Remote sensing of earth terrain

A systematic approach for the identification of terrain media such as vegetation canopy, forest, and snow covered fields is developed using the optimum polarimetric classifier. The covariance matrices for the various terrain cover are computed from theoretical models of random medium by evaluating the full polarimetric scattering matrix elements. The optimal classification scheme makes use of a quadratic distance measure and is applied to classify a vegetation canopy consisting of both trees and grass. Experimentally measured data are used to validate the classification scheme. Theoretical probability of classification error using the full polarimetric matrix are compared with classification based on single features including the phase difference between the VV and HH polarization returns. It is shown that the full polarimetric results are optimal and provide better classification performance than single feature measurements

Remote sensing of earth terrain

A mathematically rigorous and fully polarimetric radar clutter model used to evaluate the radar backscatter from various types of terrain clutter such as forested areas, vegetation canopies, snow covered terrains, or ice fields is presented. With this model, the radar backscattering coefficients for the multichannel polarimetric radar returns can be calculated, in addition to the complex cross correlation coefficients between elements of the polarimetric measurement vector. The complete polarization covariance matrix can be computed and the scattering properties of the clutter environment characterized over a broad range of incident angle and frequencies

Remote sensing of earth terrain

A systematic approach for the identification of terrain media such as vegetation canopy, forest, and snow covered fields is developed using the optimum polarimetric classifier. The covariance matrices for the various terrain covers are computed from the theoretical models of random medium by evaluating the full polarimetric scattering matrix elements. The optimal classification scheme makes use of a quadratic distance measure and is applied to classify a vegetation canopy consisting of both trees and grass. Experimentally measured data are used to validate the classification scheme. Theoretical probability of classification error using the full polarimetric matrix are compared with classification based on single features including the phase difference between the VV and HH polarization returns. It is shown that the full polarimetric results are optimal and provide better classification performance than single feature measurements. A systematic approach is presented for obtaining the optimal polarimetric matched filter which produces maximum contrast between two scattering classes, each represented by its respective covariance matrix

Specular null polarization theory: applications to radar meteorology

Includes bibliographical references.Specular null polarization theory (SNPT) has been recently introduced for the case of coherent scattering where a 2 x 2 scattering matrix is sufficient to describe the scattering process. In this paper, SNPT is extended to the case of incoherent scattering. Optimum polarization states are derived and the results are discussed in relation to the classic radar optimum polarizations. In traditional radar polarimetry, modeling of the radar receive/transmit network is included in the radar voltage equation and consequently this affects the optimum polarizations and polarization responses of scatterers. SNPT eliminates this effect and therefore allows for a more direct analysis of scatterers. Modeling of ensembles of precipitation particles is used to illustrate the results of the analysis.This work was supported by the National Science Foundation under Grants ATM-8915141 and ATM-9214864

Microphysical characteristics of ice crystals and snowflakes as revealed by polarimetric radar measurements

Summer 1998.Also issued as Christine Musick Reese Butler's thesis (M.S.) -- Colorado State University, 1998.Includes bibliographical references.This research encompassed both observational and theoretical aspects of copolar and differential reflectivity in the less explored, yet important, winter season precipitation. The observational portion was conducted with the multiparameter, CSU-CHILL radar and supplemented by observers at the Fort Collins Weather Station on the Campus of Colorado State University (FCL) who recorded microphysical features of the snowfall such as snow type, composition, size, and degree of riming. Additionally, a 2-D video disdrometer, located at FCL, made particle size distribution measurements. In order to compare the appropriate radar data with the ground observations, the approximate trajectory of the snow was computed from the height it was interrogated by the radar to the surface. The trajectory, applied in reverse from FCL, identified the source region of the observed snow in the 0.5° and 1° elevation scans of the radar. The results of the observational analyses suggest that nearly homogeneous populations of aggregates can be distinguished from platelike crystals (i.e. dendrites, stellar crystals, and plates) using a combination of co-polar and differential reflectivity (Z and ZoR) radar observations. Furthermore, it appears possible to discern whether or not the platelike crystals are intensely rimed. Additionally, the results challenge the validity of the common assumption that aggregates always produce a ZoR value of O dB. Scattering model studies based on T-matrix theory and the Mueller matrix method were conducted to demonstrate the consistency of the observed radar variables with theoretical values and to test our speculations on which hydrometeor microphysical characteristics were responsible for the observed variations in those variables. Our modeling results suggest several conclusions. First, the aggregate shapes are more relevant and have more impact on ZoR than generally expected; therefore, the modeling assumption that all aggregates are nearly spherical can produce erroneously low ZoR values. Secondly, the size-dependent density formulas for aggregates which predict that bulk densities decrease with size may not always be applicable. Next, the canting of hydrometeors can overcome the influence of microphysical characteristics on Zoa; thus, in a model, it is important to include canting for turbulent situations. when it likely occurred and to exclude it for calmer situations where it was not likely to have occurred. Lastly, the model results validated the idea that intensely rimed platelike crystals could be distinguished from other platelike crystals and highlighted the problems that can be encountered if modelers depend upon size-dependent axis ratio formulas without considering the effects of riming.Sponsored by the National Science Foundation ATM-9612519

Electromagnetic Wave Theory and Applications

Contains reports on twelve research projects.Joint Services Electronics Program (Contract DAALO3-86-K-0002)National Science Foundation (Grant ECS 85-04381)National Aeronautics and Space Administration/Goddard Space Flight Center (Contract NAG5-270)National Aeronautics and Space Administration/Goddard Space Flight Center (Contract NAG5-725)U.S. Navy - Office of Naval Research (Contract N00014-83-K-0258)U.S. Navy - Office of Naval Research (Contract N00014-86-K-0533)U.S. Army - Research Office Durham (Contract DAAG29-85-K-0079)International Business Machines, Inc.National Aeronautics and Space Administration/Goddard Space Flight Center (Contract NAG5-269)Simulation TechnologiesSchlumberger-Doll Researc

Development of a polarimetric radar based hydrometeor classification algorithm for winter precipitation

2012 Fall.Includes bibliographical references.The nation-wide WSR-88D radar network is currently being upgraded for dual-polarized technology. While many convective, warm-season fuzzy-logic hydrometeor classification algorithms based on this new suite of radar variables and temperature have been refined, less progress has been made thus far in developing hydrometeor classification algorithms for winter precipitation. Unlike previous studies, the focus of this work is to exploit the discriminatory power of polarimetric variables to distinguish the most common precipitation types found in winter storms without the use of temperature as an additional variable. For the first time, detailed electromagnetic scattering of plates, dendrites, dry aggregated snowflakes, rain, freezing rain, and sleet are conducted at X-, C-, and S-band wavelengths. These physics-based results are used to determine the characteristic radar variable ranges associated with each precipitation type. A variable weighting system was also implemented in the algorithm's decision process to capitalize on the strengths of specific dual-polarimetric variables to discriminate between certain classes of hydrometeors, such as wet snow to indicate the melting layer. This algorithm was tested on observations during three different winter storms in Colorado and Oklahoma with the dual-wavelength X- and S-band CSU-CHILL, C-band OU-PRIME, and X-band CASA IP1 polarimetric radars. The algorithm showed success at all three frequencies, but was slightly more reliable at X-band because of the algorithm's strong dependence on specific differential phase. While plates were rarely distinguished from dendrites, the latter were satisfactorily differentiated from dry aggregated snowflakes and wet snow. Sleet and freezing rain could not be distinguished from rain or light rain based on polarimetric variables alone. However, high-resolution radar observations illustrated the refreezing process of raindrops into ice pellets, which has been documented before but not yet explained. Persistent, robust patterns of decreased correlation coefficient, enhanced differential reflectivity, and an inflection point around enhanced reflectivity occurred over the exact depth of the surface cold layer indicated by atmospheric soundings during times when sleet was reported at the surface. It is hypothesized that this refreezing signature is produced by a modulation of the drop size distribution such that smaller drops preferentially freeze into ice pellets first. The melting layer detection algorithm and fall speed spectra from vertically pointing radar also captured meaningful trends in the melting layer depth, height, and mean correlation coefficient during this transition from freezing rain to sleet at the surface. These findings demonstrate that this new radar-based winter hydrometeor classification algorithm is applicable for both research and operational sectors

Contrasting local and long-range-transported warm ice-nucleating particles during an atmospheric river in coastal California, USA

Ice-nucleating particles (INPs) have been found to influence the amount, phase and efficiency of precipitation from winter storms, including atmospheric rivers.Warm INPs, those that initiate freezing at temperatures warmer than -10°C, are thought to be particularly impactful because they can create primary ice in mixed-phase clouds, enhancing precipitation efficiency. The dominant sources of warm INPs during atmospheric rivers, the role of meteorology in modulating transport and injection of warm INPs into atmospheric river clouds, and the impact of warm INPs on mixed-phase cloud properties are not well-understood. In this case study, time-resolved precipitation samples were collected during an atmospheric river in northern California, USA, during winter 2016. Precipitation samples were collected at two sites, one coastal and one inland, which are separated by about 35 km. The sites are sufficiently close that air mass sources during this storm were almost identical, but the inland site was exposed to terrestrial sources of warm INPs while the coastal site was not. Warm INPs were more numerous in precipitation at the inland site by an order of magnitude. Using FLEXPART (FLEXible PARTicle dispersion model) dispersion modeling and radar-derived cloud vertical structure, we detected influence from terrestrial INP sources at the inland site but did not find clear evidence of marine warm INPs at either site.We episodically detected warm INPs from long-range-transported sources at both sites. By extending the FLEXPART modeling using a meteorological reanalysis, we demonstrate that long-range-transported warm INPs were observed only when the upper tropospheric jet provided transport to cloud tops. Using radar-derived hydrometeor classifications, we demonstrate that hydrometeors over the terrestrially influenced inland site were more likely to be in the ice phase for cloud temperatures between 0 and -10°C. We thus conclude that terrestrial and long-rangetransported aerosol were important sources of warm INPs during this atmospheric river. Meteorological details such as transport mechanism and cloud structure were important in determining (i) warm INP source and injection temperature and (ii) ultimately the impact of warm INPs on mixed-phase cloud properties

Revealing layers of pristine oriented crystals embedded within deep ice clouds using differential reflectivity and the co-polar correlation coefficient

Pristine ice crystals typically have high aspect ratios (>>1), have a high density and tend to fall preferentially with their major axis aligned horizontally. Consequently, they can, in certain circumstances, be readily identified by measurements of differential reflectivity (ZDR), which is related to their average aspect ratio. However, because ZDR is reflectivity-weighted, its interpretation becomes ambiguous in the presence of even a few, larger aggregates or irregular polycrystals. An example of this is in mixed-phase regions that are embedded within deeper ice cloud. Currently, our understanding of the microphysical processes within these regions is hindered by a lack of good observations. In this paper, a novel technique is presented that removes this ambiguity using measurements from the 3 GHz Chilbolton Advanced Meteorological Radar in Southern England. By combining measurements of ZDR and the co-polar correlation coefficient (ρhv), we show that it is possible to retrieve both the relative contribution to the radar signal and “intrinsic” ZDR (ZPDRI) of the pristine oriented crystals, even in circumstances where their signal is being masked by the presence of aggregates. Results from two case studies indicate that enhancements in ZDR embedded within deep ice clouds are typically produced by pristine oriented crystals with ZPDRI values between 3 and 7 dB (equivalent to 5-9 dB at horizontal incidence) but with varying contributions to the radar reflectivity. Vertically pointing 35 GHz cloud radar Doppler spectra and in-situ particle images from the FAAM BAe-146 aircraft support the conceptual model used and are consistent with the retrieval interpretatio