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Kotaro Bessho, Tetsuo Nakazawa, Shuji Nishimura, and Koji Kato

Abstract

The temperature profiles of organized cloud clusters developing or not developing (nondeveloping) into tropical storms (TSs; maximum surface wind >34 kt) over the western North Pacific in 2004 were investigated using Advanced Microwave Sounding Unit (AMSU) observations in combination with the independently created early stage Dvorak analysis. Typical temperature profiles of the developing and nondeveloping cloud clusters were compared. From this comparison, positive upper-troposphere temperature anomalies were found in both cluster types; however, the spatial extent of the temperature anomalies for the developing cloud clusters was larger than those of the nondeveloping cloud clusters. Statistical analysis was performed on the temperature anomalies near the center of all clusters retrieved from AMSU observational data. Findings indicate that the area-average temperature anomalies increased along with the intensity of the clusters indicated by the Dvorak T-number classification. Using time series analysis of upper-level temperature anomalies associated with these cloud clusters, a definition of warm core structures showing the temperature anomaly greater than a threshold (WCT) was created. WCT exists when the area averaged temperature anomaly exceeds 0.9 K. Using this definition, almost 70% of the cloud clusters that had WCTs later became TSs, while 85% of those that did not have WCTs eventually dissipated without being classified as a TS. For the WCT clusters that developed into TSs, the lead time from the detection of their AMSU-based WCT to their classification as TSs was 27.7 h. These results indicate that there is a good possibility that the detection and forecasting of tropical cyclone formation, particularly those storms that later may become classified as TSs, will be improved using temperature anomalies derived from AMSU data.

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Taishi Hashimoto, Koji Nishimura, Masaki Tsutsumi, and Toru Sato

Abstract

Strong meteor trail echoes are interferences in the wind velocity estimates made from mesosphere radar observations. Contaminated spectra are detected by their discontinuity and are removed at the risk of greater fluctuations of spectra, leading to a severe reduction of the signal-to-noise ratio (SNR) and inaccurate wind estimates for weak atmospheric echoes. This paper presents an adaptive signal processing technique for the suppression of spectral contaminations by meteor trail echoes. The method is based on the norm-constrained and directionally constrained minimization of power (NC-DCMP), which balances the capability of canceling the clutter and the robustness of beam shaping, at the cost of a slight decrease in the SNR, which can be determined in advance. Simulation results show that with a 3-dB decrease of the SNR being allowed, the method improves the signal-to-interference ratio (SIR) by 15 dB, giving wind estimates that are about 8 m s−1 better in terms of root-mean-square error and providing 4 times as wide an observable range when compared with the results of the ordinary nonadaptive beamforming method. The results for an actual observation show that the improvement of both the SIR and the observable range are achieved as in the simulations, which implies that the method should provide the simulated accuracy for the estimation of wind velocity from actual observations.

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Koji Nishimura, Takuji Nakamura, Toru Sato, and Kaoru Sato

Abstract

Aspect-sensitive backscattering of the atmosphere causes a small error in an effective line-of-sight direction in vertical beam observations leading to a serious degradation of vertical wind estimates due to contamination by horizontal wind components. An adaptive beamforming technique for a multichannel mesosphere–stratosphere–troposphere (MST) radar is presented, which makes it possible to measure the vertical wind velocity with higher accuracy by adaptively generating a countersteered reception beam against an off-vertically shifted echo pattern. The technique employs the norm-constrained direction-constrained minimization of power (NC-DCMP) algorithm, which provides not only robustness but also higher accuracy than the basic direction-constrained minimization of power algorithm in realistic conditions. Although the technique decreases the signal-to-noise ratio, the ratio is controlled and bound at a specified level by the norm constraint. In the case that a decrease of −3 dB is acceptable in a vertical beam observation, for which usually a much higher signal-to-noise ratio is obtained than for oblique beams, the maximum contamination is suppressed to even for the most imbalanced aspect sensitivity.

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Taishi Hashimoto, Koji Nishimura, Masaki Tsutsumi, Kaoru Sato, and Toru Sato

Abstract

This paper presents a novel method for the automatic determination of the diagonal-loading level for robust adaptive beamforming on radar wind profilers. This method balances the degradation of the signal-to-interference ratio with that of the signal-to-noise ratio to maximize the detectability of the backscattered signals. Because radial wind velocities are usually estimated from the first moment of the spectrum of backscattered echoes, both the residual ground clutter and any increase in noise level degrade the detectability of atmospheric echoes. The proposed algorithm evaluates the power spectral density of the residual clutter and increased noise to determine the optimal diagonal-loading level by balancing these two factors. The results of numerical simulation show that, without the need to specify any user parameters, the proposed algorithm is stable and more effective at maximizing the signal-to-interference ratio than the conventional norm-constrained diagonal-loading approach. The stability and clutter suppression capability of the proposed algorithm are examined using data from the Program of the Antarctic Syowa Mesosphere–Stratosphere–Troposphere/Incoherent Scatter Radar.

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Taishi Hashimoto, Akinori Saito, Koji Nishimura, Masaki Tsutsumi, Kaoru Sato, and Toru Sato

Abstract

The Program of the Antarctic Syowa Mesosphere–Stratosphere–Troposphere/Incoherent Scatter (PANSY) radar is a large atmospheric radar located at the Antarctic Syowa Station (69.01°S, 39.59°E). The PANSY radar performed the first incoherent scatter (IS) measurements in the Antarctic region in 2015. Several specific observations were undertaken in 2017 including a 24-h observation of the ionosphere using a peripheral antenna array to suppress interference from the field-aligned irregularities (FAIs). This paper presents the preliminary results derived from the IS measurements using the PANSY radar and the adaptive signal processing techniques to suppress FAIs. The norm-constrained and directionally constrained minimization of power (NC-DCMP) algorithm was applied to the 24-h ionosphere observations by the PANSY radar with a weighting applied to the directional constraint based on the gain differences of the subarrays. When compared with the conventional nonadaptive approach, the number of usable power profiles was increased by about 24% by the gain-weighted NC-DCMP algorithm, suggesting its effectiveness for FAI clutter suppression in ionosphere observations. Furthermore, detection of FAIs using the dedicated antenna array was found valuable in assessing the reliability of estimations of electron density based on VHF-band IS radar data.

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Yoshihiro Tomikawa, Masahiro Nomoto, Hiroaki Miura, Masaki Tsutsumi, Koji Nishimura, Takuji Nakamura, Hisao Yamagishi, Takashi Yamanouchi, Toru Sato, and Kaoru Sato

Abstract

Characteristically strong vertical wind disturbances (VWDs) with magnitudes larger than 1 m s−1 were observed in the Antarctic troposphere using a new mesosphere–stratosphere–troposphere (MST) radar called the Program of the Antarctic Syowa MST/incoherent scatter (IS) Radar (PANSY) during 15–19 June 2012 at Syowa Station (69.0°S, 39.6°E). In the same period, two synoptic-scale cyclones approached Syowa Station and caused a strong wind event (SWE) at the surface. The VWDs observed during the SWE at Syowa Station had a nearly standing (i.e., no phase tilt with height) phase structure up to the tropopause and a power spectrum proportional to the − power of frequency. On the other hand, the observed VWDs were not associated with systematic horizontal momentum fluxes. Meteorological fields around Syowa Station during the SWE were successfully simulated using the Nonhydrostatic Icosahedral Atmospheric Model (NICAM). A strong VWD was also simulated at the model grid of 70.0°S, 40.0°E in NICAM, which had a standing phase structure similar to the observed ones. An analysis based on the Froude number showed that the simulated VWD was likely due to a hydraulic jump leeward of the coastal mountain ridge. The Scorer parameter analysis indicated that the observed VWDs at Syowa Station during 16–17 June 2012 were likely due to the hydraulic jump similar to that in NICAM. On the other hand, a possibility of lee waves was also suggested for the VWD observed on 18 June 2012.

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