SEARCH · Engineering Papers

Results for “Cloud tracking”

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.

SourceResearch connectionFrom yearThrough year

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

1,043 records · Page 58

All sources NASA NTRS DOE OSTI

NASA NTRS2002

A Desorbed Gas Molecular Ionization Mechanism for Arcing Onset in Solar Arrays Immersed in a Low-Density Plasma

Previous experimental studies have hypothesized that the onset of Solar Array Arc (SAA) initiation in low-density space plasmas is caused by a desorbed gas molecular ionization mechanism. Indeed past investigations performed at the NASA Glenn Plasma Interaction Facility tend to not only support the desorbed gas molecular ionization mechanism, but have gone as far as identifying the crucial molecular species that must be present for molecular ion dominated process to occur. When electrical breakdown occurs at a triple junction site on a solar array panel, a quasi-neutral plasma cloud is ejected. Assuming the main component of the expelled plasma cloud by weight is due to water vapor, the fastest process available is due to HO molecules and OH(+) ions, or more succinctly, dissociative molecular-ion dominated recombination processes: H2O(+) + e(-) yields H* + OH*. Recently published spectroscopic observations of solar array arc spectra in ground tests have revealed the well-known molecular OH band (302 to 309nm), as well as the molecular SiH band (387nm peak), and the molecular CH band (432nm peak). Note that the OH band is observed in emission arcs where water vapor is present. Strong atomic lines were also observed for H(sub beta) at 486nm and H(sub alpha) at 656.3nm in prior ground testing. Independent supporting evidence of desorbed gas molecular ionization mechanisms also come from measurements of arc current pulse widths at different capacitances. We will revisit an earlier first order approximation demonstrating the dependence of arc current pulse widths on the square root of the capacitance. The simple arc current pulse width model will be then be used to estimate the temperature of the arc plasma (currently believed to be somewhere in the range of 3 to 5 eV). The current paper then seeks to extend the outlined work by including numerous vacuum chamber measurements obtained with a quadrupole mass spectrometer. A small solar array was mounted inside the vacuum chamber. A plasma source, also mounted inside the vacuum chamber, is used to simulate a low-density plasma environment. The solar array is then biased to a high negative potential and allowed to arc while a mass spectrometer is used to record the partial pressure of H2O and to track other significant changes in mass (1 to 150) AMU.

Galofaro, J.↗

NASA NTRS2014

ldentifying Episodes of Earth Science Phenomena Using a Big-Data Technology

A significant portion of Earth Science investigations is phenomenon- (or event-) based, such as the studies of Rossby waves, volcano eruptions, tsunamis, mesoscale convective systems, and tropical cyclones. However, except for a few high-impact phenomena, e.g. tropical cyclones, comprehensive records are absent for the occurrences or events of these phenomena. Phenomenon-based studies therefore often focus on a few prominent cases while the lesser ones are overlooked. Without an automated means to gather the events, comprehensive investigation of a phenomenon is at least time-consuming if not impossible. We have constructed a prototype Automated Event Service (AES) system that is used to methodically mine custom-defined events in the reanalysis data sets of atmospheric general circulation models. Our AES will enable researchers to specify their custom, numeric event criteria using a user-friendly web interface to search the reanalysis data sets. Moreover, we have included a social component to enable dynamic formation of collaboration groups for researchers to cooperate on event definitions of common interest and for the analysis of these events. An Earth Science event (ES event) is defined here as an episode of an Earth Science phenomenon (ES phenomenon). A cumulus cloud, a thunderstorm shower, a rogue wave, a tornado, an earthquake, a tsunami, a hurricane, or an El Nino, is each an episode of a named ES phenomenon, and, from the small and insignificant to the large and potent, all are examples of ES events. An ES event has a duration (often finite) and an associated geo-location as a function of time; it's therefore an entity embedded in four-dimensional (4D) spatiotemporal space. Earth Science phenomena with the potential to cause massive economic disruption or loss of life often rivet the attention of researchers. But, broader scientific curiosity also drives the study of phenomena that pose no immediate danger, such as land/sea breezes. Due to Earth System's intricate dynamics, we are continuously discovering novel ES phenomena. We generally gain understanding of a given phenomenon by observing and studying individual events. This process usually begins by identifying the occurrences of these events. Once representative events are identified or found, we must locate associated observed or simulated data prior to commencing analysis and concerted studies of the phenomenon. Knowledge concerning the phenomenon can accumulate only after analysis has started. However, as mentioned previously, comprehensive records only exist for a very limited set of high-impact phenomena; aside from these, finding events and locating associated data currently may take a prohibitive amount of time and effort on the part of an individual investigator. The reason for the lack of comprehensive records for most of the ES phenomena is mainly due to the perception that they do not pose immediate and/or severe threat to life and property. Thus they are not consistently tracked, monitored, and catalogued. Many phenomena even lack precise and/or commonly accepted criteria for definitions. Moreover, various Earth Science observations and data have accumulated to a previously unfathomable volume; NASA Earth Observing System Data Information System (EOSDIS) alone archives several petabytes (PB) of satellite remote sensing data, which are steadily increasing. All of these factors contribute to the difficulty of methodically identifying events corresponding to a given phenomenon and significantly impede systematic investigations. We have not only envisioned AES as an environment for identifying customdefined events but also aspired for it to be an interactive environment with quick turnaround time for revisions of query criteria and results, as well as a collaborative environment where geographically distributed experts may work together on the same phenomena. A Big Data technology is thus required for the realization of such a system. In the following, we first introduce the technology selected for AES in the next section. We then demonstrate the utility of AES using a use case, Blizzard, before we conclude.

Kuo, Kwo-Sen↗

NASA NTRSDate not supplied

Overview of NASA's Ocean Color Instrument Solar Calibration Architecture, Pre-Launch Tests and Preliminary On-Orbit Results

Launched in February 2024, the PACE mission represents NASA’s next investment in ocean biology, clouds, and aerosol data records. A key feature of PACE is the inclusion of an advanced satellite radiometer known as the Ocean Color Instrument (OCI), a global mapping radiometer that combines multispectral and hyperspectral remote sensing. Like its predecessors, OCI will provide two day global coverage of TOA radiances. Unlike its predecessors, OCI will cover a spectral range from 340nm to 2260nm. Below 900nm, OCI will include two spectrometers that continuously span the ultraviolet to 600nm and 600nm to near-infrared spectral regions to provide hyperspectral radiances sampled every 2.5 nm, with a bandwidth of 5 nm for each channel. Wavelengths above 900nm are measured in seven discrete multispectral bands of varying bandwidths, six of which are at similar wavelengths to those on heritage missions to support both atmospheric and ocean color applications. Nominal spatial resolution is similar to the SeaWiFS instrument with 1050 m at nadir. As for SeaWiFS, the pixel size increases due to a ~20 degree tilt and as a function of scan angle. Variations in the radiometric sensitivity of each OCI channel over time will be monitored by solar diffuser measurements for short term instrument gain adjustments and independent lunar measurements for trend adjustments of long time periods, similar to the approach employed for the VIIRS instrument [4]. The OCI flight-unit was built at NASA’s Goddard Space Flight Center. At the time of this writing, OCI has completed on-orbit commissioning activities and normal science operations have begun. A key aspect of the OCI architecture is the capability to trend absolute and relative calibration changes over the course of mission life with solar calibration. Every 24 hours, the PACE spacecraft performs an inertial hold as the ground track nears the North Pole which orients a Quasi-Volume Diffuser (QVD) mounted on OCI towards the sun. By knowing the irradiance of the sun and the reflectivity of the target, the absolute radiance at the input to the OCI aperture can be computed as OCI scans the target. The allowable absolute uncertainty budget for each solar calibration measurement is 1.6% 1-sigma below 900nm at beginning of life (BOL) and the allowable relative uncertainty budget is ~0.26% 1-sigma. The Solar Calibration Assembly (SCA) consists of three targets selectable via a single mechanism which also opens a door. The targets consist of a Daily Bright Target (DBT), Monthly Bright Target (MBT), and Daily Dim Target (DDT). The bright targets are quartz QVDs with the monthly target being used to track the degradation of the daily target. The dim target is used to track CCD linearity using Progressive Time-Delay Integration (PTDI). A composite baffle is attached to the SCA housing aperture to block Earth shine and stray light from the spacecraft. The SCA assembly is mounted to a view port ~90° from OCI nadir. This paper provides an overview of driving solar calibration requirements, error-budgets and early trade studies which drove the solar calibration assembly (SCA) architecture and on-orbit maneuver. Measurements of the diffuser Bidirectional Reflectance Distribution Function (BRDF) at TNO, Netherlands and GSFC are briefly described. Optical modelling and test results at the sub-system and instrument level are included. Finally, preliminary measurements on-orbit are compared to pre-launch predictions.

Joseph J Knuble↗

NASA NTRSDate not supplied

Overview of NASA's Ocean Color Instrument Solar Calibration Architecture, Pre-Launch Tests and Preliminary On-Orbit Results

ocean color↗

NASA NTRS1998

Performance Improvements to the Lidar Atmospheric Sensing Experiment (LASE)

Lidar Atmospheric Sensing Experiment (LASE) is the first fully-engineered, modular, tunable, autonomous Differential Absorption Lidar (DIAL) system for the remote measurement of water vapor, aerosols and clouds across the troposphere. It was designed, built and environmentally tested at LARC. LASE was designed to fly aboard a NASA/Ames ER-2 aircraft (NASA's high altitude aircraft) and operate at altitudes from 58,000 to 70,000 feet. Since its first flight on May 11, 1994, it has flown 28 total missions on board the ER-2. LASE has been validated with results showing an accuracy better than the initial requirement for vertical profiles of water vapor in the troposphere. LASE can also deploy on several other aircraft including the NASA P-3 and will fly aboard the NASA DC-8 during the Convection And Moisture EXperiment (CAMEX) in July-September 1998. The tunable laser system of LASE was designed to operate in a double-pulse mode at 5Hz, with energy outputs of up to 15OmJ per pulse in the 813 to 819nm wavelength region and with 99% of the output energy within a spectral interval of 1.06 pm. Sixteen wavelengths were selected to cover the various water vapor absorption cross sections needed for the DIAL measurement. The Ti:Sapphire laser was constructed using a frequency-doubled Nd:YAG laser as the pump source and a single mode diode laser as a injection seeder for the Ti:Al2O3 laser. We have improved the LASE instrument in several important ways. Improvements to the seed source have demonstrated that DFB laser diodes can be used as reliable seed sources on airborne DIAL instruments. The DFB diode has enabled LASE to gather more data and significantly reduced the maintenance required to insure that the system performance requirements are met. The multiwavelength sequential seeding technique is the current method of data collection for LASE. It has the advantages of providing an entire atmospheric coverage of H2O(v) from the ground to the aircraft altitude along a single ground track. The development of a flight deployable system to measure spectral purity will insure that the LASE instrument or any future flight based DIAL system can meet the performance specifications to insure data accuracy.

Edwards, W. C.↗

NASA NTRS2012

Evaluating Nighttime CALIOP 0.532 micron Aerosol Optical Depth and Extinction Coefficient Retrievals

NASA Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP) Version 3.01 5-km nighttime 0.532 micron aerosol optical depth (AOD) datasets from 2007 are screened, averaged and evaluated at 1 deg X 1 deg resolution versus corresponding/co-incident 0.550 micron AOD derived using the US Navy Aerosol Analysis and Prediction System (NAAPS), featuring two-dimensional variational assimilation of quality-assured NASA Moderate Resolution Imaging Spectroradiometer (MODIS) and Multi-angle Imaging Spectroradiometer (MISR) AOD. In the absence of sunlight, since passive radiometric AOD retrievals rely overwhelmingly on scattered radiances, the model represents one of the few practical global estimates available from which to attempt such a validation. Daytime comparisons, though, provide useful context. Regional-mean CALIOP vertical profiles of night/day 0.532 micron extinction coefficient are compared with 0.523/0.532 micron ground-based lidar measurements to investigate representativeness and diurnal variability. In this analysis, mean nighttime CALIOP AOD are mostly lower than daytime (0.121 vs. 0.126 for all aggregated data points, and 0.099 vs. 0.102 when averaged globally per normalised 1 deg. X 1 deg. bin), though the relationship is reversed over land and coastal regions when the data are averaged per normalised bin (0.134/0.108 vs. 0140/0.112, respectively). Offsets assessed within single bins alone approach +/- 20 %. CALIOP AOD, both day and night, are higher than NAAPS over land (0.137 vs. 0.124) and equal over water (0.082 vs. 0.083) when averaged globally per normalised bin. However, for all data points inclusive, NAAPS exceeds CALIOP over land, coast and ocean, both day and night. Again, differences assessed within single bins approach 50% in extreme cases. Correlation between CALIOP and NAAPS AOD is comparable during both day and night. Higher correlation is found nearest the equator, both as a function of sample size and relative signal magnitudes inherent at these latitudes. Root mean square deviation between CALIOP and NAAPS varies between 0.1 and 0.3 globally during both day/night. Averaging of CALIOP along-track AOD data points within a single NAAPS grid bin improves correlation and RMSD, though day/night and land/ocean biases persist and are believed systematic. Vertical profiles of extinction coefficient derived in the Caribbean compare well with ground-based lidar observations, though potentially anomalous selection of a priori lidar ratios for CALIOP retrievals is likely inducing some discrepancies. Mean effective aerosol layer top heights are stable between day and night, indicating consistent layer-identification diurnally, which is noteworthy considering the potential limiting effects of ambient solar noise during day.

aerosol optical depth↗

NASA NTRS2008

Seeking Augmented Information Content Concerning Diurnal Precipitation Achieved by Combining TRMM-PR and CloudSat-CPR Radar Data Sets

The CloudSat satellite's Cloud Profiling Radar (CPR) is a highly sensitive 94 GHz (W-band) nadir viewing radar system flown in retrograde sun synchronous orbit useful for determining the vertical structure of cloud hydrometeors down to sensitivity of approx. -30 dBZ reflectivity factor. Given this sensitivity, it is possible to unambiguously measure precipitation rates in clouds over a spectrum extending from approx. 0.08 - 3.0 mm hr (sup -1) down to altitudes of 0.5 km with approx.0.25 km vertical binning. This enables an effective means to measure a great deal of the drizzle and light rain spectrum. However, because of its near-polar sunsynchronous orbit, CloudSat cannot sample the diurnal cycle of precipitation, nor with its nadir-only CPR view can it obtain a high duty cycle in sampling precipitation at fixed local times over fixed positions. On the other hand, the TRMM satellite, which is flown in a non-sunsynchronous 35-degree inclined orbit carrying the 13.8 GHz KU-band Precipitation Radar (PR) scanning through nadir over an approx. 225 km swath, can sample both the diurnal cycle and with a much improved duty cycle relative to CloudSat. Moreover, the PR and CPR have the same 0.25 km vertical binning capability. The PR's greatest shortcoming is its approx. +17 dBZ sensitivity, which eliminates the possibility of measuring rain rates below -0.3-0.5 mm hr(sup -1), which can involve rainfall accumulations of up to 50% of the total over some regions. This begs the question of whether by combining CPR and PR data sets, whether it is possible to obtain an augmented measurement of the diurnal precipitation cycle. By collecting complimentary datasets during CloudSat and TRMM satellite orbit crossings within a delta t = 45-min proximity window, it is possible to demonstrate that whenever TRMM detects a precipitation signal, the correlations along the vertical axis between the reflectivities acquired from the CPR and PR are in inverse proportion to the magnitude of the delta t proximity window. By taking advantage of these underlying correlations, it is possible to develop a functional which can be used to broaden the reflectivity spectrum, concomitantly the rain rate spectrum, of the PR measurements based on the inherently broader reflectivity spectrum of the CPR at the lower reflectivity end of the spectrum, concomitantly at lighter rain rates. With the functional in place, it is then possible to produce synthetic CloudSat precipitation imagery over the PR track and thus over the diurnal time period. These augmented data are then used to study the spectral-vertical diurnal properties of precipitation over oceanic regions observed by TRMM.

Smith, Eric A.↗

NASA NTRS2012

First Assessments of Predicted ICESat-2 Performance Using Aircraft Data

The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) is a next-generation laser altimeter designed to continue key observations of ice sheet elevation change, sea ice freeboard, vegetation canopy height, earth surface elevation, and sea surface height. Scheduled for launch in mid-2016, ICESat-2 will use a high repetition rate (10 kHz), small footprint (10 m nominal ground diameter) laser, and a single-photon-sensitive detection strategy (photon counting) to measure precise range to the earth's surface. Using green light (532 nm), the six beams of ICESat-2 will provide improved spatial coverage compared with the single beam of ICESat, while the differences in transmit energy among the beams provide a large dynamic range. The six beams are arranged into three pairs of beams which allow slopes to measured on an orbit-by-orbit basis. In order to evaluate models of predicted ICESat-2 performance and provide ICESat-2-like data for algorithm development, an airborne ICESat-2 simulator was developed and first flown in 2010. This simulator, the Multiple Altimeter Beam Experimental Lidar (MABEL) was most recently deployed to Iceland in April 2012 and collected approx 85 hours of science data over land ice, sea ice, and calibration targets. MABEL uses a similar photon-counting measurement strategy to what will be used on ICESat-2. MABEL collects data in 16 green channels and an additional 8 channels in the infrared aligned across the direction of flight. By using NASA's ER-2 aircraft flying at 20km altitude, MABEL flies as close to space as is practical, and collects data through approx 95% of the atmosphere. We present background on the MABEL instrument, and data from the April 2012 deployment to Iceland. Among the 13 MABEL flights, we collected data over the Greenland ice sheet interior and outlet glaciers in the southwest and western Greenland, sea ice data over the Nares Strait and Greenland Sea, and a number of small glaciers and ice caps in Iceland and Svalbard. Several of the flights were coincident in time and space with NASA's Operation IceBridge, which provides an independent data set for validation. MABEL also collected data along CryoSat track 10482 in north central Greenland approximately one month after CryoSat passed overhead.

Neumann, Thomas↗

DOE OSTI2025

Forest Breeze–Cold Pool Interactions Drive Convective Organization over Heterogeneous Vegetation

Heterogeneous landscapes can influence the development of convection through the generation of thermally driven mesoscale circulations. To assess the impacts of these circulations and their interaction with sea breezes, we simulated convection in an idealized coastal environment using the Regional Atmospheric Modeling System (RAMS). We compared simulations with striped patterns of surface vegetation to those of uniform vegetation to identify the importance of vegetation heterogeneity in impacting convective development. Under dry soil conditions representative of those during the Tracking Aerosol Convection Interactions Experiment (TRACER) and Experiment of Sea Breeze Convection, Aerosols, Precipitation, and Environment (ESCAPE) campaigns in June 2022, we found that these vegetation-induced circulations, referred to in the literature as “forest breezes,” are more important than the sea breeze in determining the location of convection initiation. Convection and precipitation are also found to be favored over forests and suppressed over pasture and suburban landscapes as a result of greater surface sensible heat flux over the forest. Our findings also indicate that forest breezes are important for initiating convection along the boundaries of the forest, but that cold pools may play a key role in propagating the forest breezes toward the center of the forest stripe. In our simulations, the collisions of these breezes in the center of the forest stripe lead to uplift and strong convection there; however, a different width of the forest stripe would alter when the forest breezes collide or whether they collide at all. The presence of these cold pools may therefore impact the “ideal stripe width,” the width of each vegetation stripe which maximizes domain-wide precipitation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Mesoscale Convective Systems in a Superparameterized E3SM Simulation at High Resolution

Accurately representing mesoscale convective systems (MCSs) is crucial to simulating the energy and water cycles in global climate models. Using a novel MCS identification and tracking algorithm applied to observations and model simulations, we evaluate how well the Energy Exascale Earth System Model simulates MCSs over the central US. Simulations performed by E3SM at 25 km grid spacing with (SP-E3SM) and without (E3SM) superparameterization are compared and evaluated against observations using multiple metrics highlighting important MCS characteristics. Compared to E3SM, SP-E3SM better simulates MCS number and MCS precipitation amount, diurnal cycle, propagation, and the probability distribution of precipitation rate in both spring and summer. The improvement from SP is partly contributed by improvement in simulating the large-scale environments, featuring enhanced atmospheric low-level moisture and larger moisture transport to the central US relative to E3SM. However, SP-E3SM still underestimates MCS precipitation amount, particularly in summer. This underestimation is closely related to the negative bias in MCS precipitation intensity, although the drier environments simulated during summer also contributes to underestimation of MCS frequency. Without SP, the larger bias in MCS precipitation amount is closely related to the negative bias in MCS frequency, while the substantial dry bias in the large-scale environments also contributes to underestimation of MCS intensity. Our results suggest that SP improves MCS simulation by improving modeling of the large-scale environments and convection initiation, which are both major limiting factors in E3SM even at 25 km grid spacing where deep convection is represented by a cumulus parameterization.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Advancing Organized Convection Representation in the Unified Model: Implementing and Enhancing Multiscale Coherent Structure Parameterization

To address the effect of stratiform latent heating on meso- to large-scale circulations, an enhanced implementation of the Multiscale Coherent Structure Parameterization (MCSP) is developed for the Met Office Unified Model. MCSP represents the top-heavy stratiform latent heating from under-resolved organized convection in general circulation models. We couple the MCSP with a mass-flux convection scheme (CoMorph-A) to improve storm lifecycle continuity. The improved MCSP trigger is specifically designed for mixed-phase deep convective cloud, combined with a background vertical wind shear, both known to be crucial for stratiform development. We also test a cloud top temperature dependent convective-stratiform heating partitioning, in contrast to the earlier fixed partitioning. Assessments from ensemble weather forecasts and decadal simulations demonstrate that MCSP directly reduces cloud deepening and precipitation areas by moderating mesoscale circulations. Indirectly, it amends tropical precipitation biases, notably correcting dry and wet biases over India and the Indian Ocean, respectively. Remarkably, the scheme outperforms a climate model ensemble by improving seasonal precipitation cycle predictions in these regions. The scheme also improves Madden-Julian Oscillation (MJO) spectra, achieving better alignment with observational and reanalysis data by intensifying the simulated MJO over the Indian Ocean during phases 4 to 5. However, the scheme increases precipitation overestimation over the Western Pacific. Shifting from fixed to temperature-dependent convective-stratiform partitioning reduces the Pacific precipitation overestimation and further improves the seasonal cycle in India. Spatially correlated biases highlight the necessity for advances beyond deterministic approaches to align MCSP with environmental conditions.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2012

Highlights of TOMS Version 9 Total Ozone Algorithm

The fundamental basis of TOMS total ozone algorithm was developed some 45 years ago by Dave and Mateer. It was designed to estimate total ozone from satellite measurements of the backscattered UV radiances at few discrete wavelengths in the Huggins ozone absorption band (310-340 nm). Over the years, as the need for higher accuracy in measuring total ozone from space has increased, several improvements to the basic algorithms have been made. They include: better correction for the effects of aerosols and clouds, an improved method to account for the variation in shape of ozone profiles with season, latitude, and total ozone, and a multi-wavelength correction for remaining profile shape errors. These improvements have made it possible to retrieve total ozone with just 3 spectral channels of moderate spectral resolution (approx. 1 nm) with accuracy comparable to state-of-the-art spectral fitting algorithms like DOAS that require high spectral resolution measurements at large number of wavelengths. One of the deficiencies of the TOMS algorithm has been that it doesn't provide an error estimate. This is a particular problem in high latitudes when the profile shape errors become significant and vary with latitude, season, total ozone, and instrument viewing geometry. The primary objective of the TOMS V9 algorithm is to account for these effects in estimating the error bars. This is done by a straightforward implementation of the Rodgers optimum estimation method using a priori ozone profiles and their error covariances matrices constructed using Aura MLS and ozonesonde data. The algorithm produces a vertical ozone profile that contains 1-2.5 pieces of information (degrees of freedom of signal) depending upon solar zenith angle (SZA). The profile is integrated to obtain the total column. We provide information that shows the altitude range in which the profile is best determined by the measurements. One can use this information in data assimilation and analysis. A side benefit of this algorithm is that it is considerably simpler than the present algorithm that uses a database of 1512 profiles to retrieve total ozone. These profiles are tedious to construct and modify. Though conceptually similar to the SBUV V8 algorithm that was developed about a decade ago, the SBUV and TOMS V9 algorithms differ in detail. The TOMS algorithm uses 3 wavelengths to retrieve the profile while the SBUV algorithm uses 6-9 wavelengths, so TOMS provides less profile information. However both algorithms have comparable total ozone information and TOMS V9 can be easily adapted to use additional wavelengths from instruments like GOME, OMI and OMPS to provide better profile information at smaller SZAs. The other significant difference between the two algorithms is that while the SBUV algorithm has been optimized for deriving monthly zonal means by making an appropriate choice of the a priori error covariance matrix, the TOMS algorithm has been optimized for tracking short-term variability using month and latitude dependent covariance matrices.

Bhartia, Pawan↗

NASA NTRS2022

Lunar Rover Localization Using Craters as Landmarks

Onboard localization capabilities for planetary rovers to date have used relative navigation, by integrating combinations of wheel odometry, visual odometry, and inertial measurements during each drive to track position relative to the start of each drive. At the end of each drive, a “ground-in-the-loop” (GITL) interaction is used to get a position update from human operators in a more global reference frame, such as a map frame defined by orbital reconnaissance imaging of a large region around the rover’s current position. For Mars rovers, this typically has involved downlinking imagery from the rover mast cameras and using interactive visualization tools on Earth to register such images to the orbital reconnaissance images. For safety purposes, rover mission operations typically specify “keep out zones”, which human operators recognize as being unsafe in the orbital images. Autonomous rover drives are limited in distance so that accumulated relative navigation error does not risk the possibility of the rover driving into a keep out zone. The allowable autonomous drive distance in this mode of operation depends on the distribution of keep out zones and the accuracy of relative navigation; in practice, drive limits of a few hundred meters between GITL cycles are to be expected. Several rover mission concepts have recently been studied that require much longer drives between GITL cycles, particularly for the Moon. This includes lunar rover mission concepts that involve (1) driving mostly in sunlight at low latitudes, (2) driving in permanently shadowed regions near the south pole, and (3) a mixture of day and night driving in mid-latitudes. These concepts include total traverse distance requirements of up to 1,800 km in 4 Earth years, with individual drives of several kilometers between stops for downlink. These concepts require greater autonomy to minimize GITL cycles to enable such large range; onboard global localization is a key element of such autonomy. Multiple techniques have been studied in the past for onboard rover global localization, including radio navigation aiding from an orbiter, recognizing horizon landmarks that are known in a regional elevation map, and correlating a local elevation map created onboard the rover with a regional elevation map. These techniques all have drawbacks, including requiring an expensive extra mission element (navigation orbiter), unavailability of sufficient regional elevation map data, or limited accuracy in resulting position estimates (e.g. a few hundred meters with horizon landmarks). For the Moon, the ubiquitous craters offer another possibility, which involves mapping craters from orbit, then recognizing crater landmarks with cameras and/or a lidar onboard the rover. This approach is applicable everywhere on the Moon, does not require high resolution stereo imaging from orbit as some other approaches do, and has potential to enable position knowledge with order of 10 m accuracy at all times. This paper will provide more detail on our technical approach to crater-based lunar rover localization and will present initial results on crater detection using 3-D point cloud data from onboard lidar or stereo cameras and using shading cues in monocular onboard imagery.

Ono, M.↗

DOE OSTI2021

Combined Mesonet and Tracker

Title: Combined Mesonet and Trackers (UNL Mobile Mesonets) Authors University of Nebraska PI: Adam Houston, UNL Professor (ahouston2@unl.edu) Mailing Address: 126 Bessey Hall P.O. Box 880340 Lincoln, NE 68588-0340 CoMeT Overview The University of Nebraska-Lincoln operates three Combined Mesonet and Tracker (CoMeTs). CoMeTs are Ford Explorers (model years 2015, 2017, and 2019) with forward-mounted suites of meteorological sensors and dual moonroofs, combining the capability of a mobile mesonet to collect near-surface observations with the capability of an unmanned aircraft systems (UAS) tracker vehicle, which enables an observer in the second row of seats to see the aircraft and maintain compliance with Federal Aviation Administration policies on UAS operation. The CoMeTs collect observations of slow temperature and humidity at ~2 m above ground level (AGL) using a Vaisala HMP155A, fast temperature at ~2 m AGL using a Campbell Scientific 109SS-L thermistor, pressure at ~2.5 m AGL using a Vaisala PTB210, wind speed and direction at ~3.25 m AGL using an R.M. Young 05103 propeller anemometer, and vehicle heading using a KVH Industries C-100 fluxgate compass (Barbieri et al. 2019). The HMP155A and 109SS-L thermistor are shielded and aspirated within a U-tube (Waugh and Frederickson 2010; Houston et al. 2016). This list of sensors is also included in the CoMeT data file metadata. Manufacturer specifications for these instruments are given in Table 1 of Hanft and Houston (2018). The reported measured quantities are summarized below.CoMeT-3 was funded through an equipment allocation included in the NSF TORUS award (AGS-1824649). Instrument Description The specific sensors included on each CoMeT are summarized in the table at the end of this section. In general each CoMeT collects observations of slow temperature and humidity at ~2 m above ground level (AGL) using a Vaisala HMP155, fast temperature at ~2 m AGL using a Campbell Scientific 109SS-L thermistor, pressure at ~2.5 m AGL using a Vaisala PTB210 barometer with a Gill pressure port, wind speed and direction at ~3.25 m AGL using an R.M. Young 05103 propeller anemometer, position using a Garmin 19x HVS receiver, and vehicle heading using a KVH Industries C-100 fluxgate compass. The HMP155 and 109SS are shielded and aspirated within a U-tube (Waugh and Frederickson 2010; Houston et al. 2016). Fast temperature and corrected RH measurements (using sensors housed within the U-tube) have a time constant of 10-12 s based on data collected across a temperature and RH shock during the CLOUD-MAP 2017 calibration/validation tests on June 26, 2017. Vehicle speed was < 10 kts for this test. CoMeT-1 CoMeT-2 CoMeT-3 Slow Temperature Slow RH Vaisala HMP155A-L20-PT Part #: 22280-7 Vaisala HMP155E Part #: E1AA11A0B1A1A0A Vaisala HMP155E Part #: E1AA11A0B1A1A0A Fast temperature Campbell Scientific 109SS-L20-PT Part #: 21448-3 Campbell Scientific 109SS-L12-PW Part #: 21448-109 Campbell Scientific 109SS-L12-PW Part #: 21448-150 Pressure Vaisala PTB-210 Part #: A1A1B Gill Pressure Port Part #: 61002 Vaisala PTB-210 Part #: A1A1B Gill Pressure Port Part #: 61002 Vaisala PTB-210 Part #: A1A1B Gill Pressure Port Part #: 61002 Wind RM Young 05103-L20-PT Part #: 18435-310 RM Young 05103-L20-PW Part #: 18435-244 RM Young 05103-L20-PW Part #: 18435-244 GPS Garmin GPS 19x HVS (NMEA 0183) Part #: 010-01010-00 Garmin GPS 19x HVS (NMEA 0183) Part #: 010-01010-00 Garmin GPS 19x HVS (NMEA 0183) Part #: 010-01010-00 Compass KVH C-100 Part #: 01-0177-15 KVH C-100 Part #: 01-0177-15 KVH C-100 Part #: 01-0177-15 Logger Campbell Scientific CR6-NA-XT-SW Part #: 28385-9 Campbell Scientific CR6-WIFI-XT-SW Part #: 28385-6 Campbell Scientific CR6-WIFI-XT-SW Part #: 28385-6 Data Collection and Real-Time Processing The reported measured quantities are summarized in the table below. Quantity Units Source Epoch time Seconds GPS Latitude and longitude Degrees GPS Altitude m GPS Pressure hPa PTB210 Temperature (fast) deg C 109SS-L Temperature (slow) deg C HMP155 RH (slow) % HMP155 Vehicle speed m/s GPS Vehicle heading deg C-100 and GPS In addition to the measured variables, several derived variables are calculated. Corrected/fast relative humidity (%) Relative humidity is adjusted to the fast temperature following Richardson et al. (1998) and Houston et al. (2016). Water vapor mixing ratio (g/kg) Dew point temperature (°C) Potential temperature (Kelvin) Virtual potential temperature (Kelvin) Equivalent potential temperature (Kelvin) Regular intercomparisons between all three CoMeTs were performed during TORUS 2019. Comparisons were also conducted between CoMeT-1 and CoMeT-2 during LAPSE-RATE (2018) on 14 July. In these intercomparisons, the vehicles were parked adjacent to each other aligned perpendicular to (and facing into) the wind. To minimize engine heating effects, intercomparisons were only conducted when the wind speed was >10 kts. Data Format Original data files for each deployment are saved as text files and then converted to NetCDF. NetCDF versions have units that are CF compliant and may not match the original units in the txt files. The naming convention for the NetCDF files is as follows: UNL.CoMeT3.{deployment date YYYYMMDD}.{start time of observation collection in UTC HHMM}.L2.{post-processing codes}.cdf example: UNL.CoMeT3.20190627.1931.L2.g1.f1.cdf Post-processing codes are included to track modifications to the raw data. These codes are closely connected to error flags associated with each record. Each letter corresponds to a particular instrument: g: GPS p: Barometer tf: Fast temperature ts: Slow temperature rh: Relative humidity f: Compass w: Wind monitor a: All instruments Each number corresponds to a particular post-processing action described more below. Measured and derived variables are included in the following table. Variable Heading Standard Name Units time Time seconds since 00:00:00, 01-01-1970 Alt Altitude meters lat Latitude degrees north lon Longitude degrees east fast_temp Air Temperature kelvin slow_temp Air Temperature kelvin pressure Air Pressure pascals logger_RH Relative Humidity percent calc_corr_RH Relative Humidity percent wind_speed Wind Speed meters per second wind_dir Wind From Direction degrees vehicle_dir Vehicle Direction degrees dewpoint Dew Point Temperature kelvin mixing_ratio Humidity Mixing Ratio g/g theta Air Potential Temperature kelvin theta_v Virtual Potential Temperature kelvin theta_e Equivalent Potential Temperature Kelvin error_flag The error_flag variable is a string that matches the post-processing codes listed above. All instruments will have an associated code, but will have a “0” if the datum is unchanged from the initial processed value. Error Codes The following table summarizes the error codes for data collected before 2020: Error Code Relevant CoMeT Description g1 1,2,3 Exact correction. GPS position and time reprocessed from raw data g2 1 As far as we can tell this is an exact correction to an error in the GPS time. During the correct time periods the time suddenly went backwards ~250s and stayed at this offset for 750s when it corrected itself. The offset was applied to the “time warp” period. p1 2 Approximate correction. Hole in the pressure tube connecting the pressure port to the barometer. Resulted in erroneously low air pressure measurements when the vehicle was in motion. Derived variables recalculated (dew point temperature [e depends on qv and p], water vapor mixing ratio, potential temperature, virtual potential temperature, equivalent potential temperature) a1 3 Exact correction. Missing data reprocessed from raw data a2 1 Bug fix to bias correction for ts1, ts2, and rh1: water vapor mixing ratio was off by a factor of 10 and virtual potential temperature was wrong because of this. f1 3 No correction, missing data. Fluxgate compass inoperable. Wind speed and direction calculated using GPS-derived vehicle heading instead. rh1 1 Approximate correction. Constant bias of +1.7% removed from relative humidity. Derived variables recalculated (corrected/fast relative humidity, dew point temperature, water vapor mixing ratio, virtual potential temperature, equivalent potential temperature) ts1 1 Approximate correction. Constant bias of +0.6 K removed from slow temperature. Derived variables recalculated (corrected/fast relative humidity, dew point temperature, water vapor mixing ratio, virtual potential temperature, equivalent potential temperature) ts2 1 Approximate correction. Constant bias of +1.0 K removed. Derived variables recalculated (corrected/fast relative humidity, dew point temperature, water vapor mixing ratio, virtual potential temperature, equivalent potential temperature) References Bolton, D., 1980: The Computation of Equivalent Potential Temperature. Mon. Wea. Rev., 108, 1046–1053, https://doi.org/10.1175/1520-0493(1980)108<1046:TCOEPT>2.0.CO;2. Hanft, W., and A. L. Houston, 2018: An Observational and Modeling Study of Mesoscale Air Masses with High Theta-E. Mon. Wea. Rev., 146, 2503–2524, https://doi.org/10.1175/MWR-D-17-0389.1.Wexler Houston, A. L., R. J. Laurence III, T. W. Nichols, S. Waugh, B. Argrow, and C. L. Ziegler, 2016: Intercomparison of unmanned aircraft-borne and mobile mesonet atmospheric sensors. Journal of Atmospheric and Oceanic Technology. 33, 1569-1582, doi: 10.1175/JTECH-D-15-0178.1. Lowe, P. R., 1977: An Approximating Polynomial for the Computation of Saturation Vapor Pressure. J. Applied Meteorology, 16, 100–103. Richardson, S. J., S. E. Frederickson, F. V. Brock, and J. A. Brotzge, 1998: Combination temperature and relative humidity probes: Avoiding large air temperature errors and associated relative humidity errors. Preprints, 10th Symp. On Meteorological Observations and Instrumentation, Phoenix, AZ, Amer. Meteor. Soc., 278–283. Waugh, S., and S. E. Frederickson, 2010: An improved aspirated temperature system for mobile meteorological observations, especially in severe weather. 25th Conf. on Severe Local Storms, Denver, CO, Amer. Meteor. Soc., P5.2. [Available online at https://ams.confex.com/ams/25SLS/techprogram/paper_176205.htm.]

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2007

Multi-Grid-Cell Validation of Satellite Aerosol Property Retrievals in INTEX/ITCT/ICARTT 2004

Aerosol transport off the US Northeast coast during the Summer 2004 International Consortium for Atmospheric Research on Transport and Transformation (ICARTT) Intercontinental Chemical Transport Experiment (INTEX) and Intercontinental Transport and Chemical Transformation (ITCT) experiments produced a wide range of aerosol types and aerosol optical depth (AOD) values, often with strong horizontal AOD gradients. In these conditions we flew the 14-channel NASA Ames Airborne Tracking Sun photometer (AATS) on a Jetstream 31 (J31) aircraft. Legs flown at low altitude (usually less than 100 m ASL) provided comparisons of AATS AOD spectra to retrievals for 90 grid cells of the satellite radiometers MODIS-Terra, MODIS-Aqua, and MISR, all over the ocean. Characterization of the retrieval environment was aided by using vertical profiles by the J31 (showing aerosol vertical structure) and, on occasion, shipboard measurements of light scattering and absorption. AATS provides AOD at 13 wavelengths lambda from 354 to 2138 nm, spanning the range of aerosol retrieval wavelengths for MODIS over ocean (466-2119 nm) and MISR (446-866 nm). Midvisible AOD on low-altitude J31 legs in satellite grid cells ranged from 0.05 to 0.9, with horizontal gradients often in the range 0.05 to 0.13 per 10 km. When possible, we used ship measurements of humidified aerosol scattering and absorption to estimate AOD below the J31. In these cases, which had J31 altitudes 60-110 m ASL (typical of J31 low-altitude transects), estimated midvisible AOD below the J31 ranged from 0.003 to 0.013, with mean 0.009 and standard deviation 0.003. These values averaged 6 percent of AOD above the 53 1. MISR-AATS comparisons on 29 July 2004 in 8 grid cells (each -17.6 km x 17.6 km) show that MISR versions 15 and 16 captured the AATS-measured AOD gradient (correlation coefficient R2 = 0.87 to 0.92), but the MISR gradient was somewhat weaker than the AATS gradient. The large AOD (midvisible values up to -0.9) and differing gradients in this case produced root-mean-square (RMS) MISR-AATS AOD differences of 0.03 to 0.21 (9 to 31%). MISR V15 Angstrom exponent alpha (= -dlnAOD/dln lambda) was closer to AATS than was MISR V16. MODIS-AATS AOD comparisons on 8 overpasses using 61 grid cells (each nominally 10 km x 10 km) had R2 approximately 0.97, with RMS AOD difference approximately 0.03 (approximately 20%). About 87% of the MODIS AOD retrievals differed from AATS values by less than the predicted MODIS over-ocean uncertainty, Delta tau = plus/minus 0.03 plus/minus 0.05 tau. In contrast to the small MODIS-AATS differences in AOD, MODIS-AATS differences in Angstrom exponent alpha were large: RMS differences for alpha (553, 855 nm) were 0.28 for MODIS-Terra and 0.64 for MODIS-Aqua; RMS differences for alpha (855, 2119 nm) were larger still, 0.61 for MODIS-Terra and 1.14 for MODIS-Aqua. The largest MODIS-AATS Angstrom exponent differences were associated with small AOD values, for which MODIS AOD relative uncertainty is large. Excluding cases with AOD(855 nm) less than 0.1 reduced MODIS-AATS alpha differences substantially. In one grid cell on 21 July 2004, smoke over cloud appeared to impair the MODIS-Aqua cloud mask, resulting in retrieved AODs that significantly exceeded AATS values. Experiments with extending MODIS retrievals into the glint mask yielded MODIS AODs consistently less than AATS AODs, especially at long wavelength, indicating that the current MODIS glint mask limits should not be reduced to the extent tried here. The sign of the AOD differences within the glint mask (MODIS AOD less than AATS AOD) is consistent with ship-measured wind speeds there.

Russell, P. B.↗

DOE OSTI2024

Novel Instrumentation for Advanced Quantum Chromodynamics Studies with Flavor Sensitivity

The true nature of ordinary matter has always fascinated humankind, whose imagination has been pointed to the right direction since the 5th century BC with the first known atomic theory by Leucippus and Democritus. They described the matter as formed by small, invisible, indivisible, and eternal particles: the atoms. A long investigation followed them, including contributions from several of history?s greatest philosophers and scientists. The progress led to the understanding that atoms have an internal structure consisting of a central nucleus composed of protons and neutrons, surrounded by a cloud of electrons. About 50 years ago, scientists discovered that nucleons also have an internal structure. Through the Deep Inelastic Scattering (DIS) experiments, on which a lepton is scattered off a nucleon, it was possible to access the distribution of partons inside the nucleon along the longitudinal direction defined by the hard-scale probe. It was a crucial step in developing Quantum Chromodynamics (QCD), currently the best theory describing the subatomic matter. Ultimately, DIS was recognized as a limited tool to investigate the nucleon structure because it is mainly sensitive to observables at the probe?s energy scale. In recent decades, theoretical developments have allowed defining soft-scale observables by measuring more complex processes. Reactions such as Semi-Inclusive Deep Inelastic Scattering (SIDIS) with single or di-hadron production, can provide information about the momentum of parton inside the nucleon. In particular, polarized SIDIS allows access to the Transverse-Momentum-Dependent (TMD) parton distributions describing the correlations of the quark and gluon degrees of freedom in transverse momentum and spin. This study can provide three-dimensional imaging of nucleon structure and inner dynamics, as long as the hadronic component in the final state can be measured. Identifying the species of the produced particles provides information on the quark flavor and assumes a crucial role in this context. The thesis describes the work carried out by the author in preparing novel instrumentation for particle identification in the final state of DIS experiments, to support modern analysis of the parton dynamics within the basic confined object (nucleon) with flavor sensitivity. The work has been focused on the CLAS12 spectrometer in operation at Jefferson Laboratory (JLab), Newport News, VA, USA, and the ePIC experiment in preparation for the future Electron-Ion Collider (EIC) at Brookhaven National Laboratory (BNL), Long Island, NY, USA. CLAS12 is a fixed-target experiment using a 12 GeV beam of polarized electrons scattering off polarized nuclear targets. In 2018 and 2022, two Ring Imaging Cherenkov (RICH) detector modules were installed to improve the ?±/K± separation in the high-momentum region (3÷8 GeV/c) of the experiment. The author contributed to the assembly, installation, and com- missioning of the second RICH module, to the efficiency studies of the first module, and to the first SIDIS analysis with high-momentum kaons identified by the RICH. These studies led to the observation of the first spin asymmetry with high-momentum kaons from the CLAS12 experiment, and an initial assessment of the systematic error associated with the hadron identification. ePIC will be the first experiment at the future EIC, the new collider designed to expand the frontiers of QCD. The author was involved in the development of the dual-radiator Ring Imaging Cherenkov (dRICH). This detector will interpolate the measurements of the Cherenkov angles of photons produced by relativistic particles crossing two different radiators to identify charged hadrons. The author contributed to the studies conducted with the dRICH prototype, developing the reconstruction and analysis software and simulations, characterizing the aerogel radiator samples, and being responsible for the tracking system used during the beam tests. The performance obtained by the prototype has been progressively improved and the results are now comparable with the expectation derived from the simulation and satisfy the requirements of the experiment. In Chapter 1, the SIDIS theory is briefly introduced, outlying the connection with the experimental measurement. Chapter 2 includes the description of the CLAS12 RICH, its assembly and installation, and the efficiency study. In Chapter 3, the analysis of the Beam-Spin Asymmetry associated with SIDIS kaons is described. Chapter 4 describes the contribution to the dRICH for EIC, starting from a description of the ePIC experiment and focusing on the studies performed for the dRICH prototype. The conclusions of this work are summarized at the end.

Vallarino, Simone↗

NASA NTRS2009

Panel Discussion: Life in the Cosmos

Water appears to be essential to all life on Earth. For this reason, "Follow the Water" has been adopted as a mantra for the search for Life in the Cosmos. Expeditions have helped to establish the limits and biodiversity of life in the most extreme environments on Earth. Microbial extremophiles inhabit acidic streams; hypersaline and hyperalkaline lakes and pools; the cold deep sea floor, permafrost, rocks, glaciers, and perennially ice-covered lakes of the polar environments; geysers, volcanic fumaroles, hydrothermal vents and hot rocks deep within the Earth's crust. The ESA Venus Express Spacecraft entered Venusian Orbit in 2006 and continues to produce exciting results. The Visible and Infrared Thermal Imaging Spectrometer (VIRTIS) instrument made the first detection of hydroxyl in the atmosphere of Venus, indicating it is much more similar to Earth and Mars than previously thought. Huge hurricane-like vortices have been found above the poles of the planet and as yet unidentified UV absorbers that form mysterious dark bands in the upper atmosphere. At 70 km and below, water vapor and sulfur dioxide combine to form sulfuric acid droplets that create a haze above the cloud tops. Thermophilic acidophiles, such as have recently been discovered on Earth, could possibly survive in the hot sulfuric acid droplets that exist in the upper atmosphere of Venus. In order to understand how to search for life elsewhere in the Solar System, over 40 VIRTIS images of Earth from Venus have been obtained to search for evidence of life on Earth. The signatures of water and molecular Oxygen were detected in the Earth s atmosphere, but the atmosphere of Venus also exhibits these signatures. The water and water ice are far more abundant on comet, the polar caps and permafrost of Mars and the icy moons of Jupiter and Saturn. These "frozen worlds" of our Solar System, are much more promising regimes where extant or extinct microbial life may exist. The ESA Mars Advanced Radar for Subsurface and Ionospheric Sounding (MARSIS) probe has found that both the North and South Polar Caps of Mars are approximately 3.5 km thick and are composed almost entirely of water ice. In winter, a thin dry ice layer covers the caps, but it sublimates directly to CO2 in the spring. The ESA Mars Express Orbiter images reveal Rupes Tenuis to be a vast snow-laden region on the southern edge of the Martian North Polar Cap. The Mars Exploration Rover Spirit found alkaline volcanic rocks in the Gusev Crater and the Phoenix Mars Lander has shown that the soil of Mars is much more alkaline than previously expected. The Phoenix Mars Lander has also made direct observations of frozen and liquid water on Mars. It is known that microorganisms from Alaska, Siberia and Antarctica can remain alive frozen in permafrost or ice for long periods of time. These discoveries increase the possibility that the Labeled Release Experiment may have discovered life on Mars during the Viking Mission and provide strong impetus for the return of life detection experiments to Mars. Changes in the spin rate of Saturn's moon Titan indicate that it may also harbor a 300 km thick liquid water ocean beneath its icy crust. The NASA/ESA/Italian Space Agency Cassini Spacecraft has imaged geysers containing water vapor, methane, carbon dioxide and organics erupting from the "tiger stripe" regions near the South Pole of Saturn's moon Enceladus. The high temperatures observed, the water vapor and large number of ice particles expelled suggest that a liquid water lake may exist beneath the "tiger stripe" ice cracks of Enceladus. The NASA Deep Impact probe found the surface temperature of comet 9P/Temple 1 at 1.5 AY was slightly above the ice/water phase change temperature (273 K). This suggests melting of water ice near the comet surface. A spectrometer the spacecraft detected a mixture of clay and carbonate minerals (that form in the presence of liquid water) streaming off the comet after the collision with the pactor. The study of chemical and mineral biomarkers, chiral amino acids and possible indigenous microfossils in SNC and carbonaceous meteorites continues. These results suggest that comets should be considered prime targets in the search for Life in the Cosmos. The ESA Rosetta mission is on track to rendezvous with comet 67P/Churyumov-Gerasimenko. The recent space observations combined with new information about the ability of microbial extremophiles to thrive in polar environments suggest that life may be far more widely distributed in the Cosmos than previously thought possible. The Panelists will review recent discoveries and provide their own insights about Life in the Cosmos -- followed by a question and answer session with the audience.

Hoover, Richard B.↗