Search Results (19)

Remote sensing precipitation products are essential for the systematic analysis of precipitation characteristics and changes. This study conducts a comparative evaluation of precipitation products from rain gauge stations, Climate Prediction Center morphing technique (CMORPH), Tropical Rainfall Measuring Mission precipitation radar (TRMM PR) version 7 and Global Precipitation Measurement (GPM) Dual-Frequency Precipitation Radar Ku band (DPR KuPR) version 6 orbital observations during the common observational period (April–September 2014) across South China. The spatial patterns and probability density function of rain rates from four precipitation products show similar features. However, average rain rates from CMORPH (0.2–2.6 mm/h) tend to be smaller than those from rain gauge (0.1–4.4 mm/h) in temporal and spatial distribution. Conversely, average rain rates from TRMM PR and GPM KuPR (0.4–10.0 mm/h) are generally larger and exhibit more pronounced monthly changes. Despite notable differences in the number of detection samples, TRMM and GPM exhibit comparable spatiotemporal distributions and vertical structures, including rain-rate profiles, storm top heights and liquid (ice) water path. This confirms the consistency of space-borne precipitation radars and provides a foundation for analyzing long-term precipitation trends. Further analysis reveals that light rain rates from CMORPH have relatively small deviations, while rain rates generally tend to underestimate the rain rate compared to rain gauge. In contrast, TRMM PR and GPM KuPR tend to generally overestimate rain rates. Meanwhile, CMORPH (1.5–6.0 mm/h) shows larger deviations from rain gauge than TRMM and GPM, and the bias progressively increases as rain rates rise, as indicated by root mean square error results. Several statistical metrics suggest that although the missing detection rates of TRMM and GPM are higher than those of CMORPH (probability of detection 10–60%), their false detection rates are spatially lower (false alert ratio 10–30%) in Middle-East China. This study aims to provide valuable insights for enhancing precipitation retrieval algorithms and improving the applicability of remote sensing precipitation products. Full article

Magnetic metal absorbing materials have exhibited excellent absorptance performance. However, their applications are still limited in terms of light weight, low thickness and wide absorption bandwidth. To address this challenge, we design a broadband and low-profile multilayer absorber using cobalt–iron (CoFe) alloys doped with rare earth elements (REEs) lanthanum (La) and Neodymium (Nd). An improved estimation of distribution algorithm (IEDA) is employed in conjunction with a mathematical model of multilayer absorbing materials (MAMs) to optimize both the relative bandwidth with reflection loss (RL) below −10 dB and the thickness. Firstly, the absorption performance of CoFe alloys doped with La/Nd with different contents is analysed. Subsequently, IEDA is introduced based on a mathematical model to achieve an optimal MAM design that obtains a balance between absorption bandwidth and thickness. To validate the feasibility of our proposed method, a triple-layer MAM is designed and optimized to exhibit wide absorption bandwidth covering C, X, and Ku bands (6.16–12.82 GHz) and a total thickness of 2.39 mm. Then, the electromagnetic (EM) absorption mechanisms of the triple-layer MAMs are systematically investigated. Finally, the triple-layer sample is further fabricated and measured. The experimental result is in good agreement with the simulated result. This paper presents a rapid and efficient optimization method for designing MAMs, offering promising prospects in microwave applications, such as radar-stealth technology, EM shielding, and reduced EM pollution for electronic devices. Full article

This paper proposes a hexagonal meander-shaped wideband electronically reconfigurable transmitarray (HMRTA) at Ku band for satellite communications and radar applications. The proposed transmitarray offers high gain, low profile, and wideband characteristics with beam-scanning and beam-forming features. The cascaded structure is a low-profile and compact transmitarray. The transmitter (T_x) layer has an angular hexagonal patch with a meandered shape and resonating parasitic patches to enhance the bandwidth. The receiver (R_x) layer comprises a two-part hexagonal receiver patch and a dual ring impedance-matching receiver layer. The current reversal phenomena have executed the 180° phase shift by integrating two diodes in opposite directions. The measured results of a unit cell achieve a minimum insertion loss of 0.86 dB and 0.92 dB for state I and state II. The maximum insertion loss is 2.58 dB from 14.12 GHz to 18.02 GHz and is about 24.83% at 16.5 GHz. The full-wave simulations of a 20 × 20 space-fed reconfigurable transmitarray were performed. Good radiation patterns at all scanning angles of two principal planes are achieved, and the cross-polarization level remains less than −20 dB. The simulated 3 dB gain fluctuation bandwidth of the array is 15.85~18.35 GHz, and the wideband characteristics are verified. The simulation results show that the array can perform beam scanning ±60° in the elevation (y-z) plane and obtain the beam-scanning characteristics for ±60° in the Azimuth (x-z) plane. Full article

In this study, the spherical particle model and ten nonspherical particle models describing the scattering properties of snow are evaluated for potential use in precipitation estimation from spaceborne dual-frequency precipitation radar. The single scattering properties of nonspherical snow particles are computed using discrete dipole approximation (DDA), while those of spherical particles are determined using Mie theory. The precipitation profiles from WRF output are then input to a forward radiative transfer model to simulate the radar reflectivity at Ka-band and Ku-band. The results are validated with Global Precipitation Mission Dual-Frequency Precipitation Radar measurements. Greater consistency between the simulated and observed reflectivity is obtained when using the sector- and dendrite-shape assumptions. For the case in this study, when using the spherical-shape assumption, radar underestimates the error of the cloud’s top by about 300 m and underestimates the error of the cloud’s area by about 15%. As snowflake shapes change with temperature, we use the range between −40 °C and −5 °C to define three temperature layers. The relationships between reflectivity (Z) and precipitation rate (R) are fitted separately for the three layers, resulting in $\mathrm{Z}=134.59·{\mathrm{R}}^{1.184}$ (sector) and $\mathrm{Z}=127.35·{\mathrm{R}}^{1.221}$ (dendrite) below −40 °C. Full article

Spaceborne snow water retrievals over oceans are assessed using a multiyear coincident dataset of CloudSat Cloud Profiling Radar (CPR) and Global Precipitation Mission (GPM) Dual-frequency Precipitation Radar (DPR). Various factors contributing to differences in snow water retrievals between CPR and DPR are carefully considered. A set of relationships between radar reflectivity (Z_e) and snow water content (SWC) at Ku- and W-bands is developed using the same microphysical assumptions. It is found that surface snow water contents from CPR are much larger than those from DPR at latitudes above 60°, while surface snow water contents from DPR slightly exceed those from CPR at latitudes below 50°. Coincident snow water content profiles between CPR and DPR are further divided into two conditions. One is that only CPR detects the falling snow. Another is that both CPR and DPR detect the falling snow. The results indicate that about 88% of all snow water content profiles are under the first condition and usually associated with light snowfall events. The remaining snow water content profiles are generally associated with moderate and heavy snowfall events. Moreover, CPR surface snow water contents are larger than DPR ones at high latitudes because most light snowfall events are misdetected by DPR due to its low sensitivity. DPR surface snow water contents exceed CPR ones at low latitudes because CPR may experience a significant reduction in backscattering efficiency of large particles and attenuation in heavy snowfall events. The low sensitivity of DPR also causes a noticeable decrease in detected snow layer depth. The results presented here can help in developing global snowfall retrieval algorithms using multi-radars. Full article

Once, bird respiration was thought to be responsible for the 10 dB-level fluctuations in the radar signals of birds. Although, recently, many researchers provide evidence against this, there are almost no quantification measurements of the contribution of respiration to bird signals in microwave anechoic chambers. Here, we first measured the radar signals modulated by the respiration of birds in a microwave anechoic chamber. Theoretically, the simulated signal fluctuation caused by the respiration of a 1 kg standard avian target (SAT) duck is approximately 1.2 dB based on the water sphere model. Then, experimentally, in a microwave anechoic chamber, we measured the signal fluctuations produced by the respiration movement of ducks using a dynamic system composed of a network analyzer and a high-speed camera. We tracked continuous radar data of a living duck and a dead duck within the S-band, X-band, and Ku-band, and then presented them using low-resolution range profiles (LRRP) and high-resolution range profiles (HRRP). The results indicate that respiration movement causes periodic signal fluctuation with a respiration rate of approximately 0.7 Hz, but the amplitudes within S-band, X-band, and Ku-band are approximately 1 dB level, much less than the 10 dB level. Respiration is not responsible for the 10 dB-level periodic signal fluctuation in radar echoes from birds. Full article

Plasma sheath poses a serious challenge to inverse synthetic aperture radar (ISAR) imaging of hypersonic targets. This paper investigated the distribution characteristics of the electron density and velocity field in the plasma sheath surrounding the hypersonic target in various flight scenes. The incident depth and reflective surface of electromagnetic (EM) waves with X-band, Ku-band, and Ka-band can be determined based on the plasma frequency. We established the echo model coupled with the velocity field of the plasma sheath on the reflective surface and obtained one-dimensional range profiles and ISAR images of the hypersonic target in various flight scenes. The simulation results indicated that the non-uniform velocity field on the reflective surface induced displacement and diffusion in the one-dimensional range profile, resulting in ISAR image distortion. A changing flight scene and radar frequency can have an impact on imaging results. Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity (SSIM) were utilized to assess the impact of plasma sheath on ISAR images. This study revealed the defocus mechanism of the ISAR image caused by the velocity field of the plasma sheath and provided a theoretical reference for the selection of radar frequency for hypersonic targets in various flight scenes. Full article

Globally consistent long-term radar measurements are imperative for understanding the global climatology and potential trends of convection. This study investigates the consistency of vertical profiles of reflectivity (VPR) and 20-dBZ echo-top height (Topht20) between the two precipitation radars onboard the Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Measurement (GPM) satellites. Results show that VPR coincidently observed by the TRMM’s and GPM’s Ku-band radar agree well for both convective and stratiform precipitation, although certain discrepancies exist in the VPR of weak convection. Topht20s of the TRMM and GPM are consistent either for coincident events, or latitudinal mean during the 7-month common period, all with biases within the radar range resolution (0.1–0.2 km). The largest difference in the Topht20 between the TRMM’s and GPM’s Ku-band radar occurs in shallow precipitation. Possible reasons for this discrepancy are discussed, including sidelobe clutter, beam-mismatch, non-uniform beam filling, and insufficient sampling. Finally, a 23-year (1998–2020) climatology of Topht20 has been constructed from the two spaceborne radars, and the global mean Topht20 time series shows no significant trend in convective depth during the last two decades. Full article

The Global Precipitation Measurement (GPM) Dual-Frequency Precipitation Radar (DPR) (Ku- and Ka-band, or 14 and 35 GHz) provides the capability to resolve the precipitation structure under moderate to heavy precipitation conditions. In this manuscript, the use of near-coincident observations between GPM and the CloudSat Profiling Radar (CPR) (W-band, or 94 GHz) are demonstrated to extend the capability of representing light rain and cold-season precipitation from DPR and the GPM passive microwave constellation sensors. These unique triple-frequency data have opened up applications related to cold-season precipitation, ice microphysics, and light rainfall and surface emissivity effects. Full article

The paper investigates the penetration properties of an airborne Ku-band frequency modulated continuous waveform (FMCW) profiling radar named Tomoradar and a satellite near-infrared lidar into the boreal forest of Finland. We achieve the accumulative energy distributions based on the Tomoradar waveforms and the satellite lidar waveforms generated from the high-density airborne lidar data within Tomoradar footprints. By comparing two groups of the height percentiles and energy percentiles derived from the accumulative energy distributions, we evaluate the relationship of penetrations between the Ku-band microwave and near-infrared laser according to the coefficients of the determination (COD), and the root mean square errors (RMSE) of linear regression analyses. The quantitative analysis results demonstrate that the height and energy percentiles derived from Tomoradar waveforms correlate well with those from satellite lidar waveforms with the mean correlation coefficients of more than 0.78 and 0.85. The linear regression models for the height and energy percentile produce excellent fits with the mean CODs of 0.95 and 0.90 and the mean RMSEs of 1.25 m and 0.03, respectively. Less than 15% of height percentiles and 87.54% of the energy percentiles in the sixth stratum near the ground derived from Tomoradar waveforms surpass those from satellite lidar waveforms. Hence, the Ku-band microwave can penetrate deeper into the forest than the near-infrared laser at the same spatial scale. In addition, quadratic fitting models are established to describe the differences of the height percentile (DHP) and the energy percentile (DEP) to expound the canopy height and closure contributions numerically. The facts that the CODs of the DHP and DEP individually are more than 0.96 and 0.89 and the fitting residual histograms approximate to normal distributions reveal the reliabilities of the proposed fitting models. Thus, the penetration analyses are valid for the explorations on the FMCW radar applications and the data fusion of the Ku-band radar and near-infrared lidar in the forest investigations. Full article

Profile radar allows direct characterization of the vertical forest structure. Short-wavelength, such as Ku or X band, microwave data provide opportunities to detect the foliage. In order to exploit the potential of radar technology in forestry applications, a helicopter-borne Ku-band profile radar system, named Tomoradar, has been developed by the Finnish Geospatial Research Institute. However, how to use the profile radar waveforms to assess forest canopy parameters remains a challenge. In this study, we proposed a method by matching Tomoradar waveforms with simulated ones to estimate forest canopy leaf area index (LAI). Simulations were conducted by linking an individual tree-based forest gap model ZELIG and a three-dimension (3D) profile radar simulation model RAPID2. The ZELIG model simulated the parameters of potential local forest succession scene, and the RAPID2 model utilized the parameters to generate 3D virtual scenes and simulate waveforms based on Tomoradar configuration. The direct comparison of simulated and collected waveforms from Tomoradar could be carried out, which enabled the derivation of possible canopy LAI distribution corresponding to the Tomoradar waveform. A 600-m stripe of Tomoradar data (HH polarization) collected in the boreal forest at Evo in Finland was used as a test, which was divided into 60 plots with an interval of 10 m along the trajectory. The average waveform of each plot was employed to estimate the canopy LAI. Good results have been found in the waveform matching and the uncertainty of canopy LAI estimation. There were 95% of the plots with the mean relative overlapping rate (RO) above 0.7. The coefficients of variation of canopy LAI estimates were less than 0.20 in 80% of the plots. Compared to lidar-derived canopy effective LAI estimation, the coefficient of determination was 0.46, and the root mean square error (RMSE) was 1.81. This study established a bridge between the Ku band profile radar waveform and the forest canopy LAI by linking the RAPID2 and ZELIG model, presenting the uncertainty of forest canopy LAI estimation using Tomoradar. It is worth noting that since the difference of backscattering contribution is caused by both canopy structure and tree species, similar waveforms may correspond to different canopy LAI, inducing the uncertainty of canopy LAI estimation, which should be noticed in forest parameters estimation with empirical methods. Full article

Radar scientists typically define the radar beamwidth as a half-power beamwidth (HPBW) in the main lobe of the antenna pattern. However, the microwave radiations outside radar HPBW might also backscatter into the radar receiver and change the distribution of the received signal. To determine an actual and effective beamwidth illuminated on the measured targets, we first generate the simulated-waveforms derived from coincident lidar points and radar equation and then develop a waveform matching method to seek out an optimal beamwidth based on the 95% threshold of correlation coefficients between radar waveforms and the simulated-waveforms. The 8565 measurements of a Ku-band profiling radar named Tomoradar and coincident lidar data in a widespread heterogeneous forest area of southern Finland are employed for resolving the effective beamwidth. The results reveal that about 97% of the effective beamwidth are larger than Tomoradar HPBW, but the effective beamwidth could be changeable for each measurement due to variations in the scattering properties of vegetation. Thus, a fixed average effective beamwidth (AEBW) with 0.1-degree resolution is introduced to determine Tomoradar cone according to the effective beamwidth and corresponding proportions. We discover that Tomoradar AEBW is approximately approaching to 8°, which is larger than Tomoradar HPBW of 6°. If we regard AEBW as the actual Tomoradar beamwidth rather than HPBW, the simulated-waveforms have substantially stronger correlation strength with Tomoradar waveforms, and canopy tops derived from lidar data within Tomoradar AEBW are much closer to those extracted from Tomoradar waveforms. The results demonstrate that radar AEBW is a more appropriate reference for designing radar antenna and selecting the region size of validation data such as lidar points or the ground truth. However, considering that radar AEBW is variable for different radar antenna pattern, we suggest that actual radar beamwidth should be defined with a fraction of total radiation energy within radar AEBW, just like the definition of laser divergence of lidar based on the percentage of transmitted laser energy. In this paper, for a forest inventory research case, the fraction of total radiation energy within the AEBW for radar system is supposed to be 91%. Full article

Similar to light detection and ranging (lidar), profile radar can detect forest vertical structure directly. Recently, the first Ku-band profile radar system designed for forest applications, called Tomoradar, has been developed and evaluated in boreal forest. However, the physical relationships between the waveform and forest structure parameters such as height, leaf area index (LAI), and aboveground biomass are still unclear, which limits later forestry applications. Therefore, it is necessary to develop a theoretical model to simulate the relationship and interpret the mechanism behind. In this study, we extend the Radiosity Applicable to Porous IndiviDual objects (RAPID2) model to simulate the profile radar waveform of forest stands. The basic assumption is that the scattering functions of major components within forest canopy are similar between profile radar and the side-looking radar implemented in RAPID2, except several modifications. These modifications of RAPID2 mainly include: (a) changing the observation angle from side-looking to nadir-looking; (b) enhancing the ground specular scattering in normal direction using Fresnel coefficient; (c) increasing the timing resolution and recording waveform. The simulated waveforms were evaluated using two plots of Tomoradar waveforms at co- and cross- polarizations, which are collected in thin and dense forest stands respectively. There is a good agreement (R² ≥ 0.80) between the model results and experimental waveforms in HH and HV polarization modes and two forest scenes. After validation, the extended RAPID2 model was used to explore the sensitivity of the stem density, single tree LAI, crown shape, and twig density on the penetration depth in the Ku-band. Results indicate that the backscattering of the profile radar penetrates deeper than previous studies of synthetic aperture radar (SAR), and the penetration depth tends to be several meters in Ku-band. With the increasing of the needle and twig density in the microwave propagation path, the penetration depth decreases gradually. It is worth noting that variation of stem density seems to have the least effect on the penetration depth, when there is no overlapping between the single tree crowns. Full article

This paper is devoted to investigating the electromagnetic (EM) backscattering from slick-free and slick-covered sea surfaces at various bands (L-band, C-band, X-band, and Ku-band) by using the second-order small slope approximation (SSA-2) and the measured synthetic aperture radar (SAR) data. It is known that the impact of slick on sea surface is mainly caused by two factors: the Marangoni damping effect and the reduction of friction velocity. In this work, the influences induced by these two factors on the sea curvature spectrum, the root mean square (RMS) height, the RMS slope, and the autocorrelation function of sea surfaces are studied in detail. Then, the slick-free and slick-covered sea surface profiles are simulated using the Elfouhaily spectrum and the Monte-Carlo model. The SSA-2 with the tapered incident wave is employed to simulate the normalized radar cross-sections (NRCSs) of sea surfaces. Furthermore, for slick-free sea surfaces, the NRCSs simulated with the SSA-2 at various bands are compared with those obtained by the first-order small slope approximation (SSA-1), the classic two-scale model (TSM), and the geophysical model functions (GMFs) at various bands, respectively. For slick-covered sea surfaces, the SSA-2-simulated NRCSs are compared with those obtained from C-band Radarsat-2 images and L-band uninhabited aerial vehicle synthetic aperture radar (UAVSAR) images, respectively. The numerical simulations illustrate that the SSA-2 can be used to study the EM backscattering from slick-free and slick-covered sea surfaces, and it has more advantages than the SSA-1 and the TSM. The works presented in this paper are helpful for understanding the EM scattering from the sea surface covered with slick, in theory. Full article