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At least 289 records · Page 16

Entrainment and Optical Properties of an Elevated Canadian Forest Fire Plume Transported into the Planetary Boundary Layer near Washington, D.C.

Smoke and pollutants from Canadian forest fires were transported over the northeastern United States in July 2002. Lidar observations at the NASA Goddard Space Flight Center show the smoke from these fires arriving in an elevated plume that was subsequently mixed to the surface. Trajectory and three-dimensional model calculations confirm the origin of the smoke and show that it mixed to the surface after it was intercepted by the turbulent planetary boundary layer. Modeled smoke optical properties agreed well with aircraft and remote sensing observations provided coagulation of smoke particles was accounted for in the model. Our results have important implications for the long-range transport of pollutants and their subsequent entrainment to the surface, as well as the evolving optical properties of smoke from boreal forest fires.

Colarco, P. R.↗

Methods of Testing Thermal Insulation and Associated Test Apparatus

The system and method for testing thermal insulation uses a cryostatic insulation tester having a vacuum chamber and a cold mass including a test chamber and upper and lower guard chambers adjacent thereto. The thermal insulation is positioned within the vacuum chamber and adjacent the cold mass. Cryogenic liquid is supplied to the test chamber, upper guard and lower guard to create a first gas layer in an upper portion of the lower guard chamber and a second gas layer in an upper portion of the test chamber. Temperature are sensed within the vacuum chamber to test the thermal insulation.

Fesmire, James E.↗

Detail Enhancement of AIRS/AMSU Temperature and Moisture Profiles Using a 3D Deep Neural Network

In recent decades, spaceborne microwave and hyperspectral infrared sounding instruments have significantly benefited weather forecasting and climate science. However, existing retrievals of lower troposphere temperature and humidity profiles have limitations in vertical resolution, and often cannot accurately represent key features such as the mixed layer thermodynamic structure and the inversion at the planetary boundary layer (PBL) top. Because of the existing limitations in PBL remote sensing from space, there is a compelling need to improve routine, global observations of the PBL and enable advances in scientific understanding and weather and climate prediction. To address this, we have developed a new 3D deep neural network (DNN) which enhances detail and reduces noise in Level 2 granules of temperature and humidity profiles from the Atmospheric Infrared Sounder (AIRS)/Advanced Microwave Sounding Unit (AMSU) sounder instruments aboard NASA’s Aqua spacecraft. We show that the enhancement improves accuracy and detail including key features such as capping inversions at the top of the PBL over land, resulting in improved accuracy in estimations of PBL height.

Adam B Milstein↗

The Mixed-Phase Arctic Cloud Experiment (M-PACE)

The Mixed-Phase Arctic Cloud Experiment (M-PACE) was conducted September 27 through October 22, 2004 on the North Slope of Alaska. The primary objective was to collect a data set suitable to study interactions between microphysics, dynamics and radiative transfer in mixed-phase Arctic clouds. Observations taken during the 1997/1998 Surface Heat and Energy Budget of the Arctic (SHEBA) experiment revealed that Arctic clouds frequently consist of one (or more) liquid layers precipitating ice. M-PACE sought to investigate the physical processes of these clouds utilizing two aircraft (an in situ aircraft to characterize the microphysical properties of the clouds and a remote sensing aircraft to constraint the upwelling radiation) over the Department of Energy s Atmospheric Radiation Measurement (ARM) Climate Research Facility (ACRF) on the North Slope of Alaska. The measurements successfully documented the microphysical structure of Arctic mixed-phase clouds, with multiple in situ profiles collected in both single-layer and multi-layer clouds over two ground-based remote sensing sites. Liquid was found in clouds with temperatures down to -30 C, the coldest cloud top temperature below -40 C sampled by the aircraft. Remote sensing instruments suggest that ice was present in low concentrations, mostly concentrated in precipitation shafts, although there are indications of light ice precipitation present below the optically thick single-layer clouds. The prevalence of liquid down to these low temperatures could potentially be explained by the relatively low measured ice nuclei concentrations.

Verlinde, J.↗

Remote sensing of ocean color from aircraft

Over 3000 ocean spectra of sunlight backscattered from the upper layers of the sea have been obtained at flight altitudes to 10,000 feet together with detailed ground truth. These spectra are from stations which include a wide range of water masses differing as to biological and physical condition. This data bank and the analysis already performed demonstrates the probable feasibility of using ocean color as a parameter to locate areas of special significance to physical oceanographers and marine biologists from aircraft and satellites.

Clarke, G. L.↗

A Tower-based Prototype VHF/UHF Radar for Subsurface Sensing: System Description and Data Inversion Results

Knowledge of subsurface characteristics such as permittivity variations and layering structure could provide a breakthrough in many terrestrial and planetary science disciplines. For Earth science, knowledge of subsurface and subcanopy soil moisture layers can enable the estimation of vertical flow in the soil column linking surface hydrologic processes with that in the subsurface. For planetary science, determining the existence of subsurface water and ice is regarded as one of the most critical information needs for the study of the origins of the solar system. The subsurface in general can be described as several near-parallel layers with rough interfaces. Each homogenous rough layer can be defined by its average thickness, permittivity, and rms interface roughness assuming a known surface spectral distribution. As the number and depth of layers increase, the number of measurements needed to invert for the layer unknowns also increases, and deeper penetration capability would be required. To nondestructively calculate the characteristics of the rough layers, a multifrequency polarimetric radar backscattering approach can be used. One such system is that we have developed for data prototyping of the Microwave Observatory of Subcanopy and Subsurface (MOSS) mission concept. A tower-mounted radar makes backscattering measurements at VHF, UHF, and L-band frequencies. The radar is a pulsed CW system, which uses the same wideband antenna to transmit and receive the signals at all three frequencies. To focus the beam at various incidence angles within the beamwidth of the antenna, the tower is moved vertically and measurements made at each position. The signals are coherently summed to achieve focusing and image formation in the subsurface. This requires an estimate of wave velocity profiles. To solve the inverse scattering problem for subsurface velocity profile simultaneously with radar focusing, we use an iterative technique based on a forward numerical solution of the layered rough surface problem. The layers are each defined in terms of a small number of unknown distributions as given above. An a priori estimate of the solution is first assumed, based on which the forward problem is solved for the backscattered measurements. This is compared with the measured data and using iterative techniques an update to the solution for the unknowns is calculated. The process continues until convergence is achieved. Numerical results will be shown using actual radar data acquired with the MOSS tower radar system in Arizona in Fall 2003, and compared with in-situ measurements.

Moghaddam, Mahta↗

Comparisons of Bispectral and Polarimetric Retrievals of Marine Boundary Layer Cloud Microphysics: Case Studies Using a LES-Satellite Retrieval Simulator

Many passive remote-sensing techniques have been developed to retrieve cloud microphysical properties from satellite-based sensors, with the most common approaches being the bispectral and polarimetric techniques. These two vastly different retrieval techniques have been implemented for a variety of polar-orbiting and geostationary satellite platforms, providing global climatological data sets. Prior instrument comparison studies have shown that there are systematic differences between the droplet size retrieval products (effective radius) of bispectral (e.g., MODIS, Moderate Resolution Imaging Spectroradiometer) and polarimetric (e.g., POLDER, Polarization and Directionality of Earth's Reflectances) instruments. However, intercomparisons of airborne bispectral and polarimetric instruments have yielded results that do not appear to be systematically biased relative to one another. Diagnosing this discrepancy is complicated, because it is often difficult for instrument intercomparison studies to isolate differences between retrieval technique sensitivities and specific instrumental differences such as calibration and atmospheric correction. In addition to these technical differences the polarimetric retrieval is also sensitive to the dispersion of the droplet size distribution (effective variance), which could influence the interpretation of the droplet size retrieval. To avoid these instrument-dependent complications, this study makes use of a cloud remote-sensing retrieval simulator. Created by coupling a large-eddy simulation (LES) cloud model with a 1-D radiative transfer model, the simulator serves as a test bed for understanding differences between bispectral and polarimetric retrievals. With the help of this simulator we can not only compare the two techniques to one another (retrieval intercomparison) but also validate retrievals directly against the LES cloud properties. Using the satellite retrieval simulator, we are able to verify that at high spatial resolution (50 m) the bispectral and polarimetric retrievals are highly correlated with one another within expected observational uncertainties. The relatively small systematic biases at high spatial resolution can be attributed to different sensitivity limitations of the two retrievals. In contrast, a systematic difference between the two retrievals emerges at coarser resolution. This bias largely stems from differences related to sensitivity of the two retrievals to unresolved inhomogeneities in effective variance and optical thickness. The influence of coarse angular resolution is found to increase uncertainty in the polarimetric retrieval but generally maintains a constant mean value.

Miller, Daniel J.↗

Microchemical and Gaseous Sensors Using Carbon Nanotubes and MEMS Fabrication Technology

The objective of this research is to use a combination of carbon nanotubes and silicon-based microfabrication and micromachining processes to produce unique micro-sized chemical and gaseous sensors. Polished quartz substrate is used. Interdigitated structure is used for the sensing elements. Metallic catalysts for the growth of the carbon nanotube include copper, iron, nickel, and cobalt. Various thicknesses of the metallic catalysts are used in this study varying between 5 to 20 microns. Depositing of the metallic catalyst is accomplished using an ion-beam sputtering thin film technique and a shadow mask. Single wall carbon nanotubes are successfully formed over the metallic catalyst layer. Preliminary measurements of the carbon nanotubes show this nanotube contained film over the sensing elements which had a resistance value of 400 ohms at room temperature. This is a more conductive film comparing to metal oxide films, such as SnO2 or ZnO, that are now widely used in gaseous sensor research. Evaluation of the carbon nanotube film for potential gaseous sensing will be carried out.

Liu, Chung-Chiun↗

Converting Soil Moisture Observations to Effective Values for Improved Validation of Remotely Sensed Soil Moisture

We compare soil moisture retrieved with an inverse algorithm with observations of mean moisture in the 0-6 cm soil layer. A significant discrepancy is noted between the retrieved and observed moisture. Using emitting depth functions as weighting functions to convert the observed mean moisture to observed effective moisture removes nearly one-half of the discrepancy noted. This result has important implications in remote sensing validation studies.

Laymon, Charles A.↗

An Ultra-Wideband, Microwave Radar for Measuring Snow Thickness on Sea Ice and Mapping Near-Surface Internal Layers in Polar Firn

Sea ice is generally covered with snow, which can vary in thickness from a few centimeters to >1 m. Snow cover acts as a thermal insulator modulating the heat exchange between the ocean and the atmosphere, and it impacts sea-ice growth rates and overall thickness, a key indicator of climate change in polar regions. Snow depth is required to estimate sea-ice thickness using freeboard measurements made with satellite altimeters. The snow cover also acts as a mechanical load that depresses ice freeboard (snow and ice above sea level). Freeboard depression can result in flooding of the snow/ice interface and the formation of a thick slush layer, particularly in the Antarctic sea-ice cover. The Center for Remote Sensing of Ice Sheets (CReSIS) has developed an ultra-wideband, microwave radar capable of operation on long-endurance aircraft to characterize the thickness of snow over sea ice. The low-power, 100mW signal is swept from 2 to 8GHz allowing the air/snow and snow/ ice interfaces to be mapped with 5 c range resolution in snow; this is an improvement over the original system that worked from 2 to 6.5 GHz. From 2009 to 2012, CReSIS successfully operated the radar on the NASA P-3B and DC-8 aircraft to collect data on snow-covered sea ice in the Arctic and Antarctic for NASA Operation IceBridge. The radar was found capable of snow depth retrievals ranging from 10cm to >1 m. We also demonstrated that this radar can be used to map near-surface internal layers in polar firn with fine range resolution. Here we describe the instrument design, characteristics and performance of the radar.

Snow Cover↗

EGIS - An Environmental GIS Developed for NASA Field Center Applications

As the principal center for Environmental Geographic Information Systems (EGIS), the John C. Stennis Space Center (SSC), located in Hancock County, Mississippi, has been assigned technical support requirements to design and to implement a basic EGIS data base for all NASA Field Centers. The intent of this Phase I effort is to produce a baseline EGIS data base incorporating newly available remotely sensed data as well as existing environmental data. A example application of the use of the data base at Stennis Space Center will be to illustrate baseline environmental conditions for consideration with proposed propulsion test stand development and operation. To effectively answer questions related to environmental issues at each center, organization of the data layers and sources will include the following categories: Cadastral/Geodetic; Geopolitical; Hydrography; Infrastructure; Physical Geography; Socioeconomic; Remote Sensing Imagery; Associated Metadata. As part of a Phase II effort, site-specific data and applications will be implemented and added to the data base at each Field Center. This poster illustrates the framework of the design and implementation of a basic EGIS data base. Shown are example data sources, hardware and software, and data base delivery and installation. The poster also depicts future recommendations for a centrally located server to house each of the NASA Field Center data bases. The server will allow real-time data base updates with additional layers and models for each center. Expansion of the EGIS data base will continue to grow as site-specific applications are developed addressing the ongoing evolution of environmental concerns at all NASA Field Centers.

Smoot, James↗

Hierarchical modeling for image classification

As part of the California Integrated Remote Sensing System's (CIRSS) San Bernardino County Project, the use of data layers from a geographic information system (GIS) as an integral part of the Landsat image classification process was investigated. Through a hierarchical modeling technique, elevation, aspect, land use, vegetation, and growth management data from the project's data base were used to guide class labeling decisions in a 1976 Landsat MSS land cover classification. A similar model, incorporating 1976-1979 Landsat spectral change data in addition to other data base elements, was used in the classification of a 1979 Landsat image. The resultant Landsat products were integrated as additional layers into the data base for use in growth management, fire hazard, and hydrological modeling.

Likens, W.↗

Observations of marine stratocumulus clouds during FIRE

The First International Satellite Cloud Climatology Project Regional Experiment (FIRE) to study extensive fields of stratocumulus clouds off the coast of California is presented. Measurements on the regional and detailed local scales were taken, allowing for a wide interpretation of the mean, turbulent, microphysical, radiative, and chemical characteristics of stratocumulus. Multiple aircraft and ground-based remote-sensing systems were used to study the time evolution of the boundary layer structure over a three-week period, and probes from tethered balloons were used to measure turbulence and to collect cloud-microphysical and cloud-radiative data. The observations provide a base for studying the generation maintenance and dissipation of stratocumulus clouds, and could aid in developing numerical models and improved methods for retrieving cloud properties by satellite.

Albrecht, Bruce A.↗

Evaluation of Terms in the Water Vapor Budget Using Airborne Dial and In Situ Measurements from the Southern Great Plans 1997 Experiment

The Southern Great Plains (SGP97) field experiment was conducted in Oklahoma during June and July 1997 primarily to validate soil moisture retrieval algorithms using microwave radiometer measurements from aircraft as well as in situ surface measurements. One important objective of the SGP97 experiment plan was to examine the effect of soil moisture on the evolution of the atmospheric boundary layer (ABL) and clouds over the Southern Great Plains during the warm season. To support boundary layer studies during SGP97. the NASA Langley Research Center's Lidar Atmospheric Sensing Experiment (LASE) was flown on a NASA-P3 aircraft in conjunction with the Electronically Scanned Thinned Array Radiometer (ESTAR). The LASE instrument is an airborne, downward-looking differential absorption lidar (DIAL) system capable of measuring water vapor concentration as well as aerosol backscatter with high horizontal and vertical resolution in the ABL. Here, we will demonstrate how the LASE data can be used to determine water vapor statistics and most of the water vapor budget terms in the ABL. This information can then be related to spatial variations in soil moisture and the surface energy budget. The extensive surface and aircraft in situ measurements conducted during SGP97 provide information on the ABL that cannot be retrieved from the LASE data alone and also offer an excellent opportunity to validate the remote water vapor budget measurements with LASE.

Senff, Christoph J.↗

Two-Axis Direct Fluid Shear Stress Sensor for Aerodynamic Applications

This miniature or micro-sized semiconductor sensor design provides direct, nonintrusive measurement of skin friction or wall shear stress in fluid flow situations in a two-axis configuration. The sensor is fabricated by microelectromechanical system (MEMS) technology, enabling small size and multiple, low-cost reproductions. The sensors may be fabricated by bonding a sensing element wafer to a fluid-coupling element wafer. Using this layered machine structure provides a truly three-dimensional device.

Bajikar, Sateesh S.↗

Protocol Sensing Across Multiple Space Missions

In this work, we present sensing performance using an architecture for a reconfigurable protocol chip for spacebased applications. Toward utilizing the IP packet architecture, utilizing data link layer framing structures for multiplexed data on a channel are the targeted application considered for demonstration purposes. Specifically, we examine three common framing standards and present the sensing performance of these standards and their relative de-correlation metrics. Some analysis is performed to investigate the impact of lossy links and on the number of packets required to perform a decision with some probability. Finally, we present results on a demonstration platform that integrated reconfigurable sensing technology into the Ground Station Interface Device (GRID) for End-to-End IP demonstrations in space.

Ground Station Interface Device (GRID)↗

Reconfigurable Protocol Sensing in an End-to-End Demonstration

In this work, we present sensing performance using an architecture for a reconfigurable protocol chip for spacebased applications. Toward utilizing the IP packet architecture, utilizing data link layer framing structures for multiplexed data on a channel are the targeted application considered for demonstration purposes. Specifically, we examine three common framing standards and present the sensing performance of these standards and their relative de-correlation metrics. Some analysis is performed to investigate the impact of lossy links. Finally, we present results on a demonstration platform that integrated reconfigurable sensing technology into the Ground Station Interface Device (GRID) for End-to-End IP demonstrations in space.

space based applications↗