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NASA NTRS2010

Illumination Conditions of the Lunar Polar Regions Using LOLA Topography

We use high-resolution altimetry data obtained by the Lunar Orbiter Laser Altimeter instrument onboard the Lunar Reconnaissance Orbiter to characterize present illumination conditions in the polar regions of the Moon. Compared to previous studies, both the spatial and temporal extent of the simulations are increased significantly, as well as the coverage (fill ratio) of the topographic maps used, thanks to the 28 Hz firing rate of the five-beam instrument. We determine the horizon elevation in a number of directions based on 240 m-resolution polar digital elevation models reaching down to 75 latitude. The illumination of both polar regions extending to 80 can be calculated for any geometry from those horizon longitudinal profiles. We validated our modeling with recent Lunar Reconnaissance Orbiter Wide-Angle Camera images. We assessed the extent of permanently shadowed regions (PSRs, defined as areas that never receive direct solar illumination), and obtained total areas generally larger than previous studies (12,866 and 16,055 sq. km, in the north and south respectively). We extended our direct illumination model to account for singly-scattered light, and found that every PSR does receive some amount of scattered light during the year. We conducted simulations over long periods (several 18.6-years lunar precession cycles) with a high temporal resolution (6 h), and identified the most illuminated locations in the vicinity of both poles. Because of the importance of those sites for exploration and engineering considerations, we characterized their illumination more precisely over the near future. Every year, a location near the Shackleton crater rim in the south polar region is sunlit continuously for 240 days, and its longest continuous period in total darkness is about 1.5 days. For some locations small height gains ( 10 m) can dramatically improve their average illumination and reduce the night duration, rendering some of those particularly attractive energy-wise as possible sites for near-continuous sources of solar power.

E. Mazarico↗

NASA NTRS2021

Global Soil Water Estimates as Landslide Predictor: The Effectiveness of SMOS, SMAP, and GRACE Observations, Land Surface Simulations, and Data Assimilation

This global feasibility study assesses the potential of coarse-scale, gridded soil water estimates for the probabilistic modeling of hydrologically-triggered landslides, using Soil Moisture Ocean Salinity (SMOS), Soil Moisture Active Passive (SMAP) and Gravity Recovery and Climate Experiment (GRACE) remote sensing data, Catchment Land Surface Model (CLSM) simulations and six data products based on the assimilation of SMOS, SMAP, and/or GRACE observations into CLSM. SMOS or SMAP observations (~40-km resolution) are only available for less than 20% of the globally reported landslide events, because they are intermittent and uncertain in regions with complex terrain. GRACE terrestrial water storage estimates include 75% of the reported landslides but have coarse spatial and temporal resolutions (monthly, ~300-km). CLSM soil water simulations have the added advantage of complete spatial and temporal coverage, and are found to be able to distinguish between “stable slope” (no landslide) conditions and landslide-inducing conditions in a probabilistic way. Assimilating SMOS and/or GRACE data increases the landslide probability estimates based on soil water percentiles for the reported landslides, relative to model-only estimates at 36-km resolution for the period 2011-2016, unless the CLSM model-only soil water content is already high (≥ 50th percentile). The SMAP Level 4 data assimilation product (at 9-km resolution, period 2015-2019) more generally updates the soil water conditions towards higher landslide probabilities for the reported landslides, but is similar to model-only estimates for the majority of landslides where SMAP data cannot easily be converted to soil moisture owing to complex terrain.

Anne Felsberg↗

NASA NTRS1992

Images and topographic relief at the north pole of Venus

The analysis of unique coverage of the north pole of Venus using a subset of 13 images from a total of about 775 synthetic aperture radar orbits during cycle 1 of the Magellan mission is reported. Images at 13 distinctly different azimuths are reported that range over 360 deg in longitude and that show the topographic relief at vastly different imaging geometries at intervals of about 20 deg. A pair of intersecting or crossing orbits is used to assess the topographic relief with stereo radargrammetric techniques, and to refine this assessment using a multiimage clinometric approach. It is shown that the pole is located in accentuated topography with elevation differences in the range of no more than 1 km. It is concluded that pinpointing the location of the pole from the overlapping images and standard mission data is accurate to within about 100 pixels or 8 km (RMS).

Leberl, Franz W.↗

NASA NTRS2011

Landsat Data Continuity Mission

The Landsat Data Continuity Mission (LDCM) is currently under development and is on schedule to launch the 8th satellite in the Landsat series in December of 2012. LDCM is a joint project between the National Aeronautics and Space Administration (NASA) and the United States Geological Survey (USGS). NASA is responsible for developing and launching the flight hardware and on-orbit commissioning and USGS is responsible for developing the ground system and operating the system onorbit after commissioning. Key components of the flight hardware are the Operational Land Imager (OLI), nearing completion by Ball Aerospace & Technologies Corp in Boulder, CO, the Thermal Infrared Sensor (TIRS), being built by NASA's Goddard Space Flight Center and the spacecraft, undergoing integration at Orbital Sciences Corp in Gilbert, Arizona. The launch vehicle will be an Atlas-5 with launch services provided by NASA's Kennedy Space Center. Key ground systems elements are the Mission Operations Element, being developed by the Hammers Corporation, and the Collection Activity Planning Element, Ground Network Element, and Data Processing and Archive System, being developed internally by the USGS Earth Resources Observations and Science (EROS) Center. The primary measurement goal of LDCM is to continue the global coverage of moderate spatial resolution imagery providing continuity with the existing Landsat record. The science goal for this imagery is to monitor land use and land cover, particularly as it relates to global climate change. Together the OLI and TIRS instruments on LDCM replace the ETM+ instrument on Landsat-7 with significant enhancements. The OLI is a pushbroom design instrument where the scanning mechanism of the ETM+ is effectively replaced by a long line of detectors. The OLI has 9 spectral bands with similar spatial resolution to ETM+: 7 of them similar to the reflective spectral bands on ETM+ and two new bands. The two new bands cover (1) the shorter wavelength blue part of the spectrum to help with coastal studies and aerosol analyses/atmospheric correction and (2) an atmospheric water absorption band, where the Earth surface is generally not visible, but Cirrus clouds are, to aid in cloud detection and screening. The radiometry of OLI benefits from improved SNR, dynamic range and quantization. OLI is undergoing system testing with a delivery scheduled for Spring 2011. The TIRS is also a pushbroom design and used QWIPS detectors that require cooling to 43K using a cryocooler. It.has two spectral bands, effectively splitting the ETM+ band 6 in half, that can be used as a split window to aid in atmospheric correction. It has nominally 100 m spatial resolution as opposed to the 60 m of Landsat-7 ETM+: TIRS has commenced integration and test, with a delivery to the spacecraft vendor scheduled for Winter 2011-2012. The Orbital spacecraft currently being integrated for LDCM will have improved capabilities for pointing over previous missions. These capabilities will allow the OLI and TIRS instruments to point off-nadir the equivalent of one WRS-2 path to increase the chances of coverage for high priority targets, particularly in the event of natural disasters. Also, the pointing capability will allow the calibration of the OLI using the sun (roughly weekly), the moon (monthly), stars (during commissioning) and the Earth (at 90 deg from normal orientation, a.k.a., side slither) quarterly. The solar calibration will be used for OLI absolute and relative calibration, the moon for trending the stability of the OLI response, the stars will be used for Line of Sight determination and the side slither will be an alternate OLI and relative gain determination methodology. The spacecraft is scheduled to begin integration with the OLI instrument in Summer 2011. The LDCM data processing and archive system (DPAS), located at USGS EROS, generates the products for distribution to users. Like Landsat-7 this includes an image assessment system for characrizing instrument performance and updating calibration parameters. Products will be generated that include the spectral bands from both instruments, terrain corrected and registered to the geoid. Also, like Landsat-7, data products will be distributed at no charge to the user. The current status and plans of the space and ground segments of the LDCM project will be presented along with performance predictions as available. More detailed information on the two instruments is intended to be presented in separate papers.

Markham, Brian↗

NASA NTRS2019

The Updated GEO Population for ORDEM 3.1

The limited availability of data for satellite fragmentations and debris in the geosynchronous orbit (GEO) region creates challenges to building accurate models for the orbital debris environment at such altitudes. Updated methods to properly incorporate and extrapolate measurement data have become a cornerstone of the GEO component in the newest version of the NASA Orbital Debris Engineering Model (ORDEM), ORDEM 3.1. For the GEO region, the Space Surveillance Network (SSN) catalog provides coverage down to a limit of approximately 1 m. A more statistically complete representation of the GEO population for smaller objects, which can pose a high risk to operational spacecraft, is thus dependent on dedicated observations by instruments optimized to observe debris smaller than the SSN cataloging threshold. For ORDEM 3.1, optical data from the Michigan Orbital DEbris Survey Telescope (MODEST) provided the input for building the GEO population down to approximately 30 cm (converting absolute magnitude to size). For smaller sizes, the size distribution of debris in the MODEST dataset was extrapolated down to 10 cm, and orbital parameters were estimated based on the orbits of the larger objects. When compared to previous versions of the model, significant improvements were made to the process of building the GEO population in ORDEM 3.1, both in the assessment of fragmentation debris in the data and assignment of orbital elements within the model. A so-called “debris ring filter,” based on a range of angles between an orbit’s angular momentum vector and that of the stable Laplace plane, was applied to the data to reduce biases from non- GEO objects, such as objects in a GEO-transfer orbit. In addition, a new approach was implemented to assign noncircular mean motions and eccentricities to the fragmentation debris observed by MODEST because the short observation window (5 min) in GEO limits orbit resolution to a circular orbit assumption for assigning orbital parameters. For ORDEM 3.1, non-circular orbital elements were assigned using relationships that were identified between mean motion and the angle between the orbit plane and the stable Laplace plane, as well as between mean motion and eccentricity, based on breakup clouds modeled by the NASA Standard Breakup Model. This approach has yielded a high-fidelity GEO model that has been validated with data from more recent MODEST observation campaigns.

Manis, A.↗

NASA NTRSDate not supplied

Experimental Testing of Data Fusion in A Distributed Ground-Based Sensing Network for Advanced Air Mobility

Advanced Air Mobility (AAM) is an active area of development which foresees the integration of autonomous uncrewed aircraft into the civil airspace for air transportation of people and cargo. Safe integration requires significant technological developments and extensive testing phases of sensing and surveillance strategies in dense airspace. Compared to well-assessed manned aviation systems scenarios, surveillance strategies in the AAM and small Uncrewed Aircraft Vehicles(UAVs) context need to detect smaller platforms flying at lower altitude against cluttered backgrounds in dense airspace. Fusion of data provided by a network of distributed sensing nodes is a powerful tool to enable detection and tracking in such complex conditions. This paper contributes to this research direction by proposing a surveillance strategy for the AAM environment based on sensor fusion of data acquired by distributed ground-based radars. Specifically, experimental data collected with two independent radars, observing the flight of two small UAVs, are used. Data fusion at tracking level is based on a leader-helper strategy where the leader radar uses the helper’s measurements to increase the lifespan of its generated tracks. This solution shows promising results with a 10%increase in track coverage with respect to the standalone leader radar tracking solution. The paper also proposes an interference removal processing method which is applied on the data collected by one of the two radars.

Federica Vitiello↗

NASA NTRS2025

Demonstration of Data Processing and Fusion from Distributed Radars for AAM Surveillance

Advanced Air Mobility (AAM) is an active area of development which foresees the integration of autonomous uncrewed aircraft into the civil airspace for air transportation of people and cargo. Safe integration requires significant technological developments and extensive testing phases of sensing and surveillance strategies in dense airspace. Compared to well-assessed manned aviation systems scenarios, surveillance strategies in the AAM and small Uncrewed Aircraft Vehicles (UAVs) context need to detect smaller platforms flying at lower altitude against cluttered backgrounds in dense airspace. Fusion of data provided by a network of distributed sensing nodes is a powerful tool to enable detection and tracking in such complex conditions. This paper contributes to this research direction by proposing a surveillance strategy for the AAM environment based on sensor fusion of data acquired by distributed ground-based radars. Specifically, experimental data collected with three independent radars, observing the flight of two small UAVs, are used. Data fusion at tracking level is based on a leader-helper strategy where the leader radar uses the helper’s measurements to increase the lifespan of its generated tracks. This solution shows promising results with a 10% increase in track coverage with respect to the standalone leader radar tracking solution. The paper also proposes an interference removal processing method which is applied on the data collected by two of the radars.

Federica Vitiello↗

NASA NTRS1996

Cygnus X-1: A Case for a Magnetic Accretion Disk?

With the advent of Rossi X-ray Timing Explorer (RXTE), which is capable of broad spectral coverage and fast timing, as well as other instruments which are increasingly being used in multi-wavelength campaigns (via both space-based and ground-based observations), we must demand more of our theoretical models. No current model mimics all facets of a system as complex as an x-ray binary. However, a modern theory should qualitatively reproduce - or at the very least not fundamentally disagree with - all of Cygnus X-l's most basic average properties: energy spectrum (viewed within a broader framework of black hole candidate spectral behavior), power spectrum (PSD), and time delays and coherence between variability in different energy bands. Below we discuss each of these basic properties in turn, and we assess the health of one of the currently popular theories: Comptonization of photons from a cold disk. We find that the data pose substantial challenges for this theory, as well as all other in currently discussed models.

Nowak, Michael A.↗

NASA NTRS1987

Orbit determination accuracy assessment for an asteroid flyby - A Galileo case study

The Galileo spacecraft may be targeted for a close flyby of an asteroid on its way to an encounter with Jupiter. An orbit determination accuracy analysis was carried out for the case of the asteroid 29 Amphitrite based on the use of radio metric and optical data types. Prior to encounter, the uncertainty in the asteroid's position, based on astrometric observations from earth, amounts to several hundred kilometers. This ephemeris uncertainty constitutes the dominant error in the determination of the spacecraft orbit with respect to Amphitrite. It is shown that the spacecraft-asteroid relative position can be improved by imaging asteroid-star pairs with the Galileo charge-coupled device (CCD) camera, enabling an accurate flyby of the asteroid. The main benefit of optical navigation is to enable the instrument pointing updates necessary for closeup viewing of the asteroid. A discussion of the evolution of the target error ellipse parameters as a function of data coverage and various combinations of radiometric and optical data types is also presented.

Kechichian, Jean A.↗

NASA NTRS2012

Quantifying Above-Cloud Aerosols through Integrating Multi-Sensor Measurements from A-Train Satellites

Quantifying above-cloud aerosols can help improve the assessment of aerosol intercontinental transport and climate impacts. Large-scale measurements of aerosol above low-level clouds had been generally unexplored until very recently when CALIPSO lidar started to acquire aerosol and cloud profiles in June 2006. Despite CALIPSO s unique capability of measuring above-cloud aerosol optical depth (AOD), such observations are substantially limited in spatial coverage because of the lidar s near-zero swath. We developed an approach that integrates measurements from A-Train satellite sensors (including CALIPSO lidar, OMI, and MODIS) to extend CALIPSO above-cloud AOD observations to substantially larger areas. We first examine relationships between collocated CALIPSO above-cloud AOD and OMI absorbing aerosol index (AI, a qualitative measure of AOD for elevated dust and smoke aerosol) as a function of MODIS cloud optical depth (COD) by using 8-month data in the Saharan dust outflow and southwest African smoke outflow regions. The analysis shows that for a given cloud albedo, above-cloud AOD correlates positively with AI in a linear manner. We then apply the derived relationships with MODIS COD and OMI AI measurements to derive above-cloud AOD over the whole outflow regions. In this talk, we will present spatial and day-to-day variations of the above-cloud AOD and the estimated direct radiative forcing by the above-cloud aerosols.

Zhang, Yan↗

NASA NTRSDate not supplied

Using NASA LANCE Near Real-Time Earth Observations for Disaster Risk Reduction

The NASA Earth Science Disasters Program handles requests from stakeholders and provides rapid response for Disaster Risk Reduction using Near Real-Time (NRT) products from NASA’s Land, Atmosphere NRT Capability for Earth Observing System (EOS) (LANCE). The combination of all available LANCE NRT satellite products provides global coverage at multiple times per day, which makes it possible to help users in different phases of the disaster’s life cycle. For wildfires and volcano eruption disasters, LANCE NRT fire and atmosphere products have been used to locate fires and high-temperature heat sources, and to assess the extent of air pollutions. Knowledge of the geographical position and direction of smokes, fires, lava flows provided critical information for disaster prediction and prevention. For hurricanes, tropical cyclones and earthquakes, LANCE global flood products and NASA’s Black Marble night-time light products have been used for monitoring land cover and land use change over time in disaster impacted areas. Users can use pre- and post-disaster maps to assess the extent of damage, and to make decisions for activities in reconstruction and recovery in infrastructure and health on the ground. LANCE NRT data are made available through the Earth data website and have been archived and visualized in NASA Disasters Mapping Portal, NASA LANCE Fire Information for Resource Management System (FIRMS) and NASA Worldview for the use of stakeholders.

Tian Yao↗

NASA NTRS2013

Comparison of Four Precipitation Forcing Datasets in Land Information System Simulations over the Continental U.S.

This paper and poster presented a description of the current real-time SPoRT-LIS run over the southeastern CONUS to provide high-resolution, land surface initialization grids for local numerical model forecasts at NWS forecast offices. The LIS hourly output also offers a supplemental dataset to aid in situational awareness for convective initiation forecasts, assessing flood potential, and monitoring drought at fine scales. It is a goal of SPoRT and several NWS forecast offices to expand the LIS to an entire CONUS domain, so that LIS output can be utilized by NWS Western Region offices, among others. To make this expansion cleanly so as to provide high-quality land surface output, SPoRT tested new precipitation datasets in LIS as an alternative forcing dataset to the current radar+gauge Stage IV product. Similar to the Stage IV product, the NMQ product showed comparable patterns of precipitation and soil moisture distribution, but suffered from radar gaps in the intermountain West, and incorrectly set values to zero instead of missing in the data-void regions of Mexico and Canada. The other dataset tested was the next-generation GOES-R QPE algorithm, which experienced a high bias in both coverage and intensity of accumulated precipitation relative to the control (NLDAS2), Stage IV, and NMQ simulations. The resulting root zone soil moisture was substantially higher in most areas.

Case, Jonathan L.↗

NASA NTRS2012

Integrating NASA Satellite Data Into USDA World Agricultural Outlook Board Decision Making Environment To Improve Agricultural Estimates

The USDA World Agricultural Outlook Board (WAOB) is responsible for monitoring weather and climate impacts on domestic and foreign crop development. One of WAOB's primary goals is to determine the net cumulative effect of weather and climate anomalies on final crop yields. To this end, a broad array of information is consulted. The resulting agricultural weather assessments are published in the Weekly Weather and Crop Bulletin, to keep farmers, policy makers, and commercial agricultural interests informed of weather and climate impacts on agriculture. The goal of the current project is to improve WAOB estimates by integrating NASA satellite precipitation and soil moisture observations into WAOB's decision making environment. Precipitation (Level 3 gridded) is from the TRMM Multi-satellite Precipitation Analysis (TMPA). Soil moisture (Level 2 swath and Level 3 gridded) is generated by the Land Parameter Retrieval Model (LPRM) and operationally produced by the NASA Goddard Earth Sciences Data and Information Services Center (GBS DISC). A root zone soil moisture (RZSM) product is also generated, via assimilation of the Level 3 LPRM data by a land surface model (part of a related project). Data services to be available for these products include GeoTIFF, GDS (GrADS Data Server), WMS (Web Map Service), WCS (Web Coverage Service), and NASA Giovanni. Project benchmarking is based on retrospective analyses of WAOB analog year comparisons. The latter are between a given year and historical years with similar weather patterns and estimated crop yields. An analog index (AI) was developed to introduce a more rigorous, statistical approach for identifying analog years. Results thus far show that crop yield estimates derived from TMPA precipitation data are closer to measured yields than are estimates derived from surface-based precipitation measurements. Work is continuing to include LPRM surface soil moisture data and model-assimilated RZSM.

Teng, William↗

NASA NTRS2018

Aircraft System Noise Prediction Uncertainty Quantification for a Hybrid Wing Body Subsonic Transport Concept

Aircraft system level noise prediction for advanced, unconventional concepts has undergone significant improvement over the past two decades. The prediction modeling uncertainty must be quantified so that potential benefits of unconventional configurations, which are outside of the range of empirical models, can be reliably assessed. This paper builds on previous work in an effort to improve estimates of element prediction uncertainties where the prediction methodology has been improved, or new experimental validation data are available, to provide an estimate of the system level uncertainty in the prediction process. In general, the uncertainty of the prediction will be strongly dependent on the aircraft configuration as well as which technologies are integrated. While the quantitative uncertainty values contained here are specific to the hybrid wing body design presented, the underlying process is the same regardless of configuration. A refined process for determining the uncertainty for each element of the noise prediction is detailed in this paper. The system level uncertainty in the prediction of the aircraft noise is determined at the three certification points, using a Monte Carlo method. Comparisons with previous work show a reduction of 1 EPNdB in the 95%coverage interval of the cumulative noise level. The largest impediment for continued reduction in uncertainty for the hybrid wing body concept is the need for improved modeling and validation experiments for fan noise, propulsion airframe aeroacoustic effects, and the Krueger flap, which comprise the bulk of the uncertainty in the cumulative certification noise level.

June, Jason C.↗

NASA NTRS2011

Signal Processing Methods for Liquid Rocket Engine Combustion Stability Assessments

The J2X Gas Generator engine design specifications include dynamic, spontaneous, and broadband combustion stability requirements. These requirements are verified empirically based high frequency chamber pressure measurements and analyses. Dynamic stability is determined with the dynamic pressure response due to an artificial perturbation of the combustion chamber pressure (bomb testing), and spontaneous and broadband stability are determined from the dynamic pressure responses during steady operation starting at specified power levels. J2X Workhorse Gas Generator testing included bomb tests with multiple hardware configurations and operating conditions, including a configuration used explicitly for engine verification test series. This work covers signal processing techniques developed at Marshall Space Flight Center (MSFC) to help assess engine design stability requirements. Dynamic stability assessments were performed following both the CPIA 655 guidelines and a MSFC in-house developed statistical-based approach. The statistical approach was developed to better verify when the dynamic pressure amplitudes corresponding to a particular frequency returned back to pre-bomb characteristics. This was accomplished by first determining the statistical characteristics of the pre-bomb dynamic levels. The pre-bomb statistical characterization provided 95% coverage bounds; these bounds were used as a quantitative measure to determine when the post-bomb signal returned to pre-bomb conditions. The time for post-bomb levels to acceptably return to pre-bomb levels was compared to the dominant frequency-dependent time recommended by CPIA 655. Results for multiple test configurations, including stable and unstable configurations, were reviewed. Spontaneous stability was assessed using two processes: 1) characterization of the ratio of the peak response amplitudes to the excited chamber acoustic mode amplitudes and 2) characterization of the variability of the peak response's frequency over the test duration. This characterization process assists in evaluating the discreteness of a signal as well as the stability of the chamber response. Broadband stability was assessed using a running root-mean-square evaluation. These techniques were also employed, in a comparative analysis, on available Fastrac data, and these results are presented here.

Kenny, R. Jeremy↗

NASA NTRS2011

Future Opportunities and Challenges in Remote Sensing of Drought

The value of satellite remote sensing for drought monitoring was first realized more than two decades ago with the application of Normalized Difference Index (NDVI) data from the Advanced Very High Resolution Radiometer (AVHRR) for assessing the effect of drought on vegetation. Other indices such as the Vegetation Health Index (VHI) were also developed during this time period, and applied to AVHRR NDVI and brightness temperature data for routine global monitoring of drought conditions. These early efforts demonstrated the unique perspective that global imagers such as AVHRR could provide for operational drought monitoring through their near-daily, global observations of Earth's land surface. However, the advancement of satellite remote sensing of drought was limited by the relatively few spectral bands of operational global sensors such as AVHRR, along with a relatively short period of observational record. Remote sensing advancements are of paramount importance given the increasing demand for tools that can provide accurate, timely, and integrated information on drought conditions to facilitate proactive decision making (NIDIS, 2007). Satellite-based approaches are key to addressing significant gaps in the spatial and temporal coverage of current surface station instrument networks providing key moisture observations (e.g., rainfall, snow, soil moisture, ground water, and ET) over the United States and globally (NIDIS, 2007). Improved monitoring capabilities will be particularly important given increases in spatial extent, intensity, and duration of drought events observed in some regions of the world, as reported in the International Panel on Climate Change (IPCC) report (IPCC, 2007). The risk of drought is anticipated to further increase in some regions in response to climatic changes in the hydrologic cycle related to evaporation, precipitation, air temperature, and snow cover (Burke et al., 2006; IPCC, 2007; USGCRP, 2009). Numerous national, regional, and global efforts such as the Famine and Early Warning System (FEWS), National Integrated Drought Information System (NIDIS), and Group on Earth Observations (GEO), as well as the establishment of regional drought centers (e.g., European Drought Observatory) and geospatial visualization and monitoring systems (e.g, NASA SERVIR) have been undertaken to improve drought monitoring and early warning systems throughout the world. The suite of innovative remote sensing tools that have recently emerged will be looked upon to fill important data and knowledge gaps (NIDIS, 2007; NRC, 2007) to address a wide range of drought-related issues including food security, water scarcity, and human health.

Wardlow, Brian D.↗

NASA NTRS1990

High-accuracy, high-resolution gravity profiles from 2 years of the Geosat Exact Repeat Mission

Satellite altimeter data from the first 44 repeat cycles (2 years) of the Geosat Exact Repeat Mission (EWRM) were averaged to improve accuracy, resolution and coverage of the marine gravity field. Individual 17-day repeat cycles were first edited and differentiated, resulting in the along-track vertical deflection (i.e., gravity disturbance). To increase the signal-to-noise ratio, 44 of these cycles were then averaged to form a single highly accurate vertical deflection profile. The largest contribution to the vertical deflection error is short-wavelength altimeter noise and longer-wavelength oceanographic variability; the combined noise level is typically 6 microrad. Both types of noise are reduced by averaging many repeat cycles. Over most ocean areas the uncertainty of the average profile is less than 1 microrad which corresponds to 1 mgal of along-track gravity disturbance. However, in areas of seasonal ice coverage, its uncertainty can exceed 5 microrad. To assess the resolution of individual and average Geosat gravity profiles, the cross-spectral analysis technique was applied to repeat profiles. Individual Geosat repeat cycles are coherent (greater than 0.5) for wavelengths greater than about 30 km and become increasingly incoherent at shorter wavelengths.

Sandwell, David T.↗

NASA NTRS2013

Assessment and Applications of NASA Ozone Data Products Derived from Aura OMI-MLS Satellite Measurements in Context of the GMI Chemical Transport Model

Measurements from the Ozone Monitoring Instrument (OMI) and Microwave Limb Sounder (MLS), both onboard the Aura spacecraft, have been used to produce daily global maps of column and profile ozone since August 2004. Here we compare and evaluate three strategies to obtain daily maps of tropospheric and stratospheric ozone from OMI and MLS measurements: trajectory mapping, direct profile retrieval, and data assimilation. Evaluation is based upon an assessment that includes validation using ozonesondes and comparisons with the Global Modeling Initiative (GMI) chemical transport model (CTM). We investigate applications of the three ozone data products from near-decadal and inter-annual timescales to day-to-day case studies. Zonally averaged inter-annual changes in tropospheric ozone from all of the products in any latitude range are of the order 1-2 Dobson Units while changes (increases) over the 8-year Aura record investigated http://eospso.gsfc.nasa.gov/atbd-category/49 vary approximately 2-4 Dobson Units. It is demonstrated that all of the ozone products can measure and monitor exceptional tropospheric ozone events including major forest fire and pollution transport events. Stratospheric ozone during the Aura record has several anomalous inter-annual events including stratospheric warming split events in the Northern Hemisphere extra-tropics that are well captured using the data assimilation ozone profile product. Data assimilation with continuous daily global coverage and vertical ozone profile information is the best of the three strategies at generating a global tropospheric and stratospheric ozone product for science applications.

GMI↗