Tropical Cyclone Activity over the North Indian Ocean

Tropical Cyclones (TCs) are intense synoptic scale weather systems which originate over warm oceans of the world, develop into massive vortices composed of swirling winds, intense clouds and torrential rains by drawing energy from the ocean. When they move over land, they cause large scale destruction to life and property over the coastal areas of the world. India, with an extensive coastline of about 7500 km is vulnerable to the destructive features associated with landfalling TCs of the North Indian Ocean (NIO) basin comprising of the Bay of Be ngal (BOB) and the Arabian Sea (AS).

Tropical Cyclones (TCs), one of the most destructive of all the natural disasters, are capable of causing loss of life and extensive damage to property. The Bay of Bengal is a potentially energetic region for the development of cyclonic storms and approximately 7 % of the global annual tropical storms form over this region with two cyclone seasons in a year (Gray, Mon Weather Rev 96:669–700, 1968). Much of the TC related damage is attributed to storm surges, high winds, damage associated with strong thunderstorm complexes and TC-induced heavy rainfall. Predicting rainfall associated with TCs is a major operational challenge. Over the last few decades flooding from TCs at landfall has become a threat to human lives in India. Although track-forecasts continue to improve, quantitative precipitation forecasts (QPF) for TCs have shown little skill. One of the uncertainties in QPF is a lack of precipitation data over the open oceans to evaluate and validate numerical weather prediction (NWP) model results. TC rainfall forecasting techniques are lagging behind those of the track forecast. However, significant progress has been made in recent years due to the advance in remote sensing observations and the improvement of mesoscale models and data assimilation techniques. Until relatively recently, TC rainfall prediction was carried out mainly using empirical methods and subjective experience on the part of the forecaster. However, advanced techniques for Quantitative Precipitation Estimate (QPE) are currently employed in operational applications in some major forecasting centres, which already have greatly improved the forecasting for TC-related rainfall. Minakshi Devi et al. (Nat Hazard Risk 5(2):93–114. doi: 10.​1080/​19475705.​2013.​775186, 2014) have shown predicted tracks of a few cyclonic events such as SIDR (Nov, 2007), Aila (May, 2009) and Laila (May, 2010) along with their contribution to precipitation in the NE India. Recent studies have indicated that some high resolution dynamical model simulations are capable of capturing the rainfall pattern of TCs. Lee and Choi (J Geophys Res 115:12105. doi: 10.​1029/​2009JD012581, 2010) investigated the torrential rainfall associated with Typhoon Rusa in South Korea in 2002 through numerical simulation using Weather Research Forecast (WRF) model. Haggag and Yamashita (Jl. of Int. Dev Coop 15(1–2):47–63, 2009) studied the hydro-meteorological features of TC Gonu using coupled atmosphere, ocean and land surface modelling with an atmospheric component based on the MM5 model. There are other studies on performance of models including, Raju et al. (Nat Hazard 63:1361–1374. doi: 10.​1007/​s11069-011-9918-1, 2012), Osuri et al. (Int J Remote Sens 33:5, 2012), Abhilash et al. (Pure Appl Geophys 169:2047–2070, 2012), Routray et al. (Pure Appl Geophys 170:2329–2350. doi: 10.​1007/​s00024-013-0648-z, 2013) and Srivastava, et al. (Nat Hazard. doi: 10.​1007/​s11069-011-9835-3, 2011). All these studies indicate that the high resolution along with the improved data assimilation, especially DWR and satellite based data can improve the rainfall forecast by the models. Though heavy rainfall prediction is still a challenge, Hurricane WRF (HWRF) is a promising model for this purpose. A number of studies have examined the track, intensity, structure and genesis of TCs, however very few studies have considered the rainfall dynamics associated with TCs. The Hydro-meteorological aspects of TC have been dealt mainly in terms of coastal storm surge and inundation studies only.

During October 2013 Bay of Bengal (BOB) tropical cyclone (TC) ‘Phailin’ hit east coast of India. This was the most intense cyclone that made landfall over India after the Odisha Super Cyclone (29 October 1999). This TC originated from a remnant cyclonic circulation from the South China Sea. It intensified into a cyclonic storm on the 9 October 2013 and moved northwestwards. It further intensified into a very severe cyclonic storm on 10 October 2013 over east central BOB. It crossed Odisha coast near Gopalpur around 2230 h IST of 12 October 2013 with a sustained maximum surface wind speed of 200–210 kmph gusting to 220 kmph. Some of its unique features included the rapid intensification of the system from 10 October to 11 October 2013 resulting in an increase of wind speed from 83 to 215 kmph. Also, at the time of landfall on 12 October, maximum sustained surface wind speed in association with the cyclone was about 215 kmph and estimated central pressure was 940 hPa with pressure drop of 66 hPa at the center compared to surroundings (RSMC, New Delhi, 2014).

Intensity and structural changes of a Tropical Cyclone (TC) are known to be associated with environmental factors such as vertical wind shear (VWS), sea surface temperature (SST) etc. as well as TC specific factors such as its location, speed and direction of motion.

Communication plays a significant role in (1) the data collection from different observatories all over Indian region and other countries, (2) dissemination of data to different agencies for processing and generating information useful for forecaster, (3) exchanging the processed data and product among forecasters and other users and (4) reception of forecast and warnings from forecasters and dissemination to various agencies involved in disaster management.

Tropical Cyclones (TCs) are the most significant weather phenomena in North Indian Ocean (NIO), where these affect Indian sub-continent in general and India in particular. The inherent vulnerability features of TC in the basin lie with a long coastline of about 7516 km of flat coastal terrain, shallow continental shelf, geographical location and physiological features (Prasad and Rao 2006). Besides these, some other factors which influence vulnerability are limitations of observation networks, prediction systems, understanding of physical processes, early warning systems and disaster management, apart from socioeconomic conditions according to World Meteorological Organisation (WMO) (2013).

Cyclone Warning Division of India Meteorological Department (IMD), New Delhi acts as a Regional Specialised Meteorological Centre (RSMC) for north Indian Ocean (NIO) and provides tropical weather outlook and tropical cyclone (TC) advisories to the World Meteorological Organisation (WMO)/Economic and Social Cooperation for Asia and the Pacific (ESCAP) Panel member countries, viz., Bangladesh, Myanmar, Thailand, Srilanka, Maldives, Pakistan and Oman. The low pressure systems over the NIO are classified (Table 1) based on the associated maximum sustained surface wind (MSW) at the surface level (IMD, Cyclone warning services: standard operation procedure. Cyclone warning division, IMD, New Delhi, 2013a). The entire process of TC monitoring and forecasting (Mohapatra et al., Mausam 64:1–12, 2013a) is shown in a schematic diagram (Fig. 1). Like other Ocean basins, the TCs over the NIO also show sometimes significant changes in track, structure and intensity prior to, during and after the landfall. Out of 5–6 TCs developing over the NIO, about 3–4 make landfall (Tyagi et al., Inter-annual variation of frequency of cyclonic disturbances landfalling over WMO/ESCAP Panel Member Countries, WMO/TD-No. 1541 on Ist WMO International conference on Indian Ocean Tropical Cyclones and climate change, Muscat, Sultanate of Oman, 08–11 March 2009, WWRP-2010/2, pp 1–7, 2010; Mohapatra et al., Construction and quality of best tracks parameters for study of climate change impact on Tropical Cyclones over the North Indian Ocean during satellite era. In: Mohanty UC, Mohapatra M, Singh OP, Bandyopadhyay BK, Rathore LS (eds) Monitoring and prediction of Tropical Cyclones over the Indian Ocean and climate change. Springers/Capital publishers, New Delhi, pp 1–17, 2014). The strategies adopted by RSMC, New Delhi to predict the changes in track, structure and intensity of landfalling TCs along with difficult situations and future plans are presented in following sections.

A tropical cyclone (TC) is a warm core large scale low pressure system with maximum sustained wind (MSW) of 34 knots or more around the centre which rotates in anti-clockwise direction in Northern Hemisphere and clockwise in Southern Hemisphere. The TCs are most destructive due to the associated storm surge, heavy rain and wind. Indian coast is more prone to TC though the proneness varies from districts to districts (Mohapatra et al., Nat Hazard 63:1601–1620, 2012a; Tropical Cycl Res Rev 1:331–339, 2012b; Mohapatra, J Earth Syst Sci 124:515–526; J Earth Syst Sci 124:861–874, 2015a, J Earth Syst Sci 124:861–874, 2015b). Though there have been significant improvement in the track and intensity forecast of the TCs over North Indian Ocean (NIO) (Mohapatra et al., Nat Hazard 63:1601–1620, 2012a, Trop Cycl Res Rev 01:331–339, 2012b, J Earth Syst Sci 122:589–601, 2013a, Mausam 64:1–12, 2013b, Nat Hazard 68:433–451, 2013c; Mohapatra, J Earth Syst Sci 124:515–526, J Earth Syst Sci 124:861–874, 2015a, J Earth Syst Sci 124:861–874, 2015b), still there are challenges in the unique cases like rapid track change, rapid intensity change etc. Hence there is need for further understanding of physical processes associated with such unique cases of TCs developing over the NIO.

A depression formed over south Andaman Sea on 23rd evening and it intensified into a cyclonic storm, Lehar in the early morning of 24 November 2013 near Latitude 10.0° N and longitude 95.0° E. Moving northwestward, it crossed Andaman and Nicobar Islands near Port Blair around 0000 UTC of 25 November as a severe cyclonic storm. On 25th morning, it emerged into southeast Bay of Bengal and moved west-northwestward, intensified into a very severe cyclonic storm in the early hours of 26 November. However, while moving west-northwestwards over westcentral Bay of Bengal, it rapidly weakened from 27th afternoon and crossed Andhra Pradesh coast close to south of Machilipatnam around 0830 UTC of 28 November 2013 as a depression.

A depression formed over southeast Bay of Bengal at 1430 h IST of 10 May 2013 near latitude 5.0° N and longitude 92.0° E. It moved northwestwards and intensified into a deep depression in the evening of the same day. Continuing its northwestward movement, it further intensified into a cyclonic storm, Viyaru in the morning of 11 May 2013. Under the influence of the anti-cyclonic circulation lying to the east, the cyclonic storm changed its direction of movement initially from northwestward to northward and then to north-northeastward on 13 and 14 May, respectively. On 15 May, it further came under the influence of the mid-latitude westerly trough running roughly along 77° E, which further helped in enhancing the north-northeastward movement of the cyclonic storm. As this trough came closer on 16th, the north-northeastward speed of the cyclonic storm significantly increased, becoming about 40–50 kmph. The cyclonic storm crossed Bangladesh coast near latitude 22.8° N and longitude 91.4° E, about 30 km south of Feni around 1330 h IST of 16 May 2013 with a sustained maximum surface wind speed of about 85–95 kmph. Maximum surface wind of 92 kmph has been reported over Patuakhali, Bangladesh during the time of landfall. Widespread rainfall with isolated heavy to very heavy falls occurred over Bangladesh. Fairly, widespread rainfall with isolated heavy rainfall also occurred over Mizoram, Manipur and Tripura. A storm surge of height of about 1 m has been reported in section of media. After the landfall, it continued to move north-northeastwards and weakened gradually due to interaction with land surface. It weakened into a deep depression over Mizoram in the evening and into a depression over Manipur around mid-night of 16th. It further weakened into a well-marked low pressure area over Nagaland in the early morning and moved away towards Myanmar as a low pressure area in the morning of 17th.

Tropical cyclone (TC) is one of the severe disastrous weather events causing loss of property and life, especially for north Indian Ocean (NIO) basin. According to Mohapatra et al. (Nat Hazards 63:1601–1620, 2012b), entire east and west coast of India is prone for TC activity. However, the degree of proneness varies from district to district depending upon the number of TCs and severe TCs crossing/affecting the district as well as, associated adverse weather like heavy rain, gale wind and storm surge over the district due to the landfalling TCs (Mohapatra et al., Nat Hazards 63:1601–1620, 2012b). About 11 cyclonic disturbances (CDs) with maximum sustained wind speed (MSW of 17 knots or more) including depressions (MSW of 17–33 knots) and TCs (MSW of 34 knots or more) develop over the NIO during a year including 9 and 2 over the Bay of Bengal (BOB) and Arabian Sea (AS), respectively based on data of 1961–2010 (Mohapatra et al., Construction and quality of best tracks parameters for study of climate change impact on Tropical Cyclones over the North Indian Ocean during satellite era. In: Mohanty UC, Mohapatra M, Singh OP, Bandyopadhyay BK, Rathore LS (eds) Monitoring and prediction of tropical cyclones over the Indian Ocean and climate change. Springers and Capital publishers, New Delhi, pp 3–17, 2014). Out of these, about five intensify into TCs including about four over BOB and one over the AS. About three severe TCs (MSW of 48 knots or more) are formed over the NIO during a year. It includes two over the BOB and one over the AS. Considering the frequency of very severe TCs (MSW of 64 knots or more), there have been about two very severe TCs per year over the NIO. The frequency is maximum during post-monsoon season (October–December) followed by pre-monsoon (March–May) and monsoon (June–September) season.

Tropical cyclones (TCs) are one of the most devastating disastrous weather events worldwide and especially over the North Indian Ocean (NIO). About 75 % of all TCs which killed 5000 or more human population had developed over this basin during the past 300 years (Dube et al., Mausam 64:193–202, 2013). Considering this, there is always a need to strengthen monitoring, prediction and warning services for the TCs apart from preparedness and planning. The preparedness and planning for TC mitigation needs climatological information about the TCs to assess the hazard potential. Mohapatra et al. (Nat Hazards 63:1601–1620, 2012a; 2015) have analysed TC hazard proneness of various coastal districts of India in terms of frequency, intensity and associated adverse weather like heavy rain, gale winds and storm surge etc., However, the damage potential and the lead time available for management of the TC disaster depend crucially on the life period of the TCs, especially its period of stay over oceanic region before the landfall as the track and landfall forecast can be provided accurately to the disaster managers after the genesis of the TC only. The TCs over the NIO show large-scale spatio-temporal variations in terms of genesis, track, intensity and landfall (Mohapatra et al., Construction and quality of best tracks parameters for study of climate change impact on tropical cyclones over the North Indian Ocean during satellite era. In: Mohanty UC, Mohapatra M, Singh OP, Bandyopadhyay BK, Rathore LS (eds.) Monitoring and prediction of tropical cyclones over the Indian Ocean and climate change. Springers and Capital publishers, New Delhi, pp 3–17, 2014; Tyagi et al., Inter-annual variation of frequency of cyclonic disturbances landfalling over WMO/ESCAP Panel Member Countries, WMO/TD-No. 1541 on Ist WMO international conference on Indian Ocean tropical cyclones and climate change, Muscat, Sultanate of Oman, 8–11 March 2009, WWRP-2010/2, pp 1–7, 2010; IMD, Tracks of cyclones and depressions (1891–2007). Electronic Version 1.0/2008, Published by IMD, Chennai, 2008; Cyclone warning in India; Standard operational procedure. IMD, New Delhi, 2013). Therefore, there is a need to find out the average life period of the cyclonic disturbances (CDs) with different intensities in different seasons and year as a whole over different ocean basins, namely, Bay of Bengal (BOB), Arabian Sea (AS) and the North Indian Ocean (NIO) as a whole. There are many studies over the Northwest Pacific and North Atlantic Ocean on the above climatological aspects. However, studies are limited over the NIO.

The extensive coastal belt of India is very vulnerable to the deadly storms known as tropical cyclones (Mohapatra et al., Nat Hazards 63:1601–1620. doi:10.​1007/​s11069-011-9891-8, 2012; Mohapatra, J Earth Syst Sci 124:515–526. doi:10.​1007/​s12040-015-0556-y, 2015). These systems form initially as low-pressure areas (when the maximum sustained surface wind speed is < 17 knots) over the north Indian Ocean (NIO) and then intensify into depressions (maximum sustained surface wind speed is between 17 and 33 knots) and occasionally become tropical cyclones (when the surface wind exceeds 33 knots). For the tropical cyclones only, the peak is observed during November, followed by October in the post-monsoon season (October–December; OND), followed by the month of May in pre-monsoon season (March–May; MAM) (Pattanaik, Int J Climatol 25:1523–1530, 2005). Over the Bay of Bengal (BOB), the months of October–November are known to produce cyclonic disturbances (CDs; system of intensity depression and higher) of severe intensity, which after crossing the coast cause damages to life and property over many countries of south Asia surrounding the BOB. The strong winds, heavy rains and large storm surges associated with CDs are the factors that eventually lead to loss of life and property. Rains (sometimes even more than 30 cm/24 h) associated with cyclones are another source of damage. The combination of a shallow coastal plain along with the world’s highest population density coupled with low socio-economic conditions in the region surrounding the BOB has resulted in several land falling CDs becoming devastating natural disasters. Thus, the seasonal forecast of frequency of CDs over the BOB is of great use to many users. Interest from the media and the general public in seasonal forecasts of CDs has increased tremendously.

The Indian sub-continent is one of the most adversely affected TC active basins that experience on an average 4–5 TCs every year. In comparison to other TC basins, this region is the most vulnerable due to relatively dense coastal population, shallow bottom topography and coastal configuration. Though the TCs formed in this region are considered to be much weaker in intensity and smaller in size as compared to other region, yet the number of deaths in the region is highest in the globe (300,000 human deaths were estimated from TC associated storm surge in Bangladesh in 1970). Out of nine recorded cases of heavy loss of human lives (~40,000) by TCs during last 300 years, seven cases (77 %) occurred in Indian sub-continent (Frank and Hussain, Bull Amer Meteor Soc 52:438–445, 1971). To overcome such loss, the advance predictions of TC in terms of their genesis, track and intensity is highly important. These advance timely information can save the life of people and help in decision making for taking the preventive measures like evacuation during the TC landfall. The predictions of TC are generated based on the models, using the satellite observations and ground based radar networks when TC reaches close to the land (Mohapatra et al., J Earth Syst Sci 122:433–451. doi:10.​1007/​s12040-013-0291-1, 2013a). Due to the advancements in numerical prediction models and, high temporal and spatial satellite observations, during the last decades the track prediction accuracy has been improved drastically (Mohapatra et al., Nat Hazards 68:589–601. doi:10.​1007/​s11069-013-0624-z, 2013b; J Earth Syst Sci 124:861–874. doi:10.​1007/​s12040-015-0581-x, 2015). However, the predictions of TC genesis and intensity are still challenging as in TC predictions (Mohapatra et al., Mausam 61:1–15, 2013c), the requirements of accuracy in genesis, track and intensity are higher compared to normal numerical weather predictions. Skillful prediction of tropical cyclogenesis will be of great benefit for the affected communities as it may provide sufficient time for planning and preparations (e.g. Brunet, Bull Amer Meteorol Soc 91:1397–1406, 2010). Due to unavailability of conventional observations, satellite data are being employed and found to be useful tool to study and understand tropical cyclogenesis (Liu et al., Meteorol Atmos Phys 56:111–123, 1995; Zehr, Satellite diagnosis of tropical cyclones. In: Proceedings of 3rd conference on satellite meteorology and oceanography, Anaheim, CA, pp 241–246, 1998; Katsaros et al., Geophys Res Lett 28:1043–1046, 2001; Sharp et al., Bull Amer Meteorol Soc 83:879–889, 2002; Li et al., Geophys Res Lett 30:2122, 2003; Chelton et al., Science 303:978–983, 2004; Wang et al., Tellus (Ser. A) 59:562–569, 2007; Geophys Res Lett 35:1–5, 2008). The microwave scatterometers onboard polar-orbiting satellites have helped to study the early stages of cyclogenesis (Sharp et al., Bull Amer Meteorol Soc 83:879–889, 2002). Sea-winds scatterometer, aboard the QuikScat satellite that infers surface wind speed and direction, has encouraged various studies regarding early identification of tropical disturbances (Sharp et al., Bull Amer Meteorol Soc 83:879–889, 2002; Li et al., Geophys Res Lett 30:2122, 2003). The wind pattern matching based technique using scatterometer derived surface wind have been discussed by Jaiswal and Kishtawal (IEEE Trans Geosci Remote Sens 49:4904–4909, 2011) and Jaiswal et al., Meteorol Atmos Phys 119:137–149, 2013. The above technique depends on the availability of coverage of the cyclonic disturbance during the satellite overpass. In the present study, the cyclogenesis prediction of the systems formed during year 2013 has been discussed using the OSCAT derived surface wind vector based cyclogenesis prediction algorithm. The brief methodology is provided in Sect. 2. The results are discussed in the Sect. 3 and the conclusions of the study are given in Sect. 4.

The aim of the study is to correlate the role of the Madden-Julian Oscillation (MJO) with the genesis of the cyclonic storms that occurred during the year 2013 in the Indian Ocean/Bay of Bengal (BOB) region. The MJO is the major fluctuation in tropical weather on weekly to monthly timescales. This eastward propagating tropical disturbance was first identified by Madden and Julian (J Atmos Sci 28:702–708, 1971). The MJO can be characterised as an eastward moving ‘pulse’ of cloud and rainfall near the equator that typically recurs every 30–60 days and has a global wave number one structure with a spatial wavelength of roughly 12,000–20,000 km (Nakazawa, J Meteorol Soc Jpn 64:17–34, 1986). The MJO is characterised by an eastward progression of large regions of both enhanced and suppressed tropical rainfall, observed mainly over the Indian and Pacific Ocean. This oscillation is associated with eastward-moving convection with an enhanced convective phase followed by a non-convective (suppressed convection) phase at any one location. The low-level wind fields associated with MJO are characterised by fluctuations between easterly and westerly phases and can be observed in several other parameters such as surface pressure, upper tropospheric wind, and proxies for deep convection such as outgoing long-wave radiation (OLR).

Tropical cyclones (TCs) are one of the most devastating weather phenomena that cause large number of human casualties and loss of property. It is well known that the TCs over North Indian Ocean (NIO) have caused the maximum loss of human lives. The death toll in Bangladesh cyclone of November 1970 has been estimated to be about 300,000. The tropical depression (Maximum Sustained Surface Wind Speed (MSSWS) 17–33 knots or more) and TCs MSSWS 34 knots or more form over warm ocean surfaces, with SST more than 26.0 °C, low magnitudes of vertical wind shear and large magnitudes of low-level relative vorticity, coriolis force and mid-tropospheric level relative humidity (Gray, Mon Weather Rev 96:669–700, 1968). Gray (Hurricanes: their formation, structure and likely role in the tropical circulation. In: Shaw DB (ed) Meteorology over the tropical oceans. Royal Meteorological Society, James Glaisher House, Gvenville Place, Bracknell, Berkshire, RG 121 BX, pp 155–218, 1979), using 20 years of data has shown that the global tropics produce about 80 TCs in a year out of which only 6 form over NIO. Most of the TCs form over NIO during October–December (primary peak season) and March–May (secondary peak season). The period of May-November is the peak season for tropical depressions (TDs) over the NorthWest Pacific Ocean (NWPO).

Tropical cyclones (TCs) are synoptic scale intense low pressure systems which form over the warm tropical oceans characterised by strong cyclonic winds and organised convection with heavy rainfall. The TC causes enormous damage to life and property at the time of crossing the coast and subsequent movement over the land. The TCs can impact over a wide area with its strong winds, heavy rains and storm surges. Gray (Hurricanes: their formation structure and likely role in the tropical circulation. In: Shaw DB (ed) Meteorology over the Tropical Oceans. Royal Meteorological Society, Bracknell, pp 155–218,1979) prepared a detailed climatology of the TCs in the global ocean basins. He observed that annually about 80 TCs form globally of which half to two thirds reach hurricane strength (maximum sustained winds greater than 33 m/s). East coast of India is frequently affected by TCs that form over Bay of Bengal (Tyagi et al., Inter-annual variation of frequency of cyclonic disturbances landfalling over WMO/ESCAP Panel Member Countries. WMO/TD-No. 1541 on 1st WMO International conference on Indian Ocean tropical cyclones and climate change, Muscat, Sultanate of Oman, 8–11 March 2009, WWRP-2010/2, 2010). During the period 1891–2010, about 134 severe TCs crossed the east coast of India (IMD, Cyclone e-Atlas-IMD tracks of cyclones and depressions over North Indian Ocean. www.​rmcchennaieatlas​.​tn.​nic.​in, 2011; Atlas of storm track). Anthes (Tropical cyclones: their evolution, structure and effects. Meteorological Monographs, American Meteorological Society, Boston, 1982) has extensively studied the three dimensional structure of TC. He observed that the surface pressure is lowest at the centre of the TC and increases outward. The wind speed reaches its maximum value at nearly 40–80 km from the centre beyond which it decreases. The central parts are warmer than the surroundings and the temperature anomaly could be more than 10° K at the upper troposphere. The TC grows upto a height of 10–15 km. Intense TCs frequently develop an eye, which is a cloud free region at the centre of the storm characterised by the presence of subsidence.

Tropical cyclones (TCs) belong to the class of severe weather systems associated with strong ocean-atmospheric coupling. They are highly disastrous weather phenomena that cause damage to the life and physical infrastructure in tropical maritime countries. The Indian coastal lands, especially the east coast, are highly vulnerable to the TCs in the post-monsoon season of October to December. Weak vertical wind shear, high sea surface temperature (SST) (>26.5 °C), pre-existing disturbance like tropical easterly waves are some of the favorable conditions (Anthes, Tropical cyclones: their Evolution, structure and effects, American Meteorological Society, Science Press, Ephrata, p 208, 1982; Gray, Mon Weather Rev 96:669–700, 1968) favouring the development and sustenance of TCs in this season in the North Indian Ocean (NIO). SST is a crucial influential parameter for the formation and development of TCs. A threshold SST value of 26.5 °C was defined by Gray (Mon Weather Rev 96:669–700, 1968) for the genesis and further development of TCs. A TC is characterised with an outward diverging motion in the upper atmosphere and converging motion at the surface. Higher upper air divergence facilitates further deepening through enhanced convergence at the lower levels. The upper ocean provides heat energy to the overlying atmospheric boundary layer and for the deepening process by enhancing the convection. Earlier studies have shown that TCs experience sudden intensification when they entered oceanic areas with higher SSTs. There are several observational and modelling studies which explained the upper-ocean response to TCs (e.g. Price, J Phys Oceanogr 11:153–175, 1981; Price et al., J Phys Oceanogr 24:233–260, 1994; Shay and Elsberry, J Phys Oceanogr 17:1249–1269, 1987; Sanford et al., J Phys Oceanogr 17:2065–2083, 1987; Bender and Ginis, Mon Weather Rev 128:917–946, 2000; Shay et al., Mon Weather Rev 128:1366–1383, 2000). Among a number of factors, the TC intensification is partly controlled by the surface heat and moisture fluxes that feed the energy to the storm and the dissipation by the roughness to the winds at the sea surface (Chen et al., J Atmos Sci 70:3198–3215, 2013). The upper ocean heat content and surface temperature are influential in the ocean–atmosphere interaction and the supply of energy through sensible and latent heat fluxes for the development and sustenance TCs. Emanuel (Nature 436:686–688, 2005) and Webster et al. (Science 309:1844–1846, 2005) suggested that the rising SSTs in the Atlantic Ocean are related to the increase in the hurricane activity. A number of studies have shown that the strong surface wind in a TC drives sea surface waves and underlying ocean currents and enhance upper-ocean turbulent mixing, cools the SST, and result in a cold wake behind (Price, 1981), which, in turn, provides a negative feedback on TC intensity (Schade and Emanuel, J Atmos Sci 56:642–651, 1999; Chan et al., J Atmos Sci 58:154–172, 2001). It has been reported that warmer SST associated with large ocean heat content causes TC intensification (Hong et al., Mon Weather Rev 128:1347–1365, 2000; Shay et al., Mon Weather Rev 128:1366–1383, 2000; Bright et al., Geophys Res Lett 29:1801, 2002), whereas negative SST anomalies associated with cold-core eddies or TC-induced cold wake weakens TC systems (Walker et al., Geophys Res Lett 32:L18610, 2005). A few workers (Knutson and Tuleya, J Climate 17:3477–3495, 2004; Michaels et al., Geophys Res Lett 33:L09708, 2006) using computer models have shown that increase in SST due to green house warming leads to increase in hurricane intensity. Michaels et al. (Geophys Res Lett 33:L09708, 2006) reported that the strong relationship of TC intensity with SST is not clear at the upper range of SSTs. Though SST is known to influence the intensity of TCs, it is still not clear how it influences the movement of the storms. It is necessary to investigate the air–sea interaction processes associated with SST parameter and upper ocean heat content by analysis of the air–sea fluxes through numerical experiments. In this study, an attempt is made to understand the role of SST on the movement and intensity of the TCs by performing numerical simulations with a mesoscale atmospheric model.

There are two tropical cyclone (TC) seasons over the North Indian Ocean (NIO), (including the Bay of Bengal (BOB) and the Arabian Sea (AS)), i.e. during the pre-monsoon months (April–early June) and the post-monsoon months (October–December) (Mohanty et al., Mar Geod 33:294–314, 2010). Further the Indian subcontinent happens to be one of the world’s highly vulnerable areas since the coastal population density is very high leading to an extensive damage to life and property. Therefore, forecasting of TC track and landfall location is critical for early warnings and mitigation of disaster. Track forecast errors over the NIO though improved significantly in recent years (Mohapatra et al., J Earth Syst Sci 122:589–601, 2013, J Earth Syst Sci 124:861–874. doi:10.​1007/​s12040-015-0581-x, 2015) are still high relative to those over the Atlantic and Pacific Oceans. With advancements in computational power, development of better NWP models (both global and regional), the forecasting capability of meteorologists have greatly increased. Several meteorological centers like NCEP, UKMet office, ECMWF, JMA, JTWC etc give a real time forecast of TC tracks from their global NWP models (deterministic as well as Ensemble Prediction Systems (EPS)) (Hamill et al. Mon Weather Rev 139:3243–3247, 2011; Froude et al. Mon Weather Rev 135:2545–2567, 2007; Buckingham et al. Weather Forecast 25:1736–1754, 2010; Heming et al. Meteorol Appl 2:171–184, 1995; Heming and Radford Mon Weather Rev 126:1323–1331, 1998). TC track prediction from an ensemble forecasting system besides providing a track from each ensemble member also provides the strike probability (Weber Mon Weather Rev 133:1840–1852, 2005). For the TCs of NIO, Mohapatra et al. (J Earth Syst Sci 122:589–601, 2013, J Earth Syst Sci 124:861–874. doi:10.​1007/​s12040-015-0581-x, 2015) provided a detailed verification of the official forecast tracks and its improvements in the recent past. This study provides a detailed verification of the NCMRWF NWP model forecasts of 2013 TC cases. Some of the earlier studies (Ashrit et al. Improved track and intensity predictions using TC bogusing and regional assimilation. In: Mohanty UC, Mohapatra M, Singh OP, Bandyopadhyay BK, Rathore LS (eds) Monitoring and prediction of TCs in the Indian ocean and climate change, Springer, Dordrecht, p 246–254, 2014; Chourasia et al. Mausam 64:135–148, 2013 and Mohandas and Ashrit Nat hazard 73:213–235, 2014) focused on the NCMRWF model TC forecasts and the impact of bogusing, assimilation and cumulus parameterisation etc. The present study is focused on the real time operational forecasts provided to India Meteorological Department (IMD). During May–December 2013, there were five TCs observed in the Bay of Bengal namely: Viyaru (May10–17), Phailin (October 4–14), Helen (November 19–23), Lehar (November 19–28) and Madi (December 6–13). This report summarises the performance of the real time prediction of these TC tracks by the NCMRWF Global Forecast Systems.

Tropical cyclones (TCs) are one of the most devastating extreme weather events causing tremendous loss to human civilisation. With the growing population and economic developments, more life and property are getting exposed to the nature’s fury, particularly, along the coastal areas and these vulnerable groups always look forward to efficient real time forecasting to minimise their losses. Numerical Weather Prediction (NWP) models with its reasonable strength to forecast for several days in advance especially for the data sparse regions over the oceans are extremely handy for the operational forecasters. There has been considerable improvement during the past decades in the prediction of track and intensity of TC (Mohapatra et al. J Earth Syst Sci 122:433–451. doi:10.​1007/​s12040-013-0291-1, 2013a, Nat Hazard 68:589–601. doi:10.​1007/​s11069-013-0624-z, 2013b, Mausam 61:1–15, 2013c) using NWP models (Kotal et al. Trop Cycl Res Rev 3:162–177, 2014). Hence, the operational forecasters across the globe look forward to the NWP models’ products.

Tropical cyclones (TCs) are one of the most devasting and deadliest meteorological phenomena worldwide. This devastation is mainly due to torrential rains, high winds and associated storm surges (Mohapatra et al. Nat Hazard 63(3). doi:10.​1007/​s11069-011-9891-8, 2012, J Earth Syst Sci 124:861–874. doi:10.​1007/​s12040-015-0581-x, 2015). The TC genesis has been attributed to both thermodynamic and dynamical factors. Palmen (Geophysica 3:26–38, 1948) showed that TCs form over regions where sea surface temperature (SST) is greater than 26 °C. In addition to SST, other important factors for genesis of TCs are: large Coriolis force (LCF), high low-level relative vorticity, weak vertical wind shear, moisture in the middle troposphere and convective instability. In the regions, moist convection dominates the process of transporting mass, energy, and momentum through the atmosphere. On longer timescales, the large-scale environment can influence and control the mesoscale organisation and activities. The long chain of multi-scale interactions of physical parameters is challenging task to handle in the numerical models of weather systems and hence, genesis of TCs is a particular example that has motivated the present study.

Tropical cyclones (TCs) are highly disastrous weather phenomena characterised with extreme winds, heavy precipitation and storm surges at landfall along coastal lands. Accurate prediction of the TC formation, movement and intensity is vital for early warning and disaster management. The favourable environmental conditions have been identified as presence of an initial disturbance in the form of incipient lows or tropical easterly waves, high sea surface temperature (SST) (≥26.5 °C) for transport of energy through air–sea fluxes, weak vertical wind shear in the 850–200 hPa layer conducive to large-scale cloud development and divergence in the upper atmosphere to facilitate further surface-level convergence and for overall sustenance of the system (Anthes TCs: their evolution, structure and effects. American Meteorological Society, Science press, Ephrata, p 208, 1982; Gray General characteristics of TCs. In: Roger P,Jr, Roger P, Sr (eds) Storms, vol 1. Routledge, 11 New Fetter Lane, London EC4P4EE. pp 145–163, 2000). The annual average frequency of TCs in the North Indian Ocean (NIO) is about five (Asnani Tropical meteorology, vols. 1 and 2, published by Prof. G.C. Asnani, c/o Indian Institute of Tropical Meteorology, Dr. HomiBhabha Road, Pashan, Pune 411008, India, 1993). Numerical prediction of TCs requires accurate specification of initial conditions that define the characteristics of an incipient storm in terms of its location, radius, central pressure, and tangential and vertical winds.

The Indian subcontinent is the worst affected part of the world due to tropical cyclones (TCs). This region account for ~7 % 0.of the total number of global TCs (Gray 1968). The formation of TCs is more pronounced over Bay of Bengal (BOB) compared to Arabian Sea. A large number of TCs form over the BOB region generally move in the north and north-west directions and make landfall along the coastal regions of India, Bangladesh, and Myanmar (Tyagi et al. 2010; Mohapatra et al. 2012, 2015). These TCs have been responsible for the damage of property, loss of agriculture crops, and thousands of human lives (Paul 2010). In the BOB, TC genesis is highly seasonal with primary maximum in the post-monsoon season (October to December) and secondary maximum during pre-monsoon season (April and May). Hence, there is a need to improve the understanding and the forecast of TC over the Indian Ocean region. Several dynamic models have been used for the forecasting of the track and intensity of TC over specific regions. There has been significant improvement in recent years in terms of track, intensity and landfall forecasts (Mohapatra et al. 2013a,b,c). However, the accurate track and intensity predictions of TCs remain a challenging task for atmospheric scientists and the research community.