A Case Study of an Outbreak of Twin Tropical Cyclones

2009 ◽  
Vol 137 (3) ◽  
pp. 863-875 ◽  
Author(s):  
Carl J. Schreck ◽  
John Molinari

Abstract Previous studies have found that twin tropical cyclogenesis typically occurs 2–3 times a year in the Pacific Ocean. During October 1997, however, three sets of twin tropical cyclones developed in the central Pacific within a single month. Tropical cyclone archives indicate that this is the only such outbreak from 1969 to 2006. This case study explores the background and synoptic conditions that led to this unique event. All three twin tropical cyclogenesis events occurred within a broad and long-lasting envelope of warm water, low surface pressure, active convection, and weak or easterly vertical shear. Westerly winds at the equator and trade easterlies farther poleward created strips of cyclonic vorticity through a deep layer. A low-pass filter showed that these favorable conditions shifted eastward with time at 1–2 m s−1. In addition to the gradual eastward movement, the equatorial westerlies and convection were modulated by higher-frequency westward propagation. These anomalies appear to have been associated with convectively coupled n = 1 equatorial Rossby waves. The twin tropical cyclones formed only when the sum of the two modes produced equatorial westerlies in excess of 5 m s−1 and brightness temperature below 270 K. Applications of these results are proposed for the operational prediction of twin tropical cyclogenesis.

Proceedings ◽  
2019 ◽  
Vol 42 (1) ◽  
pp. 47
Author(s):  
Ahmadreza Mahmoudzadeh ◽  
Sayna Firoozi Yeganeh ◽  
Sara Arezoumand ◽  
Amir Golroo

Data collection plays an important role in pavement health monitoring, which is usually performed using costly devices, including point-based lasers and laser scanners. The main aim of this study measures pavement characteristics using an RGB-D sensor. By recording the depth and color images simultaneously, the sensor benefits the data fusion. By mounting the sensor on a moving cart, and fixing the vertical distance from the ground, data were collected along 100 m of the asphalt pavement using MATLAB. At each stop point, multiple frames were collected, the central region of interests was stored, and a low pass filter was subsequently applied to the data. To create a 3D surface of the pavement, sensor calibration was performed to map the RGB and depth infrared images. The SURF (speeded-up robust features) and MSAC (M-estimator sample consensus) algorithms were used to match the stitched images along the longitudinal profile. A case study of measuring roughness and rutting is applied to test the validity of the method. The result confirms that the proposed system is capable of measuring such indices with acceptable accuracy.


2017 ◽  
Vol E100.C (10) ◽  
pp. 858-865 ◽  
Author(s):  
Yohei MORISHITA ◽  
Koichi MIZUNO ◽  
Junji SATO ◽  
Koji TAKINAMI ◽  
Kazuaki TAKAHASHI

2016 ◽  
Vol 15 (12) ◽  
pp. 2579-2586
Author(s):  
Adina Racasan ◽  
Calin Munteanu ◽  
Vasile Topa ◽  
Claudia Pacurar ◽  
Claudia Hebedean

Author(s):  
Nanan Chomnak ◽  
Siradanai Srisamranrungrueang ◽  
Natapong Wongprommoon
Keyword(s):  

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