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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Observed changes in hydroclimate attributed to human forcing

Observational and modeling studies indicate significant changes in the global hydroclimate in the twentieth and early twenty-first centuries due to anthropogenic climate change. In this review, we analyze the recent literature on the observed changes in hydroclimate attributable to anthropogenic forcing, the physical and biological mechanisms underlying those changes, and the advantages and limitations of current detection and attribution methods. Changes in the magnitude and spatial patterns of precipitation minus evaporation (P–E) are consistent with increased water vapor content driven by higher temperatures. While thermodynamics explains most of the observed changes, the contribution of dynamics is not yet well constrained, especially at regional and local scales, due to limitations in observations and climate models. Anthropogenic climate change has also increased the severity and likelihood of contemporaneous droughts in southwestern North America, southwestern South America, the Mediterranean, and the Caribbean. An increased frequency of extreme precipitation events and shifts in phenology has also been attributed to anthropogenic climate change. While considerable uncertainties persist on the role of plant physiology in modulating hydroclimate and vice versa, emerging evidence indicates that increased canopy water demand and longer growing seasons negate the water-saving effects from increased water-use efficiency.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

High-count rate effects in event processing for XRISM/ Resolve X-ray microcalorimeter: I. Ground test

The spectroscopic performance of an X-ray microcalorimeter is compromised at high count rates. We utilize the Resolve X-ray microcalorimeter onboard the XRISM satellite to examine the effects observed during high-count rate measurements and propose modeling approaches to mitigate them. We specifically address the following instrumental effects that impact performance: CPU limit, pile-up, and untriggered electrical cross-talk. Experimental data at high count rates were acquired during ground testing using the flight model instrument and a calibration X-ray source. In the experiment, data processing not limited by the performance of the onboard CPU was run in parallel, which cannot be done in orbit. This makes it possible to access the data degradation caused by limited CPU performance. We use these data to develop models that allow for a more accurate estimation of the aforementioned effects. To illustrate the application of these models in observation planning, we present a simulated observation of GX 13+1. Understanding and addressing these issues is crucial to enhancing the reliability and precision of X-ray spectroscopy in situations characterized by elevated count rates.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Current and Future Global Lake Methane Emissions: A Process‐Based Modeling Analysis

Abstract Freshwater ecosystem contributions to the global methane budget remains the most uncertain among natural sources. With warming and accompanying carbon release from thawed permafrost and thermokarst lake expansion, the increase of methane emissions could be large. However, the impact and relative importance of various factors related to warming remain uncertain. Based on diverse lake characteristics incorporated in modeling and observational data, we calibrate and verify a lake biogeochemistry model. The model is then applied to estimate global lake methane emissions and examine the impacts of temperature increase for the first and the last decades of the 21st century under different climate scenarios. We find that current emissions are 24.0 ± 8.4 Tg CH 4 yr −1 from lakes larger than 0.1 km 2 , accounting for 11% of the global total natural source as estimated based on atmospheric inversion. Future projections under the RCP8.5 scenario suggest a 58%–86% growth in emissions from lakes. Our model sensitivity analysis indicates that additional carbon substrates from thawing permafrost may enhance methane production under warming in the Arctic. Warming enhanced methane oxidation in lake water can be an effective sink to reduce the net release from global lakes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Learning Forecasts of Rare Stratospheric Transitions from Short Simulations

Abstract Rare events arising in nonlinear atmospheric dynamics remain hard to predict and attribute. We address the problem of forecasting rare events in a prototypical example, sudden stratospheric warmings (SSWs). Approximately once every other winter, the boreal stratospheric polar vortex rapidly breaks down, shifting midlatitude surface weather patterns for months. We focus on two key quantities of interest: the probability of an SSW occurring, and the expected lead time if it does occur, as functions of initial condition. These optimal forecasts concretely measure the event’s progress. Direct numerical simulation can estimate them in principle but is prohibitively expensive in practice: each rare event requires a long integration to observe, and the cost of each integration grows with model complexity. We describe an alternative approach using integrations that are short compared to the time scale of the warming event. We compute the probability and lead time efficiently by solving equations involving the transition operator, which encodes all information about the dynamics. We relate these optimal forecasts to a small number of interpretable physical variables, suggesting optimal measurements for forecasting. We illustrate the methodology on a prototype SSW model developed by Holton and Mass and modified by stochastic forcing. While highly idealized, this model captures the essential nonlinear dynamics of SSWs and exhibits the key forecasting challenge: the dramatic separation in time scales between a single event and the return time between successive events. Our methodology is designed to fully exploit high-dimensional data from models and observations, and has the potential to identify detailed predictors of many complex rare events in meteorology.

Finkel, Justin↗
DOE OSTI2026

Data for Zheng et al. (2025), "AquaMEND: Reconciling multiple impacts of salinization on soil carbon biogeochemistry"

Soil salinization, exacerbated by climate change, poses a global threat to coastal ecosystems and soil function. Salinity affects soil carbon cycling by directly impacting microbial activity and indirectly altering soil physicochemical properties, but current models inadequately represent these complexities. This dataset contains the observational and modeling data from Zheng et al. (2025), which described a process-based modeling framework that couples soil solution chemistry with microbial carbon cycling reactions to study the impacts of soil salinization. This conceptual model is implemented numerically into the open-source geochemical program PHREEQC 3.0 (Parkhurst and Appelo, 2013). This dataset consists of: - Figure2_AquaMEND_salinity_buffer: Contains model simulation outputs to assess the impact of three different cation exchange and surface complexation processes on salinity buffering (Fig. 2 from Zheng et al. 2025). - Figure3_Salinity_function: Contains salinity function fitting for literature data (Fig. 3 from Zheng et al. 2025). - Figure4_AquaMEND_microbial_mechanisms: Contains model simulation outputs for testing various microbial process-based hypotheses related to soil salinization, including microbial mortality, carbon use efficiency (CUE), extracellular enzyme activity, and other microbial mechanisms (Fig. 4 from Zheng et al. 2025). - Figure5_AquaMEND_Redox: Contains on model simulation outputs to evaluate shifts among key redox processes, such as aerobic respiration, sulfate reduction, and methanogenesis (Fig.5 from Zheng et al. 2025). - Figure6_AquaMEND_sorption: Contains on model simulation outputs for investigating the effects of salinity on dissolved organic matter (DOM) sorption and desorption processes (Fig. 6 from Zheng et al. 2025). - Figure7_AquaMEND_process_couple: Contains on model simulation outputs for exploring coupled biotic-abiotic processes and their interactions (Fig. 7 from Zheng et al. 2025). - data: Includes datasets used to develop salinity response functions and evaluate salinity buffering capacity. Datasets for MEND model calibration. - database: Contains the `.dat` file required by PHREEQC for model execution. - README.md: A Markdown plain text file describing the computational tools and directories. Files are a mixture of plain text CSV (comma-separated value) and plain text *.dat files written by the model; no special software is required to read them.

EARTH SCIENCE > AGRICULTURE > SOILS > SOIL SALINIT↗
DOE OSTI2024

Comparative Analysis of Cosmological Simulations via Angular Power Spectra

Cosmology is the study of the universe's origin, large-scale structure, and dynamics. One such area of study is understanding dark energy and dark matter. Dark matter has not been observed to interact with luminous matter other than through gravitational attractions, forming large scale structures observed throughout the universe. In this area, the primary model is the Lambda Cold Dark Matter (ΛCDM) model. This standard model consists of cosmological dark energy (Λ), cold dark matter (CDM), and normal luminous matter. We use angular power spectra (APS) to compare simulated ΛCDM models with observed large-scale galaxy distributions from the DECam Local Volume Exploration Survey (DELVE) [1]. After ensuring that the simulations can produce APS that match observational results, we vary cosmological parameters to constrain the allowed ranges of parameter values that are consistent with the observed data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Fundamental physics studies in time domain and multi-messenger astronomy

The era of ime domain and multi-messenger astronomy is not only leading to the development of a much broader set of detectors and instruments for astrophysical observations, but is also providing the means for astronomy to tie directly to cutting-edge studies in physics. In this manner, fundamental physics (theory and experiment) coupled with a strong theoretical understanding of astrophysical phenomena (guided by high-performance computing simulations) can tie directly to the amazing new observations in astronomy. This paper discusses how physics, astrophysical models, and observations can not only help astronomy probe fundamental physics but guide the needs for next-generation astrophysical missions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Comparative analysis of cosmological simulations via angular power spectra

Cosmology is the study of the universe's origin, large-scale structure, and dynamics. One such area of study is understanding dark energy and dark matter. Dark matter has not been observed to interact with luminous matter other than through gravitational attractions, forming large scale structures observed throughout the universe. In this area, the primary model is the Lambda Cold Dark Matter (ΛCDM) model. This standard model consists of cosmological dark energy (Λ), cold dark matter (CDM), and normal luminous matter. We use Angular Power Spectra (APS) to compare simulated ΛCDM models with observed large-scale galaxy distributions from the DECam Local Volume Exploration Survey (DELVE). After ensuring that the simulations can produce APS which match observational results, we vary cosmological parameters to constrain the allowed ranges of parameter values that are consistent with the observed data.

Feithen, William↗
DOE OSTI2023

Constraining Bedrock Groundwater Residence Times in a Mountain System with Environmental Tracer Observations and Bayesian Uncertainty Quantification: Modeling and Data Package

Groundwater residence times provide fundamental descriptions of hydrologic dynamics and mixing processes in mountainous watersheds. Yet, few observational datasets that can constrain groundwater residence times over broad timescales are available in high elevation mountain systems. Here we present field observations from May 2021 of dissolved noble gases (He, Ne, Ar, Kr, and Xe), Chloroflourcarbons (CFCs), Sulfurhexaflouride (SF6), and tritium (3H) sampled from the Pumphouse Lower Montane study site (wells PLM1, PLM6, and PLM7) within the East River Watershed, Colorado. The presented noble gas (PLM_noblegas_2021.csv) and environmental tracer (PLM_tracers_2021.csv) observation datasets, along with the associated modeling scripts, aide in quantifying groundwater residence times and recharge conditions in a high elevation mountain system. Furthermore, the modeling scripts quantify groundwater residence time and noble gas recharge condition uncertainties using a novel Markov-chain Monte Carlo approach. All data modeling scripts are written in the Python code.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Assessing mass balance-based inverse modeling methods via a pseudo-observation test to constrain NO x emissions over South Korea

This study constrains NO x emissions by utilizing mass balance–based inverse modeling methods and examines the optimization of inverse modeling conditions through a pseudo-observation test for South Korea, which has complex topography. Here, we applied mass balance–based inverse modeling methods such as Basic Mass Balance (BMB), Finite Difference Mass Balance (FDMB), and Iterative Finite Difference Mass Balance (IFDMB). We performed a numerical simulation of air quality using the Community Multi-scale Air Quality (CMAQ) model to calculate the NO 2 column density required for the inverse modeling. The pseudo-observation test was performed according to season, modeling resolution, and regridding methodology of satellite observation data to identify various conditions while applying the inverse modeling for South Korea. Comparing the inverse modeling results from the BMB, FDMB, and IFDMB methods, IFDMB was the most effective method in constraining NO x emissions in the South Korean region since it minimized smearing effects (i.e., transport-induced errors) through iterative calculations. The accuracy of the constrained NO x emissions using mass balance–based inversions in South Korea was the highest in the summer due to the minimized smearing effects, and the 9 km resolution modeling was the most efficient for inverse modeling of the region. In addition, the results of inverse modeling varied depending on the regridding methods, implying the importance of using a suitable regridding method and modeling resolution. This study used pseudo-observations, but the inversions are expected to be applied based on actual satellite data in the future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Using Large Ensembles to Identify Regions of Systematic Biases in Moderate-to-Heavy Daily Precipitation

Because of internal variability in both the real-world and global climate models, it is unclear whether disagreement between models and observations reflects true systematic differences, or different phasing of internal variability in the short observational period. Here, we address this issue through an examination of moderate-to-heavy precipitation in large ensembles of global climate models. We find that model inconsistency with a global observational product is lowest for extratropical precipitation in northern hemisphere winter. The inconsistency is systematically greater for the southern hemisphere winter, but the difference between hemispheres could be due to observational quality. Moderate-to-heavy extratropical winter precipitation is less inconsistent than moderate-to-heavy tropical precipitation in most models. Within the tropics, moderate-to-heavy precipitation is particularly inconsistent with the reference in regions including the Caribbean (especially during JJA), the northern and southern flanks of the Pacific and Atlantic ITCZ, and the Indian Ocean.

58 GEOSCIENCES↗
DOE OSTI2022

Parameter estimation from spontaneous imbibition into volcanic tuff

Two-phase fluid flow properties underlie quantitative prediction of water and gas movement, but constraining these properties typically requires multiple time-consuming laboratory methods. The estimation of two-phase flow properties (van Genuchten parameters, porosity, and intrinsic permeability) is illustrated in cores of vitric nonwelded volcanic tuff using Bayesian parameter estimation that fits numerical models to observations from spontaneous imbibition experiments. The uniqueness and correlation of the estimated parameters is explored using different modeling assumptions and subsets of the observed data. The resulting estimation process is sensitive to both moisture retention and relative permeability functions, thereby offering a comprehensive method for constraining both functions. The data collected during this relatively simple laboratory experiment, used in conjunction with a numerical model and a global optimizer, result in a viable approach for augmenting more traditional capillary pressure data obtained from hanging water column, membrane plate extractor, or mercury intrusion methods. This method may be useful when imbibition rather than drainage parameters are sought, when larger samples (e.g., including heterogeneity or fractures) need to be tested that cannot be accommodated in more traditional methods, or when in educational laboratory settings.

58 GEOSCIENCES↗
DOE OSTI2021

Regional-scale, sector-specific evaluation of global CO2 inversion models using aircraft data from the ACT-America project

We use vertical profiles of airborne measurements of CO2 from frontal cases during the summer 2016 Atmospheric Carbon and Transport – America (ACT-America) campaign to evaluate the skill of a set of ten global CO2 inversion models participating in the Orbiting Carbon Observatory – 2 (OCO-2) Model Intercomparison Project (MIP). Model errors and biases (model minus observation) were categorized by region (Mid-Atlantic, Midwest, and South), frontal sector (warm or cold), and transport model (predominantly Tracer Model 5 (TM5) and Goddard Earth Observing System – Chemistry (GEOS-Chem)). Overall, the inversions reproduce the general structures of the observed vertical profiles and the enhanced / depleted low-level CO2 in warm / cold sectors, but tend to underestimate the magnitude of the sector difference in each region. In the Midwest and South warm sectors, inversion biases were about 1 ppm above 1500 m AGL, though model spread (quantified by interquartile range) was often even smaller; below 1500 m AGL, model biases were negative and about -2 ppm near the surface. For the Midwest and South cold sectors, models had +2-3 ppm biases below 1500 m AGL, but with comparable model spread. Uniquely, in the Mid-Atlantic there was a consistent difference between TM5 and GEOS-Chem mole fractions for both sectors up to 3000 m AGL (TM5 lower by 2 ppm), on the order of the observation-relative biases. In the MidAtlantic TM5 inversions had negative biases in warm sectors, while GEOS-Chem inversions had positive biases in cold sectors. Possible reasons for the regional variability are discussed.

Gaudet, Brian J.↗
DOE OSTI2025

Boundary-Layer-Coupled and Decoupled Clouds in Global Storm-Resolving Models: Comparisons With the ARM Observations

The accurate representation of interactions between clouds and planetary boundary layer (PBL) is a persistent challenge in climate models, critical for simulating surface energy budget. The emergence of kilometer-grid-scale global storm resolving models (GSRMs) offers the potential for enhanced details of PBL processes in these complex interactions. This study evaluates the representation of PBL-coupled and decoupled clouds in nine GSRM simulations against extensive ground-based observations by the Department of Energy Atmospheric Radiation Measurement (ARM) program, across six sites encompassing diverse regimes such as marine and continental environments in tropics and midlatitude. By differentiating coupling based on the relative positions between cloud bases and PBL tops, our analysis focuses on the simulation of PBL height, cloud frequency, position and vertical extent. The GSRMs generally exhibit commendable agreements with observed cloud structures and PBL diurnal cycles across different ARM sites. In contrast to the relatively consistent representation of decoupled clouds, discrepancies exist between the simulated and the observed coupled clouds, particularly in areas of intense convection, for example, over tropical rainforests and mountainous regions. These biases are probably associated with the models' tendency to underestimate the boundary layer humidity and the frequency of coupled clouds within different ranges of PBL heights. This study underscores the importance for continuous improvements in the representation of boundary layer and convection within these global kilometer-grid-scale models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Sea Ice Rheology Experiment (SIREx): 2. Evaluating Linear Kinematic Features in High-Resolution Sea Ice Simulations

Simulating sea ice drift and deformation in the Arctic Ocean is still a challenge because of the multiscale interaction of sea ice floes that compose the Arctic Sea ice cover. The Sea Ice Rheology Experiment (SIREx) is a model intercomparison project of the Forum of Arctic Modeling and Observational Synthesis (FAMOS). In SIREx, skill metrics are designed to evaluate different recently suggested approaches for modeling linear kinematic features (LKFs) to provide guidance for modeling small-scale deformation. These LKFs are narrow bands of localized deformation that can be observed in satellite images and also form in high resolution sea ice simulations. In this contribution, spatial and temporal properties of LKFs are assessed in 36 simulations of state-of-the-art sea ice models and compared to deformation features derived from the RADARSAT Geophysical Processor System. All simulations produce LKFs, but only very few models realistically simulate at least some statistics of LKF properties such as densities, lengths, or growth rates. All SIREx models overestimate the angle of fracture between conjugate pairs of LKFs and LKF lifetimes pointing to inaccurate model physics. The temporal and spatial resolution of a simulation and the spatial resolution of atmospheric boundary condition affect simulated LKFs as much as the model's sea ice rheology and numerics. Only in very high resolution simulations (≤2 km) the concentration and thickness anomalies along LKFs are large enough to affect air-ice-ocean interaction processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Mesoscale Convective Systems in a Superparameterized E3SM Simulation at High Resolution

Accurately representing mesoscale convective systems (MCSs) is crucial to simulating the energy and water cycles in global climate models. Using a novel MCS identification and tracking algorithm applied to observations and model simulations, we evaluate how well the Energy Exascale Earth System Model simulates MCSs over the central US. Simulations performed by E3SM at 25 km grid spacing with (SP-E3SM) and without (E3SM) superparameterization are compared and evaluated against observations using multiple metrics highlighting important MCS characteristics. Compared to E3SM, SP-E3SM better simulates MCS number and MCS precipitation amount, diurnal cycle, propagation, and the probability distribution of precipitation rate in both spring and summer. The improvement from SP is partly contributed by improvement in simulating the large-scale environments, featuring enhanced atmospheric low-level moisture and larger moisture transport to the central US relative to E3SM. However, SP-E3SM still underestimates MCS precipitation amount, particularly in summer. This underestimation is closely related to the negative bias in MCS precipitation intensity, although the drier environments simulated during summer also contributes to underestimation of MCS frequency. Without SP, the larger bias in MCS precipitation amount is closely related to the negative bias in MCS frequency, while the substantial dry bias in the large-scale environments also contributes to underestimation of MCS intensity. Our results suggest that SP improves MCS simulation by improving modeling of the large-scale environments and convection initiation, which are both major limiting factors in E3SM even at 25 km grid spacing where deep convection is represented by a cumulus parameterization.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Sea Ice Rheology Experiment (SIREx): 1. Scaling and Statistical Properties of Sea-Ice Deformation Fields

As the sea-ice modeling community is shifting to advanced numerical frameworks, developing new sea-ice rheologies, and increasing model spatial resolution, ubiquitous deformation features in the Arctic sea ice are now being resolved by sea-ice models. Initiated at the Forum for Arctic Modeling and Observational Synthesis, the Sea Ice Rheology Experiment (SIREx) aims at evaluating state-of-the-art sea-ice models using existing and new metrics to understand how the simulated deformation fields are affected by different representations of sea-ice physics (rheology) and by model configuration. Part 1 of the SIREx analysis is concerned with evaluation of the statistical distribution and scaling properties of sea-ice deformation fields from 35 different simulations against those from the RADARSAT Geophysical Processor System (RGPS). For the first time, the viscous-plastic (and the elastic-viscous-plastic variant), elastic-anisotropic-plastic, and Maxwell-elasto-brittle rheologies are compared in a single study. We find that both plastic and brittle sea-ice rheologies have the potential to reproduce the observed RGPS deformation statistics, including multi-fractality. Model configuration (e.g., numerical convergence, atmospheric representation, spatial resolution) and physical parameterizations (e.g., ice strength parameters and ice thickness distribution) both have effects as important as the choice of sea-ice rheology on the deformation statistics. It is therefore not straightforward to attribute model performance to a specific rheological framework using current deformation metrics. In light of these results, we further evaluate the statistical properties of simulated Linear Kinematic Features in a SIREx Part 2 companion paper.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Representations of Precipitation Diurnal Cycle in the Amazon as Simulated by Observationally Constrained Cloud‐System Resolving and Global Climate Models

Abstract The ability of an observationally‐constrained cloud‐system resolving model (Weather Research and Forecasting; WRF, 4‐km grid spacing) and a global climate model (Energy Exascale Earth System Model; E3SM, 1‐degree grid spacing) to represent the precipitation diurnal cycle over the Amazon basin during the 2014 wet season is assessed. The WRF model coupled with a 3‐D variational data assimilation scheme reproduces the spatial variability of the precipitation diurnal cycle over the basin and the lifecycle of westward propagating MCSs initiated by the coastal sea‐breeze front. In contrast, a single morning peak in rainfall is produced by E3SM for simulations despite the nudging of large‐scale winds toward global reanalysis, indicating precipitation in E3SM is largely controlled by local convection associated with diurnal heating. The role of propagating MCS on the environment are discussed by using a multivariate perturbation analysis. We also find that the advection of moisture perturbations from ocean to inland regions have a higher correlation with the occurrence of MCSs in the Amazon than the intensity of colder air intrusion associated with sea breezes along the coast. Moreover, the presence of large cold pools over the central Amazon basin are responsible for the maintenance of propagating deep convection.

54 ENVIRONMENTAL SCIENCES↗