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

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.

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

Atmospheric Measurement Techniques ◽

10.5194/amt-7-4151-2014 ◽

2014 ◽

Vol 7 (12) ◽

pp. 4151-4166 ◽

Cited By ~ 20

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.

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Multi-year 100-metre-scale urban precipitation study based on X-band radar observations

10.5194/ems2021-326 ◽

2021 ◽

Author(s):

Finn Burgemeister ◽

Marco Clemens ◽

Felix Ament

Keyword(s):

Urban Areas ◽

Measurement Errors ◽

Low Cost ◽

Elevation Angle ◽

Weather Radar ◽

Local Area ◽

Hourly Precipitation ◽

Precipitation Climatology ◽

X Band ◽

Precipitation Characteristics

An operational, single-polarized X-band weather radar monitors precipitation within a 20 km scan radius around Hamburg&#8217;s city center for almost eight years. This weather radar operates at an elevation angle (~3.5&#176;) with a high temporal (30 s), range (60 m), and sampling (1&#176;) resolution refining observations of the German nationwide C-band radars. Studies on short time periods (several months and case studies) proofs the performance of this low-cost local area weather radar. The synergy of observations of the X-band radar, vertically pointing micro rain radars, and rain gauges yields a reliable eight-year precipitation climatology with 100 m resolution. The two guiding questions of this presentation are: Is the variability of this precipitation climatology representative and not contaminated by measurement errors? Which sub-hourly precipitation characteristics can we infer from this precipitation climatology?Several sources of radar-based errors were adjusted gradually affecting the precipitation estimate, e.g. the radar calibration, alignment, attenuation, noise, non-meteorologial echoes. Additionally, statistical relations (k-Z and Z-R relation) increase the uncertainty of the precipitation estimate. However, the deployment of additional vertically pointing micro rain radars yields drop size distributions at relevant heights, which increases the data quality effectively and assesses the statistics of the long-term precipitation observations. The resulting climatology allows studies on the spatial and temporal scale of urban precipitation. We outline the performance of the climatology, present first results on sub-hourly precipitation characteristics and discuss open issues and limitations.This multi-year urban precipitation analysis is groundwork for further hydrological research in an urban area within the project Sustainable Adaption Scenarios for Urban Areas &#8211; Water from Four Sides of the Cluster of Excellence Climate Climatic Change, and Society (CliCCS). Future urban precipitation studies will be improved by the extension of networked observations with a second X-band weather radar site and additional micro rain radars in Hamburg measuring since the beginning of 2021.

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X-Band local area weather radar – preliminary calibration results

Water Science & Technology ◽

10.2166/wst.2002.0038 ◽

2002 ◽

Vol 45 (2) ◽

pp. 135-138 ◽

Cited By ~ 15

Author(s):

N.E. Jensen

Keyword(s):

High Resolution ◽

Weather Radar ◽

Cost Effective ◽

Local Area ◽

Rain Gauges ◽

X Band ◽

Danish Meteorological Institute ◽

Typical Range ◽

Meteorological Institute ◽

Good Calibration

DHI has developed a cost-effective X-Band Local Area Weather Radar (LAWR) with a typical range (radius) of 60 km, 500 × 500 m areal resolution and 253 reflection levels. The development is performed in a co-operation with a number of European partners, including Danish Meteorological Institute. The specifications of the weather radar and preliminary results from the calibration are presented. Good calibration results have been obtained using high-resolution rain gauges.

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

10.5194/egusphere-egu2020-9299 ◽

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

The University of Hamburg operates a single-polarized X-band weather radar to investigate small scale precipitation in Hamburg&#8217;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&#176; 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?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.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.

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A downscaling framework for precipitation nowcasting by merging radar retrievals at different scales and resolutions

10.5194/egusphere-egu21-11062 ◽

2021 ◽

Author(s):

Roberto Deidda ◽

Stefano Farris ◽

Maria Grazia Badas ◽

Marino Marrocu ◽

Luca Massidda ◽

...

Keyword(s):

High Resolution ◽

Prediction Models ◽

Spatial Scales ◽

Weather Prediction ◽

Weather Radar ◽

Early Warning Systems ◽

Small Scale ◽

Time Step ◽

Radar Network ◽

X Band

Convective rainfall events represent one of the most critical issues in urban areas, where numerical weather prediction models are affected by a large uncertainty related to the short temporal and spatial scales involved, thus making early warning systems ineffective. Conversely, radar-based nowcasting models may be a useful tool to guarantee short-term forecasts, through the extrapolation of most recent properties in observed precipitation fields, for lead times ranging from minutes to few hours.In this study we develop a procedure for merging relevant information from two radar products with different resolutions and scales: (i) high-resolution observations retrieved by an X-band weather radar in a small domain (the metropolitan area of Cagliari, located in Sardinia, Italy), and (ii) the mosaic data provided by the Italian Civil Protection national radar network (the whole region of Sardinia). Specifically, we here adapt some STEPS procedures to merge the large-scale advection from the latter radar network, and the small-scale statistical properties for the former X-band weather radar. We thus combine the corresponding forecasts preserving the higher resolution scale. In details, for each time step we (i) evaluate the power spectra of the two forecasts (ii) merge the two spectra taking the power of the large (small) frequencies from the high (low) resolution data spectrum and (iii) achieve optimal downscaling by reconstructing the high-resolution nowcast from the blend of the two spectra.

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Precipitation and microphysical studies with a low cost high resolution X-band radar: an innovative project prospective

Advances in Geosciences ◽

10.5194/adgeo-20-25-2009 ◽

2009 ◽

Vol 20 ◽

pp. 25-32 ◽

Cited By ~ 6

Author(s):

J. Van Baelen ◽

Y. Pointin ◽

W. Wobrock ◽

A. Flossmann ◽

G. Peters ◽

...

Keyword(s):

High Resolution ◽

Low Cost ◽

Ground Truth ◽

Local Area ◽

Size Spectrum ◽

Catchment Basin ◽

Small Catchment ◽

Innovative Project ◽

Model Studies ◽

X Band

Abstract. This paper describes an innovative project which has just been launched at the "Laboratoire de Météorologie Physique" (LaMP) in Clermont-Ferrand in collaboration with the "Meteorologische Institut" in Hamburg, where a low cost X-band high resolution precipitation radar is combined with supporting measurements and a bin microphysical cloud resolving model in order to develop adapted Z–R relationships for accurate rain rate estimates over a local area such as a small catchment basin, an urban complex or even an agriculture domain. In particular, the use of K-band micro rain radars which can retrieve vertical profiles of drop size distribution and the associated reflectivity will be used to perform direct comparisons with X-band radar volume samples while a network of rain-gauges provides ground truth to which our rain estimates will be compared. Thus, the experimental suite of instrumentation should provide a detailed characterization of the various rain regimes and their associated Z–R relationship. Furthermore, we will make use of the hilly environment of the radar to test the use of novel attenuation methods in order to estimate rainfall rates. A second important aspect of this work is to use the detailed cloud modeling available at LaMP. Simulations of precipitating clouds in highly resolved 3-D dynamics model allow predicting the spectra of rain drops and precipitating ice particles. Radar reflectivity determined from these model studies will be compared with the observations in order to better understand which raindrop size spectrum shape factor should be applied to the radar algorithms as a function of the type of precipitating cloud. Likewise, these comparisons between the modeled and the observed reflectivity will also give us the opportunity to further improve our model microphysics and the parameterizations for meso-scale models.

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A low-cost, human-like, high-resolution, tactile sensor based on optical fibers and an image sensor

International Journal of Advanced Robotic Systems ◽

10.1177/1729881418783631 ◽

2018 ◽

Vol 15 (4) ◽

pp. 172988141878363 ◽

Cited By ~ 2

Author(s):

Utku Büyükşahin ◽

Ahmet Kırlı

Keyword(s):

High Resolution ◽

Spatial Resolution ◽

Fiber Optic ◽

Low Cost ◽

Experimental Studies ◽

Main Idea ◽

Tactile Sensor ◽

Image Sensor ◽

Sensor Design ◽

Tactile Sensors

Tactile sensors are commonly a coordinated group of receptors forming a matrix array meant to measure force or pressure similar to the human skin. Optic-based tactile sensors are flexible, sensitive, and fast; however, the human fingertip’s spatial resolution, which can be regarded as the desired spatial resolution, still could not be reached because of their bulky nature. This article proposes a novel and patented optic-based tactile sensor design, in which fiber optic cables are used to increase the number of sensory receptors per square centimeter. The proposed human-like high-resolution tactile sensor design is based on simple optics and image processing techniques, and it enables high spatial resolution and easy data acquisition at low cost. This design proposes using the change in the intesity of the light occured due to the deformation on contact/measurement surface. The main idea is using fiber optic cables as the afferents of the human physiology which can have 9 µm diameters for both delivering and receiving light beams. The variation of the light intensity enters sequent mathematical models as the input, then, the displacement, the force, and the pressure data are evaluated as the outputs. A prototype tactile sensor is manufactured with 1-mm spatial and 0.61-kPa pressure measurement resolution with 0–15.6 N/cm2 at 30 Hz sampling frequency. Experimental studies with different scenarios are conducted to demonstrate how this state-of-the-art design worked and to evaluate its performance. The overall accuracy of the first prototype, based on different scenarios, is calculated as 93%. This performance is regarded as promising for further developments and applications such as grasp control or haptics.

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Stand-alone low-cost sensor network in the inner city of Munich for modeling urban air pollutants

10.5194/egusphere-egu21-15182 ◽

2021 ◽

Author(s):

Adrian Wenzel ◽

Jia Chen ◽

Florian Dietrich ◽

Sebastian T. Thekkekara ◽

Daniel Zollitsch ◽

...

Keyword(s):

Air Quality ◽

High Resolution ◽

Sensor Network ◽

Air Pollutants ◽

Low Cost ◽

Air Pollutant ◽

Sensor Nodes ◽

Sensor Data ◽

Small Scale ◽

Urban Air

Modeling urban air pollutants is a challenging task not only due to the complicated, small-scale topography but also due to the complex chemical processes within the chemical regime of a city. Nitrogen oxides (NOx), particulate matter (PM) and other tracer gases, e.g. formaldehyde, hold information about which chemical regime is present in a city. As we are going to test and apply chemical models for urban pollution &#8211; especially with respect to spatial and temporally variability &#8211; measurement data with high spatial and temporal resolution are critical.Since governmental monitoring stations of air pollutants such as PM, NOx, ozone (O3) or carbon monoxide (CO) are large and costly, they are usually only sparsely distributed throughout a city. Hence, the official monitoring sites are not sufficient to investigate whether small-scale variability and its integrated effects are captured well by models. Smart networks consisting of small low-cost air pollutant sensors have the ability to provide the required grid density and are therefore the tool of choice when it comes to setting up or validating urban modeling frameworks. Such sensor networks have been established and run by several groups, achieving spatial and temporal high-resolution concentration maps [1, 2].After having conducted a measurement campaign in 2016 to create a high-resolution NO2 concentration map for Munich [3], we are currently setting up a low-cost sensor network to measure NOx, PM, O3 and CO concentrations as well as meteorological parameters [4]. The sensors are stand-alone, so that they do not demand mains supply, which gives us a high flexibility in their deployment. Validating air quality models not only requires dense but also high-accuracy measurements. Therefore, we will calibrate our sensor nodes on a weekly basis using a mobile reference instrument and apply the gathered sensor data to a Machine Learning model of the sensor nodes. This will help minimize the often occurring drawbacks of low-cost sensors such as sensor drift, environmental influences and sensor cross sensitivities.&#160;[1] Bigi, A., Mueller, M., Grange, S. K., Ghermandi, G., and Hueglin, C.: Performance of NO, NO2 low cost sensors and three calibration approaches within a real world application, Atmos. Meas. Tech., 11, 3717&#8211;3735, https://doi.org/10.5194/amt-11-3717-2018, 2018[2] Kim, J., Shusterman, A. A., Lieschke, K. J., Newman, C., and Cohen, R. C.: The BErkeley Atmospheric CO2 Observation Network: field calibration and evaluation of low-cost air quality sensors, Atmos. Meas. Tech., 11, 1937&#8211;1946, https://doi.org/10.5194/amt-11-1937-2018, 2018[3] Zhu, Y., Chen, J., Bi, X., Kuhlmann, G., Chan, K. L., Dietrich, F., Brunner, D., Ye, S., and Wenig, M.: Spatial and temporal representativeness of point measurements for nitrogen dioxide pollution levels in cities, Atmos. Chem. Phys., 20, 13241&#8211;13251, https://doi.org/10.5194/acp-20-13241-2020, 2020[4] Zollitsch, D., Chen, J., Dietrich, F., Voggenreiter, B., Setili, L., and Wenig, M.: Low-Cost Air Quality Sensor Network in Munich, EGU General Assembly 2020, Online, 4&#8211;8 May 2020, EGU2020-19276, https://doi.org/10.5194/egusphere-egu2020-19276, 2020

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X-band compact low cost multi-channel radar prototype for short range high resolution 3D-InISAR

2014 11th European Radar Conference ◽

10.1109/eurad.2014.6991231 ◽

2014 ◽

Cited By ~ 7

Author(s):

Stefano Lischi ◽

Riccardo Massini ◽

Daniele Stagliano ◽

Luca Musetti ◽

Fabrizio Berizzi ◽

...

Keyword(s):

High Resolution ◽

Short Range ◽

Low Cost ◽

X Band

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Incorporating emergency management needs in the development of weather radar networks

Journal of Emergency Management ◽

10.5055/jem.2009.0086 ◽

2009 ◽

Vol 7 (1) ◽

pp. 45 ◽

Cited By ~ 3

Author(s):

Ellen J. Bass, PhD ◽

Leigh Baumgart, MS ◽

Brenda Philips, MBA ◽

Kevin Kloesel, PhD ◽

Kathleen Dougherty, MA ◽

...

Keyword(s):

High Resolution ◽

Emergency Management ◽

Low Cost ◽

High Resolution Data ◽

Product Usage ◽

Adaptive Sensing ◽

Emergency Managers ◽

Radar Networks ◽

Network Concept ◽

Resolution Data

The Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) is developing networks of lowpower, low-cost radars that adaptively collect, process, and visualize high-resolution data in the lowest portion of the atmosphere. CASA researchers are working with emergency managers (EM) to ensure that the network concept is designed with EMs’ needs in mind. Interviews, surveys, analysis of product usage logs, and simulated scenarios are being used to solicit EM input. Results indicate the need for products for both high- and low-bandwidth end users, visualizations for velocity products that are more easily interpreted, and enhanced training. CASA researchers are developing interventions to address these needs.

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