Changes in extreme rainfall events in the recent decades and their linkage with atmospheric moisture transport
Graphical abstract
First epoch -(1951–1985), Second epoch- (1986–2020), VIMF- vertically integrated moisture flux, EREs- Extreme rainfall events, MR- Moisture River patterns.
Introduction
The Indian summer monsoon (ISM) is always distinct from all other monsoon systems due to the immense contribution of rainfall to the annual total (Rao, 1976). The ISM rainfall is the most complex rain forming system, and it shows variabilities extending from intraseasonal to multidecadal (Varikoden and Babu, 2015; Seetha et al., 2020; Hrudya et al., 2020). There are intraseasonal variations that encompass active and break conditions, which are associated with high and low rainfall, respectively (Ramamurthy, 1969; Goswami and Mohan, 2001; Gadgil, 2003; Joseph and Sabin, 2008; Rajeevan et al., 2010). Several studies also comprise significant interdecadal variability in various components of the Indian summer monsoon (Mooley and Parthasarathy, 1984; Kripalani and Kulkarni, 1997; Mehta and Lau, 1997; Chang et al., 2000; Wu and Wang, 2002; Goswami, 2006; Joseph et al., 2013; Varikoden and Babu, 2015). Over the ages, serious steps have been taken to understand the patterns and imposing factors affecting the rainfall associated with the Indian summer monsoon; among them, the source and distribution of the moisture flux are the least explored. The rainfall activity is directly associated with moisture transported from the adjacent ocean (Pisharoty, 1965; Ghosh et al., 1978; Murakami et al., 1984; Clemens and Oglesby, 1992; Swapna and Ramesh Kumar, 2002; Levine and Turner, 2011; Nair et al., 2021). The recent increasing trends in extreme rainfall events were reported in several studies (e.g., Goswami et al., 2006; Guhathakurta et al., 2011; Varikoden et al., 2013, Roxy et al., 2017; Varikoden and Revadekar, 2020; Swain et al., 2020; Thomas et al., 2021; Aggarwal et al., 2022; Anandh and Vissa, 2022). These increasing trends are found to be associated with increased greenhouse gas emissions under the warming atmosphere (Ramanathan et al., 2005; Ramanathan and Carmichael, 2008; Vinoj et al., 2014; Singh et al., 2019). Some of the catastrophes reported accompanied by extreme rainfall events in the last decades have been violent and unforeseen. This demands an in-depth investigation of the mechanism responsible for the occurrence of rainfall extremes.
Gimeno et al. (2010) found that the Arabian Sea is the major source of moisture for Indian summer monsoon rainfall, and more precisely, Gupta et al. (2005) observed that the Arabian Sea serves as the moisture source for most of the extreme events in the western parts of the Indian subcontinent. On the other hand, the moisture induced from the Bay of Bengal caused rainfall and its extremes mostly in the eastern parts of the Indian subcontinent, and this moisture is mainly exposed to the existence of monsoon depressions in the Bay of Bengal (Gupta et al., 2005). The movement of the water vapour along with the LLJ (Low Level Jet Stream) towards the western part of the subcontinent was reported in detail by Ordóñez et al. (2012). They found that during the monsoon season, the path of LLJ over the ocean surface evaporates more and becomes the major source of extreme events in western and southern India. The recent increase in the Arabian Sea moisture followed by a decreasing trend in the previous decades is documented in the study of Ratna et al. (2016). The Atmospheric River (AR) concept is primarily used in the detection and investigation of torrential rainfall events in the mid-latitudes (Gao et al., 2016; Guan and Waliser, 2015; Zhang et al., 2019; Curry et al., 2019). However, Lélé et al. (2015) referred to the low-level moisture transport as Moisture River (MR). Patil et al. (2019) studied the association of extreme rainfall with the MR pattern during the 1982–2011 period over the Indian region.
In this study, we are investigating extreme rainfall events and their association with atmospheric moisture fluxes and their transport for the past seventy years from 1951 to 2020. Previously, back trajectory analysis based on the HYSPLIT (Hybrid Single Particle Lagrangian Integrated Trajectory) model was used to find the sources of moisture (e.g. Kurita, 2011; Jana et al., 2018; Saranya et al., 2021, Anandh and Vissa, 2022; Nanditha et al., 2022). The moisture transport from adjoining water masses is channelled through certain corridors to the Indian subcontinent, which appears like the Atmospheric River (AR). The extreme flood event recorded in the second week of August 2018 in the state of Kerala was linked with an AR pattern that originated from the southern Indian Ocean (Lyngwa and Nayak, 2021).
The water vapour flux towards the extreme event location plays a key role in understanding the characteristics of the rainfall. The sources of water vapour can be identified using an isotopic study of water molecules collected from the event location (Gao et al., 2011). But unfortunately, isotopic studies are not commonly applied due to the expensive experimental setup. Here, the role of atmospheric water vapour flux on extreme rainfall events is studied with an emphasis on the moisture river, its back trajectory and vertically integrated moisture flux. In this scenario, analysis is designed to identify the detection of moisture flux and its source region. The manuscript is organised as follows. The background studies of the extreme rainfall events and their known mechanisms are given in section 1, followed by the data used and the methodology adopted for detection of moisture river and trajectory is presented in section 2. Major results and their detailed discussions are presented in section 3, which is trailed by the conclusions that are presented in section 4.
Section snippets
Data and methodology
Our study is mainly focused on the extreme rainfall events and associated moisture transport mechanisms during the summer monsoon season from 1951 to 2020. The base period is set to 1951–2020 and was divided into two multidecadal epochs (1951–1985 and 1986–2020). We used the IMD (India Meteorological Department) gridded daily rainfall with a spatial resolution of 0.25°Х0.25° latitude-longitude grid (Pai et al., 2014). The same data is used to calculate the daily climatology and standard
Changes in the moisture transport and rainfall
The Indian subcontinent is enriched with ample moisture from the adjoining oceans and this moisture contributes to the monsoon rainfall, especially during the southwest monsoon period, and hence spatial distribution of the rainfall is heterogeneous and complex (Rao, 1976; Gimeno et al., 2010). The 70-year climatology of rainfall during the summer monsoon period (June, July, August and September) is given in Fig. 1a. The maximum rainfall accounts in the southwest coastal belts, especially on the
Conclusions
The seasonal rainfall anomaly depicts an increased rainfall over the NE sector, including Meghalaya and Mizoram, also the eastern sector of Orissa during the second epoch, alongside a negative anomaly over the southwest coast, Uttarpradesh and parts of Assam and Arunachal Pradesh. The extreme rainfall events identified during the past 70 years show an increased frequency primarily over the western coastal region, and northwest and east central regions of the Indian subcontinent. However,
Declaration of Competing Interest
The authors confirm that there are no known conflicts of interest associated with this article. The authors have no competing interests as defined by the Publishing Group, or other interests that might be perceived to influence the results and/or discussion reported in this paper.
Acknowledgements
The first and third authors are grateful to Cochin University of Science and Technology, and the second author is grateful to the Director, Indian Institute of Tropical Meteorology, Pune, for providing the facility. The second and third authors acknowledge support from the Department of Science and Technology, India, in the form of a SERB Project (EMR/2016/003682). The first author acknowledges the support in the form of a Research Fellowship from CSIR, New Delhi (09/239(0549)/2019-EMR-I). The
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