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At least 829 records · Page 46

(abstract) Optical Scattering and Surface Microroughness of Ion Beam Deposited Au and Pt Thin Films

Thin films of gold and platinum have been deposited onto superpolished fused silica substrates using thermal evaporation, ion assisted deposition (IAD), and ion assisted sputtering. The influence of ion beam flux, thin film material, and deposition rate on the films microroughness have been investigated. Short range surface microroughness of the films has been examined using scanning tunneling microscopy (STM) and atomic force microscopy (AFM). Long range surface microroughness has been characterized using an angle resolved optical scatterometer. Results indicate that ion beam deposited coatings have improved microstructure over thermally evaporated films.

assisted sputtering fused silica ion beam microrou↗

Sea Surface Temperature and Wind-Generated Current Variations in the Arabian Sea During 1992 and 1993

Monthly mean wind-generated Ekman and Sverdup transports and the vertical transport into and out of the Ekman layer were computed from satellite scatterometer estimates of 10-m height wind speed components recorded from April 1992 to December 1993...This brief report describes a search for correspondence between variations of monthly mean SST and wind-driven currents in the Arabian Sea during April 1992 and December 1993.

north indian ocean clouds wind mixing heat advecti↗

Ground Calibration of an Orbiting Spacecraft Transmitter

The SeaWinds Calibration Ground Station (CGS) is a novel Ku-band receiving station that supports the June 1999-launched JPL/NASA SeaWinds scatterometer radar which measures the near-surface wind speeds over 90% of the ice-free oceans.

QuickSCAT SeaWinds Calibration Ground Station CGS↗

Radar Backscatter Across the Gulf Stream Sea Surface Temperature Front

Ocean backscatter signatures were measured by the Jet Propulsion Laboratory airborne NUSCAT K(sub u)-band scatterometer across the Gulf Stream sea surface temperature front. The measurements were made during the Surface Wave Dynamics Experiment (SWADE) off the coast of Virginia and Maryland in the winter of 1991.

Ocean Backscatter Temperature front Gulf Stream↗

Teleconnection of the 1997 El Nino Observed by Spaceborne Sensors and the Dacadal Anomalies in the Northeast Pacific

Liu et al.[1998] (hereafter referred as LTH), superimposed wind velocity anomalies observed by the NASA Scatterometer (NSCAT) on the map of sea surface temperature (SST) anomalies observed by the Advanced Very High Resolution Radiometer (AVHRR) in the Pacific at the end of May 1997, and illustrated that the three regions of anomalous warming in the North Pacific Ocean are related to wind anomalies through different mechanisms.

global change Empirical Orthogonal Function (EOF) ↗

Field of View Analysis of SeaWinds Reflector Antenna

Antennas are often mounted among many other instruments on the spacecraft platform. The electromagnetic interference (EMI) and compatibility (EMC) issues are of great concern to the antenna and spacecraft system design engineers. Considering the rotating reflector antenna of the NASA SeaWinds Scatterometer on the Japanes ADEOS II spacecraft, it is desirable to determine the antenna's field of view (FOV) performance. In other words, how far should the other boxes be kept away from the reflector antenna to minimize the blockage/diffraction effects on the antenna's performance requirements.

electromagnetic interference EMI↗

Satellite remote sensing of landscape freeze/thaw state dynamics for complex Topography and Fire Disturbance Areas Using multi-sensor radar and SRTM digital elevation models

We characterize differences in radar-derived freeze/thaw state, examining transitions over complex terrain and landscape disturbance regimes. In areas of complex terrain, we explore freezekhaw dynamics related to elevation, slope aspect and varying landcover. In the burned regions, we explore the timing of seasonal freeze/thaw transition as related to the recovering landscape, relative to that of a nearby control site. We apply in situ biophysical measurements, including flux tower measurements to validate and interpret the remotely sensed parameters. A multi-scale analysis is performed relating high-resolution SAR backscatter and moderate resolution scatterometer measurements to assess trade-offs in spatial and temporal resolution in the remotely sensed fields.

synthetic aperture radars (SARs)↗

Anomalous snow accumulation over the southeast region of the Greenland ice sheet during 2002-2003 snow season

Our objective is to determine seasonal snow accumulation in the percolation zone of the Greenland ice sheet on the daily-weekly basis over the large scale. Our approach utilizes data from the Greenland Climate Network (GC-Net) and from the SeaWinds Scatterometer on the QuikSCAT satellite (QSCAT) to measure snow accumulation (SA) in the percolation zone of the Greenland ice sheet. GC-Net measurements provide crucial in-situ data to facilitate the interpretation of QSCAT backscatter signature for the development of an algorithm to map SA.

Greenland↗

Observations of Arctic environmental change

This overview paper presents recent observations of anomalous change in Arctic environment using satellite scatterometer data together with in-situ and field measurements over land, snow, sea ice, and Greenland ice sheet.

snow↗

Mapping of ice layer extent and snow accumulation in the percolation zone of the Greenland ice sheet

The Greenland ice sheet underwent record extensive melt in 2002 and prolonged melt in 2003. The severe melting created a significant and extensive ice layer over the Greenland ice sheet. An innovative approach is developed to detect the ice layer formation using data acquired by the SeaWinds scatterometer on the QuikSCAT satellite. QuikSCAT backscatter together with in situ data from automatic weather stations of the Greenland Climate Network are used to map the extent of ice layer formation. The results reveal areas of extensive ice layer formed by the 2002 melt, which is consistent with the maximum melt extent in 2002. Moreover, during freezing seasons, QuikSCAT data show a linear decrease in backscatter (in decibels or dB) that is related to the amount of snow accumulation in the ice layer formation region. This snow accumulation signature is caused by the attenuation of radar waves in the snow layer, accumulating since the last major melt event, whose thickness appears as an exponential function in relation to the backscatter signature. We use the Greenland Climate Network data to calibrate the QuikSCAT accumulation rate in order to estimate and map snow accumulation. QuikSCAT results capture the extreme snowfall in mid-April 2003, which deposited more than 0.5 m of snow in a day as measured by the automated weather station at the NASA South East site. Large-scale QuikSCAT results show an anomalous increase of snow accumulation over the southeast region of Greenland during the 2002-2003 freezing season.

snow↗

Antarctic Iceberg Tracking Based on Time Series of Aqua AMSRE Microwave Brightness Temperature Measurements

Observations of icebergs are identified as one of the requirements for the GEOSS (Global Earth Observation System of Systems) in the area of reducing loss of life and property from natural and human-induced disasters. However, iceberg observations are not included among targets in the GEOSS 10-Year Implementation Plan, and thus there is an unfulfilled need for iceberg detection and tracking in the near future. Large Antarctic icebergs have been tracked by the National Ice Center and by the academic community using a variety of satellite sensors including both passive and active microwave imagers, such as SSM/I (Special Sensor Microwave/Imager) deployed on the DMSP (Defense Meteorological Satellite Program) spacecraft. Improvements provided in recent years by NASA and non-NASA satellite radars, scatterometers, and radiometers resulted in an increased number of observed icebergs and even prompted a question: Is The Number of Antarctic Icebergs Really Increasing? [D.G. Long, J. Ballantyne, and C. Bertoia, Eos, Transactions of the American Geophysical Union 83 (42): 469 & 474, 15 October 2002]. AMSR-E (Advanced Microwave Scanning Radiometer for the Earth Observing System) represents an improvement over SSM/I, its predecessor. AMSR-E has more measurement channels and higher spatial resolution than SSM/I. For example, the instantaneous field of view of the AMSR-E s 89-GHz channels is 6 km by 4 km versus 16 km by 14 km for SSM/I s comparable 85-GHz channels. AMSR-E, deployed on the Aqua satellite, scans across a 1450-km swath and provides brightness temperature measurements with nearglobal coverage every one or two days. In polar regions, overlapping swaths generate coverage up to multiple times per day and allow for creation of image time series with high temporal resolution. Despite these advantages, only incidental usage of AMSR-E data for iceberg tracking has been reported so far, none in an operational environment. Therefore, an experiment was undertaken in the RPC (Rapid Prototyping Capability) of NASA s (National Aeronautics and Space Administration) Applied Science Program to demonstrate that passive microwave brightness temperature measurements acquired by AMSR-E can be effectively used to track iceberg movement around Antarctica. The RPC s robust computation environment enabled processing of terabytes of data products available from the NASA Distributed Active Archive Center at the National Snow and Ice Data Center. Iceberg tracking based on the AMSR-E Level 2A data product was compared with records from the National Ice Center for currently existing icebergs. Some icebergs as small as roughly 10 km in size were easily observed, but tracking of many others, even larger ones, was obscured by presence of sea ice surrounding the icebergs. The best results, such as for the large iceberg A22A, were achieved when an iceberg was in open ocean.

Blonski, Slawomir↗

On Ambiguities in SAR Design

Ambiguities are an aliasing effect caused by the periodic sampling of the scene backscatter inherent to pulsed radar systems such as Synthetic Aperture radar (SAR). In this paper we take a fresh look at the relationship between SAR range and azimuth ambiguity constraints on the allowable pulse repetition frequency (PRF) and the antenna length. We show that for high squint angles smaller antennas may be feasible in some cases. For some applications, the ability to form a synthetic aperture at high squint angles is desirable, but the size of the antenna causes problems in the design of systems capable of such operation. This is because the SAR system design is optimized for a side-looking geometry. In two examples design examples we take a suboptimum antenna size and examine the performance in terms of azimuth resolution and swath width as a function of squint angle. We show that for stripmap SARs, the swath width is usually worse for off-boresight squint angles, because it is severely limited by range walk, except in cases where we relax the spatial resolution. We consider the implications for the design of modest-resolution, narrow swath, scanning SAR scatterometers .

Synthetic Aperture radar (SAR)↗

Variations in the Sea Ice Edge and the Marginal Ice Zone on Different Spatial Scales as Observed from Different Satellite Sensor

The Marginal sea Ice Zone (MIZ) and the sea ice edge are the most dynamic areas of the sea ice cover. Knowledge of the sea ice edge location is vital for routing shipping in the polar regions. The ice edge is the location of recurrent plankton blooms, and is the habitat for a number of animals, including several which are under severe ecological threat. Polar lows are known to preferentially form along the sea ice edge because of induced atmospheric baroclinicity, and the ice edge is also the location of both vertical and horizontal ocean currents driven by thermal and salinity gradients. Finally, sea ice is both a driver and indicator of climate change and monitoring the position of the ice edge accurately over long time periods enables assessment of the impact of global and regional warming near the poles. Several sensors are currently in orbit that can monitor the sea ice edge. These sensors, though, have different spatial resolutions, different limitations, and different repeat frequencies. Satellite passive microwave sensors can monitor the ice edge on a daily or even twice-daily basis, albeit with low spatial resolution - 25 km for the Special Sensor Microwave Imager (SSM/I) or 12.5 km for the Advanced Microwave Scanning Radiometer (AMSR-E). Although special methods exist that allow the detection of the sea ice edge at a quarter of that nominal resolution (PSSM). Visible and infrared data from the Advanced Very High Resolution Radiometer (AVHRR) and from the Moderate Resolution Imaging Spectroradiometer (MODIS) provide daily coverage at 1 km and 250 m, respectively, but the surface observations me limited to cloud-free periods. The Landsat 7 Enhanced Thematic Mapper (ETM+) has a resolution of 15 to 30 m but is limited to cloud-free periods as well, and does not provide daily coverage. Imagery from Synthetic Aperture Radar (SAR) instruments has resolutions of tens of meters to 100 m, and can be used to distinguish open water and sea ice on the basis of surface and volume scattering characteristics. The Canadian RADARSAT C-band SAR provides data that cover the Arctic Ocean and the MIZ every 3 days. A change-point detection approach was utilized to obtain an ice edge estimate from the RADARSAT data The Quickscat scatterometer provides ice edge information with a resolution of a few kilometers on a near-daily basis. During portions of March and April of 2003 a series of aircraft flights were conducted over the ice edge in the Bering Sea carrying the Polarimetric Scanning Radiometer (PSR), which provides spectral coverage identical with the AMSR-E instrument at a resolution of 500 meters. In this study we investigated these different data sets and analyzed differences in their definition of the sea ice edge and the marginal ice zone and how these differences as well as their individual limitations affect the monitoring of the ice edge dynamics. We also examined how the nature of the sea ice edge, including its location, compactness and shape, changes over the seasons. Our approach was based on calculation of distances between ice edges derived from the satellite and aircraft data sets listed above as well as spectral coherence methods and shape parameters such as tortuosity, curvature, and fractional dimension.

Markus, Thorsten↗