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A listing of the source deck of each finite element FORMA subroutine is given to remove the 'black-box' aura of the subroutines so that the analyst may better understand the detailed operations of each subroutine. The FORTRAN 4 programming language is used in all finite element FORMA subroutines.
Reactive schema-based navigation is possible in space domains by extending the methods developed for ground-based navigation found within the Autonomous Robot Architecture (AuRA). Reformulation of two dimensional motor schemas for three dimensional applications is a straightforward process. The manifold advantages of schema-based control persist, including modular development, amenability to distributed processing, and responsiveness to environmental sensing. Simulation results show the feasibility of this methodology for space docking operations in a cluttered work area.
Structural dynamics and its auxiliary fields are the most progressive and challenging areas space system engineering design and operations face. Aerospace systems are dependent on structural dynamicists for their success. Past experiences (history) are colored with many dynamic issues, some producing ground or flight test failures. The innovation and creativity that was brought to these issues and problems are the aura from the past that lights the path to the future. Using this illumination to guide understanding of the dynamic phenomena and designing for its potential occurrence are the keys to successful space systems. Our great paradox, or challenge, is how we remain in depth specialists, yet become generalists to the degree that we make good team members and set the right priorities. This paper will deal with how we performed with acclaim in the past, the basic characteristics of structural dynamics (loads cycle, for example), and the challenges of the future.
Measuring tropospheric chemical constituents from space has been only of the "Holy Grails" of remote sensing. Tropospheric remote sensing has been done in two phases, extracting troposheric constituent information from satellite instruments designed for other purposes and constituent measurements with instruments optimized for tropospheric detection. Examples from the first phase, tropospheric ozone and aerosols from Total Ozone Mapping Spectrometer (TOMS) and Global Ozone Monitoring Experiment (GOME) will be presented. Expected results from upcoming instruments and missions, Atmospheric Ultraviolet Radiance Analyzer (AURA), Ozone Monitoring Instrument (OMI), GOME2, and Scanning Imaging Spectrometer for Atmospheric Chartography (SCIAMACHY) will be presented.
We present follow-up HST/Space Telescope Imaging Spectrograph (STIS) observations of the Ly-alpha bright jet associated with the near-ZAMS Herbig Ae star HD163296. The proper motions and radial velocities of the knots in the flow are consistent with a collimated outflow inclined by 40 deg relative to the plane of the sky with a flow velocity that varies from 350 to 500 km/s along the jet. A new knot is visible in the jet at a projected distance of 0.33 arcsec (40 AU) from the central star. The knot has a dynamical age of only seven months, making it the youngest HH knot ever observed. We did not detect any emission from the counterjet within 2.5 arcsec of the source, which is consistent with absorption due to a uniform 450 AU radius disk tilted at 50 deg relative to the line of sight. We also present observations made with the Goddard Fabry-Perot Imager which show additional, more distant knots along the blue and red shifted outflow lobes, and discuss the collimation of the jet and implications for a magnetosphere associated with HD 163296. Support for this study was provided by HST STIS GTO funding through support to the NOAO, in response to the NASA A/O OSSA-4-84 through the Hubble Space Telescope Project at GSFC, as well as NASA grant NRA-98-03-UVG-O11. NOAO is operated by the Association of Universities for Research in Astronomy (AURA), Inc., under cooperative agreement with the National Science Foundation. Data analysis facilities were provided by the Laboratory for Astronomy & Solar Physics, NASA/GSFC.
An overview of the NASA EOS (Earth Observing System) Validation Program will be given with special emphasis on synergy of airborne field missions and EOS satellite missions. Presentation will describe objectives of program and recent field campaigns for validation of standard scientific data products from EOS Terra. Airborne simulators developed for Terra validation will also be described. Plans for future field activity and airborne simulators, especially for EOS Aqua validation and also encompassing EOS Aura validation, will also be briefly presented.
Instruments such as the Global Ozone Monitoring Experiment (GOME, on the European Remote Sensing Satellite (ERS-2), launched 1995), the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY, on ENVISAT, to be launched July 2001) and the Ozone Monitoring Instrument (OMI on EOS Aura, to be launched 2003) make measurements of the total column of NO2. There is interest in separating the stratospheric and tropospheric contributions to the column, as the tropospheric column provides a measure of pollution. We are using a 3D chemistry and transport model driven by winds from the Goddard Space Flight Center Data Assimilation System to examine variability in the stratospheric NO2 column. Model results for NOx = NO + NO2 + 2N2O5 will be shown to compare well with sunset observations from the Halogen Occultation Experiment on the Upper Atmosphere Research Satellite, and to exhibit similar temporal and spatial dependence. Partitioning between NO, NO2, and N2O5 is also shown to compare well with observations. This good agreement supports the use of simulated fields in the stratosphere to derive the tropospheric column from the total column. Preliminary comparisons of the tropospheric column with model simulations for the troposphere will also be shown.
CloudSat is a satellite experiment designed to measure the vertical structure of clouds from space. The expected launch of CloudSat is planned for 2004 and, once launched, CloudSat will orbit in formation as part of a constellation of satellites including NASA's Aqua and Aura satellites, a NASA-CNES lidar satellite (P-C) and a CNES satellite carrying a polarimeter (PARASOL). A unique feature that CloudSat brings to this constellation is the ability to fly a precise orbit enabling the fields of view of the CloudSat radar to be overlapped with the P-C lidar footprint and the other measurements of the EOS constellation. The precision of this overlap creates a unique multi-satellite observing system for studying the atmospheric processes essential to the hydrological cycle. The vertical profile of cloud properties provided by CloudSat fills a critical gap in the investigation of feedback mechanisms linking clouds to climate. Measuring the vertical profile of cloud properties requires a combination of active and passive instruments, and this will be achieved by combining the radar data of CloudSat with active and passive data from other sensors of the constellation. This paper describes the underpinning science, and gives an overview of the mission, and provides some idea of the expected products and anticipated application of these products. Notably, the CloudSat mission is expected to provide new knowledge about global cloudiness, stimulating new areas of research on clouds including data assimilation and cloud parameterization. The mission also provides an important opportunity to demonstrate active sensor technology for future scientific and tactical applications. The CloudSat mission is a partnership between NASA/JPL, the Canadian Space Agency, Colorado State University, the US Air Force, and the US Department of Energy.
Ozone distributions derived from the Solar Backscatter UltraViolet/2 (SBUV/2) instruments and the Earth Probe Total Ozone Mapping Spectrometer (EP TOMS) have been assimilated in near-real time at the NASA/Goddard Data Assimilation Office since January 2000. Observed-minus-forecast (O-F) residuals are the differences between the incoming ozone data and the co-located short-term model forecast. They are routinely produced and monitored in the assimilation process. Using examples from the NOAA-14 and NOAA-16 SBUV/2 and the EP-TOMS instruments, it is demonstrated that the monitoring of time series of O-F residual statistics is an effective method of identifying time-dependent changes in the observation-error characteristics of ozone. In addition, the data assimilation system was used to assist the validation of updated calibration coefficients for the NOAA-14 SBUV/2 instrument. This assimilation-based monitoring work will be extended to ozone data from instruments on new satellites: Envisat EOS, Aqua, and EOS Aura.
Assimilated ozone is produced at the NASA/Goddard Data Assimilation Office by blending ozone retrieved from the Solar Backscatter UltraViolet/2 (SBUV/2) instrument and the Earth Probe Total Ozone Mapping Spectrometer (EP TOMS) measurements into an off-line transport model. The current system tends to overestimate the amount of lower stratospheric ozone. This is a region where ozone plays a key role in the forcing of climate. A biased ozone field in this region will adversely impact calculations of the stratosphere-troposphere exchange and, when used as a first guess in retrievals, the values determined from satellite observations. Since these are all important applications of assimilated ozone products, effort is being directed towards reducing this bias. The SBUV ozone data have a coarse vertical resolution with increased uncertainty below the ozone maximum, and TOMS provides only total ozone columns. Thus, the assimilated ozone in the lower stratosphere, and its vertical distribution in particular, are only weakly constrained by the incoming SBUV and TOMS data. Consequently, the assimilated ozone distribution should be sensitive to changes in inputs to the statistical analysis scheme. Accordingly, the sensitivity of the assimilated lower stratospheric ozone fields to changes in the TOMS error-covariance modeling and the SBUV data selection has been investigated. The use of a spatially correlated TOMS error covariance model led to improvements in the product. However, withholding the SBUV/2 data for the layer between 63 and 126 hPa typically degraded the product, a result which vindicates the use of this layer ozone product, despite its known errors. These efforts to improve the lower stratospheric distribution will be extended to include a more advanced forecast error covariance model, and by assimilating ozone products from new instruments on Envisat and EOS Aura.
The Upper Atmosphere Research Satellite (UARS) was launched in September 1991 by the Space Shuttle Discovery and continues to make relevant atmospheric measurements (as of October 2002). This successful satellite has fostered a better understanding of the middle atmospheric processes, especially those important in the control of ozone. Seven of the original ten instruments aboard the UARS are still functional and six instruments regularly make measurements. The UARS is in a stable observing configuration, in spite of experiencing several anomalies over its lifetime. It is expected that the UARS will overlap the Earth Observing System (EOS) Aura satellite (scheduled launch in January 2004) for several months before the end of the UARS mission.
The Goddard Earth Observing System Data Assimilation System (GEOS-DAS) timeseries is a globally gridded atmospheric data set for use in climate research. This near real-time data set is produced by the Data Assimilation Office (DAO) at the NASA Goddard Space Flight Center in direct support of the operational EOS instrument product generation from the Terra (12/1999 launch), Aqua (05/2002 launch) and Aura (01/2004 launch) spacecrafts. The data is archived in the EOS Core System (ECS) at the Goddard Earth Sciences Data and Information Services Center/Distributed Active Archive Center (GES DISC DAAC). The data is only a selection of the products available from the GEOS-DAS. The data is organized chronologically in timeseries format to facilitate the computation of statistics. GEOS-DAS data will be available for the time period January 1, 2000, through present.
We have been producing near-real tropical tropospheric ozone ('TTO') data from TOMS since 1997 with Prof. Hudson and students at the University of Maryland. Maps for 1996-2000 for the operational Earth-Probe instrument reside at: . We also have archived 'TTO' data from the Nimbus 7/TOMS satellite (1979-1992). The tropics is a region strongly influenced by natural variability and anthropogenic activity and the satellite data have been used to track biomass burning pollution and to detect interannual variability and climate signals in ozone. We look forward to future ozone sensors from NASA; four will be launched in 2004 as part of the EOS AURA Mission. The satellite view of chemical-dynamical interactions in tropospheric ozone is not adequate to capture vertical variability. Thus, in 1998, NASA's Goddard Space Flight Center, NOAA's Climate Monitoring and Diagnostics Laboratory (CMDL) and a team of international sponsors established the SHADOZ (Southern Hemisphere ADditional OZonesondes) project to address the gap in tropical ozone soundings. SHADOZ augments launches at selected sites and provides a public archive of ozonesonde data from twelve tropical and subtropical stations at http://croc.nsfc.nasa.gov/shadoz. The stations are: Ascension Island; Nairobi, Kenya; Irene, South Africa; R,union Island; Watukosek, Java; Fiji; Tahiti; American Samoa; San Cristobal, Galapagos; Natal, Brazil, Malindi, Kenya; Paramaribo, Surinam. From the first 3-4 years of data (presently greater than 1700 sondes), the following features emerge: (a) highly variable tropospheric ozone; (b) a zonal wave-one pattern in tropospheric column ozone; (c) tropospheric ozone variability over the Indian and Pacific Ocean displays strong convective signatures.
The Ozone Monitoring Instrument (OMI) is the Dutch-Finnish contribution to the NASA EOS-Aura mission scheduled for launch in January 2004. OM1 is an imaging spectrometer that will measure the back-scattered Solar radiance between 270 an 500 nm. With its relatively high spatial resolution (13x24 sq km at nadir) and daily global coverage. OM1 will make a major contribution to our understanding of atmospheric chemistry and to climate research. OM1 will provide data continuity with the TOMS instruments. One of the pleasant surprises of the TOMS data record was its information on aerosol properties. First, only the absorbing aerosol index, which is sensitive to elevated lay- ers of aerosols such as desert dust and smoke aerosols, was derived. Recently these methods were further improved to yield aerosol optical thickness and single scattering albedo over land and ocean for 19 years of TOMS data (1979-1992,1997-2002), making it one of the longest and most valuable time series for aerosols presently available. Such long time series are essential to quantify the effect of aerosols on the Earth& climate. The OM1 instrument is better suited to measure aerosols than the TOMS instruments because of the smaller footprint, and better spectral coverage. The better capabilities of OMI will enable us to provide an improved aerosol product, but the knowledge will also be used for further analysis of the aerosol record from TOMS. The OM1 aerosol product that is currently being developed for OM1 combines the TOMS experience and the multi-spectral techniques that are used in the visible and near infrared. The challenge for this new product is to provide aerosol optical thickness and single scattering albedo from the near ultraviolet to the visible (330-500 nm) over land and ocean. In this presentation the methods for deriving the OM1 aerosol product will be presented. Part of these methods developed for OM1 can already be applied to TOMS data and results of such analysis will be shown.
This talk will discuss assimilation of ozone data from satellite-borne instruments. Satellite observations of ozone total columns and profiles have been measured by a series of Total Ozone Mapping Spectrometer (TOMS), Solar Backscatter Ultraviolet (SBUV) instruments, and more recently by the Global Ozone Monitoring Experiment. Additional profile data are provided by instruments on NASA's Upper Atmosphere Research Satellite and by occultation instruments on other platforms. Instruments on Envisat' and future EOS Aura satellite will supply even more comprehensive data about the ozone distribution. Satellite data contain a wealth of information, but they do not provide synoptic global maps of ozone fields. These maps can be obtained through assimilation of satellite data into global chemistry and transport models. In the ozone system at NASA's Data Assimilation Office (DAO) any combination of TOMS, SBUV, and Microwave Limb sounder (MLS) data can be assimilated. We found that the addition of MLS to SBUV and TOMS data in the system helps to constrain the ozone distribution, especially in the polar night region and in the tropics. The assimilated ozone distribution in the troposphere and lower stratosphere is sensitive also to finer changes in the SBUV and TOMS data selection and to changes in error covariance models. All results are established by comparisons of assimilated ozone with independent profiles from ozone sondes and occultation instruments.
Our research focused on Kelvin waves in the tropical lower stratosphere, and resulted in three papers published or submitted to the Journal of Geophysical Research. The first of these, published in 2002, used temperature data from the Microwave Limb Sounder to examine the amplitude, frequency, phase, and spatial structure of leading modes of Kelvin waves. The second and third, submitted late in 2002 and currently in revision, described the response to Kelvin waves of various trace constituents measured by MLS and CLAES (methane, nitrous oxide, CFC-12, and ozone in the second paper; water vapor in the third paper). Water vapor is a special case because the vertical structure induced by Kelvin waves is convolved with water vapor's seasonally varying vertical profile induced by seasonal variations in temperature at the tropical tropopause. Forward modeling indicated that the vertical resolution of MLS was indeed adequate to capture this complicated structure, yet it was not visible in the MLS data, though the Kelvin wave signature was clear on certain UARS levels. The effects of Kelvin waves on the tropical tropopause and on stratosphere- troposphere exchange cannot be quantified from UARS data because of poor vertical resolution and sensitivity in that region. It is recommended that this analysis be repeated using data from the new MLS and HIRDLS instruments aboard Aura, and that priority be given to fine-scale retrievals of temperature, water vapor, and ozone in the tropical tropopause region.
This presentation poster covers data products from the Distributed Active Archive Center (DAAC) of the Goddard Earth Sciences (GES) Data and Information Services Center (DISC). Total Ozone Mapping Spectrometer products (TOMS) introduced in the presentation include TOMS Version 8 as well as Aura, which provides 25 years of TOMS and Upper Atmosphere Research Satellite (UARS) data. The presentation lists a number of atmospheric chemistry and dynamics data sets at DAAC.
The higher spectral resolution, coverage, and sampling of the Aura satellite ozone monitoring instrument (OMI), as compared with the total ozone mapping spectrometer (TOMS) should allow for improved ozone retrievals, including estimates of tropospheric ozone. By default, the TOMS-like OMI total column ozone algorithm uses climatological cloud-top pressures based on infrared (IR) measurements to estimate the column ozone below the clouds. Alternatively, cloud pressure can be retrieved using atmospheric rotational Raman scattering with OMI. The retrieved cloud pressures should be more consistent with assumptions made in the total ozone algorithm. Here, we use data from the global ozone monitoring experiment (GOME) to estimate total ozone using both the IR-climatological and retrieved cloud pressures. The exceed approximately 15 DU. Use of the UV cloud pressure retrievals leads to a smoother distribution of ozone along a satellite track by reducing small spatial irregularities presumably caused by errors in the climatological cloud pressures.