observation of cyclone occurred in arabian sea and bay of ...megha-tropiques was launched in...

International Journal of Applied Engineering Research ISSN 0973-4562 Volume 12, Number 22 (2017) pp. 12821-12832

© Research India Publications. http://www.ripublication.com

12821

Observation of Cyclone Occurred in Arabian Sea 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

The evaluation of life cycle of tropical cyclone using satellite

data means and includes analysis of genesis, development and

its intensity variations. Sondeur Atmosphérique du Profil

d’Humidité Intertropicale par Radiométrie (SAPHIR)

microwave sounder on-board Megha-Tropiques satellite

operating at high resolution of 10 km nadir with six frequency

channels at 183.31±11.0 GHz has been used as one of ocean

application using satellite data applicable for observation of life

cycle of tropical cyclone. This analysis has been done by

utilizing SAPHIR brightness temperature dataset to all 20

tropical cyclones occurred from 2011 to 2016 in Arabian Sea

and Bay of Bengal basin over the North Indian Ocean.

Comparison of the 6 channels of SAPHIR shows the clear

variations of cyclone eye under various conditions. Further the

exceptional highlights of this study are SAPHIR sounder data

will demonstrate quantitative and subjective improvement in

acquiring near real time information identifying with (i)

latitude and longitude position of cyclone path (ii) cloud

features of cyclone eye center (iii) cloud features of tropical

cyclone eye wall formation. Our comparative study shows the

possibility of using SAPHIR sounder data to identify the eye

center positions of tropical cyclones, and also possibility of

using the Dvorak method for estimation of cyclone intensity.

Our near real time examination will additionally affirm that the

positional variations in life cycle of tropical cyclone (from

genesis to dissipation/landfall) can be obtained by using

multiple linear regression models. A comparative analysis of

SAPHIR dataset, Indian Meteorological Department (IMD)

dataset and Advance Microwave Sounding Unit (AMSU)

sounder dataset show positional variations of tropical cyclone,

ranging from 0.2 to 0.3 degrees (latitude/longitude).

Keywords: Brightness Temperature, SAPHIR sounder,

Tropical Cyclone, Cyclone track, Megha - Tropiques.

INTRODUCTION

Tropical cyclone is generally explained as a rotating, organized

low-pressure system of clouds and thunderstorms over tropical

waters. It consists of three distinct phases

namely, genesis, intensification and land-fall. During the last

several years, due to non availability of conventional

observations over the sea surface, satellite data are used by

researchers to study and understand tropical cyclogenesis. It is

observed that about 4.8% of tropical cyclones around the

world are developed in Arabian Sea (ARB) basin and Bay of

Bengal (BOB) basins of North Indian Ocean (NIO). Passive

microwave sensors have been used for oceanographic

applications starting from past 4 decades (from SEASAT,

SSMI, MHS, HSB, AMSU-A & B, SAPHIR) [3]. When

compared to visible or infrared observations, the main

advantages of microwave sounder observations is microwave

radiation can sense severe storms and tropical cyclones

through the cloud-covered areas without atmospheric

attenuations.

Satellite observation from microware radiometer plays a major

role in early detection of TC, its development and landfall.

The TC genesis and intensity is observed from TC Eye

position and associated Maximum Sustainable wind speed

measured according to IMD standards [2]. SAPHIR onboard

Megha-Tropiques (MT) satellite has a good spatial resolution

of 10 km at nadir and 14 km at edge and a swath of ~2060 km.

Megha-Tropiques was launched in near-circular inclined orbit

of 200 on 12 October 2011 [8][9] and giving high-quality

information identified with ocean surface [1], atmospheric

humidity profile and land-related application. It is also

observed that Level 1 (L1) data of SAPHIR sounder can be

used for observation and tracking of TC over ARB and BOB

Basins of NIO [11]. Observation of cloud patterns and features

of low-pressure storm over ARB and BOB by microwave

sounder instrument aboard satellites is becoming increasingly

important. It is possible that SAPHIR sounder L1 data can also

be used to explain the observed intensity and structure changes

of tropical cyclones. Velden. C et.al., (2007) [7][13], Julie L.

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

AMSU data it is possible to estimate the tropical cyclone eye

size and intensity. Shuuji Nishimura et.al, (2008) [10] an

enhanced form of Dvorak technique foranalyzing center

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

track of tropical cyclones over the North Indian Sea. The

MME technique for forecast latitude and longitude

positions at 12 hr interval upto 72 hr forecast based on five

selected predictors of operational numerical weather

prediction models. S D Kotal et al., (2013) [6] later by

analyzing tropical cyclone genesis potential parameter for

North Indian Sea to predict the intensity of tropical

cyclones at early stages of development in North Indian

Sea.

It has been observed that the cloud patterns and features of

low-pressure storm over ARB and BOB from level 1 data are

useful for understanding: (i) the capability of the SAPHIR

sounder channels, (ii) find the possible, optimal

bandwidth/frequencies suitable for correct measurement and

(iii) receptivity of the sensor about 4-6 times a day.

SAPHIR level 1 data relating to ARB and BOB Basins of

North Indian Ocean has been used for our observation. Arabian

Sea has a maximum width of ~2400 km and Bay of Bengal has

a maximum width of ~1610 km. The two basins have a similar

geographical setting, with distinctively different freshwater

influx.

METHODOLOGY

SAPHIR metadata products named as “MT1SAPSL1A”

(Megha-Tropiques SAPHIR Segment-wise Level 1A) from

2011 to 2016 contains all the parameters of brightness

temperature temporal, humidity profile measured by all 6

channels data in HDF file format by Meteorological and

Oceanographic Satellite Data Archival Centre (MOSDAC

ISRO Ahmedabad) (www.mosdac.gov.in) and ICARE data

processing center (France www.icare.fr). SAPHIR Level-1

(L1) products will be available to the users on 3 sub-levels are

L1A, L1A2 and L1A3. L1A data includes all the information

like brightness temperature geo-tagged product, merged with

time and location information for all channels in scan mode.

L1A2 brightness temperature product is in grid mode i.e., non-

overlapping pixels. L1A3 is a scan mode product. Level- 1

products generally includes two types of products namely

segment wise (possibly exceeding one revolution, variable in

size) and orbit wise (i.e., one revolution) [4] [12]. In this study

the segment wise data samples have been used for the purpose

of deriving model for evaluation of cyclone life cycle of 20

TC’s formed over ARB and BOB basins of NIO during 2011 to

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).

Table 1(a): Tropical cyclones formed over Arabian Sea [2011–

2016]

Year Name Formed Time

(UTC) Lat

0N

Long 0E

Dissipated

2011 Keila 29-10-2011 06.00 13.0 62.0 04-11-2011

2012 Murjan 23-10-2012 03.00 11.0 65.5 26-10-2012

2014 Nanauk 10-06-2014 09.00 15.5 68.5 14-06-2014

2014 Nilofar 25-10-2014 00.00 12.5 61.5 31-10-2014

2015 Ashobaa 07-06-2015 03.00 14.5 68.5 12-06-2015

2015 Chapala 28-10-2015 03.00 11.5 65.0 04-11-2015

2015 Megha 05-11-2015 00.00 14.1 66.0 10-11-2015

Table 1(b): Tropical cyclones formed over Arabian Sea

(coastal landfall) [2011 – 2016]

Year Name Dissipated Landfall

2011 Keila 04-11-2011 Extreme Eastern Yemen

2012 Murjan 26-10-2012 Bari Region of Northeastern Somalia

2014 Nanauk 14-06-2014 landfall in Oman

2014 Nilofar 31-10-2014 Gujarat coastal Disdtricts

2015 Ashobaa 12-06-2015 Oman's eastern coast-at

South Sharqiyah

2015 Chapala 04-11-2015 Yemen’s Arabian Sea coast

2015 Megha 10-11-2015 Yemen at-Socotra Island

Table 2(a): Tropical cyclones formed over Bay of Bengal

[2011 – 2016]

Year Name Formed Time

(UTC)

Lat 0N

Long 0E

Dissipated

2011 Thane 25-12-2011 12.00 08.5 88.5 31-12-2011

2012 Nilam 28-10-2012 06.00 09.5 86.0 01-11-2012

2013 Viyaru 10-05-2013 09.00 05.0 92.0 17-05-2013

2013 Phailin 08-10-2013 03.00 12.0 96.0 14-10-2013

2013 Helen 19-11-2013 00.00 10.0 84.0 23-11-2013

2013 Lehar 23-11-2013 12.00 08.5 96.5 28-11-2013

2013 Madi 06-12-2013 12.00 10.0 84.0 13-12-2013

2014 Hudhud 07-10-2014 03.00 11.5 95.0 14-10-2014

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

(coastal landfall) [2011 – 2016]

Year Name Dissipated Landfall

2011 Thane 31-12-2011 Tamil Nadu Cuddalore and

Puducherry

2012 Nilam 01-11-2012 Tamil Nadu at

Mahabalipuram

2013 Viyaru 17-05-2013 Bangladesh-at -Chittagong

2013 Phailin 14-10-2013 Andhra Pradesh at Odisha

coast in Gopalpur

2013 Helen 23-11-2013 Andhra Pradesh

2013 Lehar 28-11-2013 Kakinada and

Visakhapatnam

2013 Madi 13-12-2013 Tamil Nadu -Southeastern

Region

2014 Hudhud 14-10-2014 Andhra Pradesh coast-

Visakhapatnam

2015 Komen 02-08-2015 Bangladesh just west of

Chittagong

2016 Roanu 23-05-2016 Bangladesh-North West of

Chittagong

2016 Kyant 28-10-2016 weakened into a D.D. out

into the sea

2016 Nada 02-12-2016 Tamil Nadu near

Nagapattinam

2016 Vardah 13-12-2016 Tamil Nadu- Chennai and

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

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

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

subjectively by contrasting the cloud features of the present

image (stage 3). If the storm has weakened before 12/24 hr

then its cloud pattern structure then decrease the T-number by

0.5 (stage 4). The cloud system has a CSC within the diameter

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

the T-number by 0.5 (stage 5). The final T-number change to

T1.5 during the first 24 hr of development, T2 in next 24 hr and

so on, most storms reach their maximum intensity 3 to 4 days

after T-number determined (stage 6).

Figure 1: Procedure for T-number Determination

Figure 2: Cloud analyzed for T-number [13]

Multiple linear regression method has been used generally to

estimate or forecast latitude and longitude position of TC.

The TC location are linearly relapsed against the observed

latitude and longitude position individually for each forecast




12824

time at 12 hr intervals for the forecast up to 72 hr.

Multiple linear regression equation, which describes the

linear relationship between the set of dependent variable

(predictant) and sets of independent variables (predictors),

is given by equation (1),

... (1)

where y is the predictant and x1, x2, …, xn are the predictors,

consider x1 x2 x3 are SAPHIR, AMSU and IMD dataset. The

linear regression model is usually expressed as regression

coefficients which are determined using

cyclone data set over the North Indian Ocean during pre and

post monsoon season. (Kotal. S.D and Roy Bhowmik. S.K,

2011). Choose different time frames to estimate the latitude

and longitude positions analysis at the interval of

12,15,18,21,24,36 and 48 hours. The latitude (Lat) in 0N and

longitude (Lon) in 0E are the predictants, the constant β0 and

the coefficients for longitude and latitude along with

the number of samples (N) at each forecast hour are given in

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

time N

Latitude

𝜷𝟎 𝜷𝟏 𝜷𝟐 𝜷𝟑

12 hr 105 0.7874 1.14424 -0.40512 0.0112

15 hr 92 1.4971 -1.7635 0.93645 -1.1256

18 hr 104 0.0442 0.2453 0.4624 -0.0952

21 hr 91 0.2686 0.1349 -0.3139 0.2091

24 hr 101 -0.0742 -0.0307 -0.1276 -1.2194

36 hr 80 0.5078 0.9976 -0.01564 -0.1645

48 hr 64 0.5207 0.9789 0.05614 -0.1284

Table 3(b): Regression coefficients for position of cyclones

Lead

time N

Longitude

12 hr 105 0.3682 -0.4498 -0.8321 0.7940

15 hr 92 1.8554 1.6295 0.61649 -1.1503

18 hr 104 0.1518 0.3463 0.2823 0.3356

21 hr 91 0.8525 0.1660 0.2434 -0.0802

24 hr 101 0.8821 0.8027 0.57793 -0.4609

36 hr 80 5.3802 0.0669 -0.9126 0.48339

48 hr 64 3.0610 0.5568 -0.2301 0.02481

The very severe cyclonic storm Vardah cyclone occurred in

BOB basin as shown in Figure 3(a) to 3(j) which explains the

prediction of the cyclonic cloud pattern of the day when a

storm is likely to reach maximum intensity from 4 to 13 Dec

2016 at 24 hr intervals shown from left to right. The cloud

structure shown from left to right being analyzed shows a day-

by-day increase in the coiling of its cloud at the same rate as

that depicted.

During the pre-storm stage, the cloud structure of cyclone

developed which is defined as low pressure area on 4 Dec 2016

and intensifies continue at the rate of T0.5 to T1 on 5 Dec 2016

increased by the length of the convective clouds. On 8 Dec to 9

Dec 2016 a tightly cloud band curvature increased by ≤ 1.50

latitude diameter indicates the increase intensity from T2.5 to

T3 has been observed 24 hr to the current observation. The

intensity of the cyclone reached T4 on 11 Dec 2016 and starts

too broken down the intensity after landfall in south coastal

area of Andhra Pradesh and north coastal area of Tamil Nadu.

Figure 3(a)-(j): Vardah cyclone cloud pattern with T-no

development.

The brightness temperature of the eye and the temperature of

the clouds surrounded the eye are important in measuring the

cyclone intensity. Comparative observation of brightness

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

detection of TC and its intensity variation. Analysis of satellite

imagery with brightness temperature (K), left to right shows

the SAPHIR channels from Ch1 to Ch6 and first column top to

bottom shows the cyclones from 1 to 7 cyclones occurred in

ARB basin shown in Figure 4 and 8 to 20 cyclones occurred in

BOB basin shown in Figure 5 with respect to T-number. The

corresponding cyclones are occurred over Arabian Sea

(during 2011 to 2016) are (1) TC- Keila, ARB basin, T-2.5; (2)

TC-Murjan, ARB basin, T-2.5; (3) TC-Nanauk, ARB basin, T-

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

2016) are (8) TC-Thane, BOB basin, T-4; (9) TC-Nilam, BOB

basin, T-3; (10) TC-Viyaru, BOB basin, T-3.5; (11) TC-

Phailin, BOB basin, T-6; (12) TC-Helen, BOB basin, T-3.5;

(13) TC-Lehar, BOB basin, T-4; (14) TC-Madi, BOB basin,

T-4; (15) TC-Hudhud, BOB basin, T-5; (16) TC-Komen, BOB

basin, T-2.5; (17) TC-Roanu, BOB basin, T-3; (18) TC- Kyant,

BOB basin, T-3.5; (19) TC-Nada, BOB basin, T-3.5; (20) TC-

Vardah, BOB basin, T-4.5.

(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(a): Comparison of cyclone location (latitude)

occurred in ARB basin observed by SAPHIR with IMD

and RAMMB

TC

Name

Peak

Intensity

Date

Lead

Time

UTC

Latitude (0N)

SAPHIR IMD RAMMB

Keila 2011-11-02 12.00 16.3 16.5 17.0

Murjan 2012-10-24 18.00 10.2 10.5 10.5

Nanauk 2014-06-11 06.00 16.5 16.9 16.9

Nilofar 2014-10-28 12.00 16.5 16.7 16.8

Ashobaa 2015-06-10 06.00 21.0 21.3 21.1

Chapala 2015-10-30 09.00 14.0 14.2 14.2

Megha 2015-11-08 03.00 12.4 12.7 12.8

Table 4(b): Comparison of cyclone location

(Longitude) occurred in ARB basin observed by

SAPHIR with IMD and RAMMB

TC

Name

Peak

Intensity

Date

Lead

Time

UTC

Longitude (0E)

SAPHIR IMD RAMMB

Keila 2011-11-02 12.00 54.2 54.5 55.0

Murjan 2012-10-24 18.00 55.0 55.5 55.3

Nanauk 2014-06-11 06.00 66.38 66.7 66.7

Nilofar 2014-10-28 12.00 61.7 61.8 61.8

Ashobaa 2015-06-10 06.00 61.4 61.5 61.5

Chapala 2015-10-30 09.00 60.5 60.8 61.1

Megha 2015-11-08 03.00 55.2 55.6 56.1




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(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).

Table 5(a): Comparison of cyclone location

(latitude) occurred in BOB basin observed by


TC

Name

Peak

Intensity

Date

Lead

Time

UTC

Latitude (0N)

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


TC

Name

Peak

Intensity

Date

Lead

Time

UTC

Longitude (0E)

SAPHIR IMD RAMMB

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




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a

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

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

cyclonic storm Nanauk (2014) (occurred in ARB basin) and

2 cyclones occurred in BOB basin cyclonic storm Roanu

and very severe cyclonic storm Vardah (over BOB basin)

cyclones from the stage of genesis up to the stage of

dissipation/landfall has been graphically shown in Figure 6.

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

basin

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

June 2015

Figure 7(b): Brightness temperature variation of Cyclonic

storm Ashobaa during 6 to 13 June 2015

Figure 7(a) shows latitude v/s longitude track of the cyclonic

storm Ashobaa occurred during 7 to 13 June 2015. The area of

cyclone occurred from 13.50N to 20.90N latitude and 69.60E to

56.20E longitude started from east central Arabian Sea and

weakened towards north eastwards towards Oman costal before

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

2014




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Figure 8(b): Brightness temperature variation of Cyclonic

storm Nanauk during 8 to 15 June 2014

Figure 8(a) shows latitude v/s longitude track of cyclonic

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,

moving towards northwestwards get intensified and weakened

towards west central Arabian Sea. Figure 8(b) shows the

variation in brightness temperature before cyclone eye formed

and weakened towards west central of Arabian Sea region i.e.,

from 8 to 15 June 2014. From 8 June to 15 June low pressure

cloud circulation area started in Arabian Sea and reaches the

complete eye, at a minimum temperature of 93.6K, moving

towards west central Arabian Sea weakened and reaches back

to normal temperature i.e., 132.9 K on 15 June 2014.

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

May 2016

Figure 9(b): Brightness temperature variation of cyclonic

storm Roanu during 14 to 22 May 2016

Figure 9(a) shows latitude v/s longitude track of cyclonic

storm Roanu occurred from 14 May to 22 May 2016. The area

of cyclone occurred from 8.40N to 23.060N latitude and 800E

to 91.680E longitude started from southwest Bay of Bengal off

Sri Lanka coast and weakened towards north eastwards

towards Manipur. Figure 9(b) shows the variation in

brightness temperature, where TB reaches to minimum of

76.36K lowest temperature on 20 May, moving towards

Manipur cyclone weakened and it reaches back to normal

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.




12831

Figure 10(a): Very Severe Cyclonic Storm (VSCS)

Vardah path during 3 to 13 Dec 2017

Figure 10(b): Brightness temperature variation of Very

Severe Cyclonic Storm (VSCS) Vardah during 3 to 13

Dec 2017

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

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.




12832

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

brightness temperature data as observed from genesis to

dissipation is shown in Figure 11 and Figure 12.

Figure 13(a): Tracking of Ashobaa cyclone comparison from

SAPHIR, IMD and AMSU dataset occurred in ARB (2015)

A comparison of brightness temperature profile of SAPHIR

acquired from all six channels demonstrates that channel six is

observed to be appropriate for location of TC and its intensity

variations. The cyclone positions obtained from multiple

linear regression method has been analyzed and is as shown in

the Figure 13 (a) and (b) where SAPHIR data has been

contrasted with the position by IMD information and AMSU

sounder demonstrates the variety extending from 0.2 to 0.3

degrees has been identified. This data can be efficiently used

for tracking cyclone with a minimal application.

Figure 13(b): Tracking of Roanu cyclone comparison from

SAPHIR, IMD and AMSU dataset occurred in BOB (2016)

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.

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