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At least 199 records · Page 11

Topographic Map Generation from the Shuttle Radar Topography Mission C-band SCANSAR Interferometry

A highly accurate global topographic map of the Earth's surface has been an elusive goal for at least three decades that may soon be achieved with the newly acquired Shuttle Radar Topographic Mission (SRTM) data. SRTM collected data for 99.97% of the Earth's landmass between -57 degrees and 60 degrees latitude during a 11 day mission in February, 2000. A modified version of the SIR-C radar that previously flew on the shuttle in 1994 augmented with a radar mounted on a 62 m boom was used to collect radar interferometric data at C (5.6 cm wavelength) and X (3 cm wavelength) bands. The C-band radar was operated in the SCANSAR mode in order to extend the swath width to 225 km the minimal amount required to achieve contiguous coverage at the equator. This paper presents an overview of the new algorithms and techniques used to process the SCANSAR data to digital elevation maps. First results of topographic maps generated from the SRTM data are used to illustrate the techniques described in this paper.

Hensley, Scott↗

An alternative multi-mode SAR for RADARSAT

The RADARSAT project was asked by the Canadian government in the spring of 1986 to design for reduced costs and increased radar performance as compared to the well-known baseline design. Both the Project Office and Canadian industry (lead by SPAR Aerospace of Montreal) have undertaken to meet this request, with a proposal to cabinet to be submitted in the fall of 1986. One alternative SAR concept is outlined which is under consideration for a revised RADARSAT configuration. The radar system described uses two frequencies (C&L band) over four possible modes: near range swath; far range swath; wide swath; and high resolution. Good sensitivity, resolution, and coverage are obtained with modest power and data rates. The antenna systems are relatively simple. Indeed, no break-through technological developments are needed. The design allows several mode combinations for simultaneous data collection or performance enhancement. The principal parameters are described. A nominal mean altitude of 700 km is assumed.

Raney, R. K.↗

SPoRT Participation in the GOES-R and JPSS Proving Grounds

For the last several years, the NASA Short-term Prediction Research and Transition (SPoRT) project at has been working with the various algorithm working groups and science teams to demonstrate the utility of future operational sensors for GOES-R and the suite of instruments for the JPSS observing platforms. For GOES-R, imagery and products have been developed from polar-orbiting sensors such as MODIS and geostationary observations from SEVIRI, simulated imagery, enhanced products derived from existing GOES satellites, and data from ground-based observing systems to generate pseudo or proxy products for the ABI and GLM instruments. The suite of products include GOES-POES basic and RGB hybrid imagery, total lightning flash products, quantitative precipitation estimates, and convective initiation products. SPoRT is using imagery and products from VIIRS, CrIS, ATMS, and OMPS to show the utility of data and products from their operational counterparts on JPSS. The products include VIIRS imagery in swath form, the GOES-POES hybrid, a suite of RGB products including the air mass RGB using water vapor and ozone channels from CrIS, and several DNB products. Over a dozen SPoRT collaborative WFOs and several National Centers are involved in an intensive evaluation of the operational utility of these products.

Jedlovec, Gary↗

Performance of an airborne imaging 92/183 GHz radiometer during the Bering Sea Marginal Ice Zone Experiment (MIZEX-WEST)

An airborne imaging 92/183 GHz radiometer was recently flown onboard NASA's Convair 990 research aircraft during the February 1983 Bering Sea Marginal Ice Zone Experiment (MIZEX-WEST). The 92 GHz portion of the radiometer was used to gather ice signature data and to generate real-time millimeter wave images of the marginal ice zone. Dry atmospheric conditions in the Arctic resulted in good surface ice signature data for the 183 GHz double sideband (DSB) channel situated + or - 8.75 GHz away from the water vapor absorption line. The radiometer's beam scanner imaged the marginal ice zone over a + or - 45 degrees swath angle about the aircraft nadir position. The aircraft altitude was 30,000 feet (9.20 km) maximum and 3,000 feet (0.92 km) minimum during the various data runs. Calculations of the minimum detectable target (ice) size for the radiometer as a function of aircraft altitude were performed. In addition, the change in the atmospheric attenuation at 92 GHz under varying weather conditions was incorporated into the target size calculations. A radiometric image of surface ice at 92 GHz in the marginal ice zone is included.

Gagliano, J. A.↗

The Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS) on the Landsat Data Continuity Mission (LDCM)

The Landsat Data Continuity Mission (LDCM), a joint NASA and United States Geological Survey (USGS) mission, is scheduled for launch in December, 2012. The LDCM instrument payload will consist of the Operational Land Imager (OLI), provided by Ball Aerospace and Technology Corporation (BATC) under contract to NASA and the Thermal Infrared Sensor (TIRS), provided by NASA's Goddard Space Flight Center (GSFC). This paper will describe the design, capabilities and status of the OLI and TIRS instruments. The OLI will provide 8 channel multispectral images at a spatial resolution of 30 meters and panchromatic images at 15 meter spatial resolution. The TIRS is a 100 meter spatial resolution push-broom imager whose two spectral channels, centered at 10.8 and 12 microns, split the ETM+ thermal bands. The two channels allow the use of the "split-window" technique to aid in atmospheric correction. The TIRS focal plane consists of three Quantum Well Infrared Photodetector (QWIP) arrays to span the 185 km swath width. The OLI and TIRS instruments will be operated independently but in concert with each other. Data from both instruments will be merged into a single data stream at the (USGS)/Earth Resources Observation and Science (EROS) facility. The ground system, being developed by USGS, includes an Image Assessment System (lAS), similar to Landsat-7's, to operationally monitor, characterize and update the calibrations of the two sensors.

Reuter, Dennis↗

Satellite-derived surface energy balance estimates in the Alaskan sub-Arctic

The capabilities of the heat capacity mapping mission (HCMM) satellite are described, together with the numerical model used for data analysis. The HCMM carries the HCM radiometer for remote sensing in the visible and 0.55-1.1 micron wavelength regions, as well as in the 10.5-12.5 micron interval, with the swath being 720 km and each pixel being a square 500 m on a side. The HCMM is intended to aid in hydrological studies of soil moisture, runoff, and evapotranspiration estimates. Data are taken of the albedos and temperatures of vegetation, assuming that all reflection is diffuse. Corrections are made in the algorithm to account for sun angle and the spacecraft distance from the earth. Sample calculations are provided from scans of a coastal plain, mountains, and plateaus of Alaska.

Gurney, R. J.↗

Fast Simulators for Satellite Cloud Optical Centroid Pressure Retrievals, 1. Evaluation of OMI Cloud Retrievals

We have developed a relatively simple scheme for simulating retrieved cloud optical centroid pressures (OCP) from satellite solar backscatter observations. We have compared simulator results with those from more detailed retrieval simulators that more fully account for the complex radiative transfer in a cloudy atmosphere. We used this fast simulator to conduct a comprehensive evaluation of cloud OCPs from the two OMI algorithms using collocated data from CloudSat and Aqua MODIS, a unique situation afforded by the A-train formation of satellites. We find that both OMI algorithms perform reasonably well and that the two algorithms agree better with each other than either does with the collocated CloudSat data. This indicates that patchy snow/ice, cloud 3D, and aerosol effects not simulated with the CloudSat data are affecting both algorithms similarly. We note that the collocation with CloudSat occurs mainly on the East side of OMI's swath. Therefore, we are not able to address cross-track biases in OMI cloud OCP retrievals. Our fast simulator may also be used to simulate cloud OCP from output generated by general circulation models (GCM) with appropriate account of cloud overlap. We have implemented such a scheme and plan to compare OMI data with GCM output in the near future.

Joiner, J.↗

Issues in Data Fusion for Satellite Aerosol Measurements for Applications with GIOVANNI System at NASA GES DISC

We look at issues, barriers and approaches for Data Fusion of satellite aerosol data as available from the GES DISC GIOVANNI Web Service. Daily Global Maps of AOT from a single satellite sensor alone contain gaps that arise due to various sources (sun glint regions, clouds, orbital swath gaps at low latitudes, bright underlying surfaces etc.). The goal is to develop a fast, accurate and efficient method to improve the spatial coverage of the Daily AOT data to facilitate comparisons with Global Models. Data Fusion may be supplemented by Optimal Interpolation (OI) as needed.

Gopalan, Arun↗

The imaging spectrometer approach

Two important sensor design drivers are the requirement for spatial registration of the spectral components and the implementation of the advanced multispectral capability, including spectral band width, number of bands and programmability. The dispersive approach, fundamental to the imaging spectrometer concept, achieves these capabilities by utilizing a spectrometer to disperse the spectral content while preserving the spatial identity of the information in the cross-track direction. Area array detectors in the spectrometer focal plane detect and store the spatial and multispectral content for each line of the image. The choice of spectral bands, image IFOV and swath width is implemented by programmed readout of the focal plane. These choices in conjunction with data compression are used to match the output data rate with the telemetry link capability. Progress in the key technologies of optics, focal plane detector arrays, onboard processing, and focal plane cooling supports the viability of the imaging spectrometer approach.

Wellman, J. B.↗

ERTS operations and data processing

The overall communications and data flow between the ERTS spacecraft and the ground stations and processing centers are generally described. Data from the multispectral scanner and the return beam vidicon are telemetered to a primary ground station where they are demodulated, processed, and recorded. The tapes are then transferred to the NASA Data Processing Facility (NDPF) at Goddard. Housekeeping data are relayed from the prime ground stations to the Operations Control Center at Goddard. Tracking data are processed at the ground stations, and the calculated parameters are transmitted by teletype to the orbit determination group at Goddard. The ERTS orbit has been designed so that the same swaths of the ground coverage pattern viewed during one 18-day coverage cycle are repeated by the swaths viewed on all subsequent cycles. The Operations Control Center is the focal point for all communications with the spacecraft. NDPF is a job-oriented facility which processes and stores all sensor data, and which disseminates large quantities of these data to users in the form of films, computer-compatible tapes, and data collection system data.

Gonzales, L.↗

ERBE data and its validation

The Earth Radiation Budget Experiment (ERBE) is to be a three-satellite complement, of which two satellites were in orbit as of October 1984. Each satellite carries scanners for earth radiance sensing and one nonscanner for solar constant sensing. Of the four channels for earth scanning, two are dedicated to limb-to-limb observations and two view a swath 1000 km wide. Comparisons are made among the channel readings, thus far producing agreement to within 1 percent. Inversion techniques which are being applied to data gathered by the sensors are checked against equivalent procedures and results with the Nimbus-7 and GOES satellites.

Barkstrom, B. R.↗

Radar systems for the water resources mission, volume 1

The state of the art determination was made for radar measurement of: soil moisture, snow, standing and flowing water, lake and river ice, determination of required spacecraft radar parameters, study of synthetic-aperture radar systems to meet these parametric requirements, and study of techniques for on-board processing of the radar data. Significant new concepts developed include the following: scanning synthetic-aperture radar to achieve wide-swath coverage; single-sideband radar; and comb-filter range-sequential, range-offset SAR processing. The state of the art in radar measurement of water resources parameters is outlined. The feasibility for immediate development of a spacecraft water resources SAR was established. Numerous candidates for the on-board processor were examined.

Moore, R. K.↗

Credible practice of modeling and simulation in healthcare: ten rules from a multidisciplinary perspective

The complexities of modern biomedicine are rapidly increasing. Thus, modeling and simulation have become increasingly important as a strategy to understand and predict the trajectory of pathophysiology, disease genesis, and disease spread in support of clinical and policy decisions. In such cases, inappropriate or ill-placed trust in the model and simulation outcomes may result in negative outcomes, and hence illustrate the need to formalize the execution and communication of modeling and simulation practices. Although verification and validation have been generally accepted as significant components of a model’s credibility, they cannot be assumed to equate to a holistic credible practice, which includes activities that can impact comprehension and in-depth examination inherent in the devel-opment and reuse of the models. For the past several years, the Committee on Credible Practice of Modeling and Simulation in Healthcare, an interdisciplinary group seeded from a U.S. interagency initiative, has worked to codify best practices. Here, we provide Ten Rules for credible practice of modeling and simulation in healthcare developed from a comparative analysis by the Committee’s multidisciplinary membership, followed by a large stakeholder com-munity survey. These rules establish a unified conceptual framework for modeling and simulation design, implementation, evaluation, dissemination and usage across the modeling and simulation life-cycle. While biomedical science and clinical care domains have somewhat different requirements and expectations for credible practice, our study converged on rules that would be useful across a broad swath of model types. In brief, the rules are: (1) Define context clearly. (2) Use contextually appropriate data. (3) Evaluate within context. (4) List limitations explicitly. (5) Use version control. (6) Document appropriately. (7) Disseminate broadly. (8) Get independent reviews. (9) Test competing imple-mentations. (10) Conform to standards. Although some of these are common sense guidelines, we have found that many are often missed or misconstrued, even by seasoned practitioners. Computational models are already widely used in basic science to generate new biomedical knowledge. As they penetrate clinical care and healthcare policy, contributing to personalized and precision medicine, clinical safety will require established guidelines for the credible practice of modeling and simulation in healthcare.

Credibility↗

Full-Waveform, Wide-Swath Lidar Imaging of Forested and Urban Areas in Leaf-On Conditions: Development, Results and Future Direction

Full-Waveform lidar measurements provide unprecedented views of the vertical and horizontal structure of vegetation and the topography of the Earth s surface. Utilizing a high signal-to-noise ratio lidar system, larger than typical laser footprints (10-20 m), and the recorded time history of interaction between a short-duration (approx. 10 ns) pulse of laser light and the surface of the Earth, full-waveform lidar is able to simultaneously image sub-canopy topography as well as the vertical structure of any overlying vegetation. These data reveal the true 3-D vegetation structure in leaf-on conditions enabling important biophysical parameters such as above-ground biomass to be estimated with unprecedented accuracy. An airborne lidar mission was conducted July-August 2003 in support of the North America Carbon Program. NASA s Laser Vegetation Imaging Sensor (LVIS) was used to image approximately 2,000 km$^2$ in Maine, New Hampshire, Massachusetts and Maryland. Areas with available ground and other data were included (e.g., experimental forests, FLUXNET sites) in order to facilitate as many bio- and geophysical investigations as possible. Data collected included ground elevation and canopy height measurements for each laser footprint, as well as the vertical distribution of intercepted surfaces. Data will be publicly distributed within 6- 12 months of collection. Further details of the mission, including the lidar system technology, the locations of the mapped areas, and examples of the numerous data products that can be derived from the return waveform data products will be presented. Future applications including detection of ground and vegetation canopy changes and a spaceborne implementation of wide-swath, full-waveform imaging lidar will also be discussed.

Blair, James B.↗

Python-Based Scientific Analysis and Visualization of Precipitation Systems at NASA Marshall Space Flight Center

At NASA Marshall Space Flight Center (MSFC), Python is used several different ways to analyze and visualize precipitating weather systems. A number of different Python‐based software packages have been developed, which are available to the larger scientific community. The approach in all these packages is to utilize pre‐existing Python modules as well as to be object‐oriented and scalable. The first package that will be described and demonstrated is the Python Advanced Microwave Precipitation Radiometer (AMPR) Data Toolkit, or PyAMPR for short. PyAMPR reads geolocated brightness temperature data from any flight of the AMPR airborne instrument over its 25‐year history into a common data structure suitable for user‐defined analyses. It features rapid, simplified (i.e., one line of code) production of quick‐look imagery, including Google Earth overlays, swath plots of individual channels, and strip charts showing multiple channels at once. These plotting routines are also capable of significant customization for detailed, publication‐ready figures. Deconvolution of the polarization‐varying channels to static horizontally and vertically polarized scenes is also available. Examples will be given of PyAMPR's contribution toward real‐time AMPR data display during the Integrated Precipitation and Hydrology Experiment (IPHEx), which took place in the Carolinas during May‐June 2014. The second software package is the Marshall Multi‐Radar/Multi‐Sensor (MRMS) Mosaic Python Toolkit, or MMM‐Py for short. MMM‐Py was designed to read, analyze, and display three‐dimensional national mosaicked reflectivity data produced by the NOAA National Severe Storms Laboratory (NSSL). MMM‐Py can read MRMS mosaics from either their unique binary format or their converted NetCDF format. It can also read and properly interpret the current mosaic design (4 regional tiles) as well as mosaics produced prior to late July 2013 (8 tiles). MMM‐Py can easily stitch multiple tiles together to provide a larger regional or national picture of precipitating weather systems. Composites, horizontal and vertical crosssections, and combinations thereof are easily displayed using as little as one line of code. MMM‐Py can also write to the native MRMS binary format, and sub‐sectioning of tiles (or multiple stitched tiles) is anticipated to be in place by the time of this meeting. Thus, MMM‐Py also can be used to power the creation of custom mosaics for targeted regional studies. Overlays of other data (e.g., lightning observations) are easily accomplished. Demonstrations of MMM‐Py, including the creation of animations, will be shown. Finally, Marshall has done significant work to interface Python‐based analysis routines with the U.S. Department of Energy's Py‐ART software package for radar data ingest, processing, and analysis. One example of this is the Python Turbulence Detection Algorithm (PyTDA), an MSFC‐based implementation of the National Center for Atmospheric Research (NCAR) Turbulence Detection Algorithm (NTDA) for the purposes of convective‐scale analysis, situational awareness, and forensic meteorology. PyTDA exploits Py‐ART's radar data ingest routines and data model to rapidly produce aviation‐relevant turbulence estimates from Doppler radar data. Work toward processing speed optimization and better integration within the Py‐ART framework will be highlighted. Python‐based analysis within the Py‐ART framework is also being done for new research related to intercomparison of ground‐based radar data with satellite estimates of ocean winds, as well as research on the electrification of pyrocumulus clouds.

Lang, Timothy J.↗

Optimal A-Train Data Utilization: A Use Case of Aura OMI L2G and MERRA-2 Aerosol Products

Ozone Monitoring Instrument (OMI) aboard NASA's Aura mission measures ozone column and profile, aerosols, clouds, surface UV irradiance, and the trace gases including NO2, SO2, HCHO, BrO, and OClO using UltraViolet electromagnetic spectrum (280 - 400 nm) with a daily global coverage and a pixel spatial resolution of 13 km × 24 km at nadir, and it's been one of the key instruments to study the Earth's atmospheric composition and chemistry. The second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) is NASA's atmospheric reanalysis using an upgraded version of Goddard Earth Observing System Model, version 5 (GEOS-5) data assimilation system. Compared to its predecessor MERRA, MERRA-2 is enhanced with more aspects of the Earth system among which is aerosol assimilation. When comparing between satellite pixel measurements and modeled grid data, how to properly handle counterpart pairing is critical considering their spatial and temporal variations. The comparison between satellite and model data by simply using Level 3 (L3) products may result biases due to lack of detailed temporal information. It has been preferred to inter-compare or implement satellite derived physical quantity (i.e., Level 2 (L2) Swath type) directly with/to model measurements with higher temporal and spatial resolution as possible. However, this has posed a challenge in the community to handle. Rather than directly handling the L2 or L3 data, there is a Level 2G (L2G) product conserving L2 pixel scientific data quality but in Grid type with the global coverage. In this presentation, we would like to demonstrate the optimal utilization of OMI L2G daily aerosol products by comparing with MERRA-2 hourly aerosol simulations matched well in both space and time.

MERRA-2 reanalysis↗

Note on the Effect of Horizontal Gradients for Nadir-Viewing Microwave and Infrared Sounders

Passive microwave and infrared nadir sounders such as the Advanced Microwave Sounding Unit A (AMSU-A) and the Atmospheric InfraRed Sounder (AIRS), both flying on NASA s EOS Aqua satellite, provide information about vertical temperature and humidity structure that is used in data assimilation systems for numerical weather prediction and climate applications. These instruments scan cross track so that at the satellite swath edges, the satellite zenith angles can reach approx. 60 deg. The emission path through the atmosphere as observed by the satellite is therefore slanted with respect to the satellite footprint s zenith. Although radiative transfer codes currently in use at operational centers use the appropriate satellite zenith angle to compute brightness temperature, the input atmospheric fields are those from the vertical profile above the center of the satellite footprint. If horizontal gradients are present in the atmospheric fields, the use of a vertical atmospheric profile may produce an error. This note attempts to quantify the effects of horizontal gradients on AIRS and AMSU-A channels by computing brightness temperatures with accurate slanted atmospheric profiles. We use slanted temperature, water vapor, and ozone fields from data assimilation systems. We compare the calculated slanted and vertical brightness temperatures with AIRS and AMSU-A observations. We show that the effects of horizontal gradients on these sounders are generally small and below instrument noise. However, there are cases where the effects are greater than the instrument noise and may produce erroneous increments in an assimilation system. The majority of the affected channels have weighting functions that peak in the upper troposphere (water vapor sensitive channels) and above (temperature sensitive channels) and are unlikely t o significantly impact tropospheric numerical weather prediction. However, the errors could be significant for other applications such as stratospheric analysis. Gradients in ozone and tropospheric temperature appear to be well captured by the analyses. In contrast, gradients in upper stratospheric and mesospheric temperature as well as upper tropospheric humidity are less well captured. This is likely due in part to a lack of data to specify these fields accurately in the analyses. Advanced new sounders, like AIRS, may help to better specify these fields in the future.

Joiner, J.↗