scholarly journals Review of Stroeve et al 'Surface-Based Ku- and Ka-band Polarimetric Radar for Sea Ice Studies'

2020 ◽  
Keyword(s):  
Sea Ice ◽  
Polarimetric Radar ◽  
Ka Band

scholarly journals Surface-based Ku- and Ka-band polarimetric radar for sea ice studies

2020 ◽  
Vol 14 (12) ◽  
pp. 4405-4426
Author(s):  
Julienne Stroeve ◽  
Vishnu Nandan ◽  
Rosemary Willatt ◽  
Rasmus Tonboe ◽  
Stefan Hendricks ◽  
...  
Keyword(s):  
Sea Ice ◽  
Snow Depth ◽  
Ice Thickness ◽  
Polarimetric Radar ◽  
Radar Altimeter ◽  
Radar Backscatter ◽  
Sea Ice Thickness ◽  
Ka Band ◽  
Snow Properties ◽  
Wide Range

Abstract. To improve our understanding of how snow properties influence sea ice thickness retrievals from presently operational and upcoming satellite radar altimeter missions, as well as to investigate the potential for combining dual frequencies to simultaneously map snow depth and sea ice thickness, a new, surface-based, fully polarimetric Ku- and Ka-band radar (KuKa radar) was built and deployed during the 2019–2020 year-long MOSAiC international Arctic drift expedition. This instrument, built to operate both as an altimeter (stare mode) and as a scatterometer (scan mode), provided the first in situ Ku- and Ka-band dual-frequency radar observations from autumn freeze-up through midwinter and covering newly formed ice in leads and first-year and second-year ice floes. Data gathered in the altimeter mode will be used to investigate the potential for estimating snow depth as the difference between dominant radar scattering horizons in the Ka- and Ku-band data. In the scatterometer mode, the Ku- and Ka-band radars operated under a wide range of azimuth and incidence angles, continuously assessing changes in the polarimetric radar backscatter and derived polarimetric parameters, as snow properties varied under varying atmospheric conditions. These observations allow for characterizing radar backscatter responses to changes in atmospheric and surface geophysical conditions. In this paper, we describe the KuKa radar, illustrate examples of its data and demonstrate their potential for these investigations.

scholarly journals Supplementary material to "Surface-Based Ku- and Ka-band Polarimetric Radar for Sea Ice Studies"

2020 ◽  
Author(s):  
Julienne Stroeve ◽  
Vishnu Nandan ◽  
Rosemary Willatt ◽  
Rasmus Tonboe ◽  
Stefan Hendricks ◽  
...  
Keyword(s):  
Sea Ice ◽  
Polarimetric Radar ◽  
Ka Band ◽  
Supplementary Material

scholarly journals Surface-Based Ku- and Ka-band Polarimetric Radar for Sea Ice Studies

2020 ◽  
Author(s):  
Julienne Stroeve ◽  
Vishnu Nandan ◽  
Rosemary Willatt ◽  
Rasmus Tonboe ◽  
Stefan Hendricks ◽  
...  
Keyword(s):  
Sea Ice ◽  
Snow Depth ◽  
Incidence Angle ◽  
Ice Thickness ◽  
Polarimetric Radar ◽  
Radar Backscatter ◽  
Sea Ice Thickness ◽  
Ka Band ◽  
Snow Properties ◽  
Wide Range

Abstract. To improve our understanding of how snow properties influence sea ice thickness retrievals from presently operational and upcoming satellite radar altimeter missions, as well as investigating the potential for combining dual frequencies to simultaneously map snow depth and sea ice thickness, a new, surface-based, fully-polarimetric Ku- and Ka-band radar (KuKa radar) was built and deployed during the 2019–2020 year-long MOSAiC International Arctic drift expedition. This instrument, built to operate both as an altimeter (stare mode) and a scatterometer (scanning mode), provided the first in situ Ku- and Ka-band dual frequency radar observations from autumn freeze-up through mid-winter, and covering newly formed ice in leads, first-year and second-year ice floes. Data gathered in the altimeter mode, will be used to investigate the potential for estimating snow depth as the difference between dominant radar scattering horizons in the Ka- and Ku-band data. In the scatterometer mode, the Ku- and Ka-band radars operated under a wide range of azimuth and incidence angle ranges, continuously assessing changes in the polarimetric radar backscatter and derived polarimetric parameters, as snow properties varied under varying atmospheric conditions. These observations allow for characterizing radar backscatter responses to changes in atmospheric and surface geophysical conditions. In this paper, we describe the KuKa radar and illustrate examples of these data and demonstrate their potential for these investigations.

scholarly journals Identifying Insects, Clouds, and Precipitation using Vertically Pointing Polarimetric Radar Doppler Velocity Spectra

2021 ◽  
Author(s):  
Christopher R. Williams ◽  
Karen L. Johnson ◽  
Scott E. Giangrande ◽  
Joseph C. Hardin ◽  
Ruşen Öktem ◽  
...  
Keyword(s):  
Power Spectra ◽  
Department Of Energy ◽  
Cloud Base ◽  
Doppler Velocity ◽  
Polarimetric Radar ◽  
Ka Band ◽  
Ice Particles ◽  
Linear Depolarization Ratio ◽  
Velocity Spectra ◽  
Discrimination Method

Abstract. This study presents a method to identify and distinguish insects, clouds, and precipitation in 35 GHz (Ka-band) vertically pointing polarimetric radar Doppler velocity power spectra and then produce masks indicating the occurrence of hydrometeors (i.e., clouds or precipitation) and insects at each range gate. The polarimetric radar used in this study transmits a linear polarized wave and receives signals in collinear (CoPol) and cross-linear (XPol) polarized channels. The insect-hydrometeor discrimination method uses CoPol and XPol spectral information in two separate algorithms with their spectral results merged and then filtered into single value products at each range gate. The first algorithm discriminates between insects and clouds in the CoPol Doppler velocity power spectra based on the spectra texture, or spectra roughness, which varies due to the scattering characteristics of insects versus cloud particles. The second algorithm distinguishes insects from raindrops and ice particles by exploiting the larger Doppler velocity spectra linear depolarization ratio (LDR) produced by asymmetric insects. Since XPol power return is always less than CoPol power return for the same target (i.e., insect or hydrometeor), fewer insects and hydrometeors are detected in the LDR algorithm than the CoPol algorithm, which drives this need for a CoPol based algorithm. After performing both CoPol and LDR detection algorithms, regions of insect and hydrometeor scattering from both algorithms are combined in the Doppler velocity spectra domain and then filtered to produce a binary hydrometeor mask indicating the occurrence of cloud, raindrops, or ice particles at each range gate. Comparison with a collocated ceilometer indicates that hydrometeor mask column bottoms are within +/-100 meters of simultaneous ceilometer cloud base heights. Forty-seven (47) summer-time days were processed with the insect-hydrometeor discrimination method using U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program Ka-band zenith pointing radar observations in northern Oklahoma (USA). All datasets and images are available on public repositories.

KuKa altimeter mode data gathered during MOSAiC: scattering from snow covered sea ice and snow depth determination using dual-frequency and polarimetric approaches

2021 ◽  
Author(s):  
Rosemary Willatt ◽  
Julienne Stroeve ◽  
Vishnu Nandan ◽  
Rasmus Tonboe ◽  
Stefan Hendricks ◽  
...  
Keyword(s):  
Sea Ice ◽  
Snow Depth ◽  
Satellite Altimetry ◽  
Field Measurements ◽  
Dual Band ◽  
Altimetry Data ◽  
Dual Frequency ◽  
Sea Ice Thickness ◽  
Ka Band ◽  
Snow And Ice

<p>Retrieving the thickness of sea ice, and its snow cover, on long time- and length-scales is critical for studying climate. Satellite altimetry has provided estimations of sea ice thickness spanning nearly three decades, and more recently altimetry techniques have provided estimations of snow depth, using dual-band satellite altimetry data. These approaches are based on assumptions about the main scattering surfaces of the radiation. The dominant scattering surface is often assumed to be the snow/ice interface at Ku-band frequencies and the air/snow interface at Ka-band and laser frequencies. It has previously been shown that these assumptions do not always hold, but field data to investigate the dominant scattering surfaces and investigate how these relate to the physical snow and ice characteristics were spatially and temporally limited. The MOSAiC expedition provided a unique opportunity to gather data using a newly-developed Ku- and Ka-band radar 'KuKa' deployed over snow-covered sea ice, along with coincident field measurements of snow and ice properties. We present transect data gathered with the instrument looking at nadir to demonstrate how the scattering characteristics vary spatially and temporally in the Ku- and Ka-bands, and discuss implications for interpretation of dual-frequency satellite radar altimetry data. We compare KuKa data with field measurements to demonstrate snow depth retrieval using Ku- and Ka-band data.</p>

Polarimetric Radar Measurements Of Artificial Sea Ice

2005 ◽  
Author(s):  
R.G. Onstott ◽  
S.H. Gaboury
Keyword(s):  
Sea Ice ◽  
Polarimetric Radar ◽  
Radar Measurements

Interferometric penetration into dry snow and sea ice at Ka-band

2015 ◽  
Author(s):  
Scott Hensley ◽  
Delwyn Moller ◽  
Ronald Kwok ◽  
Xiaoqing Wu ◽  
Shadi Oveisgharan ◽  
...  
Keyword(s):  
Sea Ice ◽  
Ka Band

The Life-Cycle of Cloud and Precipitation Microphysics in Radar Observation and Numerical Model

2021 ◽  
Author(s):  
Gregor Möller ◽  
Florian Ewald ◽  
Silke Groß ◽  
Martin Hagen ◽  
Christoph Knote ◽  
...  
Keyword(s):  
Prediction Models ◽  
Model Simulation ◽  
Weather Prediction ◽  
Horizontal Resolution ◽  
Polarimetric Radar ◽  
Dual Frequency ◽  
Microphysics Scheme ◽  
Ka Band ◽  
Radar Observations ◽  
Conversion Rates

<p>The representation of microphysical processes in numerical weather prediction models remains a main source of uncertainty. To tackle this issue, we exploit the synergy of two polarimetric radars to provide novel observations of model microphysics parameterizations. In the framework of the IcePolCKa project (Investigation of the initiation of Convection and the Evolution of Precipitationusing simulatiOns and poLarimetric radar observations at C- and Ka-band) we use these observations to study the initiation of convection as well as the evolution of precipitation. At a distance of 23 km between the C-band PoldiRad radar of the German Aerospace Center (DLR) in Oberpfaffenhofen and the Ka-band Mira35 radar of the Ludwig-Maximilians-University of Munich (LMU), the two radar systems allow targeted observations and coordinated scan patterns. A second C-band radar located in Isen and operated by the German Weather Service (DWD) provides area coverage and larger spatial context. By tracking the precipitation movement, the dual-frequency and polarimetric radar observations allow us to characterize important microphysical parameters, such as predominant hydrometeor class or conversion rates between these classes over a significant fraction of the life time of a convective cell. A WRF (Weather Research and Forecasting Model) simulation setup has been established including a Europe-, a nested Germany- and a nested Munich- domain. The Munich domain covers the overlap area of our two radars Mira35 and Poldirad with a horizontal resolution of 400 m. For each of our measurement days we conduct a WRF hindcast simulation with differing microphysics schemes. To allow for a comparison between model world and observation space, we make use of the radar forward-simulator CR-SIM. The measurements so far include 240 coordinated scans of 36 different convective cells over 10 measurement days between end of April and mid July 2019 as well as 40 days of general dual-frequency volume scans between mid April and early October 2020. The performance of each microphysics scheme is analyzed through a comparison to our radar measurements on a statistical basis over all our measurements.</p>

scholarly journals The application of S-band polarimetric radar measurements to Ka-band attenuation prediction

1997 ◽  
Vol 85 (6) ◽  
pp. 893-909 ◽  
Author(s):  
J.D. Beaver ◽  
V.N. Bringi
Keyword(s):  
Polarimetric Radar ◽  
Ka Band ◽  
Radar Measurements
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