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102 records · Page 6

Backscatter characteristics of the winter ice cover in the Beaufort Sea

The microwave backscatter statistics of the sea ice cover in the winter Beaufort Sea are characterized using C band synthetic aperture radar (SAR) data collected by the European Earth Resources Satellite 1. Sea ice backscatter signatures were sampled from SAR image data collected during the winter of 1991-1992 and winter of 1992-1993. The spatial and temporal variabilities of the backscatter signatures of different ice types are discussed. The results show considerable seasonal stability of the backscatter signature of multiyear ice as well as of first-year ice. Small amplitude regional variations of the multiyear ice backscatter can be observed. Consistent contrast between multiyear ice and first-year ice is maintained throughout the season. The highest radiometric variability is observed in sea ice in leads. On the basis of these observations the backscatter from the principal ice types (multiyear and first-year) are consistent with scatterometer observations and can be easily identified under winter conditions. Correlations of the regional variations of multiyear ice signatures to physical processes are suggested.

Kwok, Ronald↗

Topographic Signatures in Aquarius Radiometer/Scatterometer Response: Initial Results

The effect of topography on remote sensing at L-band is examined using the co-located Aquarius radiometer and scatterometer observations over land. A correlation with slope standard deviation is demonstrated for both the radiometer and scatterometer at topographic scales. Although the goal of Aquarius is remote sensing of sea surface salinity, the radiometer and scatterometer are on continuously and collect data for remote sensing research over land. Research is reported here using the data over land to determine if topography could have impact on the passive remote sensing at L-band. In this study, we report observations from two study regions: North Africa between 15 deg and 30 deg Northern latitudes and Australia less the Tasmania Island. Common to these two regions are the semi-arid climate and low population density; both favorable conditions to isolate the effect of topography from other sources of scatter and emission such as vegetation and urban areas. Over these study regions, topographic scale slopes within each Aquarius pixel are computed and their standard deviations are compared with Aquarius scatterometer and radiometer observations over a 36 day period between days 275 and 311 of 2011.

Utku, C.↗

Detection of soil moisture and snow characteristics from Skylab

The author has identified the following significant results. The most significant result is the good response of the passive radiometers, particularly the L-band radiometer, to changing soil moisture conditions near the surface of the earth. Radiometer response was very good for the five complete data sets consisting of three passes across Texas and two passes across Kansas. When data from the five different passes were combined, the correlation between the S194 radiometric temperature and soil moisture content remained high with a value of -0.96. The performance of the S193 passive radiometer was less consistent; however, one data set gave a very high correlation of -0.95. The scatterometer response to soil moisture at incidence angles near 30 deg was not as good as for the radiometers.

Eagleman, J. R.↗

An analysis of Skylab II S193 scatterometer data

Skylab II S193 scatterometer data for the passes of June 5, 1973, over the Gulf of Mexico and June 6, 1973, over Pacific Hurricane AVA were analyzed. These two passes were chosen since it was possible to correlate the scattering data with simultaneous measurements of the local ocean wind conditions. The S193 scatterometer measured the radar cross section of the ocean at 13.9 GHz (Ku-band) as a function of incidence angle. The S193 data of June 5, 1973, when a practically uniform wind field was present, show reasonable agreement with the Naval Research Laboratory (NRL) empirical and theoretical models. The data of June 6, 1973, are more complex, due to rapid variations in wind speeds and directions around Hurricane AVA. The NRL empirical model was interpolated to account for variation in wind heading relative to the S193 antenna pointing direction; a reasonable comparison could then be made with the corresponding S193 data of June 6, 1973.

Jordan, A. K.↗

Radar backscatter modelling

The terrain analysis software package was restructured and documentation was added. A program was written to test Johnson Space Center's four band scatterometer data for spurious signals data. A catalog of terrain roughness statistics and calibrated four frequency multipolarization scatterometer data is being published to support the maintenance of Death Valley as a radar backscatter calibration test site for all future airborne and spacecraft missions. Test pits were dug through sand covered terrains in the Eastern Sahara to define the depth and character of subsurface interfaces responsible for either backscatter or specular response in SIR-A imagery. Blocky sandstone bedrock surfaces at about 1 m depth were responsible for the brightest SIR-A returns. Irregular very dense CaCO3 cemented sand interfaces were responsible for intermediate grey tones. Ancient river valleys had the weakest response. Reexamination of SEASAT l-band imagery of U.S. deserts continues.

Schaber, G. G.↗

Aquarius: Status and Recent Results

Aquarius is a combination active/passive instrument at L band designed to map sea surface salinity globally from space. The radiometer (passive) is the primary instrument for retrieving salinity, and the scatterometer (active) provides information to correct for a major source of error, sea surface roughness (waves). In addition, the radiometer includes a number of special features designed to meet the goal for this challenging measurement, including measurement of the third Stokes parameter to help with the correction for Faraday rotation and rapid sampling to help with the mitigation of radio frequency interference. Aquarius was launched on 10 June 2011 aboard the Aquarius/SAC-D observatory and has been working well. The salinity retrieval continues to improve, and the special features suggest the potential for new applications of remote sensing from space at L band.

Aquarius↗

RADAR Reveals Titan Topography

The Cassini Titan RADAR Mapper is a K(sub u)-band (13.78 GHz, lambda = 2.17 cm) linear polarized RADAR instrument capable of operating in synthetic aperture (SAR), scatterometer, altimeter and radiometer modes. During the first targeted flyby of Titan on 26 October, 2004 (referred to as Ta) observations were made in all modes. Evidence for topographic relief based on the Ta altimetry and SAR data are presented here. Additional SAR and altimetry observations are planned for the T3 encounter on 15 February, 2005, but have not been carried out at this writing. Results from the T3 encounter relevant to topography will be included in our presentation. Data obtained in the Ta encounter include a SAR image swath

Kirk, R. L.↗

Modeling multi-frequency diurnal backscatter from a walnut orchard

The Michigan Microwave Canopy Scattering Model (MIMICS) is used to model scatterometer data that were obtained during the August 1987 EOS (Earth Observing System) synergism study. During this experiment, truck-based scatterometers were used to measure radar backscatter from a walnut orchard in Fresno County, California. Multipolarized L- and X-band data were recorded for orchard plots for which dielectric and evapotranspiration characteristics were monitored. MIMICS is used to model a multiangle data set in which a single orchard plot was observed at varying impedance angles and a series of diurnal measurements in which backscatter from this same plot was measured continuously over several 24-h periods. MIMICS accounts for variations in canopy backscatter driven by changes in canopy state that occur diurnally as well as on longer time scales. L-band backscatter is dependent not only on properties of the vegetation but also on properties of the underlying soil surface. The behavior of the X-band backscatter is dominated by properties of the tree crowns.

Mcdonald, Kyle C.↗

AAFE RADSCAT 13.9-GHz measurements and analysis - Wind-speed signature of the ocean

The Advanced Applications Flight Experiment Radiometer Scatterometer, or 'AAFE RADSCAT', was developed as a research tool for the evaluation of the use of microwave remote sensors in gathering data on wind speed at the ocean's surface. The most important function of AAFE RADSCAT was to furnish a data base of ocean normalized radar cross section (NRCS) measurements as a function of surface wind vector at 13.9 GHz. The NRCS measurements cover a wide parametric range of incidence and azimuth angles and winds. Attention is presently given to analyses of data from the 26 RADSCAT flights during which the quality of the sensors and the surface wind measurements were felt to be understood; subsets of the data base are used to model the relationship between the Ku-band radar signature and the ocean surface wind vector.

Schroeder, L. C.↗

The modulation of a radar signal from the ocean surface due to slope and hydrodynamic effects

The modulation of the signal level of a tower-based radar scatterometer illuminating a small area of the ocean surface is predicted from direct measurements of the hydrodynamic conditions of the ocean surface and compared with X band radar measurements taken simultaneously. The radar backscatter is assumed to be due to Bragg resonance between the signal and the ripple waves. The effects of the slope of the ocean surface due to passing long waves are modeled by converting a measured wave height series into a slope time series. Laser-slope-gauge measurements of the spectrum of the ripple waves that ride upon the long ocean waves are used to predict the hydrodynamic effects. Comparisons with the measured radar signal show that the slope modulation alone gives a poor prediction of the modulation. Inclusion of the hydrodynamic effects in the simulation appears more promising, although it also is not entirely successful with this data set.

West, James C.↗

Lessons Learned from the Aquarius Radiometer Engineering Model

The Aquarius instrument is a combination microwave radiometer and scatterometer operating in the L-band for the measurement of sea surface salinity (SSS) over the open-ocean. "The Aquarius science goals are to observe and model the processes that relate salinity variations to climatic changes in the global cycling of water and to understand how these variations influence the general ocean circulation. By measuring salinity globally and synoptically every month for 3 years, Aquarius will provide an unprecedented new view of the ocean's role in climate." (http://aquarius.asfc.nasa.gov on Jan. 4, 2007). To launch in 2009, Aquarius will provide 8-day global coverage and monthly-averaged salinity maps at approx.120-km spatial resolution. Because the microwave emissivity of the ocean surface is weakly dependent upon salinity, the Aquarius radiometer remain sufficiently stable to provide accurate salinity measurements. An engineering model (EM) of one radiometer receiver was developed and tested for functionality and performance at NASA's Goddard Space Flight Center. It was tested for long-term stability starting July 27,2006. Two discrepancies where found at the start of testing and a four-month correction process ensued. This paper covers the testing and debugging of the EM radiometer through resolution of the problems. The radiometer is required to have calibration stability of less than or equal to 0.15 K over 7 days. The radiometer is in a three-beam push-broom configuration with each beam being an independent three-state Dicke radiometer (antenna, reference load, and additive noise). Internal noise diodes and reference loads provide periodic and rapid calibration of the receiver. Front-end loss contributions must be corrected as the lossy components are outside the calibration loop. A key design feature for obtaining stability is active thermal control of the front-end lossy components and the RF receiver. The thermal stability is predicted to be about 0.1 C over an orbit and no more than 1 C over a year. The radiometric stability requirement is 0.13 K rms 1 7 days without using temperature corrections. Temperature corrections and post-launch calibration are expected to extend the stability period through the life of the mission.

Piepmeier, Jeffrey↗

Assimilation of Global Radar Backscatter and Radiometer Brightness Temperature Observations to Improve Soil Moisture and Land Evaporation Estimates

Active radar backscatter (s◦) observations from the Advanced Scatterometer (ASCAT) and passive radiometer brightness temperature (TB) observations from the Soil Moisture Ocean Salinity (SMOS) mission are assimilated either individually or jointly into the Global Land Evaporation Amsterdam Model (GLEAM) to improve its simulations of soil moisture and land evaporation. To enable s◦ and TB assimilation, GLEAM is coupled to the Water Cloud Model and the L-band Microwave Emission from the Biosphere (L-MEB) model. The innovations, i.e. differences between observations and simulations, are mapped onto the model soil moisture states through an Ensemble Kalman Filter. The validation of surface (0-10 cm) soil moisture simulations over the period 2010-2014 against in situ measurements from the International Soil Moisture Network (ISMN) shows that assimilating s◦ or TB alone improves the average correlation of seasonal anomalies (Ran) from 0.514 to 0.547 and 0.548, respectively. The joint assimilation further improves Ran to 0.559. Associated enhancements in daily evaporative flux simulations by GLEAM are validated based on measurements from 22 FLUXNET stations. Again, the singular assimilation improves Ran from 0.502 to 0.536 and 0.533, respectively for s◦ and TB, whereas the best performance is observed for the joint assimilation (Ran = 0.546). These results demonstrate the complementary value of assimilating radar backscatter observations together with brightness temperatures for improving estimates of hydrological variables, as their joint assimilation outperforms the assimilation of each observation type separately.

GLEAM↗