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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

Impact of Urban Growth on Surface Climate: A Case Study in Oran, Algeria

We develop a land use map discriminating urban surfaces from other cover types over a semiarid region in North Africa and use it in a land surface model to assess the impact of urbanized land on surface energy, water and carbon balances. Unlike in temperate climates where urbanization creates a marked heat island effect, this effect is not strongly marked in semiarid regions. During summer, the urban class results in an additional warming of 1.45 C during daytime and 0.81 C at night compared to that simulated for needleleaf trees under similar climate conditions. Seasonal temperatures show urban areas warmer than their surrounding during summer and slightly cooler in winter. The hydrological cycle is practically "shut down" during summer and characterized by relatively large amount of runoff in winter. We estimate the annual amount of carbon uptake to 1.94 million metric tons with only 11.9% assimilated during the rainy season. However, if urbanization expands to reach 50% of the total area excluding forests, the annual total carbon uptake will decline by 35% and the July mean temperature would increase only 0.10 C, compared to current situation. In contrast, if urbanization expands to 50% of the total land excluding forests and croplands but all short vegetation is replaced by native broadleaf deciduous trees, the annual carbon uptake would increase 39% and the July mean temperature would decrease by 0.9 C, compared to current configuration. These results provide guidelines for urban planners and land use managers and indicate possibilities for mitigating the urban heat.

Bounoua, Lahouari↗
NASA NTRS2008

Modification of Roberts' Theory for Rocket Exhaust Plumes Eroding Lunar Soil

Roberts' model of lunar soil erosion beneath a landing rocket has been updated in several ways to predict the effects of future lunar landings. The model predicts, among other things, the number of divots that would result on surrounding hardware due to the impact of high velocity particulates, the amount and depth of surface material removed, the volume of ejected soil, its velocity, and the distance the particles travel on the Moon. The results are compared against measured results from the Apollo program and predictions are made for mitigating the spray around a future lunar outpost.

Metzger, Philip T.↗
NASA NTRS2018

AMSR2 Soil Moisture Downscaling Using Temperature and Vegetation Data

Soil moisture (SM) applications in terrestrial hydrology require higher spatial resolution soil moisture products than those provided by passive microwave remote sensing instruments (grid resolution of 9 km or larger). In this investigation, an innovative algorithm that uses visible/infrared remote sensing observations to downscale Advanced Microwave Scanning Radiometer 2 (AMSR2) coarse spatial resolution SM products was developed and implemented for use with data provided by the Advanced Microwave Scanning Radiometer 2 (AMSR2). The method is based on using the Normalized Difference Vegetation Index (NDVI) modulated relationships between day/night SM and temperature change at corresponding times. Land surface model output variables from the North America Land Data Assimilation System (NLDAS), remote sensing data from the Moderate-Resolution Imaging Spectroradiometer (MODIS), and Advanced Very High Resolution Radiometer (AVHRR) were used in this methodology. The functional relationships developed using NLDAS data at a grid resolution of 12.5 km were applied to downscale AMSR2 JAXA (Japan Aerospace Exploration Agency) SM product (25 km) using MODIS land surface temperature (LST) and NDVI observations (1 km) to produce the 1 km SM estimates. The downscaled SM estimates were validated by comparing them with ISMN (International Soil Moisture Network) in situ SM in the Black Bear-Red Rock watershed, central Oklahoma between 2015-2017. The overall statistical variables of the downscaled AMSR2 SM validation R2, slope, RMSE and bias, demonstrate good accuracy. The downscaled SM better characterized the spatial and temporal variability of SM at watershed scales than the original SM product.

AMSR2; passive microwave soil moisture; soil moist↗
NASA NTRS2019

Surface Flow Visualization of the High-Lift Common Research Model

A 10% scale version of the High-Lift Common Research Model (CRM-HL) was tested in the NASA Langley 14- by 22-Foot Subsonic Tunnel (14x22) in support of the NASA Advanced Air Transport Technology (AATT) Project. The CRM-HL experiment included various configurations such as conventional and simple-hinged flaps, with and without engine nacelle/pylon, with and without nacelle chine, different Active Flow Control (AFC) methods (sweeping jets, alternating pulsed jets, and preconditioned boundary layer blowing), and their various parameters. This particular study is focused on the surface flow visualization of the conventional CRM-HL model at landing configuration. The conventional CRM-HL model with the single-slotted Fowler flap system serves as a baseline for the AFC-enabled simplified high-lift configuration as well as a high-lift technology development platform due to its publicly open geometry. Surface flow visualizations were performed using fluorescent minitufts, which were found to be nonintrusive to the aerodynamic performance. Tuft flow visualizations are supplemented with the relevant pressure and force measurements in order to understand the flow characteristics developed on the conventional CRM- HL model. In addition, three dimensional, unsteady, compressible Computational Fluid Dynamic (CFD) simulations were performed for selective cases. The surface streamlines and transverse velocity fluctuations obtained by the CFD simulations are qualitatively compared to the tuft direction and tuft unsteadiness, respectively. Force measurements of the CRM-HL model show performance degradation at higher angles of attack. Surface flow visualizations revealed the performance loss due to the nacelle/pylon wake that grows with angle of attack and eventually promotes flow separation over the inboard wing. This performance loss was successfully recovered by placing a chine on the engine nacelle.

Koklu, Mehti↗
NASA NTRS2018

Benefits and Pitfalls of GRACE Terrestrial Water Storage Data Assimilation

Satellite observations of terrestrial water storage (TWS) from the Gravity Recovery and Climate Experiment (GRACE) mission have a coarse resolution in time (monthly) and space (roughly 150,000 sq km at midlatitudes) and vertically integrate all water storage components over land, including soil moisture and groundwater. Nonetheless, data assimilation can be used to horizontally downscale and vertically partition GRACE-TWS observations. This presentation illustrates some of the benefits and drawbacks of assimilating TWS observations from GRACE into a land surface model over the continental United States and India. The assimilation scheme yields improved skill metrics for groundwater compared to the no-assimilation simulations. A smaller impact is seen for surface and root-zone soil moisture. Further, GRACE observes TWS depletion associated with anthropogenic groundwater extraction. Results from the assimilation emphasize the importance of representing anthropogenic processes in land surface modeling and data assimilation systems.

TWS↗
NASA NTRS2016

Experimental Study of Wake / Flap Interaction Noise and the Reduction of Flap Side Edge Noise

The effects of the interaction of a wake with a half-span flap on radiated noise are examined. The incident wake is generated by bars of various widths and lengths or by a simplified landing gear model. Single microphone and phased array measurements are used to isolate the effects of the wake interaction on the noise radiating from the flap side edge and flap cove regions. The effects on noise of the wake generator's geometry and relative placement with respect to the flap are assessed. Placement of the wake generators upstream of the flap side edge is shown to lead to the reduction of flap side edge noise by introducing a velocity deficit and likely altering the instabilities in the flap side edge vortex system. Significant reduction in flap side edge noise is achieved with a bar positioned directly upstream of the flap side edge. The noise reduction benefit is seen to improve with increased bar width, length and proximity to the flap edge. Positioning of the landing gear model upstream of the flap side edge also leads to decreased flap side edge noise. In addition, flap cove noise levels are significantly lower than when the landing gear is positioned upstream of the flap mid-span. The impact of the local flow velocity on the noise radiating directly from the landing gear is discussed. The effects of the landing gear side-braces on flap side edge, flap cove and landing gear noise are shown.

Hutcheson, Florence V.↗
NASA NTRS2014

Evaluating LSM-Based Water Budgets Over a West African Basin Assisted with a River Routing Scheme

Within the framework of the African Monsoon Multidisciplinary Analysis (AMMA) Land Surface Model Intercomparison Project phase 2 (ALMIP-2), this study evaluates the water balance simulated by the Interactions between Soil, Biosphere, and Atmosphere (ISBA) over the upper Oum River basin, in Benin, using a mesoscale river routing scheme (RRS). The RRS is based on the nonlinear Muskingum Cunge method coupled with two linear reservoirs that simulate the time delay of both surface runoff and base flow that are produced by land surface models. On the basis of the evidence of a deep water-table recharge in that region,a reservoir representing the deep-water infiltration (DWI) is introduced. The hydrological processes of the basin are simulated for the 2005-08 AMMA field campaign period during which rainfall and stream flow data were intensively collected over the study area. Optimal RRS parameter sets were determined for three optimization experiments that were performed using daily stream flow at five gauges within the basin. Results demonstrate that the RRS simulates stream flow at all gauges with relative errors varying from -22% to 3% and Nash-Sutcliffe coefficients varying from 0.62 to 0.90. DWI varies from 24% to 67% of the base flow as a function of the sub-basin. The relatively simple reservoir DWI approach is quite robust, and further improvements would likely necessitate more complex solutions (e.g., considering seasonality and soil type in ISBA); thus, such modifications are recommended for future studies. Although the evaluation shows that the simulated stream flows are generally satisfactory, further field investigations are necessary to confirm some of the model assumptions.

Multidisciplinary↗
NASA NTRS1972

Land use mapping and modelling for the Phoenix quadrangle

The author has identified the following significant results. Experimentation with 70mm squares cut from ERTS-1 9.5 inch MSS positive transparencies in an I2S color additive viewer, a Richardson film production viewer at 10X magnification, and in a microfiche viewer at 12X and 18X magnification has indicated that band 5 photography provides the most useful interpretable data. In the I2S viewer high intensities of blue and red light in bands 4 and 6 respectively enhance faint vegetation patterns not easily detectable. Slides produced from 35mm color transparencies made by photographing the I2S viewing screen are suitable visual aids for use during presentation. Interpretation of MSS transparencies allowed compilation of a map of land use change in the Phoenix quadrangle.

Place, J. L.↗
NASA NTRS2011

Towards Improved Snow Water Equivalent Estimation via GRACE Assimilation

Passive microwave (e.g. AMSR-E) and visible spectrum (e.g. MODIS) measurements of snow states have been used in conjunction with land surface models to better characterize snow pack states, most notably snow water equivalent (SWE). However, both types of measurements have limitations. AMSR-E, for example, suffers a loss of information in deep/wet snow packs. Similarly, MODIS suffers a loss of temporal correlation information beyond the initial accumulation and final ablation phases of the snow season. Gravimetric measurements, on the other hand, do not suffer from these limitations. In this study, gravimetric measurements from the Gravity Recovery and Climate Experiment (GRACE) mission are used in a land surface model data assimilation (DA) framework to better characterize SWE in the Mackenzie River basin located in northern Canada. Comparisons are made against independent, ground-based SWE observations, state-of-the-art modeled SWE estimates, and independent, ground-based river discharge observations. Preliminary results suggest improved SWE estimates, including improved timing of the subsequent ablation and runoff of the snow pack. Additionally, use of the DA procedure can add vertical and horizontal resolution to the coarse-scale GRACE measurements as well as effectively downscale the measurements in time. Such findings offer the potential for better understanding of the hydrologic cycle in snow-dominated basins located in remote regions of the globe where ground-based observation collection if difficult, if not impossible. This information could ultimately lead to improved freshwater resource management in communities dependent on snow melt as well as a reduction in the uncertainty of river discharge into the Arctic Ocean.

Forman, Bart↗
NASA NTRS2010

The Contribution of Soil Moisture Information to Forecast Skill: Two Studies

This talk briefly describes two recent studies on the impact of soil moisture information on hydrological and meteorological prediction. While the studies utilize soil moisture derived from the integration of large-scale land surface models with observations-based meteorological data, the results directly illustrate the potential usefulness of satellite-derived soil moisture information (e.g., from SMOS and SMAP) for applications in prediction. The first study, the GEWEX- and ClIVAR-sponsored GLACE-2 project, quantifies the contribution of realistic soil moisture initialization to skill in subseasonal forecasts of precipitation and air temperature (out to two months). The multi-model study shows that soil moisture information does indeed contribute skill to the forecasts, particularly for air temperature, and particularly when the initial local soil moisture anomaly is large. Furthermore, the skill contributions tend to be larger where the soil moisture initialization is more accurate, as measured by the density of the observational network contributing to the initialization. The second study focuses on streamflow prediction. The relative contributions of snow and soil moisture initialization to skill in streamflow prediction at seasonal lead, in the absence of knowledge of meteorological anomalies during the forecast period, were quantified with several land surface models using uniquely designed numerical experiments and naturalized streamflow data covering mUltiple decades over the western United States. In several basins, accurate soil moisture initialization is found to contribute significant levels of predictive skill. Depending on the date of forecast issue, the contributions can be significant out to leads of six months. Both studies suggest that improvements in soil moisture initialization would lead to increases in predictive skill. The relevance of SMOS and SMAP satellite-based soil moisture information to prediction are discussed in the context of these studies.

Koster, Randal↗
NASA NTRS2013

Comparison of Four Precipitation Forcing Datasets in Land Information System Simulations over the Continental U.S.

The NASA Short ]term Prediction Research and Transition (SPoRT) Center in Huntsville, AL is running a real ]time configuration of the NASA Land Information System (LIS) with the Noah land surface model (LSM). Output from the SPoRT ]LIS run is used to initialize land surface variables for local modeling applications at select National Weather Service (NWS) partner offices, and can be displayed in decision support systems for situational awareness and drought monitoring. The SPoRT ]LIS is run over a domain covering the southern and eastern United States, fully nested within the National Centers for Environmental Prediction Stage IV precipitation analysis grid, which provides precipitation forcing to the offline LIS ]Noah runs. The SPoRT Center seeks to expand the real ]time LIS domain to the entire Continental U.S. (CONUS); however, geographical limitations with the Stage IV analysis product have inhibited this expansion. Therefore, a goal of this study is to test alternative precipitation forcing datasets that can enable the LIS expansion by improving upon the current geographical limitations of the Stage IV product. The four precipitation forcing datasets that are inter ]compared on a 4 ]km resolution CONUS domain include the Stage IV, an experimental GOES quantitative precipitation estimate (QPE) from NESDIS/STAR, the National Mosaic and QPE (NMQ) product from the National Severe Storms Laboratory, and the North American Land Data Assimilation System phase 2 (NLDAS ]2) analyses. The NLDAS ]2 dataset is used as the control run, with each of the other three datasets considered experimental runs compared against the control. The regional strengths, weaknesses, and biases of each precipitation analysis are identified relative to the NLDAS ]2 control in terms of accumulated precipitation pattern and amount, and the impacts on the subsequent LSM spin ]up simulations. The ultimate goal is to identify an alternative precipitation forcing dataset that can best support an expansion of the real ]time SPoRT ]LIS to a domain covering the entire CONUS.

Case, Jonathan L.↗
NASA NTRS1976

Model and full-scale large transport airframe noise

Results are presented for an airframe noise experiment intended to obtain airframe noise data of a 0.03-scale model of a large transport aircraft in a flow facility for comparison with similar airframe noise data from full-scale flyover tests of the same aircraft. The test model simulated the landing and cruise configuration, including individual flap systems. Considerable noise is found to be associated with the extension of the model's leading edge flap system and to be reduced across the noise spectra when the gaps between the leading-edge flaps and the leading edge of the wing are sealed. Amplitude and frequency scaling relationships are developed which correlate respective data for a variety of aircraft configurations. Normalized model landing gear noise failed to simulate full-scale data.

Shearin, J. G.↗
NASA NTRS2019

Soil Moisture Data Assimilation to Estimate Irrigation Water Use

Knowledge of irrigation is essential to support food security, manage depleting water resources, and comprehensively understand the global water and energy cycles. Despite the importance of understanding irrigation, little consistent information exists on the amount of water that is applied for irrigation. In this study, we develop and evaluate a new method to predict daily to seasonal irrigation magnitude using a particle batch smoother data assimilation approach, where land surface model soil moisture is applied in different configurations to understand how characteristics of remotely sensed soil moisture may impact the performance of the method. The study employs a suite of synthetic data assimilation experiments, allowing for systematic diagnosis of known error sources. Assimilation of daily synthetic soil moisture observations with zero noise produces irrigation estimates with a seasonal bias of 0.66% and a correlation of 0.95 relative to a known truth irrigation. When synthetic observations were subjected to an irregular overpass interval and random noise similar to the Soil Moisture Active Passive satellite (0.04 cm(exp 3) cm(exp -3)), irrigation estimates produced a median seasonal bias of <1% and a correlation of 0.69. When systematic biases commensurate with those between NLDAS‐2 land surface models and Soil Moisture Active Passive are imposed, irrigation estimates show larger biases. In this application, the particle batch smoother outperformed the particle filter. The presented framework has the potential to provide new information into irrigation magnitude over spatially continuous domains, yet its broad applicability is contingent upon identifying new method(s) of determining irrigation schedule and correcting biases between observed and simulated soil moisture, as these errors markedly degraded performance.

R Abolafia-Rosenzweig↗
NASA NTRS2011

Assimilation of Terrestrial Water Storage from GRACE in a Snow-Dominated Basin

Terrestrial water storage (TWS) information derived from Gravity Recovery and Climate Experiment (GRACE) measurements is assimilated into a land surface model over the Mackenzie River basin located in northwest Canada. Assimilation is conducted using an ensemble Kalman smoother (EnKS). Model estimates with and without assimilation are compared against independent observational data sets of snow water equivalent (SWE) and runoff. For SWE, modest improvements in mean difference (MD) and root mean squared difference (RMSD) are achieved as a result of the assimilation. No significant differences in temporal correlations of SWE resulted. Runoff statistics of MD remain relatively unchanged while RMSD statistics, in general, are improved in most of the sub-basins. Temporal correlations are degraded within the most upstream sub-basin, but are, in general, improved at the downstream locations, which are more representative of an integrated basin response. GRACE assimilation using an EnKS offers improvements in hydrologic state/flux estimation, though comparisons with observed runoff would be enhanced by the use of river routing and lake storage routines within the prognostic land surface model. Further, GRACE hydrology products would benefit from the inclusion of better constrained models of post-glacial rebound, which significantly affects GRACE estimates of interannual hydrologic variability in the Mackenzie River basin.

Forman, Barton A.↗
NASA NTRS2008

Ongoing Development of NASA's Global Land Data Assimilation System

NASA's Global Land Data Assimilation System (GLDAS) produces global fields of land surface states (e.g., soil moisture and temperature) and fluxes (e.g., latent heat flux and runoff) by driving offline land surface models with observation-based inputs, using the Land Information System (LIS) software. Since production began in 2001, GLDAS has supported more than 100 scientific investigations and applications. Some examples are GEWEX and NASA Energy and Water Cycle Study (NEWS) global water and energy budget analyses, interpretations of hydrologic data derived from the Gravity Recovery and Climate Experiment (GRACE) satellite mission, and forecast model initiation studies at NOAA and NASA. At the same time, the GLDAS team has continued improve results through the development of new modeling and data assimilation techniques. Here we describe several recent and ongoing innovations. These include global implementation of a runoff routing procedure, GRACE data assimilation, advanced snow cover assimilation, and irrigation modeling.

Rodell, Matthew↗