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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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116 records · Page 7
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NASA NTRS2014

Technology Development for 3-D Wide Swath Imaging Supporting ACE

The National Academy of Sciences Decadal Survey (DS) Aerosol-Cloud-Ecosystems Mission (ACE) aims to advance our ability to observe and predict changes to the Earth's hydrological cycle and energy balance in response to climate forcing, especially those changes associated with the effects of aerosol on clouds and precipitation. ACE is focused on obtaining measurements to reduce the uncertainties in current climate models arising from the lack in understanding of aerosol-cloud interactions. As part of the mission instrument suite, a dual-frequency radar comprised of a fixed-beam 94 gigahertz (W-band) radar and a wide-swath 35 gigahertz (Ka-band) imaging radar has been recommended by the ACE Science Working Group.In our 2010 Instrument Incubator Program project, we've developed a radar architecture that addresses the challenge associated with achieving the measurement objectives through an innovative, shared aperture antenna that allows dual-frequency radar operation while achieving wide-swath (100 kilometers) imaging at Ka-band. The antenna system incorporates 2 key technologies; a) a novel dual-band reflectorreflectarray and b) a Ka-band Active Electronically Scanned Array (AESA) feed module. The dual-band antenna is comprised of a primary cylindrical reflectorreflectarray surface illuminated by a point-focus W-band feed (compatible with a quasi-optical beam waveguide feed, such as that employed on CloudSat); the Ka-band AESA line feed provides wide-swath across-track scanning. The benefits of this shared-aperture approach include significant reductions in ACE satellite payload size, weight, and cost, as compared to a two aperture approach. Four objectives were addressed in our project. The first entailed developing the tools for the analysis and design of reflectarray antennas, assessment of candidate reflectarray elements, and validation using test coupons. The second objective was to develop a full-scale aperture design utilizing the reflectarray surface and to detail specific requirements and trades for the Ka-band AESA line feed. As part of the third objective a subscale antenna, similar to the full-scale aperture design, was developed, integrated, and flown with the Cloud Radar System during the 2014 Integrated Precipitation and Hydrology Experiment. The fourth and ongoing objective entails developing a GaN MMIC (Gallium Nitride Monolithic Microwave Integrated Circuits) power amplifier for use in the Ka-band AESA. An overview of the progress made on this project and a look ahead at the 2013 IIP (Instrument Incubator Program) award selection will be presented.

Antenna↗
NASA NTRS2014

Antenna Technology for 3-D Wide Swath Imaging Supporting ACE

A fundamental goal for the National Academy of Sciences Decadal Survey (DS) Aerosol-Cloud-Ecosystems Mission (ACE) is to advance our ability to observe and predict changes to the Earth's hydrological cycle and energy balance in response to climate forcing, especially those changes associated with the effects of aerosol on clouds and precipitation. ACE is focused on obtaining measurements to reduce the uncertainties in current climate models arising from the lack of understanding of aerosol-cloud interactions. As part of the mission instrument suite, the ACE Science Working Group has recommended a dual-frequency radar comprised of a fixed-beam 94 GHz (W-band) radar and a wide-swath 35 GHz (Ka-band) imaging radar. Our ACE radar architecture addresses the challenge associated with achieving the measurement objectives through an innovative, shared aperture antenna that allows dual-frequency radar operation while achieving wide-swath (>100 km) imaging at Ka-band. The antenna system incorporates 2 key technologies; a) a novel dual-band reflector/reflectarray and b) a Ka-band AESA feed module. The benefits of this shared-aperture approach include significant reductions in ACE satellite payload size, weight, and cost while enabling wide-swath imaging at Ka-band. This presentation describes the approach used to develop the reflectarray surface and plans for its TRL maturation.The dual-frequency antenna is comprised of a primary cylindrical reflector/reflectarray surface illuminated by a fixed W-band feed (compatible with a quasi-optical beam waveguide feed, such as that employed on CloudSat) and a Ka-band AESA line feed. The AESA feed design leverages state-of-the-art GaN transmit/receive (T/R) MMICs with high RF output power, high power added efficiency and low noise figure. The innovative reflectarray surface provides beam focusing at W-band, but it is transparent at Ka-band.

RAdar Antenna↗
NASA NTRS2006

Constellation Operations: Lessons Learned For Future Exploration

The Earth science community has long advocated placing numerous instruments in space to study the Earth and its environment. Space agencies from many countries have responded to this call with a wide range of orbiting satellites. Scientists also envisioned placing some satellites in constellations, to enable diverse remote sensing instruments to observe the same part of the Earth (or its atmosphere) at about the same time, thereby increasing the opportunities for coincident science observations. The Earth Science Afternoon Constellation is answering this call, but there have been unique challenges on the way to its deployment. Currently, the Afternoon Constellation is to comprise six satellites. Three are currently on orbit: NASA's Earth Observing System (EOS)-Aqua (2002) and EOS-Aura (2004), and CNES's Polarization & Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar (PARASOL) (2004). Two more satellites, the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) and Cloudsat, are to be jointly launched in late 2005, followed by the Orbiting Carbon Observatory (OCO) in 2008. The Afternoon Constellation is unlike most satellite constellations in that: 1) It is not a homogenous mix of identical satellites; rather it comprises several satellites with complementary observational capabilities; 2) The satellites are not spaced around the Earth to provide instantaneous, global coverage (as for a communications satellite constellation); rather they orbit in close proximity so observations occur at about the same time over approximately the same region; and 3) Lastly, the satellites are not managed and controlled by one organization; rather the list of organizations is diverse: CNES in France, NASA Centers at Goddard, Langley, and the Jet Propulsion Laboratory, and the US Air Force facility in New Mexico. The PARASOL launch and early orbit (L&EO) phase proved to be a learning experience for constellation members (including Constellation management). Prior to launch, all members signed an operations coordination document that spelled out basic requirements for keeping the constellation safe and resolving non-nominal events. Once PARASOL reached orbit and the mission teams gained experience using the newly-developed constellation monitoring tools, it became clear that some of the guidelines in the signed agreements had to be adjusted. This paper presents the L&EO lessons learned and how they were used to prepare for the next phase - the period following the CloudSat/CALIPSO launch.

Kelly, Angelita C.↗
NASA NTRS2009

WRF Simulations of the 20-22 January 2007 Snow Events over Eastern Canada: Comparison with In-Situ and Satellite Observations

One of the grand challenges of the Global Precipitation Measurement (GPM) mission is to improve cold season precipitation measurements in middle and high latitudes through the use of high-frequency passive microwave radiometry. For this, the Weather Research and Forecasting (WRF) model with the Goddard microphysics scheme is coupled with a satellite data simulation unit (WRF-SDSU) that has been developed to facilitate over-land snowfall retrieval algorithms by providing a virtual cloud library and microwave brightness temperature (Tb) measurements consistent with the GPM Microwave Imager (GMI). This study tested the Goddard cloud microphysics scheme in WRF for two snowstorm events, a lake effect and a synoptic event, that occurred between 20 and 22 January 2007 over the Canadian CloudSAT/CALIPSO Validation Project (C3VP) site in Ontario, Canada. The 24h-accumulated snowfall predicted by the WRF model with the Goddard microphysics was comparable to the observed accumulated snowfall by the ground-based radar for both events. The model correctly predicted the onset and ending of both snow events at the CARE site. WRF simulations capture the basic cloud properties as seen by the ground-based radar and satellite (i.e., CloudSAT, AMSU-B) observations as well as the observed cloud streak organization in the lake event. This latter result reveals that WRF was able to capture the cloud macro-structure reasonably well.

Shi, J. J.↗
NASA NTRS2008

Air Quality Study Using Satellites - Current Capability and Future Plans

Satellite instruments have had great success in monitoring the stratospheric ozone and in understanding the processes that control its daily to decadal scale variations. This field is now reaching its zenith with a number of satellite instruments from the US, Europe and Canada capping several decades of active research in this field. The primary public policy imperative of this research was to make reliable prediction of increases in biologically active surface UV radiation due to human activity. By contrast retrieval from satellite data of atmospheric constituents and photo-chemically active radiation that affect air quality is a new and growing field that is presenting us with unique challenges in measurement and data interpretation. A key distinction compared to stratospheric sensors is the greatly enhanced role of clouds, aerosols, and surfaces (CAS) in determining the quality and quantity of useful data that is available for air quality research. In our presentation we will use data from several sensors that are currently flying on the A-train satellite constellation, including OMI, MODIS, CLOUDSAT, and CALIPSO, to highlight that CAS can have both positive and negative effects on the information content of satellite measurements. This is in sharp contrast to other fields of remote sensing where CAS are usually considered an interference except in those cases when they are the primary subject of study. Our analysis has revealed that in the reflected wavelengths one often sees much further down into the atmosphere, through most cirrus, than one does in the emitted wavelengths. The lower level clouds provide a nice background against which one can track long-range transport of trace gases and aerosols. In addition, differences in trace gas columns estimated over cloudy and adjacent clear pixels can be used to measure boundary layer trace gases. However, in order to take full advantage of these features it will be necessary to greatly advance our understanding of how CAS affect the radiation at wavelengths that are used to derive the atmospheric constituents that affect air quality as well as the radiation that controls the photolysis of chemically active trace gases. We will discuss how we are using these new insights to design future satellite missions to study air quality.

Bhartia, Pawan K.↗
NASA NTRSDate not supplied

Improved Characterization of PSC Processes Derived from a Third-Generation CALIOP and MLS Detection and Composition Classification Algorithm

The new 3-year CloudSat and CALIPSO Science Team project described in this poster will use a unique combination of data from the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) instrument on CALIPSO and the Microwave Limb Sounder (MLS) on Aura, in conjunction with supporting meteorological information and detailed modeling studies, to advance our understanding of polar stratospheric cloud (PSC) processes and their role in ozone depletion. We will develop a third-generation (Gen3) PSC detection and composition algorithm that incorporates a new, more robust two-dimensional, multi-channel CALIOP feature detection scheme (2D-McDA). We will also devise and implement an improved two-dimensional PSC composition classification scheme that utilizes multiple parameters (e.g., CALIOP 532-nm parallel and perpendicular scattering ratios, CALIOP 1064-nm total scattering ratio, MLS HNO3 and H2O, ambient temperature, and temperature histories) in a Bayesian approach to determine the most likely PSC composition and help constrain solid PSC particle number density and size/shape. The combined CALIOP/MLS analyses will allow us to study in detail the full life cycle of PSCs and their resulting impact on gas-phase HNO3 and H2O, which should lead to improved parameterizations of PSC microphysics in global CCMs where detailed particle information is not available. The Gen3 CALIOP PSC algorithm will be a natural stepping-stone toward the analysis of data collected during future spaceborne lidar missions, such as NASA’s Atmosphere Observation System (AtmOS) mission currently scheduled for launch late in this decade. We will also investigate possible trends in PSC occurrence and composition over the entire CALIOP data record and through further comparisons with the Stratospheric Aerosol Measurement (SAM) II solar occultation PSC record from 1979-1989. Finally, we will validate the mountain-wave parameterization and PSC schemes used in the UM-UKCA (Unified Model coupled to the United Kingdom Chemistry and Aerosol module) chemistry-climate model through detailed comparisons with earlier CALIOP PSC data products and those developed under this proposal.

CALIPSO↗
NASA NTRSDate not supplied

Improved Characterization of PSC Processes Derived from a Third-Generation CALIOP and MLS Detection and Composition Classification Algorithm

The new 3-year CloudSat and CALIPSO Science Team project described in this poster will use a unique combination of data from the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) instrument on CALIPSO and the Microwave Limb Sounder (MLS) on Aura, in conjunction with supporting meteorological information and detailed modeling studies, to advance our understanding of polar stratospheric cloud (PSC) processes and their role in ozone depletion. We will develop a third-generation (Gen3) PSC detection and composition algorithm that incorporates a new, more robust two-dimensional, multi-channel CALIOP feature detection scheme (2D-McDA). We will also devise and implement an improved two-dimensional PSC composition classification scheme that utilizes multiple parameters (e.g., CALIOP 532-nm parallel and perpendicular scattering ratios, CALIOP 1064-nm total scattering ratio, MLS HNO3 and H2O, ambient temperature, and temperature histories) in a Bayesian approach to determine the most likely PSC composition and help constrain solid PSC particle number density and size/shape. The combined CALIOP/MLS analyses will allow us to study in detail the full life cycle of PSCs and their resulting impact on gas-phase HNO3 and H2O, which should lead to improved parameterizations of PSC microphysics in global chemistry-climate models (CCMs) where detailed particle information is not available. The Gen3 CALIOP PSC algorithm will be a natural stepping-stone toward the analysis of data collected during future spaceborne lidar missions, such as NASA’s Atmosphere Observation System (AOS) mission currently scheduled for launch late in this decade. We will also investigate possible trends in PSC occurrence and composition over the entire CALIOP data record and through further comparisons with the Stratospheric Aerosol Measurement (SAM) II solar occultation PSC record from 1979-1989. Finally, we will validate the mountain-wave parameterization and PSC schemes used in the UM-UKCA (Unified Model coupled to the United Kingdom Chemistry and Aerosol module) CCM through detailed comparisons with earlier CALIOP PSC data products and those developed under this proposal.

CALIPSO↗
DOE OSTI2024

Development of a Full-Scale Connected U-Net for Reflectivity Inpainting in Spaceborne Radar Blind Zones

CloudSat’s Cloud Profiling Radar is a valuable tool for remotely monitoring high-latitude snowfall, but its ability to observe hydrometeor activity near the Earth’s surface is limited by a radar blind zone caused by ground clutter contamination. This study presents the development of a deeply supervised U-Net-style convolutional neural network to predict cold season reflectivity profiles within the blind zone at two Arctic locations. The network learns to predict the presence and intensity of near-surface hydrometeors by coupling latent features encoded in blind zone-aloft clouds with additional context from collocated atmospheric state variables (i.e., temperature, specific humidity, and wind speed). Results show that the U-Net predictions outperform traditional linear extrapolation methods, with low mean absolute error, a 38% higher Sørensen–Dice coefficient, and vertical reflectivity distributions 60% closer to observed values. The U-Net is also able to detect the presence of near-surface cloud with a critical success index (CSI) of 72% and cases of shallow cumuliform snowfall and virga with 18% higher CSI values compared to linear methods. An explainability analysis shows that reflectivity information throughout the scene, especially at cloud edges and at the 1.2-km blind zone threshold, along with atmospheric state variables near the tropopause, are the most significant contributors to model skill. This surface-trained generative inpainting technique has the potential to enhance current and future remote sensing precipitation missions by providing a better understanding of the nonlinear relationship between blind zone reflectivity values and the surrounding atmospheric state.

54 ENVIRONMENTAL SCIENCES↗