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At least 91 records · Page 5

Estimating the Concentration of Large Raindrops from Polarimetric Radar and Disdrometer Observations

Estimation of rainfall integral parameters, including radar observables, and empirical relations between them are sensitive to the truncation of the drop size distribution (DSD), particularly at the large drop end. The sensitivity of rainfall integral parameters to the maximum drop diameter (D(sub max)) is exacerbated at C‐band since resonance effects are pronounced for large drops in excess of 5 mm diameter (D). Due to sampling limitations, it is often difficult to reliably estimate D(sub max) with disdrometers. The resulting uncertainties in D(sub max0 potentially increase errors in radar retrieval methods, particularly at C‐band, that rely on disdrometer observations for DSD input to radar models. In fact, D(sub max) is typically an assumed DSD parameter in the development of radar retrieval methods. Because of these very uncertainties, it is difficult to independently confirm disdrometer estimates of D(sub max) with polarimetric radar observations. A couple of approaches can be taken to reduce uncertainty in large drop measurement. Longer integration times can be used for the collection of larger disdrometer samples. However, integration periods must be consistent with a radar resolution volume (RRV) and the temporal and spatial scales of the physical processes affecting the DSD therein. Multiple co‐located disdrometers can be combined into a network to increase the sample size within a RRV. However, over a reasonable integration period, a single disdrometer sample volume is many orders of magnitudes less than a RRV so it is not practical to devise a network of disdrometers that has an equivalent volume to a typical RRV. Since knowledge of DSD heterogeneity and large drop occurrence in time and space is lacking, the specific accuracy or even general representativeness of disdrometer based D(sub max) and large drop concentration estimates within a RRV are currently unknown. To address this complex issue, we begin with a simpler question. Is the frequency of occurrence of large rain drops (D > 5 mm) in disdrometer observations, either stand alone or networked, generally representative and consistent with polarimetric radar observations? We first show from simulations that the concentration of large (D > 5 mm) rain drops (N(sub T5)) can be estimated from polarimetric observations of specific differential phase (K(sub dp)) and differential reflectivity (Z(sub dr)), N(sub T5)=F(K(sub dp),Z(sub dr)), or horizontal reflectivity (Z(sub h)) and Z(sub dr), N(sub T5)=(Z(sub h),Z(sub dr)). We assess the error associated with polarimetric retrieval of N(sub T5), including sensitivity to D(sub max) parameterization assumptions and measurement error in the radar simulations. Polarimetric measurements at S‐band and C‐band will then be used to retrieve estimates of N(sub T5) and compared to disdrometer estimates of N(sub T5). After careful consideration of retrieval error, we will check consistency between disdrometer and polarimetric radar estimates of N(sub T5) and the frequency of occurrence of large rain drops in a variety of precipitating regimes using data from NASA's Global Precipitation Measurement (GPM) Ground Validation (GV) program, including field campaigns such as MC3E (Oklahoma) and IFloodS (Iowa) and extended measurements over Huntsville, Alabama and NASA Wallops Flight Facility in coastal Virginia.

Carey, Lawrence D.↗

Radar estimation of slant path rain attenuation at frequencies above 10 GHz and comparisons with measured multi-season results

Techniques and results pertaining to estimating Earth satellite path rain attenuation events and statistics using radar at nonattenuating wavelengths are presented. The radar formulation and beam scanning methods are described and the procedure for relating the radar measured Rayleigh reflectivity to the high frequency Mie attenuation coefficient are given. Examples of radar derived single terminal statistics and estimation criteria as they relate to path angle and frequency are reviewed. Radar derived space diversity statistics and their dependence on terminal spacing and frequency are described. Site diversity performance curves obtained by radar and radiometry are compared with each other demonstrating the utility of radar methods. Results of a multi-year experiment to test, refine, and establish accuracies of radar methods for arriving at estimates of rain attenuation along an Earth-satellite path are discussed. Comparisons of measured and radar estimated fade events are presented and found to be good. Comparisons of cumulative fade distributions show agreement to be excellent giving an rms deviation of 1 dB.

Goldhirsh, J.↗

Backscattering by nonspherical hydrometeors as calculated by the coupled-dipole method - An application in radar meteorology

The severest test of a theory of scattering by particles is how well it calculates scattering in the backward direction. The coupled-dipole method can be used for accurately calculating backscattering at 94 GHz by hexagonal ice crystals. Backscattering by columns is markedly different from that by plates, which indicates that it might be possible to infer size and shape distributions of ice crystals using recently developed millimeter wave radar.

Dungey, Clifton E.↗

A boundary integral method for numerical computation of radar cross section of 3D targets using hybrid BEM/FEM with edge elements

This contribution presents the boundary integral formulation for numerical computation of time-harmonic radar cross section for 3D targets. Method relies on hybrid edge element BEM/FEM to compute near field edge element coefficients that are associated with near electric and magnetic fields at the boundary of the computational domain. Special boundary integral formulation is presented that computes radar cross section directly from these edge element coefficients. Consequently, there is no need for near-to-far field transformation (NTFFT) which is common step in RCS computations. By the end of the paper it is demonstrated that the formulation yields accurate results for canonical models such as spheres, cubes, cones and pyramids. Method has demonstrated accuracy even in the case of dielectrically coated PEC sphere at interior resonance frequency which is common problem for computational electromagnetic codes. - Graphical abstract: - Highlights: • Hybrid edge element BEM/FEM is used to find edge element coefficients. • New formulation for RCS computation directly from edge element coefficients is presented. • Formulation is tested on canonical cases and on coated dielectric sphere at interior resonance frequency.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Wind regime peculiarities in the lower thermosphere in the winter of 1983/84

Temporal variations of prevailing winds at 90 to 100 km obtained from measurements carried out in winter 1983 to 1984 at three sites in the USSR and two sites in East Germany are reported. These variations are compared with those of the thermal stratospheric regime. Measurements were carried out using the drifts D2 method (meteor wind radar) and the D1 method (ionospheric drifts). Temporal variations of zonal and meridional prevailing wind components for all the sites are given. Also presented are zonal wind data obtained using the partial reflection wind radar. Wind velocity values were obtained by averaging data recorded at between 105 and 91 km altitude. Wind velocity data averaged in such a way can be related to about the same height interval to which the data obtained by the meteor radar and ionospheric methods at other sites, i.e., the mean height of the meteor zone (about 95 km). The results presented show that there are significant fluctuations about the seasonal course of both zonal and meridional prevailing winds.

Lysenko, I. A.↗

Studies on remote sensing method of particle size and water density distribution in mists and clouds using laser radar techniques

A method of remote measurement of the particle size and density distribution of water droplets was developed. In this method, the size of droplets is measured from the Mie scattering parameter which is defined as the total-to-backscattering ratio of the laser beam. The water density distribution is obtained by a combination of the Mie scattering parameter and the extinction coefficient of the laser beam. This method was examined experimentally for the mist generated by an ultrasonic mist generator and applied to clouds containing rain and snow. Compared with the conventional sampling method, the present method has advantages of remote measurement capability and improvement in accuracy.

Shimizu, H.↗

Assessment of Rainfall Estimates Using a Standard Z-R Relationship and the Probability Matching Method Applied to Composite Radar Data in Central Florida

Precipitation estimates from radar systems are a crucial component of many hydrometeorological applications, from flash flood forecasting to regional water budget studies. For analyses on large spatial scales and long timescales, it is frequently necessary to use composite reflectivities from a network of radar systems. Such composite products are useful for regional or national studies, but introduce a set of difficulties not encountered when using single radars. For instance, each contributing radar has its own calibration and scanning characteristics, but radar identification may not be retained in the compositing procedure. As a result, range effects on signal return cannot be taken into account. This paper assesses the accuracy with which composite radar imagery can be used to estimate precipitation in the convective environment of Florida during the summer of 1991. Results using Z = 30OR(sup 1.4) (WSR-88D default Z-R relationship) are compared with those obtained using the probability matching method (PMM). Rainfall derived from the power law Z-R was found to he highly biased (+90%-l10%) compared to rain gauge measurements for various temporal and spatial integrations. Application of a 36.5-dBZ reflectivity threshold (determined via the PMM) was found to improve the performance of the power law Z-R, reducing the biases substantially to 20%-33%. Correlations between precipitation estimates obtained with either Z-R relationship and mean gauge values are much higher for areal averages than for point locations. Precipitation estimates from the PMM are an improvement over those obtained using the power law in that biases and root-mean-square errors are much lower. The minimum timescale for application of the PMM with the composite radar dataset was found to be several days for area-average precipitation. The minimum spatial scale is harder to quantify, although it is concluded that it is less than 350 sq km. Implications relevant to the WSR-88D system are discussed.

Crosson, William L.↗

Application of a Threshold Method to the TRMM Radar for the Estimation of Space-Time Rain Rate Statistics

One of the TRMM radar products of interest is the monthly-averaged rain rates over 5 x 5 degree cells. Clearly, the most directly way of calculating these and similar statistics is to compute them from the individual estimates made over the instantaneous field of view of the Instrument (4.3 km horizontal resolution). An alternative approach is the use of a threshold method. It has been established that over sufficiently large regions the fractional area above a rain rate threshold and the area-average rain rate are well correlated for particular choices of the threshold [e.g., Kedem et al., 19901]. A straightforward application of this method to the TRMM data would consist of the conversion of the individual reflectivity factors to rain rates followed by a calculation of the fraction of these that exceed a particular threshold. Previous results indicate that for thresholds near or at 5 mm/h, the correlation between this fractional area and the area-average rain rate is high. There are several drawbacks to this approach, however. At the TRMM radar frequency of 13.8 GHz the signal suffers attenuation so that the negative bias of the high resolution rain rate estimates will increase as the path attenuation increases. To establish a quantitative relationship between fractional area and area-average rain rate, an independent means of calculating the area-average rain rate is needed such as an array of rain gauges. This type of calibration procedure, however, is difficult for a spaceborne radar such as TRMM. To estimate a statistic other than the mean of the distribution requires, in general, a different choice of threshold and a different set of tuning parameters.

Meneghini, Robert↗

Validation of Satellite-Based Objective Overshooting Cloud-Top Detection Methods Using CloudSat Cloud Profiling Radar Observations

Two satellite infrared-based overshooting convective cloud-top (OT) detection methods have recently been described in the literature: 1) the 11-mm infrared window channel texture (IRW texture) method, which uses IRW channel brightness temperature (BT) spatial gradients and thresholds, and 2) the water vapor minus IRW BT difference (WV-IRW BTD). While both methods show good performance in published case study examples, it is important to quantitatively validate these methods relative to overshooting top events across the globe. Unfortunately, no overshooting top database currently exists that could be used in such study. This study examines National Aeronautics and Space Administration CloudSat Cloud Profiling Radar data to develop an OT detection validation database that is used to evaluate the IRW-texture and WV-IRW BTD OT detection methods. CloudSat data were manually examined over a 1.5-yr period to identify cases in which the cloud top penetrates above the tropopause height defined by a numerical weather prediction model and the surrounding cirrus anvil cloud top, producing 111 confirmed overshooting top events. When applied to Moderate Resolution Imaging Spectroradiometer (MODIS)-based Geostationary Operational Environmental Satellite-R Series (GOES-R) Advanced Baseline Imager proxy data, the IRW-texture (WV-IRW BTD) method offered a 76% (96%) probability of OT detection (POD) and 16% (81%) false-alarm ratio. Case study examples show that WV-IRW BTD.0 K identifies much of the deep convective cloud top, while the IRW-texture method focuses only on regions with a spatial scale near that of commonly observed OTs. The POD decreases by 20% when IRW-texture is applied to current geostationary imager data, highlighting the importance of imager spatial resolution for observing and detecting OT regions.

Bedka, Kristopher M.↗

The real-time display of interferometry data for Goldstone radar astronomy data acquisition

A method for visualizing radar interferometry data in real time has been developed for the Goldstone radar astronomy ranging data-acquisition system. The presentation is similar in appearance to a vector field display or data-based grid. This form was selected to facilitate the recognition of characteristic patterns of local variation in the phase and magnitude of complex elements in a two-dimensional data array. The design emphasized efficiency under the demands of real-time processing and remote monitoring. The interferometry 'phase-magnitude' presentation, as it has come to be called, has been used to monitor radar interferometry experiments on three targets, beginning with the asteroid 4179 Toutatis, and continuing with Mars and Mercury.

Howard, S. D.↗

Improved accuracy of radar WPMM estimated rainfall upon application of objective classification criteria

Application of the window probability matching method to radar and rain gauge data that have been objectively classified into different rain types resulted in distinctly different Z(sub e)-R relationships for the various classifications. These classification parameters, in addition to the range from the radar, are (a) the horizontal radial reflectivity gradients (dB/km); (b) the cloud depth, as scaled by the effective efficiency; (c) the brightband fraction within the radar field window; and (d) the height of the freezing level. Combining physical parameters to identify the type of precipitation and statistical relations most appropriate to the precipitation types results in considerable improvement of both point and areal rainfall measurements. A limiting factor in the assessment of the improved accuracy is the inherent variance between the true rain intensity at the radar measured volume and the rain intensity at the mouth of the rain guage. Therefore, a very dense rain gauge network is required to validate most of the suggested realized improvement. A rather small sample size is required to achieve a stable Z(sub e)-R relationship (standard deviation of 15% of R for a given Z(sub e)) -- about 200 mm of rainfall accumulated in all guages combined for each classification.

Rosenfeld, Daniel↗

Sensitivity of Spaceborne and Ground Radar Comparison Results to Data Analysis Methods and Constraints

With the availability of active weather radar observations from space from the Precipitation Radar (PR) on board the Tropical Rainfall Measuring Mission (TR.MM) satellite, numerous studies have been performed comparing PR reflectivity and derived rain rates to similar observations from ground-based weather radars (GR). These studies have used a variety of algorithms to compute matching PR and GR volumes for comparison. Most studies have used a fixed 3-dimensional Cartesian grid centered on the ground radar, onto which the PR and GR data are interpolated using a proprietary approach and/or commonly available GR analysis software (e.g., SPRINT, REORDER). Other studies have focused on the intersection of the PR and GR viewing geometries either explicitly or using a hybrid of the fixed grid and PR/GR common fields of view. For the Dual-Frequency Precipitation Radar (DPR) of the upcoming Global Precipitation Measurement (GPM) mission, a prototype DPR/GR comparison algorithm based on similar TRMM PR data has been developed that defines the common volumes in terms of the geometric intersection of PR and GR rays, where smoothing of the PR and GR data are minimized and no interpolation is performed. The PR and GR volume-averaged reflectivity values of each sample volume are accompanied by descriptive metadata, for attributes including the variability and maximum of the reflectivity within the sample volume, and the fraction of range gates in the sample average having reflectivity values above an adjustable detection threshold (typically taken to be 18 dBZ for the PR). Sample volumes are further characterized by rain type (Stratiform or Convective), proximity to the melting layer, underlying surface (land/water/mixed), and the time difference between the PR and GR observations. The mean reflectivity differences between the PR and GR can differ between data sets produced by the different analysis methods; and for the GPM prototype, by the type of constraints and categorization applied to the data. In this paper, we will show results comparing the 3-D gridded analysis "black box" approach to the GPM prototype volume-matching approach, using matching TRMM PR and WSR-88D ground radar data. The affects of applying data constraints and data categorizations on the volume-matched data to the results will be shown, and explanations of the differences in terms of data and analysis algorithm characteristics will be presented. Implications of the differences to the determination of PR/DPR calibration differences and use of ground radar data to evaluate the PR and DPR attenuation correction algorithms will be discussed.

Morris, Kenneth R.↗

Comparing Methods for Assessing Reliability Uncertainty Based on Pass/Fail Data Collected Over Time

In this paper, we compare statistical methods for analyzing pass/fail data collected over time; some methods are traditional and one (the RADAR or Rationale for Assessing Degradation Arriving at Random) was recently developed. These methods are used to provide uncertainty bounds on reliability. We make observations about the methods' assumptions and properties. Finally, we illustrate the differences between two traditional methods, logistic regression and Weibull failure time analysis, and the RADAR method using a numerical example.

97 MATHEMATICS AND COMPUTING↗