International Journal of Applied Engineering Research ISSN 0973-4562 Volume 12, Number 22 (2017) pp. 12821-12832 © Research India Publications. http://www.ripublication.com

Observation of Cyclone Occurred in and Bay of Bengal from SAPHIR Sensor Data

Vasudha. MP Research Scholar, Department of Electronics and Communication Engineering, School of Engineering and Technology, Jain University, Bangalore, India. Orcid Id: 0000-0002-8520-2474

G. Raju Professor, Department of Electronics and Communication Engineering, School of Engineering and Technology, Jain University, Bangalore, India. Orcid Id: 0000-0001-6694-5478

Abstract namely, genesis, intensification and land-fall. During the last several years, due to non availability of conventional The evaluation of life cycle of using satellite observations over the sea surface, satellite data are used by data means and includes analysis of genesis, development and researchers to study and understand . It is its intensity variations. Sondeur Atmosphérique du Profil observed that about 4.8% of tropical cyclones around the d’Humidité Intertropicale par Radiométrie (SAPHIR) world are developed in Arabian Sea (ARB) basin and Bay of microwave sounder on-board Megha-Tropiques satellite Bengal (BOB) basins of North Indian Ocean (NIO). Passive operating at high resolution of 10 km nadir with six frequency microwave sensors have been used for oceanographic channels at 183.31±11.0 GHz has been used as one of ocean applications starting from past 4 decades (from SEASAT, application using satellite data applicable for observation of life SSMI, MHS, HSB, AMSU-A & B, SAPHIR) [3]. When cycle of tropical cyclone. This analysis has been done by compared to visible or infrared observations, the main utilizing SAPHIR brightness temperature dataset to all 20 advantages of microwave sounder observations is microwave tropical cyclones occurred from 2011 to 2016 in Arabian Sea radiation can sense severe storms and tropical cyclones and Bay of Bengal basin over the North Indian Ocean. through the cloud-covered areas without atmospheric Comparison of the 6 channels of SAPHIR shows the clear attenuations. variations of cyclone under various conditions. Further the exceptional highlights of this study are SAPHIR sounder data Satellite observation from microware radiometer plays a major will demonstrate quantitative and subjective improvement in role in early detection of TC, its development and land- fall. acquiring near real time information identifying with (i) The TC genesis and intensity is observed from TC Eye latitude and longitude position of cyclone path (ii) cloud position and associated Maximum Sustainable wind speed features of cyclone eye center (iii) cloud features of tropical measured according to IMD standards [2]. SAPHIR onboard cyclone eye wall formation. Our comparative study shows the Megha-Tropiques (MT) satellite has a good spatial resolution possibility of using SAPHIR sounder data to identify the eye of 10 km at nadir and 14 km at edge and a swath of ~2060 km. center positions of tropical cyclones, and also possibility of Megha-Tropiques was launched in near-circular inclined orbit using the Dvorak method for estimation of cyclone intensity. of 200 on 12 October 2011 [8][9] and giving high-quality Our near real time examination will additionally affirm that the information identified with ocean surface [1], atmospheric positional variations in life cycle of tropical cyclone (from humidity profile and land-related application. It is also genesis to dissipation/landfall) can be obtained by using observed that Level 1 (L1) data of SAPHIR sounder can be multiple linear regression models. A comparative analysis of used for observation and tracking of TC over ARB and BOB SAPHIR dataset, Indian Meteorological Department (IMD) Basins of NIO [11]. Observation of cloud patterns and features dataset and Advance Microwave Sounding Unit (AMSU) of low-pressure storm over ARB and BOB by microwave sounder dataset show positional variations of tropical cyclone, sounder instrument aboard satellites is becoming increasingly ranging from 0.2 to 0.3 degrees (latitude/longitude). important. It is possible that SAPHIR sounder L1 data can also be used to explain the observed intensity and structure changes Keywords: Brightness Temperature, SAPHIR sounder, of tropical cyclones. Velden. C et.al., (2007) [7][13], Julie L. Tropical Cyclone, Cyclone track, Megha - Tropiques. Demuth. et.al., (2004) [3] showed that, it is possible to retrieve

tropical cyclone warm core information from 54.96 GHz of

AMSU temperature anomalies at 250 mb level and from INTRODUCTION AMSU data it is possible to estimate the tropical cyclone eye Tropical cyclone is generally explained as a rotating, organized size and intensity. Shuuji Nishimura et.al, (2008) [10] an low-pressure system of clouds and thunderstorms over tropical enhanced form of foranalyzing center waters. It consists of three distinct phases positions of tropical cyclones using this microwave imagery analysis is developed. S D Kotal et al., (2011) [5] proposed the

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Multi-Model Ensemble (MME) technique for predicting Table 1(a): Tropical cyclones formed over Arabian Sea [2011– track of tropical cyclones over the North Indian Sea. The 2016] MME technique for forecast latitude and longitude positions at 12 hr interval upto 72 hr forecast based on five Time Lat Long selected predictors of operational numerical weather Year Name Formed 0 Dissipated (UTC) 0N E prediction models. S D Kotal et al., (2013) [6] later by analyzing tropical cyclone genesis potential parameter for 2011 Keila 29-10-2011 06.00 13.0 62.0 04-11-2011 North Indian Sea to predict the intensity of tropical 2012 Murjan 23-10-2012 03.00 11.0 65.5 26-10-2012 cyclones at early stages of development in North Indian 2014 Nanauk 10-06-2014 09.00 15.5 68.5 14-06-2014 Sea. 2014 Nilofar 25-10-2014 00.00 12.5 61.5 31-10-2014 It has been observed that the cloud patterns and features of low-pressure storm over ARB and BOB from level 1 data are 2015 Ashobaa 07-06-2015 03.00 14.5 68.5 12-06-2015 useful for understanding: (i) the capability of the SAPHIR 2015 Chapala 28-10-2015 03.00 11.5 65.0 04-11-2015 sounder channels, (ii) find the possible, optimal bandwidth/frequencies suitable for correct measurement and 2015 Megha 05-11-2015 00.00 14.1 66.0 10-11-2015 (iii) receptivity of the sensor about 4-6 times a day. Table 1(b): Tropical cyclones formed over Arabian Sea SAPHIR level 1 data relating to ARB and BOB Basins of (coastal landfall) [2011 – 2016] North Indian Ocean has been used for our observation. Arabian Sea has a maximum width of ~2400 km and Bay of Bengal has Year Name Dissipated Landfall a maximum width of ~1610 km. The two basins have a similar 2011 Keila 04-11-2011 Extreme Eastern geographical setting, with distinctively different freshwater 2012 Murjan 26-10-2012 Bari Region of influx. Northeastern 2014 Nanauk 14-06-2014 landfall in 2014 Nilofar 31-10-2014 Gujarat coastal Disdtricts METHODOLOGY 2015 Ashobaa 12-06-2015 Oman's eastern coast-at SAPHIR metadata products named as “MT1SAPSL1A” South Sharqiyah 2015 Chapala 04-11-2015 Yemen’s Arabian Sea coast (Megha-Tropiques SAPHIR Segment-wise Level 1A) from 2011 to 2016 contains all the parameters of brightness 2015 Megha 10-11-2015 Yemen at- Island temperature temporal, humidity profile measured by all 6 channels data in HDF file format by Meteorological and Table 2(a): Tropical cyclones formed over Bay of Bengal Oceanographic Satellite Data Archival Centre (MOSDAC [2011 – 2016] ISRO Ahmedabad) (www.mosdac.gov.in) and ICARE data processing center (France www.icare.fr). SAPHIR Level-1 Time Lat Long (L1) products will be available to the users on 3 sub-levels are Year Name Formed Dissipated (UTC) 0N 0E L1A, L1A2 and L1A3. L1A data includes all the information like brightness temperature geo-tagged product, merged with 2011 Thane 25-12-2011 12.00 08.5 88.5 31-12-2011 time and location information for all channels in scan mode. 2012 Nilam 28-10-2012 06.00 09.5 86.0 01-11-2012 L1A2 brightness temperature product is in grid mode i.e., non- 2013 Viyaru 10-05-2013 09.00 05.0 92.0 17-05-2013 overlapping pixels. L1A3 is a scan mode product. Level- 1 products generally includes two types of products namely 2013 Phailin 08-10-2013 03.00 12.0 96.0 14-10-2013 segment wise (possibly exceeding one revolution, variable in 2013 Helen 19-11-2013 00.00 10.0 84.0 23-11-2013 size) and orbit wise (i.e., one revolution) [4] [12]. In this study the segment wise data samples have been used for the purpose 2013 Lehar 23-11-2013 12.00 08.5 96.5 28-11-2013 of deriving model for evaluation of cyclone life cycle of 20 2013 Madi 06-12-2013 12.00 10.0 84.0 13-12-2013 TC’s formed over ARB and BOB basins of NIO during 2011 to 2014 Hudhud 07-10-2014 03.00 11.5 95.0 14-10-2014 2016. The tropical cyclones so observed are placed in two groups as shown in Table 1(a) and (b) and Table 2 (a) and (b). 2015 Komen 26-07-2015 03.00 22.0 90.8 02-08-2015 2016 Roanu 17-05-2016 03.00 11.0 81.0 23-05-2016 2016 Kyant 21-10-2016 03.00 17.0 91.2 28-10-2016 2016 Nada 29-11-2016 12.00 10.7 80.7 02-12-2016 2016 Vardah 07-12-2016 00.00 11.2 90.5 13-12-2016

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Table 2(b): Tropical cyclones formed over Bay of Bengal 0.5 (stage 4). The cloud system has a CSC within the diameter (coastal landfall) [2011 – 2016] 2.5° latitude or less and CSC lasts for 6 hours or progressively and the cloud system region seems under less than 2° latitude from center and 1.5° latitude in diameter at that point increment Year Name Dissipated Landfall the T-number by 0.5 (stage 5). The final T-number change to Tamil Nadu Cuddalore and T1.5 during the first 24 hr of development, T2 in next 24 hr and 2011 Thane 31-12-2011 Puducherry so on, most storms reach their maximum intensity 3 to 4 days Tamil Nadu at after T-number determined (stage 6). 2012 Nilam 01-11-2012 Mahabalipuram 2013 Viyaru 17-05-2013 -at -Chittagong Andhra Pradesh at Odisha 2013 Phailin 14-10-2013 coast in Gopalpur 2013 Helen 23-11-2013 Andhra Pradesh Kakinada and 2013 Lehar 28-11-2013 Visakhapatnam Tamil Nadu -Southeastern 2013 Madi 13-12-2013 Region Andhra Pradesh coast- 2014 Hudhud 14-10-2014 Visakhapatnam Bangladesh just west of 2015 Komen 02-08-2015 Chittagong Bangladesh-North West of 2016 Roanu 23-05-2016 Chittagong weakened into a D.D. out 2016 Kyant 28-10-2016 into the sea Tamil Nadu near 2016 Nada 02-12-2016 Nagapattinam Tamil Nadu- Chennai and 2016 Vardah 13-12-2016 coastal districts

The tropical cyclone intensity estimations are generally performed by analyzing the cloud pattern formed specifically at the storm center called cyclone eye and at cyclone walls. In Figure 1: Procedure for T-number Determination order to classify the TC intensity variation, by using Dvorka procedure the particular distinctive TC numbers (or T- Numbers) are relegated relying on their intensity variations. The T (for tropical) number characterized by the cloud features of a cyclone that are related with intensity. The procedure to assign T-number of TC intensity are shown in Figure 1, i.e., intensity development and dissipation data comprises 6 stages which initially determine the TC center or eye region and its intensity at Cloud System Center (CSC) (stage 1). The earliest indications of tropical cyclone advancement are seen around 1-1.5 days before an aggravation reaches and storm strength. In microwave imaginary, if a cloud band extends in any occasion almost the way around the eye, the EYE pattern is material. A spiral cloud band wrapped Figure 2: Cloud analyzed for T-number [13] around a relative warm spot with a diameter of curvature of 1.50 latitude or less shown in Figure 2. (stage 2). The pattern of the previous 24/12 hr intensity change is resolved Multiple linear regression method has been used generally to subjectively by contrasting the cloud features of the present estimate or forecast latitude and longitude position of TC. image (stage 3). If the storm has weakened before 12/24 hr The TC location are linearly relapsed against the observed then its cloud pattern structure then decrease the T-number by latitude and longitude position individually for each forecast

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International Journal of Applied Engineering Research ISSN 0973-4562 Volume 12, Number 22 (2017) pp. 12821-12832 © Research India Publications. http://www.ripublication.com time at 12 hr intervals for the forecast up to 72 hr. The very severe cyclonic storm Vardah cyclone occurred in Multiple linear regression equation, which describes the BOB basin as shown in Figure 3(a) to 3(j) which explains the linear relationship between the set of dependent variable prediction of the cyclonic cloud pattern of the day when a (predictant) and sets of independent variables (predictors), storm is likely to reach maximum intensity from 4 to 13 Dec is given by equation (1), 2016 at 24 hr intervals shown from left to right. The cloud structure shown from left to right being analyzed shows a day- ... (1) by-day increase in the coiling of its cloud at the same rate as where y is the predictant and x1, x2, …, xn are the predictors, that depicted. consider x1 x2 x3 are SAPHIR, AMSU and IMD dataset. The linear regression model is usually expressed as regression During the pre-storm stage, the cloud structure of cyclone coefficients which are determined using developed which is defined as low pressure area on 4 Dec 2016 cyclone data set over the North Indian Ocean during pre and and intensifies continue at the rate of T0.5 to T1 on 5 Dec 2016 post monsoon season. (Kotal. S.D and Roy Bhowmik. S.K, increased by the length of the convective clouds. On 8 Dec to 9 2011). Choose different time frames to estimate the latitude Dec 2016 a tightly cloud band curvature increased by ≤ 1.50 and longitude positions analysis at the interval of latitude diameter indicates the increase intensity from T2.5 to 12,15,18,21,24,36 and 48 hours. The latitude (Lat) in 0N and T3 has been observed 24 hr to the current observation. The 0 longitude (Lon) in E are the predictants, the constant β0 and intensity of the cyclone reached T4 on 11 Dec 2016 and starts the coefficients for longitude and latitude along with too broken down the intensity after landfall in south coastal the number of samples (N) at each forecast hour are given in area of Andhra Pradesh and north coastal area of Tamil Nadu. Table 3(a) and 3(b) and the SAPHIR and AMSU position data are used as predictors. The positive coefficients are based on the how much dependent variable is expected to increase i.e., x and y changes in the same direction and if the coefficient is negative when then independent variable increase by one i.e., x and y changes in opposite directions. The above methodology has been applied to all 20 cyclones listed in Table 1 and Table 2 that occurred in ARB and BOB basin surrounding Indian sub-continent from 2011 to 2016.

Table 3(a): Regression coefficients for position of cyclones Lead Latitude N time 휷ퟎ 휷ퟏ 휷ퟐ 휷ퟑ 12 hr 105 0.7874 1.14424 -0.40512 0.0112 Figure 3(a)-(j): Vardah cyclone cloud pattern with T-no 15 hr 92 1.4971 -1.7635 0.93645 -1.1256 development. 18 hr 104 0.0442 0.2453 0.4624 -0.0952 21 hr 91 0.2686 0.1349 -0.3139 0.2091 The brightness temperature of the eye and the temperature of 24 hr 101 -0.0742 -0.0307 -0.1276 -1.2194 the clouds surrounded the eye are important in measuring the 36 hr 80 0.5078 0.9976 -0.01564 -0.1645 cyclone intensity. Comparative observation of brightness 48 hr 64 0.5207 0.9789 0.05614 -0.1284 temperature for all 20 tropical cyclones eye region during peak intensity from all the six channels (Ch1 to Ch6) of SAPHIR

sounder, where channel Ch6 is found to be suitable for Table 3(b): Regression coefficients for position of cyclones detection of TC and its intensity variation. Analysis of satellite Lead Longitude imagery with brightness temperature (K), left to right shows N time the SAPHIR channels from Ch1 to Ch6 and first column top to bottom shows the cyclones from 1 to 7 cyclones occurred in 12 hr 105 0.3682 -0.4498 -0.8321 0.7940 ARB basin shown in Figure 4 and 8 to 20 cyclones occurred in 15 hr 92 1.8554 1.6295 0.61649 -1.1503 BOB basin shown in Figure 5 with respect to T-number. The 18 hr 104 0.1518 0.3463 0.2823 0.3356 21 hr 91 0.8525 0.1660 0.2434 -0.0802 corresponding cyclones are occurred over Arabian Sea 24 hr 101 0.8821 0.8027 0.57793 -0.4609 (during 2011 to 2016) are (1) TC- Keila, ARB basin, T-2.5; (2) 36 hr 80 5.3802 0.0669 -0.9126 0.48339 TC-Murjan, ARB basin, T-2.5; (3) TC-Nanauk, ARB basin, T- 48 hr 64 3.0610 0.5568 -0.2301 0.02481 3; (4) TC-Nilofar, ARB basin, T-5.5; (5) TC-Ashobaa, ARB basin, T-3; (6) TC-Chapala, ARB basin, T-6; and (7) TC- Megha, ARB basin, T-5;

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The cyclones occurred over Bay of Bengal (during 2011 to T-4; (15) TC-Hudhud, BOB basin, T-5; (16) TC-Komen, BOB 2016) are (8) TC-Thane, BOB basin, T-4; (9) TC-Nilam, BOB basin, T-2.5; (17) TC-Roanu, BOB basin, T-3; (18) TC- Kyant, basin, T-3; (10) TC-Viyaru, BOB basin, T-3.5; (11) TC- BOB basin, T-3.5; (19) TC-Nada, BOB basin, T-3.5; (20) TC- Phailin, BOB basin, T-6; (12) TC-Helen, BOB basin, T-3.5; Vardah, BOB basin, T-4.5. (13) TC-Lehar, BOB basin, T-4; (14) TC-Madi, BOB basin,

(a) Ch1 (b) Ch2 (c) Ch3 (d) Ch4 (e) Ch5 (f) Ch6 Figure 4(a)-(f): Analysis of 7 cyclones occurred in ARB using SAPHIR sensor (Ch1 to Ch6)

Table 4(b): Comparison of cyclone location Table 4(a): Comparison of cyclone location (latitude) (Longitude) occurred in ARB basin observed by occurred in ARB basin observed by SAPHIR with IMD SAPHIR with IMD and RAMMB and RAMMB TC Peak Lead 0 Peak Lead 0 Longitude ( E) TC Latitude ( N) Name Intensity Time Intensity Time SAPHIR IMD RAMMB Name SAPHIR IMD RAMMB Date UTC Date UTC Keila 2011-11-02 12.00 54.2 54.5 55.0 Keila 2011-11-02 12.00 16.3 16.5 17.0 Murjan 2012-10-24 18.00 10.2 10.5 10.5 Murjan 2012-10-24 18.00 55.0 55.5 55.3 Nanauk 2014-06-11 06.00 16.5 16.9 16.9 Nanauk 2014-06-11 06.00 66.38 66.7 66.7 Nilofar 2014-10-28 12.00 16.5 16.7 16.8 Nilofar 2014-10-28 12.00 61.7 61.8 61.8 Ashobaa 2015-06-10 06.00 21.0 21.3 21.1 Ashobaa 2015-06-10 06.00 61.4 61.5 61.5 Chapala 2015-10-30 09.00 14.0 14.2 14.2 Chapala 2015-10-30 09.00 60.5 60.8 61.1 Megha 2015-11-08 03.00 12.4 12.7 12.8 Megha 2015-11-08 03.00 55.2 55.6 56.1

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Table 5(a): Comparison of cyclone location (latitude) occurred in BOB basin observed by SAPHIR with IMD and RAMMB

Peak Lead Latitude (0N) TC Intensity Time Name Date UTC SAPHIR IMD RAMMB Thane 2011-12-28 12.00 12.4 12.5 12.0

Nilam 2012-10-31 09.00 11.2 11.5 12.0

Viyaru 2013-05-15 18.00 18.9 19.0 19.6

Phailin 2013-10-11 00.00 15.8 16.0 15.8 Helen 2013-11-22 03.00 16.0 16.2 16.2 Lehar 2013-11-25 21.00 12.3 12.5 12.2

Madi 2013-12-08 15.00 9.8 10.0 13.0

Hudhud 2014-10-11 18.00 16.2 16.4 16.6 Komen 2015-07-30 00.00 21.5 21.7 NA Roanu 2016-05-21 06.00 19.80 21.9 22.0 Kyant 2016-10-26 03.00 16.4 16.6 16.6 Nada 2013-12-30 03.00 08.0 08.2 08.6 Vardha 2016-12-11 06.00 13.0 13.3 12.9

Table 5(b): Comparison of cyclone location (longitude) occurred in BOB basin observed by SAPHIR with IMD and RAMMB

TC Peak Lead Longitude (0E) Name Intensity Time SAPHIR IMD RAMMB Date UTC Thane 2011-12-28 12.00 84.4 84.5 84.1 Nilam 2012-10-31 09.00 80.8 81.0 81.1 Viyaru 2013-05-15 18.00 88.4 88.5 89.1 Phailin 2013-10-11 00.00 88.4 88.5 88.8 Helen 2013-11-22 03.00 81.5 81.7 82.0 Lehar 2013-11-25 21.00 91.0 91.0 91.1 Madi 2013-12-08 15.00 84.0 84.0 84.8 Hudhud 2014-10-11 18.00 84.3 84.7 84.6 Komen 2015-07-30 00.00 91.0 91.2 NA Roanu 2016-05-21 06.00 93.83 91.0 91.0 Kyant 2016-10-26 03.00 88.2 88.5 88.5 Nada 2013-12-30 03.00 85.1 85.3 85.7 Vardha 2016-12-11 06.00 82.8 83.0 83.7

(a) Ch1 (b) Ch2 (c) Ch3 (d) Ch4 (e) Ch5 (f) Ch6 Figure 5(a)-(f): Analysis of 13 cyclones occurred in BOB using SAPHIR sensor (Ch1 to Ch6).

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Comparison of TC latitude and longitude position of the peak intensity day with respect to lead time which is observed by SAPHIR compared with TC position reported by IMD (Indian Meteorological Department) and RAMMB (Regional and Mesoscale Meteorology Branch) tabulated in Table 4(a) and Table 4(b) for ARB basin and Table 5(a) and Table 5(b) for BOB basin. The observation shows only marginal variation of mean error 0.2 to 0.3 degrees which may be due to in situ corrections and different algorithms made by the respective departments.

RESULTS AND DISCUSSION Figure 7(b): Brightness temperature variation of Cyclonic storm Ashobaa during 6 to 13 June 2015 In this section a detailed analysis of tracking the life cycle of TC using SAPHIR sounder scientific data with respect to

latitude and longitude position path have been discussed. The cyclone path of cyclonic storm Ashobaa (2015) and Figure 7(a) shows latitude v/s longitude track of the cyclonic cyclonic storm Nanauk (2014) (occurred in ARB basin) and storm Ashobaa occurred during 7 to 13 June 2015. The area of 0 0 0 2 cyclones occurred in BOB basin cyclonic storm Roanu cyclone occurred from 13.5 N to 20.9 N latitude and 69.6 E to 0 and very severe cyclonic storm Vardah (over BOB basin) 56.2 E longitude started from east central Arabian Sea and cyclones from the stage of genesis up to the stage of weakened towards north eastwards towards Oman costal before dissipation/landfall has been graphically shown in Figure 6. landfall. Figure 7(b) shows the variation in brightness temperature observed by SAPHIR sensor before cyclone eye formed and weakened towards northeastwards area i.e., from 6 to 13 June 2015. On 8 June 2015 the TB reaches to minimum of 97.4K lowest temperature and moving towards Oman costal cyclone weakened and it reaches back to normal temperature i.e., 177K on 13 June 2015.

Figure 6: Track of cyclones in Arabian Sea and Bay of Bengal basin

Figure 8(a): Cyclonic storm Nanauk path during 8 to 15 June

2014

Figure 7(a): Cyclonic storm Ashobaa path during 7 to 13 June 2015 12827

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Figure 8(b): Brightness temperature variation of Cyclonic storm Nanauk during 8 to 15 June 2014

Figure 9(b): Brightness temperature variation of cyclonic Figure 8(a) shows latitude v/s longitude track of cyclonic storm Roanu during 14 to 22 May 2016 storm Nanauk during 8 to 15 June 2014. The area of cyclone occurred from 14.090N to 20.050N latitude and 67.90E to 62.60E longitude started from east central Arabian Sea, Figure 9(a) shows latitude v/s longitude track of cyclonic moving towards northwestwards get intensified and weakened storm Roanu occurred from 14 May to 22 May 2016. The area towards west central Arabian Sea. Figure 8(b) shows the of cyclone occurred from 8.40N to 23.060N latitude and 800E variation in brightness temperature before cyclone eye formed to 91.680E longitude started from southwest Bay of Bengal off and weakened towards west central of Arabian Sea region i.e., Sri Lanka coast and weakened towards north eastwards from 8 to 15 June 2014. From 8 June to 15 June low pressure towards Manipur. Figure 9(b) shows the variation in cloud circulation area started in Arabian Sea and reaches the brightness temperature, where TB reaches to minimum of complete eye, at a minimum temperature of 93.6K, moving 76.36K lowest temperature on 20 May, moving towards towards west central Arabian Sea weakened and reaches back Manipur cyclone weakened and it reaches back to normal to normal temperature i.e., 132.9 K on 15 June 2014. temperature i.e., 151.32K on 22 May 2016.

Figure 10(a) shows the VSCS Vardha cyclone tracking path during 3 Dec 2016 (genesis) to 13 Dec 2016 (dissipated). The area of cyclone occurred from 5.60N to 160N latitude and 97.70E to 80.030E longitude started from south Andaman Sea and adjoining southeast Bay of Bengal and weekend towards westwards after landfall and crossed north Tamil Nadu coast. Variation of VSCS Vardah brightness temperature observed by SAPHIR shown in Figure 10(b), where on 11 Dec 2016 the TB reaches to 91K lowest temperature and after landfall near Tamil Nadu coast it reaches back to normal temperature i.e., 177.2K.

Figure 9(a): Cyclonic storm Roanu path during 14 to 22 May 2016

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Figure 10(a): Very Severe Cyclonic Storm (VSCS) Vardah path during 3 to 13 Dec 2017

(e) Cyclone – Ashobaa (2015) (f) Cyclone – Chapala (2015)

Figure 10(b): Brightness temperature variation of Very Severe Cyclonic Storm (VSCS) Vardah during 3 to 13 Dec 2017 Figure 11(a)-(h): TC occurred in Arabian Sea during 2011- 2016 (SAPHIR)

Figure 11(a) to 11(h) shows the progressive development of tropical cyclone eye by using SAPHIR brightness temperature dataset from cyclone genesis to dissipation occurred in ARB basin and Figure 12(a) to 12(m) cyclone occurred in BOB basin of north Indian Ocean during 2011 to 2016. The cloud band structure variations observed from lead time of 24 hrs interval based on cyclonic rotation of cloud eye wall area. A CSC is noticed with respect to time variation from genesis to dissipation as the cloud curvature band increased from day-to- day.

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Figure 12 (a)-(m): TC occurred in Bay of Bengal during 2011 to 2016 (SAPHIR)

From the Table 4(a), 4(b), 5(a) and 5(b), SAPHIR dataset has been compared with IMD and AMSU dataset in tracking cyclone shows the small variation of 0.2 to 0.3 degrees

variations seen in Figure 13(a) cyclonic storm Ashobaa occurred from 6 to 13 June 2015 in Arabian Sea basin and Figure 13(b) cyclonic storm Roanu during 17 to 22 May 2016 in Bay of Bengal basin from genesis to dissipation of cyclone.

CONCLUSION For our study we have selected the TC occurred in ARB and BOB basin of North Indian Ocean during 2011 to 2016. Among 20 cyclones considered for this study, the duration (from genesis to landfall and/or dissipation) of 16 cyclones was 144 hours (from genesis to landfall and/or dissipation) and out of 16 cyclones 04 cyclones (cyclones like Vardah, Hudhud, Viyaru, Madi) was 172 hours. The graphical representation of life cycle of all 20 tropical cyclones (from genesis to dissipation) occurred in Arabian Sea and Bay of Bengal basin over the Indian sub-continent has been made using SAPHIR level 1 brightness temperature data. By using brightness temperature data of all six channels of SAPHIR sounder sensor, observation of eye region (at the time of cyclone genesis, at the time of attaining peak intensity and at the time of variation in intensity) of all 20 cyclones selected for our study has been made. For every 12 hours observation of eye region, classification of eye region according to pattern recognition described in Dvorak technique has been applied to microwave SAPHIR sounder

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images also. In the next step we have observed and recorded the latitude and longitude positions of cyclone eye region. Thereafter, by considering latitude and longitude positions and by using multiple linear regression models we predicted the movement of cyclone. Our near real time examination affirm that, by using SAPHIR level 1 brightness temperature data, observation of eye wall region, classification of cyclone eye region is more accurate and useful in tracking the life cycle of tropical cyclones. In addition the orbital position of Megha Tropiques will prove the quantitative improvement in real time information. The graphical representation of tracking the life cycle of all 20 tropical cyclones occurred in Arabian Sea and Bay of Bengal basin over the Indian sub-continent using SAPHIR level 1 Figure 13(b): Tracking of Roanu cyclone comparison from brightness temperature data as observed from genesis to SAPHIR, IMD and AMSU dataset occurred in BOB (2016) dissipation is shown in Figure 11 and Figure 12.

ACKNOWLEDGEMENT The authors would like to express their sincere gratitude to Indian Space Research Organization (ISRO) MOSDAC for providing SAPHIR sensor dataset and ICARE France. The authors also thank the Dr. Keshavan and Dr. Thangadurai.N Jain University for their valuable suggestions which led to the improvement of the manuscript.

REFERENCES [1] Aguttes. J.P, Schrive. J, Goldstein. C, Rouzé. M and Raju. G, “Megha-Tropiques a Satellite for Studying the Water Cycle and Energy Exchanges in the Tropiques”, IEEE Proceedings of International Conference of Figure 13(a): Tracking of Ashobaa cyclone comparison from Geoscience Remote Sensing Symposium, 7, 3042-3044, SAPHIR, IMD and AMSU dataset occurred in ARB (2015) 2000.

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