Doppler W-band polarization diversity space-borne radar simulator for wind studies
<p>CloudSat observations are used in combination with collocated European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis to simulate space-borne W-band Doppler observations from slant-looking radars. The simulator also includes cross-polarization effects which are relevant if...
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doaj-595424ed49484fd983e977e46d7b4df02020-11-25T02:52:08ZengCopernicus PublicationsAtmospheric Measurement Techniques1867-13811867-85482018-10-01115965597910.5194/amt-11-5965-2018Doppler W-band polarization diversity space-borne radar simulator for wind studiesA. Battaglia0A. Battaglia1R. Dhillon2A. Illingworth3Department of Physics and Astronomy, University of Leicester, Leicester, UKNational Centre for Earth Observation, UKDepartment of Physics and Astronomy, University of Leicester, Leicester, UKDepartment of Meteorology, University of Reading, Reading, UK<p>CloudSat observations are used in combination with collocated European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis to simulate space-borne W-band Doppler observations from slant-looking radars. The simulator also includes cross-polarization effects which are relevant if the Doppler velocities are derived from polarization diversity pulse pair correlation. A specific conically scanning radar configuration (WIVERN), recently proposed to the ESA-Earth Explorer 10 call that aims to provide global in-cloud winds for data assimilation, is analysed in detail in this study.</p><p>One hundred granules of CloudSat data are exploited to investigate the impact on Doppler velocity estimates from three specific effects: (1) non-uniform beam filling, (2) wind shear and (3) crosstalk between orthogonal polarization channels induced by hydrometeors and surface targets. Errors associated with non-uniform beam filling constitute the most important source of error and can account for almost 1 m s<sup>−1</sup> standard deviation, but this can be reduced effectively to less than 0.5 m s<sup>−1</sup> by adopting corrections based on estimates of vertical reflectivity gradients. Wind-shear-induced errors are generally much smaller ( ∼ 0.2 m s<sup>−1</sup>). A methodology for correcting these errors has been developed based on estimates of the vertical wind shear and the reflectivity gradient. Low signal-to-noise ratios lead to higher random errors (especially in winds) and therefore the correction (particularly the one related to the wind-shear-induced error) is less effective at low signal-to-noise ratio. Both errors can be underestimated in our model because the CloudSat data do not fully sample the spatial variability of the reflectivity fields, whereas the ECMWF reanalysis may have smoother velocity fields than in reality (e.g. they underestimate vertical wind shear).</p><p>The simulator allows for quantification of the average number of accurate measurements that could be gathered by the Doppler radar for each polar orbit, which is strongly impacted by the selection of the polarization diversity <i>H</i> − <i>V</i> pulse separation, <i>T</i><sub><i>h</i><i>v</i></sub>. For WIVERN a selection close to 20 µs (with a corresponding folding velocity equal to 40 m s<sup>−1</sup>) seems to achieve the right balance between maximizing the number of accurate wind measurements (exceeding 10 % of the time at any particular level in the mid-troposphere) and minimizing aliasing effects in the presence of high winds.</p><p>The study lays the foundation for future studies towards a thorough assessment of the performance of polar orbiting wide-swath W-band Doppler radars on a global scale. The next generation of scanning cloud radar systems and reanalyses with improved resolution will enable a full capture of the spatial variability of the cloud reflectivity and the in-cloud wind fields, thus refining the results of this study.</p>https://www.atmos-meas-tech.net/11/5965/2018/amt-11-5965-2018.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
A. Battaglia A. Battaglia R. Dhillon A. Illingworth |
spellingShingle |
A. Battaglia A. Battaglia R. Dhillon A. Illingworth Doppler W-band polarization diversity space-borne radar simulator for wind studies Atmospheric Measurement Techniques |
author_facet |
A. Battaglia A. Battaglia R. Dhillon A. Illingworth |
author_sort |
A. Battaglia |
title |
Doppler W-band polarization diversity space-borne radar simulator for wind studies |
title_short |
Doppler W-band polarization diversity space-borne radar simulator for wind studies |
title_full |
Doppler W-band polarization diversity space-borne radar simulator for wind studies |
title_fullStr |
Doppler W-band polarization diversity space-borne radar simulator for wind studies |
title_full_unstemmed |
Doppler W-band polarization diversity space-borne radar simulator for wind studies |
title_sort |
doppler w-band polarization diversity space-borne radar simulator for wind studies |
publisher |
Copernicus Publications |
series |
Atmospheric Measurement Techniques |
issn |
1867-1381 1867-8548 |
publishDate |
2018-10-01 |
description |
<p>CloudSat observations are used in combination with collocated European Centre
for Medium-Range Weather Forecasts (ECMWF) reanalysis to simulate space-borne
W-band Doppler observations from slant-looking radars. The simulator also
includes cross-polarization effects which are relevant if the Doppler
velocities are derived from polarization diversity pulse pair correlation. A
specific conically scanning radar configuration (WIVERN), recently
proposed to the ESA-Earth Explorer 10 call that aims to provide global
in-cloud winds for data assimilation, is analysed in detail in this study.</p><p>One hundred granules of CloudSat data are exploited to investigate the impact
on Doppler velocity estimates from three specific effects: (1) non-uniform
beam filling, (2) wind shear and (3) crosstalk between orthogonal
polarization channels induced by hydrometeors and surface targets. Errors
associated with non-uniform beam filling constitute the most important source
of error and can account for almost 1 m s<sup>−1</sup> standard deviation, but this
can be reduced effectively to less than 0.5 m s<sup>−1</sup> by adopting
corrections based on estimates of vertical reflectivity gradients.
Wind-shear-induced errors are generally much smaller ( ∼ 0.2 m s<sup>−1</sup>).
A methodology for correcting these errors has been developed based on
estimates of the vertical wind shear and the reflectivity gradient. Low
signal-to-noise ratios lead to higher random errors (especially in winds) and
therefore the correction (particularly the one related to the wind-shear-induced error) is less effective at low signal-to-noise ratio. Both errors
can be underestimated in our model because the CloudSat data do not fully
sample the spatial variability of the reflectivity fields, whereas the ECMWF
reanalysis may have smoother velocity fields than in reality (e.g. they
underestimate vertical wind shear).</p><p>The simulator allows for quantification of the average number of accurate
measurements that could be gathered by the Doppler radar for each polar
orbit, which is strongly impacted by the selection of the polarization
diversity <i>H</i> − <i>V</i> pulse separation, <i>T</i><sub><i>h</i><i>v</i></sub>. For WIVERN a selection close to
20 µs (with a corresponding folding velocity equal to 40 m s<sup>−1</sup>)
seems to achieve the right balance between maximizing the number of accurate
wind measurements (exceeding 10 % of the time at any particular level in
the mid-troposphere) and minimizing aliasing effects in the presence of high
winds.</p><p>The study lays the foundation for future studies towards a thorough
assessment of the performance of polar orbiting wide-swath W-band Doppler
radars on a global scale. The next generation of scanning cloud radar systems
and reanalyses with improved resolution will enable a full capture of the
spatial variability of the cloud reflectivity and the in-cloud wind fields,
thus refining the results of this study.</p> |
url |
https://www.atmos-meas-tech.net/11/5965/2018/amt-11-5965-2018.pdf |
work_keys_str_mv |
AT abattaglia dopplerwbandpolarizationdiversityspaceborneradarsimulatorforwindstudies AT abattaglia dopplerwbandpolarizationdiversityspaceborneradarsimulatorforwindstudies AT rdhillon dopplerwbandpolarizationdiversityspaceborneradarsimulatorforwindstudies AT aillingworth dopplerwbandpolarizationdiversityspaceborneradarsimulatorforwindstudies |
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