ALBERT

Description: We used Hinode X-Ray Telescope (XRT) and Solar Optical Telescope (SOT) filtergraph (FG) Stokes-V magnetogram observations, to study the early onset of a solar eruption that includes an erupting filament that we observe in TRACE EUV images. The filament undergoes a slow rise for at least 20min prior to its fast eruption and strong soft X-ray (SXR) flaring; such slow rises have been previously reported, and the new Hinode data elucidate the physical processes occurring during this period. XRT images show that during the slow-rise phase, an SXR sigmoid forms from apparent reconnection low in the sheared core field traced by the filament, and there is a low-level intensity peak in both EUV and SXRs during the slow rise. MDI and SOT FG Stokes-V magnetograms show that the pre-emption filament is along a neutral line between opposing-polarity enhanced network cells, and the SOT magnetograms show that these opposing fields are flowing together and canceling for at least six hours prior to eruption. From the MDI data we measured the canceling network fields to be approx. 40 G, and we estimated that approx. 10(exp 19)Mx of flux canceled during the five hours prior to eruption; this is only approx.5% of the total flux spanned by the eruption and flare, but apparently its tether-cutting cancellation was enough to destabilize the sigmoid field holding the filament and resulted in that field's eruption.

Description: Images and the radial profiles of the temperature, abundance, and brightness for 70 clusters of galaxies observed by XMM-Newton are presented along with a detailed discussion of the data reduction and analysis methods, including background modeling, which were used in the processing. Proper consideration of the various background components is vital to extend the reliable determination of cluster parameters to the largest possible cluster radii. The various components of the background including the quiescent particle background, cosmic diffuse emission, soft proton contamination, and solar wind charge exchange emission are discussed along with suggested means of their identification, filtering, and/or their modeling and subtraction. Every component is spectrally variable, sometimes significantly so, and all components except the cosmic background are temporally variable as well. The distributions of the events over the FOV vary between the components, and some distributions vary with energy. The scientific results from observations of low surface brightness objects and the diffuse background itself can be strongly affected by these background components and therefore great care should be taken in their consideration.

Description: This viewgraph presentation gives a general overview of the X-43A program. The contents include: 1) X-43A Program Overview; 2) Vehicle Description; 3) Flight 1, MIB & Return to Flight; 4) Flight 2 and Results; and 5) Flight 3 and Results.

Description: A viewgraph presentation describing the hypersonics program at NASA Dryden Flight Research Center is shown. The topics include: 1) X-43A Program Overview; 2) Vehicle Description; 3) Flight 1, MIB & Return to Flight; 4) Flight 2 and Results; 5) Flight 3 and Results; and 6) Concluding Remarks

Description: The Hinode satellite (formerly Solar-B) of the Japan Aerospace Exploration Agency's Institute of Space and Astronautical Science (ISAS/JAXA) was successfully launched in September 2006. As the successor to the Yohkoh mission, it aims to understand how magnetic energy is transferred from the photosphere to the upper atmospheres and resulting in explosive energy releases. Hinode is an observatory style mission, with all the instruments being designed and built to work together to address the science aims. There are three instruments onboard: the Solar Optical Telescope (SOT), the EUV Imaging Spectrometer (EIS), and the X-ray Telescope (XRT). This paper overviews the mission, including the satellite, the scientific payload and operations. It will conclude with discussions on how the international science community can participate in the analysis of the mission data.

Description: For all past and current human space missions, the final scheduling of tasks to be done in space has been devoid of crew control, flexibility, and insight. Ground controllers, with minimal input from the crew, schedule the tasks and uplink the timeline to the crew or uplink the command sequences to the hardware. Prior to the International Space Station (ISS), the crew could make requests about tomorrow s timeline, they could omit a task, or they could request that something in the timeline be delayed. This lack of control over one's own schedule has had negative consequences. There is anecdotal consensus among astronauts that control over their own schedules will mitigate the stresses of long duration missions. On ISS, a modicum of crew control is provided by the job jar. Ground controllers prepare a task list (a.k.a. "job jar") of non-conflicting tasks from which jobs can be chosen by the in space crew. Because there is little free time and few interesting non-conflicting activities, the task-list approach provides little relief from the tedium of being micro-managed by the timeline. Scheduling for space missions is a complex and laborious undertaking which usually requires a large cadre of trained specialists and suites of complex software tools. It is a giant leap from today s ground prepared timeline (with a job jar) to full crew control of the timeline. However, technological advances, currently in-work or proposed, make it reasonable to consider scheduling a collaborative effort by the ground-based teams and the in-space crew. Collaboration would allow the crew to make minor adjustments, add tasks according to their preferences, understand the reasons for the placement of tasks on the timeline, and provide them a sense of control. In foreseeable but extraordinary situations, such as a quick response to anomalies and extended or unexpected loss of signal, the crew should have the autonomous ability to make appropriate modifications to the timeline, extend the timeline, or even start over with a new timeline. The Vision for Space Exploration (VSE), currently being pursued by the National Aeronautics and Space Administration (NASA), will send humans to Mars in a few decades. Stresses on the human mind will be exacerbated by the longer durations and greater distances, and it will be imperative to implement stress-reducing innovations such as giving the crew control of their daily activities.

Description: We use Hinode X-Ray Telescope (XRT) and Solar Optical Telescope (SOT) filtergraph (FG) Stokes-V magnetogram observations, to study the early onset of a solar eruption that includes an erupting filament that we observe in TRACE EUV images. The filament undergoes a slow rise for at least 20 min prior to its fast eruption and strong soft X-ray flaring; such slow rises have been previously reported, and the new Hinode data elucidate the physical processes occurring during this period. XRT images show that during the slow-rise phase, a soft X-ray (SXR) sigmoid forms from apparent reconnection low in the sheared core field traced by the filament, and there is a low-level intensity peak in both EUV and SXRs during the slow rise. MDI and SOT FG/V magnetograms show that the pre-eruption filament is along a neutral line between opposing-polarity enhanced network cells, and the SOT magnetograms show that these opposing fields are flowing together and canceling for at least six hours prior to eruption. From the MDI data we measure the canceling network fields to be approx. 40 G, and we estimate that approx. 10(exp 19) Mx of flux canceled during the five hours prior to eruption; this is only approx. 5% of the total flux spanned by the eruption and flare, but apparently its tether-cutting cancellation was enough to destabilize the sigmoid field holding the filament and resulted in that field's eruption.

Description: Medical requirements for the future Crew Exploration Vehicle (CEV), Lunar Surface Access Module (LSAM), advanced Extravehicular Activity (EVA) suits and Lunar habitat are currently being developed. Crews returning to the lunar surface will construct the lunar habitat and conduct scientific research. Inherent in aggressive surface activities is the potential risk of injury to crewmembers. Physiological responses and the operational environment for short forays during the Apollo lunar missions were studied and documented. Little is known about the operational environment in which crews will live and work and the hardware will be used for long-duration lunar surface operations. Additional information is needed regarding productivity and the events that affect crew function such as a compressed timeline. The Space Medicine Division at the NASA Johnson Space Center (JSC) requested a study in December 2005 to identify Apollo mission issues relevant to medical operations that had impact to crew health and/or performance. The operationally oriented goals of this project were to develop or modify medical requirements for new exploration vehicles and habitats, create a centralized database for future access, and share relevant Apollo information with the multiple entities at NASA and abroad participating in the exploration effort.

Description: To accurately model radiative fluxes at the surface and within the atmosphere, we need to know both vertical and horizontal structures of cloudiness. While MODIS provides accurate information on cloud horizontal structure, it has limited ability to estimate cloud vertical structure. ICESat/GLAS on the other hand, provides the vertical distribution and internal structure of clouds as deep as the laser beam can penetrate and return a signal. Having different orbits, MODIS and GLAS provide few collocated measurements; hence a statistical approach is needed to learn about 3D cloud structures from the two instruments. In the presentation, we show the results of the statistical analysis of vertical and horizontal structure of cloudiness using GLAS and MODIS cloud top(s) data acquired in October-November 2003. We revisit the (H1, C1) plot, previously used for analyzing cloud liquid water data, and illustrate cloud structure for single and multiple-layer clouds.

Description: Lightning is responsible for an estimated 15 percent of total NO emissions, and is one of the most prominent sources in the upper troposphere. In this study, we present evidence of lightning-generated NO2 (LNO2) using data from the Ozone Monitoring Instrument (OMI), which has observed tropospheric NO2 since its launch in 2004. Although LNO2 has been also reported in previous satellite studies from the Global Ozone Monitoring Experiment (GOME) and SCIAMACHY, OMI is better suited for such measurements by virtue of its higher spatial resolution and daily global coverage. We will present data clearly showing the LNO2 signal in the OMI tropospheric NO2 product on two days over and downwind of specific convective systems in the US Midwest. Gridded monthly mean tropospheric NO 2 data are subtracted from the daily gridded data to obtain the presumed LNO2 signal. Observed cloud-to-ground (CG) lightning flashes from the National Lightning Detection Network (NLDN) were counted along middle and upper tropospheric back trajectories that were run from the regions containing the LNO2 signal. A vertically-weighted average number of upwind CG flashes was obtained using a profile of LNO(x) mass obtained from a series of midlatitude cloud-resolved storm chemistry simulations. The number of CG flashes was scaled up to total flashes (intracloud (IC) flashes plus CG) using a climatological IC/CG ratio. The number of moles of LNO(x) in the region considered was estimated by assuming that LNO2 is 30 percent of LNO(x). This value was divided by the number of upwind flashes to obtain an average estimate of the number of moles produced per flash. Results yield values in the range obtained through other estimation techniques (e.g., aircraft measurements, models). We will also present a similar analysis over northern Australia during the SCOUT-O3/ACTIVE field campaigns in November and December 2005, in which we will compare the OMI LNOx signals with aircraft observations from the storm anvils.