing for the development of secondary molecular species. Furthermore, across the NaOH concentrations (0.01 M – 1.0 M), ~50% of the Na + ions were concentrated in the surface region, developing silica surface charges between –0.01 C/m 2 (0.01 M NaOH) and –0.76 C/m 2 (1.0 M NaOH) due to surface site deprotonation. Five inner-sphere adsorption complexes were identified, including monodentate, bidentate, and tridentate configurations and two additional structures, with Na + ions coordinated by bridging oxygen and hydroxyl groups or water molecules. Coordination of Na + ions by bridging oxygen atoms indicates partial or complete incorporation of Na + ions into the silica surface. Residence time analysis identified that Na + ions coordinated by bridging oxygen atoms stayed adsorbed onto the surface four times longer than the mono/bi/tridentate species, indicating formation of relatively stable and persistent Na + ion adsorption structures. Such inner-sphere complexes form only at NaOH concentrations of > 0.5 M. Na + adsorption and lifetimes have implications for the stability of silica surfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Minimal cyclic behavior in sheared amorphous solids

Although jammed packings of soft spheres exist in potential energy landscapes with a vast number of minima, when subjected to cyclic shear they may revisit the same configurations repeatedly. Simple hysteretic spin models, in which particle rearrangements are represented by interacting spin flips called hysterons, capture many features of this periodic behavior. Yet it has been unclear to what extent individual rearrangements can be described by such binary objects and how such objects interact with one another. Using a particularly sensitive algorithm, we identify rearrangements in simulated jammed packings and select pairs of rearrangements that undo one another to create periodic cyclic behavior. We find that the rearrangement pairs surprisingly persist down to the smallest increments in strain, even in the smallest systems we can study. We explore the statistics of these rearrangement pairs and find that there is a relation between the amount of hysteresis and the energy drop and mean-square displacement of the particles; these results are inconsistent with the scaling found in models that treat rearrangements as localized buckling events. Finally, our analysis shows that there is no clean distinction between the particle motions that represent the identity of a single, individual rearrangement and the particle motions that lead to interactions between separated rearrangements or hysterons. These results offer insight into how complex systems such as amorphous solids can reach a limit cycle.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

The Heavy Rainfall Mechanism Revealed by a Terrain-Resolving 4DVar Data Assimilation System—A Case Study

In this study, a newly developed terrain-resolving four-dimensional variational (4DVar)-based data assimilation system, Immersed Boundary Method_Variational Doppler Radar Analysis System (IBM_VDRAS), is applied to investigate the mechanisms leading to a heavy precipitation event that occurred in Taiwan during the Southwesterly Monsoon Experiment (SoWMEX) conducted in 2008. The multivariate analyses using IBM_VDRAS and surface observations reveal that the warm and moist southwesterly flow from the ocean decelerates after making landfall, forming a surface convergence zone along the coast, which is further strengthened during the passage of a prefrontal rainband. The flow ascends as it advances inland until reaching the mountains, producing persistent precipitation and the enhancement of evaporative cooling as well as a widespread high pressure zone. A very shallow (<0.4 km) layer of offshore flow can be identified over the southwestern plain, which helps to generate a quasi-stationary convergence zone near the coast. Furthermore, sensitivity studies are carried out to quantify the relative importance of the contributions made by topographic blockage, evaporative cooling, and their nonlinear interaction, to the evolution of this type of convective system. The influence of the topography is identified as the dominant factor in modulating the flow structure of the rainfall system. However, it is the nonlinear interaction between terrain and evaporation that determines the distribution of the temperature and pressure fields.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

KOI-1003: a new spotted, eclipsing RS CVn binary in the Kepler field

Using the high-precision photometry from the Kepler space telescope, thousands of stars with stellar and planetary companions have been observed. The characterization of stars with companions is not always straightforward and can be contaminated by systematic and stellar influences on the light curves. Here, through a detailed analysis of starspots and eclipses, we identify KOI-1003 as a new, active RS CVn star—the first identified with data from Kepler. The Kepler light curve of this close binary system exhibits the system’s primary transit, secondary eclipse, and starspot evolution of two persistent active longitudes. The near equality of the system’s orbital and rotation periods indicates the orbit and primary star’s rotation are nearly synchronized (P{sub orb}=8.360613±0.000003 days; P{sub rot}∼8.23 days). By assuming the secondary star is on the main sequence, we suggest the system consists of a 1.45{sub −0.19}{sup +0.11} M{sub ⊙} subgiant primary and a 0.59{sub −0.04}{sup +0.03} M{sub ⊙} main-sequence companion. Our work gives a distance of 4400 ± 600 pc and an age of t=3.0{sub +2.0}{sup −0.5} Gyr, parameters which are discrepant with previous studies that included the star as a member of the open cluster NGC 6791.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Xanthos-Lake Dataset

The Xanthos-Lake v1.0 dataset provides the input data, trained machine-learning models, and simulation outputs needed to characterize lake water balance, snow and ice conditions, and mixing-layer temperature within the Xanthos global hydrological modeling framework. The dataset supports lake representation across a wide range of lake sizes and hydroclimatic conditions by combining xLSIM, a basin-specific machine-learning emulator of lake snow, ice, ice-cover fraction, and mixing-layer temperature, with the Xanthos-Lake water-balance model. The archive contains NetCDF datasets used to train and evaluate xLSIM, trained model weights, processed meteorological and lake-property inputs, and basin- and lake-category-specific simulation outputs. These materials are organized into four primary data groups, described below. Snowice_model_inputs: Contains the NetCDF input data used to train xLSIM. The xLSIM machine-learning framework uses three lake-based datasets. The meteorological forcing dataset provides monthly relative humidity, specific humidity, surface wind speed, maximum and minimum air temperature, downward longwave and shortwave radiation, snowfall, surface air pressure, and total precipitation. Lake surface area is included as an additional static predictor. The target-state dataset provides lake ice thickness, snow depth, snow cover, and lake mixing-layer temperature, while a companion lake-surface dataset provides the lake ice-cover fraction. Before training, ice thickness and snow depth are converted from meters to centimeters, mixing-layer temperature is converted from kelvin to degrees Celsius and constrained to nonnegative values, and ice-cover fraction is converted from a fraction to a percentage. The predictor variables are normalized using statistics calculated across the selected lakes and time steps. Snowice_model_outputs: Contains the NetCDF outputs generated by xLSIM. For each basin, xLSIM produces a file containing observed and predicted lake-state variables for the training, validation, and testing periods. The modeled variables include lake ice thickness, snow depth, snow cover, mixing-layer temperature, and lake ice-cover fraction. For basins without a sufficiently persistent snow-and-ice signal, the emulator predicts only mixing-layer temperature. The outputs also include training and validation loss histories, the selected model configuration, identifiers of the lakes used in training, and SHAP-based feature-importance information at the global, lake, and seasonal-regime levels. The trained machine-learning model weights are provided separately within the dataset archive. Together, these files support model evaluation and subsequent coupling with the Xanthos-Lake water-balance framework. XanthosLAKES: Contains the NetCDF input data used by the Xanthos-Lake framework. Monthly meteorological inputs include relative and specific humidity, downward shortwave and longwave radiation, mean, maximum, and minimum air temperature, wind speed, precipitation, snowfall, and surface air pressure. Static lake-property datasets provide lake identifiers, geographic locations, surface area, volume, mean depth, elevation, drainage area, fetch, outlet-routing information, and associated Xanthos grid-cell attributes. Separate bathymetric datasets provide the coefficients of the area–depth and volume–depth relationships for each aggregated lake unit. GLEV-based records provide observed lake surface area and evaporation data used to initialize lake states, define reference conditions, and calibrate and evaluate the model. Xanthos-Lake Outputs: Contains the basin- and lake-category-specific NetCDF outputs generated by Xanthos-Lake. Monthly variables include lake surface area, storage volume, outlet discharge, evaporation rate, evaporation volume, lake–groundwater exchange, lake inflow, ice thickness, snow depth, snow-cover fraction, ice-cover fraction, and mixing-layer temperature. The files also contain lake-specific calibration and validation statistics, including normalized root-mean-square error, mean absolute error, Nash–Sutcliffe efficiency, Kling–Gupta efficiency, and percent bias. Stored calibrated and derived parameters include the weir discharge coefficient, fractional freeboard, groundwater exchange coefficient, reference water level, corresponding reference surface area and storage volume, weir-width adjustment factor, and the fraction of routed inflow entering the lake. Basin identifiers, lake category, simulation period, calibration and validation periods, and parameter-schema information are retained as NetCDF metadata.

Abeshu, Guta [Pacific Northwest National Laborator↗
DOE OSTI2024

A Novel Membrane-Associated Protein Aids Bacterial Colonization of Maize

The soil environment affected by plant roots and their exudates, termed the rhizosphere, significantly impacts crop health and is an attractive target for engineering desirable agricultural traits. Engineering microbes in the rhizosphere is one approach to improving crop yields that directly minimizes the number of genetic modifications made to plants. Soil microbes have the potential to assist with nutrient acquisition, heat tolerance, and drought response if they can persist in the rhizosphere in the correct numbers. Unfortunately, the mechanisms by which microbes adhere and persist on plant roots are poorly understood, limiting their application. This study examined the membrane proteome shift upon adherence to roots in two bacteria of interest, Klebsiella variicola and Pseudomonas putida. From this surface proteome data, we identified a novel membrane protein from a non-laboratory isolate of P. putida that increases binding to maize roots using unlabeled proteomics. When this protein was moved from the environmental isolate to a common lab strain (P. putida KT2440), we observed increased binding capabilities of P. putida KT2440 to both abiotic mimic surfaces and maize roots. We observed a similar increased binding capability to maize roots when the protein was heterologously expressed in K. variicola and Stutzerimonas stutzeri. With the discovery of this novel binding protein, we outline a strategy for harnessing natural selection and wild isolates to build more persistent strains of bacteria for field applications and plant growth promotion.

rhizosphere, colonization, membrane proteome, plan↗
DOE OSTI2020

A Causal Inference Model Based on Random Forests to Identify the Effect of Soil Moisture on Precipitation

Soil moisture influences precipitation mainly through its impact on land–atmosphere interactions. Understanding and correctly modeling soil moisture–precipitation (SM–P) coupling is crucial for improving weather forecasting and subseasonal to seasonal climate predictions, especially when predicting the persistence and magnitude of drought. However, the sign and spatial structure of SM–P feedback are still being debated in the climate research community, mainly due to the difficulty in establishing causal relationships and the high degree of nonlinearity in land–atmosphere processes. To this end, we developed a causal inference model based on the Granger causality analysis and a nonlinear machine learning model. This model includes three steps: nonlinear anomaly decomposition, nonlinear Granger causality analysis, and evaluation of the quality of SM–P feedback, which eliminates the nonlinear response of interannual and seasonal variability and the memory effects of climatic factors and isolates the causal relationship of local SM–P feedback. We applied this model by using National Climate Assessment–Land Data Assimilation System (NCA-LDAS) datasets over the United States. Here, the results highlight the importance of nonlinear atmosphere responses in land–atmosphere interactions. In addition, the strong feedback over the southwestern United States and the Great Plains both highlight the impacts of topographic factors rather than only the sensitivity of evapotranspiration to soil moisture. Furthermore, the SM–P index defined by our framework is used to benchmark Earth system models (ESMs), which provides a new metric for efficiently identifying potential model biases in modeling local land–atmosphere interactions and may help the development of ESMs in improving simulations of water cycle variability and extremes.

54 ENVIRONMENTAL SCIENCES↗