Arabian Sea Tropical Cyclones, 1881-2014: A spatio-temporal - - PowerPoint PPT Presentation

Arabian Sea Tropical Cyclones, 1881-2014: A spatio-temporal analysis in support of natural hazard risk appraisal in Oman Suad Al-Manji

Introduction

• Tropical cyclones and storms coming from the

Arabian Sea are common in Oman (Evan and Camargo, 2011a; Byju and Kumar, 2011).

• In the Arabian Sea region, the majority of tropical

cyclones form near the Laccadive Islands (~11° N, 73° E) in two seasons: the pre-monsoon and the post- monsoon (Galvin 2008a).

Introduction

• Guno (2007), Cyclone Guno, the first super cyclone

(category 5) recorded in the Arabian Sea in a century (Evan and Camargo, 2011a).

• The most intense recent events to impact Oman were

in the 2015 North Indian Ocean season (Ashobaa and the extreme cyclonic storms Chapala and Megh), 2018 (Sagar and Mekunu).

Introduction

• The study presents a spatiotemporal analysis of cyclones

tracks in the Arabian Sea region, drawing on observations from 1880 – 2014.

• The analysis aims to identify high-frequency seasons, the

cyclone direction in each season, and the linear direction trend.

• The results are intended for use in identifying the more

exposed areas around the Arabian Sea and particularly in Oman, and to support disaster risk appraisal and management.

Data and Methods

• A spatial (GIS) database of tropical cyclones was created

based on tracks obtained from the Indian Metrological Department Atlas for the period 1881-1999 (IMD, 1979; IMD 1999 ) and the IMD e-Atlas for storm and depression tracks

• ver the North Indian Ocean for 1891-2014 (IMD, 2014).
• The tracks show tropical system intensity (category) with data
• rganised based on the temporal (seasonal and monthly)

distribution of cyclone tracks and their point of origin.

• Tracks that made landfall in Oman were extracted from the

total tracks for dedicated analysis

• Two methods were used in the spatio-temporal

analysis.

• KDE , LDM
• The KDE and LDM analyses thus show the location-

frequency (density) of the Arabian Sea tropical cyclones (1881-2014) and their mean tracks, and how these factors vary over time, by cyclone intensity, and in particular for those cyclones which pose the greatest risk to Oman, those making landfall.

Arabian Sea tropical cyclones frequency

Landfall country Frequency % India 61 27.4 Oman 41 18.4 Pakistan 10 4.5 Somalia 6 2.7 Yemen (Socotra islands) 5 2.2 Terminates at Sea 99 44.4 Arabian Sea 93 41.7 Gulf of Aden 6 2.7 Total 222 100

Table 1. Distribution of tropical systems in the Arabian Sea, 1881-2014

Table 2. Monthly distribution of tropical events making landfall in Oman, 1881-2014

Jan Feb Mar Apr May June Jul Aug Sep Oct Nov Dec Total % 1880-1894 1 2 3 7 1895-1909 2 1 1 4 10 1910-1924 3 1 4 10 1925-1939 1 1 2 5 1940-1954 1 1 1 3 7 1955-1969 3 1 1 2 1 1 9 21 1970-1984 1 2 1 2 1 1 8 19 1985-1999 1 1 1 1 4 10 2000-2014 2 2 1 5 12 Total 13 9 2 2 5 7 1 3 42 100 % 31 21 5 5 12 17 2 7 100

5 10 15 20 25 1880-1894 1895-1909 1910-1924 1925-1939 1940-1954 1955-1969 1970-1984 1985-1999 2000-2014

Arabian Sea storm track analysis

Arabian Sea tracks classification.

Monthly distribution of Arabian Sea cyclone tracks, 1881-2014: (a) pre-monsoon, (b) post-monsoon, (c) pre-monsoon (with landfall in Oman) (d) post-monsoon (with landfall in Oman).

Arabian Sea storm track analysis

Spatio-temporal distribution of Arabian Sea cyclone tracks

KDE of Arabian Sea tracks 1881-2014: (a) all, (b) all pre-monsoon, (c) all post-monsoon, (d) all those making landfall in Oman, (e) pre-monsoon making Oman landfall, (f) post- monsoon making Oman landfall.

Arabian Sea storm track analysis

Spatio-temporal distribution of Arabian Sea cyclone tracks

KDE of Arabian Sea tracks 1881-2014: (a) all-May, (b) all-June, (c) all-Oct, (d) all-Nov, (e) all those making landfall in Oman in May, (f) making Oman landfall in June, (g) making Oman landfall in Oct, (h) making Oman landfall in Sept.

Arabian Sea storm track analysis

Spatio-temporal distribution of Arabian Sea cyclone tracks

Linear direction mean (LDM) of Arabian Sea cyclone tracks: (a) all tracks, (b) tracks making landfall in Oman, and (c) tracks making landfall in Oman by pre- and post- monsoon month.

Arabian Sea storm track analysis

Average sea surface temperature (ºC) of the Arabian Sea, 1880-2014

Average sea surface temperature (ºC) of the Arabian Sea, 1880-2014

Discussion and conclusions

• The analysis shows how cyclone tracks vary

seasonally and by pre and post-monsoon month.

• Cyclones tend to travel to the north of the Arabian

Sea, revealed by the high density all tracks KDE in the northeast Arabian Sea and the LDM analysis that shows cyclones travel to the northwest.

• In the pre-monsoon, a high density of tracks is found

in the northeast Arabian Sea, and the LDM moves to the north; in the post-monsoon, a high density of tracks occurs in the southeast Arabian Sea, with the LDM moving to the west.

• Turning to the cyclones that made landfall in Oman,

we find that in the pre-monsoon, cyclones tend to

• riginate in the south of the region in May and move

northward in June.

• tropical storm Ashobaa developed in June 2015

strike Oman in the northern region near Ras-Al Had.

• tropical cyclone Chapala and tropical cyclone Megh

that formed in the Arabian Sea in November 2015 both took a direction to the southwest Arabian Sea toward Yemen’s Socotra islands 240 km off the Horn

• f Africa

• These results reveal a series of general and broadly

predictable spatio-temporal patterns.

• the general patterns are useful in informing natural

hazard risk assessment and management in the region, including Oman which has suffered extensive damage in the past due to tropical cyclones.

• The results could, for example, assist with more

targeted cyclone preparation and deployment of emergency response resources, based upon areas most at risk to cyclones overall (strategic planning), and to specific storm events when these are first identified (tactical planning). For example, knowing that cyclones that develop in June are more likely to make landfall in the northern part of Oman is valuable emergency planning intelligence.

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