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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 145 records · Page 8
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NASA NTRS1986

Off-line processing of ERS-1 synthetic aperture radar data with high precision and high throughput

The first European remote sensing satellite ERS-1 will be launched by the European Space Agency (ESA) in 1989. The expected lifetime is two to three years. The spacecraft sensors will primarily support ocean investigations and to a limited extent also land applications. Prime sensor is the Active Microwave Instrumentation (AMI) operating in C-Band either as Synthetic Aperture Radar (SAR) or as Wave-Scatterometer and simultaneously as Wind-Scatterometer. In Europe there will be two distinct types of processing for ERS-1 SAR data, Fast Delivery Processing and Precision Processing. Fast Delivery Proceessing will be carried out at the ground stations and up to three Fast Delivery products per pass will be delivered to end users via satellite within three hours after data acquisition. Precision Processing will be carried out in delayed time and products will not be generated until several days or weeks after data acquisition. However, a wide range of products will be generated by several Processing and Archiving Facilities (PAF) in a joint effort coordinated by ESA. The German Remote Sensing Data Center (Deutsches Fernerkundungsdatenzentrum DFD) will develop and operate one of these facilities. The related activities include the acquisition, processing and evaluation of such data for scientific, public and commercial users. Based on this experience the German Remote Sensing Data Center is presently performing a Phase-B study regarding the development of a SAR processor for ERS-1. The conceptual design of this processing facility is briefly outlined.

Gredel, J.↗
NASA NTRS1988

Tropical Rainfall Measurement Mission

It has long been noted that anomalies in the sea surface temperature (SST) in the tropics are strongly correlated with climate in the temperate latitudes on a seasonal time scale. The ability to measure the global SST and the atmospheric pressure/temperature patterns has made great progress. However, rainfall measurement, the putative connection between the two, is poorly accomplished. The Tropical Rainfall Measurement Mission (TRMM) was conceived to fill this gap. The TRMM spacecraft would fly in a low inclination, (about 35 deg), orbit which would concentrate the sampling in the very important tropical latitudes. The precession of such an orbit would enable observations at all times of the day over the span of a month which would permit corrections for the diurnal cycle of precipitation which is quite marked in parts of the tropics. The payload of the TRMM spacecraft is carefully designed to provide accurate measurements of rain. It consists of microwave radiometers, a microwave radar and visible/infrared radiometer. The two types of microwave instruments provide direct measurements of the hydrometeors, each having strengths which compensate for weaknesses of the other. The VIS/IR instrument provides a connection to the long time series of VIS/IR measurements from polar and Geosynchronous spacecraft which are currently the best available source of global rainfall estimates. The TRMM is currently in a phase A (feasibility) study.

Wilheit, T. T.↗
NASA NTRS1992

Predicting Clear-Air Turbulence From Microwave Radiometry

Proposed system combines microwave-instrument measurement of vertical temperature gradient with inertial navigation-system measurement of wind vector and provides warnings about time and severity of upcoming clear air turbulence (CAT), and indicates how to avoid it. Also saves fuel by making it unnecessary to detour around regions conservative forecasts indicate might contain CAT, instead, one navigates more efficiently by following altitude-avoidance advisories of proposed instrument.

Gary, Bruce L.↗
NASA NTRS1992

Ground-based microwave monitoring of stratospheric ozone

A microwave instrument developed for operational measurements of ozone for the Network for Detection of Stratospheric Change is discussed. The instrument observes two spectral lines near 3-mm wavelength with a bandwidth of 630 MHz, allowing profile retrieval from 20 to 70 km. The observing technique and calibration procedures are described. The measurement forward model and retrieval algorithm are formulated. Preliminary comparisons with a colocated ground-based lidar and the SAGE II instrument are presented. The measurements are shown to typically agree to within 5 to 10 percent.

Parrish, A.↗
NASA NTRS1991

Multi-frequency, multi-polarization SAR and radiometer sea ice classification

Microwave remotely sensed data were acquired simultaneously in March 1988 over Beaufort, Chukchi, and Bering Sea ice using the JPL multifrequency, polarimetric synthetic aperture radar (SAR), and multifrequency dual-polarization GSFC radiometer. The experiment was conducted as a series of coordinated underflights of the DMSP SSM/I satellite radiometer to validate ice products derived from its radiance values. Concurrent flights by an NRL P-3 aircraft enabled overlapping high-resolution, single-frequency images to be acquired over the same surfaces using a Ka-band scanning microwave radiometer. Precise coregistration to an accuracy of 100 m, +/- 25 m enables comparison of temporally and spatially coincident active and passive microwave datasets. Three-channel polarimetric SAR data are compared with dual-polarized radiometer data at several SSM/I frequencies, showing backscatter signatures to be highly correlated with radiometric temperatures. Further comparisons are used to evaluate ice concentration retrievals and to show how multiparameter datasets can be used to resolve ambiguities present in identifying certain sea ice forms with a single microwave instrument.

Drinkwater, Mark R.↗
NASA NTRS1993

COBE looks back to the Big Bang

An overview is presented of NASA-Goddard's Cosmic Background Explorer (COBE), the first NASA satellite designed to observe the primeval explosion of the universe. The spacecraft carries three extremely sensitive IR and microwave instruments designed to measure the faint residual radiation from the Big Bang and to search for the formation of the first galaxies. COBE's far IR absolute spectrophotometer has shown that the Big Bang radiation has a blackbody spectrum, proving that there was no large energy release after the explosion.

Mather, John C.↗
NASA NTRS1993

Evaluation of two January - June 1992 ERS-1 AMI wind vector data sets

A Jan. - Jun. 1992 10 m height wind vector field was computed with the CMOD2 model function. Freilich and Dunbar used ESA measurements of AMI (Active Microwave Instrument) sigma-naught to derive a refined model function and to produce an alternate Jan. - Jun. 1992 10 m height wind vector field, named FD data. The ESA and FD model functions and algorithms were substantially different. The FD wind vectors were in better agreement with the climatological mean wind field and with moored buoy wind measurements. The average correlation coefficients between monthly mean and daily averaged FD and moored buoy matchups of the Cartesian wind components were 0.84 and 0.74, respectively. The average root mean square differences between the monthly mean and daily averaged FD and moored buoy matchups of the Cartesian wind components were 1.25 and 3.0 m/s, respectively.

Halpern, D.↗
NASA NTRS1993

Techniques and Applications of SAR interferometry for ERS-1: Topographic Mapping, Change Detection, and Slope Measurement

SAR (Synthetic Aperture Radar) interferometry allows the measurement of high resolution topography of terrain from repeat orbit SAR data sets obtained by the ERS-1 AMI (Active Microwave Instrument). The system parameters which affect the accuracy of the topographic maps are errors in determination of the interferometric baseline, non parallel orbit tracks, decorrelation caused by baseline length, thermal noise, and surface change. Surface change can be observed in the interferograms either through decorrelation of the interferometric phase, or coherent phase shifts caused by locally uniform surface displacements. Phase gradient maps can be derived directly from the complex interferograms and can be transformed into surface slopes mapped onto a geometrically corrected grid.

Charles L Werner↗
NASA NTRS1993

Mission planning for an Earth observation low Earth orbiter: ERS-1

ERS-1, the first European Remote Sensing satellite, has a payload which consists primarily of microwave instruments and is in a polar sun-synchronous orbit. All ground and on-board activities from user requests to delivery of data products are combined into one integrated system. In view of the high number of products which can be generated by ERS-1, the Mission Planning System (MPS), which plans the on-board activities of ERS-1, is an essential tool for operations since manual planning of the large number of daily operations is out of the question. In addition the MPS, in line with the integrated nature of the ERS-1 system, also plans activities at the prime ground station, including among others, the operation of the payload data processing systems there. This paper outlines the operations concepts for ERS-1 mission planning, and describes the Mission Planning System used at the ERS-1 Control Center. Novel functionalities, such as automatic resource clash resolution, are described. A critical discussion gives lessons learned for future mission planning systems.

Lockyer, Paul↗
NASA NTRS1994

ERS-1 scatterometer estimates of annual variations of Atlantic ITCZ and Pacific NECC

A 10 m height wind vector data set, named CMODFD, from ERS-1 Active Microwave Instrument (AMI) measurements, was compared with moored buoy wind observations. The CMODFD wind vectors compared favorably with moored buoy wind observations at about 60 sites. Satisfactory results were obtained from intercomparisons between CMODFD and moored buoy estimates of horizontal wind divergence and wind stress curl. The CMODFD positions of the Intertropical Convergence Zone (ITCZ) at 28 deg west were nearly equal to those determined from satellite images of clouds. The CMODFD data were employed to compute the Ekman vertical velocity in the region of the Pacific North Equatorial Countercurrent (NECC), and a correlative relation was found between the annual cycles and longitudinal variations of the NECC and Ekman vertical motion.

Halpern, D.↗
NASA NTRS1994

ERS-1 scatterometer measurements over the Southern Ocean

Backscatter cross section measurements from the ERS-1 Active Microwave Instrument (AMI) scatterometer were reprocessed to vector winds using the Freilich-Dunbar model function and a meteorologically aided ambiguity removal scheme. This consistent data set was used to examine the wind field over the Southern Ocean from 20 to 60 deg South. The large number of ERS-1 measurements allows relatively accurate calculation of annual mean wind, stress, and curl fields as well as overall statistics of the winds at mid to high southern latitudes. The long duration of the data time series allows preliminary examination of low frequency (semi annual) wind variability.

Freilich, M. H.↗
NASA NTRS1994

Comparison of ERS-1 scatterometer and Florida State University tropical winds

Monthly mean winds from the CMODFD (wind vector data set) ERS-1 Active Microwave Instrument (AMI) scatterometer are evaluated by comparing them to monthly mean tropical Pacific and Indian Ocean wind analyses based on in-situ data. The FSU (an observation based set of fields) winds agree qualitatively with the ERS-1 winds. Magnitudes of the vector differences are 2 to 4 m/s. Evident in the ERS-1 fields are north-south oriented bands which coincide with orbital sampling swaths. These bands are more evident in the curl maps of the mean monthly wind fields. Suitability of the ERS-1 monthly mean wind fields for ocean modeling is evaluated through a comparison of results from a model of the tropical Pacific forced by both FSU and ERS-1 wind fields. Model responses in the eastern equatorial Pacific are similar, and both track variability in the observed sea level. However, ERS-1 wind results do not correlate as well to the monthly variations in the sea level data.

Legler, David M.↗
NASA NTRS1993

Physical initialization using SSM/I rain rates

Following our recent study on physical initialization for tropical prediction using rain rates based on outgoing long-wave radiation, the present study demonstrates a major improvement from the use of microwave radiance-based rain rates. A rain rate algorithm is used on the data from a special sensor microwave instrument (SSM/I). The initialization, as before, uses a reverse surface similarity theory, a reverse cumulus parameterization algorithm, and a bisection method to minimize the difference between satellite-based and the model-based outgoing long-wave radiation. These are invoked within a preforecast Newtonian relaxation phase of the initialization. These tests are carried out with a high-resolution global spectral model. The impact of the initialization on forecast is tested for a complex triple typhoon scenario over the Western Pacific Ocean during September 1987. A major impact from the inclusion of the SSM/I is demonstrated. Also addressed are the spin-up issues related to the typhoon structure and the improved water budget from the physical initialization.

Krishnamurti, T. N.↗
NASA NTRS1994

Validation of ERS-1 environmental data products

Evaluation of the launch-version algorithms used by the European Space Agency (ESA) to derive wind field and ocean wave estimates from measurements of sensors aboard the European Remote Sensing satellite, ERS-1, has been accomplished through comparison of the derived parameters with coincident measurements made by 24 open ocean buoys maintained by the National Oceanic and Atmospheric Administration). During the period from November 1, 1991 through February 28, 1992, data bases with 577 and 485 pairs of coincident sensor/buoy wind and wave measurements were collected for the Active Microwave Instrument (AMI) and Radar Altimeter (RA) respectively. Based on these data, algorithm retrieval accuracy is estimated to be plus or minus 4 m/s for AMI wind speed, plus or minus 3 m/s for RA wind speed and plus or minus 0.6 m for RA wave height. After removing 180 degree ambiguity errors, the AMI wind direction retrieval accuracy was estimated at plus or minus 28 degrees. All of the ERS-1 wind and wave retrievals are relatively unbiased. These results should be viewed as interim since improved algorithms are under development. As final versions are implemented, additional assessments should be conducted to complete the validation.

Goodberlet, Mark A.↗
NASA NTRS1995

An atlas of monthly mean distributions of SSMI surface wind speed, AVHRR/2 sea surface temperature, AMI surface wind velocity, TOPEX/POSEIDON sea surface height, and ECMWF surface wind velocity during 1993

The following monthly mean global distributions for 1993 are presented with a common color scale and geographical map: 10-m height wind speed estimated from the Special Sensor Microwave Imager (SSMI) on a United States (U.S.) Air Force Defense Meteorological Satellite Program (DMSP) spacecraft; sea surface temperature estimated from the Advanced Very High Resolution Radiometer (AVHRR/2) on a U.S. National Oceanic and Atmospheric Administration (NOAA) satellite; 10-m height wind speed and direction estimated from the Active Microwave Instrument (AMI) on the European Space Agency (ESA) European Remote Sensing (ERS-1) satellite; sea surface height estimated from the joint U.S.-France Topography Experiment (TOPEX)/POSEIDON spacecraft; and 10-m height wind speed and direction produced by the European Center for Medium-Range Weather Forecasting (ECMWF). Charts of annual mean, monthly mean, and sampling distributions are displayed.

Halpern, D.↗
NASA NTRS1999

Remote Sensing May Provide Unprecedented Hydrological Data

Basic hydrological research and water resources management may reap tremendous benefits from remote sensing technology, studies are showing. Satellite coverage may allow unprecedented accuracy in the quantification of the global hydrological cycle, for example. Yet despite such benefits, few hydrologists currently use such data. This is partly because the needed tools and algorithms are not fully developed. Such development requires field experiments that combine remotely sensed data with detailed in situ observations. AGU's Remote Sensing in Hydrology Committee has constructed a Web site (http://Iand.gsfc.nasa.gov/RSHC.html) that gives an overview of many such experiments. Included on the site is information on each experiment's overall goal, the types of in situ and remotely sensed measurements taken, relevant climate and vegetation conditions, and so forth. Links to additional relevant Web sites are included. The site is designed to be a suitable starting point for those interested in learning more about remote sensing in hydrology. It lists members of the committee who can be contacted for further information. Hydrologists have recognized the potential of remote sensing technology since the 1970s. It offers a way to avoid the logistical and economic difficulties associated with obtaining continuous in situ measurements of various hydrological variables, difficulties that are particularly pronounced in remote regions. Microwave instruments in particular can potentially provide all-weather, areally averaged estimates of certain variables (such as precipitation, soil moisture, and snow water content) that have been essentially unattainable in the past. In remote sensing, the conversion of emitted and reflected radiances into useful hydrological data is a complex problem. The measured radiances, for example, reflect the integrated character of a pixel area, a scale inconsistent with the point measurements of traditional hydrology. To develop the needed algorithms, field experiments must be designed that combine relevant satellite measurements with traditional in situ measurements in regions that are al- ready well understood hydrologically. Such field experiments can lead to the development of hydrological models that are driven with remotely sensed data. Once the performance of these models is deemed acceptable in the heavily monitored basins, they can be "transported" for use in regions having little or no in situ measurement system. Author,5: Randal D. Koster, Paul R. Houser and Edwin T. Engman, Hydrological Sciences Branch, Laboratory for Hydrospheric Process, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA; William P. Kustas, Hydrology Laboratory, Agricultural Research Service, U.S. Department of Agriculture, Beltsville, Maryland, USA.

Koster, R.↗
NASA NTRS2000

The Global Precipitation Mission

The Global Precipitation Mission (GPM), expected to begin around 2006, is a follow-up to the Tropical Rainfall Measuring Mission (TRMM). Unlike TRMM, which primarily samples the tropics, GPM will sample both the tropics and mid-latitudes. The primary, or core, satellite will be a single, enhanced TRMM satellite that can quantify the 3-D spatial distributions of precipitation and its associated latent heat release. The core satellite will be complemented by a constellation of very small and inexpensive drones with passive microwave instruments that will sample the rainfall with sufficient frequency to be not only of climate interest, but also have local, short-term impacts by providing global rainfall coverage at approx. 3 h intervals. The data is expected to have substantial impact upon quantitative precipitation estimation/forecasting and data assimilation into global and mesoscale numerical models. Based upon previous studies of rainfall data assimilation, GPM is expected to lead to significant improvements in forecasts of extratropical and tropical cyclones. For example, GPM rainfall data can provide improved initialization of frontal systems over the Pacific and Atlantic Oceans. The purpose of this talk is to provide information about GPM to the USWRP (U.S. Weather Research Program) community and to discuss impacts on quantitative precipitation estimation/forecasting and data assimilation.

Braun, Scott↗
NASA NTRS2000

Recent Trends in the Analysis of Quasioptical Systems

The recent trend in microwave instruments is the use of multiple millimeter and submillimeter wavelength bands. These systems are typically analyzed by using physical optics, Gaussian beams or ray tracing techniques. Physical optics offers high accuracy at the expense of computation time. This trade-off becomes particularly apparent in the analysis of multiple reflector antennas, such as beam waveguide antennas, where physical optics is used to compute the current on each reflector from the current on the previous reflector. At the other end of the spectrum is ray tracing approaches that ignore diffraction effects entirely. These methods are fast but sacrifice the ability to predict some effects accurately. An intermediate approach is to use an appropriate set of expansion functions to model the field between the reflectors. If the set is chosen wisely only a few coefficients need to be determined from each reflector current. The field is then computed at the next reflector through the use of the expansion functions and their coefficients rather than by using the previous reflector current. For a beam waveguide system with no enclosing tubes an excellent set of expansion functions is the Gaussian beam mode set. In many cases a preliminary design which includes the effects on diffraction may be obtained by considering only the fundamental mode and a thin lens model for the reflectors. Higher-order modes are included to model the effects of the curved reflector, which include asymmetric distortion of the beam, cross polarization, and beam truncation. This paper describes a computer code implementing higher-order Gaussian beam scattering by multiple reflector systems. There are four essential steps in the algorithm. (1) Compute the current on the first reflector using physical optics using either a feed model or by an incident set of Gaussian beam modes. (2) Find the direction of propagation for the reflected Gaussian beam-set using ray tracing. (3) Determine the waist size and location for the output beam set by examining the amplitude and phase distribution of the current on the reflector. (4) Compute the amplitudes of the individual modes in the output mode set. These steps are then repeated for each addition reflector in the chain. In each of these cases the previous Gaussian beam set provides the input field for the current calculation. Details of the four steps discussed above will be discussed. Examples will compare results from the Gaussian beam approach to pure physical optics, illustrating both its merits and limitations. Hybrid approaches capable of eliminating some of the limitations will also be discussed.

Hoppe, D. J.↗