Array Weather Radar (AWR) is a novel type weather radar equipped with a distributed phased array technology. As a new instrument with new technology, the AWR offers very high spatiotemporal resolution that enables detection of the fine-scale flow fie...
X-band dual-polarization phased-array weather radars (X-PARs) have been used in South China extensively. Eliminating the attenuation and system bias of X-band radar data is the key to utilizing the advantage of X-PAR networks. In this paper, the disd...
Ground clutter persists as residual stationary or recurrent echo in gridded reflectivity-only weather radar products, then is converted into spurious light rainfall when reflectivity is mapped to rain rate. This study presents an image-level quality...
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 netw...
Weather radars play a crucial role in the monitoring of severe convective weather. However, due to their limited detection range, they cannot conduct an effective monitoring in remote offshore areas. Therefore, this paper utilized UNet++ to establish...
Short-term quantitative precipitation forecast is a challenging topic in meteorology, as the number of severe meteorological phenomena is increasing in most regions of the world. Weather radar data is of utmost importance to meteorologists for issuin...
The study aims to develop vertical radar reflectivity profiles based on lightning density data from the Geostationary Lightning Mapper (GLM) on the GOES-16 satellite in the subtropical region of Brazil. The primary objective is to improve the assimil...
Weather radars are essential in the Quantitative Precipitation Estimates (QPE) but are susceptible to calibration errors. Previous work demonstrated that observations from the Ku-band Dual Polarization Radar (DPR) radar on board the Global Precipitat...
Weather radar reflectivity plays a critical role in precipitation estimation and convective storm identification. However, due to terrain limitations and the uneven spatial distribution of radar stations, oceanic regions have long suffered from a lac...
In this study, a method capable of simultaneously extrapolating the position, shape, and intensity of weather radar echoes is proposed. As the method is an improved version of the previously proposed nonlinear grid transformation (NGT) method, it is...
Modeled statistical differential reflectivity–reflectivity (i.e., ZDR–Ze) correspondences for no bright-band warm rain and stratiform bright-band rain are evaluated using measurements from an operational polarimetric weather radar and ind...
This work evaluates and compares the performance of the radar reflectivity and lightning data assimilation schemes implemented in weather research and forecasting-four-dimensional data assimilation (WRF-FDDA) for short-term precipitation and lightnin...
This research work focuses on the development and application of a storm-tracking algorithm for identifying and tracking storm cells. The algorithm first identifies storm cells on the basis of reflectivity thresholds and then matches the cells in the...
Cloud seeding is a targeted weather modification strategy aimed at enhancing precipitation, particularly in regions facing water scarcity. This study evaluates the impacts of wintertime cloud seeding events in the western United States, focusing on t...
Hail events commonly affect the Western part of Catalonia, producing damage mainly in the agricultural sector. Comparison of the weather radar data with hail pad registers at ground level allows for the diagnosis of hail severity. However, limitation...
Radar reflectivity (RR) greater than 35 dBZ usually indicates the presence of severe convective weather, which affects a variety of human activities, including aviation. However, RR data are scarce, especially in regions with poor radar coverage or s...
Quantitative precipitation estimation (QPE) through remote sensing has to take rain microstructure into consideration, because it influences the relationship between radar reflectivity Z and rain intensity R. For this reason, separate equations are u...
Forest fire risk is rising with climate warming, highlighting the need for timely monitoring and early warning. Satellite-based monitoring, currently a primary tool in remote sensing for fire detection, suffers from spatiotemporal gaps due to limited...
Convective storms represent a dangerous atmospheric phenomenon, particularly for the heavy and concentrated precipitation they can trigger. Given their high velocity and variability, their prediction is challenging, though it is crucial to issue reli...
The modern era of polarimetric radar begins with radiowave propagation research starting in the early 1970s with applications to measurement and modeling of wave attenuation in rain and depolarization due to ice particles along satellite–earth...
Strong updrafts occur in severe thunderstorms, causing the overshooting tops, an increase in the total lightning activity, and generating a frozen drops nucleus that will produce severe weather when it collapses. The Echo Top is a measurement of the...
In this study, the relationship between radar reflectivity and rain rate (Z–R) was investigated. The analysis was conducted using data collected by the OTT Parsivel1 disdrometer during the periods 2012–2014 and 2019–2025 in Warsaw,...
Rain properties vary spatially and temporally for several reasons. In particular, rain types (convective and stratiform) affect the rain drop size distribution (DSD). It has also been established that local weather conditions are influenced by large-...
The accuracy of weather radar-measured products, such as reflectivity, plays a crucial factor in obtaining good quality, derived remote sensing products, such as hydrometeor classification. A slight mismatch of a few decibels in reflectivity may caus...
Ground-based weather radars are essential to better understand precipitation systems, to improve the Quantitative Precipitation Estimation (QPE), and to subsequently provide input to hydrological models. However, reflectivity measured by radars is ty...
This study developed a real-time rainfall forecasting system that can predict rainfall in a particular area a few hours before a typhoon’s arrival. The reflectivity of nine elevation angles obtained from the volume coverage pattern 21 Doppler radar s...
The echo of weather radar is seriously disturbed by clear-air turbulence echo (CAT) which needs identifying and eliminating to improve the data quality of weather radar. Using the data observed with the five X-band dual polarimetric radars in Changpi...
Dual-band weather radar networks enable complementary multi-radar observations, improving the accuracy, three-dimensional characterization, and early warning capability for severe convective weather. S-band radar provides strong penetration and long...
This study, conducted in the framework of the LIAISE field campaign in NE Spain (May–September 2021), investigates how near-surface relative humidity influences early-stage rainfall characteristics when precipitation is most affected by tempera...
In this study, a polarimetric radar forward model operator was developed for the Weather Research and Forecasting (WRF) model that was based on a scattering algorithm using the T-matrix methodology. Three microphysics schemes—Thompson, Morrison...
Rain attenuation can hinder the implementation of quantitative precipitation estimations using X-band weather radar. Numerous studies have been conducted on correcting the attenuation of radar reflectivity by utilizing a dual-polarimetric radar and a...
Weather radars commonly suffer from the data-missing problem that limits their data quality and applications. Traditional methods for the completion of weather radar missing data, which are based on radar physics and statistics, have shown defects in...
The purpose of this study was to develop an optimal estimation model for rainfall rate retrievals using radar reflectivity, thereby gaining an effective grasp of rainfall information for disaster prevention uses. A process was designed for evaluating...
A polarimetric radar method to estimate mean shapes of ice hydrometeors was applied to several snowfall and ice cloud events observed by operational and research weather radars. The hydrometeor shape information is described in terms of their aspect...
Applications of weather radar data to complex orography are manifold, as are the problems. The difficulties start with the choice of suitable locations for the radar sites and their construction, which often involves long transport routes and harsh w...
Weather radars are commonly used to track the development of convective storms due to their high resolution and accuracy. However, the coverage of existing weather radar is very limited, especially in mountainous and ocean areas. Geostationary meteor...
To address the challenge of rapidly selecting optimal numerical model products for weather forecasting in critical applications such as aviation route planning, this study proposes an enhanced object-based methodology comprising individual object sco...
Hydrometeor classification from dual-polarization weather radar is important for precipitation monitoring, cloud microphysical analysis, and severe weather warnings. However, operational performance remains limited by non-meteorological echoes, incom...
“Bright” scatterers are useful for monitoring modern weather radars. In order to be “bright”, a point target with deterministic backscattering properties should be present at a near range and be hit by the antenna beam axis. I...
A new method is proposed for identifying ground clutter in single-polarization radar data based on the gated recurrent unit (GRU) neural network. This method needs five independent input variables related to radar reflectivity structure, which are th...
Assimilation of weather radar data, as well as additional data like lightning data, in high-resolution weather forecast models is a promising method to improve short-term forecasting (nowcasting) of flash-flood events. A data assimilation system base...
Multi-source radar data fusion has become increasingly vital for advancing weather monitoring and forecasting. However, effectively integrating Doppler radar with an X-band phased-array radar remains challenging. Doppler radar offers only low and inc...
Polarimetric radar data (PRD) have potential to be used in numerical weather prediction (NWP) models to improve convective-scale weather forecasts. However, thus far only a few studies have been undertaken in this research direction. To assimilate PR...
It is commonly believed that clear-air echoes detected by weather radars are caused by atmobios migration. However, clear-air echoes are sometimes inconsistently related to the activity of living creatures. In some cases, the characteristics of radar...
Tornadoes are severe convective weather exhibiting localized and sudden occurrences. Weather radar is widely regarded as the most effective tool for monitoring tornadoes and issuing early warnings. Dual-polarization updating has significantly improve...
Radar data with high spatiotemporal resolution and automatic weather station (AWS) data are used in the data assimilation experiment to improve the precipitation forecast of a numerical model. The numerical model considered in this study is the Weath...
Quantitative precipitation estimation (QPE) is a fundamental task of hydrometeorological applications, ranging from flash-flood detection to water-resource management. While weather radars offer superior spatial coverage compared with rain gauges, tr...
During extreme events such as tropical cyclones, the precision of sensors used to sample the meteorological data is vital to feed weather and climate models for storm path forecasting, quantitative precipitation estimation, and other atmospheric para...
Weather radar echo is the data detected by the weather radar sensor and reflects the intensity of meteorological targets. Using the technique of radar echo extrapolation, which is the prediction of future echoes based on historical echo observations,...
Precipitation nowcasting can predict and alert for any possibility of abrupt weather changes which may cause both human and material risks. Most of the conventional nowcasting methods extrapolate weather radar echoes, but precipitation nowcasting is...
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