Measurements of ocean wave and current field using dual polarized X-band radar

A new ocean wave and sea surface current monitoring system with horizontally-(HH) and vertically-(VV) polarized X-band radar was developed.Two experiments into the use of the radar system were carried out at two sites,respectively,for calibration process in Zhangzi Island of the Yellow Sea,and for validation in the Yellow Sea and South China Sea.Ocean wave parameters and sea surface current velocities were retrieved from the dual polarized radar image sequences based on an inverse method.The results obtained from dual-polarized radar data sets acquired in Zhangzi Island are compared with those from an ocean directional buoy.The results show that ocean wave parameters and sea surface current velocities retrieved from radar image sets are in a good agreement with those observed by the buoy.In particular,it has been found that the vertically-polarized radar is better than the horizontally-polarized radar in retrieving ocean wave parameters,especially in detecting the significant wave height below 1.0 m.

A new method for the estimation of oceanic mixed-layer depth using shipboard X-band radar images

Shipboard X-band radar images acquired on 24 June 2009 are used to study nonlinear internal wave characteristics in the northeastern South China Sea.The studied images show three nonlinear internal waves in a packet.A method based on the Radon Transform technique is introduced to calculate internal wave parameters such as the direction of propagation and internal wave velocity from backscatter images.Assuming that the ocean is a two-layer finite depth system,we can derive the mixed-layer depth by applying the internal wave velocity to the mixed-layer depth formula.Results show reasonably good agreement with in-situ thermistor chain and conductivity-temperature-depth data sets.

Extraction of internal wave amplitude from nautical X-Band radar observations

One of the most important parameters for oceanic internal waves (IWs) is their amplitude. We have developed a method to retrieve the IW amplitude from nautical X-Band radar images based on the KdV equation for continuous stratified finite depth system. We have also tested the method of measuring the amplitude of IWs from X-Band radar backscatter image sequences acquired on June 2009 in the northeastern South China Sea. The method was applied in several radar images. Experiments show that the retrieval amplitudes are consistent with the in-situ observational amplitudes of IWs by using the towed thermistor chain and conductivity-temperature-depth (CTD) profile. The uncertainty of the method is also discussed.

Extraction of Sea-State Parameters with an X-Band Radar

Ocean wave spectrum and surface currents can be determined from a series of spatial wave images recorded by an X-band marine radar. In the absence of a surface current, the three-dimensional spectral energy found by using the series of images will be confined to a trajectory defined by the still water dispersion relationship. The presence of a surface current will make the three-dimensional spectral energy show a corresponding Doppler shill which may determine the current using the least squares method and obtain the directional wave spectrum. On the basis of conventional wave spectrum and directional function, the paper emulates a series of X-band radar images considering shadowing modulation and simulates numerically the threedimensional image spectrum both with and without a surface current, calculates the current velocity by virtue of the Doppler shift, and obtains the two-dimensional image spectrum. Finally the paper analyzes measured wave level elevation-a function of time t to obtain one-dimensional image spectrum, and the data comes from an X-band radar in McMaster University.

A novel algorithm for ocean wave direction inversion from X-band radar images based on optical flow method

As one of the important sea state parameters for navigation safety and coastal resource management, the ocean wave direction represents the propagation direction of the wave. A novel algorithm based on an optical flow method is developed for the ocean wave direction inversion of the ocean wave fields imaged by the X-band radar continuously. The proposed algorithm utilizes the echo images received by the X-band wave monitoring radar to estimate the optical flow motion, and then the actual wave propagation direction can be obtained by taking a weighted average of the motion vector for each pixel. Compared with the traditional ocean wave direction inversion method based on frequency-domain, the novel algorithm is fully using a time-domain signal processing method without determination of a current velocity and a modulation transfer function（MTF）. In the meantime,the novel algorithm is simple, efficient and there is no need to do something more complicated here. Compared with traditional ocean wave direction inversion method, the ocean wave direction of derived by using this proposed method matches well with that measured by an in situ buoy nearby and the simulation data. These promising results demonstrate the efficiency and accuracy of the algorithm proposed in the paper.

A curvelet-based method to determine wave directions from nautical X-band radar images

A new method to determine wave directions from nautical X-band images is proposed. The signatures of ocean waves show obvious scale and directional characteristics in nautical X-band radar images. Curvelet transform（CT） possesses very high scale and directional sensitivities. Therefore, it has good capability to analyze ocean wave fields. The radar images are decomposed at different scales, in different directions, and at different positions by CT, and curvelet coefficients are obtained. Given to the scale and directional characteristics of surface waves,the information of ocean waves is centralized in the curvelet coefficients of certain directions and at certain scales.Therefore, the wave orientations can be determined. The 180 ambiguity is removed by calculating crosscorrelation coefficients（CCCs） between continuous collected images. The proposed method is verified by the dataset collected on the Northwest coast of the Zhangzi Island in the Yellow Sea of China from March to April 2009.

Effect of Changes in Sea-Surface State on Statistical Characteristics of Sea Clutter with X-Band Radar

We have made observations of X-band radar sea clutter from the sea surface and sea-surface state in the Uraga Suido Traffic Route, which is used by ships entering and leaving Tokyo Bay, and the nearby Daini Kaiho Sea Fortress. We estimated the distributions of reflected amplitudes due to sea clutter using models that assume Weibull, Log-Weibull, Log-normal, and K-distributions. We then compared the results of estimating these distributions with sea-surface state data to investigate the effects of changes in the sea-surface state on the statistical characteristics of sea clutter. As a result, we showed that observed sub-ranges not containing a target conformed better to the Weibull distribution regardless of Significant Wave Height (SWH). Further, sub-ranges conforming to the Log-Weibull or Log-normal distribution in areas contained a target when the SWH was large, and as SWH decreases, sub-ranges conforming to a Log-normal. We also showed that for observed sub-ranges not containing a target, the shape parameter, c, of both Weibull and Log-Weibull distribution correlated with SWH. The correlation between wave period and shape parameters of Weibull and Log-Weibull distribution showed a weak correlation.

Ocean surface current retrieval and imaging with a new shore-based X-band radar based on time-shifted up-and-down linear frequency modulated signal

This paper proposes a multifunction radar that can not only measure sea currents but also perform sea-surface imaging.The fundamental aspect of the proposed radar comprises transmitting time-shifted up-and-down continuous wave linear frequency modulated signals that allow for the offset of two one-dimensional range images of the sea surface that respectively correspond to the upward linear frequency modulated(LFM)signal and the downward LFM signal.Owing to the Doppler frequency shift from the sea surface,a range offset,which is proportional to the radial velocity of the sea surface,occurs between the upward and downward LFM signals.By using the least-squares linear fitting method in the transformed domain,the range offset can be measured and the current velocity can be retrieved.Finally,we verify the accuracy of current measurement with simulation results.

Characterization and Application of S-Band Polarimetric Radar and X-Band Phased Array Radar for a Tornadic Storm Event on June 16,2022

The X-band phased array radar offers faster scanning speed and higher spatial resolution compared to the S-band radar,making it capable of enhancing tornado monitoring and early warning capabilities.This study analyzed the characteristics and nowcasting signals of a tornado case that occurred on June 16,2022 in the Guangzhou region.Our findings indicate that the violent contraction of rotation radius and the dramatic increase in rotation speed were important signal characteristics associated with tornado formation.The X-band phased array radar,with its high temporal and spatial resolution,provided an opportunity to capture early warning signals from polarimetric characteristics.The X-band phased array radar demonstrated noteworthy ability to identify apparent tornado vortex signature(TVS)features in a 10-minute lead time,surpassing the capabilities of the CINRAD/SA radar.Additionally,due to its higher scanning frequency,the Xband phased-array radar was capable of consistently identifying TVS with shorter intervals,enabling a more precise tracking of the tornado's path.The application of professional radars,in this case,provides valuable insights for the monitoring of evolutions of severe local storms and even tornadoes and the issuance of early warning signals.

Quantitative Precipitation Estimation Using X-band Phased Array Weather Radar

This study utilized data from an X-band phased array weather radar and ground-based rain gauge observations to conduct a quantitative precipitation estimation(QPE)analysis of a heavy rainfall event in Xiong an New Area from 20:00 on August 21 to 07:00 on August 22,2022.The analysis applied the Z-R relationship method for radar-based precipitation estimation and evaluated the QPE algorithm s performance using scatter density plots and binary classification scores.The results indicated that the QPE algorithm accurately estimates light to moderate rainfall but significantly underestimates heavy rainfall.The study identified disparities in the predictive accuracy of the QPE algorithm across various precipitation intensity ranges,offering essential insights for the further refinement of QPE techniques.

APPLICATION OF TWO-DIMENSIONAL WAVELET TRANSFORM IN NEAR-SHORE X-BAND RADAR IMAGES

Among existing remote sensing applications, land-based X-band radar is an effective technique to monitor the wave fields, and spatial wave information could be obtained from the radar images. Two-dimensional Fourier Transform （2-D FT） is the common algorithm to derive the spectra of radar images. However, the wave field in the nearshore area is highly non-homogeneous due to wave refraction, shoaling, and other coastal mechanisms. When applied in nearshore radar images, 2-D FT would lead to ambiguity of wave characteristics in wave number domain. In this article, we introduce two-dimensional Wavelet Transform （2-D WT） to capture the non-homogeneity of wave fields from nearshore radar images. The results show that wave number spectra by 2-D WT at six parallel space locations in the given image clearly present the shoaling of nearshore waves. Wave number of the peak wave energy is increasing along the inshore direction, and dominant direction of the spectra changes from South South West （SSW） to West South West （WSW）. To verify the results of 2-D WT, wave shoaling in radar images is calculated based on dispersion relation. The theoretical calculation results agree with the results of 2-D WT on the whole. The encouraging performance of 2-D WT indicates its strong capability of revealing the non-homogeneity of wave fields in nearshore X-band radar images.

Reduction of rain effect on wave height estimation from marine X-band radar images using unsupervised generative adversarial networks

An intelligent single radar image de-raining method based on unsupervised self-attention generative adversarial networks is proposed to improve the accuracy of wave height parameter inversion results.The method builds a trainable end-to-end de-raining model with an unsupervised cycle-consistent adversarial network as an AI framework,which does not require pairs of rain-contaminated and corresponding ground-truth rain-free images for training.The model is trained by feeding rain-contaminated and clean radar images in an unpaired manner,and the atmospheric scattering model parameters are not required as a prior condition.Additionally,a self-attention mechanism is introduced into the model,allowing it to focus on rain clutter when processing radar images.This combines global and local rain clutter context information to output more accurate and clear de-raining radar images.The proposed method is validated by applying it to actualfield test data,which shows that compared with the wave height derived from the original rain-contaminated data,the root-mean-square error is reduced by 0.11 m and the correlation coefficient of the wave height is increased by 14%using the de-raining method.These results demonstrate that the method effectively reduces the impact of rain on the accuracy of wave height parameter estimation from marine X-band radar images.

Real Time Monitoring of Extreme Rainfall Events with Simple X-Band Mini Weather Radar

Real time rainfall events monitoring is very important for a large number of reasons: Civil Protection, hydrogeological risk management, hydroelectric power purposes, road and traffic regulation, and tourism. Efficient monitoring operations need continuous, high-resolution and large-coverage data. To monitor and observe extreme rainfall events, often much localized over small basins of interest, and that could frequently causing flash floods, an unrealistic extremely dense rain gauge network should be needed. On the other hand, common large C-band or S-band long range radars do not provide the necessary spatial and temporal resolution. Simple short-range X-band mini weather radar can be a valid compromise solution. The present work shows how a single polarization, non-Doppler and non-coherent, simple and low cost X-band radar allowed monitoring three very intense rainfall events occurred near Turin during July 2014. The events, which caused damages and floods, are detected and monitored in real time with a sample rate of 1 minute and a radial spatial resolution of 60 m, thus allowing to describe the intensity of the precipitation on each small portion of territory. This information could be very useful if used by authorities in charge of Civil Protection in order to avoid inconvenience to people and to monitor dangerous situations.

Comparison of the Observation Capability of an X-band Phased-array Radar with an X-band Doppler Radar and S-band Operational Radar

An X-band phased-array meteorological radar （XPAR） was developed in China and will be installed in an airplane to observe precipitation systems for research purposes.In order to examine the observational capability of the XPAR and to test the operating mode and calibration before installation in the airplane,a mobile X-band Doppler radar （XDR） and XPAR were installed at the same site to observe convective precipitation events.Nearby S-band operational radar （SA） data were also collected to examine the reflectivity bias of XPAR.An algorithm for quantitative analysis of reflectivity and velocity differences and radar sensitivity of XPAR is presented.The reflectivity and velocity biases of XPAR are examined with SA and XDR.Reflectivity sensitivities,the horizontal and vertical structures of reflectivity by the three radars are compared and analyzed.The results indicated that while the XPRA with different operating modes can capture the main characteristic of 3D structures of precipitation,and the averaged reflectivity differences between XPAR and XDR,and XDR and SA,were 0.4 dB and 6.6 dB on 13 July and-4.5 dB and 5.1 dB on 2 August 2012,respectively.The minimum observed reflectivities at a range of 50 km for XPAR,XDR and SA were about 15.4 dBZ,13.5 dBZ and-3.5 dBZ,respectively.The bias of velocity between XPAR and XDR was negligible.This study provides a possible method for the quantitative comparison of the XPAR data,as well as the sensitivity of reflectivity,calibration,gain and bias introduced by pulse compression.

Improvement of X-Band Polarization Radar Melting Layer Recognition by the Bayesian Method and ITS Impact on Hydrometeor Classification

Using melting layer(ML)and non-melting layer(NML)data observed with the X-band dual linear polarization Doppler weather radar(X-POL)in Shunyi,Beijing,the reflectivity(ZH),differential reflectivity(ZDR),and correlation coefficient(CC)in the ML and NML are obtained in several stable precipitation processes.The prior probability density distributions(PDDs)of the ZH,ZDR and CC are calculated first,and then the probabilities of ZH,ZDR and CC at each radar gate are determined(PBB in the ML and PNB in the NML)by the Bayesian method.When PBB>PNB the gate belongs to the ML,and when PBB<PNB the gate belongs to the NML.The ML identification results with the Bayesian method are contrasUsing melting layer(ML)and non-melting layer(NML)data observed with the X-band dual linear polarization Doppler weather radar(X-POL)in Shunyi,Beijing,the reflectivity(ZH),differential reflectivity(ZDR),and correlation coefficient(CC)in the ML and NML are obtained in several stable precipitation processes.The prior probability density distributions(PDDs)of the ZH,ZDR and CC are calculated first,and then the probabilities of ZH,ZDR and CC at each radar gate are determined(PBB in the ML and PNB in the NML)by the Bayesian method.When PBB>PNB the gate belongs to the ML,and when PBB<PNB the gate belongs to the NML.The ML identification results with the Bayesian method are contrasted under the conditions of the independent PDDs and joint PDDs of the ZH,ZDR and CC.The results suggest that MLs can be identified effectively,although there are slight differences between the two methods.Because the values of the polarization parameters are similar in light rain and dry snow,it is difficult for the polarization radar to distinguish them.After using the Bayesian method to identify the ML,light rain and dry snow can be effectively separated with the X-POL observed data.ted under the conditions of the independent PDDs and joint PDDs of the ZH,ZDR and CC.The results suggest that MLs can be identified effectively,although there are slight differences between the two methods.Because the values of the polarization parameters are similar in light rain and dry snow,it is difficult for the polarization radar to distinguish them.After using the Bayesian method to identify the ML,light rain and dry snow can be effectively separated with the X-POL observed data.

The measurement of sea surface profile with X-band coherent marine radar

The line-of-sight velocity of scattering facets is related to the Doppler signals of X-band coherent marine radar from the oceanic surface. First, the sign Doppler Estimator is applied to estimate the Doppler shift of each radar resolution cell. And then, in terms of the Doppler shift, a retrieval algorithm extracting the vertical displacement of the sea surface has been proposed. The effects induced by radar look-direction and radar spatial resolution are both taken into account in this retrieval algorithm. The comparison between the sea surface spectrum of buoy data and the retrieved spectrum reveals that the function of the radar spatial resolution is equivalent to a low pass filter, impacting especially the spectrum of short gravity waves. The experimental data collected by McMaster IPIX radar are also used to validate the performance of the retrieval algorithm. The derived significant wave height and wave period are compared with the in situ measurements, and the agreement indicates the practicality of the retrieval technology.

Reliability of X-band Dual-polarization Phased Array Radars Through Comparison with an S-band Dual-polarization Doppler Radar

Based on the observations of a squall line on 11 May 2020 and stratiform precipitation on 6 June 2020 from two X-band dual-polarization phased array weather radars(DP-PAWRs)and an S-band dual-polarization Doppler weather radar(CINRAD/SA-D),the data reliability of DP-PAWR and its ability to detect the fine structures of mesoscale weather systems were assessed.After location matching,the observations of DP-PAWR and CINRAD/SA-D were compared in terms of reflectivity(Z_(H)),radial velocity(V),differential reflectivity(Z_(DR)),and specific differential phase(K_(DP)).The results showed that:(1)DP-PAWR has better ability to detect mesoscale weather systems than CINRAD/SAD;the multi-elevation-angles scanning of the RHI mode enables DP-PAWR to obtain a wider detection range in the vertical direction.(2)DP-PAWR’s Z_(H)and V structures are acceptable,while its sensitivity is worse than that of CINRAD/SA-D.The Z H suffers from attenuation and the Z_(H)area distribution is distorted around strong rainfall regions.(3)DP-PAWR’s Z_(DR)is close to a normal distribution but slightly smaller than that of CINRAD/SA-D.The K_(DP)products of DP-PAWR have much higher sensitivity,showing a better indication of precipitation.(4)DP-PAWR is capable of revealing a detailed and complete structure of the evolution of the whole storm and the characteristics of particle phase variations during the process of triggering and enhancement of a small cell in the front of a squall line,as well as the merging of the cell with the squall line,which cannot be observed by CINRAD/SA-D.With its fast volume scan feature and dual-polarization detection capability,DP-PAWR shows great potential in further understanding the development and evolution mechanisms of meso-γ-scale and microscale weather systems.

X-Band Mini Radar for Observing and Monitoring Rainfall Events

Quantitative precipitation estimation and rainfall monitoring based on meteorological data, potentially provides continuous, high-resolution and large-coverage data, are of high practical use: Think of hydrogeological risk management, hydroelectric power, road and tourism. Both conventional long-range radars and rain-gauges suffer from measurement errors and difficulties in precipitation estimation. For efficient monitoring operation of localized rain events of limited extension and of small basins of interest, an unrealistic extremely dense rain gauge network should be needed. Alternatively C-band or S-band meteorological long range radars are able to monitor rain fields over wide areas, however with not enough space and time resolution, and with high purchase and maintenance costs. Short-range X-band radars for rain monitoring can be a valid compromise solution between the two more common rain measurement and observation instruments. Lots of scientific efforts have already focused on radar-gauge adjustment and quantitative precipitation estimation in order to improve the radar measurement techniques. After some considerations about long range radars and gauge network, this paper presents instead some examples of how X-band mini radars can be very useful for the observation of rainfall events and how they can integrate and supplement long range radars and rain gauge networks. Three case studies are presented: A very localized and intense event, a rainfall event with high temporal and spatial variability and the employ of X-band mini radar in a mountainous region with narrow valleys. The adaptability of such radar devoted to monitor rain is demonstrated.

Application of X-band Polarimetric Phased-array Radars in Quantitative Precipitation Estimation

The performance of different quantitative precipitation estimation(QPE) relationships is examined using the polarimetric variables from the X-band polarimetric phased-array radars in Guangzhou,China.Three QPE approaches,namely,R(ZH),R(ZH,ZDR) and R(KDP),are developed for horizontal reflectivity,differential reflectivity and specific phase shift rate,respectively.The estimation parameters are determined by fitting the relationships to the observed radar variables using the T-matrix method.The QPE relationships were examined using the data of four heavy precipitation events in southern China.The examination shows that the R(ZH) approach performs better for the precipitation rate less than 5 mm h-1, and R(KDP) is better for the rate higher than 5 mm h-1, while R(ZH,ZDR) has the worst performance.An adaptive approach is developed by taking the advantages of both R(ZH) and R(KDP) approaches to improve the QPE accuracy.

Numerical simulation and inversion of offshore area depth based on x-band microwave radar

A detection method of offshore area depth utilizing the x-band microwave radar is proposed. The method is based on the sea clutter imaging mechanism of microwave radar, and combined with dispersion equation of the liner wave theorem and least square method （LSM）, consequently get the inversion results of water depth in the detected region. The wave monitoring system OSMAR-X exploited by the Ocean State Laborato-ry, Wuhan University, based on a microwave radar has proven to be a powerful tool to monitor ocean waves in time and space. Numerical simulation and inversion of offshore area depth are carried out here; since JONSWAP model can give description of stormy waves in different growth phase, it is suitable for simulation. Besides, some results from measured data detected by OSMAR-X x-band radar located at Longhai of Fujian Province, China, validates this method. The tendency of the average water depths inferred from the radar images is in good agreement with the tide level detected by Xiamen tide station. These promising results suggest the possibility of using OSMAR-X to monitor operationally morphodynamics in coastal zones. This method can be applied to both shore-based and shipborne x-band microwave radar.