Impact of Southern Annular Mode on the variability of Heavy Rainfall Events over Kerala during August.

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Sreevidya Ravi, SREEKALA P.P This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4097582/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Kerala has witnessed a surge in heavy rainfall events (HRE) during August in recent years. This study examines the influence of ocean-atmospheric conditions in the Southern Hemisphere on the variability of HRE in Kerala during August. The study finds that the changing ocean-atmospheric conditions in the South Indian Ocean such as uneven sea surface temperature (SST) trends (warming near Madagascar Island and cooling to the south of Madagascar Island, north-south SST gradient), weakening of the Mascarene High, strengthening of the Australian High and associated circulation changes significantly impact the recent trend in HRE over Kerala. A significant negative correlation exists between the April Southern Annular Mode (SAM) index and August HRE. Negative April SAM induces warm SST in the southwest Pacific Ocean (SWPO SST), which persist until August. April SWPO SST is positively associated with the north-south SST gradient in the southwest Indian Ocean in August. The intensification of cyclonic circulation over the southwest Indian Ocean and anticyclonic circulation over the southeast Indian Ocean may be the atmospheric response to April SAM, facilitated through SWPO SST. This cyclonic circulation over the southwest Indian Ocean may enhance divergent winds from the cool eastern Indian Ocean, and increase the moisture transport from the central equatorial Indian Ocean to the Kerala region and causes HRE over Kerala. A positive correlation between April SWPO SST and enhanced regional Hadley circulation over Kerala in August emphasizes this hypothesis. Therefore, negative SAM and warming in the SWPO in April can be considered as precursory factors for HRE occurrence over Kerala in August. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 1 Introduction The study of Heavy Rainfall Events (HRE) holds significant importance because of its potential to trigger flooding and other catastrophic consequences. A comprehensive understanding of the underlying mechanisms, trends, and variability of HRE is essential for enhancing our ability to predict and mitigate these events effectively. The extreme events are amplifying under the increasing global temperature (Allan and Soden, 2008 ) as compared to the increase in the mean rainfall (Pall et al., 2007 ; Kharin et al., 2013 , Myhre et al., 2019 ). The increase in extreme events often follows the Clausius-Clapeyron relation (Lochbihler et al., 2019 ). As air warms by 1°C, the water-holding capacity of air increases by about 7% causing an increase in the water vapor content of the atmosphere. Hence produces more intense precipitation events (Trenberth et al.,2011). While the thermodynamic contribution is robust for developing extreme events (O’Gorman et al., 2015), the dynamic contribution is also crucial in modifying the regional response to such events (Pfahl et al., 2017 ). The formation of extreme events is assumed to be related to teleconnection patterns (Hong et al., 2011 ; Lau et al., 2012, Boers et al., 2019 ). Hence, gaining a better understanding of both local driving forces and remote teleconnections is essential for evaluating and enhancing future predictions of similar events (Chatterjee et al., 2023). Nevertheless, research in India that delves into the connections between HRE and these large-scale climate patterns is relatively limited. Only a few recent studies have explored these relationships (Rathinasamy et al., 2019 ; Sharma et al., 2020 ; Athira et al., 2023 ). Kerala, situated at the southernmost tip of India on the west coast, is often referred to as the "gateway of the monsoon." It is flanked by the Arabian Sea to the west and the Western Ghats to the east. The years 2018 and 2019 witnessed devastating floods in Kerala, igniting a keen interest within the scientific community to delve into the generating mechanisms of these particular events in the region. Viswanadhapalli et al., 2019 identified strong low-level jet in the Arabian Sea, convective instability, and the transport of moisture from both the mid-troposphere and the Bay of Bengal are the primary drivers of flooding. The presence of "Remotely Aligned Intense Tropical Circulations (RAITC)" contributed to an extra supply of moisture to Kerala from the northwest Pacific Ocean (Mohandas et al.,2020), an intense moisture supply from the western flank of the west Pacific subtropical high (WPSH) to Kerala region (Chaluvadi et al., 2021 ), An uncommon moisture transportation from the southern equatorial Indian Ocean to Kerala, influenced by the Subtropical Indian Ocean Dipole (SIOD) (Athira et al., 2021 ), The flooding event was characterized by the presence of an atmospheric river stretching from the Arabian Sea into the Bay of Bengal. (Lyngwa et al.,2021), The intrusion of cold, dry air from the Middle East region interacted with monsoon circulation and created an unstable atmosphere (Kumar et al., 2020 ), The substantial moisture convergence over Kerala during the flood event was linked to westward-propagating barotropic Rossby waves (Mukhopadhyay et al., 2021 ), the dynamical impact of the west Pacific cyclones aids in the development of HRE over Kerala (Musaid et al., 2023 ). Additionally, several studies highlighted the role of cloud microphysics in developing floods ( Chakraborty et al., 2021 ; Thomas et al., 2021 ; Vijaykumar et al., 2021 ), considered the climate change perspective (Hunt and Menon 2020 ), and explored the impact of reservoir storage on the flooding (Mishra et al., 2018 ; Ramasamy et al., 2019 ; Sudheer et al., 2019 ). While existing studies have focused on specific events, a comprehensive analysis regarding the development of HRE over Kerala is still lacking. The Indian monsoon system is a part of general atmospheric circulation, the monsoon current originates from the southern hemisphere as southeasterly currents become south-westerly after crossing the equator, hence climate variability in the southern hemisphere can modulate the ISMR. The dominant mode of climate variability in the extratropical Southern Hemisphere is the Southern Annular Mode (SAM)(Rogers and van Loon, 1982 ; Thompson & Wallace, 2000 , Pohl et al.,2012). In the positive phase of the SAM, a prominent feature is the presence of a strengthened high-pressure belt located around 40°S. Which causes the belt of strong westerly winds in higher latitudes to contract towards Antarctica. In contrast, during a negative SAM phase, the high-pressure belt weakens at 40°S, leading to the expansion of the belt of strong westerly winds towards the equator. The relationship between SAM and the Indian monsoon has been demonstrated in various studies (Viswambharan et al., 2013; Prabhu et al., 2017; Dou, 2017; Pal et al., 2017 ; Gnanaseelan et al., 2021; Dwivedi et al., 2022 ). Additionally, the El Niño-Southern Oscillation (ENSO) is a notable phenomenon that significantly influences Indian Summer Monsoon Rainfall. Another influential factor in the Indian Summer Monsoon Rainfall from the Southern Hemisphere is the Mascarene High (Krishnamurthy and Bhalme, 1976). The present study seeks to investigate the impact of the southern hemisphere oceanic and atmospheric conditions on the development of the HRE over Kerala during August. The primary aim of this study is to investigate the potential impacts of Southern Hemisphere pre-monsoon ocean-atmospheric conditions on the variability of Heavy Rainfall Events (HRE) in the subsequent August, as well as to elucidate the associated physical mechanisms. The paper is structured as follows: Section 2 provides a comprehensive overview of the data and methodology employed. Section 3 explores the analysis of HRE trends and variability over Kerala, the teleconnections of August HRE over Kerala, and the physical mechanisms that explain how the "coupled oceanic-atmospheric bridge" process extends the SAM signal and transmits its influence to Kerala in August. Section 4 presents the summary and conclusions of this study. 2.1 Data Gridded daily rainfall data from 1981 to 2020 during the summer monsoon season, with a resolution of 0.25° latitude and 0.25° longitude, were obtained from the Indian Meteorological Department (IMD). Derived from measurements collected by 6955 rain gauge stations across India (6.5°N-37.5°N; 66.5°E-101.5°E), the dataset exhibits improved spatial coverage compared to earlier versions (Pai et al., 2014 ), employing the Inverse Distance Weighted scheme for spatial interpolation (Shepard et al., 1968). The HadISST from the Met Office Hadley Centre, with a spatial resolution of 1° × 1° latitude–longitude grid is used for the analysis (HadISST; Rayner et al., 2003 ). The daily SST anomalies were obtained from NOAA OISST data. The dataset for atmospheric pressure, wind data, and vertically integrated moisture transport (VIMT) was obtained from ERA5, provided by the Copernicus Climate Change Service. The ERA-5 is the fifth-generation reanalysis developed at the ECMWF (European Centre for Medium-Range Weather Forecasts). It provides hourly estimates for a large amount of atmospheric and land surface variables. The information from observations is extracted from many satellites or conventional instruments (Hersbachet et al., 2020). The atmospheric component is interpolated to 37 pressure levels from the surface up to 1 Pa. The study employs NCEP/NCAR monthly wind data for the analysis. This study utilizes the Marshal SAM index, which is the station-based Southern Annular Mode (SAM) index. It is derived from the zonal pressure difference between the latitudes of 40° S and 65° S. 2.2 METHODS The Peak Over Threshold (POT) method is a statistical technique used to identify the HRE from time series data. The POT identifies extreme events by focusing on all data points that exceed a predefined threshold. There are two types of POT methods, absolute threshold (a fixed value) or a varying threshold based on percentiles. The varying threshold is suitable for regions with heterogeneous characteristics, in rainfall, where extreme events can vary significantly across geographical locations. In this study, a HRE is defined as any day when the rainfall exceeds the 95th percentile threshold. This calculation is performed individually for each grid point. To determine this threshold, the 95th percentile value for each grid was computed using a dataset spanning 40 years specific to that grid location. The study utilized linear trend tests for conducting trend analysis, employing the non-parametric Mann-Kendall trend tests (Mann et al., 1945; Kendall et al.,1948) to evaluate the statistical significance of these trends. The daily wind stream function was calculated using the following equation, $$u=\frac{\partial {\Psi }}{\partial y}, v=-\frac{\partial {\Psi }}{\partial x}$$ Where u is a zonal wind vector, v is the meridional wind vector ψ is the stream function. The Vertically Integrated Moisture Transport (VIMT) is used to describe the total amount of moisture being transported through the atmosphere in a vertical column. VIMT is often calculated by integrating the horizontal moisture transport from the surface to a pressure level, of up to 200 hPa. $$VIMT=\frac{1}{g}{\int }_{p200}^{p1000}qVdp$$ Where q is the specific humidity, V is the wind vector, P is the pressure, and g is the acceleration due to gravity. The composites in this study are constructed to examine atmospheric conditions during HRE in Kerala. Kendall's tau rank correlation analysis is employed to uncover the connection between HRE in Kerala and the presence of favorable atmospheric conditions. This statistical method helps to determine whether there is a significant association between the occurrence of HREs and specific atmospheric variables. 3 Results 3.1 Trend and variability of HRE over Kerala The trend and variability of HRE over Kerala (74 0 E,78 0 E-8 0 N,12 0 N) during August from 1981 to 2020 is discussed here. A significant increasing trend in HRE is observed over Kerala, particularly in southern Kerala and the Western Ghats regions (Fig. 1 a). These findings are consistent with the observations made by Subrahmanyam et al., 2023 , indicating an increase in HRE occurrences over the core monsoon zone in August from 1901 to 2022. The trend in mean rainfall and contribution from HRE also showed an increase in August over Kerala (Fig. 1 b, 1 c). The frequent occurrences of HRE can be attributed to the increase in mean rainfall over Kerala. An increasing trend in the mean rainfall over Kerala is also reported by Revadekar et al., ( 2018 ); Guhathakurta et al., ( 2020 ). The reasons behind the occurrence of HRE over Kerala during August need to be explored for the timely forecast of such events in the future. The inter-annual variability of HRE during August over the 40 years is depicted in Fig. 1 d. During the period from 1981 to 1999, the frequency of HRE exhibited negative values, suggesting reduced HRE activity. However, from the year 2000 onwards, there is a noticeable positive trend in the frequency of HRE. The increases observed in recent years are likely contributing to the pronounced positive trend in the frequency of HRE. Additionally, there is a noticeable shift in climate patterns around 2000, characterized by negative values before 2000 and positive values thereafter. Several studies have argued the retrieval of ISMR after 2002 (Roxy et al., 2017; Goswami et al., 2023, etc.). This study underscores the climate shift in occurrences of HRE after 2000 during August over Kerala. 3.2 The association of southern hemisphere ocean-atmospheric conditions and HRE over Kerala during August To explore the influence of Southern Hemisphere subtropical ocean- atmospheric conditions on the variability of the HRE over Kerala. First examined the trends of sea surface temperature (SST), mean sea level pressure (MSLP), upper-level wind, and lower-level wind in the Southern Hemisphere during August (2001–2020), as illustrated in Fig. 2 a- 2 b. The SST exhibits a positive trend in the northern Arabian Sea, the southern Indian Ocean near Madagascar island, as well as in the southwest Pacific Ocean and the North Pacific Ocean, forming a 'horse-shoe pattern of SST trend.' A cooling trend is observed in the south of Madagascar island in the southwest Indian Ocean and the central Pacific Ocean (Fig. 2 a). A decreasing trend in MSLP near Madagascar Island and an increasing trend in MSLP near Australia, with an alternative 850hPa “cyclonic” and “anticyclonic” wind trend in the respective locations, are observed from the analysis as shown in Fig. 2 b. The upper-level wind pattern shows alternating "cyclonic" and "anticyclonic" patterns from Madagascar to the east of Australia through the South Indian Ocean (Fig. 2 a), indicating the trend in the Rossby wave in the subtropical jet stream. A strong upper-level easterly wind trend is observed over the warming region of the southwest Indian Ocean. The association of these changes in the Southern Ocean with the HRE over Kerala is the major objective of the present study. The correlation of the frequency of HRE over Kerala during August with different ocean-atmospheric variables is analyzed for this purpose. The influence of these changes in the Southern Hemisphere on the occurrence of HRE over Kerala is the major objective of the present study. The correlation of the frequency of HRE over Kerala during August with different Ocean-Atmospheric variables is analyzed for this purpose. Since there is a climatic shift around 2000, we have further analyzed the comparison between the early (1981–2000) and recent (2001–2020) epochs. The spatial correlation pattern of SST anomalies and frequency of HRE in Kerala from 1981 to 2000 is illustrated in Fig. 3 a. A significant positive correlation is observed with SST anomalies in the western Indian Ocean region (20°S to 20°N), while a negative relation is noted with SST in the South Indian Ocean near 40°S, especially over the Mascarene high region. In Fig. 3 b, depicting the correlation between SST anomalies and August HRE in Kerala from 2001 to 2020, it is observed that August HRE is linked to two distinct SST dipole patterns in the southern Pacific Ocean and the Indian Ocean. This involves cooling in the eastern equatorial Pacific Ocean, warming in the southwest Pacific Ocean, and simultaneous cooling in the eastern equatorial Indian Ocean and warming in the western Indian Ocean. Furthermore, a negative correlation exists between southwest Indian Ocean SST near 40°S and August HRE. Comparing the two epochs, distinct SST correlation patterns emerge. In the first epoch, HRE is solely linked to the Indian Ocean SST. However, while the South Pacific Ocean's influence on August HRE development over Kerala has grown in the second epoch, the relationship with the Indian Ocean remains significant. In the second epoch, the HRE correlation with SST is positive near Madagascar island, contrasting with the negative correlation in the first epoch. The correlation pattern of SST observed in Fig. 3 b in the recent epoch appears to be similar to the observed trend of SST pattern, which emphasizes the influence of SST trend on the trend in HRE over Kerala. It is important to understand the moisture source for the occurrence of HRE. So, we have correlated the HRE frequency with vertically integrated moisture transport (VIMT). In the second epoch, a notable correlation between VIMT and August HRE in the North Indian Ocean is evident in Fig. 3 b. During this period, the connection between moisture transport from the eastern equatorial Indian Ocean to the Kerala region has strengthened. In contrast, the first epoch lacks a significant relationship between HRE and moisture transport in the Indian Ocean region (Fig. 3 a). The surge in HRE frequency over Kerala became apparent only after 2000, potentially explaining the increased correlation between HRE and VIMT in the second epoch. Since the HRE is linked to negative SST anomalies over the eastern Indian Ocean and positive SST anomalies in the western Indian Ocean, the observed relationship between moisture transport and the HRE is consistent with these associations. The spatial correlation pattern of MSLP and the August HRE are illustrated in Fig. 3 c- 3 d. In the second epoch, a negative correlation between the HRE and the MSLP over the entire western Indian Ocean is observed (Fig. 3 d), while in the previous epoch, the negative correlation was predominantly concentrated in the southwestern Indian Ocean. A significant positive correlation pattern is observed in the eastern Indian Ocean and Australian region. Hence a dipole pattern of the MSLP i.e., low-pressure anomaly over the western Indian Ocean and high-pressure anomaly over the eastern Indian Ocean is conducive for the occurrence of the HRE over Kerala in the recent epoch. The relation between the August HRE over Kerala and the Mascarene High is inversely proportional in both periods. The relation between the Australian high with the HRE over Kerala is increasing in the second epoch as compared to the first epoch. The strengthening of the relationship between the August HRE and the eastern Pacific Ocean in the second epoch is evident. Additionally, a negative correlation with the southwest Pacific Ocean is also noticeable. The positive MSLP anomalies in the tropical eastern Pacific and negative MSLP anomalies in the middle latitudes of the southwest Pacific Ocean are favourable for the occurrence of HRE over Kerala. This correlation pattern resembles a dipole in the north-south (meridional) direction in the Pacific Ocean. Hence, the strengthening of La Niña, coupled with the low pressure near Madagascar island, may contribute to an increase in the August HRE over Kerala. Additionally, the MSLP correlation pattern reflects two distinct dipoles in the South Pacific and the Indian Ocean regions, which closely resemble the SST correlation patterns observed in the second epochs. The correlation pattern of MSLP in the Southern Hemisphere subtropics appears to be the same as the observed trend in MSLP. The correlation between 850hPa winds and the HRE over Kerala during August is illustrated in Fig. 3 c- 3 d. In the second epoch, the HRE strongly correlates with the south-westerly winds over the northern Indian Ocean (Fig. 3 d). The south-westerly winds appear from the eastern Indian Ocean and the equatorial Indian Ocean, indicating an observed eastward shift in the cross-equatorial flow. A previous study by Chaluvadi et al., ( 2021 ) reported that during the 2018 Kerala flood, an eastward shift in the cross-equatorial flow was observed. Furthermore, the relation between the HRE and the cyclonic circulations in the South Pacific and southwest Indian Ocean has increased during the recent epoch. In contrast, during the first epoch, the relation of the HRE with the cyclonic circulations in the southern Indian Ocean was weak and absent in the southern Pacific Ocean (Fig. 3 c). From the trend analysis of lower-level wind, cyclonic circulation is increasing over the southwest Indian Ocean and southwest Pacific Ocean. Hence, the positive relation of HRE with these cyclonic circulations, and the increasing trend of these circulations, may cause the increase in HRE activity. The atmospheric conditions conducive to the HRE in recent epochs may encompass factors such as the weakening of Mascarene High, the strengthening of the Australian High, and the intensification of the lower-level cyclonic circulations in the middle latitudes of the southern hemisphere, warming of Southwest Pacific Ocean. It is worth noting that numerous studies have indicated that the recent period of the global warming hiatus (GWH) is characterized by the warming of the Indian Ocean (Zhao et al., 2018 ), and the weakening of the Mascarene high (P JV et al., 2020). Therefore, the factors triggering the occurrence of the HRE over Kerala can be associated with global climate change, which, in turn, modifies atmospheric conditions in the southern hemisphere, potentially creating conditions favorable for the occurrence of the HRE over Kerala. To further explore the dynamics of the HRE, we examine daily composite maps of SST, wind, VIMT (Vertically Integrated Moisture Transport), and upper-level stream function during the time of occurrence of HRE over Kerala. The composites are based on twenty events of heavy rainfalls during August within the last two decades (2001–2020) are depicted in Fig. 4 a- 4 b. Warming is observed in the southwest Pacific Ocean, the central Indian Ocean, and the vicinity of the Madagascar island region, with cooling near the 40°S regions of the southern Indian Ocean during the time of the HRE. This SST pattern may contribute to the weakening of the Mascarene high and facilitate the intensification of lower-level cyclonic circulation, promoting the occurrence of HRE. An enhanced moisture convergence over Kerala is evident during the time of events. The SST and VIMT patterns closely resemble the correlation and trend patterns, highlighting the potential for an increased occurrence of HRE over Kerala during August. While examining 200 hpa stream function anomalies in the middle latitudes of the south Indian Ocean, positive, negative, and positive patterns are observed (Fig. 4 b). These patterns may be attributed to the waviness within the southern hemisphere subtropical jets over the Indian Ocean. Extension of a positive stream function near the southern tip of India from the southern hemisphere is evident. Conversely, negative stream function anomalies are observed in the north Indian regions during these events. This indicates the presence of low-pressure systems in the monsoon trough region, likely advected from the Bay of Bengal. Several studies have reported the presence of LPS in the Bay of Bengal during flood events (Kumar et al., 2020 ; Athira et al., 2021 ; Chaluvadi et al., 2021 ). The lower-level wind patterns in the middle latitudes of the South Indian Ocean reveal a cyclonic, anticyclonic, and cyclonic pattern, aligning with the observed pattern in stream functions (Fig. 4 b) and trend in 850 hpa wind. Consequently, the anticyclonic circulation in the southeastern Indian Ocean and the cyclonic circulation in the southwestern Indian Ocean can favor wind convergence over Kerala. Additionally, the negative stream function in north India and the positive stream function in the southern tip of India may channel the Low-Level Jet toward Kerala by shifting it southward from its normal position. This, in turn, leads to increased precipitation in the Kerala region. Based on this analysis, it can be inferred that the Southern Hemisphere subtropical circulations have a crucial role in modulating the path and position of LLJ over the Indian subcontinent. 3.3 Relation between April SAM and August HRE teleconnection The influence of Southern Hemisphere atmospheric circulation on the variability of the HRE in recent times is evident. Since the Southern Annular Mode (SAM) is the dominant mode of climate variability in the Southern Hemisphere, here we examine whether SAM influences the occurrence of HRE over Kerala during August. To explore the influence of the SAM on the HRE occurrence over Kerala in August, we correlate the monthly SAM indices with the frequency of HRE from 1981–2020 period. This study reveals that the April SAM exhibits a negative relationship with the frequency of HRE over Kerala during the subsequent August, with a correlation coefficient of -0.228 and a significant confidence level of 95% (Fig. 5 b). The relationship of the August HRE with the SAM index in other months is generally insignificant, except for January, which exhibits a correlation coefficient of 0.19. Hence, further analysis will focus on the relationship between the April SAM and the frequency of HRE over Kerala during subsequent August. The spatial correlation map of the April SAM index and HRE frequency over Kerala for the study period is shown in Fig. 5 a. It is observed that a significant negative correlation exists between the April SAM and the frequency of HRE over Kerala in August. Previous studies, such as Pal et al., ( 2017 ), revealed that the rainfall anomalies of August are not linked to SAM. Instead, they observed an out-of-phase relationship between the SAM index of June and July rainfall. However, Viswambaran et al., (2013) found that August rainfall in India has an out-of-phase relationship with the June SAM index. These earlier studies primarily explore the association between mean rainfall and SAM, consistently highlighting a negative correlation between rainfall in India and the SAM, particularly along the west coast. Our study specifically delves into the relationship between the SAM and the occurrence of the HRE over Kerala during August. The focus on the HRE in this study may have led to different observations compared to other studies, although the out-of-phase relationship with the SAM and the rainfall remains consistent, even in the context of the HRE. The time series of standardized values of the April SAM and the frequency of HRE in August are illustrated in Fig. 5 b, indicating the out-of-phase relationship between the April SAM and the August HRE increased in the recent two decades (after the year 2000). As mentioned earlier, the study observed an increase in the occurrence of the HRE over Kerala after 2000. This suggests that the influence of the April SAM on the HRE has become more significant in the recent two decades. Therefore, the subsequent analysis will be focused on the recent two decades (2001–2020). In conclusion, this study reveals a significant negative correlation between the April SAM index and the frequency of HRE over Kerala in August. Additionally, it underscores that the influence of the April SAM on the HRE has grown more prominent in the recent two decades. 3.4 Mechanism behind the lag correlation of SAM (April) and HRE (August) In this section, we explore how does the preceding April SAM continue to impact the occurrence of the HRE in Kerala during the following August. Here we examine the mechanisms for SAM’s temporal persistence and its influence on regional climate patterns. It is widely acknowledged that atmospheric signals like SAM have limited persistence. Zhang et al., (2020) observed that the SAM exhibits persistence across different timescales, with its primary variations occurring on sub-seasonal and cross-seasonal scales. They also emphasized the connection between cross-seasonal SAM variability and extratropical air-sea interactions as well as extratropical SST. The SST anomalies generated by the SAM can effectively retain the SAM signal, preserving it over an extended period and subsequently impacting the regional climate in the ensuing months(Nan and Li 2003 ; Nan et al., 2009 ; Wu et al., 2009 , 2015 ; Zheng and Li 2012 ; Liu et al., 2016 ; Prabhu et al., 2016 ; Dou et al., 2017 ). The function of the "ocean bridge" will be considered to comprehend the mechanism that causes the April SAM to affect the HRE in the following August. In the subsequent analysis, our focus will be on identifying the specific SST anomalies generated by the April SAM. These anomalies act as the critical components of the "ocean bridge" mechanism, facilitating the influence of the April SAM on the modification of HRE over Kerala in August. The spatial correlation pattern of SST anomalies in April and August with the frequency of HRE in August is depicted in Fig. 6 a- 6 b. In April, August HRE is related to positive anomalies in the southwestern Pacific Ocean and negative anomalies of SST in the tropical eastern Pacific and the equatorial eastern Indian Ocean. In August, HRE showed a negative relationship with the SST over tropical eastern Pacific Ocean. The positive correlation with SST anomalies in the southwest Pacific Ocean remains consistent. Simultaneously, there is a negative association with the SST anomalies in the eastern Indian Ocean region and a positive relationship with the SST anomalies in the west Indian Ocean. Consequently, the development of La Niña from spring to summer in the Pacific Ocean, the progressive cooling in the eastern equatorial Indian Ocean from April to August, and the persistent warming in the southwest Pacific Ocean from April to August collectively increase the likelihood of HRE occurring over Kerala in August. The spatial correlation patterns of SST for April and August with respect to the April SAM are presented in Fig. 6 c- 6 d. The spatial correlation pattern of SST with the April SAM is precisely opposite to the pattern observed in the spatial correlation between the SST and the August HRE. This out-of-phase relationship between correlation patterns aligns with the negative relationship between the August HRE and the April SAM. In April, in the South Pacific Ocean, characterized by a negative relation with SST in the southwest Pacific Ocean and a positive relation with SST in the eastern Pacific Ocean (Fig. 6 c). In August, the negative correlation with southwest Pacific SST persists and extends toward the western equatorial Pacific Ocean (Fig. 6 d). From this analysis, it can be inferred that the negative April SAM signals lead to the development of warm SST anomalies over the southwest Pacific Ocean (SWPO, 25 0 S-40 0 S,177 0 W-150 0 W), this region is marked in the box (Fig. 6 a- 6 b). The positive SST anomalies that developed due to the negative SAM in April over the SWPO persist and extend toward the equator as the season progresses. This anomalous SST pattern can influence changes in the overlying atmospheric circulations, consequently increasing the occurrence of the HRE over Kerala in August. Therefore, it can be deduced that anomalous SST in the southwest Pacific Ocean (SWPOSST) plays a crucial role in establishing the connection between the April SAM and the subsequent August HRE. Thus, the SWPOSST serves as an oceanic bridge linking the April SAM to the ensuing August HRE over Kerala. The SAM can lead to SST anomalies in the southern hemisphere that persist into subsequent seasons. These SST anomalies play a regulatory role in the meridional circulation and large-scale precipitation patterns by influencing the meridional gradient of SST (Zheng et al., 2015 ; Liu et al., 2021 ). Examining further, it is important to consider how the April SAM-generated SST anomalies in the SWPO can affect SST anomalies in the following August. The spatial correlation pattern of SWPO SST anomalies in April with August SST (Fig. 7 a) closely resembles the correlation pattern between the August HRE and August SST anomalies (Fig. 6 b). The April SWPOSST region shows a negative association with August SST anomalies near the equatorial eastern Pacific Ocean and the southwest Indian Ocean to the south of Madagascar island (Fig. 7 a). The cool SST anomalies in the southwest Indian Ocean in August may play a crucial role in enhancing the lower-level cyclonic circulation. From the analysis, it can be inferred that the positive SST anomalies in SWPO developed by negative SAM in April can potentially modify the SST pattern in August over the Indian Ocean and Pacific Ocean regions. To investigate the influence of the April SWPO SST on the regional Hadley circulation over the Indian Ocean region, which contributes to the modification of the August HRE occurrences over Kerala, we conducted a correlation analysis between the SWPO SST and the Hadley circulation. Figure 7 b illustrates the correlation pattern of the regional Hadley cells with the August HRE. The August HRE is associated with ascending motion near 10°N, a circulation in the upper tropospheric levels, and the intrusion of southerlies from the upper troposphere to the middle troposphere. The upper-level southerlies could be attributed to the influence of circulations in the Southern Ocean or the subtropical jets of the Southern Hemisphere. Figure 7 c illustrates the correlation pattern of the regional Hadley circulation over the Indian Ocean with the HRE over Kerala in August, revealing a strong ascending motion from the equator to the Kerala region. Notably, the correlation pattern of the SWPO SST in April with regional Hadley circulation closely resembles the pattern observed in the correlation of August HRE with regional Hadley circulation, featuring an ascending motion from the equator to around 10°N. Consequently, it can be inferred that warm SST anomalies in the SWPO during April have the potential to influence the regional Hadley circulation over the Indian region. 4 Summary and conclusions The present study explored the influence of southern hemisphere ocean-atmospheric conditions on the occurrence of heavy rainfall events over Kerala in August. The HRE during August shows a significant increasing trend. A surge in the formation of the HRE over Kerala has been observed in the recent two decades (2001–2020). The warming of southwest Indian Ocean and associated weakening of Mascarene High and strengthening of Australian High are found to be positively correlated with the frequency of HRE. Southern Hemisphere subtropical circulations have a crucial role in modulating the path and position of LLJ over the Indian subcontinent. An intensification of anticyclonic circulation over the southeast Indian Ocean and the cyclonic circulation over the southwest Indian Ocean is observed in the recent decades. These changes in the southern midlatitude circulation shows a significant impact on the occurrence of HRE. In the early epoch, HRE is solely linked to the warming of west Indian Ocean. In the recent decades, HRE is correlated with the east (cool)-west (warm) SST dipole pattern in the Equatorial Indian Ocean and warming of Southwest Pacific Ocean and cooling of eastern Pacific Ocean. A possible mechanism by which the southern hemispheric circulation influences the HRE over Kerala can be through the enhancement of easterly wind from the cool eastern Indian Ocean. This wind diverge in the central Indian Ocean and one part is flowing towards Kerala as south westerly wind and the other part as towards the warm southwest Indian Ocean. The cyclonic circulation over the southwest Indian Ocean may have the potential to enhance the divergent wind from the Eastern Indian Ocean which increases the moisture transport from the central equatorial Indian Ocean to the Kerala region and leads to a spell of heavy rainfall activity. Further analysis in the present study revealed an out-of-phase relationship between the April SAM index and August HRE. It is observed that the negative SAM is related with the warming over the southwest Pacific Ocean (25°S-40°S, 177°W-150°W) in April (SWPO SST) which persisted up to the subsequent August. This April SWPO SST is correlated with the north (warming near Madagascar island)-south (cooling to the south of Madagascar island) SST gradient over the southern Indian Ocean and cooling in the eastern Pacific Ocean in August. The above-mentioned north-south SST gradient can lead to cyclonic circulation in the southwest Indian Ocean. These changes in the middle latitude circulation in the southern Indian Ocean modify the regional Hadley circulation and place the ascending branch of the cell over Kerala. Hence, the SWPO SST during April can be considered as an “ocean bridge” conveying the April SAM signals to the subsequent months The intensification of cyclonic circulation (weakening of the Mascarene High) to the southwest (at 40°S) of the Indian Ocean plays a crucial role in the occurrence of HRE over Kerala. The periodicity of these occurrences may hinge on the undulation of jet streams or other atmospheric wave activities. Notably, the SAM demonstrates an intrinsic timescale of 10–30 days (Zhang et al., 2023 ). The negative SAM-induced SWPO SST anomalies can impact subtropical jets, leading to undulations in the jet stream and variations in the strength and position of middle-latitude high-pressure systems. Occasionally, other atmospheric phenomena may also influence these patterns. Consequently, further analysis is essential to pinpoint the mechanism connecting April SAM to August HRE over Kerala. Despite this, the influence of Southern Hemisphere circulation on the variability of HRE over Kerala is evident. The negative SAM and warming in the SWPO in April can be considered precursory factors for the occurrence of HRE over Kerala in August. Integrating these factors into atmospheric models has the potential to enhance the predictability of these events. Declarations Author contributions Sreekala P P: Conceptualization, Supervision Sreevidya Ravi: Visualization, Drafting the manuscript. Acknowledgment The authors would like to acknowledge the Department of Atmospheric Sciences, Cochin University of Science and Technology, India for providing the facilities and financial support. The authors are grateful to the IMD, NOAA, ECMWF, NCEP/NCAR, and The Met Office Hadley Centre for providing the data. The first author also appreciates the valuable assistance received from P S Suthinkumar in Python programming. Competing interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Data availability The rainfall data were obtained https://www.imdpune.gov.in/cmpg/Griddata/Rainfall_25_NetCDF.html , the SST data at https://www.imdpune.gov.in/cmpg/Griddata/Rainfall_25_NetCDF.html the wind MSLP,VIMT data at https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-pressure-levels?tab=overview and https://psl.noaa.gov/data/gridded/data.ncep.reanalysis.html the SAM index were obtained at https://climatedataguide.ucar.edu/climate-data/marshall-southern-annular-mode-sam-index-station-based. References Allan, R. P., & Soden, B. J. (2008). Atmospheric warming and the amplification of precipitation extremes. Science, 321(5895), 1481-1484. Athira, K., Singh, S., & Abebe, A. (2023). 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Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4097582","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":283408362,"identity":"2e21ba09-fda4-4ffc-a021-f76a6853992e","order_by":0,"name":"Sreevidya Ravi","email":"","orcid":"","institution":"Cochin University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Sreevidya","middleName":"","lastName":"Ravi","suffix":""},{"id":283408363,"identity":"21696e44-7dab-435e-8146-8c1ddb5f390b","order_by":1,"name":"SREEKALA P.P","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+UlEQVRIiWNgGAWjYJACxgYGCyizAoiZmRuI0SIBYR04A9LCSIqWg21QPj4gP/vwwYczaiTk+WekP/z8cV5tNH87UMuPim04tRicS0s23HBMwnDGjRxjiYPbjufOOMzYwNhz5jZuLTw8ZpIP2CQYN0jkMAC1HMttAGphZmzDrUW+h//7zwf/JOw3SKQ//nFwzrHc+YS0MJzhYWPc2CaRuEEiwUziYENN7gZCWgzOsBlLzuyTSJ5x5o2ZxZljB3I3ArUcxOcX+R7mhx97vtnY9renP75RUVOXO+/84YMPflTgcRgaOAwmDxCtHgjqSFE8CkbBKBgFIwQAAMgIX06Qq3ETAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0003-0221-7417","institution":"S.V.University, Tirupati","correspondingAuthor":true,"prefix":"","firstName":"SREEKALA","middleName":"","lastName":"P.P","suffix":""}],"badges":[],"createdAt":"2024-03-14 05:55:32","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4097582/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4097582/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":53627379,"identity":"8ac17c6b-eba5-41ae-97fe-f369b7ce06ff","added_by":"auto","created_at":"2024-03-28 09:09:32","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":86946,"visible":true,"origin":"","legend":"\u003cp\u003eThe seasonal trend and monthly trends of frequency of HRE, the ratio of contribution of HRE to the mean rainfall, and mean rainfall over Kerala for the period 1981–2020. The trend in frequency of HRE is a) in August, and.b) The ratio of the contribution of HRE to the mean rainfall trend in August c) The mean rainfall trend is in August,. The hatching indicates trend values significant at 95% confidence level. The IMD rainfall data is used for the analysis. d) Standardised frequency of HRE during August for the period 1981–2020. Red line indicates the linear trend of the frequency of August HRE.\u003c/p\u003e","description":"","filename":"image1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4097582/v1/bd8faa17c50012959922e90b.jpeg"},{"id":53627381,"identity":"65e66ded-6aa6-4f73-b81b-ddcfe9963d12","added_by":"auto","created_at":"2024-03-28 09:09:32","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":348452,"visible":true,"origin":"","legend":"\u003cp\u003eThe trend analysis of oceanic- atmospheric components from 2001-2020.a) 200 hpa wind overlayed on SST (degC), b) 850 hpa wind overlayed on MSLP. The shade regions hatching indicates trend values significant at 95% confidence level.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-4097582/v1/6a444b35b823f0851583ec0f.png"},{"id":53627384,"identity":"9e579f81-2046-41c4-8477-67920e8acb7f","added_by":"auto","created_at":"2024-03-28 09:09:32","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1716848,"visible":true,"origin":"","legend":"\u003cp\u003eEpochal variability of atmospheric condition related to August HRE. The data was divided into two time periods 1981-2000 and 2001-2020. The simultaneous correlation map of HRE with SST (shade) and VIMT (vector) a) first epoch b) second epoch. The simultaneous correlation map of HRE with SLP (shade) and Wind (vector) c) first epoch d) SLP and wind (vector) second epoch.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-4097582/v1/bca4f37d959edb07813d1fde.png"},{"id":53628049,"identity":"f60b1f25-80d5-4b7b-bcac-4ffe74c76a0f","added_by":"auto","created_at":"2024-03-28 09:17:32","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":823773,"visible":true,"origin":"","legend":"\u003cp\u003eThe composite anomalies of oceanic-atmospheric component during HRE from 2000 to 2020 c) VIMT anomalies (Kg/m/sec) overlayed on SST anomaly (degC). d) 850 hpa wind anomalies in m/s overlayed on 200 hpa stream function anomaly (10\u003csup\u003e6 \u003c/sup\u003em\u003csup\u003e2\u003c/sup\u003e/s).\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-4097582/v1/d7cbce43562d7a7ee71eba3b.png"},{"id":53627383,"identity":"81bc5132-8ac2-442a-8e88-d000429a8201","added_by":"auto","created_at":"2024-03-28 09:09:32","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":65512,"visible":true,"origin":"","legend":"\u003cp\u003ea) Correlation of August HRE with different month SAM index. b) spatial correlation of April SAM with August 1981-2020. Significant values of correlation coefficients at the 95% confidence level are hatched in black. c) Standardized HRE (Blue bar) and April SAM (Red line).\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-4097582/v1/1953100dcf0d31958e288687.png"},{"id":53627380,"identity":"acc36ad6-675a-4dc3-9661-608d2d054b32","added_by":"auto","created_at":"2024-03-28 09:09:32","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":812766,"visible":true,"origin":"","legend":"\u003cp\u003eThe correlation maps of a) August HRE and April SST\u003cstrong\u003e \u003c/strong\u003eb) August HRE and August SST c) April SAM with April SST d) April SAM with August SST. The hatching indicates correlation coefficients significant at 95% confidence level.\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-4097582/v1/59025778782f0925474ba0d9.png"},{"id":53628050,"identity":"2b1b5d54-96ff-4eb1-beaa-666f523edcb3","added_by":"auto","created_at":"2024-03-28 09:17:32","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":392184,"visible":true,"origin":"","legend":"\u003cp\u003e(a) The correlation of SWPO SST in April with SST in subsequent August. The hatching indicates correlation coefficients significant at a 95% confidence level. The SST averaged over the SWPO box (Fig 5a-4b) is used for the analysis. The HadISST used for the analysis. . The correlation pattern of regional Hadley circulation b) with August HRE c) with April SST. The wind is averaged over Kerala longitude (74\u003csup\u003e0\u003c/sup\u003eE -78\u003csup\u003e0\u003c/sup\u003eE). The SST averaged over the SWPO box (25\u003csup\u003e0\u003c/sup\u003eS-40\u003csup\u003e0\u003c/sup\u003eS,177\u003csup\u003e0\u003c/sup\u003eW-150\u003csup\u003e0\u003c/sup\u003eW) is used for the analysis.\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-4097582/v1/e9fde48f4c68e3348673af0d.png"},{"id":57235874,"identity":"13b864cc-55c7-4468-8cb4-adf09c9ed53f","added_by":"auto","created_at":"2024-05-28 01:36:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4173745,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4097582/v1/bf603c76-990b-474d-b169-fab0136c243e.pdf"}],"financialInterests":"","formattedTitle":"Impact of Southern Annular Mode on the variability of Heavy Rainfall Events over Kerala during August.","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eThe study of Heavy Rainfall Events (HRE) holds significant importance because of its potential to trigger flooding and other catastrophic consequences. A comprehensive understanding of the underlying mechanisms, trends, and variability of HRE is essential for enhancing our ability to predict and mitigate these events effectively. The extreme events are amplifying under the increasing global temperature (Allan and Soden, \u003cspan class=\"CitationRef\"\u003e2008\u003c/span\u003e) as compared to the increase in the mean rainfall (Pall et al., \u003cspan class=\"CitationRef\"\u003e2007\u003c/span\u003e; Kharin et al., \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e, Myhre et al., \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e). The increase in extreme events often follows the Clausius-Clapeyron relation (Lochbihler et al., \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e). As air warms by 1\u0026deg;C, the water-holding capacity of air increases by about 7% causing an increase in the water vapor content of the atmosphere. Hence produces more intense precipitation events (Trenberth et al.,2011). While the thermodynamic contribution is robust for developing extreme events (O\u0026rsquo;Gorman et al., 2015), the dynamic contribution is also crucial in modifying the regional response to such events (Pfahl et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e). The formation of extreme events is assumed to be related to teleconnection patterns (Hong et al., \u003cspan class=\"CitationRef\"\u003e2011\u003c/span\u003e; Lau et al., 2012, Boers et al., \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e). Hence, gaining a better understanding of both local driving forces and remote teleconnections is essential for evaluating and enhancing future predictions of similar events (Chatterjee et al., 2023). Nevertheless, research in India that delves into the connections between HRE and these large-scale climate patterns is relatively limited. Only a few recent studies have explored these relationships (Rathinasamy et al., \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e; Sharma et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e; Athira et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eKerala, situated at the southernmost tip of India on the west coast, is often referred to as the \"gateway of the monsoon.\" It is flanked by the Arabian Sea to the west and the Western Ghats to the east. The years 2018 and 2019 witnessed devastating floods in Kerala, igniting a keen interest within the scientific community to delve into the generating mechanisms of these particular events in the region. Viswanadhapalli et al., \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e identified strong low-level jet in the Arabian Sea, convective instability, and the transport of moisture from both the mid-troposphere and the Bay of Bengal are the primary drivers of flooding. The presence of \"Remotely Aligned Intense Tropical Circulations (RAITC)\" contributed to an extra supply of moisture to Kerala from the northwest Pacific Ocean (Mohandas et al.,2020), an intense moisture supply from the western flank of the west Pacific subtropical high (WPSH) to Kerala region (Chaluvadi et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e), An uncommon moisture transportation from the southern equatorial Indian Ocean to Kerala, influenced by the Subtropical Indian Ocean Dipole (SIOD) (Athira et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e), The flooding event was characterized by the presence of an atmospheric river stretching from the Arabian Sea into the Bay of Bengal. (Lyngwa et al.,2021), The intrusion of cold, dry air from the Middle East region interacted with monsoon circulation and created an unstable atmosphere (Kumar et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e), The substantial moisture convergence over Kerala during the flood event was linked to westward-propagating barotropic Rossby waves (Mukhopadhyay et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e), the dynamical impact of the west Pacific cyclones aids in the development of HRE over Kerala (Musaid et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e). Additionally, several studies highlighted the role of cloud microphysics in developing floods ( Chakraborty et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e; Thomas et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e; Vijaykumar et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e), considered the climate change perspective (Hunt and Menon \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e), and explored the impact of reservoir storage on the flooding (Mishra et al., \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e; Ramasamy et al., \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e; Sudheer et al., \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e). While existing studies have focused on specific events, a comprehensive analysis regarding the development of HRE over Kerala is still lacking.\u003c/p\u003e\n\u003cp\u003eThe Indian monsoon system is a part of general atmospheric circulation, the monsoon current originates from the southern hemisphere as southeasterly currents become south-westerly after crossing the equator, hence climate variability in the southern hemisphere can modulate the ISMR. The dominant mode of climate variability in the extratropical Southern Hemisphere is the Southern Annular Mode (SAM)(Rogers and van Loon, \u003cspan class=\"CitationRef\"\u003e1982\u003c/span\u003e; Thompson \u0026amp; Wallace, \u003cspan class=\"CitationRef\"\u003e2000\u003c/span\u003e, Pohl et al.,2012). In the positive phase of the SAM, a prominent feature is the presence of a strengthened high-pressure belt located around 40\u0026deg;S. Which causes the belt of strong westerly winds in higher latitudes to contract towards Antarctica. In contrast, during a negative SAM phase, the high-pressure belt weakens at 40\u0026deg;S, leading to the expansion of the belt of strong westerly winds towards the equator. The relationship between SAM and the Indian monsoon has been demonstrated in various studies (Viswambharan et al., 2013; Prabhu et al., 2017; Dou, 2017; Pal et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e; Gnanaseelan et al., 2021; Dwivedi et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e). Additionally, the El Ni\u0026ntilde;o-Southern Oscillation (ENSO) is a notable phenomenon that significantly influences Indian Summer Monsoon Rainfall. Another influential factor in the Indian Summer Monsoon Rainfall from the Southern Hemisphere is the Mascarene High (Krishnamurthy and Bhalme, 1976). The present study seeks to investigate the impact of the southern hemisphere oceanic and atmospheric conditions on the development of the HRE over Kerala during August.\u003c/p\u003e\n\u003cp\u003eThe primary aim of this study is to investigate the potential impacts of Southern Hemisphere pre-monsoon ocean-atmospheric conditions on the variability of Heavy Rainfall Events (HRE) in the subsequent August, as well as to elucidate the associated physical mechanisms. The paper is structured as follows: Section 2 provides a comprehensive overview of the data and methodology employed. Section \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e explores the analysis of HRE trends and variability over Kerala, the teleconnections of August HRE over Kerala, and the physical mechanisms that explain how the \"coupled oceanic-atmospheric bridge\" process extends the SAM signal and transmits its influence to Kerala in August. Section \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e presents the summary and conclusions of this study.\u003c/p\u003e"},{"header":"2.1 Data ","content":"\u003cp\u003eGridded daily rainfall data from 1981 to 2020 during the summer monsoon season, with a resolution of 0.25\u0026deg; latitude and 0.25\u0026deg; longitude, were obtained from the Indian Meteorological Department (IMD). Derived from measurements collected by 6955 rain gauge stations across India (6.5\u0026deg;N-37.5\u0026deg;N; 66.5\u0026deg;E-101.5\u0026deg;E), the dataset exhibits improved spatial coverage compared to earlier versions (Pai et al., \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e), employing the Inverse Distance Weighted scheme for spatial interpolation (Shepard et al., 1968). The HadISST from the Met Office Hadley Centre, with a spatial resolution of 1\u0026deg; \u0026times; 1\u0026deg; latitude\u0026ndash;longitude grid is used for the analysis (HadISST; Rayner et al., \u003cspan class=\"CitationRef\"\u003e2003\u003c/span\u003e). The daily SST anomalies were obtained from NOAA OISST data. The dataset for atmospheric pressure, wind data, and vertically integrated moisture transport (VIMT) was obtained from ERA5, provided by the Copernicus Climate Change Service. The ERA-5 is the fifth-generation reanalysis developed at the ECMWF (European Centre for Medium-Range Weather Forecasts). It provides hourly estimates for a large amount of atmospheric and land surface variables. The information from observations is extracted from many satellites or conventional instruments (Hersbachet et al., 2020). The atmospheric component is interpolated to 37 pressure levels from the surface up to 1 Pa. The study employs NCEP/NCAR monthly wind data for the analysis. This study utilizes the Marshal SAM index, which is the station-based Southern Annular Mode (SAM) index. It is derived from the zonal pressure difference between the latitudes of 40\u0026deg; S and 65\u0026deg; S.\u003c/p\u003e\n\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n\u003ch2\u003e2.2 METHODS\u003c/h2\u003e\n\u003cp\u003eThe Peak Over Threshold (POT) method is a statistical technique used to identify the HRE from time series data. The POT identifies extreme events by focusing on all data points that exceed a predefined threshold. There are two types of POT methods, absolute threshold (a fixed value) or a varying threshold based on percentiles. The varying threshold is suitable for regions with heterogeneous characteristics, in rainfall, where extreme events can vary significantly across geographical locations. In this study, a HRE is defined as any day when the rainfall exceeds the 95th percentile threshold. This calculation is performed individually for each grid point. To determine this threshold, the 95th percentile value for each grid was computed using a dataset spanning 40 years specific to that grid location. The study utilized linear trend tests for conducting trend analysis, employing the non-parametric Mann-Kendall trend tests (Mann et al., 1945; Kendall et al.,1948) to evaluate the statistical significance of these trends.\u003c/p\u003e\n\u003cp\u003eThe daily wind stream function was calculated using the following equation,\u003c/p\u003e\n\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\n\u003cdiv id=\"FileID_Equa\" class=\"mathdisplay\"\u003e$$u=\\frac{\\partial {\\Psi }}{\\partial y}, v=-\\frac{\\partial {\\Psi }}{\\partial x}$$\u003c/div\u003e\n\u003c/div\u003e\n\u003cp\u003eWhere u is a zonal wind vector, v is the meridional wind vector \u0026psi; is the stream function.\u003c/p\u003e\n\u003cp\u003eThe Vertically Integrated Moisture Transport (VIMT) is used to describe the total amount of moisture being transported through the atmosphere in a vertical column. VIMT is often calculated by integrating the horizontal moisture transport from the surface to a pressure level, of up to 200 hPa.\u003c/p\u003e\n\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\n\u003cdiv id=\"FileID_Equb\" class=\"mathdisplay\"\u003e$$VIMT=\\frac{1}{g}{\\int }_{p200}^{p1000}qVdp$$\u003c/div\u003e\n\u003c/div\u003e\n\u003cp\u003eWhere q is the specific humidity, V is the wind vector, \u003cem\u003eP\u003c/em\u003e is the pressure, and \u003cem\u003eg\u003c/em\u003e is the acceleration due to gravity. The composites in this study are constructed to examine atmospheric conditions during HRE in Kerala. Kendall's tau rank correlation analysis is employed to uncover the connection between HRE in Kerala and the presence of favorable atmospheric conditions. This statistical method helps to determine whether there is a significant association between the occurrence of HREs and specific atmospheric variables.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"3 Results","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n\u003ch2\u003e3.1 Trend and variability of HRE over Kerala\u003c/h2\u003e\n\u003cp\u003eThe trend and variability of HRE over Kerala (74\u003csup\u003e0\u003c/sup\u003eE,78\u003csup\u003e0\u003c/sup\u003eE-8\u003csup\u003e0\u003c/sup\u003eN,12\u003csup\u003e0\u003c/sup\u003eN) during August from 1981 to 2020 is discussed here. A significant increasing trend in HRE is observed over Kerala, particularly in southern Kerala and the Western Ghats regions (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ea). These findings are consistent with the observations made by Subrahmanyam et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e, indicating an increase in HRE occurrences over the core monsoon zone in August from 1901 to 2022. The trend in mean rainfall and contribution from HRE also showed an increase in August over Kerala (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eb,\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ec). The frequent occurrences of HRE can be attributed to the increase in mean rainfall over Kerala. An increasing trend in the mean rainfall over Kerala is also reported by Revadekar et al., (\u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e); Guhathakurta et al., (\u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). The reasons behind the occurrence of HRE over Kerala during August need to be explored for the timely forecast of such events in the future.\u003c/p\u003e\n\u003cp\u003eThe inter-annual variability of HRE during August over the 40 years is depicted in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ed. During the period from 1981 to 1999, the frequency of HRE exhibited negative values, suggesting reduced HRE activity. However, from the year 2000 onwards, there is a noticeable positive trend in the frequency of HRE. The increases observed in recent years are likely contributing to the pronounced positive trend in the frequency of HRE. Additionally, there is a noticeable shift in climate patterns around 2000, characterized by negative values before 2000 and positive values thereafter. Several studies have argued the retrieval of ISMR after 2002 (Roxy et al., 2017; Goswami et al., 2023, etc.). This study underscores the climate shift in occurrences of HRE after 2000 during August over Kerala.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n\u003ch2\u003e3.2 The association of southern hemisphere ocean-atmospheric conditions and HRE over Kerala during August\u003c/h2\u003e\n\u003cp\u003eTo explore the influence of Southern Hemisphere subtropical ocean- atmospheric conditions on the variability of the HRE over Kerala. First examined the trends of sea surface temperature (SST), mean sea level pressure (MSLP), upper-level wind, and lower-level wind in the Southern Hemisphere during August (2001\u0026ndash;2020), as illustrated in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ea-\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eb. The SST exhibits a positive trend in the northern Arabian Sea, the southern Indian Ocean near Madagascar island, as well as in the southwest Pacific Ocean and the North Pacific Ocean, forming a 'horse-shoe pattern of SST trend.' A cooling trend is observed in the south of Madagascar island in the southwest Indian Ocean and the central Pacific Ocean (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ea). A decreasing trend in MSLP near Madagascar Island and an increasing trend in MSLP near Australia, with an alternative 850hPa \u0026ldquo;cyclonic\u0026rdquo; and \u0026ldquo;anticyclonic\u0026rdquo; wind trend in the respective locations, are observed from the analysis as shown in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eb. The upper-level wind pattern shows alternating \"cyclonic\" and \"anticyclonic\" patterns from Madagascar to the east of Australia through the South Indian Ocean (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ea), indicating the trend in the Rossby wave in the subtropical jet stream. A strong upper-level easterly wind trend is observed over the warming region of the southwest Indian Ocean. The association of these changes in the Southern Ocean with the HRE over Kerala is the major objective of the present study. The correlation of the frequency of HRE over Kerala during August with different ocean-atmospheric variables is analyzed for this purpose. The influence of these changes in the Southern Hemisphere on the occurrence of HRE over Kerala is the major objective of the present study. The correlation of the frequency of HRE over Kerala during August with different Ocean-Atmospheric variables is analyzed for this purpose. Since there is a climatic shift around 2000, we have further analyzed the comparison between the early (1981\u0026ndash;2000) and recent (2001\u0026ndash;2020) epochs.\u003c/p\u003e\n\u003cp\u003eThe spatial correlation pattern of SST anomalies and frequency of HRE in Kerala from 1981 to 2000 is illustrated in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ea. A significant positive correlation is observed with SST anomalies in the western Indian Ocean region (20\u0026deg;S to 20\u0026deg;N), while a negative relation is noted with SST in the South Indian Ocean near 40\u0026deg;S, especially over the Mascarene high region. In Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eb, depicting the correlation between SST anomalies and August HRE in Kerala from 2001 to 2020, it is observed that August HRE is linked to two distinct SST dipole patterns in the southern Pacific Ocean and the Indian Ocean. This involves cooling in the eastern equatorial Pacific Ocean, warming in the southwest Pacific Ocean, and simultaneous cooling in the eastern equatorial Indian Ocean and warming in the western Indian Ocean. Furthermore, a negative correlation exists between southwest Indian Ocean SST near 40\u0026deg;S and August HRE. Comparing the two epochs, distinct SST correlation patterns emerge. In the first epoch, HRE is solely linked to the Indian Ocean SST. However, while the South Pacific Ocean's influence on August HRE development over Kerala has grown in the second epoch, the relationship with the Indian Ocean remains significant. In the second epoch, the HRE correlation with SST is positive near Madagascar island, contrasting with the negative correlation in the first epoch. The correlation pattern of SST observed in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eb in the recent epoch appears to be similar to the observed trend of SST pattern, which emphasizes the influence of SST trend on the trend in HRE over Kerala.\u003c/p\u003e\n\u003cp\u003eIt is important to understand the moisture source for the occurrence of HRE. So, we have correlated the HRE frequency with vertically integrated moisture transport (VIMT). In the second epoch, a notable correlation between VIMT and August HRE in the North Indian Ocean is evident in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eb. During this period, the connection between moisture transport from the eastern equatorial Indian Ocean to the Kerala region has strengthened. In contrast, the first epoch lacks a significant relationship between HRE and moisture transport in the Indian Ocean region (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ea). The surge in HRE frequency over Kerala became apparent only after 2000, potentially explaining the increased correlation between HRE and VIMT in the second epoch. Since the HRE is linked to negative SST anomalies over the eastern Indian Ocean and positive SST anomalies in the western Indian Ocean, the observed relationship between moisture transport and the HRE is consistent with these associations.\u003c/p\u003e\n\u003cp\u003eThe spatial correlation pattern of MSLP and the August HRE are illustrated in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ec-\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ed. In the second epoch, a negative correlation between the HRE and the MSLP over the entire western Indian Ocean is observed (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ed), while in the previous epoch, the negative correlation was predominantly concentrated in the southwestern Indian Ocean. A significant positive correlation pattern is observed in the eastern Indian Ocean and Australian region. Hence a dipole pattern of the MSLP i.e., low-pressure anomaly over the western Indian Ocean and high-pressure anomaly over the eastern Indian Ocean is conducive for the occurrence of the HRE over Kerala in the recent epoch. The relation between the August HRE over Kerala and the Mascarene High is inversely proportional in both periods. The relation between the Australian high with the HRE over Kerala is increasing in the second epoch as compared to the first epoch. The strengthening of the relationship between the August HRE and the eastern Pacific Ocean in the second epoch is evident. Additionally, a negative correlation with the southwest Pacific Ocean is also noticeable. The positive MSLP anomalies in the tropical eastern Pacific and negative MSLP anomalies in the middle latitudes of the southwest Pacific Ocean are favourable for the occurrence of HRE over Kerala. This correlation pattern resembles a dipole in the north-south (meridional) direction in the Pacific Ocean. Hence, the strengthening of La Ni\u0026ntilde;a, coupled with the low pressure near Madagascar island, may contribute to an increase in the August HRE over Kerala. Additionally, the MSLP correlation pattern reflects two distinct dipoles in the South Pacific and the Indian Ocean regions, which closely resemble the SST correlation patterns observed in the second epochs. The correlation pattern of MSLP in the Southern Hemisphere subtropics appears to be the same as the observed trend in MSLP.\u003c/p\u003e\n\u003cp\u003eThe correlation between 850hPa winds and the HRE over Kerala during August is illustrated in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ec-\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ed. In the second epoch, the HRE strongly correlates with the south-westerly winds over the northern Indian Ocean (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ed). The south-westerly winds appear from the eastern Indian Ocean and the equatorial Indian Ocean, indicating an observed eastward shift in the cross-equatorial flow. A previous study by Chaluvadi et al., (\u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e) reported that during the 2018 Kerala flood, an eastward shift in the cross-equatorial flow was observed. Furthermore, the relation between the HRE and the cyclonic circulations in the South Pacific and southwest Indian Ocean has increased during the recent epoch. In contrast, during the first epoch, the relation of the HRE with the cyclonic circulations in the southern Indian Ocean was weak and absent in the southern Pacific Ocean (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ec). From the trend analysis of lower-level wind, cyclonic circulation is increasing over the southwest Indian Ocean and southwest Pacific Ocean. Hence, the positive relation of HRE with these cyclonic circulations, and the increasing trend of these circulations, may cause the increase in HRE activity.\u003c/p\u003e\n\u003cp\u003eThe atmospheric conditions conducive to the HRE in recent epochs may encompass factors such as the weakening of Mascarene High, the strengthening of the Australian High, and the intensification of the lower-level cyclonic circulations in the middle latitudes of the southern hemisphere, warming of Southwest Pacific Ocean. It is worth noting that numerous studies have indicated that the recent period of the global warming hiatus (GWH) is characterized by the warming of the Indian Ocean (Zhao et al., \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e), and the weakening of the Mascarene high (P JV et al., 2020). Therefore, the factors triggering the occurrence of the HRE over Kerala can be associated with global climate change, which, in turn, modifies atmospheric conditions in the southern hemisphere, potentially creating conditions favorable for the occurrence of the HRE over Kerala.\u003c/p\u003e\n\u003cp\u003eTo further explore the dynamics of the HRE, we examine daily composite maps of SST, wind, VIMT (Vertically Integrated Moisture Transport), and upper-level stream function during the time of occurrence of HRE over Kerala. The composites are based on twenty events of heavy rainfalls during August within the last two decades (2001\u0026ndash;2020) are depicted in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ea-\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eb. Warming is observed in the southwest Pacific Ocean, the central Indian Ocean, and the vicinity of the Madagascar island region, with cooling near the 40\u0026deg;S regions of the southern Indian Ocean during the time of the HRE. This SST pattern may contribute to the weakening of the Mascarene high and facilitate the intensification of lower-level cyclonic circulation, promoting the occurrence of HRE. An enhanced moisture convergence over Kerala is evident during the time of events. The SST and VIMT patterns closely resemble the correlation and trend patterns, highlighting the potential for an increased occurrence of HRE over Kerala during August.\u003c/p\u003e\n\u003cp\u003eWhile examining 200 hpa stream function anomalies in the middle latitudes of the south Indian Ocean, positive, negative, and positive patterns are observed (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eb). These patterns may be attributed to the waviness within the southern hemisphere subtropical jets over the Indian Ocean. Extension of a positive stream function near the southern tip of India from the southern hemisphere is evident. Conversely, negative stream function anomalies are observed in the north Indian regions during these events. This indicates the presence of low-pressure systems in the monsoon trough region, likely advected from the Bay of Bengal. Several studies have reported the presence of LPS in the Bay of Bengal during flood events (Kumar et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e; Athira et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e; Chaluvadi et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eThe lower-level wind patterns in the middle latitudes of the South Indian Ocean reveal a cyclonic, anticyclonic, and cyclonic pattern, aligning with the observed pattern in stream functions (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eb) and trend in 850 hpa wind. Consequently, the anticyclonic circulation in the southeastern Indian Ocean and the cyclonic circulation in the southwestern Indian Ocean can favor wind convergence over Kerala. Additionally, the negative stream function in north India and the positive stream function in the southern tip of India may channel the Low-Level Jet toward Kerala by shifting it southward from its normal position. This, in turn, leads to increased precipitation in the Kerala region. Based on this analysis, it can be inferred that the Southern Hemisphere subtropical circulations have a crucial role in modulating the path and position of LLJ over the Indian subcontinent.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n\u003ch2\u003e\u003cstrong\u003e3.3 Relation between April SAM and August HRE teleconnection\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe influence of Southern Hemisphere atmospheric circulation on the variability of the HRE in recent times is evident. Since the Southern Annular Mode (SAM) is the dominant mode of climate variability in the Southern Hemisphere, here we examine whether SAM influences the occurrence of HRE over Kerala during August.\u003c/p\u003e\n\u003cp\u003eTo explore the influence of the SAM on the HRE occurrence over Kerala in August, we correlate the monthly SAM indices with the frequency of HRE from 1981\u0026ndash;2020 period. This study reveals that the April SAM exhibits a negative relationship with the frequency of HRE over Kerala during the subsequent August, with a correlation coefficient of -0.228 and a significant confidence level of 95% (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eb). The relationship of the August HRE with the SAM index in other months is generally insignificant, except for January, which exhibits a correlation coefficient of 0.19. Hence, further analysis will focus on the relationship between the April SAM and the frequency of HRE over Kerala during subsequent August.\u003c/p\u003e\n\u003cp\u003eThe spatial correlation map of the April SAM index and HRE frequency over Kerala for the study period is shown in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003ea. It is observed that a significant negative correlation exists between the April SAM and the frequency of HRE over Kerala in August. Previous studies, such as Pal et al., (\u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e), revealed that the rainfall anomalies of August are not linked to SAM. Instead, they observed an out-of-phase relationship between the SAM index of June and July rainfall. However, Viswambaran et al., (2013) found that August rainfall in India has an out-of-phase relationship with the June SAM index. These earlier studies primarily explore the association between mean rainfall and SAM, consistently highlighting a negative correlation between rainfall in India and the SAM, particularly along the west coast. Our study specifically delves into the relationship between the SAM and the occurrence of the HRE over Kerala during August. The focus on the HRE in this study may have led to different observations compared to other studies, although the out-of-phase relationship with the SAM and the rainfall remains consistent, even in the context of the HRE.\u003c/p\u003e\n\u003cp\u003eThe time series of standardized values of the April SAM and the frequency of HRE in August are illustrated in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eb, indicating the out-of-phase relationship between the April SAM and the August HRE increased in the recent two decades (after the year 2000). As mentioned earlier, the study observed an increase in the occurrence of the HRE over Kerala after 2000. This suggests that the influence of the April SAM on the HRE has become more significant in the recent two decades. Therefore, the subsequent analysis will be focused on the recent two decades (2001\u0026ndash;2020). In conclusion, this study reveals a significant negative correlation between the April SAM index and the frequency of HRE over Kerala in August. Additionally, it underscores that the influence of the April SAM on the HRE has grown more prominent in the recent two decades.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n\u003ch2\u003e3.4 Mechanism behind the lag correlation of SAM (April) and HRE (August)\u003c/h2\u003e\n\u003cp\u003eIn this section, we explore how does the preceding April SAM continue to impact the occurrence of the HRE in Kerala during the following August. Here we examine the mechanisms for SAM\u0026rsquo;s temporal persistence and its influence on regional climate patterns. It is widely acknowledged that atmospheric signals like SAM have limited persistence. Zhang et al., (2020) observed that the SAM exhibits persistence across different timescales, with its primary variations occurring on sub-seasonal and cross-seasonal scales. They also emphasized the connection between cross-seasonal SAM variability and extratropical air-sea interactions as well as extratropical SST. The SST anomalies generated by the SAM can effectively retain the SAM signal, preserving it over an extended period and subsequently impacting the regional climate in the ensuing months(Nan and Li \u003cspan class=\"CitationRef\"\u003e2003\u003c/span\u003e; Nan et al., \u003cspan class=\"CitationRef\"\u003e2009\u003c/span\u003e; Wu et al., \u003cspan class=\"CitationRef\"\u003e2009\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e; Zheng and Li \u003cspan class=\"CitationRef\"\u003e2012\u003c/span\u003e; Liu et al., \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e; Prabhu et al., \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e; Dou et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e). The function of the \"ocean bridge\" will be considered to comprehend the mechanism that causes the April SAM to affect the HRE in the following August. In the subsequent analysis, our focus will be on identifying the specific SST anomalies generated by the April SAM. These anomalies act as the critical components of the \"ocean bridge\" mechanism, facilitating the influence of the April SAM on the modification of HRE over Kerala in August.\u003c/p\u003e\n\u003cp\u003eThe spatial correlation pattern of SST anomalies in April and August with the frequency of HRE in August is depicted in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003ea-\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eb. In April, August HRE is related to positive anomalies in the southwestern Pacific Ocean and negative anomalies of SST in the tropical eastern Pacific and the equatorial eastern Indian Ocean. In August, HRE showed a negative relationship with the SST over tropical eastern Pacific Ocean. The positive correlation with SST anomalies in the southwest Pacific Ocean remains consistent. Simultaneously, there is a negative association with the SST anomalies in the eastern Indian Ocean region and a positive relationship with the SST anomalies in the west Indian Ocean. Consequently, the development of La Ni\u0026ntilde;a from spring to summer in the Pacific Ocean, the progressive cooling in the eastern equatorial Indian Ocean from April to August, and the persistent warming in the southwest Pacific Ocean from April to August collectively increase the likelihood of HRE occurring over Kerala in August.\u003c/p\u003e\n\u003cp\u003eThe spatial correlation patterns of SST for April and August with respect to the April SAM are presented in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003ec- \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003ed. The spatial correlation pattern of SST with the April SAM is precisely opposite to the pattern observed in the spatial correlation between the SST and the August HRE. This out-of-phase relationship between correlation patterns aligns with the negative relationship between the August HRE and the April SAM. In April, in the South Pacific Ocean, characterized by a negative relation with SST in the southwest Pacific Ocean and a positive relation with SST in the eastern Pacific Ocean (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003ec). In August, the negative correlation with southwest Pacific SST persists and extends toward the western equatorial Pacific Ocean (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003ed). From this analysis, it can be inferred that the negative April SAM signals lead to the development of warm SST anomalies over the southwest Pacific Ocean (SWPO, 25\u003csup\u003e0\u003c/sup\u003eS-40\u003csup\u003e0\u003c/sup\u003eS,177\u003csup\u003e0\u003c/sup\u003eW-150\u003csup\u003e0\u003c/sup\u003eW), this region is marked in the box (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003ea-\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eb). The positive SST anomalies that developed due to the negative SAM in April over the SWPO persist and extend toward the equator as the season progresses. This anomalous SST pattern can influence changes in the overlying atmospheric circulations, consequently increasing the occurrence of the HRE over Kerala in August. Therefore, it can be deduced that anomalous SST in the southwest Pacific Ocean (SWPOSST) plays a crucial role in establishing the connection between the April SAM and the subsequent August HRE. Thus, the SWPOSST serves as an oceanic bridge linking the April SAM to the ensuing August HRE over Kerala.\u003c/p\u003e\n\u003cp\u003eThe SAM can lead to SST anomalies in the southern hemisphere that persist into subsequent seasons. These SST anomalies play a regulatory role in the meridional circulation and large-scale precipitation patterns by influencing the meridional gradient of SST (Zheng et al., \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e; Liu et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). Examining further, it is important to consider how the April SAM-generated SST anomalies in the SWPO can affect SST anomalies in the following August. The spatial correlation pattern of SWPO SST anomalies in April with August SST (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003ea) closely resembles the correlation pattern between the August HRE and August SST anomalies (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eb). The April SWPOSST region shows a negative association with August SST anomalies near the equatorial eastern Pacific Ocean and the southwest Indian Ocean to the south of Madagascar island (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003ea). The cool SST anomalies in the southwest Indian Ocean in August may play a crucial role in enhancing the lower-level cyclonic circulation. From the analysis, it can be inferred that the positive SST anomalies in SWPO developed by negative SAM in April can potentially modify the SST pattern in August over the Indian Ocean and Pacific Ocean regions.\u003c/p\u003e\n\u003cp\u003eTo investigate the influence of the April SWPO SST on the regional Hadley circulation over the Indian Ocean region, which contributes to the modification of the August HRE occurrences over Kerala, we conducted a correlation analysis between the SWPO SST and the Hadley circulation. Figure\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003eb illustrates the correlation pattern of the regional Hadley cells with the August HRE. The August HRE is associated with ascending motion near 10\u0026deg;N, a circulation in the upper tropospheric levels, and the intrusion of southerlies from the upper troposphere to the middle troposphere. The upper-level southerlies could be attributed to the influence of circulations in the Southern Ocean or the subtropical jets of the Southern Hemisphere. Figure\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003ec illustrates the correlation pattern of the regional Hadley circulation over the Indian Ocean with the HRE over Kerala in August, revealing a strong ascending motion from the equator to the Kerala region. Notably, the correlation pattern of the SWPO SST in April with regional Hadley circulation closely resembles the pattern observed in the correlation of August HRE with regional Hadley circulation, featuring an ascending motion from the equator to around 10\u0026deg;N. Consequently, it can be inferred that warm SST anomalies in the SWPO during April have the potential to influence the regional Hadley circulation over the Indian region.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"4 Summary and conclusions","content":"\u003cp\u003eThe present study explored the influence of southern hemisphere ocean-atmospheric conditions on the occurrence of heavy rainfall events over Kerala in August. The HRE during August shows a significant increasing trend. A surge in the formation of the HRE over Kerala has been observed in the recent two decades (2001\u0026ndash;2020). The warming of southwest Indian Ocean and associated weakening of Mascarene High and strengthening of Australian High are found to be positively correlated with the frequency of HRE. Southern Hemisphere subtropical circulations have a crucial role in modulating the path and position of LLJ over the Indian subcontinent. An intensification of anticyclonic circulation over the southeast Indian Ocean and the cyclonic circulation over the southwest Indian Ocean is observed in the recent decades. These changes in the southern midlatitude circulation shows a significant impact on the occurrence of HRE.\u003c/p\u003e \u003cp\u003eIn the early epoch, HRE is solely linked to the warming of west Indian Ocean. In the recent decades, HRE is correlated with the east (cool)-west (warm) SST dipole pattern in the Equatorial Indian Ocean and warming of Southwest Pacific Ocean and cooling of eastern Pacific Ocean. A possible mechanism by which the southern hemispheric circulation influences the HRE over Kerala can be through the enhancement of easterly wind from the cool eastern Indian Ocean. This wind diverge in the central Indian Ocean and one part is flowing towards Kerala as south westerly wind and the other part as towards the warm southwest Indian Ocean. The cyclonic circulation over the southwest Indian Ocean may have the potential to enhance the divergent wind from the Eastern Indian Ocean which increases the moisture transport from the central equatorial Indian Ocean to the Kerala region and leads to a spell of heavy rainfall activity.\u003c/p\u003e \u003cp\u003eFurther analysis in the present study revealed an out-of-phase relationship between the April SAM index and August HRE. It is observed that the negative SAM is related with the warming over the southwest Pacific Ocean (25\u0026deg;S-40\u0026deg;S, 177\u0026deg;W-150\u0026deg;W) in April (SWPO SST) which persisted up to the subsequent August. This April SWPO SST is correlated with the north (warming near Madagascar island)-south (cooling to the south of Madagascar island) SST gradient over the southern Indian Ocean and cooling in the eastern Pacific Ocean in August. The above-mentioned north-south SST gradient can lead to cyclonic circulation in the southwest Indian Ocean. These changes in the middle latitude circulation in the southern Indian Ocean modify the regional Hadley circulation and place the ascending branch of the cell over Kerala. Hence, the SWPO SST during April can be considered as an \u0026ldquo;ocean bridge\u0026rdquo; conveying the April SAM signals to the subsequent months\u003c/p\u003e \u003cp\u003eThe intensification of cyclonic circulation (weakening of the Mascarene High) to the southwest (at 40\u0026deg;S) of the Indian Ocean plays a crucial role in the occurrence of HRE over Kerala. The periodicity of these occurrences may hinge on the undulation of jet streams or other atmospheric wave activities. Notably, the SAM demonstrates an intrinsic timescale of 10\u0026ndash;30 days (Zhang et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The negative SAM-induced SWPO SST anomalies can impact subtropical jets, leading to undulations in the jet stream and variations in the strength and position of middle-latitude high-pressure systems. Occasionally, other atmospheric phenomena may also influence these patterns. Consequently, further analysis is essential to pinpoint the mechanism connecting April SAM to August HRE over Kerala. Despite this, the influence of Southern Hemisphere circulation on the variability of HRE over Kerala is evident. The negative SAM and warming in the SWPO in April can be considered precursory factors for the occurrence of HRE over Kerala in August. Integrating these factors into atmospheric models has the potential to enhance the predictability of these events.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSreekala P P: Conceptualization, Supervision\u003c/p\u003e\n\u003cp\u003eSreevidya Ravi: Visualization, Drafting the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to acknowledge the Department of Atmospheric Sciences, Cochin University of Science and Technology, India for providing the facilities and financial support. The authors are grateful to the IMD, NOAA, ECMWF, NCEP/NCAR, and The Met Office Hadley Centre for providing the data. The first author also appreciates the valuable assistance received from P S Suthinkumar in Python programming.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe rainfall data were obtained https://www.imdpune.gov.in/cmpg/Griddata/Rainfall_25_NetCDF.html , the SST data at \u0026nbsp;https://www.imdpune.gov.in/cmpg/Griddata/Rainfall_25_NetCDF.html the wind MSLP,VIMT data at https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-pressure-levels?tab=overview and https://psl.noaa.gov/data/gridded/data.ncep.reanalysis.html the SAM index were obtained at https://climatedataguide.ucar.edu/climate-data/marshall-southern-annular-mode-sam-index-station-based.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAllan, R. 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Journal of Climate, 28(17), 6859-6881.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4097582/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4097582/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eKerala has witnessed a surge in heavy rainfall events (HRE) during August in recent years. This study examines the influence of ocean-atmospheric conditions in the Southern Hemisphere on the variability of HRE in Kerala during August. The study finds that the changing ocean-atmospheric conditions in the South Indian Ocean such as uneven sea surface temperature (SST) trends (warming near Madagascar Island and cooling to the south of Madagascar Island, north-south SST gradient), weakening of the Mascarene High, strengthening of the Australian High and associated circulation changes significantly impact the recent trend in HRE over Kerala. A significant negative correlation exists between the April Southern Annular Mode (SAM) index and August HRE. Negative April SAM induces warm SST in the southwest Pacific Ocean (SWPO SST), which persist until August. April SWPO SST is positively associated with the north-south SST gradient in the southwest Indian Ocean in August. The intensification of cyclonic circulation over the southwest Indian Ocean and anticyclonic circulation over the southeast Indian Ocean may be the atmospheric response to April SAM, facilitated through SWPO SST. This cyclonic circulation over the southwest Indian Ocean may enhance divergent winds from the cool eastern Indian Ocean, and increase the moisture transport from the central equatorial Indian Ocean to the Kerala region and causes HRE over Kerala. A positive correlation between April SWPO SST and enhanced regional Hadley circulation over Kerala in August emphasizes this hypothesis. Therefore, negative SAM and warming in the SWPO in April can be considered as precursory factors for HRE occurrence over Kerala in August.\u003c/p\u003e","manuscriptTitle":"Impact of Southern Annular Mode on the variability of Heavy Rainfall Events over Kerala during August.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-28 09:09:27","doi":"10.21203/rs.3.rs-4097582/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5597f677-ad16-4464-a710-20908ed027c9","owner":[],"postedDate":"March 28th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-05-28T01:28:13+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-28 09:09:27","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4097582","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4097582","identity":"rs-4097582","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}