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Precise knowledge of the antenna pointing direction is a key facet to ensure the accuracy of observations from scanning weather radars. The sun is an often-used reference point to aid accurate alignment of weather radar systems and is particularly useful when observed as interference during normal scanning operations. In this study, we combine two online solar interference approaches to determine the pointing accuracy of an X-band mobile weather radar system deployed for 26 months in northern England (54.517°N, 3.615°W). During the deployment, several shifts in the tilt of the radar system are diagnosed between site visits. One extended period of time (>11 months) is shown to have a changing tilt that is independent of human intervention. To verify the corrections derived from this combined approach, quantitative precipitation estimates (QPEs) from the radar system are compared to surface observations: an approach that takes advantage of the variations in the magnitude of partial beam blockage corrections required due to tilting of the radar system close to mountainous terrain. The observed improvements in QPE performance after correction support the use of the derived tilt corrections for further applications using the corrected dataset. Finally, recommendations for future deployments are made, with particular focus on higher latitudes where solar interference spikes show more seasonality than those at mid-latitudes. [ABSTRACT FROM AUTHOR]

In this study, the quantitative precipitation estimation (QPE) capability of three X-band dual-polarization phased array radars (PAR) in Guangzhou, South China, was demonstrated, with an S-band operational dual-polarization radar as the benchmark. Rainfall rate (R) estimators based on the specific differential phase (KDP) for summer precipitation for both X-band and S-band radars were derived from the raindrop size distributions (DSDs) observed by a 2-dimensional video disdrometer (2DVD) in South China. Rainfall estimates from the radars were evaluated with gauge observations in three events, including pre-summer rainfall, typhoon precipitation, and local severe convective precipitation. Observational results showed that radar echoes from the X-band PARs suffered much more severely from attenuation than those from the S-band radar. Compared to S-band observations, the X-band echoes can disappear when the signal-to-noise ratio drops to a certain level due to severe attenuation, resulting in different estimated rainfall areas for X- and S-band radars. The attenuation corrected by KDP had good consistency with S-band observations, but the accuracy of attenuation correction was affected by DSD uncertainty and may vary in different types of precipitation. The QPE results demonstrated that the R(KDP) estimator produced better rainfall accumulations from the X-band PAR observations compared to the S-band observations. For both the X-band and S-band radars, the estimates of hourly accumulated rainfall became more accurate in heavier rainfall, due to the decreases of both the DSD uncertainty and the impact of measurement errors. In the heavy precipitation area, the estimation accuracy of the X-band radar was high, and the overestimation of the S-band radar was obvious. Through the analysis of the ZH-ZDR distribution in the three weather events, it was found that the X-band PAR with the capability of high spatiotemporal observations can capture minute-level changes in the microphysical characteristics, which help improve the estimation accuracy of ground rainfall. [ABSTRACT FROM AUTHOR]

Development of satellite and radar applications has been continuously studied to reach the demand in the recent communication technology. In this study, a new oval-square-shaped split-ring resonator with left-handed metamaterial properties was developed for C-band and X-band applications. The proposed metamaterial was fabricated on 9 × 9 × 0.508 mm3 size of Rogers RO4003C substrate. The proposed metamaterial structure was designed and simulated using Computer Simulation Technique (CST) Microwave Studio with the frequency ranging between 0 to 12 GHz. The simulated result of the proposed design indicated dual resonance frequency at 5.52 GHz (C-band) and 8.81 GHz (X-band). Meanwhile, the experimental result of the proposed design demonstrated dual resonance frequency at 5.53 GHz (C-band) and 8.31 GHz (X-band). Therefore, with a slight difference in the dual resonance frequency, the simulated result corresponded to the experimental result. Additionally, the proposed design exhibited the ideal properties of electromagnetic which is left-handed metamaterial (LHM) behavior. Hence, the metamaterial structure is highly recommended for satellite and radar applications. [ABSTRACT FROM AUTHOR]

An X-band dual-polarization radar (XPRAD) was deployed in Guangdong province as part of the Southern China Monsoon Rainfall Experiment (SCMREX) during the storm season in 2016. This paper presents a comprehensive assessment of XPRAD observations during SCMREX with emphasis on data processing and rainfall products. The differential phase-based attenuation correction and radar calibration using self-consistency of dual-polarization observables are presented. It is found that the standard deviation of the Zdr bias is less than 0.2 dB based on 'light rain at low angle' and 'dry aggregate snow' observations. Cross-comparison with two standard S-band China New Generation Weather Radars (CINRAD) shows that the bias of Zh has a mean value less than 1.5 dBZ and a standard deviation less than 0.5 dBZ. In addition, fifteen rainfall events that occurred during the intensive observing period (IOP) are analyzed to demonstrate the rainfall estimation performance of XPRAD. In particular, rainfall accumulations at 1-, 2- and 3-h scales derived using R(Kdp) and R(Zh, Zdr) relations are evaluated using national level rain gauge data and CINRAD-based rainfall estimation. The results show that both R(Kdp)- and R(Zh, Zdr)-based products agree well with the rain gauge observations and CINRAD estimation. The difference between R(Kdp) and R(Zh, Zdr) is not significant, although R(Kdp) shows slightly better performance than R(Zh, Zdr). [ABSTRACT FROM AUTHOR]

Phased array technology features rapid and directional scanning and has become a promising approach for remote sensing and wireless communication. In addition, element-level digitization has increased the feasibility of complicated signal processing and simultaneous multi-beamforming processes. However, the high cost and bulky characteristics of beam-steering systems have prevented their extensive application. In this paper, an X-band element-level digital phased array radar utilizing fully integrated complementary metal-oxide-semiconductor (CMOS) transceivers is proposed for achieving a low-cost and compact-size digital beamforming system. An 8–10 GHz transceiver system-on-chip (SoC) fabricated in 65 nm CMOS technology offers baseband filtering, frequency translation, and global clock synchronization through the proposed periodic pulse injection technique. A 16-element subarray module with an SoC integration, antenna-in-package, and tile array configuration achieves digital beamforming, back-end computing, and dc–dc conversion with a size of 317 × 149 × 74.6 mm3. A radar demonstrator with scalable subarray modules simultaneously realizes range sensing and azimuth recognition for pulsed radar configurations. Captured by the suggested software-defined pulsed radar, a complete range–azimuth figure with a 1 km maximum observation range can be displayed within 150 ms under the current implementation. [ABSTRACT FROM AUTHOR]

This paper presents a new configuration of a slotted waveguide antenna (SWA) array aimed at the X-band within the desired band of 9.38~9.44 GHz for shipboard marine radars. The SWA array, which typically consists of a slotted waveguide, a polarizing filter, and a metal reflector, is widely employed in marine radar applications. Nonetheless, conventional slot array designs are weighty, mechanically complex, and geometrically large to obtain high performances, such as gain. These features of the conventional SWA are undesirable for the shipboard marine radar, where the antenna rotates at high angular speed for the beam scanning mechanism. The proposed SWA array herein reduces the conventional design's size by 62% using a tapered dielectric-inset guide structure. It shows high gain performance (up to 30 dB) and obtains improvements in radiation efficiency (up to 80% in the numerical simulations) and weight due to the use of loss and low-density dielectric material. [ABSTRACT FROM AUTHOR]

Discharge forecasting is a key component for early warning systems and extremely useful for decision makers. Forecasting models require accurate rainfall estimations of high spatial resolution and other geomorphological characteristics of the catchment, which are rarely available in remote mountain regions such as the Andean highlands. While radar data is available in some mountain areas, the absence of a well distributed rain gauge network makes it hard to obtain accurate rainfall maps. Thus, this study explored a Random Forest model and its ability to leverage native radar data (i.e., reflectivity) by providing a simplified but efficient discharge forecasting model for a representative mountain catchment in the southern Andes of Ecuador. This model was compared with another that used as input derived radar rainfall (i.e., rainfall depth), obtained after the transformation from reflectivity to rainfall rate by using a local Z-R relation and a rain gauge-based bias adjustment. In addition, the influence of a soil moisture proxy was evaluated. Radar and runoff data from April 2015 to June 2017 were used. Results showed that (i) model performance was similar by using either native or derived radar data as inputs (0.66 < NSE < 0.75; 0.72 < KGE < 0.78). Thus, exhaustive pre-processing for obtaining radar rainfall estimates can be avoided for discharge forecasting. (ii) Soil moisture representation as input of the model did not significantly improve model performance (i.e., NSE increased from 0.66 to 0.68). Finally, this native radar data-based model constitutes a promising alternative for discharge forecasting in remote mountain regions where ground monitoring is scarce and hardly available. [ABSTRACT FROM AUTHOR]

Despite many efforts of the radar community, quantitative precipitation estimation (QPE) from weather radar data remains a challenging topic. The high resolution of X-band radar imagery in space and time comes with an intricate correction process of reflectivity. The steep and high mountain topography of the Andes enhances its complexity. This study aims to optimize the rainfall derivation of the highest X-band radar in the world (4450 m a.s.l.) by using a random forest (RF) model and single Plan Position Indicator (PPI) scans. The performance of the RF model was evaluated in comparison with the traditional step-wise approach by using both, the Marshall-Palmer and a site-specific Z–R relationship. Since rain gauge networks are frequently unevenly distributed and hardly available at real time in mountain regions, bias adjustment was neglected. Results showed an improvement in the step-wise approach by using the site-specific (instead of the Marshall-Palmer) Z–R relationship. However, both models highly underestimate the rainfall rate (correlation coefficient < 0.69; slope up to 12). Contrary, the RF model greatly outperformed the step-wise approach in all testing locations and on different rainfall events (correlation coefficient up to 0.83; slope = 1.04). The results are promising and unveil a different approach to overcome the high attenuation issues inherent to X-band radars. [ABSTRACT FROM AUTHOR]