Radar Data Quality Research Articles

HF radar data quality requirements for wave measurement

HF radar wave measurements are presented focussing on theoretical limitations, and thus radar operating parameters, and quality control requirements to ensure robust measurements across a range of sea states. Data from three radar deployments, off the west coast of Norway, Celtic Sea and Liverpool Bay using two different radar systems, WERA and Pisces, and different radio frequency ranges, are used to demonstrate the wave measurement capability of HF radar and to illustrate the points made. Aspects of the measurements that require further improvements are identified. These include modifications to the underlying theory particularly in high sea states, identification and removal of ships and interference from the radar signals before wave processing and/or intelligent partitioning to remove these from the wave spectrum. The need to match the radio frequency to the expected wave peak frequency and waveheight range, with lower radio frequencies performing better at higher waveheights and lower peak frequencies and vice versa, is demonstrated. For operations across a wide range of oceanographic conditions a radar able to operate at more than one frequency is recommended for robust wave measurement. Careful quality control is needed to ensure accurate wave measurements.

A VAD-Based Dealiasing Method for Radar Velocity Data Quality Control

AbstractThis paper describes a new velocity–azimuth display (VAD)-based dealiasing method developed for automated radar radial velocity data quality control to satisfy the high-quality standard and efficiency required by operational radar data assimilation. The method is built on an alias-robust velocity–azimuth display (AR-VAD) analysis. It upgrades and simplifies the previous three-step dealiasing method in three major aspects. First, the AR-VAD is used with sufficiently stringent threshold conditions in place of the original modified VAD for the preliminary reference check to produce alias-free seed data in the first step. Second, the AR-VAD is more accurate than the traditional VAD for the refined reference check in the original second step, so the original second step becomes unnecessary and is removed. Third, a block-to-point continuity check procedure is developed, in place of the point-to-point continuity check in the original third step, which serves to enhance the use of the available seed data in a properly enlarged block area around each flagged data point that is being checked with multiple threshold conditions to avoid false dealiasing. The new method has been tested extensively with aliased radial velocity data collected under various weather conditions, including hurricane high-wind conditions. The robustness of the new method is exemplified by the results tested with three cases. The limitations of the new method and possible improvements are discussed.

2005-2006년 라디오존데 자료를 이용한 레이더 빔전파와 연관된 대기상태의 통계적 특성

The variation of atmospheric conditions including subrefraction, normal refraction, superrefraction, and ducting is an important factor that affects the quality of radar data by controling the propagation of radar beams. The occurrence frequency of the conditions is statistically analyzed using the atmospheric soundings from seven radiosonde stations in South Korea over two years. The occurrence of superrefraction and ducting at Baengnyeongdo is significantly higher than the others. Osan and Kwangju show significant variation in time. Among the different duct conditions, the surface duct is dominant at most stations except for Gosan. The elevated duct is dominant at Heuksando and Gosan. Duct is more frequent in summer than in winter at all stations. Baengnyeongdo shows the most frequent duct in spring, fall, and winter while Pohang had the highest frequency in summer. Osan and Kwangju show least duct during all seasons. The difference of variation of monthly duct occurrence between 00 UTC and 12 UTC is insignificant at all stations except for Osan and Kwangju. Kwangju, Heuksando and Gosan show relatively low frequency of duct with the monthly maximum barely reaching 60%. The highest number of elevation angles that are affected by duct was four at Osungsan radar (KSN). The maximum elevation angle is around at all stations and Jindo radar (JNI) shows the maximum value of .

Data Processing and Image Enhancement of GPR Surveys of Roman Villas in Austria

Introduction The quality of ground penetrating radar data can suffer from many different sources of noise. Some of these sources are varying distances of the antennas to the ground due to rough surfaces, different surface conditions (e.g. compression due to tractor tracks), external electromagnetic fields and instrumental noise and instabilities (Seren, 2007). Analyses of recorded raw data and knowledge of the source of noise lead to specialised processing methods to improve the signal-to-noi...

Difficulties with Correcting Radar Rainfall Estimates Based on Rain Gauge Data: A Case Study of Severe Weather in Montana on 16–17 June 2007

Abstract The principal source of information for operational flash flood monitoring and warning issuance is weather radar–based quantitative estimates of precipitation. Rain gauges are considered truth for the purposes of validating and calibrating real-time radar-derived precipitation data, both in a real-time sense and climatologically. This paper examines various uncertainties and challenges involved with using radar and rain gauge data in a severe local storm environment. A series of severe thunderstorm systems that occurred across northeastern Montana illustrates various problems with comparing radar precipitation estimates and real-time gauge data, including extreme wind effects, hail, missing gauge data, and radar quality control. Ten radar–gauge time series pairs were analyzed with most found to be not useful for real-time radar calibration. These issues must be carefully considered within the context of ongoing efforts to develop robust real-time tools for evaluating radar–gauge uncertainties. Recommendations are made for radar and gauge data quality control efforts that would benefit the operational use of gauge data.

3-hourly quantitative precipitation estimation over Central and Northern Europe from rain gauge and radar data

Continental-scale 3-hourly precipitation fields have been analysed from operational CERAD (Central European Radar) and BALTRAD (Baltic Radar) networks and adjusted with daily precipitation measurements from about 10,000 synoptic and climate stations. Here we focus on the application of CERAD and BALTRAD for quantitative precipitation estimation (QPE) that is the choice of quality control methods, the impact of input radar data quality on the analysis results and the analysis algorithm. The quality of the radar derived precipitation fields has been estimated by comparison with ground truth fields at the spatio-temporal scale of the ELDAS (European Land Data Assimilation System) project grid (0.2°/daily). Additionally, statistics on the availability of CERAD and BALTRAD data for the entire ELDAS period from Oct. 1999 to Dec. 2000 have been compiled. The final ELDAS precipitation product covers the whole of Europe and is available in GRIB format from the ECMWF MARS archive.

Weather radar to predict exceedances of faecal coliforms

Weather radar data have been used in a project in Scotland to develop a methodology to improve real-time predictions of faecal coliform concentrations in bathing waters. Poor bathing water quality, characterised by high faecal coliform concentrations, is primarily caused by pollutants mobilised during wet weather in river and urban drainage catchments discharging close to beaches. This paper reports on a study carried out with data for two sites in western Scotland, Irvine and Saltcoats, where good quality radar data and a high number of water quality samples exist. The analysis shows that radar data improve on rain-gauge data in their ability to predict water quality at the beach for one site and are marginally poorer than rain-gauge data at the other site. This is an innovative use of weather radar within a system for managing water quality and points the way for similar approaches to meet the challenge of the European Union's bathing water and water framework directives.

Assessment of radar data quality in upland catchments

AbstractOperational weather radar data have been compared with surface rain gauge measurements to quantify the uncertainties in radar‐derived surface rainfall values over upland areas. This comparison is necessary to assess the potential of radar data for flood forecasting and warning in non‐gauged upland catchments. Radar rainfall accumulations across three contrasting upland catchments in England and Wales over a 12‐month period are compared with surface rain gauge measurements. Results show that the addition of orographic corrections applied as part of the operational radar data processing chain leads to considerable improvement in the quantitative accuracy of the derived surface rainfall, typically reducing the error between radar and gauge measurements by 50%. Comparison of rainfall accumulations during specific events shows that radar data quality over upland areas is currently insufficient for quantitative use as a reliable flood warning tool in non‐gauged upland catchments. Only about 50% of rainfall events when in excess of 30 mm recorded by surface gauges are diagnosed as exceeding that threshold by the corrected radar data. © Crown copyright 2007. Reproduced with the permission of Her Majesty's Stationery Office. Published by John Wiley & Sons, Ltd

The Impact of Beam Broadening on the Quality of Radar Polarimetric Data

Abstract The impact of beam broadening on the quality of radar polarimetric data in the presence of nonuniform beam filling (NBF) is examined both theoretically and experimentally. Cross-beam gradients of radar reflectivity Z, differential reflectivity ZDR, and differential phase ΦDP within the radar resolution volume may produce significant biases of ZDR, ΦDP, and the cross-correlation coefficient ρhv. These biases increase with range as a result of progressive broadening of the radar beam. They are also larger at shorter radar wavelengths and wider antenna beams. Simple analytical formulas are suggested for estimating the NBF-induced biases from the measured vertical and horizontal gradients of Z, ZDR, and ΦDP. Analysis of polarimetric data collected by the KOUN Weather Surveillance Radar-1988 Doppler (WSR-88D) demonstrates that frequently observed perturbations of the radial ΦDP profiles and radially oriented “valleys” of ρhv depression can be qualitatively and quantitatively explained using the suggested NBF model.

Radar data quality control methods in VOLTAIRE

In the scope of the EU-project VOLTAIRE (Validation of multisensors precipitation fields and numerical modelling in Mediterranean test sites) a software library for automatic and rapid radar data quality check and modification has been developed and tests have been performed with data from different countries. Automatic procedures will never replace an experienced observer, but they help him to do his work and they can be used at places, where observation is not possible.This paper gives an overview over the algorithms that have been adopted or developed during the VOLTAIRE project for radar data quality control. Two examples of these algorithms illustrate the possibilities for data correction but also their limitations. These examples are a clutter correction combined with speckle removal for Plan Position Indicator (PPI) data in particular of non-Doppler radars and a beam blockage correction for PPI data, where no Digital Elevation Model (DEM) is available.

Assessing vertical resolution requirements for operational weather radar data quality

AbstractHigh‐resolution, 0.28° beamwidth range‐height‐indicator (RHI) data are used to simulate the reflectivities measured at various ranges by an operational radar with a 1° beamwidth. It is found that the sampling is optimal when the elevation increments equal the beamwidth. Larger increments lead to an unacceptable loss of information. Copyright © 2006 Royal Meteorological Society

Tropical Forest Measurement by Interferometric Height Modeling and P-Band Radar Backscatter

Abstract A new approach to tropical forest biomass monitoring with airborne interferometric X and P-band synthetic aperture radar (SAR) data is presented. Forest height, basal area, and aboveground biomass are modeled from remote sensing data for a study site in the Brazilian Amazon. Radar data quality has improved: A novel digital model of vegetation height from X- and P-band interferometry is available along with the usual P-band backscatter information. The digital vegetation height model is derived from the interferometric surface models of the ground (from P-band) and the forest canopy (from X-band). The difference between the surface models is called “interferometric height,” and is used as a measure of vegetation height. Interferometric height is shown to relate to a subset of the forest trees that changes according to the forest successional stages. The suitability of radar backscatter and interferometric height as a means for forest and biomass monitoring was explored by relating forest parameters as measured in the field to remote sensing data. Basal area and biomass were related to radar backscatter with limited precision of r2 = 0.19 and r2 = 0.34, respectively. Mean forest height is shown to relate to interferometric height with good precision (r2 = 0.83, RMSE = 4.1 m). A statistical model for forest biomass as a function of both P-band backscatter and interferometric height information not only arrives at high values of precision (with r2 = 0.89 and a RMSE from cross-validation of only 46.1 t/ha), but also overcomes the well-known issue of backscatter saturation. This research shows that tropical forest biomass can be quantified and mapped over large areas for a range of forest structures with reasonably tight and similar errors. FOR. SCI. 51(6):585–594.

Effects of propagation conditions on radar beam-ground interaction: impact on data quality

Abstract. A large part of the research in the radar meteorology is devoted to the evaluation of the radar data quality and to the radar data processing. Even when, a set of absolute quality indexes can be produced (like as ground clutter presence, beam blockage rate, distance from radar, etc.), the final product quality has to be determined as a function of the task and of all the processing steps. In this paper the emphasis lies on the estimate of the rainfall at the ground level taking extra care for the correction for ground clutter and beam blockage, that are two main problems affecting radar reflectivity data in complex orography. In this work a combined algorithm is presented that avoids and/or corrects for these two effects. To achieve this existing methods are modified and integrated with the analysis of radar signal propagation in different atmospheric conditions. The atmospheric refractivity profile is retrieved from the nearest in space and time radiosounding. This measured profile is then used to define the `dynamic map' used as a declutter base-field. Then beam blockage correction is applied to the data at the scan elevations computed from this map. Two case studies are used to illustrate the proposed algorithm. One is a summer event with anomalous propagation conditions and the other one is a winter event. The new algorithm is compared to a previous method of clutter removal based only on static maps of clear air and vertical reflectivity continuity test. The improvement in rain estimate is evaluated applying statistical analysis and using rain gauges data. The better scores are related mostly to the ``optimum" choice of the elevation maps, introduced by the more accurate description of the signal propagation. Finally, a data quality indicator is introduced as an output of this scheme. This indicator has been obtained from the general scheme, which takes into account all radar data processing steps.

'Down-to-Earth' modelling of equivalent surface precipitation using multisource data and radar

The estimation of surface rainfall from reflectivity data derived from weather radar has been much studied over many years. It is now clear that central to this problem is the adjustment of these data for the impacts of vertical variations in the reflectivity. In this paper a new procedure (known as Down-to-Earth, DTE) is proposed and tested for combining radar measurements aloft with information from a numerical weather-prediction (NWP) model and an analysis system. The procedure involves the exploitation of moist cloud physics in an attempt to account for physical processes impacting on precipitation during its descent from the height of radar echo measurements to the surface. The application of DTE leads to increased underestimation in the radar measurements compared to precipitation gauge observations at short and intermediate radar ranges (0-120 km), but is successful at reducing the bias at further ranges. However the application of DTE does not lead to significant decreases in the random error of the surface rain rate estimate. No improvement is made when attempting to account for the precipitation phase measured by radar. It is concluded that further work on radar data quality control, along with improvements to the NWP model, are essential to improve upon results using such a physically based procedure.

Towards a roadmap for use of radar rainfall data in urban drainage

Radar rainfall has received growing attention in the urban drainage community since its first appearance on an Urban Storm Drainage Conference in 1984. Still, operational applications of radar rainfall in urban hydrology is limited. The following aspects have to be considered for radar rainfall data use specifically in urban hydrology: the type of the radar, the application requirements on the radar data, the achievable radar data quality, forecast possibilities and limits. Quantitative applications of weather radar to urban hydrology are becoming more mature with better understanding of limitations and achievable accuracy. Research in the US and Europe has led to operational applications of radar to site-specific forecasting of floods and management of sewer overflow during wet weather. The uncertainties and methods for obtaining accurate rainfall measurements at high resolution and with areal extents consistent with urban catchments is a major focus of this article. Evaluation and improvement of quantitative precipitation measurements are described in this overview with specific research and operational examples of radar use in urban hydrology.

Towards a roadmap for use of radar rainfall data in urban drainage

Radar rainfall has received growing attention in the urban drainage community since its first appearance on an Urban Storm Drainage Conference in 1984. Still, operational applications of radar rainfall in urban hydrology is limited. The following aspects have to be considered for radar rainfall data use specifically in urban hydrology: the type of the radar, the application requirements on the radar data, the achievable radar data quality, forecast possibilities and limits. Quantitative applications of weather radar to urban hydrology are becoming more mature with better understanding of limitations and achievable accuracy. Research in the US and Europe has led to operational applications of radar to site-specific forecasting of floods and management of sewer overflow during wet weather. The uncertainties and methods for obtaining accurate rainfall measurements at high resolution and with areal extents consistent with urban catchments is a major focus of this article. Evaluation and improvement of quantitative precipitation measurements are described in this overview with specific research and operational examples of radar use in urban hydrology.

Radar rainfall image repair techniques

Abstract. There are various quality problems associated with radar rainfall data viewed in images that include ground clutter, beam blocking and anomalous propagation, to name a few. To obtain the best rainfall estimate possible, techniques for removing ground clutter (non-meteorological echoes that influence radar data quality) on 2-D radar rainfall image data sets are presented here. These techniques concentrate on repairing the images in both a computationally fast and accurate manner, and are nearest neighbour techniques of two sub-types: Individual Target and Border Tracing. The contaminated data is estimated through Kriging, considered the optimal technique for the spatial interpolation of Gaussian data, where the "screening effect" that occurs with the Kriging weighting distribution around target points is exploited to ensure computational efficiency. Matrix rank reduction techniques in combination with Singular Value Decomposition (SVD) are also suggested for finding an efficient solution to the Kriging Equations which can cope with near singular systems. Rainfall estimation at ground level from radar rainfall volume scan data is of interest and importance in earth bound applications such as hydrology and agriculture. As an extension of the above, Ordinary Kriging is applied to three-dimensional radar rainfall data to estimate rainfall rate at ground level. Keywords: ground clutter, data infilling, Ordinary Kriging, nearest neighbours, Singular Value Decomposition, border tracing, computation time, ground level rainfall estimation

Age estimates of isochronous reflection horizons by combining ice core, survey, and synthetic radar data

Ice core records and ice‐penetrating radar data contain complementary information on glacial subsurface structure and composition, providing various opportunities for interpreting past and present environmental conditions. To exploit the full range of possible applications, accurate dating of internal radar reflection horizons and knowledge about their constituting features is required. On the basis of three ice core records from Dronning Maud Land, Antarctica, and surface‐based radar profiles connecting the drilling locations, we investigate the accuracies involved in transferring age‐depth relationships obtained from the ice cores to continuous radar reflections. Two methods are used to date five internal reflection horizons: (1) conventional dating is carried out by converting the travel time of the tracked reflection to a single depth, which is then associated with an age at each core location, and (2) forward modeling of electromagnetic wave propagation is based on dielectric profiling of ice cores and performed to identify the depth ranges from which tracked reflections originate, yielding an age range at each drill site. Statistical analysis of all age estimates results in age uncertainties of 5–10 years for conventional dating and an error range of 1–16 years for forward modeling. For our radar operations at 200 and 250 MHz in the upper 100 m of the ice sheet, comprising some 1000–1500 years of deposition history, final age uncertainties are 8 years in favorable cases and 21 years at the limit of feasibility. About one third of the uncertainty is associated with the initial ice core dating; the remaining part is associated with radar data quality and analysis.

Comparison of raingage and WSR-88D Stage III precipitation data over the Texas-Gulf basin

Precipitation is one of the most important hydrologic model inputs and is characterized by spatial and temporal variability. Traditionally, raingage networks have provided precipitation data for hydrologic studies. Weather radars like the WSR-88D estimate precipitation with high spatial and temporal sampling frequencies, but radar estimates suffer from errors due to several reasons. Assessment of the quality of radar precipitation data is necessary before the application of radar data in hydrologic studies and is important for improving radar data processing algorithms. Accuracy assessment of Stage III precipitation data from the WSR-88D network over the Texas-Gulf basin was performed for the period 1995–99 using 24-h accumulations from 545 raingages. Sampling differences between point raingage measurements and areal radar estimates were ignored. WSR-88D underestimated the five-year precipitation at a vast majority of the raingages. Difference in the total precipitation depth between radar and raingage was within ±500 mm only at 42% of the raingages; the root mean squared difference was more than 10 mm at 78% of the raingages. Such large differences between both rainfall data sources will have significant implications for the hydrologic applications of WSR-88D Stage III data. Radar estimation efficiency was better than 0.50 at 71% of the First Order/FAA raingages and 41% of the cooperative observer raingages. Radar performance varied significantly over the years, and, in general, improvement in radar performance was observed, which is consistent with the on-going developments in WSR-88D data processing algorithms; however, an overestimation trend was identified during 1998–99. Evaluation of the quality of WSR-88D Stage III data and making necessary corrections are important before their application in hydrologic studies.

Spurious weather radar echo identification and removal using multisource temperature information

AbstractA simple and pragmatic method utilising the difference between analysed near‐surface and Meteosat IR temperatures (ΔT) is presented and applied with the aim of identifying and removing non‐precipitation echoes in weather radar composite imagery. Despite inherent deficiencies in these multisource data, such as lower spatial and temporal resolutions relative to the radar data, T is demonstrated to efficiently identify efficiently those areas void of potentially precipitating clouds, and to remove radar echoes in them. A set of 243 manually analysed composites from the summer of 2000 was used to evaluate the method. False alarm rates (FAR), percent correct (PC) and Hanssen‐Kuipers skill (HKS) scores were calculated from standard contingency tables for five echo classes: weak, strong, land, sea, and all. FAR was lowered in all classes, PC was generally raised by a few percent to be over 95%, while HKS either remained unchanged or was slightly lowered through the application of T. These results indicate that T successfully removes a significant amount of non‐precipitation, sometimes at the expense of a small amount of true precipitation. This penalty is larger over sea, which indicates that the method may need to be tuned differently for land and sea environments. This method may act as a foundation on which improvements to radar data quality control can be made with the introduction of new and improved satellite instrumentation such as that found on board the Meteosat Second Generation platform. However, this type of method should remain complementary to improved signal processing and radar data analysis techniques. Copyright © 2004 Royal Meteorological Society.