New pathways for high-resolution weather radar products in the Hamburg metropolitan region

2020 ◽  
Author(s):  
Finn Burgemeister ◽  
Tobias Sebastian Finn ◽  
Tobias Machnitzki ◽  
Marco Clemens ◽  
Felix Ament
Keyword(s):  
Weather Radar ◽  
Real Data ◽  
Potential Method ◽  
Metropolitan Region ◽  
Small Scale ◽  
Radar Observations ◽  
Range Resolution ◽  
Weather Radars ◽  
X Band ◽  
The One

<p>The University of Hamburg operates a single-polarized X-band weather radar to investigate small scale precipitation in Hamburg’s center since 2013. This weather radar provides a temporal resolution of 30 s, a range resolution of 60 m, and a sampling resolution of 1° within a 20 km radius. The X-band observations refine the coarse measurements of the German nationwide C-band radars. On the one hand, the resolution enables new capabilities in research and detection of extreme events, e.g. flash floods or tornadoes in rain events. On the other hand, with the single polarization and small wavelength, attenuation, noise, and non-meteorological echoes become a challenging issue. How can we derive products from disturbed weather radar observations?</p><p>We demonstrate new methods to process X-band weather radar observations effectively using synthetic and real data. Firstly, we present our python package for local weather radars. This package combines all steps of processing our measurements and includes well-established algorithms of image processing and radar meteorology. Secondly, we study machine learning as a new and potential method for our weather radar products. The developed neural network uses raw reflectivity measurements as input and results in data, which is free of noise and non-meteorological echoes. We outline assets and drawbacks of both methods and show possible connections.</p><p>Further X-band weather radar systems are planned for 2020 to monitor precipitation for the Hamburg metropolitan region in a networked environment. The high-quality and -resolution weather radar products will be provided for urban hydrology research within the Cluster of Excellence CLICCS - Climate, Climatic Change, and Society.</p>

scholarly journals Performance of high-resolution X-band weather radar networks – the PATTERN example

2014 ◽  
Vol 7 (8) ◽  
pp. 8233-8270
Author(s):  
K. Lengfeld ◽  
M. Clemens ◽  
H. Münster ◽  
F. Ament
Keyword(s):  
High Resolution ◽  
Spatial Resolution ◽  
Low Cost ◽  
Weather Radar ◽  
Local Area ◽  
Small Scale ◽  
Rain Event ◽  
Range Resolution ◽  
Radar Networks ◽  
X Band

Abstract. This publication intends to proof that a network of low-cost local area weather radars (LAWR) is a reliable and scientifically valuable complement to nationwide radar networks. A network of four LAWRs has been installed in northern Germany within the framework of the project Precipitation and Attenuation Estimates from a High-Resolution Weather Radar Network (PATTERN) observing precipitation with temporal resolution of 30 s, azimuthal resolution of 1° and spatial resolution of 60 m. The network covers an area of 60 km × 80 km. In this paper algorithms used to obtain undisturbed precipitation fields from raw reflectivity data are described and their performance is analysed. In order to correct for background noise in reflectivity measurements operationally, noise level estimates from the measured reflectivity field is combined with noise levels from the last 10 time steps. For detection of non-meteorological echoes two different kinds of clutter filters are applied: single radar algorithms and network based algorithms that take advantage of the unique features of high temporal and spatial resolution of the network. Overall the network based clutter filter works best with a detection rate of up to 70%, followed by the classic TDBZ filter using the texture of the logarithmic reflectivity field. A comparison of a reflectivity field from the PATTERN network with the product from a C-band radar operated by the German Meteorological Service indicates high spatial accordance of both systems in geographical position of the rain event as well as reflectivity maxima. A longterm study derives good accordance of X-band radar of the network with C-band radar. But especially at the border of precipitation events the standard deviation within a range gate of the C-band radar with range resolution of 1 km is up to 3 dBZ. Therefore, a network of high-resolution low-cost LAWRs can give valuable information on the small scale structure of rain events in areas of special interest, e.g. urban regions, in addition the nationwide radar networks.

scholarly journals Performance of high-resolution X-band weather radar networks – the PATTERN example

2014 ◽  
Vol 7 (12) ◽  
pp. 4151-4166 ◽  
Author(s):  
K. Lengfeld ◽  
M. Clemens ◽  
H. Münster ◽  
F. Ament
Keyword(s):  
High Resolution ◽  
Low Cost ◽  
Weather Radar ◽  
Probability Of Detection ◽  
Small Scale ◽  
Rain Event ◽  
Range Resolution ◽  
Radar Networks ◽  
X Band ◽  
Rain Events

Abstract. This publication intends to prove that a network of low-cost local area weather radars (LAWR) is a reliable and scientifically valuable complement to nationwide radar networks. A network of four LAWRs has been installed in northern Germany within the framework of the Precipitation and Attenuation Estimates from a High-Resolution Weather Radar Network (PATTERN) project observing precipitation with a temporal resolution of 30 s, a range resolution of 60 m and a sampling resolution of 1° in the azimuthal direction. The network covers an area of 60 km × 80 km. In this paper, algorithms used to obtain undisturbed precipitation fields from raw reflectivity data are described, and their performance is analysed. In order to correct operationally for background noise in reflectivity measurements, noise level estimates from the measured reflectivity field are combined with noise levels from the last 10 time steps. For detection of non-meteorological echoes, two different kinds of clutter algorithms are applied: single-radar algorithms and network-based algorithms. Besides well-established algorithms based on the texture of the logarithmic reflectivity field (TDBZ) or sign changes in the reflectivity gradient (SPIN), the advantage of the unique features of the high temporal and spatial resolution of the network is used for clutter detection. Overall, the network-based clutter algorithm works best with a detection rate of up to 70%, followed by the classic TDBZ filter using the texture of the logarithmic reflectivity field. A comparison of a reflectivity field from the PATTERN network with the product from a C-band radar operated by the German Meteorological Service indicates high spatial accordance of both systems in the geographical position of the rain event as well as reflectivity maxima. Long-term statistics from May to September 2013 prove very good accordance of the X-band radar of the network with C-band radar, but, especially at the border of precipitation events, higher-resolved X-band radar measurements provide more detailed information on precipitation structure because the 1 km range gate of C-band radars is only partially covered with rain. The standard deviation within a range gate of the C-band radar with a range resolution of 1 km is up to 3 dBZ at the borders of rain events. The probability of detection is at least 90%, the false alarm ratio less than 10% for both systems. Therefore, a network of high-resolution low-cost LAWRs can give valuable information on the small-scale structure of rain events in areas of special interest, e.g. urban regions, in addition to the nationwide radar networks.

scholarly journals Combined wind profiler-weather radar observations of orographic rainband around Kyushu, Japan in the Baiu season

2004 ◽  
Vol 22 (11) ◽  
pp. 3971-3982 ◽  
Author(s):  
Y. Umemoto ◽  
M. Teshiba ◽  
Y. Shibagaki ◽  
H. Hashiguchi ◽  
M. D. Yamanaka ◽  
...  
Keyword(s):  
Weather Radar ◽  
Horizontal Wind ◽  
Wind Component ◽  
Wind Profiler ◽  
Strong Wind ◽  
Clockwise Rotation ◽  
Weather Radars ◽  
X Band ◽  
Western Japan ◽  
Lifting Condensation Level

Abstract. A special observation campaign (X-BAIU), using various instruments (wind profilers, C-band weather radars, X-band Doppler radars, rawinsondes, etc.), was carried out in Kyushu (western Japan) during the Baiu season, from 1998 to 2002. In the X-BAIU-99 and -02 observations, a line-shaped orographic rainband extending northeastward from the Koshikijima Islands appeared in the low-level strong wind with warm-moist airs. The weather radar observation indicated that the rainband was maintained for 11h. The maximum length and width of the rainband observed in 1999 was ~200km and ~20km, respectively. The rainband observed in 2002 was not so developed compared with the case in 1999. The Froude number averaged from sea level to the top of the Koshikijima Islands (~600m) was large (>1), and the lifting condensation level was below the tops of the Koshikijima Islands. Thus, it is suggested that the clouds organizing the rainband are formed by the triggering of the mountains on the airflow passing over them. The vertical profile of horizontal wind in/around the rainband was investigated in the wind profiler observations. In the downdraft region 60km from the Koshikijima Islands, strong wind and its clockwise rotation with increasing height was observed below 3km altitude. In addition, a strong wind component perpendicular to the rainband was observed when the rainband was well developed. These wind behaviors were related to the evolution of the rainband.

High-Temporal Resolution Polarimetric X-Band Doppler Radar Observations of the 20 May 2013 Moore, Oklahoma, Tornado

2015 ◽  
Vol 143 (7) ◽  
pp. 2711-2735 ◽  
Author(s):  
James M. Kurdzo ◽  
David J. Bodine ◽  
Boon Leng Cheong ◽  
Robert D. Palmer
Keyword(s):  
Temporal Resolution ◽  
Doppler Radar ◽  
Medical Center ◽  
Small Scale ◽  
High Temporal Resolution ◽  
Radar Observations ◽  
University Of Oklahoma ◽  
X Band ◽  
Damage Indicators ◽  
Gust Front

Abstract On 20 May 2013, the cities of Newcastle, Oklahoma City, and Moore, Oklahoma, were impacted by a long-track violent tornado that was rated as an EF5 on the enhanced Fujita scale by the National Weather Service. Despite a relatively sustained long track, damage surveys revealed a number of small-scale damage indicators that hinted at storm-scale processes that occurred over short time periods. The University of Oklahoma (OU) Advanced Radar Research Center’s PX-1000 transportable, polarimetric, X-band weather radar was operating in a single-elevation PPI scanning strategy at the OU Westheimer airport throughout the duration of the tornado, collecting high spatial and temporal resolution polarimetric data every 20 s at ranges as close as 10 km and heights below 500 m AGL. This dataset contains the only known polarimetric radar observations of the Moore tornado at such high temporal resolution, providing the opportunity to analyze and study finescale phenomena occurring on rapid time scales. Analysis is presented of a series of debris ejections and rear-flank gust front surges that both preceded and followed a loop of the tornado as it weakened over the Moore Medical Center before rapidly accelerating and restrengthening to the east. The gust front structure, debris characteristics, and differential reflectivity arc breakdown are explored as evidence for a “failed occlusion” hypothesis. Observations are supported by rigorous hand analysis of critical storm attributes, including tornado track relative to the damage survey, sudden track shifts, and a directional debris ejection analysis. A conceptual description and illustration of the suspected failed occlusion process is provided, and its implications are discussed.

scholarly journals Adaptive and High-Resolution Estimation of Specific Differential Phase for Polarimetric X-Band Weather Radars

2018 ◽  
Vol 35 (3) ◽  
pp. 555-573 ◽  
Author(s):  
Ricardo Reinoso-Rondinel ◽  
Christine Unal ◽  
Herman Russchenberg
Keyword(s):  
Standard Deviation ◽  
Spatial Variability ◽  
Heavy Rain ◽  
Storm Events ◽  
Band Frequency ◽  
Adaptive Approach ◽  
Range Resolution ◽  
Differential Phase ◽  
Weather Radars ◽  
X Band

ABSTRACTOne of the most beneficial polarimetric variables may be the specific differential phase KDP because of its independence from power attenuation and radar miscalibration. However, conventional KDP estimation requires a substantial amount of range smoothing as a result of the noisy characteristic of the measured differential phase ΨDP. In addition, the backscatter differential phase δhv component of ΨDP, significant at C- and X-band frequency, may lead to inaccurate KDP estimates. In this work, an adaptive approach is proposed to obtain accurate KDP estimates in rain from noisy ΨDP, whose δhv is of significance, at range resolution scales. This approach uses existing relations between polarimetric variables in rain to filter δhv from ΨDP while maintaining its spatial variability. In addition, the standard deviation of the proposed KDP estimator is mathematically formulated for quality control. The adaptive approach is assessed using four storm events, associated with light and heavy rain, observed by a polarimetric X-band weather radar in the Netherlands. It is shown that this approach is able to retain the spatial variability of the storms at scales of the range resolution. Moreover, the performance of the proposed approach is compared with two different methods. The results of this comparison show that the proposed approach outperforms the other two methods in terms of the correlation between KDP and reflectivity, and KDP standard deviation reduction.

scholarly journals Staggered-PRT Sequences for Doppler Weather Radars. Part I: Spectral Analysis Using the Autocorrelation Spectral Density

2017 ◽  
Vol 34 (1) ◽  
pp. 51-63 ◽  
Author(s):  
Sebastián M. Torres ◽  
David A. Warde
Keyword(s):  
Spectral Analysis ◽  
Spectral Density ◽  
Power Spectral Density ◽  
Weather Radar ◽  
Real Data ◽  
Pulse Repetition ◽  
Spectral Processing ◽  
Weather Radars ◽  
Power Spectral ◽  
Repetition Time

AbstractThe autocorrelation spectral density (ASD) was introduced as a generalization of the classical periodogram-based power spectral density (PSD) and as an alternative tool for spectral analysis of uniformly sampled weather radar signals. In this paper, the ASD is applied to staggered pulse repetition time (PRT) sequences and is related to both the PSD and the ASD of the underlying uniform-PRT sequence. An unbiased autocorrelation estimator based on the ASD is introduced for use with staggered-PRT sequences when spectral processing is required. Finally, the strengths and limitations of the ASD for spectral analysis of staggered-PRT sequences are illustrated using simulated and real data.

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

2017 ◽  
Vol 98 (5) ◽  
pp. 915-935 ◽  
Author(s):  
James M. Kurdzo ◽  
Feng Nai ◽  
David J. Bodine ◽  
Timothy A. Bonin ◽  
Robert D. Palmer ◽  
...  
Keyword(s):  
Temporal Resolution ◽  
Pulse Compression ◽  
Radar Imaging ◽  
Narrow Beam ◽  
Digital Beamforming ◽  
Range Resolution ◽  
Imaging Radar ◽  
Weather Radars ◽  
X Band ◽  
Receive Array

Abstract Mobile 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.

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.

Towards a multi-year urban precipitation climatology at 100 m scale using X-band radar observations

2021 ◽  
Author(s):  
Finn Burgemeister ◽  
Marco Clemens ◽  
Felix Ament
Keyword(s):  
Urban Area ◽  
Elevation Angle ◽  
Weather Radar ◽  
Rain Event ◽  
Data Set ◽  
Radar Observations ◽  
Precipitation Climatology ◽  
X Band ◽  
Time Periods ◽  
Radar Calibration

<p>An operational, single-polarized X-band weather radar provides measurements in Hamburg’s city center for almost eight years. This weather radar operates at an elevation angle (~3.5°) with a high temporal (30 s), range (60 m), and sampling (1°) resolution resulting<span> in a</span> high information density within <span>the</span> 20 km <span>scan radius</span>. <span>Studies on short time periods (several months) proofs the performance of this low-cost local area weather radar. </span><span>For example, a</span><span> case study on a tornado in a rain event demonstrates its refined resolution </span><span>compared to</span><span> the German nationwide C-band radars. </span><span>Now, we aim for a eight-year precipitation climatology with 100 m resolution. This data set will enable reliable studies on urban extreme precipitation. This presentation will describe h</span><span>ow we </span><span>can</span><span> infer a precipitation estimate based on multi-</span><span>year</span><span> weather radar observations in the urban area of Hamburg.</span></p><p>The single-polarization and <span>small</span> <span>wavelength</span> <span>comes along with</span> high resolution <span>but at the same time</span> high uncertainties. We address several sources of errors affecting th<span>e</span> radar-based <span>precipitation</span> estimate, like the radar calibration, alignment, attenuation, noise, non-meteorologial echoes, <span>and </span><span><em>Z</em></span><span>-</span><span><em>R</em></span><span> relation. The deployment of additional vertically pointing micro rain radars yields drop size distributions at relevant heights reducing errors effectively concerning the radar calibration and required statistical relations (</span><span><em>k</em></span><span>-</span><span><em>Z</em></span><span> and </span><span><em>Z</em></span><span>-</span><span><em>R</em></span><span> relation). We outline the performance of the correction methods for long time periods and discuss open issues and limitations.</span></p><p><span>With this high-quality and -resolution weather radar product, refined studies on the spatial and temporal scale of </span><span>urban </span><span>precipitation will be possible. </span><span>This data set will be used for</span><span> further hydrological research in an urban area </span><span>within the project <em>Sustainable Adaption Scenarios for Urban Areas – Water from Four Sides</em> of the</span><span> Cluster of Excellence <em>Climate Climatic Change, and Society</em> (CliCCS).</span></p>

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