Scanning Weather Radars Research Articles

Correcting for Mobile X-Band Weather Radar Tilt Using Solar Interference

Precise knowledge of the antenna pointing direction is a key facet to ensure the accuracy of observations from scanning weather radars. The sun is an often-used reference point to aid accurate alignment of weather radar systems and is particularly useful when observed as interference during normal scanning operations. In this study, we combine two online solar interference approaches to determine the pointing accuracy of an X-band mobile weather radar system deployed for 26 months in northern England (54.517°N, 3.615°W). During the deployment, several shifts in the tilt of the radar system are diagnosed between site visits. One extended period of time (>11 months) is shown to have a changing tilt that is independent of human intervention. To verify the corrections derived from this combined approach, quantitative precipitation estimates (QPEs) from the radar system are compared to surface observations: an approach that takes advantage of the variations in the magnitude of partial beam blockage corrections required due to tilting of the radar system close to mountainous terrain. The observed improvements in QPE performance after correction support the use of the derived tilt corrections for further applications using the corrected dataset. Finally, recommendations for future deployments are made, with particular focus on higher latitudes where solar interference spikes show more seasonality than those at mid-latitudes.

Radar and ground-level measurements of clouds and precipitation collected during the POPE 2020 campaign at Princess Elisabeth Antarctica

Abstract. The datasets presented in this article were collected during a 4-month measurement campaign at the Belgian research base Princess Elisabeth Antarctica (PEA). The campaign, named PEA Orographic Precipitation Experiment (POPE), was conducted by the Environmental Remote Sensing Laboratory of the École Polytechnique Fédérale de Lausanne, with the logistical support of the International Polar Foundation, between the end of November 2019 and the beginning of February 2020. The datasets have been collected at five different sites. A W-band Doppler cloud profiler and a multi-angle snowflake camera (MASC) have been deployed in the immediate proximity of the main building of the station. An X-band dual-polarization Doppler scanning weather radar was installed 1.9 km southeast of PEA. Information on the various hydrometeor types have been derived from its measurements and from the images collected by the MASC. The remaining three sites were located in a transect across the mountain chain south of the base, between 7 and 17 km apart from each other. At each site, a K-band Doppler profiler and an automated weather station have been deployed. A pyrgeometer and a pyranometer accompanied the instruments at the site in the middle of the transect. The radar variables and the measurements collected by the weather stations and radiometers are available at https://doi.org/10.5281/zenodo.7428690 (Ferrone and Berne, 2023c). The Doppler spectra are available at https://doi.org/10.5281/zenodo.7507087 (Ferrone and Berne, 2023a) and https://doi.org/10.5075/epfl-lte-299685 (Ferrone and Berne, 2023b). A case study, covering the precipitation event recorded on 23 December 2019, is presented to illustrate the various datasets. Overall, the availability of radar measurements over a complex terrain, relatively far from a scientific base, is extremely rare in the Antarctic context and opens a wide range of possibilities for precipitation studies over the region.

Detecting wave features in Doppler radial velocity radar observations

Abstract. Mesoscale, wave-like perturbations in horizontal air motions in the troposphere (velocity waves) are associated with vertical velocity, temperature, and pressure perturbations that can initiate or enhance precipitation within clouds. The ability to detect velocity waves from horizontal wind information is an important tool for atmospheric research and weather forecasting. This paper presents a method to routinely detect velocity waves using Doppler radial velocity data from a scanning weather radar. The method utilizes the difference field between consecutive position plan indicator (PPI) scans at a given elevation angle. Using the difference between fields a few minutes apart highlights small-scale perturbations associated with waves because the larger-scale wind field changes more slowly. Image filtering retains larger contiguous velocity bands and discards noise. Wave detection scales are limited by the size of the temporal difference relative to the wave motion and the radar resolution volume size.

Calibration of X-Band Radar for Extreme Events in a Spatially Complex Precipitation Region in North Peru: Machine Learning vs. Empirical Approach

Cost-efficient single-polarized X-band radars are a feasible alternative due to their high sensitivity and resolution, which makes them well suited for complex precipitation patterns. The first horizontal scanning weather radar in Peru was installed in Piura in 2019, after the devastating impact of the 2017 coastal El Niño. To obtain a calibrated rain rate from radar reflectivity, we employ a modified empirical approach and draw a direct comparison to a well-established machine learning technique used for radar QPE. For both methods, preprocessing steps are required, such as clutter and noise elimination, atmospheric, geometric, and precipitation-induced attenuation correction, and hardware variations. For the new empirical approach, the corrected reflectivity is related to rain gauge observations, and a spatially and temporally variable parameter set is iteratively determined. The machine learning approach uses a set of features mainly derived from the radar data. The random forest (RF) algorithm employed here learns from the features and builds decision trees to obtain quantitative precipitation estimates for each bin of detected reflectivity. Both methods capture the spatial variability of rainfall quite well. Validating the empirical approach, it performed better with an overall linear regression slope of 0.65 and r of 0.82. The RF approach had limitations with the quantitative representation (slope = 0.44 and r = 0.65), but it more closely matches the reflectivity distribution, and it is independent of real-time rain-gauge data. Possibly, a weighted mean of both approaches can be used operationally on a daily basis.

Diagnosis of Tilted Weather Radars Using Solar Interference

AbstractFor mechanically scanning weather radars, precise pointing of the antenna is a key factor in ensuring accurate observation of the atmosphere at far range. Since operational radars typically scan the atmosphere using a series of 360° sweeps at fixed elevation angles, level scanning during azimuthal rotation is also important, but often not actively monitored after installation.One method of gauging pointing accuracy of a radar is to use solar interference which occurs as the antenna sweeps past the sun. By comparing the observed position of the sun with its known position, an estimate of pointing error in both elevation and azimuth can be obtained. A basic model for this error assumes that the radar sweep is perfectly level and that biases in elevation are therefore independent of azimuth. We extend this model to allow for the possibility that the plane of rotation may not be level. Consequently, the direction and severity of tilt may be diagnosed in addition to any constant error in elevation and azimuth pointing.The extended model was applied to a subset of radars from the Australian weather radar network resulting in the discovery of several out of level radars. One radar, Captains Flat near Canberra, showed a severe tilt of 0.81° prompting inspection by a technician. This revealed that mounting studs on the pedestal of the radar tower were badly worn and loose. Correction of this issue resolved the tilt component of the diagnosed elevation error and prevented further mechanical damage to the instrument.

Quantitative Evaluation of Polarimetric Estimates from Scanning Weather Radars Using a Vertically Pointing Micro Rain Radar

AbstractConventionally, Micro Rain Radars (MRRs) have been used as a tool to calibrate reflectivity from weather radars, estimate the relation between rainfall rate and reflectivity, and study microphysical processes in precipitation. However, limited attention has been given to the reliability of the retrieved drop size distributions (DSDs) from MRRs. This study sheds more light on this aspect by examining the sensitivity of retrieved DSDs to the assumptions made to map Doppler spectra into size distributions, and investigates the capability of an MRR to assess polarimetric observations from operational weather radars. For that, an MRR was installed near the Cabauw observatory in the Netherlands, between the International Research Center for Telecommunications and Radar (IRCTR) Drizzle Radar (IDRA) X-band radar and the Herwijnen operational C-band radar. The measurements of the MRR from November 2018 to February 2019 were used to retrieve DSDs and simulate horizontal reflectivity Ze, differential reflectivity ZDR, and specific differential phase KDP in rain. Attention is given to the impact of aliased spectra and right-hand-side truncation on the simulation of polarimetric variables. From a quantitative assessment, the correlations of Ze and ZDR between the MRR and Herwijnen radar were 0.93 and 0.70, respectively, while those between the MRR and IDRA were 0.91 and 0.69. However, Ze and ZDR from the Herwijnen radar showed slight biases of 1.07 and 0.25 dB. For IDRA, the corresponding biases were 2.67 and −0.93 dB. Our results show that MRR measurements are advantageous to inspect the calibration of scanning radars and validate polarimetric estimates in rain, provided that the DSDs are correctly retrieved and controlled for quality assurance.

Observations of Severe Local Storms and Tornadoes with the Atmospheric Imaging Radar

AbstractMobile radar platforms designed for observation of severe local storms have consistently pushed the boundaries of spatial and temporal resolution in order to allow for detailed analysis of storm structure and evolution. Digital beamforming, or radar imaging, is a technique that is similar in nature to a photograwphic camera, where data samples from different spaces at the same range are collected simultaneously. This allows for rapid volumetric update rates compared to radars that scan with a single narrow beam. The Atmospheric Imaging Radar (AIR) is a mobile X-band (3.14-cm wavelength) imaging weather radar that transmits a vertical, 20° fan beam and uses a 36-element receive array to form instantaneous range–height indicators (RHIs) with a native beamwidth of 1° × 1°. Rotation in azimuth allows for 20° × 90° volumetric updates in under 6 s, while advanced pulse compression techniques achieve 37.5-m range resolution. The AIR has been operational since 2012 and has collected data on tornadoes and supercells at ranges as close as 6 km, resulting in high spatial and temporal resolution observations of severe local storms. The use of atmospheric imaging is exploited to detail rapidly evolving phenomena that are difficult to observe with traditional scanning weather radars.

On the Atmospheric Regulation of the Growth of Moderate to Deep Cumulonimbus in a Tropical Environment

AbstractSome cumulus clouds with tops between 3 and 7 km (Cu3km–7km) remain in this height region throughout their lifetime (congestus) while others develop into deeper clouds (cumulonimbus). This study describes two techniques to identify the congestus and cumulonimbus cloud types using data from scanning weather radar and identifies the atmospheric conditions that regulate these two modes. A two-wet-season cumulus cloud database of the Darwin C-band polarimetric radar is analyzed and the two modes are identified by examining the 0-dBZ cloud-top height (CTH) of the Cu3km–7km cells over a sequence of radar scans. It is found that ~26% of the classified Cu3km–7km population grow into cumulonimbus clouds. The cumulonimbus cells exhibit reflectivities, rain rates, and drop sizes larger than the congestus cells. The occurrence frequency of cumulonimbus cells peak in the afternoon at ~1500 local time—a few hours after the peak in congestus cells. The analysis of Darwin International Airport radiosonde profiles associated with the two types of cells shows no noticeable difference in the thermal stability rates, but a significant difference in midtropospheric (5–10 km) relative humidity. Moister conditions are found in the hours preceding the cumulonimbus cells when compared with the congestus cells. Using a moisture budget dataset derived for the Darwin region, it is shown that the existence of cumulonimbus cells, and hence deep convection, is mainly determined by the presence of the midtroposphere large-scale upward motion and not merely by the presence of congestus clouds prior to deep convection. This contradicts the thermodynamic viewpoint that the midtroposphere moistening prior to deep convection is solely due to the preceding cumulus congestus cells.

A Combined Wind Profiler and Polarimetric Weather Radar Method for the Investigation of Precipitation and Vertical Velocities

Abstract A method is presented by which combined S-band polarimetric weather radar and UHF wind profiler observations of precipitation can be used to extract the properties of liquid phase hydrometeors and the vertical velocity of the air through which they are falling. Doppler spectra, which contain the air motion and/or fall speed of hydrometeors, are estimated using the vertically pointing wind profiler. Complementary to these observations, spectra of rain drop size distribution (DSD) are simulated by several parameters as related to the DSD, which are estimated through the two polarimetric parameters of radar reflectivity (ZH) and differential reflectivity (ZDR) from the scanning weather radar. These DSDs are then mapped into equivalent Doppler spectra (fall speeds) using an assumed relationship between the equivolume drop diameter and the drop’s terminal velocity. The method is applied to a set of observations collected on 11 March 2007 in central Oklahoma. In areas of stratiform precipitation, where the vertical wind motion is expected to be small, it was found that the fall speeds obtained from the spectra of the rain DSD agree well with those of the Doppler velocity estimated with the profiler. For those cases when the shapes of the Doppler spectra are found to be similar in shape but shifted in velocity, the velocity offset is attributed to vertical air motion. In convective rainfall, the Doppler spectra of the rain DSD and the Doppler velocity can exhibit significant differences owing to vertical air motions together with atmospheric turbulence. Overall, it was found that the height dependencies of Doppler spectra measured by the profiler combined with vertical profiles of Z, ZDR, and the cross correlation (ρHV) as well as the estimated spectra of raindrop physical terminal fall speeds from the polarimetric radar provide unique insight into the microphysics of precipitation. Vertical air motions (updrafts/downdrafts) can be estimated using such combined measurements.

Detailed Observations of Wind Turbine Clutter with Scanning Weather Radars

Abstract The wind power industry has seen tremendous growth over the past decade and with it has come the need for clutter mitigation techniques for nearby radar systems. Wind turbines can impart upon these radars a unique type of interference that is not removed with conventional clutter-filtering methods. Time series data from Weather Surveillance Radar-1988 Doppler (WSR-88D) stations near wind farms were collected and spectral analysis was used to investigate the detailed characteristics of wind turbine clutter. Techniques to mask wind turbine clutter were developed that utilize multiquadric interpolation in two and three dimensions and can be applied to both the spectral moments and spectral components. In an effort to improve performance, a nowcasting algorithm was incorporated into the interpolation scheme via a least mean squares criterion. The masking techniques described in this paper will be shown to reduce the impact of wind turbine clutter on weather radar systems at the expense of spatial resolution.

Bright‐band detection from radar vertical reflectivity profiles

The use of quantitative scanning weather radar for precipitation measurements is a vital element of modern hydrology and limits the development of all distributed models of catchment behaviour. The presence of the so‐called bright band (or melting layer) contaminates the quantitative precipitation estimates and has delayed the widespread take‐up of radar‐based precipitation estimates in operational models. The study of the Vertical Reflectivity Profile (VRP) of precipitation is important in order to develop algorithms to correct scanning weather radar measurements for the variation of the VRP at long ranges. Therefore, this paper presents an algorithm to detect the extent of the bright band using high‐resolution VRP's. The boundaries of the bright band are identified by a new algorithm which utilizes a rotational coordinate system for identifying the upper and lower parts of the bright band. This overcomes some of the difficulties experienced when using the gradient of the reflectivity in conventional bright‐band detection algorithms. The reflectivities above, within, and below the bright band are then used to construct idealized VRP's to correct scanning weather radar measurements.

Monitoring the Reflectivity Calibration of a Scanning Radar Using a Profiling Radar and a Disdrometer

Abstract This paper describes a method of absolutely calibrating and routinely monitoring the reflectivity calibration from a scanning weather radar using a vertically profiling radar that has been absolutely calibrated using a collocated surface disdrometer. The three instruments have different temporal and spatial resolutions, and the concept of upscaling is used to relate the small resolution volume disdrometer observations with the large resolution volume scanning radar observations. This study uses observations collected from a surface disdrometer, two profiling radars, and the National Weather Service (NWS) Weather Surveillance Radar-1988 Doppler (WSR-88D) scanning weather radar during the Texas–Florida Underflight-phase B (TEFLUN-B) ground validation field campaign held in central Florida during August and September 1998. The statistics from the 2062 matched profiling and scanning radar observations during this 2-month period indicate that the WSR-88D radar had a reflectivity 0.7 dBZ higher than the disdrometer-calibrated profiler, the standard deviation was 2.4 dBZ, and the 95% confidence interval was 0.1 dBZ. This study implies that although there is large variability between individual matched observations, the precision of a series of observations is good, allowing meaningful comparisons useful for calibration and monitoring.

Radar hydrometeorology using a vertically pointing radar

Abstract. A Vertically Pointing Radar (VPR) has been commissioned and deployed at a number of sites in southern England, to investigate numerically spatial and temporal variations in the vertical reflectivity profile (Zvp); particularly those associated with the intersection by the radar beam of a melting layer – the bright band. Comparisons with data from other instrumentation, notably with the S-band research radar at Chilbolton, but also with disdrometer data and rainfall measurements from a number of sophisticated rain gauges, show that VPR scans of the atmosphere provide detailed and reliable quantitative measurements of the Zvp. Analysis of a three year archive of Zvp data for Manchester has shown a bright band to be present in over 80% of rainfall events, highlighting the extent of the problem of bright band errors in scanning weather radar data. The primary characteristics of the bright band such as the height and magnitude (in dBZ) of the top, bottom and peak are identified objectively from VPR Zvp data by an automatic bright band recognition algorithm. It is envisaged that this approach could form the basis of an objective, automatic real time correction procedure for scanning weather radars. Keywords: Vertically Pointing Radar, weather radar, hydrometeorology, bright-band, melting-layer, vertical radar reflectivity

A 3-GHz Profiler for Precipitating Cloud Studies

Abstract A 3-GHz profiler has been developed by the National Oceanic and Atmospheric Administration’s Aeronomy Laboratory to observe the evolution and vertical structure of precipitating cloud systems. The profiler is very portable, robust, and relatively inexpensive, so that continuous, unattended observations of overhead precipitation can be obtained, even at remote locations. The new profiler is a vertically looking Doppler radar that operates at S band, a commonly used band for scanning weather radars (e.g., WSR-88D). The profiler has many features in common with the 915-MHz profiler developed at the Aeronomy Laboratory during the past decade primarily for measurement of lower-tropospheric winds in the Tropics. This paper presents a description of the new profiler and evaluates it in the field in Illinois and Australia in comparison with UHF lower-tropospheric profilers. In Illinois, the new profiler was evaluated alongside a collocated 915-MHz profiler at the Flatland Atmospheric Observatory. In Aust...

The accuracy of rainfall estimates by radar as a function of range

AbstractHigh‐spatial‐resolution data were collected for nearby convective storms by using a volume scanning weather radar with 200m resolution, and for stratiform events by using a high‐resolution (20m) vertically pointing radar. Errors in the estimation of rainfall by the scanning radar, due to the radar beam intersecting or overshooting features such as the bright band, were simulated by using these high‐resolution images. It was found that these effects define a maximum useful range for the radar that is a strong function of the prevailing meteorological conditions (e.g. bright‐band height, intense cell diameter and height).Sudden changes in bright‐band height over short times and the large scatter observed in its thickness limit the accuracy with which corrections for the vertical profile of reflectivity may be precalculated in stratiform rain events. A scheme for using a vertically pointing radar to produce these corrections in real time is proposed. the convective events show enough significant storm‐to‐storm variability that caution is required in extending the useful range of the radar too far.