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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Deriving cloud droplet number concentration from surface-based remote sensors with an emphasis on lidar measurements

Abstract. Given the importance of constraining cloud droplet number concentrations (Nd) in low-level clouds, we explore two methods for retrieving Nd from surface-based remote sensing that emphasize the information content in lidar measurements. Because Nd is the zeroth moment of the droplet size distribution (DSD), and all remote sensing approaches respond to DSD moments that are at least 2 orders of magnitude greater than the zeroth moment, deriving Nd from remote sensing measurements has significant uncertainty. At minimum, such algorithms require the extrapolation of information from two other measurements that respond to different moments of the DSD. Lidar, for instance, is sensitive to the second moment (cross-sectional area) of the DSD, while other measures from microwave sensors respond to higher-order moments. We develop methods using a simple lidar forward model that demonstrates that the depth to the maximum in lidar-attenuated backscatter (Rmax⁡) is strongly sensitive to Nd when some measure of the liquid water content vertical profile is given or assumed. Knowledge of Rmax⁡ to within 5 m can constrain Nd to within several tens of percent. However, operational lidar networks provide vertical resolutions of > 15 m, making a direct calculation of Nd from Rmax⁡ very uncertain. Therefore, we develop a Bayesian optimal estimation algorithm that brings additional information to the inversion such as lidar-derived extinction and radar reflectivity near the cloud top. This statistical approach provides reasonable characterizations of Nd and effective radius (re) to within approximately a factor of 2 and 30 %, respectively. By comparing surface-derived cloud properties with MODIS satellite and aircraft data collected during the MARCUS and CAPRICORN II campaigns, we demonstrate the utility of the methodology.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1991

Analyses of the lunar surface with advanced remote sensors: Expectations for the 1990's

Today's advanced sensor capabilities provide unprecedented opportunities for exploration that mesh well with the science requirements for a sophisticated integration of several types of remotely acquired information. Science priorities for the 1990's include an evaluation of the global composition and structure of the primordial lunar crust in order to model its origin and evolution, using the Moon as a natural laboratory to study the impact process and time-cumulative events at 1 AU, and, ultimately, constraining the origin of the Moon and its relation to Earth.

Pieters, Carle M.↗
NASA NTRS1972

Applications of remote sensor data to geologic and economic analysis on the Bonanza Test Site, Colorado

Recent studies conducted in the Bonanza Test Site, Colorado, area indicated that: (1) more geologic structural information is available from remote sensing data than from conventional techniques; (2) greater accuracy results from using remote sensing data; (3) all major structural features were detected; (4) of all structural interpretations, about 75% were correct; and (5) interpretation of remote sensing data will not supplant field work, but it enables field work to be done much more efficiently.

Reeves, R. G.↗
NASA NTRS1972

The use of remote sensors to relate biological and physical indicators to environmental and public health problems

Relationships between biological, ecological and botanical structures, and disease organisms and their vectors which might be detected and measured by remote sensing are determined. In addition to the use of trees as indicators of disease or potential disease, an attempt is made to identify environmental factors such as soil moisture and soil and water temperatures as they relate to disease or health problems and may be detected by remote sensing. The following three diseases and one major health problem are examined: Malaria, Rocky Mountain spotted fever, Encephalitis and Red Tide. It is shown that no single species of vascular plant nor any one environmental factor can be used as the indicator of disease or health problems. Entire vegetation types, successional stages and combinations of factors must be used.

Source record↗
NASA NTRS1974

Interpretation of air pollution data as measured by an airborne remote sensor

The investigation described is a continuation of the work reported by Smith et al. (1974) in which a single source was studied. In the current study, multiple sources of known location are considered. The study is concerned with the strength of each source and the resulting pollution concentration field. The characteristics of the remotely sensed data are discussed along with the parameter estimation procedure, the estimation of pollution parameters, and a numerical example.

Smith, G. L.↗
NASA NTRS2012

The Physics of Imaging with Remote Sensors : Photon State Space & Radiative Transfer

Standard (mono-pixel/steady-source) retrieval methodology is reaching its fundamental limit with access to multi-angle/multi-spectral photo- polarimetry. Next... Two emerging new classes of retrieval algorithm worth nurturing: multi-pixel time-domain Wave-radiometry transition regimes, and more... Cross-fertilization with bio-medical imaging. Physics-based remote sensing: - What is "photon state space?" - What is "radiative transfer?" - Is "the end" in sight? Two wide-open frontiers! center dot Examples (with variations.

clouds↗
NASA NTRS1985

Computerized data reduction techniques for nadir viewing remote sensors

Computer resources have been developed for the analysis and reduction of MAPS experimental data from the OSTA-1 payload. The MAPS Research Project is concerned with the measurement of the global distribution of mid-tropospheric carbon monoxide. The measurement technique for the MAPS instrument is based on non-dispersive gas filter radiometer operating in the nadir viewing mode. The MAPS experiment has two passive remote sensing instruments, the prototype instrument which is used to measure tropospheric air pollution from aircraft platforms and the third generation (OSTA) instrument which is used to measure carbon monoxide in the mid and upper troposphere from space platforms. Extensive effort was also expended in support of the MAPS/OSTA-3 shuttle flight. Specific capabilities and resources developed are discussed.

Tiwari, S. N.↗
DOE OSTI2025

A large-eddy simulation exploration of the assumptions used in retrieving entrainment from a mixing diagram approach with ground-based remote sensors

Entrainment is a crucial component of the atmospheric boundary layer (BL) moisture and heat budget. While usually thought of as only entrainment flux, entrainment within the mixed layer budget equation is really composed of two terms: the flux of a property across the boundary separating the BL from the free troposphere and the change in the concentration of a property as the depth of the BL changes. In a recent study, Wakefield et al. (2023) used ground-based remote-sensing observations to estimate entrainment flux as the residual of a mixing diagram framework that was applied to the daytime convective boundary layer. This present work uses large-eddy simulation (LES) to examine how well this residual assumption for entrainment fluxes alone compares to the actual sum of those two entrainment terms derived from spatial averages of the LES output. We highlight the importance of the second entrainment term in closing the mixed layer budget and show that the residual assumption does not represent entrainment flux only but rather a total entrainment term when the boundary layer depth is changing.

Rosenberger, Tessa E. [Cleveland State Univ., Clev↗
NASA NTRS1973

Application of remote sensor data to geologic analysis of the Bonanza Test Site Colorado

A geologic map of the Bonanza Test Site is nearing completion. Using published large scale geologic maps from various sources, the geology of the area is being compiled on a base scaled at 1:250,000. Sources of previously published geologic mapping include: (1) USGS Bulletins; (2) professional papers and geologic quadrangle maps; (3) Bureau of Mines reports; (4) Colorado School of Mines quarterlies; and (5) Rocky Mountain Association of Geologist Guidebooks. This compilation will be used to evaluate ERTS, Skylab, and remote sensing underflight data.

Lee, K.↗
NASA NTRS2008

The Development of a Remote Sensor System and Decision Support Systems Architecture to Monitor Resistance Development in Transgenic Crops

The United States Environmental Protection Agency (EPA) has declared that "significant benefits accrue to growers, the public, and the environment" from the use of transgenic pesticidal crops due to reductions in pesticide usage for crop pest management. Large increases in the global use of transgenic pesticidal crops has reduced the amounts of broad spectrum pesticides used to manage pest populations, improved yield and reduced the environmental impact of crop management. A significant threat to the continued use of this technology is the evolution of resistance in insect pest populations to the insecticidal Bt toxins expressed by the plants. Management of transgenic pesticidal crops with an emphasis on conservation of Bt toxicity in field populations of insect pests is important to the future of sustainable agriculture. A vital component of this transgenic pesticidal crop management is establishing the proof of concept basic understanding, situational awareness, and monitoring and decision support system tools for more than 133650 square kilometers (33 million acres) of bio-engineered corn and cotton for development of insect resistance . Early and recent joint NASA, US EPA and ITD remote imagery flights and ground based field experiments have provided very promising research results that will potentially address future requirements for crop management capabilities.

Cacas, Joseph↗