scholarly journals Real-Time Calibration and Monitoring of Radar Reflectivity on Nationwide Dual-Polarization Weather Radar Network

2021 ◽  
Vol 13 (15) ◽  
pp. 2936
Author(s):  
Jeong-Eun Lee ◽  
Soohyun Kwon ◽  
Sung-Hwa Jung
Keyword(s):  
Real Time ◽  
Weather Forecasting ◽  
Weather Radar ◽  
Weather Conditions ◽  
Absolute Calibration ◽  
Dual Polarization ◽  
Ground Clutter ◽  
Radar Systems ◽  
Radar Network ◽  
Time Calibration

Monitoring calibration bias in reflectivity (ZH) in an operational S-band dual-polarization weather radar is the primary requisite for monitoring and prediction (nowcasting) of severe weather and routine weather forecasting using a weather radar network. For this purpose, we combined methods based on self-consistency (SC), ground clutter (GC) monitoring, and intercomparison to monitor the ZH in real time by complementing the limitations of each method. The absolute calibration bias can be calculated based on the SC between dual-polarimetric observations. Unfortunately, because SC is valid for rain echoes, it is impossible to monitor reflectivity during the non-precipitation period. GC monitoring is an alternative method for monitoring changes in calibration bias regardless of weather conditions. The statistics of GC ZH near radar depend on the changes in radar system status, such as antenna pointing and calibration bias. The change in GC ZH relative to the baseline was defined as the relative calibration adjustment (RCA). The calibration bias was estimated from the change in RCA, which was similar to that estimated from the SC. The ZH in the overlapping volume of adjacent radars was compared to verify the homogeneity of ZH over the radar network after applying the calibration bias estimated from the SC. The mean bias between two radars was approximately 0.0 dB after correcting calibration bias. We can conclude that the combined method makes it possible to use radar measurements, which are immune to calibration bias, and to diagnose malfunctioning radar systems as soon as possible.

scholarly journals A Radar Radial Velocity Dealiasing Algorithm for Radar Data Assimilation and its Evaluation with Observations from Multiple Radar Networks

2019 ◽  
Vol 11 (20) ◽  
pp. 2457
Author(s):  
Guangxin He ◽  
Juanzhen Sun ◽  
Zhuming Ying ◽  
Lejian Zhang
Keyword(s):  
Data Assimilation ◽  
Radial Velocity ◽  
Weather Forecasting ◽  
Weather Radar ◽  
Weather Conditions ◽  
Radar Data ◽  
Next Generation ◽  
Radar Network ◽  
Numerical Weather Forecasting ◽  
Radar Data Assimilation

Automated and accurate radar dealiasing algorithms are very important for their assimilation into operational numerical weather forecasting models. A radar radial velocity dealiasing algorithm aimed at radar data assimilation is introduced and assessed using from several S-band and C-band radar observations under the severe weather conditions of hurricanes, typhoons, and deep continental convection in this paper. This dealiasing algorithm, named automated dealiasing for data assimilation (ADDA), is a further development of the dealiasing algorithm named the China radar network (CINRAD) improved dealiasing algorithm (CIDA), originally developed for China’s CINRAD (China Next Generation Weather Radar) radar network. The improved scheme contains five modules employed to remove noisy data, select the suitable first radial, preserve the convective regions, execute multipass dealiasing in both azimuthal and radial directions and conduct the final local dealiasing with an error check. This new dealiasing algorithm was applied to two hurricane cases, two typhoon cases, and three intense-convection cases that were observed from the CINRAD of China, Taiwan‘s radar network, and NEXRAD (Next Generation Weather Radar) of the U.S. with a continuous period of more than 12 h for each case. The dealiasing results demonstrated that ADDA performed better than CIDA for all selected cases. This algorithm not only produced a high success rate for the S-band radar, but also a reasonable performance for the C-band radar.

scholarly journals Bayesian Echo Classification for Australian Single-Polarization Weather Radar with Application to Assimilation of Radial Velocity Observations

2015 ◽  
Vol 32 (7) ◽  
pp. 1341-1355 ◽  
Author(s):  
S. J. Rennie ◽  
M. Curtis ◽  
J. Peter ◽  
A. W. Seed ◽  
P. J. Steinle ◽  
...  
Keyword(s):  
Weather Radar ◽  
Training Data ◽  
Training Dataset ◽  
Bayes Classifier ◽  
Threshold Method ◽  
Ground Clutter ◽  
Radar Network ◽  
Routine Monitoring ◽  
Single Polarization ◽  
Anomalous Propagation

AbstractThe Australian Bureau of Meteorology’s operational weather radar network comprises a heterogeneous radar collection covering diverse geography and climate. A naïve Bayes classifier has been developed to identify a range of common echo types observed with these radars. The success of the classifier has been evaluated against its training dataset and by routine monitoring. The training data indicate that more than 90% of precipitation may be identified correctly. The echo types most difficult to distinguish from rainfall are smoke, chaff, and anomalous propagation ground and sea clutter. Their impact depends on their climatological frequency. Small quantities of frequently misclassified persistent echo (like permanent ground clutter or insects) can also cause quality control issues. The Bayes classifier is demonstrated to perform better than a simple threshold method, particularly for reducing misclassification of clutter as precipitation. However, the result depends on finding a balance between excluding precipitation and including erroneous echo. Unlike many single-polarization classifiers that are only intended to extract precipitation echo, the Bayes classifier also discriminates types of nonprecipitation echo. Therefore, the classifier provides the means to utilize clear air echo for applications like data assimilation, and the class information will permit separate data handling of different echo types.

Research on X-Band Weather Radar Network Based on Sensor Grid

2012 ◽  
Vol 468-471 ◽  
pp. 1274-1277
Author(s):  
Chen Li
Keyword(s):  
Weather Radar ◽  
Key Technology ◽  
Radar Systems ◽  
Radar Network ◽  
Additional Equipment ◽  
X Band ◽  
Architectural Framework ◽  
Information Advantage ◽  
New Generation ◽  
Network Advantage

Monitoring of precipitation using X-band weather radar systems is becoming popular. X-band weather radar network, as an additional equipment of China new generation weather radar, primarily used to measure weather echo within 3km above the ground and has a high prospect. The network, based on sensor grid, is greater information advantage and network advantage. This paper describes the design, the key technology and implementation of an architectural framework of the weather radar network based on sensor grid. The results show that the network works robustly in real time.

scholarly journals Detection of Ground Clutter from Weather Radar Using a Dual-Polarization and Dual-Scan Method

Atmosphere ◽  
2016 ◽  
Vol 7 (6) ◽  
pp. 83 ◽  
Author(s):  
Mohammad-Hossein Golbon-Haghighi ◽  
Guifu Zhang ◽  
Yinguang Li ◽  
Richard Doviak
Keyword(s):  
Weather Radar ◽  
Dual Polarization ◽  
Ground Clutter

An Optimization Method for Economical Ship-Routing and Ship Operation Considering the Effect of Wind-Assisted Rotors

2020 ◽  
Author(s):  
Wenyu Sun ◽  
Xiyang Liu ◽  
Li Yang
Keyword(s):  
Real Time ◽  
Weather Forecasting ◽  
Weather Conditions ◽  
Optimization Method ◽  
Optimization Strategy ◽  
Fuel Cost ◽  
Ship Routing ◽  
The Real ◽  
Critical Issues ◽  
Ship Route

Abstract With the increasingly strict regulations for energy saving and emission reduction technology of ships, minimizing fuel cost is one of the most critical issues in the design and operation of merchant ships. A method to reduce the fuel cost for merchant ship is to select an economical route based on the real-time meteorological environment and weather forecasting data. So far, numerous ship routing strategies have been proposed with the development of weather routing system. More recently, many wind-assisted devices like rotors, wind sails, etc. have been investigated and designed to utilize the renewable wind energy. With the equipment of wind-assisted rotors, the optimization of ship route becomes more important because the effect of this wind-assisted device highly depends on the local wind field along the ship route. In this paper, an improved optimization strategy with the combination of the A* algorithm and a realtime optimizer has been proposed to determinate the optimal ship route and ship operations including ship heading, propeller’s rpm and rotor’s rpm. The real-time information for the weather conditions, ocean climate and sea states are obtained from European Center for Medium-range Weather Forecasts and the ship performance is evaluated by data-driven models. Finally, the proposed method was applied to test cases of ships operating in Pacific route and Indian Ocean route and the results show that the total fuel consumption could be reduced compared to the minimum distance route.

scholarly journals Calibration Accuracy of the Dual-Polarization Receivers of the C-Band Swiss Weather Radar Network

Atmosphere ◽  
2016 ◽  
Vol 7 (6) ◽  
pp. 76 ◽  
Author(s):  
Marco Gabella ◽  
Marco Boscacci ◽  
Maurizio Sartori ◽  
Urs Germann
Keyword(s):  
Weather Radar ◽  
Dual Polarization ◽  
Radar Network ◽  
Calibration Accuracy

scholarly journals RadarNet-Sur First Weather Radar Network in Tropical High Mountains

2017 ◽  
Vol 98 (6) ◽  
pp. 1235-1254 ◽  
Author(s):  
Jörg Bendix ◽  
Andreas Fries ◽  
Jorge Zárate ◽  
Katja Trachte ◽  
Rütger Rollenbeck ◽  
...  
Keyword(s):  
El Niño ◽  
Weather Forecasting ◽  
El Nino ◽  
Weather Radar ◽  
Cost Effective ◽  
Radar Signal ◽  
High Mountains ◽  
Radar Network ◽  
X Band ◽  
Southern Ecuador

Abstract Weather radar networks are indispensable tools for forecasting and disaster prevention in industrialized countries. However, they are far less common in the countries of South America, which frequently suffer from an underdeveloped network of meteorological stations. To address this problem in southern Ecuador, this article presents a novel radar network using cost-effective, single-polarization, X-band technology: the RadarNet-Sur. The RadarNet-Sur network is based on three scanning X-band weather radar units that cover approximately 87,000 km2 of southern Ecuador. Several instruments, including five optical disdrometers and two vertically aligned K-band Doppler radar profilers, are used to properly (inter) calibrate the radars. Radar signal processing is a major issue in the high mountains of Ecuador because cost-effective radar technologies typically lack Doppler capabilities. Thus, special procedures were developed for clutter detection and beam blockage correction by integrating ground-based and satelliteborne measurements. To demonstrate practical applications, a map of areas frequently affected by intense rainfall is presented, based on a time series of one radar that has been in operation since 2002. Such information is of vital importance to, for example, infrastructure management because rain-driven landslides are a major issue for road maintenance and safety throughout Ecuador. The presented case study of exceptionally strong rain events during the recent El Niño in March 2015 highlights the system’s practicality in weather forecasting related to disaster management. For the first time, RadarNet-Sur warrants a spatial-explicit observation of El Niño-related heavy precipitation in a transect from the coast to the highlands in a spatial resolution of 500 m.

scholarly journals Coupling X-band dual-polarized mini-radars and hydro-meteorological forecast models: the HYDRORAD project

2013 ◽  
Vol 13 (5) ◽  
pp. 1229-1241 ◽  
Author(s):  
E. Picciotti ◽  
F. S. Marzano ◽  
E. N. Anagnostou ◽  
J. Kalogiros ◽  
Y. Fessas ◽  
...  
Keyword(s):  
Decision Support ◽  
High Frequency ◽  
Weather Radar ◽  
Decision Support Tool ◽  
Dual Polarization ◽  
Radar Observations ◽  
Support Tool ◽  
Radar Network ◽  
X Band ◽  
Modelling System

Abstract. Hydro-meteorological hazards like convective outbreaks leading to torrential rain and floods are among the most critical environmental issues world-wide. In that context weather radar observations have proven to be very useful in providing information on the spatial distribution of rainfall that can support early warning of floods. However, quantitative precipitation estimation by radar is subjected to many limitations and uncertainties. The use of dual-polarization at high frequency (i.e. X-band) has proven particularly useful for mitigating some of the limitation of operational systems, by exploiting the benefit of easiness to transport and deploy and the high spatial and temporal resolution achievable at small antenna sizes. New developments on X-band dual-polarization technology in recent years have received the interest of scientific and operational communities in these systems. New enterprises are focusing on the advancement of cost-efficient mini-radar network technology, based on high-frequency (mainly X-band) and low-power weather radar systems for weather monitoring and hydro-meteorological forecasting. Within the above context, the main objective of the HYDRORAD project was the development of an innovative \\mbox{integrated} decision support tool for weather monitoring and hydro-meteorological applications. The integrated system tool is based on a polarimetric X-band mini-radar network which is the core of the decision support tool, a novel radar products generator and a hydro-meteorological forecast modelling system that ingests mini-radar rainfall products to forecast precipitation and floods. The radar products generator includes algorithms for attenuation correction, hydrometeor classification, a vertical profile reflectivity correction, a new polarimetric rainfall estimators developed for mini-radar observations, and short-term nowcasting of convective cells. The hydro-meteorological modelling system includes the Mesoscale Model 5 (MM5) and the Army Corps of Engineers Hydrologic Engineering Center hydrologic and hydraulic modelling chain. The characteristics of this tool make it ideal to support flood monitoring and forecasting within urban environment and small-scale basins. Preliminary results, carried out during a field campaign in Moldova, showed that the mini-radar based hydro-meteorological forecasting system can constitute a suitable solution for local flood warning and civil flood protection applications.

scholarly journals Monitoring the differential reflectivity and receiver calibration of the German polarimetric weather radar network

2020 ◽  
Vol 13 (3) ◽  
pp. 1051-1069 ◽  
Author(s):  
Michael Frech ◽  
John Hubbert
Keyword(s):  
Temperature Sensitivity ◽  
Weather Radar ◽  
Calibration Procedure ◽  
Low Noise ◽  
Antenna Gain ◽  
Dual Polarization ◽  
Target Uncertainty ◽  
Temperature Range ◽  
Radar Network ◽  
Differential Reflectivity

Abstract. It is a challenge to calibrate differential reflectivity ZDR to within 0.1–0.2 dB uncertainty for dual-polarization weather radars that operate 24∕7 throughout the year. During operations, a temperature sensitivity of ZDR larger than 0.2 dB over a temperature range of 10 ∘C has been noted. In order to understand the source of the observed ZDR temperature sensitivity, over 2000 dedicated solar box scans, two-dimensional scans of 5∘ azimuth by 8∘ elevation that encompass the solar disk, were made in 2018 from which horizontal (H) and vertical (V) pseudo antenna patterns are calculated. This assessment is carried out using data from the Hohenpeißenberg research radar which is identical to the 17 operational radar systems of the German Meteorological Service (Deutscher Wetterdienst, DWD). ZDR antenna patterns are calculated from the H and V patterns which reveal that the ZDR bias is temperature dependent, changing about 0.2 dB over a 12 ∘C temperature range. One-point-calibration results, where a test signal is injected into the antenna cross-guide coupler outside the receiver box or into the low-noise amplifiers (LNAs), reveal only a very weak differential temperature sensitivity (<0.02 dB) of the receiver electronics. Thus, the observed temperature sensitivity is attributed to the antenna assembly. This is in agreement with the NCAR (National Center for Atmospheric Research) S-Pol (S-band polarimetric radar) system, where the primary ZDR temperature sensitivity is also related to the antenna assembly (Hubbert, 2017). Solar power measurements from a Canadian calibration observatory are used to compute the antenna gain and to validate the results with the operational DWD monitoring results. The derived gain values agree very well with the gain estimate of the antenna manufacturer. The antenna gain shows a quasi-linear dependence on temperature with different slopes for the H and V channels. There is a 0.6 dB decrease in gain for a 10 ∘C temperature increase, which directly relates to a bias in the radar reflectivity factor Z which has not been not accounted for previously. The operational methods used to monitor and calibrate ZDR for the polarimetric DWD C-band weather radar network are discussed. The prime sources for calibrating and monitoring ZDR are birdbath scans, which are executed every 5 min, and the analysis of solar spikes that occur during operational scanning. Using an automated ZDR calibration procedure on a diurnal timescale, we are able to keep ZDR bias within the target uncertainty of ±0.1 dB. This is demonstrated for data from the DWD radar network comprising over 87 years of cumulative dual-polarization radar operations.

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