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Ann. Geophys., 24, 791-805, 2006
www.ann-geophys.net/24/791/2006/
© European Geosciences Union 2006
High-resolution vertical imaging of the troposphere and lower stratosphere using the new MU radar system
H. Luce1, G. Hassenpflug2, M. Yamamoto2, and S. Fukao2
1Laboratoire de Sondages Electromagnétiques de l’Environnement Terrestre, Université de Toulon et du Var, CNRS, La Garde, 83957, France
2Research Institute for Sustainable Humanosphere, Kyoto University, Uji, 611-0011, Japan
Abstract. In the present paper, a new application of the range imaging technique
called Frequency Interferometry Imaging (FII) or Range Imaging (RIM),
performed in April 2005, is shown using the new 46.5-MHz Middle and Upper
(MU) atmosphere radar system (Shigaraki, Japan). Height-time images of brightness
distribution have been computed at the highest resolution ever obtained for
imaging with VHF radars in the troposphere and, for the very first time, in
the lower stratosphere, up to about 22 km. The images were produced by
processing signals obtained with an initial range-resolution of
Δr=150 m and five equally-spaced frequencies within Δf=1.0 MHz, with
the adaptive Capon method. These values represent an improvement of a factor
2 over all the previous published experiments at VHF, which were performed
with Δr=300 m and Δf=0.5 MHz. The Capon images present
realistic and self-consistent features, and reveal many more organized
structures than the height-time SNR plots at the initial range-resolution.
For example, the Capon images show persistent enhanced brightness layers
significantly thinner than 150 m in the stratosphere, which are impossible
to track with the standard single-frequency mode owing to a lack of range
resolution. These observations thus support the idea of strong
stratification even at vertical scales much smaller than 100 m, as suggested
by recent high-resolution temperature observations by balloons (Dalaudier et
al., 1994). We also present comparisons of Capon images with patterns
obtained from the dual-FDI technique and two parametric methods (the MUSIC
algorithm and the newly-introduced Maximum Entropy Method based on an
auto-regressive (AR) model). The comparisons confirm the insufficiencies of
the dual-FDI technique and indicate that parametric methods such as MEM and
the MUSIC algorithm can help to validate the Capon images when the
parametric methods provide similar patterns.
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