Study on Quantitative Precipitation Estimation by Polarimetric Radar Using Deep Learning

Accurate radar quantitative precipitation estimation(QPE)plays an essential role in disaster prevention and mitigation.In this paper,two deep learning-based QPE networks including a single-parameter network and a multi-parameter network are designed.Meanwhile,a self-defined loss function(SLF)is proposed during modeling.The dataset includes Shijiazhuang S-band dual polarimetric radar(CINRAD/SAD)data and rain gauge data within the radar’s 100-km detection range during the flood season of 2021 in North China.Considering that the specific propagation phase shift(KDP)has a roughly linear relationship with the precipitation intensity,KDP is set to 0.5°km^(-1 )as a threshold value to divide all the rain data(AR)into a heavy rain(HR)and light rain(LR)dataset.Subsequently,12 deep learning-based QPE models are trained according to the input radar parameters,the precipitation datasets,and whether an SLF was adopted,respectively.The results suggest that the effects of QPE after distinguishing rainfall intensity are better than those without distinguishing,and the effects of using SLF are better than those that used MSE as a loss function.A Z-R relationship and a ZH-KDP-R synthesis method are compared with deep learning-based QPE.The mean relative errors(MRE)of AR models using SLF are improved by 61.90%,51.21%,and 56.34%compared with the Z-R relational method,and by 38.63%,42.55%,and 47.49%compared with the synthesis method.Finally,the models are further evaluated in three precipitation processes,which manifest that the deep learning-based models have significant advantages over the traditional empirical formula methods.

Persymmetric adaptive polarimetric detection of subspace range-spread targets in compound Gaussian sea clutter

This paper focuses on the adaptive detection of range and Doppler dual-spread targets in non-homogeneous and nonGaussian sea clutter.The sea clutter from two polarimetric channels is modeled as a compound-Gaussian model with different parameters,and the target is modeled as a subspace rangespread target model.The persymmetric structure is used to model the clutter covariance matrix,in order to reduce the reliance on secondary data of the designed detectors.Three adaptive polarimetric persymmetric detectors are designed based on the generalized likelihood ratio test(GLRT),Rao test,and Wald test.All the proposed detectors have constant falsealarm rate property with respect to the clutter texture,the speckle covariance matrix.Experimental results on simulated and measured data show that three adaptive detectors outperform the competitors in different clutter environments,and the proposed GLRT detector has the best detection performance under different parameters.

Data-driven polarimetric imaging: a review

This study reviews the recent advances in data-driven polarimetric imaging technologies based on a wide range of practical applications.The widespread international research and activity in polarimetric imaging techniques demonstrate their broad applications and interest.Polarization information is increasingly incorporated into convolutional neural networks(CNN)as a supplemental feature of objects to improve performance in computer vision task applications.Polarimetric imaging and deep learning can extract abundant information to address various challenges.Therefore,this article briefly reviews recent developments in data-driven polarimetric imaging,including polarimetric descattering,3D imaging,reflection removal,target detection,and biomedical imaging.Furthermore,we synthetically analyze the input,datasets,and loss functions and list the existing datasets and loss functions with an evaluation of their advantages and disadvantages.We also highlight the significance of data-driven polarimetric imaging in future research and development.

Microphysical Characteristics of Extreme-Rainfall Convection over the Pearl River Delta Region, South China from Polarimetric Radar Data during the Pre-summer Rainy Season

During the pre-summer rainy season,heavy rainfall occurs frequently in South China.Based on polarimetric radar observations,the microphysical characteristics and processes of convective features associated with extreme rainfall rates(ERCFs)are examined.In the regions with high ERCF occurrence frequency,sub-regional differences are found in the lightning flash rate(LFR)distributions.In the region with higher LFRs,the ERCFs have larger volumes of high reflectivity factor above the freezing level,corresponding to more active riming processes.In addition,these ERCFs are more organized and display larger spatial coverage,which may be related to the stronger low-level wind shear and higher terrain in the region.In the region with lower LFRs,the ERCFs have lower echo tops and lower-echo centroids.However,no clear differences of the most unstable convective available potential energy(MUCAPE)exist in the ERCFs in the regions with different LFR characteristics.Regardless of the LFRs,raindrop collisional coalescence is the main process for the growth of raindrops in the ERCFs.In the ERCFs within the region with lower LFRs,the main mechanism for the rapid increase of liquid water content with decreasing altitude below 4 km is through the warm-rain processes converting cloud drops to raindrops.However,in those with higher LFRs,the liquid water content generally decreases with decreasing altitude.

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.

Shallow sea topography detection using fully Polarimetric Gaofen-3 SAR data based on swell patterns

Compared to single-polarization synthetic aperture radar(SAR)data,fully polarimetric SAR data can provide more detailed information of the sea surface,which is important for applications such as shallow sea topography detection.The Gaofen-3 satellite provides abundant polarimetric SAR data for ocean research.In this paper,a shallow sea topography detection method was proposed based on fully polarimetric Gaofen-3 SAR data.This method considers swell patterns and only requires SAR data and little prior knowledge of the water depth to detect shallow sea topography.Wave tracking was performed based on preprocessed fully polarimetric SAR data,and the water depth was then calculated considering the wave parameters and the linear dispersion relationships.In this paper,four study areas were selected for experiments,and the experimental results indicated that the polarimetric scattering parameterαhad higher detection accuracy than quad-polarization images.The mean relative errors were 14.52%,10.30%,12.56%,and 12.90%,respectively,in the four study areas.In addition,this paper also analyzed the detection ability of this model for different topographies,and the experiments revealed that the topography could be well recognized when the topography gradient is small,the topography gradient direction is close to the wave propagation direction,and the isobath line is regular.

Coastal wind field retrieval from polarimetric synthetic aperture radar

Coastal winds are strongly influenced by topology and discontinuity between land and sea surfaces. Wind assessment from remote sensing in such a complex area remains a challenge. Space-borne scatterometer does not provide any information about the coastal wind field, as the coarse spatial resolution hampers the radar backscattering. Synthetic aperture radar （SAR） with a high spatial resolution and all-weather observation abilities has become one of the most important tools for ocean wind retrieval, especially in the coastal area. Conventional methods of wind field retrieval from SAR, however, require wind direction as initial information, such as the wind direction from numerical weather prediction models （NWP）, which may not match the time of SAR image acquiring. Fortunately, the polarimetric observations of SAR enable independent wind retrieval from SAR images alone. In order to accurately measure coastal wind fields, this paper proposes a new method of using co-polarization backscattering coefficients from polarimetric SAR observations up to polarimetric correlation backscattering coefficients, which are acquired from the conjugate product of co-polarization backscatter and cross-polarization backscatter. Co-polarization backscattering coefficients and polarimetric correlation backscattering coefficients are obtained form Radarsat-2 single-look complex （SLC） data.The maximum likelihood estimation is used to gain the initial results followed by the coarse spatial filtering and fine spatial filtering. Wind direction accuracy of the final inversion results is 10.67 with a wind speed accuracy of 0.32 m/s. Unlike previous methods, the methods described in this article utilize the SAR data itself to obtain the wind vectors and do not need external wind directional information. High spatial resolution and high accuracy are the most important features of the method described herein since the use of full polarimetric observations contains more information about the space measured.This article is a useful addition to the work of independent SAR wind retrieval. The experimental results herein show that it is feasible to employ the co-polarimetric backscattering coefficients and the polarimetric correlation backscattering coefficients for coastal wind field retrieval.

Polarimetric whitening filter for POLSAR image based on subspace decomposition

Speckle filtering is an indispensable pre-processing step for applications of polarimetric synthetic aperture radar （POLSAR）, such as terrain classification, target detection, etc. As one of the most typical methods, the polarimetric whitening filter （PWF） can be used to produce a minimum-speckle image by combining the complex elements of the scattering matrix, but polarimetric information is lost after the filtering process. A polarimetric filter based on subspaze decomposition which was proposed by Cu et al specializes in retrieving principle scattering characteristics, but the corresponding mean value of an image after filtering is not kept well. A new filter is proposed for improving the disadvantage based on subspace decomposition. Under the constraint that a weighted combination of the polarimetric SAR images equals to the output of the PWF, the Euclidean distance between an unfiltered parameter vector and a signal space vector is minimized so that noises can be reduced. It is also shown that the proposed method is equivalent to the subspace filter in the case of no constraint. Experimental results with the NASA/JPL airborne polarimetric SAR data demonstrate the effectiveness of the proposed method.

A Quality Assurance Procedure and Evaluation of Rainfall Estimates for C-Band Polarimetric Radar

A mobile C-band dual polarimetric weather radar J type （PCDJ）, which adopts simultaneous transmission and simultaneous reception （STSR） of horizontally and vertically polarized signals, was first developed in China in 2008. It was deployed in the radar observation plan in the South China Heavy Rainfall Experiment （SCHeREX） in the summer of 2008 and 2009, as well as in Tropical Western Pacific Ocean Observation Experiments and Research on the Predictability of High Impact Weather Events from 2008 to 2010 in China （TWPOR）. Using the observation data collected in these experiments, the radar systematic error and its sources were analyzed in depth. Meanwhile an algorithm that can smooth differential propagation phase （~Dp） for estimating the high-resolution specific differential phase （KDP） was developed. After attenuation correction of reflectivity in horizontal polarization （ZH） and differential reflectivity （ZDR） of PCDJ radar by means of KDP, the data quality was improved significantly. Using quality-controlled radar data, quantitative rainfall estimation was performed, and the resutls were compared with rain-gauge measurements. A synthetic ZH /KDp-based method was analyzed. The results the traditional ZH-based method when the rain suggest that the synthetic method has the advantage over rate is 〉5 mm h^-1. The more intensive the rain rates, the higher accuracy of the estimation.

Solution for polarimetric radar cross section measurement and calibration

The exact radar cross-section （RCS） measurement is difficult when the scattering of targets is low. Ful polarimetric cali-bration is one technique that offers the potential for improving the accuracy of RCS measurements. There are numerous polarimetric calibration algorithms. Some complex expressions in these algo-rithms cannot be easily used in an engineering practice. A radar polarimetric coefficients matrix （RPCM） with a simpler expression is presented for the monostatic radar polarization scattering matrix （PSM） measurement. Using a rhombic dihedral corner reflector and a metal ic sphere, the RPCM can be obtained by solving a set of equations, which can be used to find the true PSM for any target. An example for the PSM of a metal ic dish shows that the proposed method obviously improves the accuracy of cross-polarized RCS measurements.

Information compression and speckle reduction for multifrequency polarimetric SAR images based on kernel PCA

Multifrequency polarimetric SAR imagery provides a very convenient approach for signal processing and acquisition of radar image. However, the amount of information is scattered in several images, and redundancies exist between different bands and polarizations. Similar to signal-polarimetric SAR image, multifrequency polarimetric SAR image is corrupted with speckle noise at the same time. A method of information compression and speckle reduction for multifrequency polarimetric SAR imagery is presented based on kernel principal component analysis （KPCA）. KPCA is a nonlinear generalization of the linear principal component analysis using the kernel trick. The NASA/JPL polarimetric SAR imagery of P, L, and C bands quadpolarizations is used for illustration. The experimental results show that KPCA has better capability in information compression and speckle reduction as compared with linear PCA.

Precipitation Microphysical Processes in the Inner Rainband of Tropical Cyclone Kajiki (2019) over the South China Sea Revealed by Polarimetric Radar

Polarimetric radar and 2D video disdrometer observations provide new insights into the precipitation microphysical processes and characteristics in the inner rainband of tropical cyclone(TC)Kajiki(2019)in the South China Sea for the first time.The precipitation of Kajiki is dominated by high concentrations and small(<3 mm)raindrops,which contribute more than 98%to the total precipitation.The average mass-weighted mean diameter and logarithmic normalized intercept are 1.49 mm and 4.47,respectively,indicating a larger mean diameter and a lower concentration compared to the TCs making landfall in eastern China.The ice processes of the inner rainband are dramatically different among different stages.The riming process is dominant during the mature stage,while during the decay stage the aggregation process is dominant.The vertical profiles of the polarimetric radar variables together with ice and liquid water contents in the convective region indicate that the formation of precipitation is dominated by warm-rain processes.Large raindrops collect cloud droplets and other raindrops,causing reflectivity,differential reflectivity,and specific differential phase to increase with decreasing height.That is,accretion and coalescence play a critical role in the formation of heavy rainfall.The melting of different particles generated by the ice process has a great influence on the initial raindrop size distribution(DSD)to further affect the warm-rain processes.The DSD above heavy rain with the effect of graupel has a wider spectral width than the region without the effect of graupel.

Spectro-polarimetric observations at the NVST:I.instrumental polarization calibration and primary measurements

This paper is devoted to the primary spectro-polarimetric observation performed at the New Vacuum Solar Telescope(NVST)of China since 2017,and our aim is to precisely evaluate the real polarimetric accuracy and sensitivity of this polarimetry by using full Stokes spectro-polarimetric observations of the photospheric line Fe I 532.4 nm.In the work,we briefly describe the salient characteristic of the NVST as a polarimeter in terms of technology and then characterize its instrumental polarization based on the operation in 2017 and 2019.It is verified that the calibration method utilizing the instrumental polarization calibration unit(ICU)is stable and credible.The calibration accuracy can reach up to 3×10^-3.Based on the scientific observation of NOAA Active Region 12645 on 2017 April 5,we estimate that the residual cross-talk from Stokes I to Stokes Q,U and V,after the instrumental polarization calibration,is about 4×10^-3 on average,which is consistent with the calibration accuracy and close to the photon noise.The polarimetric sensitivity(i.e.,the detection limit)for polarized light is of the order of 10-3 with an integration time over 20 s.Slow modulation rate is indeed an issue for the present system.The present NVST polarimeter is expected to be integrated with a high-order adaptive optics system and a field scanner to realize 2 D vector magnetic field measurements in the following instrumentation update.

Raindrop Size Distribution Parameters Retrieved from Xinfeng C-Band Polarimetric Radar Observations

The objective of this research was to acquire a raindrop size distribution(DSDs)retrieved from C-band polarimetric radar observations scheme for the first time in south China.An observation period of the precipitation process was selected,and the shape-slope(μ-Λ)relationship of this region was statistically analyzed using the raindrop sample observations from the two-dimensional video disdrometer(2DVD)at Xinfeng Station,Guangdong Province.Simulated data of the C-band polarimetric radar reflectivity ZHHand differential reflectivity ZDRwere obtained through scattering simulation.The simulation data were combined with DSD fitting to determine the ZDR-Λand log10(ZHH/N0)-Λrelationships.Using Xinfeng C-band polarimetric radar observations ZDRand ZHH,the raindrop Gamma size distribution parametersμ,Λ,and N0were retrieved.A scheme for using C-band polarimetric radar to retrieve the DSDs was developed.This research revealed that during precipitation process,the DSDs obtained using the C-band polarimetric radar retrieval scheme are similar to the 2DVD observations,the precipitation characteristics of rainfall intensity(R),mass-weighted mean diameter(Dm)and intercept parameter(Nw)with time obtained by radar retrieval are basically consistent with the observational results of the 2DVD.This scheme establishes the relationship between the observations of the C-band polarimetric radar and the physical quantities of the numerical model.This method not only can test the prediction of the model data assimilation system on the convective scale and determine error sources,but also can improve the microphysical precipitation processes analysis and radar quantitative precipitation estimation.The present research will facilitate radar data assimilation in the future.

The polarimetric features of oil spills in full polarimetric synthetic aperture radar images

Compared with single-polarized synthetic aperture radar （SAR） images, full polarimetric SAIl images contain not only geometrical and backward scattering characteristics, but also the polarization features of the scattering targets. Therefore, the polarimetric SAR has more advantages for oil spill detection on the sea surface. As a crucial step in the oil spill detection, a feature extraction directly influences the accuracy of oil spill discrimination. The polarimetric features of sea oil spills, such as polarimetric entropy, average scatter angle, in the full polarimetric SAR images are analyzed firstly. And a new polarimetric parameter P which reflects the proportion between Bragg and specular scattering signals is proposed. In order to investigate the capability of the polarimetric features for observing an oil spill, systematic comparisons and analyses of the multipolarization features are provided on the basis of the full polarimetric SAR images acquired by SIR-C/X-SAR and Radarsat-2. The experiment results show that in C-band SAR images the oil spills can be detected more easily than in L-band SAR images under low to moderate wind speed conditions. Moreover, it also finds that the new polarimetric parameter is sensitive to the sea surface scattering mechanisms. And the experiment results demonstrate that the new polarimetric parameter and pedestal height perform better than other polarimetric parameters for the oil spill detection in the C-band SAR images.

Targets detecting in the ocean using the cross-polarized channels of fully polarimetric SAR data

Azimuth ambiguities （ghost targets） discrimination is of great interest with the development of a synthet- ic aperture radar （SAR）. And the azimuth ambiguities are often mistaken as actual targets and cause false alarms. For actual targets, HV channel signals acquired by a fully polarimetric SAR are approximately equal to a VH channel in magnitude and phase, i.e., the reciprocity theorem applies, but shifted in phase about ±π for the first-order azimuth ambiguities. Exploiting this physical behavior, the real part of the product of the two cross-polarized channels, i.e. （SHVSVH）, hereafter called A12r, is employed as a new parameter for a target detection at sea. Compared with other parameters, the contrast of A12r image between a target and the surrounding sea surface will be obviously increased when A12r image is processed by mean filtering algo- rithm. Here, in order to detect target with constant false-alarm rates （CFARs）, an analytical expression for the probability density function （pdf） ofA12r is derived based on the complexWishart-distribution. Because a value of A12r is greater/less than 0 for real target/its azimuth ambiguities, the first-order azimuth ambiguities can be completely removed by this A12r-based CFAR technology. Experiments accomplished over C-band RADARSAT-2 fully polarimetric imageries confirm the validity.

Dry/wet snow mapping based on the synergistic use of dual polarimetric SAR and multispectral data

We propose a multi-sensor multi-spectral and bi-temporal dual-polarimetric Synthetic Aperture Radar(SAR) data integration scheme for dry/wet snow mapping using Sentinel-2 and Sentinel-1 data which are freely available to the research community. The integration is carried out by incorporating the information retrieved from ratio images of the conventional method for wet snow mapping and the multispectral data in two different frameworks. Firstly, a simple differencing scheme is employed for dry/wet snow mapping, where the snow cover area is derived using the Normalized Differenced Snow Index(NDSI). In the second framework, the ratio images are stacked with the multispectral bands and this stack is used for supervised and unsupervised classification using support vector machines for dry/wet snow mapping. We also investigate the potential of a state of the art backscatter model for the identification of dry/wet snow using Sentinel-1 data. The results are validated using a reference map derived from RADARSAT-2 full polarimetric SAR data. A good agreement was observed between the results and the reference data with an overall accuracy greater than 0.78 for the different blending techniques examined. For all the proposed frameworks, the wet snow was better identified. The coefficient of determination between the snow wetness derived from the backscatter model and the reference based on RADARSAT-2 data was observed to be 0.58 with a significantly higher root mean square error of 1.03 % by volume.

Kinematics and Microphysical Characteristics of the First Intense Rainfall Convective Storm Observed by Jiangsu Polarimetric Radar Network

The polarimetric radar network in Jiangsu Province has just been operationalized since 2020.The first intense precipitation event observed by this polarimetric radar network and disdrometer occurred during August 28-29,2020 and caused severe flooding and serious damage in eastern Jiangsu Province.The microphysics and kinetics for this heavy precipitation convective storm is diagnosed in this study,in order to promote the application of this polarimetric radar network.Drop size distribution(DSD)of this event is estimated from measurements of a ground disdrometer,and the corresponding three-dimensional atmospheric microphysical features are obtained from the multiple polarimetric radars.According to features of updraft and lighting,the evolution of the convective storm is divided into four stages:developing,mature with lightning,mature without lightning and dissipating.The DSD of this event is featured by a large number of raindrops and a considerable number of large raindrops.The microphysical characteristics are similar to those of warm-rain process,and ice-phase microphysical processes are active in the mature stages.The composite vertical structure of the convective storm indicates that deep ZDR and KDP columns coincide with strong updrafts during both mature stages.The hierarchical microphysical structure retrieved by the Hydrometeor Identification Algorithm(HID)shows that depositional growth has occurred above the melting level,and aggregation is the most widespread ice-phase process at the-10℃level or higher.During negative lightning activity,the presence of strongest updrafts and a large amount of ice-phase graupel by riming between the 0℃and-35℃layers generate strong negative electric fields within the cloud.These convective storms are typical warm clouds with very high precipitation efficiency,which cause high concentration of raindrops,especially the presence of large raindrops within a short period of time.The ice-phase microphysical processes above the melting layer also play an important role in the triggering and enhancing of precipitation.

Precision integration of grating-based polarizers onto focal plane arrays of near-infrared photovoltaic detectors for enhanced contrast polarimetric imaging

Polarimetric imaging enhances the ability to distinguish objects from a bright background by detecting their particular polarization status,which offers another degree of freedom in infrared remote sensing.However,to scale up by monolithically integrating grating-based polarizers onto a focal plane array(FPA)of infrared detectors,fundamental technical obstacles must be overcome,including reductions of the extinction ratio by the misalignment between the polarizer and the detector,grating line width fluctuations,the line edge roughness,etc.This paper reports the authors’latest achievements in overcoming those problems by solving key technical issues regarding the integration of large-scale polarizers onto the chips of FPAs with individual indium gallium arsenide/indium phosphide(In Ga As/In P)sensors as the basic building blocks.Polarimetric and photovoltaic chips with divisions of the focal plane of 540×4 pixels and 320×256 superpixels have been successfully manufactured.Polarimetric imaging with enhanced contrast has been demonstrated.The progress made in this work has opened up a broad avenue toward industrialization of high quality polarimetric imaging in infrared wavelengths.

Assimilation of Polarimetric Radar Data Using an Ensemble Kalman Filter for the Analysis and Forecast of Tropical Storm Ewiniar(2018)

This study explores the potential for directly assimilating polarimetric radar data(including reflectivity Z and differential reflectivity Z_(DR))using an ensemble Kalman filter(EnKF)based on the Weather Research and Forecasting model to improve analysis and forecast of Tropical Storm Ewiniar(2018).Ewiniar weakened but brought about heavy rainfall over Guangdong,China after its final landfall.In the present study,two experiments are performed,one assimilating only Z and the other assimilating both Z and Z_(DR).Assimilation of Z_(DR)together with Z effectively modifies hydrometeor fields,and improves the forecast of the intensity,shape and position of rainbands.Forecast of 24-hour extraordinary rainfall≥250 mm is significantly improved.Improvement can also be seen in the wind fields because of cross-variable covariance.The current study shows the possibility of applying polarimetric radar data to improve forecasting of tropical cyclones,which deserves more research in the future.