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India Meteorological Department (IMD) categorises the tropical cyclones (TCs) as cyclonic storm (CS), severe cyclonic storm (SCS), very severe cyclonic storm (VSCS), extremely severe cyclonic storm (ESCS) and super cyclonic storm (SuCS). The long term climatology of TCs in these categories and the trends in frequency and intensity of TCs in these categories developing over the NIO and crossing different coastal regions are limited. Hence a study has been undertaken to analyse the characteristics of genesis and intensification of CDs in the above categories developing over the NIO and crossing different coastal regions based on the data of satellite era (1965-2020). The most intense TCs (ESCS & above) cross the coast maximum over Odisha (ODS) followed by Andhra Pradesh (AP)/Myanmar (MMR) & Bangladesh (BDS) and low intensity TCs (CS/SCS) cross maximum over BDS followed by AP, ODS & Tamilnadu (TN) and medium intensity TCs (VSCS) cross maximum over TN/AP/BDS followed by ODS/West Bengal (WB)/MMR during a year as a whole. While maximum CS/SCS cross BDS, maximum VSCS cross BDS/MMR and maximum ESCS cross MMR coast during pre-monsoon season. While maximum CS/SCS/VSCS cross AP coast, maximum ESCS cross ODS coast during post monsoon season. Over the AS, the landfall frequency of VSCS is maximum over Arabia - Africa (AA) coast followed by Saurashtra and Kutch coast. The coastal vulnerability due to ESCS continues over the Bay of Bengal (BoB) region, as there is no significant trend in the frequency of genesis of ESCS and above intensity storms, though there is decreasing trend in the genesis frequency of D/DD, CS, SCS, VSCS over the BoB. It has increased over the AA coast due to increasing trend in frequency of genesis of VSCS and above intensity storms over Arabian Sea.
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MAUSAM, 72, 1 (January 2021), 1-26
551.515.2 (267)
(1)
Frequency of genesis and landfall of different categories of tropical cyclones
over the North Indian Ocean
MRUTYUNJAY MOHAPATRA, MONICA SHARMA, SUNITHA S. DEVI,
S. V. J. KUMAR and BHARATI S. SABADE
India Meteorological Department, Ministry of Earth Sciences, New Delhi – 110 003, India
e mail : m.mohapatra@imd.gov.in
   󰫥  (IMD)󰬍󰲐 󰬴󰰣 (TCs)  󰬴  (CS), 󰭈 󰬴 
(SCS),  󰭈 󰬴  (VSCS), 󰫽 󰭈 󰬴  (ESCS)  󰬴  (SuCS) 󰲒 󰭑󰰣 󰰗
󰰏   󰭑󰰣 󰰗 󰬍󰲐 󰬴󰰣  󰫦  󰫥  󰰌 󰲓  (NIO) 
   󰱷  󰫤󰭃󰰣      󰭑󰰣 󰰗 󰬍󰲐 󰬴󰰣 󰲒 󰰌  󰭐 󰲒 󰭈󰰌
 󰰚  󰬶  (1965-2020)  󰰣    󰰌 󰲓  (NIO) 󰰗 󰫦󰱇 󰭑󰰣 󰰗 󰬴 󰫤󰰣
󰲒 󰫽󰰌  󰭐  󰱷  󰫤󰭃󰰣    󰲒 󰰱  󰲄    󰬀 󰲑  
 󰫦    󰭐 󰬍󰲐 󰬴 (ESCS    󰭐)   (ODS)   
󰭆 󰭈 (AP)/󰬆 (MMR)  󰫰 (BDS)    󰰚,   󰭐  󰬍󰲐 󰬴 (CS/SCS)
 BDS    AP, ODS   (TN)    󰰚,  󰬀 󰭐  󰬍󰲐 󰬴
(VSCS)  TN / AP/ BDS    ODS / WB / MMR   󰰚 󰲑 -󰫦    
CS/SCS 󰭑  󰬴 BDS    󰰚,  VSCS 󰭑 󰬴 BDS / MMR    󰰚  
ESCS 󰭑 󰬴 MMR    󰰚 󰲑 󰰌     CS/SCS/VSCS 󰭑 󰬴 AP
    󰰚   ESCS 󰭑  󰬴 ODS     󰰚 AS 󰰗 VSCS 󰬎 󰭈 󰲒 󰰌 󰫦
  󰭉󰲒 (AA)      󰲇  󰫳    
ESCS   󰲒  (BoB) 󰫤󰭃   󰱳   , 󰫮󰰣󰲑 ESCS    󰭐  󰰣
 󰫽󰰌  󰰌 󰰗  󰫽󰫦 󰭈󰰌 󰰎 , 󰲑  󰲒  󰰗 D/ DD, CS, SCS, VSCS 󰲒 󰫽󰰌 󰲒 󰰌
󰰗  󰲒 󰭈󰰌    󰰗 VSCS   󰭐  󰰣 󰲒 󰫽󰰌 󰲒 󰰌 󰰗 󰱮  AA   
󰱳 󰲒 󰰌 󰰗 󰱮 󰰀 
ABSTRACT. India Meteorological Department (IMD) categorises the tropical cyclones (TCs) as cyclonic storm
(CS), severe cyclonic storm (SCS), very severe cyclonic storm (VSCS), extremely severe cyclonic storm (ESCS) and
super cyclonic storm (SuCS). The long term climatology of TCs in these categories and the trends in frequency and
intensity of TCs in these categories developing over the NIO and crossing different coastal regions are limited. Hence a
study has been undertaken to analyse the characteristics of genesis and intensification of CDs in the above categories
developing over the NIO and crossing different coastal regions based on the data of satellite era (1965-2020).
The most intense TCs (ESCS & above) cross the coast maximum over Odisha (ODS) followed by Andhra Pradesh
(AP)/Myanmar (MMR) & Bangladesh (BDS) and low intensity TCs (CS/SCS) cross maximum over BDS followed by
AP, ODS & Tamilnadu (TN) and medium intensity TCs (VSCS) cross maximum over TN/AP/BDS followed by
ODS/West Bengal (WB)/MMR during a year as a whole. While maximum CS/SCS cross BDS, maximum VSCS cross
BDS/MMR and maximum ESCS cross MMR coast during pre-monsoon season. While maximum CS/SCS/VSCS cross
AP coast, maximum ESCS cross ODS coast during post monsoon season. Over the AS, the landfall frequency of VSCS is
maximum over Arabia - Africa (AA) coast followed by Saurashtra and Kutch coast.
The coastal vulnerability due to ESCS continues over the Bay of Bengal (BoB) region, as there is no significant
trend in the frequency of genesis of ESCS and above intensity storms, though there is decreasing trend in the genesis
frequency of D/DD, CS, SCS, VSCS over the BoB. It has increased over the AA coast due to increasing trend in
frequency of genesis of VSCS and above intensity storms over Arabian Sea.
Keywords – Tropical cyclone, Landfall, Bay of Bengal, Arabian Sea, Pre-monsoon, Post-monsoon.
2 MAUSAM, 72, 1 (January 2021)
1. Introduction
About 11 cyclonic disturbances (CDs) with
maximum sustained wind speed (MSW) of 17 knots (kt)
or more including depression(D)/deep depression (DD)
with MSW of 17-33 kt and tropical cyclones (TCs) with
MSW of 34 kt or more develop over the North Indian
Ocean (NIO) during a year based on data of 1961-2010
(Mohapatra et al., 2014). It includes 9 and 2 CDs over the
Bay of Bengal (BOB) and Arabian Sea (AS) respectively.
Out of these, about five intensify into TC including about
4 over BOB and 1 over the AS. About 3 severe TCs
(MSW of 48 kt or more) are formed over the NIO during a
year (Mohapatra and Sharma, 2019; Mohapatra et al.,
2014). The frequency of TCs is maximum during post-
monsoon season (October-December) followed by pre-
monsoon (March-May) and monsoon (June-September)
season [India Meteorological Department (IMD), 2008].
Out of 5 TCs developing over the NIO, about 3 to 4
TCs make landfall (Tyagi et al., 2010) causing loss of life
and property. Though the number of such TCs is less as
compared to other Ocean basins like north Pacific and
north Atlantic Ocean, the impact is felt more in the region
due to poor socio-economic condition. The tropical warm
NIO, like the tropical north Atlantic, the south Pacific and
the northwest Pacific, is a breeding ground for the
disastrous TC phenomenon. Low lying coastal belts of
West Bengal, Odisha and Andhra Pradesh have borne the
brunt of the fury of these very severe TCs (IMD, 2003 &
2008; Mohapatra et al., 2012a; Mohapatra, 2015). Though
the number of deaths due to TCs have decreased
significantly (Mohapatra and Sharma, 2019), still there is
huge loss to property.
The risk management of the TCs depends on several
factors including (i) hazard & vulnerability analysis,
(ii) preparedness & planning, (iii) early warning,
(iv) prevention and mitigation. The early warning
component is a major component which is targeted for
improvement through the improvement in skill of
monitoring and prediction and effective warning products
generation by IMD. The IMD has the responsibility of
monitoring and prediction of CDs including TCs and
D/DD, collection, processing and archival of all data
pertaining to CDs and preparation of best track data over
the NIO. IMD has taken a number of steps in recent years
to continuously enhance the TC database to enable the
research and development for the improvement in
monitoring, numerical modelling and forecasting.
Specially, in the satellite era since 1961, there has been
significant improvement in TC monitoring which has
further advanced with augmentation of upper air
observations with pilot balloons in 1960s, radiosonde and
radio wind (RS/RW) observations in 1970s, cyclone
detection radars in 1970s, introduction of Indian satellites
in 1980s, meteorological buoys in late 1990s and
augmentation of surface observational network including
automatic weather stations and automatic rain gauges in
2000s (Mohapatra et al., 2012b and 2014). Though, the
TC data base is maintained by IMD since 1877, it is
reasonably accurate for any kind of research and
development in terms of climatological analysis, hazard
analysis, landfall characteristics and impact studies for the
period 1961 onwards (Mohapatra et al., 2012b). As
optimum observational network including satellite leading
to better estimation of location and intensity without
missing of CDs was available since 1961, the climatology
of genesis, location, intensity, movement (track) and
landfall can be best represented based on the data set of
1961 onwards. While real-time reception of satellite
imagery by IMD commenced in December 1963 through
an automatic picture transmission (APT) station at
Mumbai, the imageries of past TCs during 1960-1963
collected from USA were investigated by several
researchers. Koteswaram (1961) analysed first satellite
pictures of a TC over the AS in 1960. However, as the
satellite data were new in initial years there could be error
in estimation of location and intensity based on satellite
image in initial years. Hence in this study the
climatological characteristics of landfalling TCs over the
NIO during 1965-2020 have been analysed.
The categorisation of low pressure systems by IMD
has undergone several changes in the past based on the
availability of observational network and analysis tools
and technique. The detailed review of this classification
has been discussed by Mohapatra et al. (2012b). Till 1974,
there were broadly three categories of CDs, viz., D/DD,
cyclonic storm (CS) with MSW of 34-47 kt and severe
cyclonic storm (SCS) with MSW of 48 kt or more
(IMD, 2008). A new classification was introduced in
1974 giving the classification of SCS into (i) SC S
(MS W : 48-63 kt) and S CS wi t h core of hurricane
winds (64 kts) (IMD, 1974).
The introduction of above classification may be
attributed to (i) introduction of geostationary satellites in
1974, (ii) adoption of Dvorak‟s technique in 1974
(Dvorak, 1975), (iii) installation of cyclone detection
radars (CDR) during 1970-1973, (iv) commencement of
pilot balloon & radio wind observations during 1960s and
1970s respectively and (v) augmentation of coastal surface
observations during 1940s and 1950s (Mohapatra et al.,
2012b). There is similar classification based on 64 knots
(33 mps) wind over other basins with different terminology.
It is called as TC over southwest Indian Ocean, severe TC
over southwest Pacific and southeast Indian Ocean,
Typhoon over northwest Pacific and Hurricane over north
Atlantic and northeast Pacific Oceans.
MOHAPATRA et al. : FREQUENCY OF GENESIS & LANDFALL OF DIFFERENT CATEGORIES OF TC 3
TABLE 1
Classification of low pressure systems over the NIO since 2015 and corresponding Dvorak’s T Number and maximum sustained wind speed
Low pressure system
T Number
Maximum sustained surface wind speed (MSW)
kt
mps
kmph
Low pressure area (L)
T 1.0
< 17
< 9
< 31
Depression (D)
T 1.5
17-27
9-14
31-49
Deep Depression (DD)
T 2.0
28-33
15-17
50-61
Cyclonic Storm (CS)
T 2.5-3.0
34-47
18-24
62-88
Severe Cyclonic Storm (SCS)
T 3.5
48-63
25-32
89-117
Very Severe Cyclonic Storm (VSCS)
T 4.0-4.5
64-89
33-46
118-166
Extremely Severe Cyclonic Storm (ESCS)
T 5.0-6.0
90-119
47-61
167-221
Super Cyclonic Storm (SuCS)
T 6.5 -8.0
≥ 120
≥ 62
≥ 222
With the introduction of high wind speed recorder,
meteorological buoys, scatterometer based sea surface
wind observation, utilization of microwave based products
from satellites and also due to increase in confidence in
estimation of intensity based on Dvorak‟s technique
(Dvorak, 1984) and Radars (Raghavan, 1997 & 2013), the
criteria of classification further changed in 1999 (IMD,
1999). The terminology „SCS with a core of hurricane
winds‟ was changed to „very severe cyclonic storm
(VSCS)‟ for the wind speeds from 64 to 119 kt and a new
terminology, viz., super CS (SuCS) for the wind speeds
120 kt & above was introduced. The term SuCS was in
line with the „super typhoon‟ terminology introduced over
the northwest Pacific Ocean by t h e Re gional
Sp e cialis ed Me teoro l o g ical Cent r e (RSMC), Tokyo
with the same threshold wind speed. The other
terminologies remained unchanged.
However, even after the introduction of SuCS, it was
felt that the VSCS category was too broad. It is seen that
in all the basins except for NW Pacific for the wind speed
64 kt (33 mps) there are three or more categories
describing the intensities of TCs. Moreover, the
bifurcation of VSCS had already been implemented with
respect to its damage potential in India since 1999 (IMD,
2002). Hence with effect from 2015, VSCS category was
bifurcated and a new terminology of Extremely Severe
Cyclonic Storm (ESCS) was introduced for the MSW of
90-119 kt and the VSCS was defined with MSW of
64-89 kt, keeping the category of SuCS (120 kt or more),
unchanged. The threshold wind speed of 90 knot of ESCS
correspond to intense TC over the southwest Indian
Ocean, severe TC (category 4) over southwest Pacific and
southeast Indian Ocean (wind speed threshold of 87 knot
and hurricane (category 2) over north Atlantic and
northeast Pacific Ocean (wind speed threshold of 83 knot.
Most of the studies in the past are based on the three
categories of the TCs, viz., D/DD, CS and SCS & above,
as the data and tracks of the TCs are available in these
three categories in the cyclone e-Atlas of IMD (2008). In
recent years, the TC data has been classified into all the
categories as used by RSMC, New Delhi like CS, SCS,
VSCS, ESCS and SuCS as given in Table 1. The data of
1965-2020 (56 years) have been considered to find out
different categories of CDs and TCs developing over the
NIO and different categories of TCs making landfall over
different coasts in the NIO region. This study will be
helpful in assessment of climate change impact on TCs
over the NIO region, hazard and vulnerability of coastal
regions due to TCs as well as help in preparedness and
planning measures for TCs management. It would also
provide climatological guidance to the forecasters.
2. Data and methodology
Based on the present criteria/classification of CDs
(Table 1), the digital dataset of TCs over the NIO has been
prepared by RSMC, New Delhi for the period of 1965-
2020 (www.rsmcnewdelhi.imd.gov.in). The CD and TC
data of 1965-2020 (56 years) have been collected and
analysed to find out different categories of TCs, viz.,
D/DD, CS, SCS, VSCS, ESCS and SuCS developing over
the BoB, AS and NIO as a whole. In the analysis, the D
and DD have been considered as one category (now
onwards, it will be referred as D only). Similarly, different
categories of TCs as mentioned above making landfall
over different coasts in the NIO region are collected and
analysed during the same period to analyse the landfall
characteristics. The frequency of D/DD, CS, SCS and
above intensity storms have been collected from the TC
e-Atlas of IMD (IMD, 2008). Similarly, the frequency of
TCs in the above categories landfalling over different
coastal states of India and the countries bordering BOB
and AS has been collected from the TC e-Atlas of IMD
(2008). The data on VSCS, ESCS and SuCS have been
collected from various publications of IMD, viz.,
Quarterly Journal Mausam, Weekly Weather Report and
4 MAUSAM, 72, 1 (January 2021)
Fig. 1. Area of study
India Daily Weather Report published by IMD as the data
on above categories are not available in TC e-Atlas of
IMD (2008). Based on the analysis of these data, the
VSCS, ESCS and SuCS have been identified and analysed
based on the Standard Operation Procedure (SOP) of
IMD. The details of the SOP are available in Sharma and
Mohapatra (2017) and IMD (2003 & 2013).
In this study, the TC is said to have made landfall,
when the centre of the TC lies over the land, though
destructive effects may occur several hours before and
after the landfall time and extend several hundred
kilometres from the landfall point in the coast line.
Observed landfall positions are accurate to within ±30 km
as estimated by Mohapatra et al. (2012b). Accuracy of
observed landfall times is estimated to be ±0.5 hr
since 1974 with introduction of coastal observations and
Radar along the coast to monitor the location of
TCs (Mohapatra et al., 2012b). The month of genesis
and landfall of a CD/TC has been considered as the
month in which the genesis (formation of D) occurred,
though the landfall can occur in a subsequent
month. Accordingly, the frequency of genesis and
landfall are calculated for the month and the season. This
is one of the limitations for the calculation and analysis of
landfall frequency. However, since the study deals with
seasonal and annual frequency, this discrepancy will not
have any impact on the results and conclusions of the
study.
The TCs show bi-modal behaviour in their genesis
with primary maxima in post-monsoon season and
secondary maxima in pre-monsoon season. The TCs
during these two seasons show different track, genesis and
intensification characteristics. The number of CS, SCS,
VSCS, ESCS and SuCS that crossed different coastal
regions in the BOB and AS during pre-monsoon season
(March-June), post monsoon season (September-
December) and the year as a whole over the BoB, AS &
NIO are calculated and analysed. There have been 17 (19)
TCs formed during June (September) including 12 (7)
over AS and 5 (12) over the BOB. Out of these there have
been 11 (14) landfalling TCs during June (September)
including 6 (2) over AS and 5 (12) over the BOB. Since
the systems in the month of June during onset phase of
monsoon have pre-monsoon characteristics, they have
been considered as the TCs in pre-monsoon season for
analysis purpose. Similarly, the TC in September has been
considered in the category of the post-monsoon season, as
it occurred during withdrawal phase of monsoon. There
are 4 (all over BOB) and 6 (all over BOB) TCs during
July and August respectively during 1965-2020. Out of
these 3 and 5 TCs (3 CS and 2 SCS) crossed coasts during
July and August respectively. While one each as CS
crossed north Andhra Pradesh (AP), Odisha (ODS) and
Bangladesh (BDS) coasts in July all the five TCs in
August crossed Odisha coast.
The area of study and coastal regions considered in
the study are shown in Fig. 1. It includes Myanmar
(MMR), BDS, West Bengal (WB), ODS, AP, Tamil Nadu
& Puducherry (TNP), Sri Lanka east (SLE), Sri Lanka
west (SLW), Kerala (KRL), Karnataka (KTK),
Maharashtra and Goa (MNG), Gujarat (GJT), Pakistan
(PAK), Iran, Arabia and Africa (IAA). The IAA includes
Somalia, Yemen, Oman and Iran coasts.
MOHAPATRA et al. : FREQUENCY OF GENESIS & LANDFALL OF DIFFERENT CATEGORIES OF TC 5
TABLE 2
Frequency of genesis and landfalling CDs over the BoB, AS and NIO
Category
Frequency of Genesis
Frequency of landfall
Basin
Post-monsoon
Pre-monsoon
Annual
Total
Mean
Total
Mean
Total
Mean
Total
Mean
Total
Mean
Total
Mean
SuCS
BoB
3
0.05
3
0.05
6
0.11
1
0.02
2
0.04
3
0.05
AS
1
0.02
1
0.02
2
0.04
0
0.00
0
0.00
0
0.00
NIO
4
0.07
4
0.07
8
0.14
1
0.02
2
0.04
3
0.05
ESCS
BoB
10
0.18
23
0.41
33
0.59
10
0.18
16
0.29
26
0.46
AS
5
0.09
7
0.13
12
0.21
3
0.05
2
0.04
5
0.09
NIO
15
0.27
30
0.52
45
0.79
13
0.23
18
0.32
31
0.55
VSCS
BoB
9
0.16
38
0.68
47
0.84
8
0.14
26
0.46
35
0.63
AS
4
0.07
9
0.16
13
0.21
4
0.07
4
0.07
8
0.14
NIO
13
0.23
47
0.89
60
1.13
12
0.21
30
0.54
43
0.77
SCS
BoB
10
0.18
25
0.45
35
0.59
8
0.14
28
0.50
37
0.66
AS
5
0.09
11
0.20
16
0.29
2
0.04
2
0.04
4
0.07
NIO
15
0.29
36
0.64
51
0.89
10
0.18
30
0.54
41
0.73
CS
BoB
16
0.29
53
0.95
78
1.39
14
0.25
35
0.63
55
0.98
AS
12
0.21
12
0.21
24
0.43
5
0.09
6
0.11
11
0.20
NIO
28
0.50
65
1.16
102
1.82
19
0.34
41
0.73
66
1.18
D
BoB
45
0.80
105
1.91
241
4.30
46
0.82
93
1.66
222
3.96
AS
22
0.39
38
0.68
64
1.14
10
0.18
11
0.20
22
0.39
NIO
67
1.19
143
2.57
305
5.44
56
1.00
104
1.86
244
4.36
CD: Cyclonic disturbance, D: Depression/Deep Depression, CS: Cyclonic storm, SCS: Severe cyclonic storm, VSCS: Very severe cyclonic storm,
ESCS: Extremely severe cyclonic storm and SuCS: Super Cyclonic Storm, BoB: Bay of Bengal, AS: Arabian Sea, NIO: North Indian Ocean
The mean frequencies of different categories of TC
developing over the NIO during 1965-2020 and the mean
values of different categories of TCs landfalling over
different coastal regions during 1965-2020 have been
calculated and analysed for different Ocean basins and
different seasons. The probability of intensification of D
into different categories of TCs and probability of
intensification of TC into different categories of higher
intensity are calculated and analysed for different seasons
and over different basins. The ratios of frequency of
occurrence of CDs and TCs during different seasons over
BoB & AS are also calculated and analysed. The
probability of landfall of TCs over different coasts are also
calculated and analysed. Further the trends in frequencies
of genesis and landfalling TCs over different coastal
regions during different seasons and year as a whole are
calculated and analysed.
The significance in the linear trends has been
analysed through student’s t test at 90% and 95% level of
confidence and the results are presented and discussed.
The results are analysed and presented in section 3.
The broad conclusions and future scope are presented in
section 4.
3. Results and discussion
The frequency of genesis of various categories of
CDs are presented and analysed in section 3.1. The trends
in genesis frequency are analysed and discussed in section
3.2. The frequency of landfalling TCs and their trends are
presented and analysed in section 3.3 and 3.4 respectively.
3.1. Mean frequency of genesis of CDs and their
probability of intensification over the NIO
3.1.1. Annual frequency
Considering different categories of CDs, the mean
frequency is about 6.5 for D, 1.8 for CS, 0.9 for SCS, 1.1
for VSCS, 0.8 for ESCS and 0.1 for SuCS develop over
the NIO in a year (Table 2) and hence about 10 CDs and 5
TCs develop over the NIO during a year (Table 3).
Comparing with Mohapatra et al., 2014, based on the data
of 1961-2010, the frequency of CD has decreased by 1 in
recent decade and there is no change in the frequency of
TCs. Out of these CDs, about 47%, 29%, 20% and 9%
intensify into CS, SCS, VSC and ESCS respectively. Out
of about 5 TCs 3 (62%) become SCS or above, 2 (42%)
become VSCS or above and 1 (20%) become ESCS or
6 MAUSAM, 72, 1 (January 2021)
TABLE 3
Cumulative frequency of genesis and landfalling CDs over the BoB, AS and NIO during 1965-2020
Category
Basin
Frequency of Genesis
Frequency of landfall
Pre-monsoon
Post-monsoon
Annual
Pre-monsoon
Post-monsoon
Annual
Total
Mean
Total
Mean
Total
Mean
Total
Mean
Total
Mean
Total
Mean
SuCS
BoB
3
0.05
3
0.05
6
0.11
1
0.02
2
0.04
3
0.05
AS
1
0.02
1
0.02
2
0.04
0
0.00
0
0.00
0
0.00
NIO
4
0.07
4
0.07
8
0.14
1
0.02
2
0.04
3
0.00
ESCS & above
BoB
13
0.23
26
0.46
39
0.70
11
0.20
18
0.32
29
0.52
AS
6
0.11
8
0.14
14
0.25
3
0.05
2
0.04
5
0.09
NIO
19
0.34
34
0.61
53
0.95
14
0.25
20
0.36
34
0.61
VSCS & above
BoB
22
0.39
64
1.14
86
1.54
19
0.34
44
0.79
64
1.14
AS
10
0.18
17
0.30
27
0.48
7
0.13
6
0.11
13
0.23
NIO
32
0.57
81
1.45
113
2.02
26
0.46
50
0.89
77
1.38
SCS & above
BoB
32
0.57
89
1.59
121
2.16
27
0.48
72
1.29
101
1.80
AS
15
0.27
28
0.50
43
0.77
9
0.16
8
0.14
17
0.30
NIO
47
0.84
117
2.09
164
2.93
36
0.64
80
1.43
118
2.11
CS & above
BoB
48
0.86
142
2.54
199
3.55
41
0.73
107
1.91
156
2.79
AS
27
0.48
40
0.71
67
1.20
14
0.25
14
0.25
28
0.50
NIO
75
1.34
182
3.25
266
4.75
55
0.98
121
2.16
184
3.29
D & above
BoB
93
1.66
249
4.45
438
7.82
87
1.55
200
3.57
378
6.75
AS
48
0.86
77
1.38
129
2.30
24
0.43
25
0.45
50
0.89
NIO
141
2.52
326
5.82
567
10.13
111
1.98
225
4.02
428
7.64
Legends same as given with Table 2
above intensity storms (Fig. 2). There is 69% and 32%
probability for an SCS to intensify into a VSCS and ESCS
respectively. Similarly, there is 47% probability for a
VSCS to intensify into an ESCS.
Considering the BOB, the average frequency of D,
CS, SCS, VSCS and ESCS are 4.3, 1.4, 0.6, 0.8 and 0.6
respectively (Table 2). The average frequency of CD, CS
& above, SCS & above, VSCS & above and ESCS &
above over the BOB is 7.8, 3.5, 2.2, 1.5 and 0.7
respectively (Table 3). Thus about 8 CDs develop over the
BOB in a year, out of which 3-4 (45%) become the TCs
[Fig. 2(b)]. About 61% of TCs become severe, 43%
become very severe and 20% become extremely severe or
above intensity storms [Fig. 2(b)]. Similarly, there is 71%
and 32% probability for an SCS to intensify into a VSCS
and ESCS respectively and 45% probability for a VSCS to
intensify into an ESCS over the BOB [Fig. 2(b)].
Over the AS, the average frequency of D, CS, SCS,
VSCS and ESCS is 2.2, 0.4, 0.3, 0.2, 0.2 respectively
(Table 2). The average frequency is 2.3, 1.2, 0.8, 0.5 and
0.3 respectively for CD, CS & above, SCS & above,
VSCS & above and ESCS & above intensity storms per
year (Table 2). Thus, about 52% of CDs intensify into
TC over the AS during a year [Fig. 2(b)]. The probability
of a TC becoming severe is 64%, becoming very severe is
40% and becoming extremely severe is 21%. There is
63% and 33% probability for an SCS to intensify into a
VSCS and ESCS respectively and 52% probability for a
VSCS to intensify into an ESCS over the AS. The above
results endorse the earlier findings of Mohapatra et al.,
2015. Thus, comparing the probability of intensification
over the BoB and AS, the probability of a CS to intensify
into SCS, VSCS and ESCS is almost same for both BOB
and AS and the probability of a CD becoming a TC is less
over the BOB as compared to AS by about 7%. It could be
attributed to the fact that a large number of D/DD develop
over the monsoon season (June-September) mainly over
the head BoB which rarely intensify into TC due to
unfavourable environmental conditions like vertical wind
shear of horizontal wind in association with Tibetan High
and Tropical Easterly Jet Stream (Mohapatra et al., 2015
& 2017 and Rao, 1976).
Considering the SuCS, its frequency has increased
during the recent years since 1990 both over the BoB and
AS and hence over the NIO (Table 4). During the period
1990-2020, there have been 4 & 2 SuCS over the BOB and
AS respectively against 2 and 0 over the BOB and AS
during 1965-1989. There have been 7 ESCS over AS during
1990-2020 against 3 during 1965-1989. There is a rising
trend in frequency of ESCS and above intensity storms over
the AS since 1990. It will be further discussed in section 3.2.
MOHAPATRA et al. : FREQUENCY OF GENESIS & LANDFALL OF DIFFERENT CATEGORIES OF TC 7
Figs. 2(a&b). Probability of intensification of D and TC into different (a) individual categories of intensity of storm and
(b) cumulative categories of intensity of storm during pre-monsoon season, post-monsoon season and year as
a whole over BOB, AS and NIO during 1965-2020
TABLE 4
Super Cyclonic Storms over the north Indian Ocean during 1965-2019
S. No.
Period Basin T. No.
Peak Intensity
(knot) Landfall Point
Landfall Intensity
(knot) & category
1. 14-20 Nov, 1977 BOB T6.5 125 AP, Chirala 125 (SuCS)
2. 01-09 Nov, 1989 BOB T6.5 130 AP, Kavali 115 (ESCS)
3. 4-10 May, 1990 BOB T6.5 130 AP, Machilipatnam 102 (ESCS)
4. 24-30 Apr, 1991 BOB T6.5 130 Bangladesh, Chittagong 127 (SuCS)
5. 25-31 Oct, 1999 BOB `T7.0 140 Odisha, Paradeep 140 (SuCS)
6. 1-7 Jun 2007, Gonu AS T6.5 130 Oman, Muscat 77 (VSCS)
7. 24 Oct-2 Nov 2019, Kyarr AS T 6.5 130 Weakened over sea Weakened over Sea
8. 16-21 May, 2020, Amphan BoB T 6.5 130 West Bengal, Sunderbans 85 (VSCS)
3.1.2. Post monsoon season
About 6 CDs develop over the NIO during post
monsoon season including about 4.5 over the BOB and
1.5 over the AS (Tables 2 & 3). Out of these about 3.2
(55%), 2.5 (57%) and 0.7 (51%) intensify into TCs over
the NIO, BOB & AS respectively [Figs. 2(a&b)]. Out of
these TCs about 2 (64%), 1.5 (45%) & 0.6 (19%) TCs
over the NIO, 1.6 (63%), 1.1 (45%) & 0.5 (18%) TCs over
the BoB and 0.5 (70%), 0.3 (43%) & 0.1 (20%) TCs over
the AS intensify into severe, very severe & extremely
severe TCs respectively [Figs. 2(a&b)]. Thus the probability
of intensification of a CD into TC is higher over the BOB
than over the AS by about 6% and the probability of
intensification of TCs into severe TCs is higher over the
AS than over the BOB by about 7% [Figs. 2(a&b)]. The
probability of SCS intensifying into a VSCS is higher
over the BOB by about 11% [Figs. 2(a&b)].
While climate variability such as the El Niño
Southern Oscillation (ENSO) and Indian Ocean Dipole
(IOD) have known influences to NIO TC activity, results
reveal that no single climate mode can well explain the
TC development concentrating on AS or BoB only.
Ng and Chan (2012); Yuan and Cao (2013); Girish Kumar
& Ravichandran (2012); Mohapatra and Kumar (2017);
Mohapatra et al. (2017 and 2015) and Wahiduzzaman
et al. (2017) highlighted the impacts of the ENSO, IOD
8 MAUSAM, 72, 1 (January 2021)
and their combined impact on TC activity over the NIO.
According to Mohapatra & Kumar (2017) and Girish
Kumar & Ravichandran (2012), the negative IOD and La
Nina conditions favour the TC activity over the BOB
during post-monsoon season and they have no significant
impact over the BOB during pre-monsoon season and
over the AS during both the seasons.
Though the frequency of TCs is less over the AS,
according to Sattar et al. (2019), AS is very active in a
few years (but with quiet BoB season) and the opposite
occurs in some others. This contrast occurs mostly
during the postmonsoon season of October- December.
Sattar et al. (2019) found that variability of the northeast
monsoon is an important factor responsible for the
difference between the two basins. Excess moisture is
available over the AS due to anomalous lowlevel flow from
the equatorial Indian Ocean in the years in which there are
more TCs in that basin and drier condition is over the
BoB. Nevertheless, the anomalous flow during active AS
TC seasons is similar to that occuring during positive IOD
and thus this climate variability may be responsible for
redistributing the moisture content in the NIO.
3.1.3. Pre monsoon season
During pre-monsoon season about 2.5 CDs develop
over the NIO including about 1.6 over the BOB and 0.9
over the AS (Table 2). Out of these CDs about 1.3 (53%),
0.8 (52%) and 0.5 (56%) intensify into TCs over the NIO,
BOB & AS respectively [Table 3, Figs. 2(a&b)]. Out of
these TCs, about 67% (56%), 46% (37%) & 27% (22%)
intensify into severe, very severe and extremely severe
TCs over the BOB (AS). Thus the probability of
intensification of a TC into severe and very severe TCs is
higher over the BoB than over the AS by about 10% each
and into ESCS is higher by about 5% [Figs. 2(a&b)].
There is no difference in probability of intensification of
an SCS over the BoB and AS into VSCS or ESCS and
VSCS into an ESCS [Figs. 2(a&b)]. While about 65-70%
of SCS intensify into VSCS, about 60% of VSCS
intensify into ESCS over both the basins.
3.1.4. Ratio of frequency of TCs between BoB & AS
The ratio of TCs over the BoB to that over the AS
varies from 1.6 to 2.3 for different categories of TCs
during pre-monsoon season, 2.5 to 4.3 during post
monsoon season and 2.0 to 3.8 during the year as a whole
[Figs. 3(a-d)]. Considering the cumulative frequencies, it
varies from 1.7 to 2.3, 3.1. to 3.8, 2.3 to 2.9 during pre -
monsoon, post monsoon and year as a whole. In general,
the ratio is higher in case of VSCS during pre-monsoon
(2.3:1), post-monsoon (3.8:1) and years a whole (3.2:1). It
can thus be inferred that the frequency of more intense
TCs is higher over the BoB as compared to AS during
both pre-monsoon and post monsoon season. Further the
ratio is lower during pre-monsoon season as compared to
post-monsoon season for all categories of TCs. It can be
attributed to the fact that most of the CDs/TCs (about
70%) over the BoB originate from the remnants of the
TCs from the Northwest Pacific Ocean and the frequency
of CDs & TCs are maximum during August to November
over Northwest Pacific Ocean. It is not the case with AS.
3.1.5. Ratio of frequency of TCs between pre-
monsoon and post monsoon season
The ratio of Frequency of TCs during post-monsoon
& pre-monsoon seasons over various basins is presented
in Figs. 3(a-d). This ratio varies from 1.0 to 2.3 over AS,
1.9 to 4.4 over BoB and 1.8 to 3.8 over the NIO for
various categories of storms. The ratio is maximum in
VSCS category being 4.4:1 over BOB and 2.3:1 over the
AS. Considering the cumulative frequency, it varies from
1.7 to 3.0, 1.3 to 1.8, 1.6 to 2.5 over BoB, AS & NIO
respectively. Thus the variation from pre-monsoon to
post-monsoon season is more over the BOB as compared
to AS. The difference in cumulative frequency of TCs
during post-monsoon & pre-monsoon seasons is higher
over BoB & hence NIO due to the reason mentioned in
previous section. The trends in seasonal variability in
formation of CDs/TCs/severe TCs are analysed by
Mohapatra et al. (2015 & 2017). According to them,
considering the recent five decades (1961-2010), the
ratio shows a significant decreasing trend for CDs and
severe TCs over the BOB and increasing trend for
TCs over the AS. The decreasing trend in the ratio of CDs
and severe TCs over the BoB could be attributed to
relatively higher decreasing trend in CDs and TCs
frequency during post monsoon season over the BoB.
3.2. Trend in frequency of genesis
3.2.1. Trend in annual frequency of genesis
There is significantly decreasing trend in frequency
of all categories of CDs including D/DD, CS, SCS, VSCS,
ESCS over the BOB; and all except ESCS over the NIO
during the year as a whole (Table 5, Figs. 4&5). There is
also decreasing trend in frequency of D & above, CS &
above, SCS & above, VSCS & above and ESCS & above
over the BOB and all the above except ESCS &
aboveover the NIO during the year as a whole [Table 5,
Figs. 4&5). However, there is no significant trend in
frequency of any such category of storms over the AS
during the period [Figs. 6{a&b(i-iii)}, Table 5] except that
there is increasing trend in the frequency of ESCS. There
is an increasing trend in the frequency of CS & above,
SCS & above, VSCS & above and ESCS & above over
MOHAPATRA et al. : FREQUENCY OF GENESIS & LANDFALL OF DIFFERENT CATEGORIES OF TC 9
Figs. 3(a-d). Ratio of (a) frequency of different categories of CDs and (b) cumulative frequency of different categories of
CDs over the BOB and AS during pre-monsoon, post-monsoon and year as a whole and ratio of (c) frequency
of different categories of CDs and (d) cumulative frequency of different categories of CDs during post-
monsoon and pre-monsoon seasons over the BOB, AS and NIO
the AS during the year as a whole [Table 5,
Figs. 6{a&b(i-iii)}]. Thus, while the increasing trend in
cumulative frequencies of different categories of storm
over the AS can be attributed to similar trend in the
frequency of ESCS & above, the decreasing trend in
cumulative frequencies over the BOB can be attributed to
similar trend in all the categories. According to Mohapatra
et al. (2014) based on data of (1961-2010), this trend in
frequency of annual CDs is mainly due to the decreasing
trend in frequency of CDs during monsoon season.
Decreasing trend in the frequency of (i) CS and above,
(ii) SCS and above and (iii) VSCS and above intensity
storms over the BOB and NIO as a whole endorses earlier
findings of Mohapatra et al. (2014). Mandal & Prem Krishna
10 MAUSAM, 72, 1 (January 2021)
Figs. 4[a&b(i-iii)]. (a) Individual and (b) cumulative frequency of various categories of TCs during (i) pre-monsoon, (ii) post-monsoon and
(iii) year as a whole over the North Indian Ocean during the period 1965-2020
[D: Depression & deep depression, CS: Cyclonic storm, SCS: Severe cyclonic storm, VSCS: Very severe cyclonic storm, ESCS: Extremely
severe cyclonic storm, Linear: Linear trend line]
(2009) have also shown decreasing trend of frequency of
very severe TC over the NIO during 1965-2008 and no
trend in the MSW associated with VSCS during the same
period. Comparing with the present study, the trend over
the NIO is mainly due to similar trend over the BoB.
The past studies show that there has been significant
increasing trend in sea surface temperature (SST) over the
BOB, AS and NIO during the satellite era (Pattanaik,
2005; Roxy et al., 2015 and Elsner & Kocher, 2000).
Pattanaik (2005) based on the NOAA SST data during
1891-2004 has shown that the SST over BOB (Lat. 10-
25° N and Long. 80-100° E) shows significant increasing
trend during pre-monsoon, monsoon and post monsoon
seasons. Similar increasing trend is also observed over
equatorial Indian Ocean (0° N-10° N, 55° E-95° E). Thus,
there is decrease in frequency of CDs, TCs and severe
TCs since 1970s, though there is increase in SST over the
BOB and NIO.
According to Singh et al. (2018), an increasing SST,
surface wind, mid-tropospheric relative humidity and
potential evaporation factor (PEF) are helpful in the
formation of intensified storms over the AS. A large
temperature anomaly difference between atmosphere
and Ocean also perceived to play a key role in modulating
the enhanced intensity of TCs. The SST range of 27.5 °C
to 29.5 °C and supportive flow field is helping to enhance
the middle and upper tropospheric moisture content;
eventually, resulting in increased SST, PEF and relative
humidity through a possible feedback mechanism.
Knutson et al. (2019, 2020) conclude that there is
only low confidence in detection and attribution of any
MOHAPATRA et al. : FREQUENCY OF GENESIS & LANDFALL OF DIFFERENT CATEGORIES OF TC 11
Figs. 5[a&b(i-iii)]. Same AS Fig. 4, but over the Bay of Bengal (BoB)
anthropogenic influence on historical TC intensity in any
basin or globally. However, the balance of evidence
suggests that there is a detectable increase in the global
average intensity of the strongest (hurricane strength) TCs
since the early 1980s. They have given similar conclusion
on detection and attribution to the trend in frequency of
TCs over the AS.
3.2.2. Trend in frequency of genesis during post-
monsoon season
Considering post-monsoon season, there is
significant decreasing trend in the frequency of D/DD,
CS, SCS, VSCS & ESCS over the BOB and D/DD, CS &
VSCS over the NIO (Table 5, Figs. 4&5). There is no
significant trend over the AS during the post-monsoon
season [Table 5, Figs. 6{a&b(i-iii)}]. There is also
decreasing trend in frequency of D & above, CS & above,
SCS & above, VSCS & above, ESCS & above over the
BoB and all except ESCS & above over the NIO (Table 5,
Figs. 4&5). According to Mohapatra et al. (2015),
considering the rate of intensification from TC to severe
TC, significant decreasing trends are noted in the
monsoon and post-monsoon seasons as well as year as a
whole over the BOB. According to Mohapatra et al.
(2017) based on the data of 1961-2010, significant
decreasing trend in mid-tropospheric humidity is
associated with the decreasing trends in frequency of CDs
and their intensification to severe TCs over BOB during
post-monsoon season. Interestingly, low level cyclonic
vorticity has also decreased over the southern parts of
BOB south of 15° N which is the climatological region of
cyclogenesis during October to December, but, it has
increased over the northern BOB during the recent years.
There is increasing trend in the frequency of VSCS
& above and ESCS & above over the AS [Table 5,
Figs. 6{a&b(i-iii)}]. Thus, during post monsoon season,
the decreasing trend in cumulative frequency over the
BoB is due to similar trend in individual categories of
12 MAUSAM, 72, 1 (January 2021)
Figs. 6[a&b(i-iii)]. Same as Fig.4, but over the Arabian Sea (AS)
storms. The increasing trend in frequency of VSCS/ESCS
& above over the AS is due to similar insignificant trend
in the categories of VSCS and ESCS. According to
Mohapatra et al. (2017), over the AS, there are increasing
trends in intensification of CDs to TCs and TCs to severe
TCs which could be in association with decreased vertical
wind shear aside from other synoptic scale forcing).
According to Knutson et al., 2019, the balance of
evidence suggests there has been some detectable increase
in the frequency of post-monsoon ESCS and above
intensity storms over the AS and there is low confidence
that anthropogenic forcing has contributed to the increase.
3.2.3. Trend in frequency of genesis during pre-
monsoon season
During pre-monsoon season, there is a decreasing
trend in frequency of D & above, SCS & above and VSCS
& above over the BoB which could be attributed to similar
decreasing trend in the frequency of D/DD and VSCS
(Table 5, Figs. 4&5). The cumulative frequencies over the
NIO do not show significant trends. According to
Mohapatra et al. (2017), during the pre-monsoon season,
the decreasing trend in intensification of CD to TC over
BOB is associated with unfavourable decrease in mid-
tropospheric humidity. According to Mohapatra et al.
(2015), there is significant decreasing trend in rate of
intensification of CDs to TCs over NIO and BOB during
pre-monsoon season during 1961-2010.
There is insignificant rising trend over the AS for
different categories of storms [Table 5, Figs. 6{a&b(i-iii)}].
But the frequency of CS & above and SCS & above over
the AS show significant increasing trend at 90% level of
confidence and insignificant rasing trend in the frequency
of VSCS & above and ESCS & above [Table 5,
Figs. 6{a&b(i-iii)}]. According to Mohapatra et al. (2015
and 2017), intensification of CDs to TCs and TCs to
severe TCs during the pre-monsoon season over the AS
shows significantly increasing trend during 1961-2010
MOHAPATRA et al. : FREQUENCY OF GENESIS & LANDFALL OF DIFFERENT CATEGORIES OF TC 13
TABLE 5
Linear Trend Coefficient (per 100 years) of individual and cumulative categories of CDs during pre-monsoon,
post monsoon and year as a whole over the period of 1965-2020
Category
Basin
Pre-monsoon
Post-monsoon
Annual
Category
Basin
Pre-monsoon
Post-monsoon
Annual
ESCS
BoB
0.02
-0.71
-0.61
ESCS & above
BoB
0.18
-0.79
-0.54
AS
0.21
0.35
0.55
AS
0.31
0.53
0.83
NIO
0.23
-0.36
-0.06
NIO
0.49
-0.27
0.29
VSCS
BoB
-0.88
-1.50
-2.78
VSCS & above
BoB
-0.69
-2.3.
-3.32
AS
0.07
0.23
0.30
AS
0.38
0.76
1.13
NIO
-0.81
-1.27
-2.48
NIO
-0.32
-1.54
-2.19
SCS
BoB
-0.15
-0.68
-1.31
SCS & above
BoB
-0.84
-2.98
-4.62
AS
0.21
-0.14
0.03
AS
0.58
0.61
1.16
NIO
0.06
-0.82
-1.27
NIO
-0.26
-2.37
-3.46
CS
BoB
0.17
-1.42
-1.67
CS & above
BoB
-0.67
-4.4
-6.29
AS
0.16
0.20
0.25
AS
0.75
0.81
1.41
NIO
0.33
-1.22
-1.42
NIO
0.08
-3.59
-4.88
D
BoB
-1.02
-1.86
-7.20
D & above
BoB
-1.79
-6.25
-13.49
AS
0.14
-0.08
-0.73
AS
0.81
0.73
0.23
NIO
-0.87
-1.93
-8.38
NIO
-0.98
-5.52
-13.27
CD: Cyclonic disturbance, D: Depression/Deep Depression, CS: Cyclonic storm, SCS: Severe cyclonic storm, VSCS: Very severe cyclonic
storm, ESCS: Extremely severe cyclonic storm, BoB: Bay of Bengal, AS : Arabian Sea, NIO: North Indian Ocean
Bold: Statistically significant at 95% level of confidence, Bold & Italics: Statistically significant at 90% level of confidence
which could be in association with decreased vertical
wind shear aside from other synoptic scale forcing.
According to Evan et al. (2011 a&b), the increase in the
intensity of pre-monsoon AS TCs during May and June
over the period of 1979-2010 was found to be associated
with a decrease in vertical wind shear which was caused
by an upward trend in anthropogenic black carbon and
sulphate emissions. They argued that anthropogenic
aerosols cause anomalous atmospheric circulation over
south Asia, which then reduce the basin-wide vertical
wind shear. Reduced wind shear thus creates an
environment more favorable for intensification of TCs.
According to Rajeevan et al. (2013), during recent years,
an increase in the intensity of pre-monsoon TCs over the
AS could be attributed to epochal variability in the storm
ambient vertical wind shear and TC heat potential (TCHP).
There is a significant increase (0.53 kJ cm2 year1) of
TCHP during recent years. The warmer upper ocean helps
TCs to sustain or increase their intensity by an
uninterrupted supply of sensible and latent heat fluxes
from the ocean surface to the atmosphere (Goni & Trinanes,
2003; Emanuel et al., 2004; DeMaria et al., 2005).
Zhang et al. (2019) examined the impacts of tropical
South Atlantic SST anomalies on the frequency of the AS
TCs during the pre-monsoon season (May-June) using
observations and climate model experiments. There is a
statistically significant association between the Atlantic
SST anomalies and the frequency of AS TCs during May-
June of 1979-2016 based on the observations. These
results can be explained from a physical perspective
through the classic Matsuno-Gill responses to the Atlantic
SST forcing, leading to changes in vertical wind shear in
the AS. The reduced vertical wind shear related to the
Atlantic SST warming is associated with anomalous
upper-level westerlies and lower-level easterlies. The
reduced vertical wind shear is associated with increase in
frequency of TCs in pre-monsoon season over the AS.
The physical mechanisms identified in the observations
are strongly supported by a suite of experiments with an
atmospheric general circulation model.
More recently, the ESCS over the AS have been
projected to increase under anthropogenic forcing using
high-resolution fully-coupled climate models (Murakami
et al., 2017). Wang et al. (2013), based upon ensembles of
global reanalyses and precipitation datasets, demonstrated
a robust intensification of the May monsoon trough over
the BOB since 1979, with a corresponding modulation of
pre-monsoon TCs. It has resulted in more intense TCs
(VSCS and above) in general and an increase in the
number of TCs that impacted Myanmar. Such circulation
changes in the pre-monsoon season have deepened the
BOB monsoon trough and led to a tendency that TCs are
occurring earlier each year. The deepened monsoon
trough also affected the frequency and track of TCs in
14 MAUSAM, 72, 1 (January 2021)
Figs. 7(a&b). Probability (%) of landfall of (a) different categories of CDs and (b) cumulative categories of CDs with
respect to genesis frequency
the BOB. Such a change in pre-monsoon circulation has
been attributed to atmospheric warming caused by
increased anthropogenic aerosols in the Indo-Gangetic
Plain. Analyses of the Coupled Earth System Model
(CESM) single-forcing experiments provide further
evidence for the effect of aerosols on the deepening of the
BOB monsoon trough and the resulting increases in TC
frequency, intensity and trajectory. However, there is a
significant decreasing trend in the frequency of SCS &
above and VSCS & above over the BOB [Table 5,
Figs. 5{a&b(i-iii)}].
Considering all the above studies, Knutson et al.
(2019, 2020) have concluded that, there is significant
increase in intense TCs over the AS during pre-monsoon
season with a low confidence in detection and attribution
to anthropogenic influences as the frequency of intense
TCs are less and the studies in this regard are limited and
based on recent years only.
3.3. Mean frequency of landfalling TCs
3.3.1. Mean frequency and probability of
landfalling TCs over the BoB and AS
Considering the data during 1965-2020, about 7.6
CDs and 3.3 TCs (CS & above) make landfall over the
NIO (Tables 2&3). Basin-wise, the average frequency of
landfall is about 6.7 for CDs and 2.8 for TCs over the BoB
and 0.9 and 0.5 respectively over the AS. Similarly, out of
about 2.1 SCS and above landfalling over the NIO, 1.8
make landfall over BoB and 0.3 over the AS. Out of 1.38
landfalling VSCS & above over the NIO, about 1.14 are
from BoB and 0.23 from the AS. About 0.6 landfalling
ESCS over the NIO includes 0.5 over the BoB and 0.1
over the AS. According to Alam et al. (2003), the annual
average number of CDs over the BoB that crossed the
coasts is 6.7 in a year, which is 86% of the total annual
number of CDs that formed based on the data of 1975-
1999 over the BoB. The annual average number of TCs
over the BoB that crossed the coasts is 3.1. Thus
comparison of the results with that of Alam et al. (2003)
indicates that the frequency of landfalling TCs over the
BoB has decreased in recent years.
About 69%, 72%, 68% and 64% of CS & above,
SCS & above, VSCS & above and ESCS & above
developing over the NIO cross the coast with at least the
intensity of CS, SCS, VSCS & ESCS respectively
[Figs. 7(a&b)]. The remaining ones either dissipate over
the sea or cross coast as a relatively weaker system.
Considering BoB (AS), about 78% (42%), 84% (40%),
74% (48%) and 74% (36%) of CS & above, SCS & above,
VSCS & above and ESCS & above cross the coast with at
least the intensity of CS, SCS, VSCS & ESCS
respectively. Thus, the rate of dissipation/weakening is
significantly higher over the AS. It may be due to (a) large
sea area as compared to BoB, (b) colder sea over west AS
and (c) larger role of mid latitude westerlies leading to
increase in vertical wind shear, (d) dry air entrainment
MOHAPATRA et al. : FREQUENCY OF GENESIS & LANDFALL OF DIFFERENT CATEGORIES OF TC 15
from the desert region of Arabia-Africa. On the other
hand, BoB is warmer, less influenced by the mid-latitude
westerlies & dry/cold air entrainment and has smaller
area which favour it to have more probability of landfall
of TCs with higher intensity. Considering the individual
categories of TCs, over the AS(BOB) about 16% (28%),
9% (31%), 30% (41%), 36% (67%) in case of CS, SCS,
VSCS and ESCS respectively cross coast with same
intensity [Figs. 7(a&b)]. Thus, considering individual
category also the probability of landfall is higher over the
BoB than over the AS by about 10-30% and it is
significantly higher in case of ESCS category.
The frequency of landfalling TCs is higher during
post-monsoon (2.2) than in pre-monsoon (1.0) season over
the NIO (Tables 2&3). It is about 1.9 (0.3) and 0.7 (0.3)
over the BoB (AS) during post-monsoon and pre-
monsoon seasons respectively. According to Alam et al.
(2003), of all the TCs that crossed the BoB coasts, 20.99%
crossed in the pre-monsoon season (March-May) and
54.32% crossed in the post-monsoon season (October-
December). On an average, the maximum frequency of
CDs crossing the coasts is 1.4 and occurs in the month of
October; that of TCs is 1.0 and occurs in November.
During post-monsoon season, about 67%, 68%, 62% and
59% of CS & above, SCS & above, VSCS & above and
ESCS & above developing over the NIO cross the coast
with at least the intensity of CS, SCS, VSCS & ESCS
respectively [Figs. 7(a&b)]. Considering BoB (AS), about
75% (35%), 81% (29%), 69% (35%) and 69% (25%) of
CS & above, SCS & above, VSCS & above and ESCS &
above cross the coast with intensity of at least CS, SCS,
VSCS and ESCS respectively. Considering the individual
categories of TCs, over the BOB(AS) about 25% (15%),
32% (07%), 41% (24%), 62% (25%) in case of CS, SCS,
VSCS and ESCS respectively cross coast with same
intensity. Thus, the probability of landfall is higher over
the BoB than the AS by about 10-35% for different
categories of TCs.
During pre-monsoon season, about 73%, 77%, 81%
and 74% of CS & above, SCS & above, VSCS and
above and ESCS & above developing over the NIO cross
the coast with at least the intensity of CS, SCS, VSCS and
ESCS respectively [Figs. 7(a&b)]. Considering BoB (AS),
about 85% (52%), 84% (60%), 86% (70%) and 85% (50%)
of CS & above, SCS & above, VSCS & above and ESCS
& above cross the coast with at least the intensity of CS,
SCS, VSCS & ESCS respectively. Considering the
individual categories of TCs, over the BOB/AS about
29%/19%, 25/13%, 36%/40%, 77%/50% in case of CS,
SCS, VSCS and ESCS respectively cross coast with same
intensity. Thus, the probability of landfall is higher over
the BoB than the AS by about 10-22% in case of CS, SCS,
ESCS and almost same in case of VSCS.
Comparing post and pre-monsoon season, the
probability of landfall is higher during pre-monsoon
season by about 6, 9, 19 and 15% in case of CS & above,
SCS & above, VSCS & above and ESCS & above over
the NIO. Similarly, it is higher by about 10% (17%), 3%
(31%), 17% (35%) and 16% (25%) over the BoB (AS)
during pre-monsoon than in post-monsoon season for CS
& above, SCS & above, VSCS & above and ESCS &
above respectively.
Considering individual categories, the probability of
landfall is higher during pre-monsoon than in post-
monsoon season by about 4, 16, 15 and 25% for CS, SCS,
VSCS & ESCS respectively over the AS. It is higher
during pre monsoon season than in post monsoon season
in case of CS (4%) and ESCS (15%) and lower in case of
SCS (7%) and VSCS (5%) over the BoB.
3.3.2. Annual frequency of landfalling TCs over
different coastal regions
About 1.71(1.13) and 0.18(0.16) CS and above (SCS
& above) make landfall over east and west coasts of India
respectively. About 0.68 and 0.17 VSCS & above 0.30 &
0.04 ESCSs & above make landfall over the east & west
coasts of India respectively. Thus, while 3-4 TCs over the
NIO make landfall, about 2 TCs make landfall over east
coast of India (Tables 6-8). Similarly, while 2 of the SCS
& above over the NIO make landfall, 1 out of these make
landfall over the east coast of India. While about 4 VSCS
& above developing over the NIO in 3 years may make
landfall, 2 out of these make landfall over east coast of
India. While about 1 ESCS & above over the NIO in 2
years make landfall, east coast of India experiences
landfall of TC with intensity of ESCS & above once in 3
years (Table 8).
Considering different coastal regions of BoB, the
annual frequency of landfall is maximum over BDS coast
followed by AP, ODS and TNP coasts in case of CS and
above [Figs. 8(a&b)], over BDS followed by AP, TNP,
ODS and WB coasts in case of SCS and above, over AP
followed by ODS/BDS, MMR, TNP and WB in case of
VSCS and above, over ODS followed by AP/MMR
and BDS in case of ESCS and above. There have been
one SuCS each crossing ODS, AP and BDS during the
period (Table 4). According to Tyagi et al., 2010, Over
48 percent of the TCs in the BoB strike different
parts of the east coast of India, 26 percent strike coasts of
BDS & MMR, 6 percent cross SLE and about 20 percent
dissipate over the sea itself. Percentage of TCs dissipating
over the AS is higher (63%) as the western AS is cooler.
Considering the individual categories of TCs,
frequency of landfall is maximum over BDS followed by
16 MAUSAM, 72, 1 (January 2021)
TABLE 6
Linear trend coefficients in individual and cumulative frequency of TCs landfalling over various regions during 1965-2020
Landfalling
region
Category
Total
Mean
Trend per 100
years
Category
Total
Mean
Trend per
100 years
NIO countries
ESCS &
above
34
0.61
-0.44
ESCS
31
0.55
-0.37
BoB countries
29
0.52
-0.39
26
0.46
-0.32
AS countries
5
0.09
0.04
5
0.09
-0.04
NIO countries
VSCS &
above
77
1.37
-2.37
VSCS
43
0.77
-1.93
BoB countries
64
1.14
-2.77
35
0.63
-2.38
AS countries
13
0.23
0.40
8
0.14
0.44
NIO countries
SCS &
above
117
2.09
-3.7
SCS
41
0.73
-1.33
BoB countries
101
1.8
-4.24
37
0.66
-1.47
AS countries
16
0.29
0.54
4
0.07
0.14
NIO countries
CS &
above
183
3.26
-4.65
CS
66
1.18
-0.95
BoB countries
156
2.79
-5.95
55
0.98
-1.71
AS countries
27
0.48
1.3
11
0.20
0.76
TC: Tropical cyclones, D: Depression/Deep Depression, CS: Cyclonic storm, SCS: Severe cyclonic storm, VSCS: Very severe cyclonic
storm, ESCS: Extremely severe cyclonic storm, NIO: North Indian Ocean, BoB: Bay of Bengal and AS: Arabian Sea
Bold: Statistically significant at 95% level of confidence, Bold & Italics: Statistically significant at 90% level of confidence
TABLE 7
Annual mean & linear trend coefficients (per 100 years) in actual frequencies of TCs landfalling over various regions during 1965-2020
Countries/
States of
India
ESCS
VSCS
SCS
CS
Total
Mean
Trend per
100 years
Total
Mean
Trend per
100 years
Total
Mean
Trend per
100 years
Total
Mean
Trend per
100 years
SLE
1
0.02
-
2
0.04
-
0
0.00
-
5
0.09
-0.26
TNP
2
0.04
-
7
0.13
-0.06
7
0.13
-0.55
4
0.07
-0.51
AP
5
0.09
-0.15
7
0.13
-0.25
10
0.18
-0.34
14
0.25
-0.16
Odisha
7
0.13
-0.16
4
0.07
-0.35
2
0.04
-
13
0.23
-1.17
WB
1
0.02
-
4
0.07
-0.23
6
0.11
0.13
2
0.04
-
BDS
4
0.07
-0.01
7
0.13
-0.91
12
0.21
-0.59
16
0.29
-0.23
MMR
6
0.11
0.16
4
0.07
-0.47
0
0.00
-
1
0.02
-
Gujarat
2
0.04
-
2
0.04
-
2
0.04
-
2
0.04
-
MNG
-
-
-
-
-
-
1
0.02
-
1
0.02
-
KTK
-
-
-
-
-
-
1
0.02
-
-
-
-
IAA
2
0.04
-
6
0.11
0.64
0
0.00
-
7
0.13
0.58
ECI
15
0.27
-0.52
22
0.39
-0.7
25
0.45
-0.89
33
0.59
-1.39
WCI
2
0.04
-
2
0.04
-
4
0.07
0.17
3
0.05
-
TC: Tropical cyclone, CS: Cyclonic storm, SCS: Severe cyclonic storm, VSCS: Very severe cyclonic storm, ESCS: Extremely severe
cyclonic storm, BoB: Bay of Bengal, AS: Arabian Sea, SLE: Sri Lanka East, TNP: Tamilnadu & Puducherry, AP: Andhra Pra desh, WB:
West Bengal, BDS: Bangladesh, MMR: Myanmar, MNG: Maharashtra & Goa, KTK: Karnataka, IAA: Iran, Arabia & Africa, ECI: East
Coast of India, WCI: West Coast of India,
Bold: Statistically significant at 95% level of confidence, Bold & Italics: Statistically significant at 90% level of confidence
AP and ODS in case of CS, over BDS followed by
AP, TNP and WB in case of SCS, over BDS/AP followed
by TNP/ODS/WB in case of VSCS, over ODS
followed by MMR, AP and BDS in case of ESCS. Thus,
to summarise, most intense TCs (ESCS & above with
MSW 90 kt) cross the coast maximum over ODS
followed by AP/MMR & BDS and low intensity
TCs (CS/SCS with MSW 34-63 kt) cross maximum
over BDS followed by AP, ODS & TNP and
medium intensity storms (VSCS with MSW
64-89 kt) cross over TN/AP/BDS followed by
ODS/WB/MMR.
MOHAPATRA et al. : FREQUENCY OF GENESIS & LANDFALL OF DIFFERENT CATEGORIES OF TC 17
TABLE 8
Annual mean & linear trend coefficients (per 100 years) in cumulative frequencies
of TCs landfalling over various regions during 1965-2020
Countries/
States of
India
ESCS & above
VSCS & above
SCS & above
CS & above
Total
Mean
Trend per
100 years
Total
Mean
Trend per
100 years
Total
Mean
Trend per
100 years
Total
Mean
Trend per 100
years
SL East
1
0.02
-
3
0.05
-
3
0.05
-
8
0.14
-0.49
TN
2
0.04
-
9
0.16
-0.06
16
0.29
-0.55
20
0.36
-0.50
AP
6
0.11
-0.25
13
0.23
-0.50
23
0.41
-0.84
37
0.66
-1.00
Odisha
8
0.14
-0.12
12
0.21
-0.46
14
0.25
-0.65
26
0.46
-1.87
WB
1
0.02
-
5
0.09
0.04
11
0.19
-0.13
13
0.23
-0.22
BDS
5
0.09
-0.02
12
0.21
-0.94
24
0.43
-1.53
40
0.71
-1.76
MMR
6
0.11
0.16
10
0.18
-0.31
10
0.18
-0.31
11
0.2
-0.15
Gujarat
2
0.04
-
4
0.07
-0.27
6
0.11
-0.32
8
0.13
-0.36
MNG
0
-
-
0
-
-
2
0.04
-
1
0.02
-
KTK
0
-
-
0
-
-
1
0.02
-
1
0.02
-
IAA
2
0.04
-
8
0.14
0.63
8
0.14
0.63
15
0.27
1.21
ECI
17
0.30
-0.59
38
0.68
-1.29
63
1.13
-2.18
96
1.71
-3.57
WCI
2
0.04
-
4
0.07
-0.27
9
0.16
-0.1
10
0.18
-0.03
TC: Tropical cyclone, CS: Cyclonic storm, SCS: Severe cyclonic storm, VSCS: Very severe cyclonic storm, ESCS: Extremely severe
cyclonic storm, BoB: Bay of Bengal, AS: Arabian Sea, SLE: Sri Lanka East, TNP: Tamilnadu & Puducherry, AP: Andhra Pradesh, WB:
West Bengal, BDS: Bangladesh, MMR: Myanmar, MNG: Maharashtra & Goa, KTK: Karnataka, IAA: Iran, Arabia & Africa, ECI: East
Coast of India, WCI: West Coast of India.
Bold: Statistically significant at 95% level of confidence, Bold & Italics: Statistically significant at 90% level of confidence
Considering the landfalling TCs over the AS, the
landfall frequencies of CS & above and SCS & above
and VSCS & above are the maximum over IAA followed
by GJT [Figs. 8(a&b)]. There is no VSCS or above
intensity storm crossing M&G coast. Further, there has
been no landfalling TC over GJT region, KRL and SLW
coast during 1965-2020. All the TCs making landfall over
GJT have crossed Saurashtra and Kutch coast during this
period. Tyagi et al. (2010) based on data of 1891-2007
also have shown that maximum landfall of TCs over the
AS occurs over GJT coast (18% of total TCs in AS) of
India followed by Oman coast.
3.3.3. Landfalling TCs for different coastal regions
during pre-monsoon season
During pre-monsoon season, the frequency of
landfalling TCs is maximum over BDS followed by MMR
in case of CS & above and SCS & above, over MMR
followed by BDS in case of VSCS & above and ESCS &
above intensity storms [Figs. 8(a&b)]. Considering
individual categories, the landfall frequency is maximum
over BDS in case of CS and SCS, over BDS/MMR in case
of VSCS and over MMR in case of ESCS. Thus, while
maximum CS/SCS cross BDS, maximum VSCS cross BDS/
MMR and maximum ESCS cross MMR coast during pre-
monsoon season. According to Pal and Chatterjee (2020),
the pre-monsoon TCs dissipated further northward
compared to the monsoon and post-monsoon TCs in BoB.
The pre-monsoon TCs over the BoB also significantly
moved eastward from average genesis location of 11.8° N/
88.7° E to 21.3° N / 91.1° E during pre-monsoon season
against 11.3° N / 88.8° E to 19.2° N / 83.5° E during post-
monsoon season. It could be therefore, the reason for TCs
to cross BDS/MMR more frequently during pre-monsoon
season. Wang et al. (2012 and 2013) have also discussed
the role of mid latitude westerlies for increased frequency
of intense storms landfalling over Myanmar.
Considering the landfalling TCs over the AS, the
landfall frequency of CS & above, SCS & above
and VSCS & above are maximum over IAA followed
by GJT. Over the AS, the mean genesis point is 12.3° N /
63.9° E and dissipation point is 19.4° N / 61.2° E during
pre-monsoon season (Pal and Chatterjee, 2020). During
pre-monsoon season usually genesis takes place over the
AS in association with onset of monsoon and they move
west-northwestwards towards IAA coasts.
3.3.4. Landfalling TCs for different coastal regions
during post-monsoon season
During post-monsoon season, the frequency of
landfall is maximum over AP followed by BDS, TNP,
18 MAUSAM, 72, 1 (January 2021)
Figs. 8[a&b(i-iii)]. (a) Individual frequency and (b) cumulative frequency of various categories of landfalling TCs during
(i) pre-monsoon, (ii) post-monsoon and (iii) year as a whole over the period 1965-2020
TC: Tropical cyclone, CS: Cyclonic storm, SCS: Severe cyclonic storm, VSCS: Very severe cyclonic storm, ESCS:
Extremely severe cyclonic storm and SuCS: Super Cyclonic Storm
SLE: Sri Lanka East, TNP: Tamilnadu and Puducherry, AP: Andhra Pradesh, OD: Odisha, WB: West Bengal, BDS:
Bangladesh, MMR: Myanmar, SLW: Sri Lanka West, KRL: Kerala, KNK: Karnataka, MNG: Maharashtra and Goa, GUJ:
Gujarat, PAK: Pakistan, IAA: Iran, Arabia and Africa
MOHAPATRA et al. : FREQUENCY OF GENESIS & LANDFALL OF DIFFERENT CATEGORIES OF TC 19
Figs. 9(i). Individual frequency of landfalling TCs over (a) NIO, (b) BoB & (c) AS and frequency of TCs landfalling over (d) Iran, Arabia &
Africa (e) West coast of India & (f) East coast of India during 1965-2020
TC: Tropical cyclone, BoB: Bay of Bengal, AS: Arabian Sea, NIO: North Indian Ocean, CS: Cyclonic storm, SCS: Severe cyclonic storm,
VSCS: Very severe cyclonic storm and ESCS: Extremely severe cyclonic storm, Linear: Linear Trend Line
ODS in case of CS & above, over AP followed by TNP,
BDS, ODS in case of SCS & above, over AP followed by
TNP, ODS, BDS in case of VSCS & above, over ODS
followed by AP, TNP/BDS in case of ESCS & above
intensity storms. Considering the individual categories,
the frequency of landfalling TCs is maximum over AP
followed by ODS, BDS, SLE, TNP in case of CS, over
AP followed by BDS & TNP in case of SCS, over
AP/TNP followed by BDS, WB & ODS in case of VSCS
and over ODS followed by AP, TNP/BDS in case of
ESCS. Thus, while maximum CS/SCS/VSCS cross AP
coast, maximum ESCS cross ODS coast during post-
monsoon season.
Considering the landfalling TCs over the AS, the
landfall frequency of CS & above and SCS & above and
VSCS & above are maximum over IAA followed by GJT.
It is also equal over IAA and GJT in the category of
VSCS & above. The maximum number of landfall over
IAA may be due to climatological track characteristics
(west-northwestward or northwestward movement of TCs
developing over the low latitude, i.e., over south AS) of
the TCs over the AS. According to Pal and Chatterjee
(2020), over the AS, the mean genesis point is near
12.1° N/66.6° E and dissipation point is near
17.5° N/60.9° E during post-monsoon season.
3.4. Trends in landfalling TCs
3.4.1. Trends in landfalling TCs over the Bay of
Bengal and Arabian Sea
There is a rising trend in frequency of VSCS and CS
over the AS [Table 6, Fig. 9 (i)]. Accordingly, there is a
20 MAUSAM, 72, 1 (January 2021)
Figs. 9(ii). Cumulative frequency of landfalling TCs over (a) NIO, (b) BoB & (c) AS and frequency of TCs landfalling over (d) Iran, Arabia &
Africa (e) West coast of India & (f) East coast of India during 1965-2020
TC: Tropical cyclone, BoB: Bay of Bengal, AS: Arabian Sea, NIO: North Indian Ocean, CS: Cyclonic storm, SCS: Severe cyclonic storm,
VSCS: Very severe cyclonic storm and ESCS: Extremely severe cyclonic storm, Linear: Linear Trend Line
rising trend in the frequency of landfalling CS & above,
SCS & above and VSCS & above over the AS [Fig. 9(ii)].
Comparing the similar trend analysis over individual
states of west coast of India and other countries like IAA,
PAK and SLW, it is found that there is rising trend in
landfalling TCs over the IAA [Table 7, Fig. 9(i)]. Thus, to
summarize, there is an increasing trend in the frequency of
landfalling TCs over AS namely in the categories of
VSCS and CS resulting in an increase in the frequency of
landfalling TCs over the IAA in the same categories and
accordingly in the frequency of CS & above, SCS &
above and VSCS & above crossing IAA. It could be
attributed to the fact that the (i) frequency of formation of
TCs over the AS might have increased in lower latitudes
and also in western longitude, (ii) westward movement of
the TCs over the AS could have increased and (iii) these
TCs are able to maintain their intensity over the relatively
colder west AS resulting in increased landfall over
Arabia-Africa. On the other hand, the frequency of
northeastward recurvature of the TCs over the AS could
have decreased due to weaker mid-latitude westerlies.
There is insignificant decreasing trend in the
frequency of landfalling TCs over the west coast of India
[Fig. 9, Tables 7&8]. To verify above hypothesis, we
analysed the westward moving and recurving tracks as
well as their genesis area over the AS. It is found that
there is a significant increasing trend in the genesis of TCs
over the southwest and westcentral AS (west of 64° E and
south of 20° N) as shown in Table 9 (Fig. 10). Most of
these TCs moved west-northwestward or northwestward
towards IAA leading to increase in landfall frequency
over the IAA. At the same time there is no trend in the
frequency of TC genesis over the east AS (east of 64° E)
and also there is no trend in the frequency of recurving
TCs over the AS [Figs. 10(a-d)].
MOHAPATRA et al. : FREQUENCY OF GENESIS & LANDFALL OF DIFFERENT CATEGORIES OF TC 21
Figs. 10(a-d). (a) Frequency of genesis and (b) frequency of recurvature of TCs over the AS during 1965-2020 and tracks of
(c) CS and (d) SCS over the AS during (i) 1965-1992 and (ii) 1993-2019
SW: Southwest, SE: Southeast, WC: Westcentral, EC: Eastcentral, AS: Arabian Sea, TC: Tropical Cyclone, Linear: Linear
Trend Line
Considering the landfalling TCs over the BoB, there
is a decreasing trend in CS & above, SCS & above, VSCS
& above and no trend in case of ESCS & above. Similar
trends are noticed in the individual categories of CS, SCS
& VSCS also (Table 6). The frequency of total landfalling
TC categories for east coast of India shows also
decreasing trend in case of CS & above, SCS & above and
VSCS & above and decreasing trend in the individual
category of CS, SCS, VSCS and ESCS. Tyagi et al.
(2010) have shown no significant trend in frequency of
22 MAUSAM, 72, 1 (January 2021)
Figs. 11(a-j). Actual Frequency of landfalling TCs over (a) Tamil Nadu, (b) Andhra Pradesh, (c) Odisha, (d) West Bengal, (e) Bangladesh
(f) Myanmar, (g) Gujarat (h) Maharashtra, (i) Pakistan and (j) Sri Lanka East during 1965-2020
TC: Tropical cyclone, BoB: Bay of Bengal, AS: Arabian Sea, NIO: North Indian Ocean, CS: Cyclonic storm, SCS: Severe cyclonic storm,
VSCS: Very severe cyclonic storm and ESCS: Extremely severe cyclonic storm, Linear: Linear Trend Line
MOHAPATRA et al. : FREQUENCY OF GENESIS & LANDFALL OF DIFFERENT CATEGORIES OF TC 23
Figs. 12(a-j). Cumulative frequency of landfalling TCs over (a) Tamil Nadu, (b) Andhra Pradesh, (c) Odisha, (d) West Bengal, (e) Bangladesh
(f) Myanmar, (g) Gujarat (h) Maharashtra, (i) Pakistan and (j) Sri Lanka East during 1965-2020
TC: Tropical cyclone, BoB: Bay of Bengal, AS: Arabian Sea, NIO: North Indian Ocean, CS: Cyclonic storm, SCS: Severe cyclonic storm,
VSCS: Very severe cyclonic storm and ESCS: Extremely severe cyclonic storm, Linear: Linear Trend Line
24 MAUSAM, 72, 1 (January 2021)
TABLE 9
Frequency of genesis and their linear trend coefficients over
different regions of AS during 1965-2020
Place of Origin
Total
Mean
Trend per 100 years
SW AS
8
0.14
0.67
SE AS
25
0.45
-0.19
WC AS
3
0.05
0.45
EC AS
28
0.50
0.45
SW+WC AS
11
0.20
1.12
SE+EC AS
53
0.95
0.26
SW+SE AS
33
0.59
0.48
WC+EC AS
31
0.55
0.90
SW: South West, SE: South East, WC: West Central, EC: East Central,
AS: Arabian Sea
landfalling CDs over east and west coasts of India during
1891-2007 excluding the short lived systems.
3.4.2. Trends in frequency of landfalling TCs over
different coastal regions
There is decreasing trend in the total frequency of
landfalling storms in the category CS & above and SCS &
above over ODS, CS & above, SCS & above and VSCS &
above over AP and BDS coasts during the year as a whole
(Table 7, Figs. 11&12). According to Singh et al., 2018,
GJT and IAA are more vulnerable coastal areas of AS
irrespective of seasons considered. According to Wang
et al. (2013), the ratio of frequency of TCs during pre-
monsoon season to the total annual frequency of TCs over
the BoB which moved towards Myanmar and Bangladesh
shows increasing trend during 1976-2011 which is
opposite to the findings of the current study.
4. Conclusions
Following broad conclusions are drawn from the
above results and discussion.
About 10 CDs and 5 TCs develop over the NIO
during a year including about 6.5 D, 1.8 CS, 0.9 SCS, 1.1
VSCS, 0.8 ESCS and 0.1 SuCS. Thus about 47%, 29%,
20% and 9% of CDs intensify into CS, SCS, VSCS and
ESCS respectively over the NIO. Similarly about 62%,
42% and 20% of total TCs intensify into SCS, VSCS and
ESCS respectively over the NIO. There is 69% and 32%
probability for an SCS to intensify into a VSCS and ESCS
respectively and 47% probability for a VSCS to intensify
into an ESCS.
The average frequency of D, CS, SCS, VSCS and
ESCS over the BoB(AS) are 4.3 (2.2), 1.4 (0.4), 0.6 (0.3),
0.8 (0.2) and 0.6 (0.2) respectively. The average frequency
of CD, CS & above, SCS & above, VSCS & above and
ESCS & above over the BoB (AS) is 7.8 (2.3), 3.5 (1.2),
2.2 (0.8), 1.5 (0.5) and 0.7 (0.3) respectively. The
probability of a CS to intensify into SCS, VSCS and ESCS
is almost same for both BOB and AS and the probability
of a CD becoming a TC is less over the BOB as compared
to AS by about 7% during the year as a whole.
The frequencies of genesis and landfall of all
categories of TCs are higher (by about 3 to 4 times) during
post-monsoon than in pre-monsoon season over the BoB.
While the genesis frequency is slightly higher in SCS,
VSCS and ESCS category, the landfall frequency is
almost same in both the seasons over the AS.
About 7.6 CDs (75% of genesis frequency) and 3.3
CS & above intensity storms (70% of CS and 33% of
genesis frequency) make landfall over the NIO. It includes
about 6.7 (0.9) and 2.8 (0.5) landfalling CDs and TCs
respectively over the BoB (AS). About 75% (35%), 81%
(29%), 69% (35%) and 69% (25%) of CS & above, SCS
& above, VSCS & above and ESCS & above during post-
monsoon season and 85% (52%), 84% (60%), 86% (70%)
and 85% (50%) of CS & above, SCS & above, VSCS &
above and ESCS & above during pre-monsoon season and
78% (42%), 84% (40%), 74% (48%) and 74% (36%) of
CS & above, SCS & above, VSCS & above and ESCS &
above over the BoB (AS) during year as a whole cross the
coast with at least the intensity of CS, SCS, VSCS &
ESCS respectively.
The most intense TCs (ESCS & above) cross the
coast maximum over ODS followed by AP/MMR & BDS
and low intensity TCs (CS/SCS) cross maximum over
BDS followed by AP, ODS & TNP and medium intensity
TCs(VSCS) cross maximum over TN/AP/BDS followed
by ODS/WB/MMR during year as a whole. While
maximum CS/SCS cross BDS, maximum VSCS cross
BDS/MMR and maximum ESCS cross MMR coast during
pre-monsoon season. While maximum CS/SCS/VSCS
cross AP coast, maximum ESCS cross ODS coast during
post-monsoon season. Over the AS, the landfall frequency
of CS & above and SCS & above and VSCS & above are
maximum over IAA followed by Saurashtra & Kutch
during both the seasons and year as a whole.
There is decreasing trend in genesis frequency of all
categories of CDs including D/DD, CS, SCS, VSCS,
ESCS and accordingly in frequency of D & above, CS &
above, SCS & above, VSCS & above and ESCS & above
during the post-monsoon season and the year as a whole,
in the frequency of D/DD, SCS, VSCS and hence D &
above, SCS & above and VSCS & above during pre-
monsoon season over the BoB. Accordingly, there is a
MOHAPATRA et al. : FREQUENCY OF GENESIS & LANDFALL OF DIFFERENT CATEGORIES OF TC 25
decreasing trend in landfalling CS, SCS, VSCS, CS &
above, SCS & above, VSCS & above over the BoB. It has
resulted in decreasing trend in the frequency of landfalling
CS, VSCS, CS & above and SCS & above over ODS, CS
& above, SCS & above and VSCS & above over AP, SCS,
VSCS, CS & above, SCS & above and VSCS & above
over BDS, VSCS over MMR coasts during the year.
There is increasing trend in the frequency of ESCS,
CS & above, SCS & above, VSCS & above and ESCS &
above during the year as a whole, VSCS, ESCS, VSCS &
above and ESCS & above during post-monsoon season
and CS & above and SCS & above during pre-monsoon
season over the AS.
There is an increasing trend in the frequency of
landfalling TCs over AS in the categories of VSCS and
CS resulting in an increase in the frequency of landfalling
TCs over the IAA in the same categories and accordingly
in the frequency of CS & above, SCS & above and VSCS
& above crossing IAA. It could be attributed to increase in
genesis frequency of the TCs over the western AS and no
significant trend in the frequency of
eastward/northeastward recurving TCs over the AS apart
from other synoptic and dynamical influences like
increase in TCHP and decrease in vertical wind shear over
the region. There is decreasing trend in frequency of
landfalling SCS & above and VSCS & above over
Saurashtra and Kutch, while there have been no landfall
over Gujarat region during the period.
While with no significant trend in the frequency of
ESCS and above intensity storms the coastal vulnerability
due to ESCS continues with same magnitude over the
BoB region, it has increased over the IAA coast due to
increasing trend in frequency of VSCS and above
intensity storms.
A further examination of TC occurrences is needed
to establish a direct cause-and-effect relationship behind
the significant trends in genesis and landfall frequencies
of TCs over the BoB and AS including the role of local
and large scale dynamical and thermodynamical,
atmospheric and Oceanic factors as well as the role
anthropogenic influence on TC activity over the region.
The latter could be better understood through fine-
resolution regional climate modelling and reanalyses of
historical TC dataset to reduce the uncertainty in the
estimation of intensity of TCs.
Acknowledgement
The authors thank Mr. Aditya Chaudhary, Mr.
Gaurav Kumar Srivastav, Ms. Shilpa Singh, Mr Mukesh
Kumar, Mr. Santosh Singh and Mr. V. Vijay Kumar,
Cyclone Warning Division of IMD for their assistance in
collection and preparation of dataset used in this study.
The contents and views expressed in this research paper
are the views of the authors and do not necessarily reflect
the views of their organizations.
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... TROPICAL cyclones (TCs) are the most catastrophic vulnerable natural weather phenomenon with substantial socioeconomic impacts [1][2][3] . The entire Indian coastal belt is prone to TCs 3 . ...
... These classifications help meteorologists predict the behaviour of the disturbances and issue warnings accordingly. Based on the T number and the maximum sustained wind speed, the classification of tropical disturbances over the NIO was adopted by IMD 3 . ...
... Based on long-term mean TC occurrences, the frequency of occurrence of TCs over the NIO is higher during the post-monsoon season than pre-monsoon season 3 . In addition, more TC formation over the Bay of Bengal (BoB) than in the Arabian Sea was also observed. ...
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The present study investigates the structural, dynamic and thermodynamic characteristics of severe cyclonic storm, ‘Dana’, the first post-monsoon tropical cyclone over the North Indian Ocean in 2024. Using synoptic data and satellite imageries, we have analysed the evolution of storm, intensity changes and atmospheric interactions. The structural analysis reveals that ‘Dana’ predominantly exhibited an irregular central dense overcast pattern with a mean diameter of 173 km throughout its lifecycle. Dynamically, the development and movement of the cyclone were influenced by wind profiles, sea-surface temperature (SST), upper-level divergence, lower-level convergence and atmospheric pressure patterns. The average vertical wind shear was 16 knots, increasing to 20 knots during cyclone strengthening. Regarding thermodynamics, SST ranged from 29°C to 30°C over the central and northern Bay of Bengal and the north Andaman Sea, with tropical cyclone heat potential between 100 and 112 kJ/cm2 This study integrates satellite-based observations with traditional meteorological data, providing valuable insights into the internal dynamics of the cyclone and contributing to improved forecasting and understanding of factors influencing tropical cyclone intensity and track in the region.
... These orbits were chosen in such a way that major portions of the TC including eyewall region covered in the DPR passes. The India Meteorological Department (IMD) classifies a TC in seven categories namely, depression (D), deep depression (DD), cyclonic storm (CS), severe CS (SCS), very severe CS (VSCS), extremely severe CS (ESCS), and super CS (SuCS) based on the maximum sustained wind speed (Mohapatra et al. 2021). In this study, we considered the GPM-DPR data for TCs with intensity of CS and above. ...
... In addition, vertical wind shear and lower to middle tropospheric humidity play distinct roles in TC genesis during pre-and post-monsoon seasons over both basins of the NIO (Duan et al. 2021). Premonsoon TCs over the NIO generally follow north northeastward track, whereas TCs formed during the post-monsoon season usually move west northwestward (Mohapatra et al. 2021). Among these 30 GPM-DPR orbits, 17 orbits for 11 TCs are over the BoB basin and 13 orbits for 10 TCs over the AS basin. ...
... Although mean surface stratiform precipitation rates during the pre-monsoon season are close to each other for TCs over the BoB and the AS basins, TCs over the AS provide about 75% higher mean surface convective precipitation rate than TCs over the BoB during the pre-monsoon season. Rather warmer sea surface temperature of the AS along with northward propagation of the intertropical convergence zone associated with setting up the southwest monsoon over India are conducive for the development of convective clouds during pre-monsoon TCs (Mohapatra et al. 2021). During post-monsoon TCs, mean surface stratiform precipitation rate is higher over the AS than the BoB, and it is opposite for the mean surface convective precipitation rate. ...
... TROPICAL cyclone (TC) is a multi-hazardous natural weather phenomenon associated with strong wind, heavy rainfall and storm surge. Although the North Indian Ocean (NIO) accounts for about 7% of the global TC activities, they intermittently lead to substantial socio-economic impacts over the affected coastal areas [1][2][3] . Based on the besttrack data of the India Meteorological Department (IMD) from 1891 to 2023, TC activities over the NIO dominate during either pre-monsoon (April to June) or post-monsoon (September to December) seasons (Figure 1 a). ...
... A significant increase in annual frequency, duration and strength of TCs over the AS was noticed during 2001-2019 compared to 1982-2000, while no significant change was observed over the BoB 1,4 . In addition, the frequency of TCs over the NIO during the southwest monsoon season showed an increasing trend associated with a decrease in vertical wind shear, warming of sea-surface temperature, and a decrease in the tropical easterly jet 5 . ...
... As per the IMD rapid intensification (RI) criteria, whether a TC has a persistent maximum sustained wind at 30 knots within 24 h, referred to as RI, has been analyzed during these 20 years (2004-2023), showing that the maximum RI occurred in the month of May As per the IMD rapid intensification (RI) criteria, whether a TC has a persistent maximum sustained wind at 30 knots within 24 h, referred to as RI, has been analyzed during these 20 years (2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017)(2018)(2019)(2020)(2021)(2022)(2023), showing that the maximum RI occurred in the month of May as compared to April, as represented in Figure 1b. Typically, the TC genesis occurs in the lower latitudes and rapidly intensifies while moving over the higher latitudes [31,32]. as compared to April, as represented in Figure 1b. ...
... as compared to April, as represented in Figure 1b. Typically, the TC genesis occurs in the lower latitudes and rapidly intensifies while moving over the higher latitudes [31,32]. According to the IMD, Cyclone Mocha initially moved southeastward over the BoB before shifting north-northwestward at a speed of 8 km/h. ...
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Citation: Pradhan, P.K.; Kumar, S.; Pandey, L.K.; Desamsetti, S.; S. Thota, M.; Ashrit, R. Dynamical Mechanisms of Rapid Intensification and Multiple Recurvature of Pre-Monsoonal Tropical Cyclone Mocha over the Bay of Bengal. Meteorology 2025, 4, 9. Abstract: Cyclone Mocha, classified as an Extremely Severe Cyclonic Storm (ESCS), followed an unusual northeastward trajectory while exhibiting a well-defined eyewall structure. It experienced rapid intensification (RI) before making landfall along the Myanmar coast. It caused heavy rainfall (~90 mm) and gusty winds (~115 knots) over the coastal regions of Bay of Bengal Initiative for Multi-Sectoral Technical and Economic Cooperation (BIMSTEC) countries, such as the coasts of Bangladesh and Myanmar. The factors responsible for the RI of the cyclone in lower latitudes, such as sea surface temperature (SST), tropical cyclone heat potential (TCHP), vertical wind shear (VWS), and mid-tropospheric moisture content, are studied using the National Ocean and Atmospheric Administration (NOAA) SST and National Center for Medium-Range Weather Forecasting (NCMRWF) Unified Model (NCUM) global analysis. The results show that SST and TCHP values of 30 • C and 100 (KJ cm −2) over the Bay of Bengal (BoB) favored cyclogenesis. However, a VWS (ms −1) and relative humidity (RH; %) within the range of 10 ms −1 and >70% also provided a conducive environment for the low-pressure system to transform into the ESCS category. The physical mechanism of RI and recurvature of the Mocha cyclone have been investigated using forecast products and compared with Cooperative Institute for Research in the Atmosphere (CIRA) and Indian Meteorological Department (IMD) satellite observations. The key results indicate that a dry air intrusion associated with a series of troughs and ridges at a 500 hPa level due to the western disturbance (WD) during that time was very active over the northern part of India and adjoining Pakistan, which brought north-westerlies at the 200 hPa level. The existence of troughs at 500 and 200 hPa levels are significantly associated with a Rossby wave pattern over the mid-latitude that creates the baroclinic zone and favorable for the recurvature and RI of Mocha cyclone clearly represented in the NCUM analysis. Moreover the Q-vector analysis and steering flow (SF) emphasize the vertical motion and recurvature of the Mocha cyclone so as to move in a northeast direction, and this has been reasonably well represented by the NCUM model analysis and the 24, 7-, and 120 h forecasts. Additionally, a quantitative assessment of the system indicates that the model forecasts of TC tracks have an error of 50, 70, and 100 km in 24, 72, and 120 h lead times. Thus, this case study underscores the capability of the NCUM model in representing the physical mechanisms behind the recurving and RI over the BoB.
... As per the IMD rapid intensification (RI) criteria, whether a TC has a persistent maximum sustained wind at 30 knots within 24 h, referred to as RI, has been analyzed during these 20 years (2004-2023), showing that the maximum RI occurred in the month of May As per the IMD rapid intensification (RI) criteria, whether a TC has a persistent maximum sustained wind at 30 knots within 24 h, referred to as RI, has been analyzed during these 20 years (2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017)(2018)(2019)(2020)(2021)(2022)(2023), showing that the maximum RI occurred in the month of May as compared to April, as represented in Figure 1b. Typically, the TC genesis occurs in the lower latitudes and rapidly intensifies while moving over the higher latitudes [31,32]. as compared to April, as represented in Figure 1b. ...
... as compared to April, as represented in Figure 1b. Typically, the TC genesis occurs in the lower latitudes and rapidly intensifies while moving over the higher latitudes [31,32]. According to the IMD, Cyclone Mocha initially moved southeastward over the BoB before shifting north-northwestward at a speed of 8 km/h. ...
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The Mocha cyclone, an extremely severe cyclonic storm (ESCS), moved unusually northeastwardly with a well-organized eyewall structure, underwent rapid intensification (RI), and then entered into coastal areas of Myanmar. It caused heavy rainfall (~90 mm) and gusty winds (~115knots ) over the coastal regions of BIMSTEC countries, such as the coasts of Bangladesh and Myanmar. The factors responsible for the RI of the cyclone in lower latitudes, such as SST, TCHP, vertical wind shear (VWS), and mid-tropospheric moisture transport, are studied using the National Ocean and Atmospheric Administration (NOAA) SST and National Centre for Medium Range Weather Forecasting (NCMRWF) Unified Global Model (NCUM) analysis. The results show that SST and TCHP values of 30℃ and 100 (KJcm-2) over BoB favored cyclogenesis. However, VWS (ms-1) and relative humidity (RH) within the range of 10 m/s and > 70% also provided a conducive environment for the cyclone to transform into the ESCS category. The physical mechanism of RI and recurvature of the Mocha cyclone have been investigated using forecast products and compared with CIRA and IMD satellite observations. Key results indicate that the dry air intrusion associated with a series of troughs and ridges at 500 hPa level due to the western disturbance (WD) during that time was very active over the northern part of India and adjoining Pakistan, which brought north-westerlies at 200hPa level. The Q-vector analysis and steering flow (SF) underscore that baroclinic instability plays a crucial role in allowing the Mocha cyclone to move in northeast directions, and it has been reasonably well represented by the NCUM model analysis and the 24-, 72-, and 120-hour forecast. Additionally, a quantitative assessment of the system indicates that the model forecasts of TC tracks have an error of 50, 70, and 100 km in 24-, 72-, and 120-hour lead times. Thus, the present case study underscores the strength of the NCUM model in representing the physical characteristics of the recurving and RI systems over BoB.
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An extremely severe cyclonic storm (ESCS) Biparjoy crossed the Gujarat coast near Jakhau around 1730 UTC 15 June 2023 with a maximum sustained wind (MSW) speed of 32–35 m s⁻¹ gusting to 39 m s⁻¹. From 1891 to 2023, 22 tropical cyclones (TCs) have crossed the Gujarat coast (India). Out of these, the ESCS in 1998 (TC Kandla) was similar to the recent TC Biparjoy. During June 1998, TC Kandla crossed the Gujarat coast near Porbandar around 0130 UTC 9 June with an MSW of 44–47 gusting to 50 m s⁻¹ and again near Kandla around 0900 UTC of the same day with an MSW of 40–43 m s⁻¹ gusting to 47 m s⁻¹. Official government records indicate that TC Kandla caused deaths of about 1173 people and TC Biparjoy caused no death in Gujarat. Despite frequently changing track and intensity and rapid intensification, the Indian Meteorological Department predicted all the features of TC Biparjoy including genesis, track, intensity, landfall, associated heavy rain, winds and storm surge, and damage accurately with sufficient lead time. Active response actions from stakeholders resulted in zero loss of life in Gujarat State. A comparative analysis of the early warning system (EWS) of TC Biparjoy in 2023 and TC Kandla in 1998 is made to evaluate the progress made over the years and identify gap areas for further improvement. The study shows that the success in EWS of TCs could be achieved through improvements in all components of EWS including observations, data communication, analysis, modeling, forecasting, and warning services. Significance Statement This study aims to evaluate the progress in the early warning system (EWS) of tropical cyclones (TCs) in the last 25 years in India by comparing the EWS for two similar TCs that hit Gujarat in 1998 and 2023. The results show that there has been a paradigm shift in all components of EWS including observations, data communication, analysis, modeling, forecasting, warning products generation, and dissemination which has enabled disaster managers to minimize the death toll associated with most TCs in the region over the past decade to double digits. The zero death during TC Biparjoy in Gujarat State in 2023 is a demonstration of role of weather and climate science, especially EWS for early action by disaster managers and hence the benefit of society.
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Tropical cyclone (TC) is a rapidly intensifying storm over warm water of oceans, critically studied for its potential to inflict severe damage and pose life-threatening hazards. The present study focuses on exploring the pre- and post-cyclone characteristics of TC Amphan and Nisarga using ECMWF Reanalysis v5 (ERA5) reanalysis. Our analysis reveals that the TC features, such as its intensity, life cycle, wind circulations, the warm-core structure evolution, and the related environmental factors, are consistent with India Meteorological Department observations. The presented results have indicated that maximum sustainable wind speed, central sea level pressure, lower troposphere temperature and lower stratosphere temperature along the radius from the TC center create a favourable condition that eventually leads to the formation and intensification of super and severe cyclonic storms, for example, Amphan and Nisarga, respectively. The analysis suggests that the atmospheric instability, TC formation, development, and energy for intensification are controlled mainly by the warmer-than-average Arabian Sea and Bay of Bengal basin sea surface temperature anomalies in the Indian Ocean region. The results indicated that the TC genesis and movement are well captured by ERA5, close to the observed best tracks provided by the India Meteorological Department, with an RMSE of ∼31 km. The vorticity budget analysis illustrates that in the developing and mature stages of TC, the tilting term converts horizontal vorticity into vertical vorticity via upward motion. During the dissipation phase, the tilting term reverses, resulting in a fall in vertical vorticity, which weakens or dissipates the TC intensity. Overall, the circulation pattern appears to reproduce most of the essential characteristics of the mature stage of TCs, like the eye and eyewall, highlighting the importance of near real-time high-resolution reanalysis datasets for exploring the details of extreme events.
Article
Cyclones tracking northward across the Bay of Bengal represent a significant threat to life and safety when they make landfall. Surface moorings of the Ocean Moored Network for the Northern Indian Ocean in the Bay of Bengal have been deployed to provide real-time observations in support of improved alerts and predictions of cyclones. Engineering goals are both to develop robust surface moorings that survive and to field meteorological and oceanographic instruments that reliably provide data in real time. While the mooring design and reliability were previously reported, the focus here is on the motivations for installing the instrumentation, and on experience gained during the passage of cyclone Amphan in May 2020, examining the sensor as well as mooring performance. The paper presents reasons for fielding the chosen sensors, merits, and shortcomings during the effort to observe Amphan, and recommendations for how to better address the challenges of providing real-time observations of cyclones in the Bay of Bengal.
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A review is presented of the radar observation of tropical cyclones in the Indian seas. The use of radar in operational cyclone tracking and forecasting as well as the knowledge gained from radar observations of the structure, wind and rainfall distribution and motion of cyclones are discussed. In the context of the expected introduction of operational Doppler ra1ars in India, the future prospects in the use of radar for operations and research are outlined. Some important areas where our understanding of cyclones can be improved by studies with radar in conjunction with other observations are listed.
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Tropical cyclone (TC) genesis over the North Indian Ocean (NIO) region showed significant amount of both spatial and temporal variability.It was observed that the TC genesis was significantly suppressed during the monsoon (June-September) compared to pre-monsoon (March-May) and post-monsoon (October-December) season specifically in terms of severe cyclonic storms (SCS) frequency. The Bay of Bengal (BoB) was characterized by higher TC frequency but lower intensity compared to the Arabian Sea (AS). It was also observed that the TC genesis locations were shifted significantly seasonally.The movement of the TCs also portrayed some significant seasonal differences. The pre-monsoon and post-monsoon season was responsible for generating TCs with higher values of accumulated cyclone energy (ACE) compared to the monsoon. The time series of TC frequency showed a statistically significant decreasing trend whereas the time series of ACE showed astatistically significant increasing trend over the NIO.
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India experiences various types of natural hazards including cyclones, floods, droughts, earthquake, landslides, heat wave, cold wave, thunder squalls and tornadoes. Most of these hazards (about 80%) are hydrometeorological in nature. Among the hydrometeorological hazards, the cyclones over the North Indian Ocean (NIO) pose a potential threat to coastal population as well as marine community of the region. The risk management of the cyclones depends on several factors including (i) hazard & vulnerability analysis, (ii) preparedness & planning, (iii) early warning, (iv) prevention and mitigation. The early warning component includes (i) skill in monitoring and prediction, (ii) effective warning products generation and dissemination, (iii) coordination with disaster response units and (iv) public awareness & perception about the credibility of early warning of cyclone issued by India Meteorological Department (IMD). Though there have been significant improvement in cyclone monitoring and warning system in recent years due to modernization programme of Ministry of Earth Sciences (MoES)/IMD and policy frame work of Govt of India, there is still scope for improvement at state and district level in terms of (i) improving the mesoscale hazard detection and monitoring in association with cyclone, (ii) improving the spatial and temporal scale of forecasts through technological upgradation, (iii) warning communication to last mile and disaster managers through state of art technology, (iv) developing synergized standard operation procedure among the early warning agencies and user agencies and (v) real time impact based forecast and risk based warning. All these aspects have been discussed with special emphasis on climatological characteristics (spatial and temporal distribution and intensity etc.), damage potential, modeling and prediction, Prediction skills, information dissemination mechanisms, socio-economic impacts, achievements in recent years, existing gap areas and future scope.
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In this study, the contribution of El Niño-Southern Oscillation (ENSO) to the rainfall and temperature over Bangladesh has been investigated. Rainfall, temperature and ENSO data have been used for a period of 60 years (1958-2017). This paper examines the spatial distribution of rainfall and temperature across Bangladesh and the results suggest that the distribution of rainfall and temperature varies with seasons. A geographically weighted regression, student t test, correlation coefficient and cross-wavelet transform were used to reveal whether different types of ENSO contribute strongly or weakly to rainfall and temperature in Bangladesh. Findings indicate that the ENSO has a strong connection with rainfall and temperature over Bangladesh.
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Climatologically, tropical cyclone (TC) activity in the North Indian Ocean (NIO) is asymmetric between the Arabian Sea (AS) and Bay of Bengal (BoB) basin. For the 172 TCs formed over NIO during 1983–2015, only 56 formed over AS and the rest (116) over BoB. During the period, AS was very active in a few years (but with quiet BoB season), and the opposite occurred in some others. It is found that this contrast occurred mostly during the post‐monsoon season of October–December. The meteorological and climate factors that accounted for these contrasting AS and BoB TC seasons are analysed. While climate variability such as the El Niño Southern Oscillation and Indian Ocean Dipole have known influences to NIO TC activity, results reveal that no single climate mode can well explain the TC development concentrating on AS or BoB only. Instead, it is found that variability of the northeast monsoon is an important factor responsible for the difference between the two basins. Excess moisture is available over the AS due to anomalous low‐level flow from the equatorial IO in the years in which there are more TCs in that basin, and dryer condition is over the BoB. In these years, there is likely excess northeast monsoon rainfall. The relationship is opposite between post‐monsoon BoB TC activity and the northeast monsoon. Nevertheless, the anomalous flow during active AS TC seasons is similar to that occurs during positive Indian Ocean Dipole, and thus this climate variability may be responsible for redistributing the moisture content in the NIO.
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The occurrence of the 2017/2018 La Niña, following a weak-to-neutral La Niña in boreal winter 2016/2017, was surprising. Based on observational records and multiple linear regression analysis for the Pacific zonal wind tendency (dU/dt), this study investigates possible reasons why the La Niña condition suddenly happened in late 2017. Similar to previous four double-peaked La Niña events (1983–1985, 1998–2000, 2007–2009, and 2010–2012), we find that the multiyearly persistent easterly anomaly in the central equatorial Pacific is a key condition to the development of the second La Niña. The occurrence of the 2017/2018 La Niña results from large warm sea surface temperature (SST) anomalies in the tropical Indian and Atlantic Oceans that act to force the persistent easterly anomaly in the Pacific via modifying the Walker Circulations. About 24% of the variance of the Pacific dU/dt can be statistically explained by the tropical Indian Ocean and Atlantic SST anomalies.
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In 2014 and 2015, post-monsoon extremely severe cyclonic storms (ESCS)—defined by the WMO as tropical storms with lifetime maximum winds greater than 46 m s⁻¹—were first observed over the Arabian Sea (ARB), causing widespread damage. However, it is unknown to what extent this abrupt increase in post-monsoon ESCSs can be linked to anthropogenic warming, natural variability, or stochastic behaviour. Here, using a suite of high-resolution global coupled model experiments that accurately simulate the climatological distribution of ESCSs, we show that anthropogenic forcing has likely increased the probability of late-season ECSCs occurring in the ARB since the preindustrial era. However, the specific timing of observed late-season ESCSs in 2014 and 2015 was likely due to stochastic processes. It is further shown that natural variability played a minimal role in the observed increase of ESCSs. Thus, continued anthropogenic forcing will further amplify the risk of cyclones in the ARB, with corresponding socio-economic implications.
Chapter
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Indian coastal regions are vulnerable to the destructive effects of land-falling tropical cyclones (TCs) that form over the North Indian Ocean (NIO). In the view of global climate variability and global warming, it is important to analyse the trends in frequencies of cyclonic disturbances (CDs) forming over the NIO. CDs include depressions (maximum sustained surface wind speed (MSW) of 17–33 knots) and TCs (MSW ≥ 34 knots). In this chapter, long-term trends in seasonal and annual frequency of CDs, TCs and severe TCs (MSW of 48 Knots or more) over the NIO are presented based on the data of 1901–2010. The trends are also analysed with the perspective of climate forcing such as the El-Nino/Southern Oscillation (ENSO). Over the Bay of Bengal (BOB) and the NIO, significant decreasing trends in the frequencies of CDs as well as TCs are observed during the monsoon season (June–Sept) during the period 1901–2010. Significant increasing trend in severe TCs during the post-monsoon season (October–December) was also observed during the same period. Over the Arabian Sea (AS), there is a significant increase in the frequency of CDs during the monsoon and the post-monsoon seasons. However, during the satellite period (1961–2010), CDs, TCs and severe TCs over the NIO and BOB show significant decreasing trends for the monsoon and post-monsoon seasons and the year as a whole. No significant trend is observed over the AS during the same period. Analysis of role of ENSO on the frequency of CDs/TCs/severe TCs indicates that the impact of ENSO has decreased in the recent years. However, in the case of the post-monsoon TCs and severe TCs, significant negative relation has emerged since 1995 with Nino 3.4 SST in concurrent and antecedent (monsoon season) modes. Significant positive relationship that existed between the monsoon rainfall over meteorological sub-divisions of Central India and CDs frequency during the period 1940–1990 weakened drastically during the later years. Also, significant positive relationship that existed with the north-east monsoon rainfall (October–December) over south-eastern sub-divisions of India up to 1980 has weakened subsequently.
Article
Tropical cyclone (TC) prediction and impact of warming environment on cyclonic activity are one of the most popular research topics. Based on sea surface temperature (SST) anomaly variation, the period 1880–2015 is divided into pre-warming (PWP; during 1880–1946) and current warming (CWP; during 1947–2015) with negative and positive anomalies respectively. Based on data availability, the period 1891–2015 is emphasized for the analysis of variability in TC climatology. The Mann-Kendall test and Sen’s slope estimation indicates a clear decreasing trend in annual TS (total storms) and CS + SCS (cyclones and severe cyclones) frequency during CWP for NIO region and particularly Bay of Bengal (BOB) at 95% confidence level. However, the TS and CS + SCS frequencies were increasing during the PWP. TC activity over southern and northern BOB is decreasing sharply during CWP. Southern sector of BOB hosts mostly severe systems and middle sector most TCs. TC activity over the eastern sector of Arabian Sea shows considerable enhancement during CWP. An increasing SST, surface wind, mid-tropospheric relative humidity and potential evaporation factor (PEF) are helpful in the formation of intensified storms during CWP. The activities during PWP were reverse compared to that of CWP. A large temperature anomaly difference between atmosphere and Ocean also perceived to play a key role in modulating the enhanced intensity of TCs during CWP. The SST range of 27.5 °C to 29.5 °C and supportive flow field is helping to enhance the middle and upper tropospheric moisture content; eventually, resulting in increased SST, PEF and relative humidity through a possible feedback mechanism.
Chapter
There is a growing need for improvement in tropical cyclone (TC) vital parameters (Knaff 2011) in view of the requirements of numerical weather prediction (NWP) models and various stake holders. As the damage due to a TC is directly proportional to the square of the maximum sustained wind (MSW) and loss due to a TC is proportional to cube of MSW, the surface wind structure associated with a TC serves insurance agencies to assess the damage due to a TC. The disaster managers who prepare for the impact of a landfalling TC may use the wind field information as guidance as to where the most severe wind or surge damage may occur. The TC Vital parameters also serve as input to NWP models and storm surge models that are run prior to landfalling events to create synthetic vortex (Chourasia et al. 2013), as most of the NWP models fail to simulate accurately the location and intensity of the TC. The creation of synthetic vortex helps in improving the track and intensity forecast of the model. In the parametric storm surge prediction models, the surface wind structure in the quadrant base form alongwith the radius of maximum wind (RMW) and pressure drop (ΔP) at the centre are utilised to create the wind stress and hence predict the storm surge (Dube et al. 2013). In post-event cases, these wind structure data are utilised for diagnosis of TC and to better plan for future TC forecasts. Engineers and planners rely on historical TC information to determine long-term risks to facilities and infrastructure and to ensure the resilience of communities to potential disasters. Another most important use of this product is the determination of ship avoidance area over the sea due to a TC.