scholarly journals X-Band Polarimetric Weather Radar Observations of a Hailstorm

2013 ◽  
Vol 30 (9) ◽  
pp. 2143-2151 ◽  
Author(s):  
Jordi Figueras i Ventura ◽  
Françoise Honoré ◽  
Pierre Tabary
Keyword(s):  
Weather Radar ◽  
Radar Data ◽  
Polarimetric Radar ◽  
Complementary Information ◽  
Radar Observations ◽  
National Network ◽  
X Band ◽  
Polarimetric Weather Radar

Abstract This paper presents an analysis of a hail event that occurred 27 May 2012 over Brignoles, located in southeastern France. The event was observed by an X-band polarimetric radar located in Mont Maurel, 75 km northeast of the hailstorm. Lightning data from the French national network (owned and operated by Météorage) are also used in the study. The analysis highlights that the lightning and radar data provide complementary information that may allow a better microphysical interpretation of the hailstorm and potentially increase the probability of its detection.

scholarly journals Radar Applications in Northern Scotland (RAiNS)

2020 ◽  
Author(s):  
Ryan R Neely ◽  
Louise Parry ◽  
David Dufton ◽  
Lindsay Bennett ◽  
Chris Collier
Keyword(s):  
High Resolution ◽  
Weather Radar ◽  
Polarimetric Radar ◽  
Summer Period ◽  
Radar Observations ◽  
X Band ◽  
Precipitation Estimates ◽  
Radar Applications ◽  
Quantitative Precipitation Estimates ◽  
Hydrological Applications

AbstractThe Radar Applications in Northern Scotland (RAiNS) experiment took place from February to August 2016 near Inverness, Scotland. The campaign was motivated by the need to provide enhanced weather radar observations for hydrological applications for the Inverness region. Here we describe the campaign in detail and observations over the summer period of the campaign that show the improvements that high-resolution polarimetric radar observations may have on quantitative precipitation estimates in this region compared to concurrently generated operational radar quantitative precipitation estimates (QPE). We further provide suggestions of methods for generating QPE using dual-polarisation X-band radars in similar regions.

scholarly journals Insights into wind turbine reflectivity and RCS and their variability using X-band weather radar observations

2020 ◽  
Author(s):  
Martin Lainer ◽  
Jordi Figueras i Ventura ◽  
Zaira Schauwecker ◽  
Marco Gabella ◽  
Montserrat F.-Bolaños ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Weather Radar ◽  
Least Square ◽  
Clear Correlation ◽  
Radar Observations ◽  
Ordinary Least Square ◽  
The North ◽  
X Band ◽  
Polarimetric Weather Radar

Abstract. The increasing need of renewable energy fosters the expansion of wind turbine sites for power production throughout Europe with manifold effects, both on the positive and negative side. The latter concerns, among others, radar observations in the proximity of wind turbine (WT) sites. With the aim of better understanding the effects of large, moving scatterers like wind turbines on radar returns, MeteoSwiss performed two dedicated measurement campaigns with a mobile X-band Doppler polarimetric weather radar (METEOR 50DX) in the north-eastern part of Switzerland in March 2019 and March 2020. Based on the usage of a X-band radar system, the performed campaigns are up to now unique. The main goal was to quantify the effects of wind turbines on the observed radar moments, to retrieve the radar cross section (RCS) of the turbine themselves, and to investigate the conditions leading to the occurrence of the largest RCS. Dedicated scan strategies, consisting of PPI (Plan Position Indicator), RHI (Range-height Indicator) and fixed-pointing modes, were defined and used for observing a wind park consisting of three large wind turbines. During both campaigns, measurements were taken in 24/7 operation. The highest measured maxima of horizontal reflectivity (ZH) and RCS reached 78.5 dBZ respectively 44.1 dBsm. A wind turbine orientation (yawing) stratified statistical analysis shows no clear correlation with the received maximum returns. However, the median values and 99th percentiles of ZH and RCS show different enhancements for specific relative orientations. Further, we show, based on investigating correlations and an OLS (ordinary least square) model analyses, that the fast changing rotor blade angle (pitch) is a key parameter, which strongly contributes to the variability of the observed returns.

scholarly journals Insights into wind turbine reflectivity and radar cross-section (RCS) and their variability using X-band weather radar observations

2021 ◽  
Vol 14 (5) ◽  
pp. 3541-3560
Author(s):  
Martin Lainer ◽  
Jordi Figueras i Ventura ◽  
Zaira Schauwecker ◽  
Marco Gabella ◽  
Montserrat F.-Bolaños ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Cross Section ◽  
Wind Turbines ◽  
Weather Radar ◽  
Radar Cross Section ◽  
Least Square ◽  
Clear Correlation ◽  
Radar Observations ◽  
X Band ◽  
Polarimetric Weather Radar

Abstract. The increasing need of renewable energy fosters the expansion of wind turbine sites for power production throughout Europe with manifold effects, both on the positive and negative side. The latter concerns, among others, radar observations in the proximity of wind turbine (WT) sites. With the aim of better understanding the effects of large, moving scatterers like wind turbines on radar returns, MeteoSwiss performed two dedicated measurement campaigns with a mobile X-band Doppler polarimetric weather radar (METEOR 50DX) in the northeastern part of Switzerland in March 2019 and March 2020. Based on the usage of an X-band radar system, the performed campaigns are up to now unique. The main goal was to quantify the effects of wind turbines on the observed radar moments, to retrieve the radar cross-section (RCS) of the turbines themselves and to investigate the conditions leading to the occurrence of the largest RCS. Dedicated scan strategies, consisting of PPI (plan position indicator), RHI (range–height indicator) and fixed-pointing modes, were defined and used for observing a wind park consisting of three large wind turbines. During both campaigns, measurements were taken in 24/7 operation. The highest measured maxima of horizontal reflectivity (ZH) and RCS reached 78.5 dBZ and 44.1 dBsm, respectively. A wind turbine orientation (yawing) stratified statistical analysis shows no clear correlation with the received maximum returns. However, the median values and 99th percentiles of ZH show different enhancements for specific relative orientations. Some of them remain still for Doppler-filtered data, supporting the importance of the moving parts of the wind turbine for the radar returns. Further, we show, based on investigating correlations and an OLS (ordinary least square) model analysis, that the fast-changing rotor blade angle (pitch) is a key parameter, which strongly contributes to the variability in the observed returns.

scholarly journals Hydrometeor classification of quasi-vertical profiles of polarimetric radar measurements using a top-down iterative hierarchical clustering method

2021 ◽  
Vol 14 (2) ◽  
pp. 1075-1098
Author(s):  
Maryna Lukach ◽  
David Dufton ◽  
Jonathan Crosier ◽  
Joshua M. Hampton ◽  
Lindsay Bennett ◽  
...  
Keyword(s):  
Weather Radar ◽  
Original Data ◽  
Optimal Number ◽  
Vertical Profiles ◽  
Radar Observations ◽  
X Band ◽  
Novel Method ◽  
Microphysical Processes ◽  
Polarimetric Weather Radar ◽  
Temporal Dimensions

Abstract. Correct, timely and meaningful interpretation of polarimetric weather radar observations requires an accurate understanding of hydrometeors and their associated microphysical processes along with well-developed techniques that automatize their recognition in both the spatial and temporal dimensions of the data. This study presents a novel technique for identifying different types of hydrometeors from quasi-vertical profiles (QVPs). In this new technique, the hydrometeor types are identified as clusters belonging to a hierarchical structure. The number of different hydrometeor types in the data is not predefined, and the method obtains the optimal number of clusters through a recursive process. The optimal clustering is then used to label the original data. Initial results using observations from the National Centre for Atmospheric Science (NCAS) X-band dual-polarization Doppler weather radar (NXPol) show that the technique provides stable and consistent results. Comparison with available airborne in situ measurements also indicates the value of this novel method for providing a physical delineation of radar observations. Although this demonstration uses NXPol data, the technique is generally applicable to similar multivariate data from other radar observations.

scholarly journals Multisensor Characterization of the Incandescent Jet Region of Lava Fountain-Fed Tephra Plumes

2020 ◽  
Vol 12 (21) ◽  
pp. 3629
Author(s):  
Luigi Mereu ◽  
Simona Scollo ◽  
Costanza Bonadonna ◽  
Valentin Freret-Lorgeril ◽  
Frank Silvio Marzano
Keyword(s):  
Warning System ◽  
Weather Radar ◽  
Weather Conditions ◽  
Radar Data ◽  
Retrieval Algorithm ◽  
Lava Fountain ◽  
X Band ◽  
L Band ◽  
The Difference ◽  
Polarimetric Weather Radar

Explosive basaltic eruptions eject a great amount of pyroclastic material into the atmosphere, forming columns rising to several kilometers above the eruptive vent and causing significant disruption to both proximal and distal communities. Here, we analyze data, collected by an X-band polarimetric weather radar and an L-band Doppler fixed-pointing radar, as well as by a thermal infrared (TIR) camera, in relation to lava fountain-fed tephra plumes at the Etna volcano in Italy. We clearly identify a jet, mainly composed of lapilli and bombs mixed with hot gas in the first portion of these volcanic plumes and here called the incandescent jet region (IJR). At Etna and due to the TIR camera configuration, the IJR typically corresponds to the region that saturates thermal images. We find that the IJR is correlated to a unique signature in polarimetric radar data as it represents a zone with a relatively high reflectivity and a low copolar correlation coefficient. Analyzing five recent Etna eruptions occurring in 2013 and 2015, we propose a jet region radar retrieval algorithm (JR3A), based on a decision-tree combining polarimetric X-band observables with L-band radar constraints, aiming at the IJR height detection during the explosive eruptions. The height of the IJR does not exactly correspond to the height of the lava fountain due to a different altitude, potentially reached by lapilli and blocks detected by the X-band weather radar. Nonetheless, it can be used as a proxy of the lava fountain height in order to obtain a first approximation of the exit velocity of the mixture and, therefore, of the mass eruption rate. The comparisons between the JR3A estimates of IJR heights with the corresponding values recovered from TIR imagery, show a fairly good agreement with differences of less than 20% in clear air conditions, whereas the difference between JR3A estimates of IJR height values and those derived from L-band radar data only are greater than 40%. The advantage of using an X-band polarimetric weather radar in an early warning system is that it provides information in all weather conditions. As a matter of fact, we show that JR3A retrievals can also be obtained in cloudy conditions when the TIR camera data cannot be processed.

scholarly journals Hydrometeor classification of quasi-vertical profiles of polarimetric radar measurements using a top-down iterative hierarchical clustering method

2020 ◽  
Author(s):  
Maryna Lukach ◽  
David Dufton ◽  
Jonathan Crosier ◽  
Joshua M. Hampton ◽  
Lindsay Bennett ◽  
...  
Keyword(s):  
Weather Radar ◽  
Original Data ◽  
Optimal Number ◽  
Vertical Profiles ◽  
Radar Observations ◽  
X Band ◽  
Novel Method ◽  
Microphysical Processes ◽  
Polarimetric Weather Radar ◽  
Temporal Dimensions

Abstract. Correct, timely and meaningful interpretation of polarimetric weather radar observations requires an accurate understanding of hydrometeors and their associated microphysical processes along with well-developed techniques that automatize their recognition in both the spatial and temporal dimensions of the data. This study presents a novel technique for identifying different types of hydrometeors from Quasi-Vertical Profiles (QVP). In this new technique, the hydrometeor types are identified as clusters belonging to a hierarchical structure. The number of different hydrometeor types in the data is not predefined and the method obtains the optimal number of clusters through a recursive process. The optimal clustering is then used to label the original data. Initial results using observations from the NCAS X-band dual-polarization Doppler weather radar (NXPol) show that the technique provides stable and consistent results. Comparison with available airborne in situ measurements also indicates the value of this novel method for providing a physical delineation of radar observations. Although this demonstration uses NXPol data, the technique is generally applicable to similar multivariate data from other radar observations.

scholarly journals Rainfall Information System Based on Weather Radar for Debris Flow Disaster Mitigation

2018 ◽  
Vol 7 (4.44) ◽  
pp. 165 ◽  
Author(s):  
Ratih Indri Hapsari ◽  
Gerard Aponno ◽  
Rosa Andrie Asmara ◽  
Satoru Oishi
Keyword(s):  
Information System ◽  
Debris Flow ◽  
Weather Radar ◽  
Active Volcano ◽  
Radar Data ◽  
Disaster Mitigation ◽  
Web Based ◽  
X Band ◽  
Secondary Hazards ◽  
Debris Flow Disaster

Rainfall-triggered debris flow has caused multiple impacts to the environment. It. is regarded as the most severe secondary hazards of volcanic eruption. However, limited access to the active volcano slope restricts the ground rain measurement as well as the direct delivery of risk information. In this study, an integrated information system is proposed for volcanic-related disaster mitigation under the framework of X-Plore/X-band Polarimetric Radar for Prevention of Water Disaster. In the first part, the acquisition and processing of high-resolution X-band dual polarimetric weather/X-MP radar data in real-time scheme for demonstrating the disaster-prone region are described. The second part presents the design of rainfall resource database and extensive maps coverage of predicted hazard information in GIS web-based platform accessible both using internet and offline. The proposed platform would be useful for communicating the disaster risk prediction based on weather radar in operational setting.  

Classification of Precipitation Types during Transitional Winter Weather Using the RUC Model and Polarimetric Radar Retrievals

2012 ◽  
Vol 51 (4) ◽  
pp. 763-779 ◽  
Author(s):  
Terry J. Schuur ◽  
Hyang-Suk Park ◽  
Alexander V. Ryzhkov ◽  
Heather D. Reeves
Keyword(s):  
Numerical Models ◽  
Radar Data ◽  
Storm Event ◽  
Model Output ◽  
Polarimetric Radar ◽  
Radar Observations ◽  
Precipitation Type ◽  
Microphysical Processes ◽  
Using Data

AbstractA new hydrometeor classification algorithm that combines thermodynamic output from the Rapid Update Cycle (RUC) model with polarimetric radar observations is introduced. The algorithm improves upon existing classification techniques that rely solely on polarimetric radar observations by using thermodynamic information to help to diagnose microphysical processes (such as melting or refreezing) that might occur aloft. This added information is especially important for transitional weather events for which past studies have shown radar-only techniques to be deficient. The algorithm first uses vertical profiles of wet-bulb temperature derived from the RUC model output to provide a background precipitation classification type. According to a set of empirical rules, polarimetric radar data are then used to refine precipitation-type categories when the observations are found to be inconsistent with the background classification. Using data from the polarimetric KOUN Weather Surveillance Radar-1988 Doppler (WSR-88D) located in Norman, Oklahoma, the algorithm is tested on a transitional winter-storm event that produced a combination of rain, freezing rain, ice pellets, and snow as it passed over central Oklahoma on 30 November 2006. Examples are presented in which the presence of a radar bright band (suggesting an elevated warm layer) is observed immediately above a background classification of dry snow (suggesting the absence of an elevated warm layer in the model output). Overall, the results demonstrate the potential benefits of combining polarimetric radar data with thermodynamic information from numerical models, with model output providing widespread coverage and polarimetric radar data providing an observation-based modification of the derived precipitation type at closer ranges.

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