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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Hydrologic models for land-atmosphere retrospective studies of the use of LANDSAT and AVHRR data

The use of a Geographic Information System (GIS) and LANDSAT analysis in conjunction with the Simulator for Water Resources on a Rural Basin (SWRRB) hydrologic model to examine the water balance on the Little Washita River basin is discussed. LANDSAT analysis was used to divide the basin into eight non-contiguous land covers or subareas: rangeland, grazed range, winter wheat, alfalfa/pasture, bare soil, water, woodland, and impervious land (roads, quarry). The use of a geographic information system allowed for the calculation of SWRRB model parameters in each subarea. Four data sets were constructed in order to compare SWRRB estimates of hydrologic processes using two methods of maximum LAI and two methods of watershed subdivision. Maximum LAI was determined from a continental scale map, which provided a value of 4.5 for the entire basin, and from its association with the type of land-cover (eight values). The two methods of watershed subdivision were determined according to drainage subbasin (four) and the eight land-covers. These data sets were used with the SWRRB model to obtain daily hydrologic estimates for 1985. The results of the one year analysis lead to the conclusion that the greater homogeneity of a land-cover subdivision provides better water yield estimates than those based on a drainage properties subdivision.

Duchon, Claude E.↗
NASA NTRS1993

Propagation model for the Land Mobile Satellite channel in urban environments

This paper presents the major characteristics of a simulation package capable of performing a complete narrow and wideband analysis of the mobile satellite communication channel in urban environments for any given orbital configuration. The wavelength-to-average urban geometrical dimension ratio has required the use of the Geometrical Theory of Diffraction (GTD). For the RF frequency range, the model has been designed to be (1 up to 60 GHz) extended to include effects of non-perfect conductivity and surface roughness. Taking advantage of the inherent capabilities of such a high frequency method, we are able to provide a complete description of the electromagnetic field at the mobile terminal. Using the information made available at the ray-tracer and GTD solver outputs, the Land Mobile Satellite (LMS) urban model can also give a detailed description of the communication channel in terms of power delay profiles, Doppler spectra, channel scattering functions, and so forth. Statistical data, e.g. cumulative distribution functions, level crossing rates or distributions of fades are also provided. The user can access the simulation tool through a Design-CAD user-friendly interface by means of which she can effectively design her own urban layout and run consequently all the envisaged routines. The software is optimized in its execution time so that numerous runs can be achieved in a considerably short time.

Sforza, M.↗
NASA NTRS1995

Narrowband land mobile satellite channel modeling

The subject of this paper is the development of a generalized analog model for the narrowband Land Mobile Satellite Channel (LMSC). It is based on the model proposed by Lutz, the 3-dimensional scattering model of Aulin and the multipath interference simulation method proposed by Jakes. Statistical tests of the simulated data show excellent agreement with the expected distributions whereas the power spectrum predicted by Aulin is duplicated in a discrete manner.

Kanatas, A. G.↗
NASA NTRS2008

Global Precipitation Measurement (GPM) Ground Validation (GV) Science Implementation Plan

For pre-launch algorithm development and post-launch product evaluation Global Precipitation Measurement (GPM) Ground Validation (GV) goes beyond direct comparisons of surface rain rates between ground and satellite measurements to provide the means for improving retrieval algorithms and model applications.Three approaches to GPM GV include direct statistical validation (at the surface), precipitation physics validation (in a vertical columns), and integrated science validation (4-dimensional). These three approaches support five themes: core satellite error characterization; constellation satellites validation; development of physical models of snow, cloud water, and mixed phase; development of cloud-resolving model (CRM) and land-surface models to bridge observations and algorithms; and, development of coupled CRM-land surface modeling for basin-scale water budget studies and natural hazard prediction. This presentation describes the implementation of these approaches.

Petersen, Walter A.↗
NASA NTRS2003

Simulation of the Onset of the Southeast Asian Monsoon During 1997 and 1998: The Impact of Surface Processes

The onset of the southeast Asian monsoon during 1997 and 1998 was simulated with a coupled mesoscale atmospheric model (MM5) and a detailed land surface model. The rainfall results from the simulations were compared with observed satellite data fiom the TRMM (Tropical Rainfall Measuring Mission) TMI (TRMM Microwave Imager) and GPCP (Global Precipitation Climatology Project). The simulation with the land surface model captured basic signatures of the monsoon onset processes and associated rainfall statistics. The sensitivity tests indicated that land surface processes had a greater impact on the simulated rainfall results than that of a small sea surface temperature change during the onset period. In both the 1997 and 1998 cases, the simulations were significantly improved by including the land surface processes. The results indicated that land surface processes played an important role in modifying the low-level wind field over two major branches of the circulation; the southwest low-level flow over the Indo- China peninsula and the northern cold front intrusion from southern China. The surface sensible and latent heat exchange between the land and atmosphere modified the lowlevel temperature distribution and gradient, and therefore the low-level. The more realistic forcing of the sensible and latent heat from the detailed land surface model improved the monsoon rainfall and associated wind simulation.

Wang, Yansen↗
NASA NTRS1988

Hydrologic models for land-atmosphere retrospective studies of the use of LANDSAT and AVHRR data

The use of a Geographic Information System (GIS) and LANDSAT analysis in conjunction with the Simulator for Water Resources on a Rural Basin (SWRRB) hydrologic model to examine the water balance on the Little Washita River basin is discussed. In the research completed to date LANDSAT analysis was used to divide the basin into eight non-contiguous land covers or sub areas. The use of a geographic informatin system allowed for the calculation of SWRRB model parameters in each subarea. Four data sets were constructed in order to compare SWRRB estimates of hydrologic processes using two methods of maximum LAI and two methods of watershed division. These data sets were used with the SWRRB model to obtain daily hydrologic estimates for 1985.

Duchon, Claude E.↗
NASA NTRS2021

Assimilation of SMAP Brightness Temperature Observations in the GEOS Land–Atmosphere Data Assimilation System

Errors in soil moisture adversely impact the modeling of land–atmosphere water and energy fluxes and, consequently, near-surface atmospheric conditions in atmospheric data assimilation systems (ADAS). To mitigate such errors, a land surface analysis is included in many such systems, although not yet in the currently operational NASA Goddard Earth Observing System (GEOS) ADAS. This article investigates the assimilation of L-band brightness temperature (Tb) observations from the Soil Moisture Active Passive (SMAP) mission in the GEOS weakly coupled land–atmosphere data assimilation system (LADAS) during boreal summer 2017. The SMAP Tb analysis improves the correlation of LADAS surface and root-zone soil moisture versus in situ measurements by ∼0.1–0.26 over that of ADAS estimates; the unbiased root-mean-square error of LADAS soil moisture is reduced by 0.002–0.008 m^3 /m^3 from that of ADAS. Furthermore, the global land average RMSE versus in situ measurements of screen-level air specific humidity (q2m) and daily maximum temperature (T2m_max ) is reduced by 0.05 g/kg and 0.04 K, respectively, for LADAS compared to ADAS estimates. Regionally, the RMSE of LADAS q2m and T2m_max is improved by up to 0.4 g/kg and 0.3 K, respectively. Improvement in LADAS specific humidity extends into the lower troposphere (below ∼700 mb), with relative improvements in bias of 15–25%, although LADAS air temperature bias slightly increases relative to that of ADAS. Finally, the root mean square of the LADAS Tb observation-minus-forecast residuals is smaller by up to ∼0.1 K than in a land-only assimilation system, corroborating the positive impact of the Tb analysis on the modeled land–atmosphere coupling.

microwave remote sensing↗
NASA NTRS2016

SMAP Data Assimilation at NASA SPoRT

The NASA Short-Term Prediction Research and Transition (SPoRT) Center maintains a near-real- time run of the Noah Land Surface Model within the Land Information System (LIS) at 3-km resolution. Soil moisture products from this model are used by several NOAA/National Weather Service Weather Forecast Offices for flood and drought situational awareness. We have implemented assimilation of soil moisture retrievals from the Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active/ Passive (SMAP) satellites, and are now evaluating the SMAP assimilation. The SMAP-enhanced LIS product is planned for public release by October 2016.

soil mositure↗
NASA NTRS2024

Dust Model Sensitivity to Dust Source Mask, Sandblasting Efficiency, Air Density, and Land Use: Implications for Model Improvement

This study compares dust storm simulations using two commonly adopted methods for representing four important dust emission parameters. Compared to a dynamic dust source mask based on land use and vegetation cover, a static mask based solely on land use overestimates dust concentration and optical depth by a factor of 2, besides generating spurious emissions. The results reinforce that seasonal variations in vegetation cover can significantly affect dust emissions. For sandblasting efficiency, a clay-dependent semiempirical expression produces 10 times more dust than a physics-based expression. Simulations using model-predicted versus a fixed constant for air density differ by only 8%. However, this difference could range between 12 and 22% for annual simulations over global dust source regions. Simulations with updated versus old land use data, using the same dust source mask, differ twofold, indicating the significant impact of land use change on regional dust emission in central Arizona. The differences in the pairs of these simulations are generally larger than the uncertainty due to meteorology. The simulations align better with observation when using the dynamic dust source mask, the physics-based sandblasting efficiency, and the up-to-date land use data. Given the high sensitivity of dust to surface conditions, the results discussed have implications for improving the dust cycle in weather and climate models and for interpreting model intercomparisons.

Dust-emission source↗
NASA NTRS2014

Assessing the Utility of 3-km Land Information System Soil Moisture Data for Drought Monitoring and Hydrologic Applications

The NASA Short term Prediction Research and Transition (SPoRT) Center in Huntsville, AL has been running a real-time configuration of the Noah land surface model within the NASA Land Information System (LIS) since June 2010. The SPoRT LIS version is run as a stand-alone land surface model over a Southeast Continental U.S. domain with 3-km grid spacing. The LIS contains output variables including soil moisture and temperature at various depths, skin temperature, surface heat fluxes, storm surface runoff, and green vegetation fraction (GVF). The GVF represents another real-time SPoRT product, which is derived from the Moderate Resolution Imaging Spectroradiometer instrument aboard NASA's Aqua and Terra satellites. These data have demonstrated operational utility for drought monitoring and hydrologic applications at the National Weather Service (NWS) office in Huntsville, AL since early 2011. The most relevant data for these applications have proven to be the moisture availability (%) in the 0-10 cm and 0-200 cm layers, and the volumetric soil moisture (%) in the 0-10 cm layer. In an effort to better understand their applicability among locations with different terrain, soil and vegetation types, SPoRT is conducting the first formal assessment of these data at NWS offices in Houston, TX, Huntsville, AL and Raleigh, NC during summer 2014. The goal of this assessment is to evaluate the LIS output in the context of assessing flood risk and determining drought designations for the U.S. Drought Monitor. Forecasters will provide formal feedback via a survey question web portal, in addition to the NASA SPoRT blog. In this presentation, the SPoRT LIS and its applications at NWS offices will be presented, along with information about the summer assessment, including training module development and preliminary results.

White, Kristopher D.↗
NASA NTRS1999

Satellite Derived Land Surface Temperature for Model Assimilation

Studies have shown that land surface temperature (LST) tendencies are sensitive to the surface moisture availability which is a function of soil moisture and vegetation. The assimilation of satellite derived LST tendencies into the surface energy budget of mesoscale models has shown promise in improving the representation of the complex effects of both soil moisture and vegetation within the models for short term simulations. LST derived from geostationary satellites has the potential of providing the temporal and spatial resolution needed for an LST assimilation process. This paper presents an analysis comparing the LST derived from GOES-8 infrared measurements with LST calculated by the MM5 numerical model. The satellite derived LSTs are calculated using a physical split window approach using channels 4 and 5 of GOES-8. The differences in the LST data sets, especially the tendencies, are presented and examined. Quantifying the differences between the data sets provide insight of possible weaknesses in the model parameterizations affecting the surface energy budget calculations and an indication of the potential effectiveness o f assimilating LST into the models.

Suggs, Ronnie J.↗
NASA NTRS2015

A Framework for the Cross-Sectoral Integration of Multi-Model Impact Projections: Land Use Decisions Under Climate Impacts Uncertainties

Climate change and its impacts already pose considerable challenges for societies that will further increase with global warming (IPCC, 2014a, b). Uncertainties of the climatic response to greenhouse gas emissions include the potential passing of large-scale tipping points (e.g. Lenton et al., 2008; Levermann et al., 2012; Schellnhuber, 2010) and changes in extreme meteorological events (Field et al., 2012) with complex impacts on societies (Hallegatte et al., 2013). Thus climate change mitigation is considered a necessary societal response for avoiding uncontrollable impacts (Conference of the Parties, 2010). On the other hand, large-scale climate change mitigation itself implies fundamental changes in, for example, the global energy system. The associated challenges come on top of others that derive from equally important ethical imperatives like the fulfilment of increasing food demand that may draw on the same resources. For example, ensuring food security for a growing population may require an expansion of cropland, thereby reducing natural carbon sinks or the area available for bio-energy production. So far, available studies addressing this problem have relied on individual impact models, ignoring uncertainty in crop model and biome model projections. Here, we propose a probabilistic decision framework that allows for an evaluation of agricultural management and mitigation options in a multi-impactmodel setting. Based on simulations generated within the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), we outline how cross-sectorally consistent multi-model impact simulations could be used to generate the information required for robust decision making. Using an illustrative future land use pattern, we discuss the trade-off between potential gains in crop production and associated losses in natural carbon sinks in the new multiple crop- and biome-model setting. In addition, crop and water model simulations are combined to explore irrigation increases as one possible measure of agricultural intensification that could limit the expansion of cropland required in response to climate change and growing food demand. This example shows that current impact model uncertainties pose an important challenge to long-term mitigation planning and must not be ignored in long-term strategic decision making

farmlands↗
NASA NTRS1992

Land surface interaction

The topics covered include the following: land and climate modeling; sensitivity studies; the process of a land model; model-specific parameterizations; water stress; within-canopy resistances; partial vegetation; canopy temperature; and present experience with a land model coupled to a general circulation model.

Dickinson, Robert E.↗
NASA NTRS2021

Expanding the application of soil moisture monitoring systems through regression-based transformation

Relative to other geophysical variables, soil moisture (SM) estimates derived from land surface models (LSMs) and land data assimilation systems (LDAS) are difficult to transfer between platforms and applications. This difficulty stems from the highly model-dependent nature of LSM SM estimates and differences in the vertical support of discretized SM values. As a result, operational SM estimates generated by one LSM (or LDAS) cannot generally be directly applied to a hydrologic monitoring or forecast system designed around a second LSM. This lack of transferability is particularly problematic for LDAS applications, where the time, expertise, and computational resources required to generate an operational LDAS analysis cannot be practically duplicated for every LSM-specific application. Here, we develop a set of simple regression tools for translating SM estimates between LSMs and multiple LDAS analyses. Results demonstrate that simple multivariate linear regression - utilizing independent variables based on multi-layer and temporally lagged SM estimates - can significantly improve upon baseline transformation approaches using direct percentile matching. The proposed regression approaches are effective for both the LSM-to-LSM and LDAS-to-LDAS transformation of multi-layer SM percentiles. Application of this approach will expand the utility of existing, high-quality (but LSM-specific) operational sources of SM information like the NASA Soil Moisture Active Passive Level-4 Soil Moisture product.

Soil Moisture↗
NASA NTRS2018

Impacts of Land Carbon Flux Variability on Variations in Atmospheric CO2

To better understand the role of atmospheric CO2 in the global carbon cycle, it is important to understand the factors that control its variability in time and space. Here we investigate these factors using a coupled land-atmosphere modeling system (the NASA GEOS-5 model) fitted with land carbon physics and atmospheric CO2 transport. To separate the influences of land carbon flux variability and atmospheric transport variability on the variability of CO2 concentrations, we conducted two carbon-fitted GEOS-5 AGCM simulations run in replay mode (a technique that guides the model's weather to match that of the MERRA-2 reanalysis): (i) a control simulation of 15-year carbon cycle dynamics and climate, and (ii) a simulation in which the climatological seasonal cycles of net biosphere production (NBP), as determined from diagnostics produced in the control experiment, are applied at the surface to the atmosphere instead. The impact of land flux variability on atmospheric CO2 variability is then isolated by subtracting the variability inherent in the second simulation (as induced, e.g., by strong El Nino conditions) from that in the control. These results are also presented in the context of supplemental simulations that have examined the impact of imposed drought in a free running AGCM simulation on carbon fluxes and atmospheric CO2 variability.

Lee, Eunjee↗
NASA NTRS1976

A model study of landing mat subjected to C-5A loadings

The 1.22 x 1.37 m mat runway in the standard brick pattern with transverse hinged joints is more stable and less susceptible to a buckling failure than the 0.60 x 2.74 m mat runway. Use of tension anchors appears to be a feasible means of controlling longitudinal displacement of the runway and potential runway buckling. Anchors appear to be a practical means to reduce maintenance on mat runways. The 1.22 x 1.37 m mat in the alternate brick pattern or the 90 deg rotated standard brick pattern forms a dynamically more stable runway with a high resistance to buckling failure. The runway in these patterns is much stiffer and longitudinal movement was less than for the standard brick pattern. The model 1.22 x 1.37 m alternate brick pattern runway was difficult to assemble and extremely difficult to take apart.

Blotter, P. T.↗