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Impact of Climate Change on Tropical Cyclones Frequency and Intensity on Indian Coasts

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Abstract and Figures

Climate change is projected to exacerbate intensity of tropical cyclonic storms in selected ocean basins with the rise in sea surface temperatures. Almost all of the tropical cyclonic storms are concentrated in the East Asia, North America, and the Central American regions. The North Indian Ocean—the Bay of Bengal and the Arabian Sea, generates only 7% of the world’s cyclones. However, their impact is comparatively high and devastating, especially when they strike the East Indian and Bangladesh coasts bordering the North Bay of Bengal due to high population density clustered around low lying areas along these coastlines. The tropical storms typically do not reach a high intensity in the Arabian Sea due to the unfavorable wind shear; dry air feed from Thar Desert and relatively lower sea surface temperatures. However, the Arabian Sea basin has also produced a few strong tropical cyclones particularly as seen in the recent years. In general, cyclones in North Indian Ocean tend to peak during May, October and November. This paper presents comprehensive analyses of the cyclonic disturbances data of the North Indian Ocean of 140 years (1877–2016) and investigates the likely impacts of climate change on tropical cyclones frequency and intensity on Indian coasts based on historical cyclone data and recent model based findings on plausible changes in Indian Ocean SSTs and circulation systems. © 2019, Springer International Publishing AG, part of Springer Nature.
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1Chapter 32
2Impact of Climate Change on Tropical
3Cyclones Frequency and Intensity
4on Indian Coasts
5Sushil Gupta, Indu Jain, Pushpendra Johari and Murari Lal
6Abstract Climate change is projected to exacerbate intensity of tropical cyclonic
7storms in selected ocean basins with the rise in sea surface temperatures. Almost all
8of the tropical cyclonic storms are concentrated in the East Asia, North America,
9and the Central American regions. The North Indian Ocean—the Bay of Bengal and
10 the Arabian Sea, generates only 7% of the world’s cyclones. However, their impact
11 is comparatively high and devastating, especially when they strike the East Indian
12 and Bangladesh coasts bordering the North Bay of Bengal due to high population
13 density clustered around low lying areas along these coastlines. The tropical storms
14 typically do not reach a high intensity in the Arabian Sea due to the unfavorable
15 wind shear; dry air feed from Thar Desert and relatively lower sea surface tem-
16 peratures. However, the Arabian Sea basin has also produced a few strong tropical
17 cyclones particularly as seen in the recent years. In general, cyclones in North
18 Indian Ocean tend to peak during May, October and November. This paper presents
19 comprehensive analyses of the cyclonic disturbances data of the North Indian
20 Ocean of 140 years (1877–2016) and investigates the likely impacts of climate
21 change on tropical cyclones frequency and intensity on Indian coasts based on
22 historical cyclone data and recent model based findings on plausible changes in
23 Indian Ocean SSTs and circulation systems.
24 Keywords North Indian Ocean Climate models Tropical cyclone
25 Sea surface temperature Cyclonic storm Severe cyclonic storm
26
S. Gupta (&)I. Jain P. Johari M. Lal
RMSI, Noida, India
e-mail: sushil.Gupta@rmsi.com
I. Jain
e-mail: indu.jain@rmsi.com
P. Johari
e-mail: pushpendra.johari@rmsi.com
M. Lal
e-mail: murari.lal@rmsi.com
Layout: T1 Standard Book ID: 447463_1_En Book ISBN: 978-3-319-77275-2
Chapter No.: 32 Date: 10-4-2018 Time: 10:40 am Page: 1/7
©Springer International Publishing AG, part of Springer Nature 2019
P. J. Rao et al. (eds.), Proceedings of International Conference on Remote Sensing
for Disaster Management, Springer Series in Geomechanics and Geoengineering,
https://doi.org/10.1007/978-3-319-77276-9_32
1
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27 1 Introduction
28 Tropical cyclones are among the most damaging natural hazards of the world. The
29 North Indian Ocean (NIO) accounts for about 7% of global Tropical Cyclones
30 (TCs). Out of these 7% of the cyclones, most forms in the Bay of Bengal
31 (BoB) than the Arabian Sea (AS), which is about 4 times higher [1,2]. In NIO,
32 there are two cyclone seasons: pre-monsoon (March to May, MAM) and
33 post-monsoon (October to December, OND). Some of the cyclonic disturbances
34 also form in transitional monsoon season (June to September, JJAS). However,
35 during the peak summer monsoon season, the depressions and deep depressions in
36 BoB generally do not intensify to cyclonic storm category due to moderate vertical
37 wind shear. On an average about 5–6 TCs form in the BoB and the AS every year,
38 of which 2–3 reach severe stage. Most of the severe cyclones of the BoB form
39 during the post-monsoon season in the months of October and November. A few
40 severe cyclones form during May also but the post-monsoon cyclones are severest
41 due to which this season is also known as storm season in south Asia [3].
42 Tropical disturbances have resulted in colossal socio-economic losses to life and
43 property, especially along the east coast of India, Bangladesh and Myanmar every
44 year due to cyclones in the BoB. Due to the high population density and rapid
45 increase in infrastructure projects in the coastal regions of India, the economic
46 losses are increasing leaps and bound. However, loss of life has reduced in recent
47 years to a greater extent due to the advancement in science and technology of
48 cyclone warning facilities and evacuation of a large number of human populations
49 and animals prior to its landfall. The recent October 2013 Cyclone Phailin and the
50 October 2014 Cyclone Hudhud are the two examples on the east coast of India that
51 made landfall near Gopalpur on October 11 at about 2130 IST and at
52 Visakhapatnam on October 12 at about 1330 IST, respectively. For both of these
53 cyclones, the loss of lives have been reduced considerably, thanks to leanings from
54 1999 Odisha Super Cyclone in which more than 10,000 people perished; however,
55 economic losses of buildings and infrastructure have increased enormously. For
56 example, industrial losses in 2014 Cyclone Hudhud at Visakhapatnam city alone
57 surpassed over INR 4000 Crores, while total losses from this cyclone were esti-
58 mated over INR 36,000 Crores. Therefore, any change in the TCs frequency and
59 intensity in the BoB and AS would have far reaching socio-economic consequences
60 for India and neighbouring countries.
61 There have been a few studies on the long-term trends and TCs frequency and
62 intensity over the BoB [3–11]. The TCs data was analysed for a period of 122 years
63 during 1877–1998 [8,9], and for a period of 129 years during 1877–2005 [3]
64 (Table 1).
65 Most of these studies have emphasized a marginal decrease in the annual fre-
66 quency of cyclones; however, there is an increasing trend in the frequency of
67 Severe Cyclonic Storms (SCS) over NIO. Trend analysis reveal that the SCS fre-
68 quency over the BoB has registered significant increasing trends in past 129 years
69 during the intense cyclonic months, though this does not necessarily imply that SCS
2 S. Gupta et al.
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70 frequency has increased continuously decade after decade [3]. In fact there has been
71 a slight decrease in SCS frequency after peaking during 1966–1970, although this
72 does not alter the long term trend much. Moreover, the intensification rate (denoted
73 hereafter by SCS/CS) during November, which accounts for highest number of
74 intense cyclones in the NIO, has registered a steep rise of 26% per hundred years,
75 implying that a tropical depression forming in the BoB during November has a high
76 probability to reach to severe cyclone stage [3].
77 This paper presents comprehensive analyses of the long-term cyclonic distur-
78 bance data of the NIO of the past 140 years (1877–2016) and investigates the likely
79 impacts of climate change on TCs frequency and intensity on Indian coasts (BoB,
80 AS) based on historical cyclonic disturbances and recent model based findings on
81 plausible changes in Indian Ocean SSTs and circulation systems.
82 2 Decadal Frequency Analysis of Tropical Disturbances
83 The long-term decadal frequency analysis of tropical disturbances in the BoB and
84 AS for a duration of 140 years (1877–2016) has been presented in Figs. 1and 2,
85 respectively. The sources of tropical storms data are India Meteorological
86 Department publication (IMD) and International Best-Track Archive for Climate
87 Stewardship (IBTrACS).
88 It can be seen from Fig. 1, that there is a general decreasing trend in the decadal
89 frequency of cyclonic disturbances in monsoon, pre-monsoon, and post-monsoon
90 seasons from 1970s onwards in BoB. Similar observations can also be made in the
91 decadal frequency of cyclonic disturbances in monsoon, pre-monsoon, and
92 post-monsoon seasons from Fig. 2, over AS. Both these analyses also corroborate
93 the earlier studies (for example [3,12,13]).
94 3 Intensity Analysis of CS and SCS
95 As mentioned earlier, we have analysed 140 years of tropical cyclonic disturbances
96 data during 1877–2016. While, Singh [3] and other authors analysed this data as
97 total numbers of CS or SCS numbers (Table 1), we not only analysed it as CS or
Table 1 Frequency of TCs
in the BoB during 1877–2005 Type of tropical
disturbance
Month
May Jun. Sept. Oct. Nov.
Cyclonic storm (CS) 59 35 92 41 116
Severe cyclonic storm
(SCS)
44 5 40 16 65
SCS/CS 0.75 0.14 0.43 0.39 0.56
Modified after Singh [3]
32 Impact of Climate Change on Tropical Cyclones …3
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0
10
20
30
40
50
60
70
Monsoon-TS
Postmonsoon-TS
Premonsoon-TS
Fig. 1 Decadal frequency analysis of tropical disturbances (1877–2016) over BoB
0
1
2
3
4
5
6
7
8
9
Monsoon-TS
Postmonsoon-TS
Premonsoon-TS
Fig. 2 Decadal frequency analysis of tropical storms (1877–2016) over Arabian Sea
4 S. Gupta et al.
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98 SCS but also divided in two segments, i.e., pre- and post-1970, and 1980 and rate of
99 intensification (SCS/CS), so that we could analyse the impact of climate change on
100 TCs intensity for both BoB and AS (Tables 2,3,4and 5).
101 Table 2clearly shows that rate of intensification of tropical storm in the BoB has
102 increased significantly in the months of May, Oct and Nov post 1980s. In general,
103 similar, observations could also be made for AS (Table 3), however, in the month
104 of October, it has not changed.
105 If we take it pre- and post-1970s, then the rate of intensification is much more
106 evident in the months of May, Oct and Nov in the BoB than pre- and post-1980s
107 (Table 4). Similarly, for AS, rate of intensification is now much more evident in
Table 2 Pre- and post-1980, intensity analysis of CS and SCS over Bay of Bengal
Type of tropical
cyclone
Pre-1980 Post-1980
May Jun. Sept. Oct. Nov. May Jun. Sept. Oct. Nov.
CS 7 2629 3411 0 1 1 6 4
SCS 14 2 14 18 30 5 0 0 12 15
SCS/CS 2.00 0.08 0.48 0.53 2.73 INF –– 2.00 3.75
Table 3 Pre- and post-1980, intensity analysis of CS and SCS over Arabian Sea
Type of tropical
cyclone
Pre-1980 Post-1980
May Jun. Sept. Oct. Nov. May Jun. Sept. Oct. Nov.
CS 2 3 2 7 4 0 1 0 1 1
SCS 3 2 2 7 16 2 2 0 1 3
SCS/CS 1.50 0.67 1.00 1.00 4.00 INF 2 –1.00 3.00
Table 4 Pre- and post-1970, intensity analysis of CS and SCS over Bay of Bengal
Type of tropical
cyclone
Pre-1970 Post-1970
May Jun. Sept. Oct. Nov. May Jun. Sept. Oct. Nov.
CS 6 25 27 30 10 1 2 3 10 5
SCS 13 2 11 17 22 6 0 3 13 23
SCS/CS 2.17 0.08 0.41 0.57 2.20 6.00 –1.00 1.30 4.60
Table 5 Pre- and post-1980, intensity analysis of CS and SCS over Arabian Sea
Type of tropical
cyclone
Pre-1970 Post-1970
May Jun. Sept. Oct. Nov. May Jun. Sept. Oct. Nov.
CS 1 3 2 6 4 1 1 0 2 1
SCS 3 2 1 6 12 2 2 1 2 7
SCS/CS 3.00 0.67 0.50 1.00 3.00 2.00 2.00 INF 1.00 7.00
32 Impact of Climate Change on Tropical Cyclones …5
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108 pre- and post-1970s than pre- and post-1980s for the month of May, Oct and Nov
109 (Table 4) and this change could be attributed to the recent warming as a conse-
110 quence of impacts of ongoing climate change.
111 4 The Influence of Climate Change on Tropical Cyclones
112 In a study [14], the behavior of Indian summer monsoon in a high resolution
113 climate model and reported that under double CO
2
conditions, fewer cyclonic
114 depressions formed in the month of June. The historical cyclonic disturbances data
115 studied in this paper also corroborate this finding.
116 Another study published in Nature Geosciences [15] reported that future pro-
117 jections based on theory and high-resolution dynamical models consistently indi-
118 cate that greenhouse warming will cause the globally averaged intensity of TCs to
119 shift towards stronger storms, with intensity increases of 2–11% by 2100. Existing
120 modeling studies also consistently project decreases in the globally averaged fre-
121 quency of TCs, by 6–34%. Balanced against this, higher resolution modeling
122 studies typically project substantial increases in the frequency of the most intense
123 cyclones, and increases of the order of 20% in the precipitation rate within 100 km
124 of the storm centre.
125 Recent global climate models continue to project future decreases in global TC
126 numbers. However, increases in the intensities of the strongest storms and increased
127 rainfall rates are projected. Some studies suggest that, by the end of the century, the
128 number of category 4 and 5 cyclones is expected to double, with heavier rainfall
129 [16]. Globally, the consensus projection is for decreases in TC numbers by about 5–
130 30%, increases in the frequency of categories 4 and 5 storms by 0–25%, an increase
131 of 0–5% in typical lifetime maximum intensity, and increases in TC rainfall rate by
132 5–20% [16]. Recent high-resolution modeling studies suggest that the frequency of
133 the most intense storms, which are associated with particularly extensive physical
134 effects, will more likely than not increase substantially in some basins under pro-
135 jected 21st century warming and there is medium confidence that TC rainfall rates
136 will increase in every affected region [16]. We obtain similar results for both BoB
137 and AS basins from our analysis of the downscaled high resolution global model
138 data sets produced under CMIP5 experiments. Detailed data analysis is still in
139 progress to strengthen our findings which would be published elsewhere.
140 5 Conclusions
141 Our analysis of long-term 140 years of cyclonic disturbances demonstrates that
142 there is a general decreasing trend in the decadal frequency of cyclonic disturbances
143 in monsoon, pre-monsoon, and post-monsoon seasons from 1970s onwards in both
144 BoB and Arabian Sea. Moreover, there is a general increasing trend in the Intensity
6 S. Gupta et al.
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145 of TCs pre- and post-1970s and 1980s in the months of May, Oct and Nov. This
146 change could be attributed to the recent rising trends of BoB and AS as a conse-
147 quence of impacts of ongoing climate change. The high resolution climate model
148 analysis also suggests that the frequency of the most intense storms in Bay of
149 Bengal and Arabian Sea will likely to increase under projected warming during the
150 21st century while the total number of cyclonic disturbances should decrease. The
151 analysis also suggests an increase of 10–15% in the rainfall associated with these
152 disturbances within the area under influence of the storm winds.
153 References
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The coastal region of India stands out as one of the most climate-vulnerable areas globally. This vulnerability arises from the frequent occurrence of high-intensity cyclones, floods, and a rapid increase in salinity intrusion. The region’s primary livelihood largely relies on agriculture and related sectors, with a predominant presence of smallholder farming communities. Climate change and its associated consequences have emerged as a grave concern for the agricultural sector in coastal India. Despite efforts by farmers to adopt various strategies as a means of adapting to climate change, there exists a notable gap in scientific literatures in comprehensively identifying and exploring these strategies. Therefore, this study has intended to identify and explore the rationale and utility of these adaptation strategies from existing literatures by systematically reviewing them. The study integrates multiple research designs and adheres to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework. Initial data retrieval was conducted through two prominent databases, namely Scopus and Web of Science. Following PRISMA protocol, a total of 27 articles were finally considered for the analysis of the study. The study was categorised into five major themes i.e., (1) Sustainable agricultural practices, (2) Soil and water management practices, (3) Improved livestock management practices, (4) Improved fisheries management practices, (5) Technological interventions. This study highlights that adaptation strategies belonged to both the category of farmers-led and advocated and majority of them were spontaneously implemented by the farmers. Indigenous knowledge played a crucial role in shaping these adaptive responses. Adaptation strategies were found to be interconnected, much like the interrelationships between the impacts of climate stressors, especially for smallholder farmers in coastal India who rely on diverse livelihood sectors. This underscores the need for stakeholders to design strategies that consider these cross-sectoral linkages. Consequently, this study provides invaluable insights into the evolution and prospective trajectory of climate adaptation strategies within the agricultural landscape of coastal India.
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The association between infrastructure damage in the aftermath of Cyclone Idai and malaria risk in Sofala Province, Mozambique: an ecological study
Article
Full-text available
  • Nov 2024
  • MALARIA J
Background In April 2019, Mozambique was hit by Cyclone Idai leaving substantial damage to infrastructure and nearly two million people in need of humanitarian assistance. Malaria risk has been associated with living in a rural setting, vicinity to water, and household structure, all factors which are impacted by severe storms. This study quantified the association between damage to infrastructure (health care facilities and schools) following Cyclone Idai and malaria outcomes: malaria incidence, severe malaria, and administration of intermittent preventative treatment in pregnancy (IPTp) in Sofala Province, Mozambique. Methods To quantify infrastructure damage, historical satellite imagery was assessed visually using Google Earth Pro®. Damage to 66 school and 105 health centres was assessed for severity and duration. Location data was imported to QGIS and joined with district level data on malaria outcomes and environmental covariates. Multivariable Poisson regression models were used to quantify the associations between facility damage and malaria incidence and severe malaria. Generalized linear models were used to determine the association between facility damage and changes in malaria incidence and administration of IPTp from 2018 to 2019. Results An increase in facility damage was associated with an increase in malaria incidence and severe malaria. An increase in proportion of facilities damaged by 10% was associated with a 7.3% (95% CI 6.8–7.8%) increase in malaria incidence. Risk of severe malaria was 2.16 (95% CI 1.42–3.32) times higher in districts with any damage compared to those with no damage. However, proportional facility damage was associated with decreased malaria incidence and increased access to IPTp from 2018 to 2019, but these were not statistically significant. Conclusion An increase in proportion of facilities damaged following Cyclone Idai was associated with increased risk of malaria and severe malaria at the district level. This may be a function of decreased access to healthcare and an increased exposure to risk factors for malaria. A non-statistically significant decrease in malaria incidence was also found at the district level from 2018 to 2019, indicating that malaria may have been underreported in 2019, likely again a function of decreased access to healthcare.
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Perceptions of El Niño-Southern Oscillation (ENSO) and La Niña Shape Fishers' Adaptive Capacity and Resilience
Article
Full-text available
  • Jul 2024
Much research has raised concerns about how a warming planet will interact with natural cyclical climatic variations, and the implications for the resilience and vulnerability of coastal communities. As the anticipated effects of climate change will continue to intensify, it is necessary to understand the response and adaptive capacity of individuals and communities. Coastal communities in Ecuador have evolved in an environment of such cyclical climatic variations referred to as El Niño-Southern Oscillation (ENSO) and La Niña. These climatic events are frequently characterized by extreme variations in precipitation, violent storms, and coastal flooding during El Niño and lowered sea water temperatures and drought during La Niña. This paper draws on survey data and long-term ethnographic research in Ecuadorian coastal communities to explore how fishers understand the impacts of ENSO and implications for their livelihood decisions and resilience to climate variability. The results suggest that fishers along the coast of Ecuador understand and respond differentially to the impacts of ENSO depending on social, cultural, environmental, and geographical factors. These differential levels of response suggest that livelihood diversification may uphold social resilience, which has implications for how coastal communities may adapt to the increasingly harsh weather conditions predicted by many climate models. Our findings further suggest that the impacts of El Niño are more salient than the impacts of La Niña; these findings have significant implications for fisheries management and science communication.
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Impacts of Extreme Climatic Events on Sustainable Urban Development in Coastal Regions: Selected Case Studies of India
Chapter
  • Feb 2024
Unequivocally, it is now evident that the earth’s climate has been changing with significant impacts on various counts and magnitudes. This is more prominent during the recent decades of the Anthropocene Epoch when extreme climatic events are occurring quite frequently, often leaving their irreparable imprints on contemporary human civilization. Given the trends of global warming under business as usual, it is expected that the higher reprehensive concentration pathways (RCPs) will be the reality to impoverish the vulnerable ecosystems, including human habitats. The change in thresholds of human adaptations in different geographic regions will necessitate more investments to recover from climatic hazards and disasters. As the countries, especially of the global south, is going to accumulate more people in the urban locations, extreme climatic events in the form of air pollution, urban heat island (UHI), urban drought, water scarcity, thunderstorm, cyclones, high-intensity rainfall, urban flooding and water logging, etc. are anticipated to jeopardize the urban environments with the consequence of increasing physical and social distresses to the inhabitants. In India, the rate of urbanization is still low, but the human population concentrated in urban centres is significantly high. Consequently, inadequate infrastructural facilities and amenities available to a greater section living on the edges, and threat to life and property to a sizeable number of population of the country are inevitable. As per records, urban areas situated in the coastal regions of the country, under the humid tropical environment, are becoming more vulnerable to extreme climatic events. Although improvement in weather forecasting systems has enabled the administration to reduce loss of life, the recurring hazards as stated earlier are incapacitating the day-to-day functions of the urban ecosystems in which the poorer section of the society is the principal victim. In this study, the prominent urban centres of both the east and west coasts of India have been selected, where a moderate climate is expected all year round due to the land-water interface; however, in recent times, these areas are experiencing extreme climatic events or hazards. Moreover, as these locations accommodate large concentrations of population, an assessment of their climatic hazard potentials needs to be studied for sustainable urban development that is both resilient and inclusive. The exercise will attempt to explore how climate change is responsible for enhanced extreme climatic events, leading to the adversities in the urban ecosystems of the coastal locations, and what mitigation, as well as adaptation strategies, may be recommended as appropriate to overcome the situation under various time windows. The analyses will be mostly done based on the review of published works of literature and recorded data, besides extensive use of satellite-based remotely sensed weather information available from various authentic sources.
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Nonstationary analysis of water and sediment in the Jinsha River Basin based on GAMLSS model
Article
Full-text available
  • Aug 2023
  • STOCH ENV RES RISK A
Nonstationary calculation of sediment load is an important basis for reservoir operation and management. The Jinsha River Basin (JRB) is the most important sediment-producing section of the Yangtze River, and the main source of sediment into the Three Gorges Reservoir (TGR). In this study, three sediment transport nonstationary analysis models were constructed through the Generalized Additive Models for Location, Scale and Shape (GAMLSS) model, namely Mode0, Mode1 and Mode2. The study found that the correlation coefficients between sediment load with runoff and rainfall are 0.78 and 0.73, respectively. Runoff and precipitation can be used as covariates for the nonstationary analysis of sediment transport. The optimal edge distribution of Mode0, Mode1, and Mode2 is Gumbel, Weibull, and Logistic, respectively. Mode2 can accurately describe the nonstationary change of sediment load, and Mode1 can basically reflect the nonstationary change of sediment load. While Mode0 is a consistent model, which cannot reflect the nonstationary change of sediment load over time. Mode2 has a good ability to simulate the quantile changes of sediment load during the training period and the test period, while Mode1 has a weak generalization ability. Mode0 cannot reflect inconsistent changes, and the simulation result is a fixed value. This study provides an important reference for the nonstationary analysis of sediment load under inconsistency conditions in the JRB.
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Increase in annual frequency of the severe cyclonic storms of the Bay after 1964- Possible causes
Article
Full-text available
  • Jan 1981
  • MAUSAM
The series of annual frequency of severe cyclonic storms which struck the coast around the Bay of Bengal during the period 1877-1977 has been examined to find out if any significant change has occurred in the mean frequency, It is observed that while the series for the period is homogeneous, a highly significant increase in the mean annual frequency has occurred after 1964. The larger annual mean frequency may be due to better facilities of detection of severe storms and/ or meteorological conditions over the Bay being more frequently favourable for intensification of storms into severe storms, An estimate of the mean annual frequency is made for the next 50-year period and the frequency distribution on the basis of this mean is given for the period, utilising the Poisson probability model which has shown good fit to past data.
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Major advances in understanding and prediction of tropical cyclones over north Indian Ocean : A Perspective
Article
Full-text available
  • Nov 2021
  • MAUSAM
lkj & mRrjh fgUn egklkxj esa m".kdfVca/kh pØokrksa ij fd, x, vuqla/kku xr 150 o"kksZa esa fofHkUu pj.kksa ls xqtjs gSa vkSj vf/kd rFkk csgrj izs{k.kksa dks fodflr djus ds fy, izkS|ksfxdh ds :Ik es bldk fodkl fd;k x;k gSA 20oha 'krkCnh ds e/; rd leqnz esa bl vkinkdkjh ifj?kVuk ds cuus vkSj blds rhoz gksus dh tkudkjh iksrksa esa gh dqN gn rd fojyrk ls izkIr gksus okys izs{k.kksa ds ek/;e ls feyrh Fkh vkSj blfy, 1960 ds n’kd rd Hkkjr esa fd, x, vf/kdka’k vuqla/kku v/;;uksa esa pØokrksa ds tyok;q foKku] mudh /kjkryh; lajpuk] mudh xfr vkSj leqnz esa tgktksa dks ig¡qpkusa okyh {kfr dks vuns[kk djus okys fu;eksa ij vf/kd cy fn;k x;k FkkA ekSle jsMkj] mifjru ok;q ifjKkiuksa] vuqla/kku ok;q;ku losZ{k.k ekSle mixzgksa vkSj daI;wVjksa ds ek/;e ls izkIr dh xbZ ubZ ok;qeaMyh; izks|ksfxdh ds izLrqrhdj.k ls 1950 ds n’kd ls ysdj 1980 ds n’kd ds nkSjku fofHkUu ns’kksa ds m".kdfVca/kh pØokr vuqla/kku esa vk’p;Ztud :Ik ls ifjorZu vk;k gSA bl vof/k esa m".kdfVca/kh pØokrksa ds laiw.kZ mRifRr pØ dk izfr:i.k djus ds fy, lS)kafrd v/;;uksa vkSj daI;wVj fun’kksaZ ds fodkl esa lq/kkj ns[kk x;k gSA bl vof/k esa m".kdfVca/kh pØokr ds ekxZ dk iwokZuqeku yxkuk Hkh vuqla/kku dk ,d {ks= cu x;k gS vkSj 1950 ds n’kd ls ysdj 1980 ds n’kd ds nkSjku tyok;q foKku] flukfIVd lkaf[;dh; vkSj xfrdh; i)fr;ksa ij vk/kkfjr rduhdksa ds izdkjksa esa fujarj fodkl gqvk gS rFkk bUgsa ekU;rk feyh gSA xr 10 o"kksZa dh vof/k ds nkSjku fodflr ns’kksa esa HkweaMyh; ifjpkyu fun’kksZa esa fufgr ifj"Ñr mPp foHksnu ds fun’kksZa dk fodkl fd;k x;k gS vkSj ikjLifjd fØ;kvksa dh izfØ;k ds :Ik esa bl Ik)fr dk fodkl djus vkSj bldh xfr dk iwokZuqeku yxkus ds fy, budh tk¡p dh xbZ gSA ;s iw.kZ :i ls lgh ikbZ xbZ gSaA Hkkjr esa Hkh bl izdkj ds fodklksa dks viuk;k x;k gSA bl 'kks/k&i= esa m".kdfVca/kh pØokr ds fodkl vkSj bldh xfr esa lfUufgr izR;{k izfØ;kvksa ds laca/k esa fd, x, izeq[k fodklksa dh lwph miyC/k djkus dk iz;kl fd;k x;k gSA lkekU; :Ik ls HkweaMyh; vuqla/kku ds {ks= esa fd, x, iz;kl fgan egklkxj csflu esa fd, tk jgs v/;;uksa ij dsafnzr jgs gSaA mRrjh fgan egklkxj esa m".kdfVca/kh pØokrksa ds vUr% nl o"khZ; fHkUurkvksa dh tk¡p dh xbZ gS vkSj 1980 ds n’kd ls budh xfr;ksa esa vDlj vR;kf/kd deh ns[kh xbZ gSA fgan egklkxj csflu esa m".k@'khr bulksa dh ?kVukvksa ds e/; dksbZ laca/k ugha ik;k x;k gSA izpaM m".kdfVca/kh pØokrksa ds fodkl vkSj xfr ds fy, vko’;d o`gr eku fLFkfr;ksa dh izÑfr ls lacaf/kr izs{k.kkRed vkSj lS}kafrd ekWMfyax i)fr;ksa esa daI;wVj izfr:i.kksa lfgr izs{k.kkRed vkSj lS)kafrd i)fr;ksa ls fHkUu fHkUu fopkjksa dk irk pyk gSA mRrjh fgan egklkxj csflu esa fd, x, vkSj vf/kd vuqla/kku dh vksj fo’ks"k /;ku nsus dh fn’kk esa dqN lq>ko fn, x, gSaA Research on tropical cyclones in the north Indian Ocean has passed through different phases in the last 150 years and progress was made as the technology for more and better observations evolved. Till the middle of the 20th century, the only way of knowing about the formation and intensification of this disastrous phenomenon, while out at sea, was through rather sparse ship observations and hence the climatology of the cyclones, their surface structure, movement and the rules to avoid the damage to shipping at sea were emphasized in most of the research studies in India till 1960s. Introduction of new atmospheric technologies through weather radars, upper air soundings, weather satellites and computers have brought a phenomenal change in tropical cyclone research in different countries during 1950s to 1980s. The period also witnessed break-through in theoretical studies and the development of computer models to simulate the complete genesis cycle of tropical cyclones. Predicting the track of tropical cyclone also became an area of active research in this period and a variety of techniques were increasingly developed. During the last 10 years sophisticated high resolution models embedded within global circulation models have been developed in advanced countries and tested for predicting the development and movement of the system as an interactive process. In India, too such developments have been adopted. Within the scope of global research effort in general, the focus of the article is on the studies in north Indian Ocean basin. Inter-decadal variation of tropical cyclones in the north Indian Ocean has been examined and the frequency of their formations have shown drastic decrease since 1980s. No connection is found between the warm/cold ENSO events in the Indian Ocean basin and tropical cyclone frequency in the basin. Observational and theoretical approaches with computer simulations have brought a convergence of views concerning the nature of large-scale conditions needed for development and movement of severe tropical cyclones. Some suggestions are provided for directing special attention toward further research in this area in the north Indian Ocean basin.
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Trends in frequency of cyclonic disturbances and their intensification over Indian seas
Article
Full-text available
  • Apr 2000
  • MAUSAM
Trends in cyclonic disturbances for the period 1891-1997 were studied over Bay of Bengal and Arabian Sea. It is noticed that there is a significant decreasing trend at 99% level of confidence in the frequency of storms. The slopes of decreasing trend in cyclonic activity over Bay of Bengal and that over Arabian Sea were found to be maximum during last four decades. Weakening of Hadley circulation due to upper tropospheric warming may be one of the cause of this decreasing trend. There appears to be decrease in intensification of cyclonic disturbances in recent period.
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Long-term trends in the frequency of severe cyclones of Bay of Bengal : Observations and simulations
Article
Full-text available
  • Jan 2007
  • MAUSAM
The east coast of India and the coasts of Bangladesh, Myanmar and Sri Lanka are vulnerable to the incidence of tropical cyclones of the Bay of Bengal. Every year these cyclones inflict heavy loss of life and property in this region. Global climate change resulting from anthropogenic activity is likely to manifest itself in the weather and climate of the Bay of Bengal region also. The long-term trends in the frequency and intensity of tropical cyclones of the Bay of Bengal during intense cyclonic months May, October and November is one such problem which has been addressed in the present paper. Utilizing the existing data of 129 years (1877-2005) pertaining to the tropical cyclone frequency and intensity in the Bay of Bengal during May, October and November, a study was undertaken to investigate the trends in the frequency of Severe Cyclonic Storms (SCS) during past decades. The results of the trend analysis reveal that the SCS frequency over the Bay of Bengal has registered significant increasing trends in past 129 years during the intense cyclonic months. It may be emphasized that these trends are long-term trends for more than hundred years based on statistical analyses which do not necessarily imply that SCS frequency has increased continuously decade after decade. As a matter of fact there has been a slight decrease in SCS frequency after peaking in the pentad 1966-1970, but this does not alter the long-term trend much. The intensification rate during November, which accounts for highest number of intense cyclones in the north Indian Ocean, has registered a steep rise of 26% per hundred years, implying that a tropical depression forming in the Bay of Bengal during November has a high probability to reach to severe cyclone stage. A regional climate model simulation revealed the enhanced cyclogenesis in the Bay of Bengal during May, October and November as a result of increased anthropogenic emissions in the atmosphere.
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A study of decreasing storm frequency over Bay of Bengal
Article
Full-text available
Examination of Sea surface Temperature and frequency of storm over Bay of Bengal during monsoon season using long period data from 1901-1998 has revealed that the storm frequency has decreased on decadal scale since 1980s in-spite of increasing SSTs. Mean of storm frequency for epoch1 (1958-1980) is found to be significantly different than that for epoch2 (1981-1998). This prompted us to see if such a decrease in storm frequency is reflected in atmospheric circulation changes over Bay of Bengal on decadal scale. Hence decadal variation of anomalies of Sea Surface Temperature (SST), relative vorticity at 850hPa, horizontal and vertical shear of zonal wind averaged over Bay of Bengal during monsoon season, have been studied using monthly mean NCEP/NCAR reanalysis data for the period 1958-1998. The anomalies of these parameters are of opposite sign for periods prior to and after 1980. Results suggest that the changes in all the atmospheric parameters from epoch1 to epoch2 are related to decreasing storm frequency in-spite of favorable SSTs.
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Synoptic scale disturbances of Indian summer monsoon as simulated in a high resolution climate model
Article
Full-text available
  • Dec 1995
The Hamburg atmospheric general circulation model ECHAM3 at T106 resolution (1.125 degrees lat./lon.) has considerable skill in reproducing the observed seasonal reversal of mean sea level pressure, the location of the summer heat low as well as the position of the monsoon trough over the Indian subcontinent. The present-day climate and its seasonal cycle are realistically simulated by the model over this region. The model simulates the structure, intensity, frequency, movement and lifetime of monsoon depressions remarkably well. The number of monsoon depressions/storms simulated by the model in a year ranged from 5 to 12 with an average frequency of 8.4 yr(-1), not significantly different from the observed climatology. The model also simulates the interannual variability in the formation of depressions over the north Bay of Bengal during the summer monsoon season. In the warmer atmosphere under doubled CO2 conditions, the number of monsoon depressions/cyclonic storms forming in Indian seas in a year ranged from 5 to 11 with an average frequency of 7.6 yr(-1), not significantly different from those inferred in the control run of the model. However, under doubled CO2 conditions, fewer depressions formed in the month of June. Neither the lowest central pressure nor the maximum windspeed changes appreciably in monsoon depressions identified under simulated enhanced greenhouse conditions. The analysis suggests there will be no significant changes in the number and intensity of monsoon depressions in a warmer atmosphere.
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Has the frequency of intense tropical cyclones increased in the north Indian Ocean?
Article
  • Feb 2001
  • CURR SCI INDIA
An effort has been made to settle the question whether the intense cyclones have become more frequent over the north Indian Ocean, posing a more serious threat to the vulnerable coastal population of the region. The results of the study, which has considered the entire existing data of 122 years of tropical cyclone frequency over the north Indian Ocean from 1877 to 1998, have shown that there is indeed a trend in the enhanced cyclogenesis during November and May. These months account for the maximum number of severe cyclones over the north Indian Ocean, The increasing trend in the cyclone frequency during these months has been primarily due to the significant positive trends over the Bay of Bengal, where the majority of north Indian Ocean cyclones develop. Thus the coastal regions of Bangladesh, India and Myanmar have indeed become more prone to the incidence of severe cyclones during November and May. There has been a two-fold increase in the tropical cyclone frequency over the Bay of Bengal during November in the past 122 years. There has been a 17% increase in the intensification rate of cyclonic disturbances to the cyclone stage, and a 25% increase to severe cyclone stage over the north Indian Ocean during November, which accounts for highest monthly average of severe cyclone frequency, All these linear trends are statistically significant at 99% level. The increasing trend in the cyclone frequency during May is also highly significant but the intensification rates to cyclone and severe cyclone stages have registered only slight increasing tendencies. The cyclonic frequencies during transitional monsoon months, June and September, have diminished considerably. The detailed results have been presented for November and May only.
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Severe Cyclonic Storms in the Bay of Bengal, 1877 1977
Article
  • Oct 1980
An examination of the severe cyclonic storms which formed over the Bay of Bengal and those which struck the coast during the period 1877-1977 brings out a higher mean annual frequency, and a higher percentage of storms intensifying into severe storms, during the period 19659-77.-from Author
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Changes in the frequency of tropical cyclones over the North Indian Ocean
Article
  • Nov 2000
Changes in the frequency of tropical cyclones developing over the Arabian Sea and the Bay of Bengal have been studied utilizing 122 year (1877–1998) data of tropical cyclone frequency. There have been significant increasing trends in the cyclone frequency over the Bay of Bengal during November and May which are main cyclone months. During transitional monsoon months; June and September however, the frequency has decreased. The results have been presented for five months, i.e., May-November which are relevant as far as tropical cyclone frequency over the Arabian Sea and the Bay of Bengal are concerned. The tropical cyclone frequency in the Arabian Sea has not shown any significant trend, probably due to small normal frequency. The frequency time series has been subjected to the spectral analysis to obtain the significant periods. The cyclone frequency over the Bay of Bengal during May has shown a 29 year cycle. A significant 44 year cycle has been found during November. Over the Arabian Sea significant cycles of 13 and 10 years have been observed during May-June and November, respectively. The tropical cyclone frequency in the North Indian Ocean has a prominent El Niño-Southern Oscillation (ENSO) scale cycle (2–5 years) during all above five months. The annual cyclone frequency exhibits 29 year and ENSO scale (2–4 years) oscillations. There is a reduction in tropical cyclone activity over the Bay of Bengal in severe cyclone months May and November during warm phases of ENSO. Examination of the frequencies of severe cyclones with maximum sustained winds ≥ 48 knots has revealed that these cyclones have become more frequent in the North Indian Ocean during intense cyclone period of the year. The rate of intensification of tropical disturbances to severe cyclone stage has registered an upward trend.
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Vulnerability of Bangladesh to Climate Change and Sea Level Rise Through Tropical Cyclones and Storm Surges
Article
  • Nov 1996
Bangladesh is frequently visited by natural disasters such as tropical cyclones, storm surges, floods, droughts, tornadoes, and norwesters. Of these, tropical cyclones originating in the Bay of Bengal and associated storm surges are the most disastrous. There are various reasons for the disastrous effects of cyclones and storm surges in Bangladesh. Superimposed on these disastrous effects, climate change and any consequent sea level rise are likely to add fuel to the fire. Arise in temperature is likely to change cyclone activity: cyclone intensity, if not cyclone frequency, may increase. As a result, storm surges may also increase substantially. Sea level rise, an increase in cyclone intensity, and consequent increases in storm surge heights will have disastrous effects on a deltaic country like Bangladesh, which is not much above the mean sea level. This paper examines the climatology of cyclones in the Bay of Bengal for the last 110 years and trends in cyclone frequency and intensity. The phenomenon of storm surges in the Bay of Bengal is examined along with the primary reasons for the severity of storm surges in Bangladesh. The paper discusses both qualitatively and quantitatively the impacts of rises in temperature on tropical cyclone intensity in Bangladesh. With the use of a mathematical model developed for the simulation of storm surges along the Bangladesh coast; various scenarios of storm surges are developed. Using lower and upper bounds of sea surface temperature rise of 2 and 4C and of sea level rise of 0.3 and 1.0 m (according to the Intergovernmental Panel on Climate Change standard), the model simulates the maximum possible surges that are likely to occur under these conditions.
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