Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
7.9
5.0
Journals
Remote Sensing
Special Issues
Advance of Radar Meteorology and Hydrology
remotesensing-logo
Submit to Remote Sensing Review for Remote Sensing Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Advance of Radar Meteorology and Hydrology

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Atmospheric Remote Sensing".

Deadline for manuscript submissions: closed (31 July 2022) | Viewed by 23585

Special Issue Editors

Dr. Sanghun Lim

E-Mail Website
Guest Editor
Korea Institute of Civil Engineering and Building Technology, Goyang-si, Republic of Korea
Interests: radar meteorology/hydrology; precipitation microphysics; precipitation identification and quantitative precipitation estimation
Special Issues, Collections and Topics in MDPI journals
Dr. Shaik Allabakash

E-Mail Website
Co-Guest Editor
Korea Institute of Civil Engineering and Building Technology, Korea
Interests: cloud microphysics and precipitation study; dynamics of atmospheric boundary layer; radar meteorology; radar signal processing

Special Issue Information

Dear Colleagues,

Tremendous advances have been made in the last 30 years in the science, technology, and engineering of radars. With the development of radar technologies such as multiple polarization, multiple wavelength, and network sensing, the radar has become a widely used tool in meteorological and hydrological applications. Radar can provide the information needed for weather systems, weather forecasting, flood warning, and climate surveys.
The goal of this Special Issue is to share the recent advances in radar meteorology and hydrology. Topics of interest include but are not limited to the following:

  • New radar system concept for precipitation observation
  • Advances in radar signal processing and quality control
  • Cloud and precipitation microphysics
  • Remote sensing precipitation measurement
  • Radar meteorological and hydrological applications
  • Remote sensing applications in climatology

Dr. Sanghun Lim
Dr. Shaik Allabakash
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Related Special Issue

Published Papers (10 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

Jump to: Other

23 pages, 7959 KiB  
Article
The Characteristics of Raindrop Size Distribution at Windward and Leeward Side over Mountain Area
by Hyeon-Joon Kim, Woonseon Jung, Sung-Ho Suh, Dong-In Lee and Cheol-Hwan You
Remote Sens. 2022, 14(10), 2419; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14102419 - 18 May 2022
Cited by 11 | Viewed by 1875
Abstract
To analyze the difference in the microphysical development characteristics of orographic rainfall, several Parsivel disdrometers were installed along the windward and leeward slope of a mountain. There were differences in the raindrop size distribution according to the difference in height and distance from [...] Read more.
To analyze the difference in the microphysical development characteristics of orographic rainfall, several Parsivel disdrometers were installed along the windward and leeward slope of a mountain. There were differences in the raindrop size distribution according to the difference in height and distance from the center of the mountain. In low-altitude coastal areas and adjacent areas, the number concentration of raindrops smaller than 1 mm was relatively lower than in mountainous areas, and the rain rate increased with the growth in the size of the raindrops. On the other hand, a higher rain rate was observed as the number concentration of raindrops smaller than 1 mm increased in the hillside area. The increase in the number concentration of small raindrops was evident at the LCL (lifting condensation level) altitude. The main factors affecting the increase in the rain rate on the windward and leeward slopes were the concentration of raindrops and the growth of raindrops, which showed regional differences. As a result of a PCA (principal component analysis), it was found that raindrop development by vapor deposition and weak convection were the main rainfall development characteristics on the windward and leeward slopes, respectively. The difference in regional precipitation development characteristics in mountainous areas affects the parameters of the rainfall estimation relational expression. This means that the rainfall relation calculated through the disdrometer observation data observed in a specific mountainous area can cause spatial and quantitative errors. Full article
(This article belongs to the Special Issue Advance of Radar Meteorology and Hydrology)
►▼ Show Figures

Graphical abstract

18 pages, 7971 KiB  
Article
The Quantile-Matching Approach to Improving Radar Quantitative Precipitation Estimation in South China
by Linye Song, Shangfeng Chen, Yun Li, Duo Qi, Jiankun Wu, Mingxuan Chen and Weihua Cao
Remote Sens. 2021, 13(23), 4956; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13234956 - 06 Dec 2021
Cited by 1 | Viewed by 2153
Abstract
Weather radar provides regional rainfall information with a very high spatial and temporal resolution. Because the radar data suffer from errors from various sources, an accurate quantitative precipitation estimation (QPE) from a weather radar system is crucial for meteorological forecasts and hydrological applications. [...] Read more.
Weather radar provides regional rainfall information with a very high spatial and temporal resolution. Because the radar data suffer from errors from various sources, an accurate quantitative precipitation estimation (QPE) from a weather radar system is crucial for meteorological forecasts and hydrological applications. In the South China region, multiple weather radar networks are widely used, but the accuracy of radar QPE products remains to be analyzed and improved. Based on hourly radar QPE and rain gauge observation data, this study first analyzed the QPE error in South China and then applied the Quantile Matching (Q-matching) method to improve the radar QPE accuracy. The results show that the rainfall intensity of the radar QPE is generally larger than that determined from rain gauge observations but that it usually underestimates the intensity of the observed heavy rainfall. After the Q-matching method was applied to correct the QPE, the accuracy improved by a significant amount and was in good agreement with the rain gauge observations. Specifically, the Q-matching method was able to reduce the QPE error from 39–44%, demonstrating performance that is much better than that of the traditional climatological scaling method, which was shown to be able to reduce the QPE error from 3–15% in South China. Moreover, after the Q-matching correction, the QPE values were closer to the rainfall values that were observed from the automatic weather stations in terms of having a smaller mean absolute error and a higher correlation coefficient. Therefore, the Q-matching method can improve the QPE accuracy as well as estimate the surface precipitation better. This method provides a promising prospect for radar QPE in the study region. Full article
(This article belongs to the Special Issue Advance of Radar Meteorology and Hydrology)
►▼ Show Figures

Figure 1

19 pages, 6106 KiB  
Article
Raindrop Size Distributions of North Indian Ocean Tropical Cyclones Observed at the Coastal and Inland Stations in South India
by Balaji Kumar Seela, Jayalakshmi Janapati, Chirikandath Kalath Unnikrishnan, Pay-Liam Lin, Jui Le Loh, Wei-Yu Chang, Utpal Kumar, K. Krishna Reddy, Dong-In Lee and Mannem Venkatrami Reddy
Remote Sens. 2021, 13(16), 3178; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13163178 - 11 Aug 2021
Cited by 14 | Viewed by 3292
Abstract
The current study summarizes the raindrop size distributions (RSDs) characteristic of the North Indian Ocean (NIO) tropical cyclones (TCs) measured with ground-based disdrometers installed at the coastal (Thiruvananthapuram, 8.5335°N, 76.9047°E) and inland (Kadapa, 14.4742°N, 78.7098°E) stations in south India. The NIO TCs observed [...] Read more.
The current study summarizes the raindrop size distributions (RSDs) characteristic of the North Indian Ocean (NIO) tropical cyclones (TCs) measured with ground-based disdrometers installed at the coastal (Thiruvananthapuram, 8.5335°N, 76.9047°E) and inland (Kadapa, 14.4742°N, 78.7098°E) stations in south India. The NIO TCs observed at the coastal station showed more mid- and large-size drops (>1 mm) than the inland station. On the other hand, for both inland and coastal stations, small and mid-size drops (<3 mm) primarily contributed to the total number concentration and rainfall rate. The RSDs of the NIO TCs segregated into precipitation types (stratiform and convective) demonstrated the presence of more mid- and large-size drops at the coastal station. The RSD relations of the NIO TCs, which are used in rain retrieval algorithms of remote sensing (global precipitation measurement) radars, exhibited contrasts between the coastal and inland station. Further, the NIO TCs’ rainfall kinetic energy relations, which are crucial in rainfall erosivity studies, estimated for the coastal station revealed dissimilar characteristics to that of the inland station. The conceivable thermo-dynamical and microphysical processes that are accountable for the disparities in the NIO TCs RSDs measured at the coastal and inland stations are also elucidated in this work. Full article
(This article belongs to the Special Issue Advance of Radar Meteorology and Hydrology)
►▼ Show Figures

Graphical abstract

17 pages, 9724 KiB  
Article
Real-Time Calibration and Monitoring of Radar Reflectivity on Nationwide Dual-Polarization Weather Radar Network
by Jeong-Eun Lee, Soohyun Kwon and Sung-Hwa Jung
Remote Sens. 2021, 13(15), 2936; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13152936 - 26 Jul 2021
Cited by 7 | Viewed by 2564
Abstract
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Advance of Radar Meteorology and Hydrology)
►▼ Show Figures

Figure 1

23 pages, 6668 KiB  
Article
Microphysical Characteristics of Rainfall Observed by a 2DVD Disdrometer during Different Seasons in Beijing, China
by Li Luo, Jia Guo, Haonan Chen, Meilin Yang, Mingxuan Chen, Hui Xiao, Jianli Ma and Siteng Li
Remote Sens. 2021, 13(12), 2303; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13122303 - 12 Jun 2021
Cited by 10 | Viewed by 2266
Abstract
The seasonal variations of raindrop size distribution (DSD) and rainfall are investigated using three-year (2016–2018) observations from a two-dimensional video disdrometer (2DVD) located at a suburban station (40.13° N, 116.62° E, ~30 m AMSL) in Beijing, China. The annual distribution of rainfall presents [...] Read more.
The seasonal variations of raindrop size distribution (DSD) and rainfall are investigated using three-year (2016–2018) observations from a two-dimensional video disdrometer (2DVD) located at a suburban station (40.13° N, 116.62° E, ~30 m AMSL) in Beijing, China. The annual distribution of rainfall presents a unimodal distribution with a peak in summer with total rainfall of 966.6 mm, followed by fall. Rain rate (R), mass-weighted mean diameter (Dm), and raindrop concentration (Nt) are stratified into six regimes to study their seasonal variation and relative rainfall contribution to the total seasonal rainfall. Heavy drizzle/light rain (R2: 0.2~2.5 mm h−1) has the maximum occurrence frequency throughout the year, while the total rainfall in summer is primarily from heavy rain (R4: 10~50 mm h−1). The rainfall for all seasons is contributed primarily from small raindrops (Dm2: 1.0~2.0 mm). The distribution of occurrence frequency of Nt and the relative rainfall contribution exhibit similar behavior during four seasons with Nt of 10~1000 m−3 registering the maximum occurrence and rainfall contributions. Rainfall in Beijing is dominated by stratiform rain (SR) throughout the year. There is no convective rainfall (CR) in winter, i.e., it occurs most often during summer. DSD of SR has minor seasonal differences, but varies significantly in CR. The mean values of log10Nw (Nw: mm−1m−3, the generalized intercept parameter) and Dm of CR indicate that the CR during spring and fall in Beijing is neither continental nor maritime, at the same time, the CR in summer is close to the maritime-like cluster. The radar reflectivity (Z) and rain rate (?) relationship (Z = ?R?) showed seasonal differences, but were close to the standard NEXRAD Z-R relationship in summer. The shape of raindrops observed from 2DVD was more spherical than the shape obtained from previous experiments, and the effect of different axis ratio relations on polarimetric radar measurements was investigated through T-matrix-based scattering simulations. Full article
(This article belongs to the Special Issue Advance of Radar Meteorology and Hydrology)
►▼ Show Figures

Graphical abstract

21 pages, 7659 KiB  
Article
Estimation of Liquid Fraction of Wet Snow by Using 2-D Video Disdrometer and S-Band Weather Radar
by Sung-Ho Suh, Hong-Il Kim, Eun-Ho Choi and Cheol-Hwan You
Remote Sens. 2021, 13(10), 1901; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13101901 - 13 May 2021
Cited by 1 | Viewed by 1806
Abstract
Wet snow may cause significant damage to humans and property, and thus, it is necessary to estimate the corresponding liquid fraction (FL). Consequently, the FL of wet snow was estimated using a novel technique; specifically, the particle shape irregularity (Ir) [...] Read more.
Wet snow may cause significant damage to humans and property, and thus, it is necessary to estimate the corresponding liquid fraction (FL). Consequently, the FL of wet snow was estimated using a novel technique; specifically, the particle shape irregularity (Ir) was estimated through the particle coordinate information obtained using 2-D video disdrometer (2DVD) measurements. Moreover, the possibility of quantitively estimating FL via Ir, based on the temperature (T), was examined. Eight snowfall cases from 2014 to 2016 were observed through a 2DVD installed in Jincheon, South Korea, to analyze the dominant properties of physical variables of snowflakes (i.e., the terminal velocity (VT), particle density (ρs), Ir, and FL) and the corresponding relationships according to the T ranges (−4.5 < T (°C) < 2.5) in which wet snow can occur. It was clarified that the volume-equivalent particle diameter (D)–FL and D–Ir relationships depended on T, and a relationship existed between Ir and FL. The analysis results were verified using the Yong-In Testbed (YIT) S-band weather radar and T-matrix scattering simulation. The D–FL relationship was implemented in the scattering simulation, and the results indicated that the simulated reflectivity (ZS) was highly correlated with the observed reflectivity (ZO) under all T classes. These features can provide a basis for radar analysis and quantitative snowfall estimation for wet snow with various FL values. Full article
(This article belongs to the Special Issue Advance of Radar Meteorology and Hydrology)
►▼ Show Figures

Graphical abstract

17 pages, 20256 KiB  
Article
Clutter Elimination Algorithm for Non-Precipitation Echo of Radar Data Considering Meteorological and Observational Properties in Polarimetric Measurements
by Young-A Oh, Hae-Lim Kim and Mi-Kyung Suk
Remote Sens. 2020, 12(22), 3790; https://0-doi-org.brum.beds.ac.uk/10.3390/rs12223790 - 18 Nov 2020
Cited by 7 | Viewed by 2388
Abstract
Non-precipitation echoes due to ground and sea clutter, chaff, anomalous propagation, biological targets, and interference in weather radar observations are major issues causing a decline in the accuracy of meteorological and hydrological applications based on radar data. Statistically based quality control techniques using [...] Read more.
Non-precipitation echoes due to ground and sea clutter, chaff, anomalous propagation, biological targets, and interference in weather radar observations are major issues causing a decline in the accuracy of meteorological and hydrological applications based on radar data. Statistically based quality control techniques using polarimetric variables have improved the accuracy of radar echo classification, however their performance is affected by attenuation, nonuniform beam filling, and hydrometeor diversity as well as terrain blockage, beam broadening, and noise correction issues due to the quality degradation of polarimetric measurements. To address this, a new quality control algorithm, named clutter elimination algorithm for non-precipitation echo of radar data (CLEANER), was designed by employing independent feature parameters and variable classification conditions with spatial and temporal observation environments to adapt to these meteorological artifacts and observational limitations. CLEANER was applied to several precipitation cases with various non-precipitation echoes, showing improved performance compared with results from the fuzzy logic-based quality control algorithm in terms of non-precipitation echo removal as well as in precipitation echo conservation. In addition, CLEANER shows better computational efficiency and robustness, as well as an excellent expandability for different radar networks. Full article
(This article belongs to the Special Issue Advance of Radar Meteorology and Hydrology)
►▼ Show Figures

Figure 1

14 pages, 9656 KiB  
Article
A Novel Electromagnetic Wave Rain Gauge and its Average Rainfall Estimation Method
by S. Lim
Remote Sens. 2020, 12(21), 3528; https://0-doi-org.brum.beds.ac.uk/10.3390/rs12213528 - 28 Oct 2020
Viewed by 1844
Abstract
It is essential to accurately estimate rainfall to predict and prevent hydrological disasters such as floods. In this paper, an electromagnetic wave rain gauge system and a method to estimate average rainfall using the system’s multiple elevation observation data are presented. The compact [...] Read more.
It is essential to accurately estimate rainfall to predict and prevent hydrological disasters such as floods. In this paper, an electromagnetic wave rain gauge system and a method to estimate average rainfall using the system’s multiple elevation observation data are presented. The compact electromagnetic wave rain gauge is a small-sized radar that performs very short-range observations using K-band dual-polarization technology. The method to estimate average rainfall is based on the concept of an average observation derived from multiple elevation scans with very short range and dual-polarization information. The proposed method was evaluated by comparing it with ground instruments, including a pit-gauge, tipping-bucket rain gauges, and a Parsivel disdrometer. The evaluation results demonstrated that the new methodology worked fairly well for various rainfall events. Full article
(This article belongs to the Special Issue Advance of Radar Meteorology and Hydrology)
►▼ Show Figures

Graphical abstract

Other

Jump to: Research

17 pages, 10299 KiB  
Technical Note
Analyzing the Application of X-Band Radar for Improving Rainfall Observation and Flood Forecasting in Yeongdong, South Korea
by Seong-Sim Yoon and Sang-Hun Lim
Remote Sens. 2022, 14(1), 43; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14010043 - 23 Dec 2021
Cited by 4 | Viewed by 2458
Abstract
The mountainous Yeongdong region of South Korea contains mountains over 1 km. Owing to this topographic blockage, the region has a low-density rain-gauge network, and there is a low-altitude (~1.5 km) observation gap with the nearest large S-band radar. The Korean government installed [...] Read more.
The mountainous Yeongdong region of South Korea contains mountains over 1 km. Owing to this topographic blockage, the region has a low-density rain-gauge network, and there is a low-altitude (~1.5 km) observation gap with the nearest large S-band radar. The Korean government installed an X-band dual-polarization radar in 2019 to improve rainfall observations and to prevent hydrological disasters in the Yeongdong region. The present study analyzed rainfall estimates using the newly installed X-band radar to evaluate its hydrological applicability. The rainfall was estimated using a distributed specific differential phase-based technique for a high-resolution 75 m grid. Comparison of the rainfall estimates of the X-band radar and the existing rainfall information showed that the X-band radar was less likely to underestimate rainfall compared to the S-band radar. The accuracy was particularly high within a 10 km observation radius. To evaluate the hydrological applicability of X-band radar rainfall estimates, this study developed a rain-based flood forecasting method—the flow nomograph—for the Samcheok-osib stream, which is vulnerable to heavy rain and resultant floods. This graph represents the flood risk level determined by hydrological–hydraulic modeling with various rainfall scenarios. Rainfall information (X-band radar, S-band radar, ground rain gauge) was applied as input to the flow nomograph to predict the flood level of the stream. Only the X-band radar could accurately predict the actual high-risk increase in the water level for all studied rainfall events. Full article
(This article belongs to the Special Issue Advance of Radar Meteorology and Hydrology)
►▼ Show Figures

Figure 1

12 pages, 1276 KiB  
Technical Note
On the Spectral and Polarimetric Signatures of a Bright Scatterer before and after Hardware Replacement
by Marco Gabella
Remote Sens. 2021, 13(5), 919; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13050919 - 01 Mar 2021
Cited by 3 | Viewed by 1209
Abstract
A previous study has used the stable and peculiar echoes backscattered by a single “bright scatterer” (BS) during five winter days to characterize the hardware of C-band, the dual-polarization radar located at Monte Lema (1625 m altitude) in Southern Switzerland. The BS is [...] Read more.
A previous study has used the stable and peculiar echoes backscattered by a single “bright scatterer” (BS) during five winter days to characterize the hardware of C-band, the dual-polarization radar located at Monte Lema (1625 m altitude) in Southern Switzerland. The BS is the 90 m tall metallic tower on Cimetta (1633 m altitude, 18 km range). In this note, the statistics of the echoes from the BS were derived from other ten dry days with normal propagation conditions in winter 2015 and January 2019. The study confirms that spectral signatures, such as spectrum width, wideband noise and Doppler velocity, were persistently stable. Regarding the polarimetric signatures, the large values (with small dispersion) of the copolar correlation coefficient between horizontal and vertical polarization were also confirmed: the average value was 0.9961 (0.9982) in winter 2015 (January 2019); the daily standard deviations were very small, ranging from 0.0007 to 0.0030. The dispersion of the differential phase shift was also confirmed to be quite small: the daily standard deviation ranged from a minimum of 2.5° to a maximum of 5.3°. Radar reflectivities in both polarizations were typically around 80 dBz and were confirmed to be among the largest values observed in the surveillance volume of the Monte Lema radar. Finally, another recent 5-day data set from January 2020 was analyzed after the replacement of the radar calibration unit that includes low noise amplifiers: these five days show poorer characteristics of the polarimetric signatures and a few outliers affecting the spectral signatures. It was shown that the “historical” polarimetric and spectral signatures of a bright scatterer could represent a benchmark for an in-depth comparison after hardware replacements. Full article
(This article belongs to the Special Issue Advance of Radar Meteorology and Hydrology)
►▼ Show Figures

Graphical abstract

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-10
Back to TopTop