scholarly journals Performance of high-resolution X-band radar for rainfall measurement in The Netherlands

2009 ◽  
Vol 6 (5) ◽  
pp. 6035-6085 ◽  
Author(s):  
C. Z. van de Beek ◽  
H. Leijnse ◽  
J. N. M. Stricker ◽  
R. Uijlenhoet ◽  
H. W. J. Russchenberg
Keyword(s):  
High Resolution ◽  
The Netherlands ◽  
Weather Radar ◽  
Rain Gauge ◽  
Signal Loss ◽  
Rainfall Events ◽  
Ground Clutter ◽  
X Band ◽  
Urban Catchments ◽  
Radar Calibration

Abstract. This study presents an analysis of 195 rainfall events gathered with the X-band weather radar SOLIDAR and a tipping bucket rain gauge network near Delft, The Netherlands, between May 1993 and April 1994. The high spatial (120 m) and temporal (16 s) resolution of the radar combined with the extent of the database make this study a climatological analysis of the potential for high-resolution rainfall measurement with non-polarimetric X-band radar over completely flat terrain. An appropriate radar reflectivity – rain rate relation is derived from measurements of raindrop size distributions and compared with radar – rain gauge data. The radar calibration is assessed using a long-term comparison of rain gauge measurements with corresponding radar reflectivities as well as by analyzing the evolution of the stability of ground clutter areas over time. Three different methods for ground clutter correction as well as the effectiveness of forward and backward attenuation correction algorithms have been studied. Five individual rainfall events are discussed in detail to illustrate the strengths and weaknesses of high-resolution X-band radar and the effectiveness of the presented correction methods. X-band radar is found to be able to measure the space-time variation of rainfall at high resolution, far greater than can be achieved by rain gauge networks or a typical operational C-band weather radar. On the other hand, SOLIDAR can suffer from receiver saturation, wet radome attenuation as well as signal loss along the path. During very strong convective situations the signal can even be lost completely. In combination with several rain gauges for quality control, high resolution X-band radar is considered to be suitable for rainfall monitoring over relatively small (urban) catchments. These results offer great prospects for the new high resolution polarimetric doppler X-band radar IDRA.

scholarly journals Performance of high-resolution X-band radar for rainfall measurement in The Netherlands

2010 ◽  
Vol 14 (2) ◽  
pp. 205-221 ◽  
Author(s):  
C. Z. van de Beek ◽  
H. Leijnse ◽  
J. N. M. Stricker ◽  
R. Uijlenhoet ◽  
H. W. J. Russchenberg
Keyword(s):  
High Resolution ◽  
The Netherlands ◽  
Weather Radar ◽  
Rain Gauge ◽  
Signal Loss ◽  
Rainfall Events ◽  
Ground Clutter ◽  
X Band ◽  
Urban Catchments ◽  
Radar Calibration

Abstract. This study presents an analysis of 195 rainfall events gathered with the X-band weather radar SOLIDAR and a tipping bucket rain gauge network near Delft, The Netherlands, between May 1993 and April 1994. The aim of this paper is to present a thorough analysis of a climatological dataset using a high spatial (120 m) and temporal (16 s) resolution X-band radar. This makes it a study of the potential for high-resolution rainfall measurements with non-polarimetric X-band radar over flat terrain. An appropriate radar reflectivity – rain rate relation is derived from measurements of raindrop size distributions and compared with radar – rain gauge data. The radar calibration is assessed using a long-term comparison of rain gauge measurements with corresponding radar reflectivities as well as by analyzing the evolution of the stability of ground clutter areas over time. Three different methods for ground clutter correction as well as the effectiveness of forward and backward attenuation correction algorithms have been studied. Five individual rainfall events are discussed in detail to illustrate the strengths and weaknesses of high-resolution X-band radar and the effectiveness of the presented correction methods. X-band radar is found to be able to measure the space-time variation of rainfall at high resolution, far greater than what can be achieved by rain gauge networks or a typical operational C-band weather radar. On the other hand, SOLIDAR can suffer from receiver saturation, wet radome attenuation as well as signal loss along the path. During very strong convective situations the signal can even be lost completely. In combination with several rain gauges for quality control, high resolution X-band radar is considered to be suitable for rainfall monitoring over relatively small (urban) catchments. These results offer great prospects for the new high resolution polarimetric doppler X-band radar IDRA.

scholarly journals Close-range radar rainfall estimation and error analysis

2016 ◽  
Vol 9 (8) ◽  
pp. 3837-3850 ◽  
Author(s):  
C. Z. van de Beek ◽  
H. Leijnse ◽  
P. Hazenberg ◽  
R. Uijlenhoet
Keyword(s):  
Positive Impact ◽  
Rain Gauge ◽  
Minor Role ◽  
Rainfall Estimation ◽  
Radar Rainfall ◽  
Sources Of Error ◽  
Ground Clutter ◽  
Received Power ◽  
Radar Calibration ◽  
Many Sources

Abstract. Quantitative precipitation estimation (QPE) using ground-based weather radar is affected by many sources of error. The most important of these are (1) radar calibration, (2) ground clutter, (3) wet-radome attenuation, (4) rain-induced attenuation, (5) vertical variability in rain drop size distribution (DSD), (6) non-uniform beam filling and (7) variations in DSD. This study presents an attempt to separate and quantify these sources of error in flat terrain very close to the radar (1–2 km), where (4), (5) and (6) only play a minor role. Other important errors exist, like beam blockage, WLAN interferences and hail contamination and are briefly mentioned, but not considered in the analysis. A 3-day rainfall event (25–27 August 2010) that produced more than 50 mm of precipitation in De Bilt, the Netherlands, is analyzed using radar, rain gauge and disdrometer data. Without any correction, it is found that the radar severely underestimates the total rain amount (by more than 50 %). The calibration of the radar receiver is operationally monitored by analyzing the received power from the sun. This turns out to cause a 1 dB underestimation. The operational clutter filter applied by KNMI is found to incorrectly identify precipitation as clutter, especially at near-zero Doppler velocities. An alternative simple clutter removal scheme using a clear sky clutter map improves the rainfall estimation slightly. To investigate the effect of wet-radome attenuation, stable returns from buildings close to the radar are analyzed. It is shown that this may have caused an underestimation of up to 4 dB. Finally, a disdrometer is used to derive event and intra-event specific Z–R relations due to variations in the observed DSDs. Such variations may result in errors when applying the operational Marshall–Palmer Z–R relation. Correcting for all of these effects has a large positive impact on the radar-derived precipitation estimates and yields a good match between radar QPE and gauge measurements, with a difference of 5–8 %. This shows the potential of radar as a tool for rainfall estimation, especially at close ranges, but also underlines the importance of applying radar correction methods as individual errors can have a large detrimental impact on the QPE performance of the radar.

scholarly journals Close-range radar rainfall estimation and error analysis

2016 ◽  
Author(s):  
Remco van de Beek ◽  
Hidde Leijnse ◽  
Pieter Hazenberg ◽  
Remko Uijlenhoet
Keyword(s):  
Positive Impact ◽  
Rain Gauge ◽  
Minor Role ◽  
Rainfall Estimation ◽  
Radar Rainfall ◽  
Sources Of Error ◽  
Ground Clutter ◽  
Received Power ◽  
Radar Calibration ◽  
Many Sources

Abstract. Quantitative precipitation estimation (QPE) using ground-based weather radar is affected by many sources of error. The most important of these are 1) radar calibration, 2) ground clutter, 3) wet radome attenuation, 4) rain induced attenuation, 5) vertical profile of reflectivity, 6) non-uniform beam filling, and 7) variations in rain drop size distribution (DSD). This study presents an attempt to separate and quantify these sources of error in flat terrain very close to the radar (1–2 km), where 4), 5), and 6) only play a minor role. A 3-day rainfall event (25–27 August 2010) that produced more than 50 mm of precipitation in De Bilt, The Netherlands is analyzed using radar, rain gauge, and disdrometer data. Without any correction it is found that the radar severely underestimates the total rain amount (by more than 50 %). The calibration of the radar receiver is operationally monitored by analyzing the received power from the sun. This turns out to cause a 1 dB of underestimation. The operational clutter filter applied by KNMI is found to incorrectly identify precipitation as clutter, especially at near-zero Doppler velocities. An alternative simple clutter removal scheme using a clear sky clutter map improves the rainfall estimation slightly. To investigate the effect of wet radome attenuation, stable returns from buildings close to the radar are analyzed. It is shown that this may have caused an underestimation of up to 4 dB. Finally, a disdrometer is used to derive event and intra-event specific Z-R relations due to variations in the observed DSDs. Such variations may result in errors when applying the operational Marshall-Palmer Z-R relation. Correcting for all of these effects has a large positive impact on the radar derived precipitation estimates and yields a good match between radar QPE and gauge measurements, with a difference of 5 to 8 %. This shows the potential of radar as a tool for rainfall estimation, especially at close ranges, but also underlines the importance of applying radar correction methods as individual errors can have a large detrimental impact on the QPE performance of the radar.

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>

scholarly journals Use of Ground Clutter to Monitor Polarimetric Radar Calibration

2012 ◽  
Vol 29 (2) ◽  
pp. 159-176 ◽  
Author(s):  
L. Borowska ◽  
D. Zrnic
Keyword(s):  
Environmental Factors ◽  
Heavy Precipitation ◽  
Cold Season ◽  
Polarimetric Radar ◽  
Operational Monitoring ◽  
Ground Clutter ◽  
X Band ◽  
Hot Days ◽  
Radar Calibration ◽  
Differential Reflectivity

Abstract It is suggested that urban ground clutter can have a role in monitoring calibration of reflectivity factor ZH and differential reflectivity ZDR on polarimetric radars. The median and average values of these variables are considered. Analysis of data from 1 month of cold season in Germany (X-band radar) and 3.5 hot days in Oklahoma (S-band radar) is presented. In the presence of up to moderate rain or snow a reflectivity threshold suffices for separating significant clutter from precipitation observed with an X-band radar. The same threshold was suitable on observations with an S-band radar in Oklahoma because heavy precipitation was not present. The tests suggest the scheme is worthy considering for operational monitoring of ZH as its median values at both locations were within the quantization interval of 0.5 dB. Environmental factors that can influence reflectivities from clutter are examined. The effects on ZDR can be significant. These are quantified in the data and possible uses for calibration and monitoring radar status are indicated.

scholarly journals Point-Based Rainfall Intensity Information System in Mt. Merapi Area by X-Band Radar

2019 ◽  
Vol 14 (1) ◽  
pp. 80-89 ◽  
Author(s):  
Santosa Sandy Putra ◽  
Banata Wachid Ridwan ◽  
Kazuki Yamanoi ◽  
Makoto Shimomura ◽  
Sulistiyani ◽  
...  
Keyword(s):  
Satellite Data ◽  
Early Warning Systems ◽  
Radar Data ◽  
Rain Gauge ◽  
Data Grid ◽  
Rainfall Data ◽  
Rainfall Events ◽  
Rain Gauge Data ◽  
X Band ◽  
Gauge Data

An X-band radar was installed in 2014 at Merapi Museum, Yogyakarta, Indonesia, to monitor pyroclastic and rainfall events around Mt. Merapi. This research aims to perform a reliability analysis of the point extracted rainfall data from the aforementioned newly installed radar to improve the performance of the warning system in the future. The radar data was compared with the monitored rain gauge data from Balai Sabo and the IMERG satellite data from NASA and JAXA (The Integrated Multi-satellitE Retrievals for GPM), which had not been done before. All of the rainfall data was compared on an hourly interval. The comparisons were conducted based on 11 locations that correspond to the ground rainfall measurement stations. The locations of the rain gauges are spread around Mt. Merapi area. The point rainfall information was extracted from the radar data grid and the satellite data grid, which were compared with the rain gauge data. The data were then calibrated and adjusted up to the optimum state. Based on January 2017–March 2018 data, it was obtained that the optimum state has a NSF value of 0.41 and R2value of 0.56. As a result, it was determined that the radar can capture around 79% of the hourly rainfall occurrence around Mt. Merapi area during the chosen calibration period, in comparison with the rain gauge data. The radar was also able to capture nearby 40–50% of the heavy rainfall events that pose risks of lahar. In contrast, the radar data performance in detecting drizzling and light rain types were quite precise (55% of cases), although the satellite data could detect slightly better (60% of cases). These results indicate that the radar sensitivity in detecting the extreme rainfall events must receive higher priority in future developments, especially for applications to the existing Mt. Merapi lahar early warning systems.

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