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CSAPR2 CMAC 2.0 level c1 data.

Raw data from ARM precipitation radars must be corrected for atmospheric phenomena and instrument characteristics (e.g., attenuation, clutter) to retrieve precipitation properties. The Corrected Moments in Antenna Coordinates Version 2 (CMAC2) value-added product (VAP) is a set of algorithms and code that does such corrections, and it also retrieves precipitation quantities from the radar measurements. Similar to the X-SAPR radars at the ARM main site, C-SAPR2 radar data also needs corrections and improvements. CMAC 2.0 has been updated to work with the ARM C-SAPR 2 radar. Data and fields that have been processed to: correct for velocity aliasing, unfold and generate a cross-polarimetric phase difference that is monotonically increasing, removing impulses caused by non-uniform beam filling and phase shift on backscatter, recalculate specific differential phase using a 20-point Sobel filter on the aforementioned phase, correct for liquid path attenuation using the polarimetric signals, estimate rainfall rates at the gate using the specific attenuation. In addition, CMAC writes the data out into a community-standard format netCDF File using the CF/Radial conventions. The data are therefore compatible with new and existing National Center for Atmospheric Research (NCAR) tools such as RadXConvert for converting to a variety of popular file formats.

54 ENVIRONMENTAL SCIENCES↗

Calibration: Practical experience with ERS-1

Viewgraphs and discussion of calibration:practical experience with ERS-1 are presented. Topics covered include: radiometric calibration, geometric calibration, phase calibration, and polarimetric calibration. Basic synthetic aperture radar (SAR) measurement parameters are radar backscattering, target position, target speed, and polarization. SAR calibration facilitates quantitative measurements needed to derive geophysical parameters of the area under observation from basic SAR measurements (e.g. soil moisture, biomass, ocean wave energy, ocean currents, ice type, and ice flow).

Louet, Jacques↗

Evaluating spectral cloud effective radius retrievals from the Enhanced MODIS Airborne Simulator (eMAS) during ORACLES

Satellite remote sensing retrievals of cloud effective radius (CER) are widely used for studies of aerosol–cloud interactions. Such retrievals, however, rely on forward radiative transfer (RT) calculations using simplified assumptions that can lead to retrieval errors when the real atmosphere deviates from the forward model. Here, coincident airborne remote sensing and in situ observations obtained during NASA's ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) field campaign are used to evaluate retrievals of CER for marine boundary layer stratocumulus clouds and to explore impacts of forward RT model assumptions and other confounding factors. Specifically, spectral CER retrievals from the Enhanced MODIS Airborne Simulator (eMAS) and the Research Scanning Polarimeter (RSP) are compared with polarimetric retrievals from RSP and with CER derived from droplet size distributions (DSDs) observed by the Phase Doppler Interferometer (PDI) and a combination of the Cloud and Aerosol Spectrometer (CAS) and the Two-Dimensional Stereo Probe (2D-S). The sensitivities of the eMAS and RSP spectral retrievals to assumptions about the DSD effective variance (CEV) and liquid water complex index of refraction are explored. CER and CEV inferred from eMAS spectral reflectance observations of the backscatter glory provide additional context for the spectral CER retrievals. The spectral and polarimetric CER retrieval agreement is case dependent, and updating the retrieval RT assumptions, including using RSP polarimetric CEV retrievals as a constraint, yields mixed results that are tied to differing sensitivities to vertical heterogeneity. Moreover, the in situ cloud probes, often used as the benchmark for remote sensing CER retrieval assessments, themselves do not agree, with PDI DSDs yielding CER values 1.3–1.6 µm larger than CAS and with CEV roughly 50 %–60 % smaller than CAS. Implications for the interpretation of spectral and polarimetric CER retrievals and their agreement are discussed.

Meyer, Kerry [NASA Goddard Space Flight Center (GS↗

TPSAS-NF1676L-34013-DND

Currently, many experiments pursuing comprehensive characterization of the atmosphere include coordinated observations by both lidar and polarimeters in order to obtain important complimentary information about aerosol properties. The most advanced passive observations by space-based multi-angle polarimeters are sensitive to the properties of aerosol in total atmospheric column, but have very limited sensitivity to vertical structure of the atmosphere. Polarimeter observations can be used not only for retrieval of aerosol optical thickness, but also for deriving microphysical information about aerosol particle shape, size distribution, complex refractive index, and the properties of underlying surface (Dubovik et al., 2019). In a contrast, the lidar observations of atmospheric responses from different altitudes to laser pulses are designed to provide vertical profiles of atmospheric characteristics. Here we present the recent advancement in GRASP algorithm (Generalized Aerosol Retrieval of Atmospheric and Surface Properties) (Dubovik et al., 2011, 2014) that allows simultaneous inversion of co-incident lidar and polarimeter spaceborne observations and derives a united set of vertically resolved aerosol and surface parameters. Such synergetic retrieval is an extension to satellite data of the approach for synergetic processing of active and passive measurements developed earlier by (Lopatin et al., 2013) for ground-based observations. Another addition to these developments is the inclusion of Raman-shifted and volume depolarization backscattering observations that improve sensitivity to the vertical properties of aerosol, while polarimetric observations provide sufficient constraints on aerosol type and loading that generally are missing in lidar signals. The potential and limitations of such synergetic processing is illustrated by application to co-incident PARASOL and CALIPSO data.

Anton Lopatin↗

Interpreting asteroid photometry and polarimetry using a model of shadowing and coherent backscattering

The shadow-hiding models for the opposition effect and negative polarization of atmosphereless solar system bodies do not explain some experimental findings, such as the enhancing opposition effect and negative polarization with decreasing particle size down to wavelength scales. The enhancement for laboratory photometric and polarimetric data on artificial glass samples with different particle size is shown. These results are in agreement with the so-called coherent backscattering or interference mechanism proposed for the interpretation of the opposition effect and negative polarization. Two different approaches for describing the opposition effect and negative polarization produced by the shadow-interference mechanism were developed. One is based on exact electromagnetic solutions for simple scattering systems that include dipole-dipole and dipole-surface coupling; The other is based on a point-scatterer approximation characterized by model photometric and polarimetric phase functions, and the mutual shadowing effect is derived using virtual volumes associated with the point-scatterers. Both approaches yield qualitatively similar results, although neither is entirely satisfactory. We regard them as prototypes for a future unified model of shadowing and coherent backscattering. The sharp opposition effect of 44 Nysa and the asteroid albedo-polarization rule are here explained using the point-scatterer approach.

Shkuratov, Y. G.↗

Polarization effects and multipolarization SAR

Imaging radar polarimeters are usually implemented using a Synthetic Aperture Radar (SAR) approach to give a high resolution image in two dimensions: range and azimuth. For each pixel in the image a polarimetric SAR gives sufficient information to characterize the polarimetric scattering properties of the imaged area (or target) as seen by the radar. Using a polarimetric SAR system as opposed to a single-polarization SAR system provides significantly more information about the target scattering mechanisms and allows better discrimination between different types of surfaces. In these notes a brief overview of SAR polarimetry is offered. The notes are intended as a text to accompany a lecture on SAR polarimetry as part of an AGARD-NATO course. Covered in the notes are the following: the polarization properties of electromagnetic waves; the concepts of radar scattering and measuring radar backscatter with a SAR; polarization synthesis; scattering matrix, Stokes matrix, and covariance matrix representations of polarimetric SAR data; polarization signature plots; design and calibration of polarimetric SAR systems; polarization filtering for target detection; fitting a simple model to polarimetric SAR measurements of naturally occurring features; and supervised classification of polarimetric SAR data.

Freeman, Anthony↗

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.↗

Enhancement effects in polarimetric radar returns: Phase difference statistics

The probability density functions (pdfs) of the co- and cross-polarized phase differences are derived for backscatter from vegetation using the coherent and incoherent scattering theories. Unlike previous derivations, no assumptions or observations other than the applicability of the Central Limit Theorem (CLT), the low fractional volume of the medium, the reciprocity of the scatterers, and the azimuthal symmetry of the scatterer's orientation statistics are employed. Everything else follows logically via the mathematics. The difference between the coherent theory and the incoherent theory is referred to as the backscatter enhancement effect. The influence of this enhancement effect on the phase difference pdfs is examined and found to be important under combined conditions of scatterer anisotropy and appropriate reflection coefficient values.

Lang, R. H.↗

Backscatter for Ice Sheet 2 Growth Phase in the Winter 1994 Winter Sea Ice Experiment

None. This is raw data from a data set taken during the CRRELEX94 experiment. The data are polarimetric C-band radar measurements of a saline ice sheet grown in the outdoor Geophysical Research Facility at the Cold Regions Research and Engineering Lab. See references for other descriptions of data.

sea ice ice sheet backscatter sea ice backscatter ↗

A fully polarimetric scattering model for a coniferous forest

For an elliptically polarized plane wave exciting a coniferous forested canopy a fully polarimetric scattering model has been developed to account for the size and orientation distributions of each forest constituent. A canopy is divided into three layers over a rough interface. The upper two layers represent the crown with its constituents (leaves, stems, and branches). The lower layer stands for the trunks and the rough interface is the canopy-ground interface. For a plane wave exciting the canopy, the explicit expressions for the bistatic scattering coefficient associated with each scattering mechanism are given. For an elliptically polarized incidence wave, the present model can be recast in a form suitable for polarimetric wave synthesis. The model validation is justified by comparing the measured and the calculated values of the backscattering coefficients for a linearly polarized incident wave. The comparison is made over a wide range of frequencies and incident angles. Numerical simulations are conducted to calculate the radar polarization signature of the canopy for different incident frequencies and angles.

Karam, M. A.↗

Multifrequency polarimetric synthetic aperture radar observations of sea ice

The present study introduces a fully polarimetric airborne SAR data set of sea ice. Images were acquired in the Beaufort, Bering, and Chukchi seas in March 1988. Statistics of the magnitude, phase, and polarization of complex backscattered signals recorded by three-frequency SAR are examined for various scenes with different ice characteristics. Results indicate that combinations of frequency and polarization enhance current capability to distinguish ice of different properties using single-frequency fixed-polarization-microwave radar. A specific example is the polarimetric identification of new ice formation which may not be easily distinguished in ERS-1 5.3-GHz VV polarization of SAR data. Such findings are consistent with theoretical model simulations of scattering characteristics of sea ice.

Drinkwater, Mark R.↗

Soil moisture retrieval in the Oberpfaffenhofen testsite using MAC Europe AIRSAR data

Soil moisture content is an important parameter in many disciplines of science like hydrology, meteorology, agriculture and others. Microwave remote sensing technique has a high potential in measuring the dielectric constant of soils, which is strongly governed by the soil moisture. Much excellent work has been done on investigating the relationship between backscattering coefficient and soil moisture. Most of these studies are measured in a laboratory or are carried out with a multitemporal data set. This means, that the variation in the backscattering coefficient is only related to the soil moisture because all other parameters influencing the backscattering like surface roughness, vegetation cover, plant geometry, phenology of plants and row direction are kept constant. In this study the sensitivity of the backscattering coefficient to soil moisture of corn fields is investigated. In the framework of the MAC-Europe Campaign in June 1991, the NASA/JPL three-frequency polarimetric AIRSAR system collected data over the test site Oberpfaffenhofen. The AIRSAR campaign in Oberpfaffenhofen was complemented with intensive ground truth measurements. The sampled corn fields are nearly in the range of the same incidence angle (approximately 20 deg) and belong to different soil types. The evaluation was carried out at a single data set. The results show that the backscattering, measured at P-band, can be described with only two parameters very well. The main parameter influencing the backscattering is the soil moisture content; the second subordinated parameter is the row direction.

Wever, Tobias↗

MAX-91: Polarimetric SAR results on Montespertoli site

The polarimetric Synthetic Aperture Radar (SAR) is a powerful sensor for high resolution ocean and land mapping and particularly for monitoring hydrological parameters in large watersheds. There is currently much research in progress to assess the SAR operational capability as well as to estimate the accuracy achievable in the measurements of geophysical parameters with the presently available airborne and spaceborne sensors. An important goal of this research is to improve our understanding of the basic mechanisms that control the interaction of electro-magnetic waves with soil and vegetation. This can be done both by developing electromagnetic models and by analyzing statistical relations between backscattering and ground truth data. A systematic investigation, which aims at a better understanding of the information obtainable from the multi-frequency polarimetric SAR to be used in agro-hydrology, is in progress by our groups within the framework of SIR-C/X-SAR Project and has achieved a most significant milestone with the NASA/JPL Aircraft Campaign named MAC-91. Indeed this experiment allowed us to collect a large and meaningful data set including multi-temporal multi-frequency polarimetric SAR measurements and ground truth. This paper presents some significant results obtained over an agricultural flat area within the Montespertoli site, where intensive ground measurements were carried out. The results are critically discussed with special regard to the information associated with polarimetric data.

Baronti, S.↗

Using Polarimetric SAR Data to Infer Soil Moisture from Surfaces with Varying Subsurface Moisture Profiles

A time-series approach is used to estimate the moisture content-based on polarimetric SAR data. It is found that under the assumption of constant soil moisture, empirically observed relationships between radar backscatter and moisture are only half as sensitive to moisture as compared to actual radar data. A numerical finite element method is used to calculate the radar backscatter for rough soils with arbitrarily varying soil moisture as a function of depth. Several instance of drying and wetting moisture profiles are considered and the radar backscatter is calculated in each case. Radar backscatter is found to crucially depend on the soil moisture variation in the top half wavelength of soil.

subsurface sensing↗

Radar backscattering from snow facies of the Greenland ice sheet: Results from the AIRSAR 1991 campaign

In June 1991, the NASA/JPL airborne SAR (AIRSAR) acquired C- (lambda = 5.6cm), L- (lambda = 24cm), and P- (lambda = 68m) band polarimetric SAR data over the Greenland ice sheet. These data are processed using version 3.55 of the AIRSAR processor which provides radiometrically and polarimetrically calibrated images. The internal calibration of the AIRSAR data is cross-checked using the radar response from corner reflectors deployed prior to flight in one of the scenes. In addition, a quantitative assessment of the noise power level at various frequencies and polarizations is made in all the scenes. Synoptic SAR data corresponding to a swath width of about 12 by 50 km in length (compared to the standard 12 x 12 km size of high-resolution scenes) are also processed and calibrated to study transitions in radar backscatter as a function of snow facies at selected frequencies and polarizations. The snow facies on the Greenland ice sheet are traditionally categorized based on differences in melting regime during the summer months. The interior of Greenland corresponds to the dry snow zone where terrain elevation is the highest and no snow melt occurs. The lowest elevation boundary of the dry snow zone is known traditionally as the dry snow line. Beneath it is the percolation zone where melting occurs in the summer and water percolates through the snow freezing at depth to form massive ice lenses and ice pipes. At the downslope margin of this zone is the wet snow line. Below it, the wet snow zone corresponds to the lowest elevations where snow remains at the end of the summer. Ablation produces enough meltwater to create areas of snow saturated with water, together with ponds and lakes. The lowest altitude zone of ablation sees enough summer melt to remove all traces of seasonal snow accumulation, such that the surface comprises bare glacier ice.

Rignot, Eric↗

A snow wetness retrieval algorithm for SAR

The objectives of this study are: (1) to evaluate the backscattering signals response to snow wetness; and (2) to develop an algorithm for snow wetness measurement using C-band polarimetric synthetic aperture radar (SAR). In hydrological investigations, modeling and forecasting of snowmelt runoff requires information about snowpack properties and their spatial variability. In particular, timely measurement of snow parameters is needed for operational hydrology. The liquid water content of snowpack is one of the important parameters. Active microwave sensors are highly sensitive to liquid water in the snowpack because of the large dielectric contrast between ice and water in the microwave spectrum. They are not affected by weather and have a spatial resolution compatible with the topographic variation in alpine regions. However, a quantitative algorithm for retrieval snow wetness has not yet been developed.

Shi, Jian-Cheng↗