Search NASA⌕ Search

SEARCH · Search NASA

Results for “surface modeling”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS2025

Integrating the Interconnections Between Groundwater and Land Surface Processes Through the Coupled NASA Land Information System and ParFlow Environment

Understanding the interactions between the atmosphere, the land, and the subsurface is fundamental to hydrology and is critical for a better assessment of the impacts of climate change and human management on hydrological systems. However, many land surface models simplify the subsurface hydrology and thereby these interactions. In this study, we couple the land surface model Noah-MP included in the NASA Land Information System (LIS) with the integrated hydrologic model ParFlow (ParFlow-LIS) using the Earth System Modeling Framework (ESMF) and the National United Operational Prediction Capability (NUOPC). This coupling improves the simulation of water and energy cycle processes by adding the three-dimensional variably saturated and heterogeneous flow in the subsurface using sophisticated and nonlinear physics-based equations as well as the advances in satellite remote sensing-based data assimilation of the land surface, thereby benefiting the integrated hydrologic modeling and data assimilation community. We use the High Plains aquifer, located in the central United States, as a testbed to evaluate the coupled ParFlow-LIS system. The new ParFlow-LIS system accounts for the effects of topographically driven flows on the land surface, producing more fine-scale patterns of land surface states and fluxes than standalone LIS. In addition, ParFlow-LIS enables the consideration of the effect of subsurface water storage on evapotranspiration. This is particularly important in areas and times with dry soils, such as during drought conditions or in the presence of a cone of depression due to pumping.

land surface modeling↗
NASA NTRS1996

Modeling the surface evapotranspiration over the southern Great Plains

We have developed a method to apply the Simple Biosphere Model of Sellers et al to calculate the surface fluxes of sensible heat and water vapor at high spatial resolution over the domain of the US DOE's Cloud and Radiation Testbed (CART) in Kansas and Oklahoma. The CART, which is within the GCIP area of interest for the Mississippi River Basin, is an extensively instrumented facility operated as part of the DOE's Atmospheric Radiation Measurement (ARM) program. Flux values calculated with our method will be used to provide lower boundary conditions for numerical models to study the atmosphere over the CART domain.

Computerized Simulation↗
NASA NTRS1990

Modeling of surface roughness effects on glaze ice accretion

A series of experimental investigations focused on studying the cause and effect of roughness on accreting glaze ice surfaces were conducted. Detailed microvideo observations were made of glaze ice accretions on 1 to 4 inch diameter cylinders in three icing wind tunnels (the Data Products of New England six inch test facility, the NASA Lewis Icing Research Tunnel, and the B. F. Goodrich Ice Protection Research Facility). Infrared thermal video recordings were made of accreting ice surfaces in the Goodrich facility. Distinct zones of surface water behavior were observed; a smooth wet zone in the stagnation region with a uniform water film; a rough zone where surface tension effects caused coalescence of surface water into stationary beads; a horn zone where roughness elements grow into horn shapes; a runback zone where surface water ran back as rivulets; and a dry zone where rime feathers formed. The location of the transition from the smooth to the rough zone was found to migrate with time towards the stagnation point. The behavior of the transition appeared to be controlled by boundary layer transition and bead formation mechanisms at the interface between the smooth and rough zones. Regions of wet ice growth and enhanced heat transfer were clearly visible in the infrared video recordings of glaze ice surfaces. A simple multi-zone modification to the current glaze ice accretion model was proposed to include spatial variability in surface roughness.

Hansman, R. John, Jr.↗
NASA NTRS1994

Growth of Au on Ni(110): a BFS Modelling of Surface Alloy Phases

Recent experiments using scanning tunneling microscopy show evidence for the formation of surface alloys of otherwise immiscible metals. Such is the case for Au deposited in Ni(11), where experiments by Pleth Nielsen et al. indicate that at low Au coverage (less than 0.5 ML), Au atoms replace Ni atoms in the surface layer forming a surface alloy while the Ni atoms form islands on the surface. In this work, we present results of a theoretical modeling of this phenomenon using the recently developed BFS method for alloys. We provide results of an extensive analysis of the growth process which strongly support the conclusions drawn from the experiment; at very low coverages, there is tendency for dimer formation on the overlayer, which later exchange positions with Ni atoms in the surface layer, thus accounting for the large number of substituted dimers. Ni island formations as well as other alternative short range order patterns are discussed.

Bozzolo, Guillermo↗
DOE OSTI2024

DeepPhenoMem V1.0: deep learning modelling of canopy greenness dynamics accounting for multi-variate meteorological memory effects on vegetation phenology

Abstract. Vegetation phenology plays a key role in controlling the seasonality of ecosystem processes that modulate carbon, water and energy fluxes between the biosphere and atmosphere. Accurate modelling of vegetation phenology in the interplay of Earth's surface and the atmosphere is thus crucial to understand how the coupled system will respond to and shape climatic changes. Phenology is controlled by meteorological conditions at different timescales: on the one hand, changes in key meteorological variables (temperature, water, radiation) can have immediate effects on the vegetation development; on the other hand, phenological changes can be driven by past environmental conditions, known as memory effects. However, the processes governing meteorological memory effects on phenology are not completely understood, resulting in their limited performance of vegetation phenology represented in land surface models. A deep learning model, specifically a long short-term memory network (LSTM), has the potential to capture and model the meteorological memory effects on vegetation phenology. Here, we apply the LSTM to model the vegetation phenology using meteorological drivers and high-temporal-resolution canopy greenness observations through digital repeat photography by the PhenoCam network. We compare a multiple linear regression model, a no-memory-effect LSTM model and a full-memory-effect LSTM model to predict the whole seasonal greenness trajectory and the corresponding phenological transition dates across 50 sites and 317 site years during 2009–2018, covering deciduous broadleaf forests, evergreen needleleaf forests and grasslands. Results show that the deep learning model outperforms the multiple linear regression model, and the full-memory-effect LSTM model performs better than the no-memory-effect model for all three plant function types (median R2 of 0.878, 0.957 and 0.955 for broadleaf forests, evergreen needleleaf forests and grasslands). We also find that the full-memory-effect LSTM model is capable of predicting the seasonal dynamic variations of canopy greenness and reproducing trends in shifting phenological transition dates. We also performed a sensitivity analysis of the full-memory-effect LSTM model to assess its plausibility, revealing its coherence with established knowledge of vegetation phenology sensitivity to meteorological conditions, particularly changes in temperature. Our study highlights that (1) multi-variate meteorological memory effects play a crucial role in vegetation phenology, and (2) deep learning opens up new avenues for improving the representation of vegetation phenological processes in land surface models via a hybrid modelling approach.

Geology↗
NASA NTRS1995

Growth of Au on Ni(110): A Semiempirical Modeling of Surface Alloy Phases

Recent experiments using scanning tunneling microscopy show evidence for the formation of surface alloys of otherwise immiscible metals. Such is the case for Au deposited in Ni(110), where experiments by Pleth Nielsen el al.indicate that at low Au coverage (less than 0. 5 ML), Au atoms replace Ni atoms in the surface layer forming a surface alloy while the Ni atoms form islands on the surface. In this paper, we present results of a theoretical modeling of this phenomenon using the recently developed Bozzolo-Ferrante-Smith method for alloys. We provide results of an extensive analysis of the growth process that strongly support the conclusions drawn from the experiment: at very low coverages, there is a tendency for dimer formation on the overlayer, which later exchange positions with Ni atoms in the surface layer, thus accounting for the large number of substituted dimers. Ni island formation as well as other alternative short-range-order patterns are discussed.

Bozzolo, Guillermo↗
NASA NTRS1984

Nitrogen on Triton

The tentative identification of liquid nitrogen as the source of the 2.16-micron absorption band in the spectrum of Triton has suggested a surface model in which nitrogen, together with the previously identified methane, occur in some kind of chemical association. Water frost may be another surface chemistry component, and dark, photochemically-produced particles occur as a minor contaminant of the ices or liquid. Temperature is noted to be a critical factor in the surface model, because the calculated subsolar surface temperature of Triton lies near nitrogen's melting-freezing temperature. The present modeling of Triton suggests nitrogen's occurrence in the form of fine grains.

Clark, R. N.↗
NASA NTRS2011

Improvements to a Response Surface Thermal Model for Orion

A study was performed to determine if a Design of Experiments (DOE)/Response Surface Methodology could be applied to on-orbit thermal analysis and produce a set of Response Surface Equations (RSE) that predict Orion vehicle temperatures within 10 F. The study used the Orion Outer Mold Line model. Five separate factors were identified for study: yaw, pitch, roll, beta angle, and the environmental parameters. Twenty-three external Orion components were selected and their minimum and maximum temperatures captured over a period of two orbits. Thus, there are 46 responses. A DOE case matrix of 145 runs was developed. The data from these cases were analyzed to produce a fifth order RSE for each of the temperature responses. For the 145 cases in the DOE matrix, the agreement between the engineering data and the RSE predictions was encouraging with 40 of the 46 RSEs predicting temperatures within the goal band. However, the verification cases showed most responses did not meet the 10 F goal. After reframing the focus of the study to better align the RSE development with the purposes of the model, a set of RSEs for both the minimum and maximum radiator temperatures was produced which predicted the engineering model output within +/-4 F. Therefore, with the correct application of the DOE/RSE methodology, RSEs can be developed that provide analysts a fast and easy way to screen large numbers of environments and assess proposed changes to the RSE factors.

Miller, Stephen W.↗
NASA NTRS2013

Consistency of Estimated Global Water Cycle Variations Over the Satellite Era

Motivated by the question of whether recent indications of decadal climate variability and a possible "climate shift" may have affected the global water balance, we examine evaporation minus precipitation (E-P) variability integrated over the global oceans and global land from three points of view-remotely sensed retrievals / objective analyses over the oceans, reanalysis vertically-integrated moisture convergence (MFC) over land, and land surface models forced with observations-based precipitation, radiation and near-surface meteorology. Because monthly variations in area-averaged atmospheric moisture storage are small and the global integral of moisture convergence must approach zero, area-integrated E-P over ocean should essentially equal precipitation minus evapotranspiration (P-ET) over land (after adjusting for ocean and land areas). Our analysis reveals considerable uncertainty in the decadal variations of ocean evaporation when integrated to global scales. This is due to differences among datasets in 10m wind speed and near-surface atmospheric specific humidity (2m qa) used in bulk aerodynamic retrievals. Precipitation variations, all relying substantially on passive microwave retrievals over ocean, still have uncertainties in decadal variability, but not to the degree present with ocean evaporation estimates. Reanalysis MFC and P-ET over land from several observationally forced diagnostic and land surface models agree best on interannual variations. However, upward MFC (i.e. P-ET) reanalysis trends are likely related in part to observing system changes affecting atmospheric assimilation models. While some evidence for a low-frequency E-P maximum near 2000 is found, consistent with a recent apparent pause in sea-surface temperature (SST) rise, uncertainties in the datasets used here remain significant. Prospects for further reducing uncertainties are discussed. The results are interpreted in the context of recent climate variability (Pacific Decadal Oscillation, Atlantic Meridional Overturning), and efforts to distinguish these modes from longer-term trends.

Robertson, F. R.↗
NASA NTRS2013

Consistency of Estimated Global Water Cycle Variations Over the Satellite Era

Motivated by the question of whether recent indications of decadal climate variability and a possible "climate shift" may have affected the global water balance, we examine evaporation minus precipitation (E-P) variability integrated over the global oceans and global land from three points of view-remotely sensed retrievals / objective analyses over the oceans, reanalysis vertically-integrated moisture convergence (MFC) over land, and land surface models forced with observations-based precipitation, radiation and near-surface meteorology. Because monthly variations in area-averaged atmospheric moisture storage are small and the global integral of moisture convergence must approach zero, area-integrated E-P over ocean should essentially equal precipitation minus evapotranspiration (P-ET) over land (after adjusting for ocean and land areas). Our analysis reveals considerable uncertainty in the decadal variations of ocean evaporation when integrated to global scales. This is due to differences among datasets in 10m wind speed and near-surface atmospheric specific humidity (2m qa) used in bulk aerodynamic retrievals. Precipitation variations, all relying substantially on passive microwave retrievals over ocean, still have uncertainties in decadal variability, but not to the degree present with ocean evaporation estimates. Reanalysis MFC and P-ET over land from several observationally forced diagnostic and land surface models agree best on interannual variations. However, upward MFC (i.e. P-ET) reanalysis trends are likely related in part to observing system changes affecting atmospheric assimilation models. While some evidence for a low-frequency E-P maximum near 2000 is found, consistent with a recent apparent pause in sea-surface temperature (SST) rise, uncertainties in the datasets used here remain significant. Prospects for further reducing uncertainties are discussed. The results are interpreted in the context of recent climate variability (Pacific Decadal Oscillation, Atlantic Meridional Overturning), and efforts to distinguish these modes from longer-term trends.

Robertson, F. R.↗
NASA NTRS2020

Contribution of Infiltration Process Uncertainty on the Simulation of Terrestrial Water and Energy Budgets

The infiltration step is the major forking point of precipitation partition in land surface models, which plays a more significant role than canopy interception for simulating water and energy budgets.In this study, we found significant differences in water and energy-related outputs amount JULES, Noah, Noah-MP, and VIC. The differences are directly or indirectly related to the infiltration components in the models. Those differences add uncertainties to the applications of land surface models. Thorough evaluations are needed to determine the reliability of infiltration schemes used in these models.

Wang, Shugong↗
DOE OSTI2020

Accelerated Cu2O Reduction by Single Pt Atoms at the Metal-Oxide Interface§

The reducibility of metal oxides, when serving as the catalyst support or the active sites themselves, plays an important role in heterogeneous catalytic reactions. Here we present an integrated experimental and theoretical study that reveals how the addition of small amounts of atomically dispersed Pt at the metal/oxide interface dramatically enhances the reducibility of a Cu2O thin film by H2. X-ray photoelectron spectroscopy (XPS) and temperature-programmed desorption (TPD) results reveal that upon oxidation, a PtCu single-atom alloy (SAA) surface is covered by a thin Cu2O film and is therefore unable to dissociate H2. Despite this, in situ studies using ambient pressure (AP) XPS reveal that the presence of a small amount of Pt under the oxide layer can, at the single-atom limit, promote the reduction of Cu2O by H2 at room temperature. We build two density functional theory based surface models to better understand these experimental findings: A Cu2O/Cu(111)-like surface oxide layer, known as the ‘29’ oxide, in which Pt is alloyed into the Cu(111) surface as well as a PtCu SAA. Our calculations suggest that the increased activity is due to the presence of atomically dispersed Pt under the surface oxide layer, which weakens the Cu-O bonds in its immediate vicinity, thus making the interface between subsurface Pt and the surface oxide a nucleation site for the formation of metallic Cu. This initial step in the reduction process results in the presence of surface Pt atoms surrounded by metallic Cu patches, and the Pt atoms become active in H2 dissociation, which consequently accelerates the reduction of the oxide layer. This work demonstrates how isolated Pt atoms at the metal/oxide interface of a Cu-based catalyst accelerate the reduction of the oxide and, therefore, helps maintain the active, reduced state of the catalyst under reaction conditions, as is required for the synthesis of methanol from CO2 hydrogenation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2018

Carbon-Nitrogen Coupling Under Three Schemes of Model Representation: A Traceability Analysis

The interaction between terrestrial carbon (C) and nitrogen (N) cycles has been incorporated into more and more land surface models. However, the scheme of C-N coupling differs greatly among models, and how these diverse representations of C-N interactions will affect C-cycle modeling remains unclear. In this study, we explored how the simulated ecosystem C storage capacity in the terrestrial ecosystem (TECO) model varied with three different commonly used schemes of C-N coupling. The three schemes (SM1, SM2, and SM3) have been used in three different coupled C-N models (i.e., TECO-CN, CLM 4.5, and O-CN, respectively). They differ mainly in the stoichiometry of C and N in vegetation and soils, plant N uptake strategies, down regulation of photosynthesis, and the pathways of N import. We incorporated the three C-N coupling schemes into the C-only version of the TECO model and evaluated their impacts on the C cycle with a traceability framework. Our results showed that all three of the C-N schemes caused significant reductions in steady-state C storage capacity compared with the C-only version with magnitudes of −23%, −30%, and −54% for SM1, SM2, and SM3, respectively. This reduced C storage capacity was mainly derived from the combined effects of decreases in net primary productivity (NPP; −29%, −15%, and −45%) and changes in mean C residence time (MRT; 9%, −17%, and −17%) for SM1, SM2, and SM3, respectively. The differences in NPP are mainly attributed to the different assumptions on plant N uptake, plant tissue C : N ratio, down regulation of photosynthesis, and biological N fixation. In comparison, the alternative representations of the plant vs. microbe competition strategy and the plant N uptake, combined with the flexible C : N ratio in vegetation and soils, led to a notable spread in MRT. These results highlight the fact that the diverse assumptions on N processes represented by different C-N coupled models could cause additional uncertainty for land surface models. Understanding their difference can help us improve the capability of models to predict future biogeochemical cycles of terrestrial ecosystems.

Du, Zhenggang↗
DOE OSTI2022

Improved Boundary Conditions for Coupled Geospace Models: An Application in Modeling Spacecraft Surface Charging Environment

Abstract Spacecraft surface charging in the inner magnetosphere often occurs in the pre‐midnight to the dawn sector when electron fluxes of tens of keV increase. Inner magnetosphere ring current models can be used to simulate/predict the spacecraft surface charging environment, with their outer boundary conditions specified either based on observations or provided by other models, such as MHD models. In the latter approach, using MHD quantities, the flux spectrum at the outer boundary is commonly assumed to follow a Kappa or Maxwellian distribution function. Such a method however often departs greatly from the realistic spectrum at E < tens of keV, a crucial energy range in the surface charging anomaly. In order to achieve a better representation of the surface charging environment, we propose to combine the MHD‐parameterized flux spectrum with an empirical electron flux model of E < 40 keV to set the electron flux boundary condition. Results indicate that as opposed to the case where the MHD‐parameterized flux distribution is solely used at the model boundary, simulations with the new boundary condition yields a more intense surface charging environment. The integrated electron flux between 10 < E < 50 keV, a measure of the severity of the surface charging environment, is significantly enhanced by 1‐2 orders of magnitude, leading to a much better agreement with Van Allen Probes measurements. This study hence demonstrates a reasonable solution to the setting of outer boundary conditions for inner magnetosphere models and is recommended for coupled geospace circulation models.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Impact of Vegetation Assimilation on Flash Drought Characteristics across the Continental United States

Predicting and managing the impacts of flash droughts is difficult owing to their rapid onset and intensification. Flash drought monitoring often relies on assessing changes in root-zone soil moisture. However, the lack of widespread soil moisture measurements means that flash drought assessments often use process-based model data like that from the North American Land Data Assimilation System (NLDAS). Such reliance opens flash drought assessment to model biases, particularly from vegetation processes. Here, we examine the influence of vegetation on NLDAS-simulated flash drought characteristics by comparing two experiments covering 1981–2017: open loop (OL), which uses NLDAS surface meteorological forcing to drive a land surface model using prognostic vegetation, and data assimilation (DA), which instead assimilates near-real-time satellite-derived leaf area index (LAI) into the land surface model. The OL simulation consistently underestimates LAI across the United States, causing relatively high soil moisture values. Both experiments produce similar geographic patterns of flash droughts, but OL produces shorter duration events and regional trends in flash drought occurrence that are sometimes opposite to those in DA. Across the Midwest and Southern United States, flash droughts are 4 weeks (about 70%) longer on average in DA than OL. Moreover, across much of the Great Plains, flash drought occurrence has trended upward according to the DA experiment, opposite to the trend in OL. This sensitivity of flash drought to the representation of vegetation suggests that representing plants with greater fidelity could aid in monitoring flash droughts and improve the prediction of flash drought transitions to more persistent and damaging long-term droughts.

Drought↗
NASA NTRS2021

Modeling Snow Ablation over the Western United States Mountains: Patterns and Controlling Factors

When compared with differences in snow accumulation predicted by widely used hydrological models, there is a much greater divergence among otherwise “good” models in their simulation of the snow ablation process. Here, we explore differences in the performance of the Variable Infiltration Capacity model (VIC), Noah land surface model with multiparameterization options (Noah-MP), the Catchment model, and the third-generation Simplified Simple Biosphere model (SiB3) in their ability to reproduce observed snow water equivalent (SWE) during the ablation season at 10 Snowpack Telemetry (SNOTEL) stations over 1992–2012. During the ablation period, net radiation generally has stronger correlations with observed melt rates than does air temperature. Average ablation rates tend to be higher (in both model predictions and observations) at stations with a large accumulation of SWE. The differences in the dates of last snow between models and observations range from several days to approximately a month (on average 5.1 days earlier than in observations). If the surface cover in the models is changed from observed vegetation to bare soil in all of the models, only the melt rate of the VIC model increases. The differences in responses of models to canopy removal are directly related to snowpack energy inputs, which are further affected by different algorithms for surface albedo and energy allocation across the models. We also find that the melt rates become higher in VIC and lower in Noah-MP if the shrub/grass present at the observation sites is switched to trees.

Snow↗
NASA NTRS2011

Comparison of Resource Requirements for a Wind Tunnel Test Designed with Conventional vs. Modern Design of Experiments Methods

The factors that determine data volume requirements in a typical wind tunnel test are identified. It is suggested that productivity in wind tunnel testing can be enhanced by managing the inference error risk associated with evaluating residuals in a response surface modeling experiment. The relationship between minimum data volume requirements and the factors upon which they depend is described and certain simplifications to this relationship are realized when specific model adequacy criteria are adopted. The question of response model residual evaluation is treated and certain practical aspects of response surface modeling are considered, including inference subspace truncation. A wind tunnel test plan developed by using the Modern Design of Experiments illustrates the advantages of an early estimate of data volume requirements. Comparisons are made with a representative One Factor At a Time (OFAT) wind tunnel test matrix developed to evaluate a surface to air missile.

DeLoach, Richard↗