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Tropical Cyclones Over the Arabian Sea and Bay of Bengal Tracked by Megha-Tropiques SAPHIR During 2011–2018

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Tropical Cyclones Over the Arabian Sea and Bay of Bengal Tracked by Megha-Tropiques SAPHIR During 2011–2018 J. Earth Syst. Sci. (2019) 128:91 c Indian Academy of Sciences https://doi.org/10.1007/s12040-019-1122-9 Tropical cyclones over the Arabian Sea and Bay of Bengal tracked by Megha-Tropiques SAPHIR during 2011–2018 M P Vasudha* and G Raju Department of Electronics and Communication Engineering, School of Engineering and Technology, Jain (Deemed-to-be University), Bangalore, India. *Corresponding author. e-mail: [email protected] MS received 10 August 2017; revised 25 June 2018; accepted 13 October 2018; published online 28 March 2019 Monitoring of tropical cyclones (TCs) using the Sondeur Atmosph´erique du Profil d’Humidit´e Intertropicale par Radiom´etrie (SAPHIR) sounder on-board the Megha-Tropiques satellite is attempted on a qualitative basis. The sounder with a high resolution of 10 km at nadir, combined with its high temporal observation ability, 4–6 times a day, and with six channels at 183.31 ± 11.0 GHz, is used for tracking the cyclones. The study has been performed by applying SAPHIR brightness temperature datasets to the cyclonic regions. In this study, 25 TCs from 2011 to 2018 in the Arabian Sea and the Bay of Bengal over the North Indian Ocean have been observed. A comparison of six channels of SAPHIR shows the clear variations of the eye of the cyclone under various conditions. Furthermore, the positional variations obtained by multiple linear regression models are used to observe the evolution of the cyclone storm from its genesis to dissipation/landfall for all the 25 cyclones. The location accuracy is found to be 0.2–0.3◦, as observed from the SAPHIR dataset that agrees reasonably well with the India Meteorological Department dataset and Advanced Microwave Sounding Unit sounder dataset in cyclone tracking. This study attempts at using the unique features of high temporal resolution, good spatial resolution and more channels and is expected to complement other methods of cyclone tracking. Keywords. Brightness temperature; sounder channels; cyclone; tracking; SAPHIR; Megha-Tropiques. 1. Introduction formed in the Arabian Sea (ARB) and Bay of Bengal (BOB) basins of the North Indian Ocean Tropical cyclone (TC) is generally explained as a (NIO) (Maneesha and Manasa Ranjan 2015). Pas- rapidly rotating cloud system with a central low- sive microwave sensors have been extensively used pressure area over tropical regions associated with for oceanographic applications for the past four closed low-level atmospheric circulation, strong decades (SEASAT, SSMI, MHS, HSB, AMSU-A wind and concentric cycles of cloud arrangement & B and SAPHIR) (Ulaby et al. 1986; Demuth of thunderstorms. Owing to the limitations asso- et al. 2004; Moore and Jones 2004). While observ- ciated with making in situ observations over the ing severe storms and features of TC life cycle, sea surface during the storm period, researchers the microwave sounder can sense microwave radia- and scientists are using satellite data to study and tion through the cloud-covered areas without much understand the life cycle of TCs. It is observed atmospheric attenuations. The visible or infrared that ∼5 to 6% of the TCs around the world are sensors cannot sense microwave radiation through 1 0123456789().,--: vol V 91 Page 2 of 15 J. Earth Syst. Sci. (2019) 128:91 clouds. Hence, compared to microwave sounders, estimate the positions of the eye of the cyclone observations from microwave visible or infrared centre using the Dvorak method. Kotal and Roy sensors are subject to more atmospheric attenu- Bhowmik 2011 proposed the multi-model ensemble ations. (MME) technique, which depends on the multiple Space-borne microwave radiometer observation linear regression-based minimisation principle to plays a pivotal role in the early detection of TC forecast positions with respect to observed latitude life cycle beginning from cyclone genesis, its growth and longitude position of cyclones over the North followed by land fall and/or weakening into a low- Indian Sea. We applied the three selected predic- pressure area. The formation of eye of the TC is tors from numerical weather prediction model at associated with the genesis and beginning of rapid 12-h interval up to 120 h in the MME technique intensification. TC characteristics such as position for forecasting and tracking the present cyclone in or location, eye centre fix, central pressure, pres- real-time. sure depth and direction of movement are used Sondeur Atmosph´erique du Profil d’Humidit´e for detecting TC genesis, eye centre and eyewall Intertropicale par Radiom´etrie (SAPHIR) on board replacement that are used for estimating TC inten- Megha-Tropiques (MT) satellite has a good spatial sity (Velden et al. 2007). Roy Bhowmik (2003) resolution of 10–20 km and a large swath of ∼2060 used the genesis parameter to study the develop- km. MT was launched in a near-circular inclined ing and non-developing systems over the NIO and orbit of 20◦ on 12 October 2011 (Raju 2012)and observed parameter values ∼20 ×10−12 s−2 against gives high-quality information on ocean surface the tropical number (T-No) 1.5. The visible and (Aguttes et al. 2000), atmospheric humidity pro- infrared imageries from the meteorological satel- file (Balaji et al. 2014) and land-related application lite to estimate the eye of the cyclone centre can (Suresh Raju et al. 2013). Observation of patterns be used only during clear sky conditions. On the and features of the cloud of low-pressure area of other hand, by using the microwave image, we can TC system over ARB and BOB by microwave simulate radiances to locate the band and eye pat- sounder instrument aboard satellites is becom- tern both under clear and cloudy sky conditions. ing increasingly important. It is with encouraging Demuth et al. (2004) showed that the estima- possibility that the SAPHIR sounder data were tion of eye of the TC size and intensity is also attempted to be used to explain the observed inten- possible using warm core brightness temperature sity and structure changes in TCs. Sivira et al. data at 250 mb level obtained from the Advanced (2015) proposed that measurements of SAPHIR Microwave Sounding Unit (AMSU) Sounder with sounder can be used to retrieve six-layer relative CF of 54.96 GHz. Velden et al. (2007) developed humidity (RH) profiles. This study observed that a technique, generally known as Dvorak tech- by utilising SAPHIR sounder Level 1A dataset, nique, for determining the TC centre location/TC it is conceivable to get cloud-top brightness tem- intensity by utilising kinematic organisational pat- peratures (normally in the eye) from all the six terns of clouds structure. Nishimura et al. (2008) channels based on various frequency channels (i.e., used the microwave imagery from AMSR-E sen- 183.31 ± 11.0 GHz) in cyclone area at near real- sor aboard earth observing satellite to analyse the time perceptions. Furthermore, repeated use of the inner structures of eye of the cyclone pattern and sensor around 4–6 times each day is valuable in Table 1. Tropical cyclones formed over Arabian Sea (2011–2018). Time Latitude Longitude Duration Year Name Formed (UTC) (◦N) (◦E) Dissipated (h) 2011 Keila 29 October 2011 06.00 13.0 62.0 04 November 2011 141 2012 Murjan 23 October 2012 03.00 11.0 65.5 26 October 2012 87 2014 Nanauk 10 June 2014 09.00 15.5 68.5 14 June 2014 99 2014 Nilofar 25 October 2014 00.00 12.5 61.5 31 October 2014 144 2015 Ashobaa 07 June 2015 03.00 14.5 68.5 12 June 2015 120 2015 Chapala 28 October 2015 03.00 11.5 65.0 04 November 2015 168 2015 Megha 05 November 2015 00.00 14.1 66.0 10 November 2015 126 2018 Sagar 16 May 2018 18.00 13.2 49.5 20 May 2018 96 2018 Mekunu 21 May 2018 12.00 09.1 57.3 27 May 2018 168 J. Earth Syst. Sci. (2019) 128:91 Page 3 of 15 91 Table 2. Tropical cyclones formed over Bay of Bengal [2011–2018]. Time Latitude Longitude Duration Year Name Formed (UTC) (◦N) (◦E) Dissipated (h) 2011 Thane 25 December 2011 12.00 08.5 88.5 31 December 2011 159 2012 Nilam 28 October 2012 06.00 09.5 86.0 01 November 2012 78 2013 Viyaru 10 May 2013 09.00 05.0 92.0 17 May 2013 87 2013 Phailin 08 October 2013 03.00 12.0 96.0 14 October 2013 144 2013 Helen 19 November 2013 00.00 10.0 84.0 23 November 2013 81 2013 Lehar 23 November 2013 12.00 08.5 96.5 28 November 2013 117 2013 Madi 06 December 2013 12.00 10.0 84.0 13 December 2013 168 2014 Hudhud 07 October 2014 03.00 11.5 95.0 14 October 2014 144 2015 Komen 26 July 2015 03.00 22.0 90.8 02 August 2015 114 2016 Roanu 17 May 2016 03.00 11.0 81.0 23 May 2016 110 2016 Kyant 21 October 2016 03.00 17.0 91.2 28 October 2016 141 2016 Nada 29 November 2016 12.00 10.7 80.7 02 December 2016 57 2016 Vardah 07 December 2016 00.00 11.2 90.5 13 December 2016 150 2017 Maarutha 15 April 2017 03.00 12.0 88.0 17 April 2017 48 2017 Mora 28 May 2017 03.00 14.5 89.5 31 May 2017 078 2017 Ockhi 29 November 2017 18.00 06.6 78.8 06 December 2017 162 Figure 2. Cloud analysed for T-number (Velden et al. 2006). 2018 contains all the parameters of brightness Figure 1.
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