North Indian Ocean Tropical Cyclones from 2010 to 2022: Loss of Economy, Fatalities and Regions affected
As we all know
the weather disaster has increased progressively in the last century. If we
focus on factors, there are two sets of factors that contribute to global weather-related
disasters. The first correlated set of factors is ocean heat level, tropical
cyclone, sea-level rise, increasing storm intensity, higher precipitation rate,
frequency of intense cyclones, and surge flooding. Second, the population density
and urbanization vulnerability specifically in coastal cities and in small
islands in developing countries with disproportionate risk calculation. The
socioeconomic incongruity, damaged ecosystem health, and unplanned fragile
infrastructures can be the other considerable reasons.
The bitter truth
is the public health hazards and their consequences after a cyclone will continue
if some robust solutions are not followed to mitigate and adapt these progressive
risk dynamics.
Tropical and
Temperate Cyclones
Whenever we heard Cyclone, we imagine fatalities and property damage, and thatās true!
Both Tropical and Temperate cyclones are powerful storm winds that can sustain for hours to days and push the ocean waters creating storm surges and potential floods over an area. In some countries, cyclones can create agitated hurricane movements and can be formed into potential Typhoons, Tornadoes, and Twisters. Tropical cyclones can occur only in the summer months in areas with high temperatures and very low pressure, which causes an imbalance of the natural climate causing an increase of the sea level water temperature beyond 26 degrees centigrade and with a high relative humidity beyond 700m. The temperate cyclones can occur any time of the year as they follow the frontal weather systems.
Most Dreaded North Indian Ocean Tropical Cyclones from 2010 to 2022
The North Indian Ocean cyclone season is the most dynamic type of cyclone
season in the North Indian Ocean. The two main oceans in the region are the Arabian
sea and the Bay of Bengal. The meteorological data of the region are mostly analyzed
officially by India Meteorological Department (IMD). The season sees 8
depressions and 5 types of storms mostly in between the months of April and
June, and October and December.
IMD categorized the severity of cyclonic storms broadly into 7 categories
considering the causing factor as wind speed (WS), Depression (WS 31-50 km/hr), Deep Depression (WS
51-62 km/hr), Cyclonic storm (WS 63-88 km/hr), Severe Cyclonic Storm (89-117 km/hr),
Very Severe Cyclonic Storm (WS 118-165 km/hr), Extremely Severe Cyclonic Storm (WS 166-
220 km/hr) and Super Cyclonic Storm (WS ā„ 221 km/hr).
The Table below can give you an idea of the most affected cyclones from
2010 to 2022 considering the categorization done by IMD; severity, damage to the economy,
and deaths ported as the three important factors.
Table: The cyclonic storm details from 2010-2022.
Year |
Name of Cyclone |
Dates of occurrence |
Category as per IMD |
Countries and areas affected |
Death cases |
Economical losses (in $) |
2010 |
Laila |
May 17-May 21 |
Severe Cyclonic Storm |
Sri Lanka, India |
65 |
117 million |
Phet |
May 31-June 7 |
Very Severe Cyclonic Storm |
Oman, Pakistan, India |
47 |
861 million |
|
Giri |
Oct 20-Oct 23 |
Extremely Severe Cyclonic Storm |
Bangladesh, Myanmar, Thailand, Yunnan |
167 |
359 million |
|
Jal |
Nov 1-Nov 8 |
Severe Cyclonic Storm |
Thailand, Malaysia, Andaman Islands, India |
117 |
1.73 billion |
|
2011 |
BOB 01 |
Feb 2- Feb 3 |
Depression |
Sri Lanka |
18 |
297 million |
BOB 04 |
Oct 19-Oct 20 |
Deep Depression |
Bangladesh, Myanmar |
215 |
1.64 million |
|
Keila |
Oct 29- Nov 4 |
Cyclonic Storm |
Oman, Yemen |
14 |
80 million |
|
Thane |
Dec 25-Dec 31 |
Very Severe Cyclonic Storm |
India |
46 |
275 million |
|
2012 |
Nilam |
Oct 28-Nov 1 |
Cyclonic storm |
Sri Lanka, India |
75 |
56.7 million |
2013
|
Viyaru |
May 10-May 17 |
Cyclonic Storm |
Indonesia, Thailand, Sri Lanka, India, Bangladesh, Myanmar |
|
|
ARB 01 |
Nov 8-Nov 11 |
Deep Depression |
Somalia, Ethiopia |
162 |
NA |
|
Phailin |
Oct 8-Oct14 |
Extremely Severe Cyclonic Storm |
Malay Peninsula, Andaman and Nicobar Islands, India, Myanmar, Nepal |
45 |
4.26 billion |
|
Helen |
Nov 19-Nov23 |
Severe Cyclonic Storm |
India |
11 |
796 million |
|
2014 |
Land 02 |
Aug 4-Aug 7 |
Deep depression |
India, Bangladesh |
47 |
NA |
Hudhud |
Oct 7-Oct 14 |
Extremely severe cyclonic storm |
Andaman and Nicobar Islands, India, Visakhapatnam, Nepal |
124 |
3.58 billion |
|
Nilofar |
Oct 25-Oct 31 |
Extremely severe cyclonic storm |
India, Pakistan |
0 |
NA |
|
2015 |
ARB 02 |
Jun 22-Jun 24 |
Deep depression |
West India |
81 |
260 million |
Komen |
Jul 26-Aug 2 |
Cyclonic storm |
Bangladesh, Myanmar, Northeastern India |
187 |
678 million |
|
Chapala |
Oct 28-Nov 4 |
Extremely severe cyclonic storm |
Oman, Somalia, Yemen |
8 |
ā„ 100 million |
|
Megh |
Nov 5-Nov 10 |
Extremely severe cyclonic storm |
Oman, Somalia, Yemen |
18 |
NA |
|
BOB 03 |
Nov 8-Nov10 |
Deep depression |
South India, Sri Lanka |
71 |
NA |
|
2016 |
Roanu |
May 17-May 22 |
Cyclonic storm |
Sri Lanka, East coast of India, Bangladesh, Myanmar, Yunnan |
135 |
2.03 billion |
|
BOB 04 |
Nov 2-Nov 6 |
Depression |
Malaysia, Thailand, India (West Bengal), Bangladesh |
80 |
NA |
|
Vardah |
Dec 6-dec 13 |
Very severe cyclonic storm |
Sumatra, Andaman and Nicobar Islands, Thailand, Malaysia, Sri Lanka, India |
47 |
3.37 billion |
2017 |
Marutha |
Apr 15-Apr 17 |
Cyclonic storm |
Myanmar, Andaman and Nicobar Islands, Thailand, Yunnan |
4 |
23,400 |
Mora |
May 28-May 31 |
Severe Cyclonic Storm |
Sri Lanka, Andaman and Nicobar Islands, East India, Northeast India, Bangladesh, Myanmar, Bhutan, Tibet |
135 |
297 million |
|
BOB 03 |
Jun 11-Jun13 |
Deep depression |
Northeast India, Bangladesh |
170 |
223 million |
|
BOB 04 |
Jul 18-Jul 19 |
Depression |
Orissa, Madhya Pradesh, Chhattisgarh |
7 |
34 million |
|
Land 01 |
Jul 26-Jul 27 |
Depression |
West Bengal, Jharkhand, Madhya Pradesh |
152 |
2.18 million |
|
Ockhi |
Nov 29-Dec 6 |
Very severe cyclonic storm |
Sri Lanka, India, Maldives |
318 |
920 million |
|
2018 |
Sagar |
May 16-May 20 |
Cyclonic storm |
Yemen, Horn of Africa |
79 |
30 million |
Mekunu |
May 21-May 27 |
Severe Cyclonic Storm |
Yemen, Oman, Saudi Arabia |
31 |
1.5 billion |
|
Luban |
Oct 6-Oct 15 |
Very severe cyclonic storm |
Yemen, Oman |
14 |
1 billion |
|
Titli |
Oct 8-Oct 12 |
Very severe cyclonic storm |
India (Andhra Pradesh, Odisha, West Bengal, Bangladesh) |
89 |
920 million |
|
Gaja |
Nov 10-Nov 19 |
Very severe cyclonic storm |
Andaman Islands, Tamil Nadu (India), Sri Lanka |
52 |
775 miilion |
|
Phethai |
Dec 13-Dec 17 |
Severe Cyclonic Storm |
India (East and Northeast) |
8 |
100 million |
|
2019 |
Pabuk |
Jan 4-Jan 7 |
Cyclonic storm |
Thailand, Myanmar, Andaman Islands |
8 |
156 million |
Fani |
Apr 26-May 4 |
Extremely severe cyclonic storm |
Sumatra, Nicobar Islands, Sri Lanka, East India, Bangladesh, Bhutan |
89 |
8.1 billion |
|
Vayu |
Jun 10-Jun 17 |
Very severe cyclonic storm |
Northern Maldives, India, Southern Pakistan, East Oman |
8 |
140,000 |
|
Bulbul |
Nov 5-Nov 11 |
Very severe cyclonic storm |
Myanmar, Andaman and Nicobar Islands, Eastern India, Bangladesh |
41 |
3.37 billion |
|
ARB 07 |
Dec 3-Dec 5 |
Deep depression |
Tamil Nadu |
25 |
NA |
|
2020 |
Amphan |
May 16-May 21 |
Super Cyclonic Storm |
India (West Bengal, Odisha), Bangladesh, Sri Lanka, Bhutan |
128 |
13.6 billion |
Nisarga |
Jun 1-Jun 4 |
Very severe cyclonic storm |
Maharashtra, Goa |
6 |
803 million |
|
BOB 02 |
Oct 11-Oct 14 |
Deep depression |
India (Andhra Pradesh, Puducherry, Telangana, Kerala, Karnataka, Goa, Maharashtra) |
98 |
681 million |
|
Gati |
Nov 21-Nov 24 |
Very severe cyclonic storm |
Somalia, Yemen, Djibouti |
9 |
1 million |
|
Nivar |
Nov 23- Nov 27 |
Very severe cyclonic storm |
Sri Lanka, India (Andhra Pradesh, Tamil Nadu, Puducherry) |
14 |
600 million |
|
Burevi |
Nov 30-Dec 5 |
Cyclonic Storm |
Sri Lanka, India (Tamil Nadu, Kerala) |
11 |
NA |
|
2021 |
Taukate |
May 14-May 19 |
Extremely severe cyclonic storm |
India (Delhi, Madhya Pradesh, Maharashtra, Karnataka, Kerala, Goa, Lakshadweep, Maldives, Rajasthan, Uttarakhand, Uttar Pradesh, Sindh, Sri Lanka, and West states) |
174 |
2.1 billion |
Yass |
May 23-May 28 |
Very severe cyclonic storm |
Andaman and Nicobar Islands, Bangladesh, India (East India and Uttar Pradesh), Nepal |
20 |
2.84 billion |
|
Gulab |
Sep 24-Sep 28 |
Cyclonic Storm |
India (Andhra Pradesh, Chhattisgarh, Maharashtra, Odisha, Telangana) |
20 |
269 million |
|
Shaheen |
Sep 30-Oct 4 |
Severe Cyclonic Storm |
Balochistan, Iran, Oman, Saudi Arabia, Sindh, United Arab Emirates, Yemen, India (Gujarat) |
14 |
100 million |
|
BOB 05 |
Nov 10-Nov 12 |
Depression |
India (Andhra Pradesh, Tamil Nadu, Kerala), Sri Lanka |
41 |
NA |
|
2022 |
Asani |
May 7-May 12 |
Severe Cyclonic Storm |
Andaman and Nicobar Islands, India (Andhra Pradesh, Tamil Nadu, Karnataka, Odisha) |
3 |
NA |
The Must-Read
Facts:
1970 Bhola
Cyclone: The fatal cyclone recorded the deaths of 500, 000 people. It occurred in Bangladesh, the Ganga-Brahmaputra Delta region in the year 1970.
1999 Odisha
Cyclone: Most intense and strongest Tropical cyclone occurred in Odisha,
India in the year 1999. The wind speed
was around 260 m/hr with a low barometric pressure of 912 mbar or 26.93 in Hg. The cyclone reported 9887 fatalities in the state and damage to $4.44 billion economies.
Amphan:
The costliest cyclone in terms of loss of economy and damages. The loss was around
$13.6 billion with 128 reported deaths. It occurred in India (West Bengal,
Odisha), Bangladesh, Sri Lanka, and Bhutan in May 2020 and was declared a Super
Cyclonic Storm by IMD.
Ockhi: The
very severe cyclonic storm was the hazardous one causing 318 fatalities in Sri
Lanka, India, and the Maldives in the year 2017. It caused damage worth $920
million.
Fani: The
cyclone was declared an Extremely Severe Cyclonic storm in Apr 2019 causing damage worth $8.1 billion and reporting 89 deaths. The cyclone was the worst hit
in the area of Sumatra, Nicobar Islands, Sri Lanka, East India, Bangladesh, and
Bhutan.