Role of warm ocean conditions and the MJO in the genesis and intensification of extremely severe cyclone Fani

Cyclone Fani, in April 2019, was the strongest pre-monsoon cyclone to form in the Bay of Bengal after 1994. It underwent rapid intensification and intensified quickly to an extremely severe cyclone. It maintained a wind speed of ≥ 51 m s−1 (≥ 100 knots) for a record time period of 36 h. The total lifespan of the cyclone was double than the climatological lifespan. Also, the duration of the cyclone in its extremely severe phase and the accumulated cyclone energy were significantly larger than the climatological records for the pre-monsoon season. In the current study, we investigate the ocean-atmospheric conditions that led to its genesis, rapid intensification and long lifespan. Our analysis shows that the Madden Julian Oscillation and anomalous high sea surface temperatures provided conducive dynamic and thermodynamic conditions for the genesis of cyclone Fani, despite forming very close to the equator where cyclogenesis is generally unlikely. Further, favourable ocean subsurface conditions and the presence of a warm core eddy in the region led to its rapid intensification to an extremely severe cyclone. A large area of warm ocean surface and subsurface temperatures aided the cyclone to maintain very high wind speed for a record time period. The vital role of the ocean surface and the subsurface in the genesis and the intensification highlights the need to efficiently incorporate ocean initial conditions (surface and sub-surface) and ocean–atmosphere coupling in the operational cyclone forecasting framework.

Tropical cyclones are among the most destructive natural disasters on earth. The north Indian Ocean, including the Arabian Sea and the Bay of Bengal, accounts for about 6% of the global tropical cyclones 1 . The cyclone frequency in this region varies between 1-3 in the pre-monsoon (March-May) to 2-5 cyclones in the postmonsoon (October-December) season 2 . Studies show that there is an increase in the intensity of pre-monsoon cyclones in the Bay of Bengal during recent decades 3 . Since 1990, four major cyclones with a maximum sustained wind speed larger than 51 m s −1 (100 knots) have formed in this basin during the pre-monsoon months (March-May) (Source: Regional Specialised Meteorological Centre reports http://www.rsmcn ewdel hi.imd.gov. in). Cyclone Fani, which formed as a depression on 26th April 2019 in the south Bay of Bengal, is the fifth major cyclone after 1990, and the strongest pre-monsoon cyclone after 1994 in the Bay of Bengal. It formed very close to the equator, intensified rapidly and attained a maximum wind speed of 59 m s −1 (115 knots). On 3rd May, it hit Odisha Coast near Puri with a wind speed of ~ 54 m s −1 (105 knots). It is for the first time since 1990 that a cyclone which formed in April hit the Odisha coastline. Cyclone Fani sustained for 204 h, which is double the average lifespan (100 h) of a pre-monsoon cyclone in the Bay of Bengal. Also, during its lifespan, it travelled a distance of 3024 km from the south Bay of Bengal (close to the equator) to the north Odisha coast and then to Bangladesh after striking the Odisha coast. The extremely high wind speed combined with coastal storm surge and flooding caused vast damage to infrastructure, agriculture and an estimated death of 70-90 human beings.
The Madden-Julian Oscillation (MJO) is known to influence cyclogenesis across the tropics [4][5][6][7][8][9][10] . In the north Indian Ocean also, the genesis and evolution of the cyclone is generally associated with the MJO 11,12 . The MJO is an eastward propagating band of enhanced convection close to the equator, followed by suppressed convection in that region at a 30-60 days cycle 13 . It is generally associated with the oscillation between low level easterly and westerly winds close to the equator. Also, corresponding variations are observed in the outgoing longwave radiation (OLR), which is a proxy of convection, with anomalous low values of OLR denoting enhanced convection. Further, the enhanced convection due to the MJO activity is associated with the strengthening of westerly winds www.nature.com/scientificreports/ in the lower troposphere to the west of the convection centre 14 . This leads to an increase in the lower level cyclonic vorticity close to the equator in both hemispheres. The anomalous westerlies associated with the MJO leads to the growth of small scale slow-moving eddies through barotropic eddy kinetic energy conversion from the mean westerly flow. These eddies, along with enhanced cyclonic vorticity, high sea surface temperatures (SSTs), and strong low-level convergence, provide conducive conditions for the genesis of the cyclone 15 . The cyclones in the north Indian Ocean are found to get clustered in the area of enhanced low level cyclonic vorticity associated with the MJO 16 . Another study shows that the seed for the genesis of cyclone in the north Indian Ocean provided by the MJO is the convectively coupled Rossby wave that detaches from the central area of MJO-induced convection 17 . MJO activity in the Indian Ocean increases the relative humidity and decreases the vertical wind shear, thus providing conducive background conditions for the genesis of the cyclone 18,19 . The chances of cyclone formation over the Bay of Bengal get significantly enhanced when the MJO associated enhanced convection is centered over the eastern Indian Ocean and the Maritime continent 19 . These studies show that the MJO plays a significant role in the genesis of cyclones in the north Indian Ocean. The unprecedented nature of cyclone Fani has motivated us to explore the role of MJO and other ocean-atmospheric processes in terms of its genesis very close to equator, its intensity, rapid intensification, and high wind speed for record duration.

Materials and methods
Cyclone data such as wind speed and track information are obtained from the India Meteorological Department (IMD) Regional Specialised Meteorological Centre (RSMC) preliminary report on Fani cyclone. To represent the combined strength and duration of the tropical cyclone, we use the accumulated cyclone energy (ACE) index. ACE is calculated by summing the squares of the 6-hourly maximum wind speed in knots for the duration when the system has a wind speed of 35 knots (18 m s −1 ) or higher. The number is divided by 10,000 to make it more readable and easy to interpret 20 . ACE is estimated as: where v is the maximum wind speed in knots. The ACE and other cyclone-specific information (such as the lifespan of cyclones in the Bay of Bengal) used in this study are estimated based on the reports from IMD RSMC. For analysing the ocean surface conditions over the north Indian Ocean during the evolution of cyclone Fani, daily SST data from the Optimum Interpolation Sea Surface Temperature (OISST) data set, at a spatial resolution of 0.25°2 1 , is utilized. The wave height data is obtained from the Indian National Centre for Ocean Information Services. Daily data for sea level anomalies are obtained from the Copernicus Marine Service Altimeter satellite gridded Sea Level Anomalies L4 dataset for the period 1993-2019. To investigate the ocean subsurface conditions that led to the intensification of the cyclone, we estimate the Tropical Cyclone Heat Potential (TCHP). TCHP is the integrated heat content per unit area relative to the 26 °C isotherm 22,23 . It is calculated as.
where C p (4178 J kg −1 °C −1 ) is the heat capacity of ocean water at constant pressure, ρ (1026 kg m −3 ) is the average ocean water density in the upper ocean, and Z 26 is the depth of 26 °C isotherm in the ocean. In our study, TCHP is calculated based on the ocean subsurface daily data obtained from Indian National Centre for Ocean Information Services-Global Ocean Data Assimilation System (INCOIS-GODAS) 24 for the period 19th-25th April 2019.
In order to explore the atmospheric conditions prevailing during the evolution of the cyclone, we used the relative vorticity and wind data (at 850 and 200 hPa levels), obtained from the ERA-Interim reanalysis dataset at a spatial resolution of 0.75°2 5 . The OLR data is obtained from NOAA interpolated OLR dataset 26 . The vertical wind shear of horizontal winds is the magnitude of vector difference in the winds at 200 hPa and 850 hPa levels. The daily anomalies of all atmospheric parameters and SST are calculated based on the daily climatology for the period 1982-2019. Student's two-tailed t test is applied to identify the significance of the ocean-atmosphere parameters anomalies at 95% confidence level.
To identify the phase and amplitude of MJO and its role on the genesis and evolution of the cyclone, Real-time Multivariate MJO (RMM) index data obtained from the Australian Bureau of Meteorology is used. The different phases of RMM indicate the region in which the convection associated with the MJO is present. The RMM index is derived using the first two empirical orthogonal functions (RMM1 and RMM2) of the equatorially averaged over the region 15°S-15°N for OLR data, and lower level (850 hPa) and upper level (200 hPa) zonal wind data 27 .

Results
Characteristics of cyclone Fani. Cyclone Fani is the strongest pre-monsoon cyclone to form in the Bay of Bengal after 1994 (Fig. 1a). The storm attained cyclonic storm status [wind speed more than 18 m s −1 (35 knots)] at 5.2°N on 27th April 1130 a.m. IST. (Fig. 2a). This is the closest formation of a cyclonic storm near to equator in the north Indian Ocean (including both the Arabian Sea and the Bay of Bengal), since 1990.

Factors controlling the genesis and rapid intensification of cyclone Fani. A week prior (19-25
April) to the formation of cyclone Fani, high SSTs of the order of 30-31 °C with significantly (P < 0.05) large SST anomalies of about 0.8-1.2 °C were observed over most parts of the Bay of Bengal (Fig. 2a), providing conducive environment for cyclone formation and intensification. These are the highest SSTs observed spatially in the Bay of Bengal prior to the genesis of the last five extremely severe cyclones in the pre-monsoon season (Fig. 3a-e). The SSTs averaged for a week (day -7 to day -1) prior to the day of cyclogenesis (day 0), over a 5° × 5° region at the genesis center, shows that the average SST prior to genesis of cyclone Fani was 30.4 °C. This is the highest SST observed at the genesis center prior to genesis of any cyclone in April month in the Bay of Bengal during the period 1990-2019. Also, from 25th April onwards, an active propagation of the MJO in the eastern Indian Ocean (phase 3) was observed (Fig. 4a). From 28th April, the MJO activity started moving towards the Maritime Continent (phase 4). Enhanced convection, as indicated by negative OLR anomalies, can be seen rapidly propagating towards the Maritime Continent (Fig. 4b). As the MJO propagated from the western to the eastern Indian Ocean and later to the maritime region, it led to anomalous westerlies in the equatorial region in the Bay of Bengal along its trailing edge of enhanced convection. Also, anomalous easterlies were seen in the Bay of Bengal at 10°N-15°N (Fig. 5a). This led to an anomalous cyclonic circulation over the southern Bay of Bengal and increased the low-level cyclonic vorticity (Fig. 5b). This anomalous low-level cyclonic vorticity is a favourable condition for the genesis of the cyclone 11 .
High relative humidity (moist atmosphere) in the low-to-middle troposphere is another crucial factor that provides conducive conditions for the genesis and the intensification of the cyclone 28,29 . The MJO propagation causes changes in the relative humidity that affects the genesis of the cyclone 30 . Generally, anomalously high relative humidity is observed over the area where an active MJO related convection is present. Figure 5c displays the average anomalous relative humidity from 1000 to 500 hPa averaged over the period 19th-25th April. It is seen that significantly (P < 0.05) anomalous relative humidity was persisting over the east Equatorial Indian Ocean during this period.
Along with relative humidity, the vertical wind shear of horizontal winds between upper and lower levels plays a significant role in the genesis and intensification of cyclones, where high wind shear inhibits cyclone formation and low wind shear favours it 7,31,32 . One week before cyclone formation, as the MJO enhanced convective moved from the western Indian Ocean to the eastern Indian Ocean, the vertical wind shear over the southern Bay of Bengal has decreased as shown by a negative anomaly (Fig. 5d). Previous studies show that the active propagation of MJO through the Bay of Bengal leads to a decrease in wind shear. This decrease in wind shear is due to anomalous low-level westerlies and anomalous upper-level easterlies, which counteract the climatological  www.nature.com/scientificreports/ as cyclone Fani moved over the area of an anticyclonic warm-core oceanic eddy which was present over the region (11°N-14°N, 85°E-88°E, See Fig. 2c) during the period 19th-25th April (represented by anomalous sea surface height of the order of 20-30 cm). These warm-core oceanic eddies are known to influence the cyclone intensity in different ocean basins. Sudden intensification of Hurricane Opal from 965 to 916 hPa in the Gulf of Mexico over 14 h after passing over a warm core eddy 22 is an excellent example of the influence of warm-core eddy on cyclones. In the north Indian Ocean also the mesoscale eddies are commonly observed 33 . Theses eddies are generated due to ocean local instability and also they propagate from the eastern or central Bay of Bengal to the western Bay of Bengal 33,34 . In the pre-monsoon season, these eddies in the western Bay of Bengal move northeastward along the east India coastal current 35 . The cyclonic and anticyclonic eddies significantly affect the intensity of the cyclone when the cyclones cross these eddies 1 . The warm-core eddy provides more warm water volume and thus aids intensification of the cyclone as the cyclone move over these eddies 36 . From Fig. 6 it can be www.nature.com/scientificreports/  www.nature.com/scientificreports/ seen that cyclone Fani was the only extremely severe cyclone among the five extremely severe cyclones, which has directly passed over the warm core eddy present over the west Bay of Bengal. There was basin wide very warm SSTs of order of 29-31 °C (Fig. 3e) and high TCHP of about 80-100 kJ cm −2 up to 15°N (Fig. 2e) along the track of cyclone Fani during the period 19th-25th April. This has aided the cyclone in maintaining a very high wind speed of ≥ 51.44 m s −1 (≥ 100 knots) for a record time period of 36 h. As the MJO further propagated eastwards in the first week of May (Fig. 4a), the relative vorticity, relative humidity and the wind shear averaged over 5° × 5° box at the region where cyclone Fani had its genesis on 26th April, again became unfavourable for cyclogenesis ( Supplementary Fig. 1). Further during 4-10 May, i.e. after the landfall of cyclone Fani, SST cooling of 1.5-2 °C was observed along and in the periphery of the cyclone track, with maximum cooling of more than 2 °C in the west-central Bay of Bengal (Fig. 2b). There was a slight reduction in the SSH anomalies (Fig. 2d) and the TCHP also reduced drastically along the track of the cyclone Fani, with www.nature.com/scientificreports/ maximum decrease observed in the west central Bay of Bengal, where the TCHP declined to less than 20 kJ cm −2 (Fig. 2f). This shows that there is a two-way interaction. Large SST warming before the cyclone energizes the cyclone and plays a significant role in its long lifespan and intensification. Thereafter, the strong cyclonic winds enhance the ocean mixing and upwelling of cold water from the sub-surface. Along with persistent cloud cover, this leads to a decrease in SST and TCHP.

Discussion and summary
Cyclone Fani formed on 26th April 2019 in the Bay of Bengal. It is the strongest pre-monsoon cyclone to form in the Bay of Bengal after 1994. It maintained its intensity as an extremely severe cyclone for 36 h, which is the longest duration by a pre-monsoon Bay of Bengal cyclone since 1990. An active propagation of MJO through the Indian Seas during 19th-25th April led to anomalous westerlies in the near-equatorial region and increased the cyclonic vorticity over the south Bay of Bengal, providing conditions favourable for cyclogenesis. The enhanced vorticity was supported by a decrease in the vertical wind shear, further enhancing the atmospheric conditions for the genesis of the cyclone. Along with conducive atmospheric conditions, anomalous warm ocean temperatures led to the genesis of the cyclone Fani on 26th April. Earlier studies show that SST plays a significant role in enhancing the accumulated cyclone energy, which is reflected in the long duration and high intensity of cyclones 12,37 . Here we show that favourable ocean subsurface conditions with a warm-core ocean eddy provided a vast reservoir of heat to the cyclone that fuelled it and led to its rapid intensification to an extremely severe cyclone. This shows that along with the SSTs, the ocean subsurface and the presence of ocean eddies also play an essential role in governing the intensity of cyclone.
Pre-monsoon Bay of Bengal cyclones are intensifying in the recent decades due to enhanced large-scale monsoon circulation, which is associated with enhancement of lower-level cyclonic and upper-level anticyclonic anomalies due to local atmospheric warming 3 . Since the Bay of Bengal is landlocked and surrounded by densely populated coastlines, it is necessary to closely monitor the basin for future storms as climate models project continued warming of the Indian Ocean 38 .

Data availability
Cyclone Fani data such as wind speed and track information are obtained from the India Meteorological Department (IMD) Regional Specialised Meteorological Centre (RSMC) preliminary report on Fani cyclone. The data for other cyclones during the period 1990-2018 were obtained from RSMC, IMD website http://www.rsmcn ewdel hi.imd.gov.in. Daily SST data (OISST data) is obtained from the NOAA Physical Sciences Laboratory website https ://psl.noaa.gov/. The wave height data is obtained from the Indian National Centre for Ocean Information Services (https ://incoi s.gov.in). Daily data for sea level anomalies are obtained from the Copernicus Marine Service Altimeter satellite gridded Sea Level Anomalies L4 dataset (https ://resou rces.marin e.coper nicus .eu/) for the period 1993-2019.The cyclone eye temperature data is obtained from the advanced Dvorak technique (ADT) estimate by Meteosat 8 satellite (MSG1), (http://tropi c.ssec.wisc.edu/). The MJO RMM index data is obtained from the Australian Bureau of Meteorology (http://www.bom.gov.au/clima te/mjo). Daily data for relative vorticity (850 hPa), wind (850 hPa and 200 hPa), relative humidity (1000-500 hPa) for the period 1982-2019 is obtained from Era Interim reanalysis dataset website https ://apps.ecmwf .int/datas ets/data/. The OLR data is obtained from NOAA interpolated OLR dataset https ://psl.noaa.gov/. www.nature.com/scientificreports/ Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creat iveco mmons .org/licen ses/by/4.0/.