Capturing sub-grid temperature and moisture variations for wildland fire modeling
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54 ENVIRONMENTAL SCIENCES↗
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Results for “Environmental Models”
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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Human–mouse comparison of the multistage nature of radiation carcinogenesis in a mathematical model
Abstract Mouse models are vital for assessing risk from environmental carcinogens, including ionizing radiation, yet the interspecies difference in the dose response precludes direct application of experimental evidence to humans. Herein, we take a mathematical approach to delineate the mechanism underlying the human–mouse difference in radiation‐related cancer risk. We used a multistage carcinogenesis model assuming a mutational action of radiation to analyze previous data on cancer mortality in the Japanese atomic bomb survivors and in lifespan mouse experiments. Theoretically, the model predicted that exposure will chronologically shift the age‐related increase in cancer risk forward by a period corresponding to the time in which the spontaneous mutational process generates the same mutational burden as that the exposure generates. This model appropriately fitted both human and mouse data and suggested a linear dose response for the time shift. The effect per dose decreased with increasing age at exposure similarly between humans and mice on a per‐lifespan basis (0.72‐ and 0.71‐fold, respectively, for every tenth lifetime). The time shift per dose was larger by two orders of magnitude in humans (7.8 and 0.046 years per Gy for humans and mice, respectively, when exposed at ~35% of their lifetime). The difference was mostly explained by the two orders of magnitude difference in spontaneous somatic mutation rates between the species plus the species‐independent radiation‐induced mutation rate. Thus, the findings delineate the mechanism underlying the interspecies difference in radiation‐associated cancer mortality and may lead to the use of experimental evidence for risk prediction in humans.
Oncology↗
Regional and Model-Specific Response Types in A Global Gridded Crop Model Ensemble
Crop models are often employed to project crop yields under changing conditions such as global warming and associated management change for adaptation. Multi-model ensembles are promoted to enhance the robustness of projections, but questions remain on what causes often large differences between projections of individual models. Global Gridded Crop Models (GGCMs) are especially exposed to this question when applied for assessing climate change impacts, adaptation, environmental impacts of agricultural production, because their results are used in downstream analyses, such as in integrated assessment or economic modeling for projecting future land-use change. Even though global gridded crop models are often based on detailed field-scale models or have implemented similar modeling principles in other ecosystem models, global-scale models are subject to substantial uncertainties from both model structure and parametrization as well as from calibration and input data quality. AgMIP’s Global Gridded Crop Model Intercomparison (GGCMI) has thus set out to intercompare GGCMs in order to evaluate model performance, describe model uncertainties, identify inconsistencies within the ensemble and underlying reasons, and to ultimately improve models and modeling capacities. In phase 2 of the GGCMI activities, 12 modeling groups followed a modeling protocol that asked for up to 1404 31-year global simulations at 0.5 arc-degree spatial resolution to assess models’ sensitivities to changes in carbon dioxide (C; 4 different levels) temperature (T; 7 different offset levels), water supply (W; 9 levels), and nitrogen (N; 3 levels), the so-called CTWN experiment (Franke et al. 2020; http://dx.doi.org/10.5194/gmd-13-2315-2020). We here present analyses of model response types using impact response surfaces along the C, T, W, and N dimensions, respectively and collectively. Doing so, we can understand differences in simulated responses per driver rather than aggregated changes in yields. We find that models’ sensitivities to the individual driver dimensions are substantially different and often more different across models than across regions. A cluster analysis finds regional and model-specific patterns. There is some agreement across models with respect to the spatial patterns of response types but strong differences in the distribution of response type clusters across models suggests that models need to undergo further scrutiny. We suggest establishing standards in model process evaluation not only against historical dynamics but also against dedicated experiments across the CTWN dimensions.
crop models↗
Controlled Environments Enable Adaptive Management in Aquatic Ecosystems Under Altered Environments
Ecosystems worldwide are impacted by altered environment conditions resulting from climate, drought, and land use changes. Gaps in the science knowledge base regarding plant community response to these novel and rapid changes limit both science understanding and management of ecosystems. We describe how CE Technologies have enabled the rapid supply of gap-filling science, development of ecosystem simulation models, and remote sensing assessment tools to provide science-informed, adaptive management methods in the impacted aquatic ecosystem of the California Sacramento-San Joaquin River Delta. The Delta is the hub for California's water, supplying Southern California agriculture and urban communities as well as the San Francisco Bay area. The changes in environmental conditions including temperature, light, and water quality and associated expansion of invasive aquatic plants negatively impact water distribution and ecology of the San Francisco Bay/Delta complex. CE technologies define changes in resource use efficiencies, photosynthetic productivity, evapotranspiration, phenology, reproductive strategies, and spectral reflectance modifications in native and invasive species in response to altered conditions. We will discuss how the CE technologies play an enabling role in filling knowledge gaps regarding plant response to altered environments, parameterization and validation of ecosystem models, development of satellite-based, remote sensing tools, and operational management strategies.
Remote Sensing↗
Urbanization exacerbates continental- to regional-scale warming
Urbanization is usually ignored when estimating past changes in large-scale climate and for future climate projections since cities historically covered a small fraction of the Earth’s surface. Here, by combining global land surface temperature observations with historical estimates of urban area, we demonstrate that the urban contribution to continental- to regional-scale warming has become non-negligible, especially for rapidly urbanizing regions and countries in Asia. Consequently, expected urban expansion over the next century suggests further increased urban influence on large-scale surface climate in the future (approximately 0.16 K for North America and Europe for high-emission scenario in 2100). Based on these results, also seen for air temperature, we argue that, in line with other forms of land use/land cover change, urbanization should be explicitly included in climate change assessments. This requires incorporation of dynamic urban extent and biophysics in current-generation Earth system models to quantify potential urban feedback on the climate system across scales.
Chakraborty, TC↗
Data-model files associated with the manuscript "The Effects of Spatial and Temporal Resolution of Gridded Meteorological Forcing on Watershed Hydrological Responses" (Shuai et al., 2022 HESS)
This data package contains the model inputs and outputs used in "The Effects of Spatial and Temporal Resolution of Gridded Meteorological Forcing on Watershed Hydrological Responses" (Shuai et al., 2022 HESS). The data.zip file contains the data used to drive the model simulations. The model.zip file contains the XML input file for ATS. The notebook.zip file contains the Jupyter notebooks for pre- and post- processing model results. The figures.zip file contains the raw figures associated with the manuscript.Meteorological forcing plays a critical role in accurately simulating the watershed hydrological cycle. With the advancement of high-performance computing and the development of integrated watershed models, simulating the watershed hydrological cycle at high temporal (hourly to daily) and spatial resolution (10s of meters) has become efficient and computationally affordable. These hyperresolution watershed models require high resolution of meteorological forcing as model input to ensure the fidelity and accuracy of simulated responses. In this study, we utilized the Advanced Terrestrial Simulator (ATS), an integrated watershed model, to simulate surface and subsurface flow and land surface processes using unstructured meshes at the Coal Creek Watershed near Crested Butte (Colorado). We compared simulated watershed hydrologic responses including streamflow, and distributed variables such as evapotranspiration, snow water equivalent (SWE), and groundwater table driven by three publicly available, gridded meteorological forcings (GMFs) -- Daily Surface Weather and Climatological Summaries (Daymet), Parameter-elevation Regressions on Independent Slopes Model (PRISM), and North American Land Data Assimilation System (NLDAS). By comparing various spatial resolutions (ranging from 400 m to 4 km) of PRISM, the simulated streamflow only becomes marginally worse when spatial resolution of meteorological forcing is coarsened to 4 km (or 30% of the watershed area). However, the 4 km resolution has much worse performance than finer resolution in spatially distributed variables such as SWE. Using temporally disaggregated PRISM, we compared models forced by different temporal resolutions (hourly to daily), sub-daily resolution preserves the dynamic watershed responses (e.g., diurnal fluctuation of streamflow) that are absent in results forced by daily resolution. Conversely, the simulated streamflow shows better performance using daily resolution compared to that using sub-daily resolution. Our findings suggest that the choice of GMF and its spatiotemporal resolution depends on the quantity of interest and its spatial and temporal scale, which may have important implications on model calibration and watershed management decisions.
54 ENVIRONMENTAL SCIENCES↗
Investigating Weathering of Basaltic Materials in Gale Crater, Mars: A Combined Laboratory, Modeling and Terrestrial Field Approach
Recent observations from Gale Crater, Mars document past aqueous alteration both in the formation of the Stimson sandstone unit, as well as in the formation of altered fractures within that unit. Geochemical and mineralogical data from Curiosity also suggest Fe-rich amorphous weathering products are present in most samples measured to date. Here we interpret conditions of possible past weathering in Gale Crater using a combination of field, laboratory, and modeling work. In order to better understand secondary Fe-rich phases on Mars, we are examining formation of weathering products in high Fe and Mg and low Al serpentine soils in the Klamath Mountains, CA. We have isolated potential weathering products from these soils, and are analyzing them using synchrotron μXRF and μXRD as well as FullPat for a direct comparison to analyses from Gale Crater. In order to interpret the implications of the persistence of potential secondary Fe-containing phases on Mars, we are also measuring the dissolution rates of the secondary weathering products allophane, Fe-rich allophane, and hisingerite. Ongoing dissolution experiments of these materials suggest that they dissolve significantly more rapidly than more crystalline secondary minerals with similar chemical compositions. Finally, to quantify the specific conditions of past aqueous alteration in Gale Crater we are performing reactive transport modeling of a range of possible past environmental conditions. Specifically, we are testing the conditions under which a Stimson unit-like material forms from a parent material similar to Rocknest or Bagnold eolian deposits, and the conditions under which observed altered fracture zones form from a Stimson unit-like parent material. Our modeling results indicate that the formation of the Stimson unit is consistent with leaching of an eolian deposit with a solution of pH = 6-8, and that formation of the altered fracture zones is consistent with leaching with a very acidic (pH = 2-3) high sulfate solution containing Ca. These results suggest circumneutral pH conditions during authigenesis or early diagenesis in the Stimson formation sediments followed by diagenetic alteration by very acidic solutions along fracture zones.
Hausrath, Elisabeth↗
Modelling the interlayer bond strength of 3D printed concrete with surface moisture
Highlights: • An analytical model for interlayer adhesion of 3DPC is proposed based on the amount of surface moisture on the interlayer. • For this mix, the model accurately (RMSE=2.5%) predicts the reduction in interlayer adhesion from 30% to 50%. • Internal curing with superabsorbent polymers increases the interlayer adhesion by 10% and flexural strength by 19%. • SAPs also improve the initial thixotropy by 49% and buildability by 25% compared to the reference. Providing additional water to the hydrating cementitious particles is essential to achieve the optimal mechanical performance of the low w/b concrete mixes preferred for 3D printing. This study incorporates superabsorbent polymers (SAP) and additional water in 3D printed concrete (3DPC) to promote the hydration process through delayed internal water release. The study shows that a retentive SAP modifies the rheological development by absorbing the pore fluid for a short period after printing. The absorption-induced stiffening increases the thixotropy and buildability by 49% and 25%, respectively. A retentive SAP increases the flexural strength and interlayer adhesion by 19% and 10%, respectively. This is due to the internal water release that promotes hydration. Evaporation of the interlayer moisture during the pass time has the opposite effect— evaporation reduces the interlayer adhesion. Based on this assumption, an analytical model is proposed. The model accounts for the pass time, bleeding, and the environmental evaporation rate to estimate the surface moisture and predict the lack of interlayer adhesion. In this study, the model accurately (RMSE = 2.5%) predicted an interlayer adhesion reduction from 30% to 50%. The interlayer adhesion results of other studies could also be predicted.
36 MATERIALS SCIENCE↗
Improving Numerical Weather Predictions of Summertime Precipitation Over the Southeastern U.S. Through a High-Resolution Initialization of the Surface State
It is hypothesized that high-resolution, accurate representations of surface properties such as soil moisture and sea surface temperature are necessary to improve simulations of summertime pulse-type convective precipitation in high resolution models. This paper presents model verification results of a case study period from June-August 2008 over the Southeastern U.S. using the Weather Research and Forecasting numerical weather prediction model. Experimental simulations initialized with high-resolution land surface fields from the NASA Land Information System (LIS) and sea surface temperature (SST) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) are compared to a set of control simulations initialized with interpolated fields from the National Centers for Environmental Prediction 12-km North American Mesoscale model. The LIS land surface and MODIS SSTs provide a more detailed surface initialization at a resolution comparable to the 4-km model grid spacing. Soil moisture from the LIS spin-up run is shown to respond better to the extreme rainfall of Tropical Storm Fay in August 2008 over the Florida peninsula. The LIS has slightly lower errors and higher anomaly correlations in the top soil layer, but exhibits a stronger dry bias in the root zone. The model sensitivity to the alternative surface initial conditions is examined for a sample case, showing that the LIS/MODIS data substantially impact surface and boundary layer properties.
Case, Jonathan L.↗
Investigations of respiratory control systems simulation
The Grodins' respiratory control model was investigated and it was determined that the following modifications were necessary before the model would be adaptable for current research efforts: (1) the controller equation must be modified to allow for integration of the respiratory system model with other physiological systems; (2) the system must be more closely correlated to the salient physiological functionings; (3) the respiratory frequency and the heart rate should be expanded to illustrate other physiological relationships and dependencies; and (4) the model should be adapted to particular individuals through a better defined set of initial parameter values in addition to relating these parameter values to the desired environmental conditions. Several of Milhorn's respiratory control models were also investigated in hopes of using some of their features as modifications for Grodins' model.
Gallagher, R. R.↗
CARETS: An experimental regional information system using ERTS data
The U. S. Geological Survey CARETS (Central Atlantic Regional Ecological Test Site)/ERTS investigation is testing the applicability of ERTS data as input to an environmental information system for a multi-state mid-Atlantic region surrounding the Chesapeake and Delaware Bays. The information system framework encompasses a flow of information through several stages from sensor to user, and involving evaluation and feedback from several potential users. Basic assumptions of the CARETS project model are that there is a measurable environmental impact associated with land use and land use change as determined with remote sensor data, and that the ERTS derived land use data sets, when properly calibrated, may thus provide regional planners and administrators with a shortcut to an understanding of the environmental changes that are going on in their regions.
Alexander, R. H.↗
Generalizability analysis of tool condition monitoring ensemble machine learning models
Tool condition monitoring (TCM) is an essential research area for the optimization and automation of metal machining processes, and could help manufacturers reduce costs, production time, machine downtime, energy use, and part scrappage. However, TCM systems developed in prior studies have struggled to reach the high level of generalizability which is necessary for industrial applications. This study addresses TCM system generalizability to new machining conditions, how variations in machining and environmental conditions may be used to improve model generalizability, and ensemble machine learning techniques for TCM. Further, milling tool life experiments were conducted using various machining conditions, and the processes' sound, spindle power, and axial load signals were collected. Different machine learning models were evaluated for the prediction of tool wear levels, including four individual models and five ensemble models. Changes in cutting speed were found to display a large effect on model performance, while the chip load showed some effect, and the feed rate had little effect. A simulated noise data augmentation technique for model improvement is applied within TCM for the first time, and resulted in increased model generalizability and reduced overfitting. Across several performance metrics the extremely randomized trees ensemble machine learning model generally performed the best for this application, achieving a leave-one-group-out cross validation accuracy score of 92.4 %, a 10-fold cross validation score of 98.9 %, and an averaged accuracy across 11 generalizability tests of 87.3 %.
42 ENGINEERING↗
Multi-Scale Modeling Framework for Mercury Biogeochemistry
Multi-Scale modeling of mercury (Hg) geochemical speciation and reactions has been performed by integrating atomistic quantum chemical calculations with continuum scale speciation models. Major progress has been made in the improvement of quantum chemical models to calculate critical thermodynamic data for Hg complexes in aquatic environments. Rapid and reliable quantum chemical approaches have been developed for calculating acid dissociation constants (pK a ) and stability constants (log K), with calculated mean unsigned errors of 0.5 and 1.5 log units, respectively for ligand molecules and Hg complexes. At the continuum scale, systematic analysis of uncertainty propagation in mercury (Hg) speciation modeling has been conducted and was used to identify environmental conditions under which thermodynamic constant uncertainties are significant and recommended to be accounted for. The integrated framework for multi-scale modeling of mercury geochemistry is open to the research community through the web-based multiscale modeling aqueous speciation resource, AQUA-MER. The improved quantum chemical approaches for thermodynamic constant calculations are accessible through AQUA-MER and can be used to provide the missing constants in the continuum scale speciation calculations. In addition to low molecular mass Hg complex speciation, modeling natural aquatic environments also involve the transport of high molecular weight dissolved organic matter (DOM) in reactive flows simultaneously with equilibrium and kinetic reactions. To this end, atomistic MD simulations were performed to capture the details of aggregation, mechanisms and distribution of functional groups in DOM at the molecular level. The elemental composition and calculated bulk properties of the DOM models are in close agreement with experimental measurements. A travel-time based reactive transport model in the hyporheic zone of stream corridors was established for the multicomponent Hg-DOM-S system and implemented through PFLOTRAN.
54 ENVIRONMENTAL SCIENCES↗
Using Complex Probability Amplitudes to Simulate Solute Transport in Composite Porous Media
Probability amplitudes are fundamental to quantum mechanics and offer robust descriptions of complicated systems, which have allowed physicists to explain behaviors inaccessible to classical physics. This article ponders how some of the same conceptual underpinnings of the mathematics used for modeling quantum systems might be applied to subsurface water resources problems and speculates how these tools could facilitate applications on quantum computers. A probability amplitude-based model for describing advective-dispersive transport in porous media using linear operators is investigated. The proposed complex valued model decomposes spreading into two “sub-continuum partial dispersion” coefficients, and this recovers classical spreading when the sum of these coefficients is the Fickian dispersion coefficient. However, the probability amplitudes have a manyto-one relationship to a probability distribution, so it embeds a level of heterogeneity into seemingly equivalent functions. Two propagators with different sub-continuum coefficients may have the same macroscopic behavior when either is considered in isolation, but when they act on the other the system’s behavior changes. Additionally, differences in the amplitudes cause a reduction in spreading as velocity correlations are disrupted, despite both propagators having identical dispersion coefficients, and this cannot be achieved using classical methods without changing the dispersion coefficient. The main point is that these amplitude-based models offer a way to embed information about the system into the propagators, instead of just “averaging it out” when making an upscaled model.
54 ENVIRONMENTAL SCIENCES↗
The effect of ion pairing on speciation and transport in ion exchange membranes at varying hydration levels: A four-state model
Understanding ion pairing in ion exchange membranes (IEMs) is essential for advancing IEM applications in energy and environmental technologies. Here, this study introduces a four-state molecular dynamics model to quantify speciation and transport within Nafion-117, specifically examining the role of ion pairing in monovalent and divalent counterions (NaCl, Na 2 SO 4 , and MgSO 4 ). By analyzing radial distribution functions (RDFs) and molecular snapshots, we distinguish ion pairing modes and classify counterions into four states: condensed counterion, condensed ion pair, free ion pair, and free counterion. A key finding is that while divalent counterions (e. g., Mg 2+ ) maintain stable speciation across hydration levels, monovalent counterions (e.g., Na + ) show notable speciation shifts with hydration. Both monovalent and divalent counterions are not diffusive when condensed onto the polymer (sorbed to membrane functional groups). In contrast, free counterions are diffusive across all hydration levels. To evaluate the overall diffusivity of counterions, four-state fractions and diffusivities are computed, each contributing to counterion transport. The condensed/free ion speciation for multivalent sulfate salts aligns with previous revisions to the Donnan-Manning framework that include ion pairing, thereby validating its relevance to established membrane theories. The four-state model's diffusivity results support several current ion exchange assumptions, including that the condensed counterions are immobile, while uncondensed counterions are mobile. The four-state model offers insights into contact ion pairing within IEMs, highlighting its potential even when undetected in aqueous solution experiments. This work advances the theoretical understanding of counterion speciation in IEMs while identifying model limitations that suggest avenues for refinement, such as distinguishing water-mediated ion pairs between fully hydrated ions.
Ion exchange membranes↗
Convolutional Non-Homogeneous Poisson Process and its Application to Wildfire Ignition Risk Quantification for Power Delivery Networks
To quantify wildfire ignition risks on power delivery networks, the current practice predominantly relies on the empirically calculated fire danger indices, which may not well capture the effects of dynamically changing environmental factors. This article proposes a spatio-temporal point process model, known as the Convolutional Non-homogeneous Poisson Process (cNHPP), and applies the model to quantify wildfire ignition risks for power delivery networks. The proposed model captures both the current (i.e., instantaneous) and cumulative (i.e., historical) effects of key environmental processes (i.e., covariates) on wildfire risks, as well as the spatio-temporal dependency among different segments of the power delivery network. The computation and interpretation of the intensity function are thoroughly investigated. We apply the proposed approach to estimate wildfire ignition risks on major transmission lines in California, using historical fire data, meteorological and vegetation data obtained from the National Oceanic and Atmospheric Administration and National Aeronautics and Space Administration. Here, a comprehensive comparison study is performed to show the applicability and predictive capability of the proposed approach.
Non-homogeneous Poisson Process↗
Analysis of Photovoltaic Energy: CRADA Number CRD-21-17862 (Cooperative Research and Development Final Report)
For this project, NREL will work with the Participant to model phase change material performance, model photovoltaic thermodynamics performance, and predict photovoltaic module durability based on environmental conditions to help develop optimized photovoltaic roofing designs. This project will develop thermodynamic models of integrated photovoltaic roofing with phase change materials. These models will be used to optimize the materials and design selections based on reducing photovoltaic operating temperatures while balancing cost effective integration of phase change materials.
14 SOLAR ENERGY↗
Benchmarking performance changes in the simulation of extratropical modes of variability across CMIP generations
In this work, we evaluate extratropical modes of variability in the three most recent phases of the Coupled Model Intercomparison Project (CMIP3, 5, and 6) to gauge improvement of climate models over time. A suite of high-level metrics is employed to objectively evaluate how well climate models simulate the qobserved Northern Annular Mode (NAM), North Atlantic Oscillation (NAO), Pacific North America pattern (PNA), Southern Annular Mode (SAM), Pacific Decadal Oscillation (PDO), North Pacific Oscillation (NPO), and North Pacific Gyre Oscillation (NPGO). We apply a Common Basis Function (CBF) approach that projects model anomalies onto observed empirical orthogonal functions (EOFs), together with the traditional EOF approach, to CMIP Historical and AMIP models. We find simulated spatial patterns of those modes have been significantly improved in the newer models, although the skill improvement is sensitive to the mode and season considered. We identify some potential contributions to the pattern improvement of certain modes (e.g., the Southern Hemisphere jet and High-top vertical coordinate), however the performance changes are likely attributed to gradual improvement of the base climate and multiple relevant processes. Less performance improvement is evident in the mode amplitude of these modes and systematic overestimation of the mode amplitude in spring remains in the newer climate models. We find that the post-dominant season amplitude errors in atmospheric modes are not limited to coupled runs but are often already evident in AMIP simulations. This suggests that rectifying the egregious post-dominant season amplitude errors found in many models can be addressed in an atmospheric-only framework making it more tractable to address in the model development process.
54 ENVIRONMENTAL SCIENCES↗