Development of a distributed sensor that can simultaneously measure strain and temperature variations based on Rayleigh-backscattering optical fibers
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A sample mount having a bottom surface, a front surface, and a second portion is disclosed. The first portion is perpendicular to the bottom surface. The second portion has an external surface and an internal surface and extends from the first portion to form a 70-degree angle relative to the bottom surface. The sample mount may also have a top surface, an opening extending through the second portion of the front surface, and a receiving area configured to receive a sample, wherein the top surface presents an unimpeded path between the sample and an SEM pole piece. The sample mount may include a spring-loaded handle configured to push the sample against the internal surface of the second portion of the front surface, wherein pushing the sample against the internal surface places the sample at the 70-degree angle relative to the bottom surface.
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During the First ISCCP Region Experiment (FIRE) cirrus intensive field observation (IFO) the High Spectral Resolution Lidar was operated from a roof top site on the University of Wisconsin-Madison campus. Because the HSRL technique separately measures the molecular and cloud particle backscatter components of the lidar return, the optical thickness is determined independent of particle backscatter. This is accomplished by comparing the known molecular density distribution to the observed decrease in molecular backscatter signal with altitude. The particle to molecular backscatter ratio yields calibrated measurements of backscatter cross sections that can be plotted ro reveal cloud morphology without distortion due to attenuation. Changes in cloud particle size, shape, and phase affect the backscatter to extinction ratio (backscatter-phase function). The HSRL independently measures cloud particle backscatter phase function. This paper presents a quantitative analysis of the HSRL cirrus cloud data acquired over an approximate 33 hour period of continuous near zenith observations. Correlations between small scale wind structure and cirrus cloud morphology have been observed. These correlations can bias the range averaging inherent in wind profiling lidars of modest vertical resolution, leading to increased measurement errors at cirrus altitudes. Extended periods of low intensity backscatter were noted between more strongly organized cirrus cloud activity. Optical thicknesses ranging from 0.01-1.4, backscatter phase functions between 0.02-0.065 sr (exp -1) and backscatter cross sections spanning 4 orders of magnitude were observed. the altitude relationship between cloud top and bottom boundaries and the cloud optical center altitude was dependent on the type of formation observed Cirrus features were observed with characteristic wind drift estimated horizontal sizes of 5-400 km. The clouds frequently exhibited cellular structure with vertical to horizontal dimension ratios of 1:5-1:1.
Intrieri et al. (1993) and later O’Connor et al. (2005) proposed a technique to constrain water drop size distribution using lidar backscatter (related to water drop cross-section) and Doppler spectral width (related to the width of the water drop size distribution). This radar-lidar technique can be used to estimate precipitation rate and microphysical characteristics at all levels in the subcloud layer when collocated radar and ceilometer observations are available. We apply this technique to the vertically pointing ARM ceilometer lidar and Ka-band Zenith Radar (KAZR2) pair. The O’Connor et al. (2005) technique requires ceilometer backscatter to be calibrated and remapped to the radar spatio-temporal resolution (here 2 s x 30 m). Ceilometer backscatter is calibrated following a variation of the O'Connor et al. (2004) technique by scaling observed path-integrated backscatter in thick stratocumulus to match theoretical cloud lidar ratio values. Satisfactory conditions for ceilometer backscatter calibration are identified as the first (in time) 20-min periods each day with standard deviation of lidar ratio smaller than 1.5. The observed backscatter during the “satisfactory 20-min period” are input to Hogan (2006)’s multi scattered model to determine a daily backscatter calibration factor. For days where satisfactory conditions are not observed, a climatological calibration factor of 1.35 is used to calibrate the observed backscatter. Calibrated ceilometer backscatter is subsequently mapped on the KAZR2 time-height grid using a nearest-neighbor approach. Following Kollias et al. (2019), KAZR2 calibration is performed using collocated surface-based Parsivel laser disdrometer-equivalent radar reflectivity estimates during light precipitation events. This radar-lidar technique generates time-height maps of precipitation rate from 200 m above ground level to 90 m below cloud base height that are filtered for aerosol contamination.
We demonstrate for the first time the utility of spaceborne Ku-band scatterometer for global snow cover monitoring. Satellite radar data were collected over the globe by the NASA Scatterometer (NSCAT) operated at 14 GHz on board the Japanese ADEOS spacecraft from September 1996 to June 1997, spanning the 1997 seasonal snow season. First, we present backscatter signature of dry and wet snow to facilitate the interpretation of NSCAT backscatter evolution over snow cover regions. Surface field experiments indicated that dry snow backscatter at Ku band is approximately 40 times stronger than that at C band. Thus, Ku-band scatterometer measurements are sensitive to snow cover, which is typically transparent to C-band scatterometer returns. Furthermore, Ku-band backscatter does not saturate for most of natural snow depths as compared to radar responses at 19 GHz and 37 GHz or higher frequencies which have more limited penetration depths into snow. Ku-band backscatter is also sensitive to wetness in snow, which is appropriate to detect early snow melt conditions. Using the snow backscatter characteristics, we investigate NSCAT backscatter evolution over global snow cover regions throughout the 1997 snow season. The results reveal detail delineations between different regional snow areas. We show the correlation of these delineations with the boundaries of different global snow classes defined by the U.S. Army Cold Regions Research and Engineering Laboratory snow classification system. Using in-situ snow depth data from the U.S. National Climatic Data Center, we show that Ku-band backscatter corresponds very well to the trend of snow melt while snow mapping products (U.S. Climate Prediction Center gridded snow charts) from visible sensors does not reflect the fast snow melt trend. To illustrate the practical application of global snow monitoring with spaceborne Ku-band scatterometer, we present NSCAT backscatter response corresponding to the snow event leading to the 1997 Flood of the Century over the U.S. Northern plains and the Canadian prarie region, which caused loss of lives and several billion dollars in flood related damages and cleanup costs. Finally, we show that the fixed incidence configuration of Seawinds scatterometers, to be launched on QuickSCAT and on ADEOS-2 in the near future, is better for snow monitoring and then discuss the use of future high-resolution scatterometers for global snow mapping.
We present the polarization reversal in backscatter over flooded land regions, and demonstrate for the first time the utility of spaceborne Ku-band scatterometer for large-scale flood mapping. Scatterometer data were collected over the globe by the NASA Scatterometer (NSCAT) operated at 14 GHz on the Japanese ADEOS spacecraft from September 1996 to June 1997. During this time span, several severe floods occurred. Over most land surface, vertical polarization backscatter (Sigma(sub upsilon(upsilon)) is larger than horizontal polarization backscatter (sigma(sub hh)). Such polarization characteristics is reversed and sigma(sub upsilon(upsilon)) is smaller than sigma(sub hh) over flooded regions, except under a dense forest canopy. The total backscatter from the flooded landscape consists of direct backscatter and boundary-interaction backscatter. The direct term is contributed by direct backscattering from objects protruding above the water surface, and by backscattering from waves on the water surface. The boundary-interaction term is contributed by the forward scattering from the protruding objects and then reflected from the water surface, and also by the forward scattering from these objects after the water-surface reflection. Over flooded regions, the boundary-interaction term is dominant at large incidence angles and the strong water-surface reflection is much larger for horizontal polarization than the vertical one due to the Brewster effect in transverse-magnetic waves. These scattering mechanisms cause the polarization reversal over flooded regions. An example obtained with the Analytic Wave Theory is used to illustrate the scattering mechanisms leading to the polarization reversal. We then demonstrate the utility of spaceborne Ku-band scatterometer for large-scale flood mapping. We process NSCAT data to obtain the polarization ratio sigma(sub hh)/sigma(sub upsilon(upsilon)) with colocated data at incidence angles larger than 40 deg. The results over Asian summer monsoon regions in September-October 1996 indicate flooded areas in many countries such as Bangladesh, India, Lao, Vietnam, Cambodia, and China. Reports documented by the United Nation Department of Humanitarian Affairs (now called UN Office for the Coordination of Humanitarian Affairs) show loss of many lives and severe flood related damages which affected many million people in the corresponding flooded areas. We also map the NSCAT polarization ratio over the same regions in the "dry season" in January 1997 as a reference to confirm our results. Furthermore, we obtain concurrent ocean wind fields also derived from NSCAT data, and Asia topographic data (USGS GTOPO30) to investigate the flooded area. The results show that winds during summer monsoon season blowing inland, which perplex flood problems. Overlaying the topographic map over NSCAT results reveals an excellent correspondence between the confinement of flooded area within the relevant topographic features, which very well illustrates the value of topographic wetness index. Finally, we discuss the applications of future spaceborne scatterometers, including QuikSCAT and Seawinds, for flood mapping over the globe.
The Doppler lidars (DL) at the ARM observatories operate at 1.5-micrometer wavelength and record backscatter and mean Doppler velocity. The DL present at the ARM ENA site records these quantities at a 1-second temporal and 30-meter range resolution. Reported here are daily files containing gridded values of noise-filtered and calibrated backscatter, and noise-filtered mean Doppler velocity. In addition we also report the noise-filtered and calibrated gradient of backscatter that is used to derive estimates of cloud base height. All of the variables are reported at a uniform 5-second temporal resolution and 30-m range resolution. The instrument reported raw backscatter was first corrected for telescope focus function, filtered for noise, and then calibrated by exploiting the constant lidar ratio exhibited during nonprecipitating stratocumulus cloud conditions. Hence, the reported backscatter can be used to derive aerosol and hydrometeor properties. Daily files are reported for the summer Intensive Operational Period (IOP) of the Aerosol, and Cloud and Experiments in the Eastern North Atlantic (ACE-ENA) field campaign. Similar files can be produced for any DL at ARM observatories. Please find below the header of the NetCDF files. double time (time) ; time:Long_Name = "Time" ; time:units = "Seconds from 1970-1-1 0:00:00" ; double height (height) ; height:Long_Name = "Height" ; height:units = "meters" ; double dl_el (time) ; dl_el:Long_Name = "elevation" ; dl_el:units = "degrees"; double dl_beta (time, height) ; dl_beta:Long_Name = "Noise Filtered Calibrated Backscatter" ; dl_beta:units = "1 / (m * Sr)" ; double dl_velo (time, height); dl_velo:Long_Name = "Mean Doppler Velocity" ; dl_velo:units = "m/s" ; double dl_att (time, height) ; dl_att:Long_Name = "Gradient of Backscatter" ; dl_att:units = "1 / (m ^ 2 * Sr)" ; double base (time) ; base:Long_Name = "Cloud base height" ; base:units = "meters" ;
A NASA Electra airplane, outfitted with a lidar system, was flown in January to February 1983 between the latitudes of 27 deg N and 76 deg N. One of the primary purposes of this mission was to determine the spatial distribution and aerosol characteristics of the El Chichon-produced stratospheric material. This report presents the lidar data from that flight mission. Representative profiles of lidar backscatter ratio, plots of the integrated backscattering function versus latitude, and contours of backscatter mixing ratio versus altitude and latitude are given. It addition, tables containing numerical values of the backscatter ratio and backscattering function versus altitude are supplied for each profile. The largest amount of material produced by the El Chichon eruptions of late March to early April 1982, which was measured by this flight, resided between 35 deg N and 52 deg N. Peak backscatter ratios at a wavelength of 0.6943 micro m decreased from 8 to 10 at the lower latitudes to 3 at the higher latitudes. Backscatter ratio profiles taken while crossing the polar vortex show that the high-altitude material from El Chichon arrived at the north polar region sometime after the winter polar vortex was established. This report presents the results of this mission in a ready-to-use format for atmospheric and climatic studies.
An experimental survey flight to determine the spatial distribution and aerosol characteristics of the El Chichon-produced stratospheric aerosol was conducted in May 1983. The mission included several different sensors flown abroad the NASA Convair 990 at latitudes between 72 deg. and 56 deg. S. This report presents the lidar data from that flight mission. Representative profiles of lidar backscatter ratio, plots of integrated backscattering function versus latitude, and contours of backscatter mixing ratio versus altitude and latitude are given. In addition, tables containing numerical values of the backscatter ratio and backscattering function versus altitude are supplied for each profile. By May 1983, material produced by the El Chichon eruptions of late March-early April 1982 had spread throughout the latitudes covered by this mission. However, the most massive portion of the material resided north of 33 deg. N and was concentrared below 21 km. In this latitude region (33 deg. N to 72 deg. N), peak backscatter ratios at a wavelength of 0.6943 microns varied between 3.5 and 4.5, and the peak integratred backscattering function was about 18 X 10 to the -4 power/sr, corresponding to a peak optical depth calculated to be approximately 0.08. This report presents the results of this mission in a ready-to-use format for atmospheric and climatic studies.
A lidar-equipped NASA Electra aircraft was flown in January 1984 between the latitude of 38 and 90 deg N. One of the primary purposes of this mission was to determine the spatial distribution and aerosol characteristics of El Chichon produced stratospheric material. Lidar data from that portion of the flight mission between 38 deg N and 77 deg N is presented. Representative profiles of lidar backscatter ratio, a plot of the integral backscattering function versus latitude, and contours of backscatter mixing ratio versus altitude and latitude are given. In addition, tables containing numerical values of the backscatter ratio and backscattering function versus altitude are applied for each profile. These data clearly show that material produced by the El Chichon eruptions of late March-early April 1982 had spread throughout the latitudes covered by this mission, and that the most massive portion of the material resided north of 55 deg N and was concentrated below 17 km in a layer that peaked at 13 to 15 km. In this latitude region, peak backscatter ratios at a wavelength of 0.6943 microns were approximately 3 and the peak integrated backscattering function was about 15 X 10 to the -4/sr corresponding to a peak optical depth of approximately 0.07. This report presents the results of this mission in a ready-to-use format for atmospheric and climatic studies.
Experimental and theoretical studies were performed of atmospheric aerosol backscatter and atmospheric dynamics with Doppler lidar as a primary tool. Activities include field and laboratory measurement and analysis efforts. The primary focus of activities related to understanding aerosol backscatter is the GLObal Backscatter Experiment (GLOBE) program. GLOBE is a multi-element effort designed toward developing a global aerosol model to describe tropospheric clean background backscatter conditions that Laser Atmospheric Wind Sounder (LAWS) is likely to encounter. Two survey missions were designed and flown in the NASA DC-8 in November 1989 and May to June 1990 over the remote Pacific Ocean, a region where backscatter values are low and where LAWS wind measurements could make a major contribution. The instrument complement consisted of pulsed and continuous-wave (CW) CO2 gas and solid state lidars measuring aerosol backscatter, optical particle counters measuring aerosol concentration, size distribution, and chemical composition, a filter/impactor system collecting aerosol samples for subsequent analysis, and integrating nephelometers measuring visible scattering coefficients. The GLOBE instrument package and survey missions were carefully planned to achieve complementary measurements under clean background backscatter conditions.
Earth Remote-Sensing Satellite (ERS) 1 synthetic aperture radar (SAR) and Landsat thematic mapper (TM) images were acquired for the same area in the Beaufort Sea, April 16 and 18, 1992. The two image pairs were colocated to the same grid (25-m resolution), and a supervised ice type classification was performed on the TM images in order to classify ice free, nilas, gray ice, gray-white ice, thin first-year ice, medium and thick first-year ice, and old ice. Comparison of the collocated SAR pixels showed that ice-free areas can only be classified under calm wind conditions (less than 3 m/s) and for surface winds greater than 10 m/s based on the backscattering coefficient alone. This is true for pack ice regions during the cold months of the year where ice-free areas are spatially limited and where the capillary waves that cause SAR backscatter are dampened by entrained ice crystals. For nilas, two distinct backscatter classes were found at -17 dB and at -10 dB. The higher backscattering coefficient is attributed to the presence of frost flowers on light nilas. Gray and gray-white ice have a backscatter signature similar to first-year ice and therefore cannot be distinguished by SAR alone. First-year and old ice can be clearly separated based on their backscattering coefficient. The performance of the Geophysical Processor System ice classifier was tested against the Landsat derived ice products. It was found that smooth first-year ice and rough first-year ice were not significantly different in the backscatter domain. Ice concentration estimates based on ERS 1 C band SAR showed an error range of 5 to 8% for high ice concentration regions, mainly due to misclassified ice-free and smooth first-year ice areas. This error is expected to increase for areas of lower ice concentration. The combination of C band SAR and TM channels 2, 4, and 6 resulted in ice typing performance with an estimated accuracy of 90% for all seven ice classes.
Clouds interfere with the distribution of short-wave and long-wave radiations over sea ice, and thereby strongly affect the surface energy balance in polar regions. To evaluate the overall effects of clouds on climatic feedback processes in the atmosphere-ice-ocean system, the challenge is to observe sea ice surface thermal states under both clear sky and cloudy conditions. From laboratory experiments, we show that C-band radar (transparent to clouds) backscatter is very sensitive to the surface temperature of first-year sea ice. The effect of sea ice surface temperature on the magnitude of backscatter change depends on the thermal regimes of sea ice thermodynamic states. For the temperature range above the mirabilite (Na2SO4.10H20) crystallization point (-8.2 C), C-band data show sea ice backscatter changes by 8-10 dB for incident angles from 20 to 35 deg at both horizontal and vertical polarizations. For temperatures below the mirabilite point but above the crystallization point of MgCl2.8H2O (-18.0 C), relatively strong backwater changes between 4-6 dB are observed. These backscatter changes correspond to approximately 8 C change in temperature for both cases. The backscattering mechanism is related to the temperature which determines the thermodynamic distribution of brine volume in the sea ice surface layer. The backscatter is positively correlated to temperature and the process is reversible with thermodynamic variations such as diurnal insolation effects. From two different dates in May 1993 with clear and overcast conditions determined by the Advanced Very High Resolution Radiometer (AVHRR), concurrent Earth Resources Satellite 1 (ERS-1) C-band ice observed with increases in backscatter over first-year sea ice, and verified by increases in in-situ sea ice surface temperatures measured at the Collaborative-Interdisciplinary Cryosphere Experiment (C-ICE) site.
The use of lidars and radars to measure forest structure attributes such as height and biomass are being considered for future Earth Observation missions. Large footprint lidar makes a direct measurement of the heights of scatterers in the illuminated footprint and can yield information about the vertical profile of the canopy. Synthetic Aperture Radar (SAR) is known to sense the canopy volume, especially at longer wavelengths and is useful for estimating biomass. Interferometric SAR (InSAR) has been shown to yield forest canopy height information. For example, the height of scattering phase retrieved from InSAR data is considered to be correlated with the three height and the spatial structure of the forest stand. There is much interest in exploiting these technologies separately and together to get important information for carbon cycle and ecosystem science. More detailed information of the electromagnetic radiation interactions within forest canopies is needed. And backscattering models can be of much utility here. As part of a NASA funded project to explore data fusion, a three-dimensional (3D) coherent radar backscattering model and a 3D lidar backscatter models were used to investigate the use of large footprint lidar, SAR and InSAR for characterizing realistic forest scenes. For this paper, we use stem maps and other forest measurements to develop a realistic spatial structure of a spruce-hemlock forest canopy found in Maine, USA. The radar and lidar models used measurements of the 3D forest scene as input and simulated the coherent radar backscattering signature and 1064nm energy backscatter, respectively. The relationships of backscatter derived forest structure were compared with field measurements. In addition, we also had detailed airborne lidar (Laser Imaging Vegetation Sensor, LVIS) data available over the stem map sites that was used to study the accuracies of tree height derived from modeled SAR backscatter and the scattering phase center retrieved from the simulated InSAR data will be compared with the height indices, or other structure parameters derived from the lidar data. These results will address the possible synergies between lidar and radar in data in terms of forest structural information.
Use of remote sensing data for mapping and monitoring of forest biomass across large spatial scales can aid in addressing uncertainties in carbon cycle. Earlier, several researchers reported on the use of Synthetic Aperture Radar (SAR) data for characterizing forest structural parameters and the above ground biomass estimation. However, these studies cannot be generalized and the algorithms cannot be applied to all types of forests without additional information on the forest physiognomy, stand structure and biomass characteristics. The radar backscatter signal also saturates as forest parameters such as biomass and the tree height increase. It is also not clear how different polarizations (VV versus VH) impact the backscatter retrievals in different forested regions. Thus, it is important to evaluate the potential of SAR data in different landscapes for characterizing forest structural parameters. In this study, the SAR data from Sentinel-1A has been used to characterize forest structural parameters including the above ground biomass from tropical forests of India. Ground based data on tree density, basal area and above ground biomass data from thirty-eight different forested sites has been collected to relate to SAR data. After the pre-processing of Sentinel 1-A data for radiometric calibration, geo-correction, terrain correction and speckle filtering, the variability in the backscatter signal in relation tree density, basal area and above biomass density has been investigated. Results from the curve fitting approach suggested exponential model between the Sentinel-1A backscatter versus tree density and above ground biomass whereas the relationship was almost linear with the basal area in the VV polarization mode. Of the different parameters, tree density could explain most of the variations in backscatter. Both VV and VH backscatter signals could explain only thirty and thirty three percent of variation in above biomass in different forest sites of India. Results also suggested saturation of the Sentinel-1A backscatter signal around hundred tonnes per hectare for VV polarization and one hundred and forty five tonnes per hectare for VH polarization. The presentation will highlight the above results in addition to potentials and limitations of Sentinel-1A data for retrieving forest structural parameters. Also, background information on different forest types of India, biomass variations and forest type mapping efforts in the region will be presented.
The Doppler lidar (DL) is an active remote-sensing instrument that provides range- and time-resolved measurements of the line-of-sight component of air velocity (i.e., radial velocity) and attenuated aerosol backscatter. The DL operates in the near-infrared and is sensitive to backscatter from atmospheric aerosol, which are assumed to be ideal tracers of atmospheric wind fields. The DL works by transmitting short pulses of infrared laser light into the atmosphere. Atmospheric aerosols scatter a small fraction of that light energy back to the transceiver, where it is collected and recorded as a time-resolved signal. From the delay between the outgoing pulse and the backscattered signal, the instrument infers the distance to the scattering volume. Coherent detection is used to measure the Doppler frequency shift of the backscatter signal. This is accomplished by mixing the backscatter signal with a reference laser beam (i.e., local oscillator) of known frequency. The onboard signal processor then determines the Doppler frequency shift from the spectrum of the mixed signal. The Doppler frequency shift and thus the radial air velocity is determined from the peak of the Doppler spectrum. The attenuated backscatter is determined from the energy content of the Doppler spectra. The DL provides accurate measurements of radial velocity in regions of the atmosphere where aerosol concentrations are high enough to ensure good signal-to-noise ratio. Thus, valid data are usually limited to the atmospheric boundary layer where aerosol is ubiquitous. Valid measurements can also be obtained in elevated aerosol layers or in optically thin clouds above the boundary layer. Most of the ARM DLs have full upper-hemispheric scanning capability, enabling 3D mapping of turbulent flows in the atmospheric boundary layer. With the scanner pointed vertically, the DL provides height- and time-resolved measurements of vertical velocity.