scholarly journals An Analysis of Ku-Band Profiling Radar Observations of Boreal Forest

2017 ◽  
Vol 9 (12) ◽  
pp. 1252 ◽  
Author(s):  
Livia Piermattei ◽  
Markus Hollaus ◽  
Milutin Milenković ◽  
Norbert Pfeifer ◽  
Raphael Quast ◽  
...  
Keyword(s):  
Boreal Forest ◽  
Radar Observations ◽  
Ku Band

scholarly journals A Robust Dual-Frequency Radar Profiling Algorithm

2011 ◽  
Vol 50 (7) ◽  
pp. 1543-1557 ◽  
Author(s):  
Mircea Grecu ◽  
Lin Tian ◽  
William S. Olson ◽  
Simone Tanelli
Keyword(s):  
Synthetic Data ◽  
Optimization Procedure ◽  
Correction Method ◽  
Single Frequency ◽  
Retrieval Algorithm ◽  
Dual Frequency ◽  
Ka Band ◽  
Radar Observations ◽  
Distribution Shape ◽  
Ku Band

AbstractIn this study, an algorithm to retrieve precipitation from spaceborne dual-frequency (13.8 and 35.6 GHz, or Ku/Ka band) radar observations is formulated and investigated. Such algorithms will be of paramount importance in deriving radar-based and combined radar–radiometer precipitation estimates from observations provided by the forthcoming NASA Global Precipitation Measurement (GPM) mission. In GPM, dual-frequency Ku-/Ka-band radar observations will be available only within a narrow swath (approximately one-half of the width of the Ku-band radar swath) over the earth’s surface. Therefore, a particular challenge is to develop a flexible radar retrieval algorithm that can be used to derive physically consistent precipitation profile estimates across the radar swath irrespective of the availability of Ka-band radar observations at any specific location inside that swath, in other words, an algorithm capable of exploiting the information provided by dual-frequency measurements but robust in the absence of Ka-band channel. In the present study, a unified, robust precipitation retrieval algorithm able to interpret either Ku-only or dual-frequency Ku-/Ka-band radar observations in a manner consistent with the information content of the observations is formulated. The formulation is based on 1) a generalized Hitschfeld–Bordan attenuation correction method that yields generic Ku-only precipitation profile estimates and 2) an optimization procedure that adjusts the Ku-band estimates to be physically consistent with coincident Ka-band reflectivity observations and surface reference technique–based path-integrated attenuation estimates at both Ku and Ka bands. The algorithm is investigated using synthetic and actual airborne radar observations collected in the NASA Tropical Composition, Cloud, and Climate Coupling (TC4) campaign. In the synthetic data investigation, the dual-frequency algorithm performed significantly better than a single-frequency algorithm; dual-frequency estimates, however, are still sensitive to various assumptions such as the particle size distribution shape, vertical and cloud water distributions, and scattering properties of the ice-phase precipitation.

scholarly journals Lidar-aided analysis of boreal forest backscatter at Ku band

2020 ◽  
Vol 91 ◽  
pp. 102133 ◽  
Author(s):  
Yuwei Chen ◽  
Ziyi Feng ◽  
Fashuai Li ◽  
Hui Zhou ◽  
Teemu Hakala ◽  
...  
Keyword(s):  
Boreal Forest ◽  
Ku Band

scholarly journals Z-R relationship of snow on Ku-band radar observations

2020 ◽  
Vol 39 (1) ◽  
pp. 33-36
Author(s):  
Kosuke Tomita ◽  
Takeshi Morimoto ◽  
Hiroki Motoyoshi ◽  
Yoshitaka Nakamura ◽  
Hideo Sakai
Keyword(s):  
Radar Observations ◽  
Relationship Of ◽  
Ku Band

scholarly journals The Penetration Analysis of Airborne Ku-Band Radar Versus Satellite Infrared Lidar Based on the Height and Energy Percentiles in the Boreal Forest

2021 ◽  
Vol 13 (9) ◽  
pp. 1650
Author(s):  
Hui Zhou ◽  
Yuwei Chen ◽  
Teemu Hakala ◽  
Ziyi Feng ◽  
Changhui Jiang ◽  
...  
Keyword(s):  
Linear Regression ◽  
Boreal Forest ◽  
Near Infrared ◽  
Infrared Laser ◽  
Airborne Lidar ◽  
Energy Distributions ◽  
Band Frequency ◽  
The Mean ◽  
Mean Square Errors ◽  
Ku Band

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.

scholarly journals Z-R relationship of snow on Ku-band radar observations

1990 ◽  
Vol 10 (1) ◽  
pp. 11-16
Author(s):  
Takayuki Matsuda ◽  
Toshio Sekikawa ◽  
Kazuhiko Miura
Keyword(s):  
Radar Observations ◽  
Relationship Of ◽  
Ku Band

Bistatic radar observations of the coherent backscatter opposition effect in dry snow

2021 ◽  
Author(s):  
Marcel Stefko ◽  
Silvan Leinss ◽  
Irena Hajnsek
Keyword(s):  
Mean Free Path ◽  
Radar System ◽  
Bistatic Radar ◽  
Snow Layer ◽  
Radar Observations ◽  
Opposition Effect ◽  
Snow Properties ◽  
X Band ◽  
Coherent Backscatter ◽  
Ku Band

<p>In this submission we report on observations of the coherent backscatter opposition effect (CBOE) in seasonal snow layers using bistatic radar, and the possible pathways towards estimation of snow properties from these radar observations.</p><p>Bistatic radar refers to a configuration where the transmitter and the receiver are not in the same location. From the point of view of the observed target, there thus exists a non-zero angular separation between  directions towards the transmitter and towards the receiver, referred to as the bistatic angle. The coherent backscatter opposition effect (CBOE) is a phenomenon that causes increased backscatter of coherent radiation at small bistatic angles (less than 1 degree) in refractive but non-absorbing disordered media (e.g. snow). It has been previously investigated to characterize surfaces of various water-ice covered Solar System bodies [1], however it has received comparatively little attention in Earth-focused observations, despite the well-known occurrence of significant volume scattering within snow and ice.</p><p>Scattering models of CBOE relate the shape of the intensity peak (width, height) to specific parameters of the random medium (grain size, mean free path, reflectivity) [2]. Measurements of the CBOE peak profile are thus a possible pathway towards improving the accuracy of estimates of these parameters, and those closely connected to them, such as the snow water equivalent (SWE).</p><p>We report on two separate observations of the CBOE-intensity peak in snow. We carried out ground-based observations using an experimental bistatic Ku-band radar system KAPRI [3], to observe the effect in a winter snow layer on top of the peak Rinerhorn in Davos, Switzerland. We also report on observations of backscatter enhancement in the accumulation zone of Aletsch glacier, using the spaceborne bistatic X-band synthetic aperture radar system TanDEM-X. Applying the aforementioned scattering models to the observations, we can estimate the mean free path of the scattered signal within the snow layer to be 10 cm at Ku-band, and 17 cm at X-band.</p><p>We believe that further study of CBOE in the context of Earth-focused observations of snow and ice opens new opportunities for development of quantitative models aiming to derive snow properties from bistatic radar observations.</p><p>REFERENCES</p><p>[1] Black et al. 2001: Icy Galilean Satellites: Modeling Radar Reflectivities as a Coherent Backscatter Effect. Icarus, 151(2), 167–180.<br>[2] Hapke et al. 1998: The Opposition Effect of the Moon: Coherent Backscatter and Shadow Hiding. Icarus, 133(1), 89–97.<br>[3] Baffelli et al. 2017: Polarimetric Calibration of the Ku-Band Advanced Polarimetric Radar Interferometer. IEEE Transactions on Geoscience and Remote Sensing, 56(4), 2295–2311.</p>

scholarly journals Cross-Validation of Observations between the GPM Dual-Frequency Precipitation Radar and Ground Based Dual-Polarization Radars

2018 ◽  
Vol 10 (11) ◽  
pp. 1773 ◽  
Author(s):  
Sounak Biswas ◽  
V. Chandrasekar
Keyword(s):  
Large Data ◽  
Radar Data ◽  
Dual Frequency ◽  
Dual Polarization ◽  
Precipitation Radar ◽  
Data Set ◽  
Ka Band ◽  
Radar Observations ◽  
Radar Calibration ◽  
Ku Band

The Global Precipitation Measurement (GPM) mission Core Observatory is equipped with a dual-frequency precipitation radar (DPR) with capability of measuring precipitation simultaneously at frequencies of 13.6 GHz (Ku-band) and 35.5 GHz (Ka-band). Since the GPM-DPR cannot use information from polarization diversity, radar reflectivity factor is the most important parameter used in all retrievals. In this study, GPM’s observations of reflectivity at dual-frequency and instantaneous rainfall products are compared quantitatively against dual-polarization ground-based NEXRAD radars from the GPM Validation Network (VN). The ground radars, chosen for this study, are located in the southeastern plains of the U.S.A. with altitudes varying from 5 to 210 m. It is a challenging task to quantitatively compare measurements from space-based and ground-based platforms due to their difference in resolution volumes and viewing geometry. To perform comparisons on a point-to-point basis, radar observations need to be volume matched by averaging data in common volume or by re-sampling data to a common grid system. In this study, a 3-D volume matching technique first proposed by Bolen and Chandrasekar (2003) and later modified by Schwaller and Morris (2011) is applied to both radar data. DPR and ground radar observations and products are cross validated against each other with a large data set. Over 250 GPM overpass cases at 5 NEXRAD locations, starting from April 2014 to June 2018, have been considered. Analysis shows that DPR Ku- and Ka-Band reflectivities are well matched with ground radar with correlation coefficient as high as 0.9 for Ku-band and 0.85 for Ka-band. Ground radar calibration is also checked by observing variation in mean biases of reflectivity between DPR and GR over time. DPR rainfall products are also evaluated. Though DPR underestimates higher rainfall rates in convective cases, its overall performance is found to be satisfactory.

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