Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Land 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.

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

At least 1,405 records · Page 78
All sourcesNASA NTRSDOE OSTI
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↗
DOE OSTI2014

Bioenergy crop productivity and potential climate change mitigation from marginal lands in the United States: An ecosystem modeling perspective

Growing biomass feedstocks from marginal lands is becoming an increasingly attractive choice for producing biofuel as an alternative energy to fossil fuels. Here, we used a biogeochemical model at ecosystem scale to estimate crop productivity and greenhouse gas (GHG) emissions from bioenergy crops grown on marginal lands in the United States. Two broadly tested cellulosic crops, switchgrass, and Miscanthus, were assumed to be grown on the abandoned land and mixed crop–vegetation land with marginal productivity. Production of biomass and biofuel as well as net carbon exchange and nitrous oxide emissions were estimated in a spatially explicit manner. We found that, cellulosic crops, especially Miscanthus could produce a considerable amount of biomass, and the effective ethanol yield is high on these marginal lands. For every hectare of marginal land, switchgrass and Miscanthus could produce 1.0–2.3 kl and 2.9–6.9 kl ethanol, respectively, depending on nitrogen fertilization rate and biofuel conversion efficiency. Nationally, both crop systems act as net GHG sources. Switchgrass has high global warming intensity (100–390 g CO 2 eq l –1 ethanol), in terms of GHG emissions per unit ethanol produced. Miscanthus , however, emits only 21–36 g CO 2 eq to produce every liter of ethanol. To reach the mandated cellulosic ethanol target in the United States, growing Miscanthus on the marginal lands could potentially save land and reduce GHG emissions in comparison to growing switchgrass. Furthermore, the ecosystem modeling is still limited by data availability and model deficiencies, further efforts should be made to classify crop–specific marginal land availability, improve model structure, and better integrate ecosystem modeling into life cycle assessment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Representing surface heterogeneity in land–atmosphere coupling in E3SMv1 single-column model over ARM SGP during summertime

Abstract. The Earth's land surface features spatial and temporal heterogeneity over a wide range of scales below those resolved by current Earth system models (ESMs). State-of-the-art land and atmosphere models employ parameterizations to represent their subgrid heterogeneity, but the land–atmosphere coupling in ESMs typically operates on the grid scale. Communicating the information on the land surface heterogeneity with the overlying atmospheric boundary layer (ABL) remains a challenge in modeling land–atmosphere interactions. In order to account for the subgrid-scale heterogeneity in land–atmosphere coupling, we implement a new coupling scheme in the Energy Exascale Earth system model version 1 (E3SMv1) that uses adjusted surface variances and covariance of potential temperature and specific water content as the lower boundary condition for the atmosphere model. The new lower boundary condition accounts for both the variability of individual subgrid land surface patches and the inter-patch variability. The E3SMv1 single-column model (SCM) simulations over the Atmospheric Radiation Measurement (ARM) Southern Great Plain (SGP) site were performed to assess the impacts. We find that the new coupling parameterization increases the magnitude and diurnal cycle of the temperature variance and humidity variance in the lower ABL on non-precipitating days. The impacts are primarily attributed to subgrid inter-patch variability rather than the variability of individual patches. These effects extend vertically from the surface to several levels in the lower ABL on clear days. We also find that accounting for surface heterogeneity increases low cloud cover and liquid water path (LWP). These cloud changes are associated with the change in cloud regime indicated by the skewness of the probability density function (PDF) of the subgrid vertical velocity. In precipitating days, the inter-patch variability reduces significantly so that the impact of accounting for surface heterogeneity vanishes. These results highlight the importance of accounting for subgrid heterogeneity in land–atmosphere coupling in next-generation ESMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Comparing land surface temperature and mean radiant temperature for urban heat mapping in Philadelphia

Many cities are experiencing more frequent extreme heat during hot summers. With the rise of global temperature, the thermal comfort in urban areas become even worse. Quantitative information of the spatial distributions of urban heat has become increasingly important for resilience and adaptation to climate change in cities. This study compares satellite-derived land surface temperature (LST) and urban microclimate modeling-based mean radiant temperature (Tmrt) for mapping the urban heat distributions in Philadelphia, Pennsylvania, USA. Here, the LST was estimated based on Landsat 8 thermal imagery with a spatial resolution of around 100 m, while the Tmrt was simulated based on high resolution LiDAR and national aerial imagery program multispectral aerial imageries with a spatial resolution of 1 m. Result shows that both LST and Tmrt show a similar general pattern of the urban heat across the study area, while the Tmrt presents much more details of the heat variations street by street and neighborhood by neighborhood. The LST tends to have a stronger relationship with the Tmrt on building roofs, which are usually not the place for human activities. This studyprovides evidence for choosing more appropriate metrics in urban heat-related studies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A Multiscale Deep Learning Model for Soil Moisture Integrating Satellite and In Situ Data

Deep learning (DL) models trained on hydrologic observations can perform extraordinarily well, but they can inherit deficiencies of the training data, such as limited coverage of in situ data or low resolution/accuracy of satellite data. In this work, we propose a novel multiscale DL scheme learning simultaneously from satellite and in situ data to predict 9 km daily soil moisture (5 cm depth). Based on spatial cross-validation over sites in the conterminous United States, the multiscale scheme obtained a median correlation of 0.901 and root-mean-square error of 0.034 m 3 /m 3 . It outperformed the Soil Moisture Active Passive satellite mission's 9 km product, DL models trained on in situ data alone, and land surface models. Our 9 km product showed better accuracy than previous 1 km satellite downscaling products, highlighting limited impacts of improving resolution. Not only is our product useful for planning against floods, droughts, and pests, our scheme is generically applicable to geoscientific domains with data on multiple scales, breaking the confines of individual data sets.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1990

A propagation experiment for modelling high elevation angle land mobile satellite channels

This paper summarizes the results of a feasibility study for conducting high elevation angle propagation experiments in the European region for land mobile satellite communication. The study addresses various aspects of a proposed experiment. These include the selection of a suitable source for transmission, possibility of gathering narrow and wide band propagation data in various frequency bands, types of useful data, data acquisition technique, possible experimental configuration, and other experimental details.

Richharia, M.↗
NASA NTRS2000

Predictability of Seasonal Means in the NSIPP-1 AGCM

The predictability of seasonal means during 1980-99 is examined from 720 seasonal integrations with version 1 of NASA's Seasonal to Interanual Prediction Project (NSIPP-1) atmospheric general circulation model (AGCM). The AGCM is the atmospheric (and land) component of the NSIPP fully-coupled atmosphere-land-ocean model. For these runs, the initial atmospheric conditions are taken from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalyses, and sea surface temperatures and sea ice are specified from observations. Results from the northern winter integrations show that the model has a very realistic El Nino/Southern Oscillation (ENSO) response in both the tropics and extratropics. Early results from the northern summer runs show a robust extratropical ENSO response in the Southern Hemisphere Pacific, as well as, a pronounced zonally-symmetric component to the ENSO response in both hemispheres. Results will be presented at the meeting highlighting the seasonal evolution in predictability and skill of the NSIPP model on both global and regional scales. A further analysis of the zonally-symmetric response will be discussed in terms of its potential impact on the predictability of middle-latitude climate variability on seasonal to interannual time scales.

Schubert, Siegfried↗
NASA NTRS2000

Geopotential Model Improvement Using POCM_4B Dynamic Ocean Topography Information: PGM2000A

The two-year mean (1993-1994) Dynamic Ocean Topography (DOT) field implied by the POCM_4B circulation model was used to develop normal equations for DOT, in a surface spherical harmonic representation. These normal equations were combined with normal equations from satellite tracking data, surface gravity data, and altimeter data from TOPEX/Poseidon and ERS-1. Several least-squares combination solutions were developed in this fashion, by varying parameters such as the maximum degree of the estimated DOT and the relative weights of the different data. The solutions were evaluated in terms of orbit fit residuals, GPS/Leveling-derived undulations, and independent DOT information from in situ WOCE hydrographic data. An optimal solution was developed in this fashion which was originally presented at the 1998 EGS meeting in Nice, France. This model, designated here PGM2000A, maintains the orbit and land geoid modeling performance of EGM96, while improving its marine geoid modeling capability. In addition, PGM2000A's error spectrum is considerably more realistic than those of other contemporary gravitational models and agrees well with the error spectrum of EGM96. We will present the development and evaluation of PGM2000A, with particular emphasis on the weighting of the DOT information implied by POCM_4B. We will also present an inter-comparison of PGM2000A with the GRIM5-C1 and TEG-4 models. Directions for future work and problematic areas will be identified.

Pavlis, N. K.↗
NASA NTRS1998

A Modeling Approach to Global Land Surface Monitoring with Low Resolution Satellite Imaging

The effects of changing land use/land cover on global climate and ecosystems due to greenhouse gas emissions and changing energy and nutrient exchange rates are being addressed by federal programs such as NASA's Mission to Planet Earth (MTPE) and by international efforts such as the International Geosphere-Biosphere Program (IGBP). The quantification of these effects depends on accurate estimates of the global extent of critical land cover types such as fire scars in tropical savannas and ponds in Arctic tundra. To address the requirement for accurate areal estimates, methods for producing regional to global maps with satellite imagery are being developed. The only practical way to produce maps over large regions of the globe is with data of coarse spatial resolution, such as Advanced Very High Resolution Radiometer (AVHRR) weather satellite imagery at 1.1 km resolution or European Remote-Sensing Satellite (ERS) radar imagery at 100 m resolution. The accuracy of pixel counts as areal estimates is in doubt, especially for highly fragmented cover types such as fire scars and ponds. Efforts to improve areal estimates from coarse resolution maps have involved regression of apparent area from coarse data versus that from fine resolution in sample areas, but it has proven difficult to acquire sufficient fine scale data to develop the regression. A method for computing accurate estimates from coarse resolution maps using little or no fine data is therefore needed.

Hlavka, Christine A.↗
NASA NTRS2003

Runway Independent Aircraft Extremely Short Takeoff and Landing Regional Airliner: The Model 110

Airports throughout the United States are plagued with growing congestion. With the increase in air traffic predicted in the next few years, congestion will worsen. The accepted solution of building larger airplanes to carry more travelers is no longer a viable option, as airports are unable to accommodate larger aircraft without expensive infrastructure changes. Past NASA research has pointed to the need for a new approach, which can economically and safely utilize smaller airports. To study this option further, NASA requested the California Polytechnic State University at San Luis Obispo (Cal Poly/SLO) to design a baseline aircraft to be used for system studies. The requirements put forth by NASA are summarized. The design team was requested to create a demonstrator vehicle, which could be built without requiring enabling technology development. To this end, NASA requested that the tested and proven high-lift system of the Boeing C-17 Globemaster III be combined with the fuselage of the BAe-146. NASA also requested that Cal Poly determine the availability and usability of underutilized airports starting with California, then expanding if time and funds permitted to the U.S.

Hall, David W.↗