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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

Coupled Model Simulation of Snowfall Events Over the Black Hills

Although many long-term simulations of snow accumulation and oblation have been made using stand-alone land surface models and surface models coupled with GCMs, less research has focused on short-term event simulations. Actually, accurate event simulations of snow-related processes are the basis for successful long-term simulation. Three advantages of event simulations of snowfall and snow melting are availability of: (1) intensive observation data from field experiments for validation; (2) more physically-realistic precipitation schemes for use in atmospheric models to simulate snowfall; and (3) a more detailed analysis of the snow melting processes. In addition to the complexities of snow related processes themselves, terrain-induced effects on snowfall/snow melting make simulations of snow events more difficult. Climatological observations indicate that terrain features such as the Black Hills of South Dakota and Wyoming can exert important effects on snow accumulation and snow oblation processes. One of the primary effects is that the orography causes forced uplift of airflow and causes atmospheric waves to form both upwind and downwind of it. Airflow often splits around the obstacle, converging on the lee side. This convergence may lead to precipitation enhancement. It also provides an elevated heat and moisture source that enhances atmospheric instability. During the period of April 5-May 5, 1999, the Upper Missouri River Basin Pilot Project (UMRBPP) made intensive observations on precipitation events occurring in the Black Hills. Two moderate snowfall events were captured during the period. The resulting high temporal and spatial resolution data provides opportunities to investigate terrain effects on snowfall amount, distribution, and melting. Successful simulation of snowfall amount, distribution, and evolution using atmospheric models is important to subsequent modeling of snow melting using snow sub-models in land surface schemes. In this paper, a coupled model system, consisting of an atmosphere model (ARPS) and a land-surface model (revised NCAR LSM), is used to simulate one of these UMRBPP cases.

Wang, Jianzhong↗
NASA NTRS2001

A Numerical Study of Tropical Sea-Air Interactions Using a Cloud Resolving Model Coupled with an Ocean Mixed-Layer Model

Coupling a cloud resolving model (CRM) with an ocean mixed layer (OML) model can provide a powerful tool for better understanding impacts of atmospheric precipitation on sea surface temperature (SST) and salinity. The objective of this study is twofold. First, by using the three dimensional (3-D) CRM-simulated (the Goddard Cumulus Ensemble model, GCE) diabatic source terms, radiation (longwave and shortwave), surface fluxes (sensible and latent heat, and wind stress), and precipitation as input for the OML model, the respective impact of individual component on upper ocean heat and salt budgets are investigated. Secondly, a two-way air-sea interaction between tropical atmospheric climates (involving atmospheric radiative-convective processes) and upper ocean boundary layer is also examined using a coupled two dimensional (2-D) GCE and OML model. Results presented here, however, only involve the first aspect. Complete results will be presented at the conference.

Shie, Chung-Lin↗
NASA NTRS2011

Evaluation of the Event Driven Phenology Model Coupled with the VegET Evapotranspiration Model Through Comparisons with Reference Datasets in a Spatially Explicit Manner

A new model coupling scheme with remote sensing data assimilation was developed for estimation of daily actual evapotranspiration (ET). The scheme represents a mix of the VegET, a physically based model to estimate ET from a water balance, and an event driven phenology model (EDPM), where the EDPM is an empirically derived crop specific model capable of producing seasonal trajectories of canopy attributes. In this experiment, the scheme was deployed in a spatially explicit manner within the croplands of the Northern Great Plains. The evaluation was carried out using 2007-2009 land surface forcing data from the North American Land Data Assimilation System (NLDAS) and crop maps derived from remotely sensed data of NASA's Moderate Resolution Imaging Spectroradiometer (MODIS). We compared the canopy parameters produced by the phenology model with normalized difference vegetation index (NDVI) data derived from the MODIS nadir bi-directional reflectance distribution function (BRDF) adjusted reflectance (NBAR) product. The expectations of the EDPM performance in prognostic mode were met, producing determination coefficient (r2) of 0.8 +/-.0.15. Model estimates of NDVI yielded root mean square error (RMSE) of 0.1 +/-.0.035 for the entire study area. Retrospective correction of canopy dynamics with MODIS NDVI brought the errors down to just below 10% of observed data range. The ET estimates produced by the coupled scheme were compared with ones from the MODIS land product suite. The expected r2=0.7 +/-.15 and RMSE = 11.2 +/-.4 mm per 8 days were met and even exceeded by the coupling scheme0 functioning in both prognostic and retrospective modes. Minor setbacks of the EDPM and VegET performance (r2 about 0.5 and additional 30 % of RMSR) were found on the peripheries of the study area and attributed to the insufficient EDPM training and to spatially varying accuracy of crop maps. Overall the experiment provided sufficient evidence of soundness and robustness of the EDPM and VegET coupling scheme, assuring its potential for spatially explicit applications.

Kovalskyy, V.↗
NASA NTRS2006

Remote Sensing and Spatial Growth Modeling Coupled with Air Quality Modeling to Assess the Impact of Atlanta, Georgia on the Local and Regional Environment

The growth of cities, both in population and areal extent, appears as an inexorable process. Urbanization continues at a rapid rate, and it is estimated that by the year 2025, 80 percent of the world s population will live in cities. Directly aligned with the expansion of cities is urban sprawl. Urban expansion has profound impacts on a host of biophysical, environmental, and atmospheric processes. A reduction in air quality over cities is a major result of these impacts. Strategies that can be directly or indirectly implemented to help remediate air quality problems in cities and that can be accepted by political decision makers and the general public are now being explored to help bring down air pollutants and improve air quality. The urban landscape is inherently complex and this complexity is not adequately captured in air quality models, particularly the Community Multiscale Air Quality (CMAQ) model that is used to assess whether urban areas are in attainment of EPA air quality standards, primarily for ground level ozone. This inadequacy of the CMAQ model to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well the model predicts ozone pollutant levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban spatial growth modeling (SGM) projections as improved inputs to the meteorology component of the CMAQ model focusing on the Atlanta, Georgia metropolitan area as a case study. These growth projections include "business as usual" and "smart growth" scenarios out to 2030. The growth projections illustrate the effects of employing urban heat island mitigation strategies, such as increasing tree canopy and albedo across the Atlanta metro area, which in turn, are used to model how ozone and air temperature can potentially be moderated as impacts on elevating ground-level ozone, as opposed to not utilizing heat island mitigation strategies. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the (CMAQ) modeling schemes. Use of these data have been found to better characterize low density/suburban development as compared with USGS 1km land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission, the regional planning agency for the area. This allows the State Environmental Protection agency to evaluate how these transportation plans will affect future air quality. The coupled SGM and air quality modeling approach provides insight on what the impacts of Atlanta s growth will be on the local and regional environment and exists as a mechanism that can be used by policy makers to make rationale decisions on urban growth and sustainability for the metropolitan area in the future.

Quattrochi, Dale A.↗
NASA NTRS1993

Session on coupled atmospheric/chemistry coupled models

The session on coupled atmospheric/chemistry coupled models is reviewed. Current model limitations, current issues and critical unknowns, and modeling activity are addressed. Specific recommendations and experimental strategies on the following are given: multiscale surface layer - planetary boundary layer - chemical flux measurements; Eulerian budget study; and Langrangian experiment. Nonprecipitating cloud studies, organized convective systems, and aerosols - heterogenous chemistry are also discussed.

Thompson, Anne↗
NASA NTRS1993

Report of the proceedings of the Colloquium and Workshop on Multiscale Coupled Modeling

The Colloquium and Workshop on Multiscale Coupled Modeling was held for the purpose of addressing modeling issues of importance to planning for the Cooperative Multiscale Experiment (CME). The colloquium presentations attempted to assess the current ability of numerical models to accurately simulate the development and evolution of mesoscale cloud and precipitation systems and their cycling of water substance, energy, and trace species. The primary purpose of the workshop was to make specific recommendations for the improvement of mesoscale models prior to the CME, their coupling with cloud, cumulus ensemble, hydrology, air chemistry models, and the observational requirements to initialize and verify these models.

Koch, Steven E.↗
NASA NTRS2023

An Investigation into the Effect of Liquid Accumulation on Thermo-Physiologic State using an Advanced Moisture Model Coupled with a High Resolution Human Thermal Model

A physics-based mathematical model for simulating heat and moisture transport on the skin and within clothing was developed to improve the accuracy of human thermal modeling predictions. In a previous study, a set of sweating hotplate experiments was specifically created to obtain test data for model validation. The clothing moisture model was subsequently coupled with a human thermal model and tested by simulating human experiments described in the open literature, which served to verify the model’s ability to predict whole body thermo-physiologic state in work-rest cycles during which sweating was known to occur. In this study, a human subject test was specifically designed to validate the model’s ability to predict local and whole body sweat evaporation and accumulation on the surface of the body. The human subject test incorporated twelve clothed male subjects of moderate physical fitness, ages 18-30, which were prescribed a work-rest cycle in a climate-controlled chamber (25 °C, 50% RH). Two activity levels were considered during the active stage (4 MET vs. 6.5 MET), and two sets of ending ambient conditions were considered for the final rest stage (25 °C vs. 15 °C, 50% RH). Model predictions were compared to the measured local skin temperatures, core temperatures, and whole body sweat losses. In general, the model was able to reproduce the trends observed in the human subject trial, but more importantly, provided insight into how dynamic changes in liquid content can impact the evolution of local and whole body thermo-physiologic state. This study demonstrates the ability of an advanced moisture model to capture distinct physics attributable to moisture accumulation, allowing for increased accuracy in predicting human thermal state and for interpreting the results of measurements derived from human subject tests.

human thermal model↗
NASA NTRS1993

Session on validation of coupled models

The session on validation of coupled models is reviewed. The current use of a mesoscale model with a grid size of 20-km during STORM-FEST in 1992 has proven to be extremely valuable. The availability of forecast products at a much higher temporal and spatial resolution was very helpful for mesoscale forecasting, mission planning, and the guidance of research aircraft. Recent numerical simulation of ocean cyclones and mesoscsle convective systems using nonhydrostatic cloud/mesoscale models with a grid size as small as 2-km have demonstrated the potential of these models for predicting mesoscale convective systems, squall lines, hurricane rainbands, mesoscale gravity waves, and mesoscale frontal structures embedded within an extratropical cyclone. Although mesoscale/cloud scale models have demonstrated strong potential for use in operational forecasting, very limited quantitative evaluation (and verification) of these models were performed. As a result, the accuracy, the systematic biases, and the useful forecasts limits were not properly defined for these models. Also, no serious attempts were made to use these models for operational prediction of mesoscale convective systems.

Kuo, Bill↗
NASA NTRS1993

A preferential vibration dissociation coupling model for nonequilibrium flowfields

A preferential vibration-dissociation coupling model is incorporated into a radiatively coupled viscous shock laver code that also includes chemical, radiative, and thermal nonequilibrium. Stagnation point flow profiles are obtained for various Fire 2 flight conditions and for a typical 14 km/sec AOTV case, and comparisons are made with Fire 2 experimental data. Adjustments in molecular absorption coefficients are also made for several diatomic species. Based on comparisons with experimental data, very little preferential dissociation behavior is present in the Fire 2 flight conditions.

Mcgough, David E.↗
NASA NTRS2023

Investigating the Response of Land-Atmosphere Interactions and Feedbacks to Spatial Representation of Irrigation in a Coupled Modeling Framework

The transport of water, heat, and momentum from the surface to the atmosphere is dependent in part on the 10 characteristics of the land surface. Together with the model physics, parameterization schemes, and parameters employed, land datasets determine the spatial variability in land surface states (i.e., soil moisture and temperature) and fluxes. Despite the importance of these datasets, they are often chosen out of convenience or regional limitations without due assessment of their impacts on model results. Irrigation is an anthropogenic form of land heterogeneity that has been shown to alter the land surface energy balance, ambient weather, and local circulations. As such, irrigation schemes are becoming more 15 prevalent in weather and climate models with rapid developments in dataset availability and parameterization scheme complexity. Thus, to address pragmatic issues related to modeling irrigation, this study uses a high-resolution, regional coupled modeling system to investigate the impacts of irrigation dataset selection on land-atmosphere (L-A) coupling using a case study from the Great Plains Irrigation Experiment (GRAINEX) field campaign. The simulations are assessed in the context of irrigated versus non-irrigated regions, subregions across the irrigation gradient, and sub-grid scale process 20 representation in coarser scale models. The results show that L-A coupling is sensitive to the choice of irrigation dataset and resolution and that the irrigation impact on surface fluxes and near surface meteorology can be dominant, conditioned on the details of the irrigation map (i.e., boundaries, heterogeneity, etc), or minimal. A consistent finding across several analyses was that even a low percentage of irrigation fraction (i.e., 4-16%) can have significant local and downstream atmospheric impacts (e.g., lower PBL height), suggesting that representation of boundaries and heterogeneous areas within irrigated 25 regions is particularly important for the modeling of irrigation impacts on the atmosphere in this model. When viewing the simulations presented here as a proxy for ‘ideal’ tiling in a Earth System Model scale gridbox, the results show that some ‘tiles’ will reach critical nonlinear moisture and planetary boundary layer (PBL) thresholds that could be important for clouds and convection, implying that heterogeneity resulting from irrigation should be taken into consideration in new sub-grid land-atmosphere exchange parameterizations.

Patricia Lawston-Parker↗
NASA NTRS2021

Large-scale features of Last Interglacial climate: results from evaluating the lig127k simulations for the Coupled Model Intercomparison Project (CMIP6)–Paleoclimate Modeling Intercomparison Project (PMIP4)

The modeling of paleoclimate, using physically based tools, is increasingly seen as a strong out-of-sample test of the models that are used for the projection of future climate changes. New to the Coupled Model Intercomparison Project (CMIP6) is the Tier 1 Last Interglacial experiment for 127 000 years ago (lig127k), designed to address the climate responses to stronger orbital forcing than the midHolocene experiment, using the same state-of-the-art models as for the future and following a common experimental protocol. Here we present a first analysis of a multi-model ensemble of 17 climate models, all of which have completed the CMIP6 DECK (Diagnostic, Evaluation and Characterization of Klima) experiments. The equilibrium climate sensitivity (ECS) of these models varies from 1.8 to 5.6°C. The seasonal character of the insolation anomalies results in strong summer warming over the Northern Hemisphere continents in the lig127k ensemble as compared to the CMIP6 piControl and much-reduced minimum sea ice in the Arctic. The multi-model results indicate enhanced summer monsoonal precipitation in the Northern Hemisphere and reductions in the Southern Hemisphere. These responses are greater in the lig127k than the CMIP6 midHolocene simulations as expected from the larger insolation anomalies at 127 than 6 ka. New synthesis for surface temperature and precipitation, targeted for 127 ka, have been developed for comparison to the multi-model ensemble. The lig127k model ensemble and data reconstructions are in good agreement for summer temperature anomalies over Canada, Scandinavia, and the North Atlantic and for precipitation over the Northern Hemisphere continents. The model–data comparisons and mismatches point to further study of the sensitivity of the simulations to uncertainties in the boundary conditions and of the uncertainties and sparse coverage in current proxy reconstructions. The CMIP6–Paleoclimate Modeling Intercomparison Project (PMIP4) lig127k simulations, in combination with the proxy record, improve our confidence in future projections of monsoons, surface temperature, and Arctic sea ice, thus providing a key target for model evaluation and optimization.

Last Interglacial climate↗
NASA NTRS2014

Background Error Covariance Estimation using Information from a Single Model Trajectory with Application to Ocean Data Assimilation into the GEOS-5 Coupled Model

An attractive property of ensemble data assimilation methods is that they provide flow dependent background error covariance estimates which can be used to update fields of observed variables as well as fields of unobserved model variables. Two methods to estimate background error covariances are introduced which share the above property with ensemble data assimilation methods but do not involve the integration of multiple model trajectories. Instead, all the necessary covariance information is obtained from a single model integration. The Space Adaptive Forecast error Estimation (SAFE) algorithm estimates error covariances from the spatial distribution of model variables within a single state vector. The Flow Adaptive error Statistics from a Time series (FAST) method constructs an ensemble sampled from a moving window along a model trajectory. SAFE and FAST are applied to the assimilation of Argo temperature profiles into version 4.1 of the Modular Ocean Model (MOM4.1) coupled to the GEOS-5 atmospheric model and to the CICE sea ice model. The results are validated against unassimilated Argo salinity data. They show that SAFE and FAST are competitive with the ensemble optimal interpolation (EnOI) used by the Global Modeling and Assimilation Office (GMAO) to produce its ocean analysis. Because of their reduced cost, SAFE and FAST hold promise for high-resolution data assimilation applications.

Data Assimilation↗
NASA NTRS1993

Nonlinear unstable auroral-arc driven thermospheric winds in an ionosphere-magnetosphere coupled model

The nonlinear evolution of thermospheric winds in an ionosphere-magnetosphere coupled model has been studied for the first time for a dynamic unstable auroral-arc environment. We treat the problem using a multi-layer, quasi-three-dimensional model which averages in altitude the thermospheric dynamics over each layer. For the upper thermosphere, we find that (1) the thermosphere can respond to the ionospheric Kelvin-Helmholtz (KH) instability on temporal scales on the order of an hour, depending on ambient conditions, and on spatial scales of tens to hundreds of kilometers, (2) strong thermospheric meridional and zonal vortical flows with embedded nonlinear jet-like structures can be generated by the ionospheric/magnetospheric KH instability and (3) neutral thermospheric winds, vortices, and associated power spectra develop in a distinctly different manner in the presence of magnetospheric coupling effects. Comparison with recent observations is made.

Keskinen, M. J.↗
NASA NTRSDate not supplied

A11I-2104 Evaluation of the NASA GEOS Chemistry-Climate Model Coupled Atmosphere-Ocean Configuration for its Suitability to Simulations of Atmospheric Composition in a Changing Climate

The NASA Goddard Earth Observing System Chemistry-Climate Model (GEOSCCM) is a full tropospheric-stratospheric chemistry enabled configuration of the NASA GEOS Earth system model. Among the objectives for research performed with GEOSCCM is to understand the impacts of climate change on recovery of the stratospheric ozone layer over the twenty-first century. Simulations performed in the past with GEOSCCM did not have an interactive ocean and were driven with projected sea surface temperature and sea ice boundary conditions provided by external models. This method limits the application of GEOSCCM for climate study because it doesn’t allow the feedback of composition changes to ocean. For a full representation of the chemistry-climate feedbacks in the Earth System, we have developed a configuration of GEOSCCM that makes use of the MOM5 ocean general circulation model coupled to the GEOS atmospheric general circulation model. This configuration leverages development of the GEOS Sub-seasonal-to-Seasonal (S2S) prediction system, and includes interactive, radiatively coupled aerosols and two-moment, aerosol-aware cloud microphysics. W e have assessed the baseline model climate sensitivity with an Monday, 11 December 2023 08:30 - 12:50 Poster Hall A-C - South (Exhibition Level, South, MC) experiment performed under pre-industrial (e.g., year 1850) greenhouse gas conditions and a second experiment under 4xCO2 conditions, similar to the typical CMIP protocol. The GEOS model is demonstrated to have a climate sensitivity of a 2.6 K increase in global mean surface temperature for an equivalent doubling of CO2 from pre-industrial conditions, in line with current CMIP models. This configuration of the GEOS model is suitable for application to multidecadal to century-long simulations of climate system response to changing greenhouse gas levels. We report here our evaluation of the climate diagnostics of this configuration and discuss future directions for work with this model configuration, including an ongoing twenty-first century projection experiment based on the Chemistry-Climate Model Intercomparison project protocol.

models↗
NASA NTRS2010

Dynamics of Ring Current and Electric Fields in the Inner Magnetosphere During Disturbed Periods: CRCM-BATS-R-US Coupled Model

We present simulation results from a one-way coupled global MHD model (Block-Adaptive-Tree Solar-Wind Roe-Type Upwind Scheme, BATS-R-US) and kinetic ring current models (Comprehensive Ring Current Model, CRCM, and Fok Ring Current, FokRC). The BATS-R-US provides the CRCM/FokRC with magnetic field information and plasma density/temperature at the polar CRCM/FokRC boundary. The CRCM uses an electric potential from the BATS-R-US ionospheric solver at the polar CRCM boundary in order to calculate the electric field pattern consistent with the CRCM pressure distribution. The FokRC electric field potential is taken from BATS-R-US ionospheric solver everywhere in the modeled region, and the effect of Region II currents is neglected. We show that for an idealized case with southward-northward-southward Bz IMF turning, CRCM-BATS-R-US reproduces well known features of inner magnetosphere electrodynamics: strong/weak convection under the southward/northward Bz; electric field shielding/overshielding/penetration effects; an injection during the substorm development; Subauroral Ion Drift or Polarization Jet (SAID/PJ) signature in the dusk sector. Furthermore, we find for the idealized case that SAID/PJ forms during the substorm growth phase, and that substorm injection has its own structure of field-aligned currents which resembles a substorm current wedge. For an actual event (12 August 2000 storm), we calculate ENA emissions and compare with Imager for Magnetopause-to-Aurora Global Exploration/High Energy Neutral Atom data. The CRCM-BATS-R-US reproduces both the global morphology of ring current and the fine structure of ring current injection. The FokRC-BATS-R-US shows the effect of a realistic description of Region II currents in ring current-MHD coupled models.

Buzulukova, N.↗