Record-breaking rainfall in Sri Lanka in 2014 enhanced by the MJO

Record-breaking rainfall in Sri Lanka in 2014 enhanced by the MJO | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Record-breaking rainfall in Sri Lanka in 2014 enhanced by the MJO Pathmarasa Kajakokulan, Kieran M R Hunt This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4786918/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 11 Feb, 2026 Read the published version in Natural Hazards → Version 1 posted 5 You are reading this latest preprint version Abstract Sri Lanka has experienced a number of severe floods over the past decades, illustrating the importance of understanding the events leading to extreme rainfall. The Madden-Julian Oscillation (MJO), an intraseasonal phenomenon over the tropical ocean, strongly influences interannual precipitation variability in Sri Lanka. However, the impact of the MJO on rainfall over Sri Lanka during the October-November-December (OND) period is less well understood. In this study, we use reanalysis data to explore the impact of the MJO on Sri Lankan rainfall during this season. We show that OND seasons with heavier-than-usual rainfall typically have more days where an active MJO is in phases 2 and 3 and that this is also true for 2014, where both November and December experienced about a week of strong phase 3 MJO. This led to a persistent synoptic-scale circulation anomaly over Sri Lanka, which increased moisture convergence over the island, leading to widespread and long-lived deep convection. We also argue that the persistent 2014 MJO events adjusted the Walker circulation, leading to anomalous ascent over Sri Lanka, which further amplified the seasonal rainfall. This study shows that a better understanding of the link between the MJO and local thermodynamics is needed to improve extreme precipitation forecasts over Sri Lanka. Madden Julian Oscillation moisture convergence extreme rainfall Sri Lanka Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 1 Introduction Rainfall has a substantial influence on many sectors, including agriculture, water resources, climate, water resource management, and ecological modeling (Cavalcante et al. 2020 ). Heavy to extreme rainfall is a natural hazard that frequently results in fatalities, flooding, and erosion (Marengo et al. 2020 ). Sri Lanka ranks as the most climate change-vulnerable country in the world, which has an impact on the natural resources of the island (De Silva and Kawasaki 2018 ). The central highlands are particularly susceptible to the consequences of climate change, as evidenced by a high frequency of very heavy rainfall (Weerasekara et al. 2021 ). Sri Lanka's standing in the Indian Ocean and topographical features make it susceptible to monsoon flooding (Amanda et al. 2021 ). The southwest part of Sri Lanka (wet zone) is particularly vulnerable to flooding during the south-west monsoon, which occurs between May and September (Filho 2015 ). On the other hand, the north and east of the island are at risk during the north-east monsoon, which spans from December to February (Kajakokulan et al. 2023a ). In addition, the north-central, south-eastern, and north-western parts of the island are the most susceptible to drought, primarily due to low rainfall, while floods frequent over the wet zones due to high rainfall (De Silva and Kawasaki 2018 ). Rainfall events with a historic two-year return period are becoming more frequent owing to climate change (Myhre et al. 2019 ). Sri Lanka, for example, experienced major flooding events during the northeast monsoon seasons of 2010, 2011, and 2014 (Alahacoon and Edirisinghe 2021 ). Koralegedara et al. ( 2019 ) showed that these extreme rainfall events arise from moisture supply from both the Bay of Bengal (BoB) and the Arabian Sea (AS), combined with locally enhanced moisture flux convergence and deep convection. Such events can occur during the first inter-monsoon season (March-April) and the second inter-monsoon season (October–November) and can arise from low-pressure systems, tropical cyclones, or mesoscale convective systems. The El Niño Southern Oscillation (ENSO) is a major mode over the Pacific Ocean that significantly affects the atmosphere and ocean in both the tropics and extratropics (Mayer and Balmaseda 2021 ). On the other hand, the Madden–Julian Oscillation (MJO) represents the most significant mode of intraseasonal variability in the tropical Indian Ocean, primarily affecting countries along its edges (Li et al. 2015 ). It is an eastward-propagating phenomenon centered around the equator, with a characteristic time scale of 30–60 days (Madden and Julian 1972), and the duration of the cycle can extend to 100 days (Zheng and Chang 2019 ; Martin et al. 2020 ). The MJO has a life cycle divided into eight phases: formation in the western Indian Ocean (Phase 1), still located in the Indian Ocean but has moved south of SL and (Phases 2 and 3), and into the Maritime Continent (Phases 4 and 5), advancing through the western and eastern Pacific (Phases 6 and 7), and decaying in the central Pacific (Phase 8; Huang et al. 2024 ). Over the past decade, numerous hypotheses have been developed to explain the dynamics of the MJO, including the moisture-mode theory by Adames and Kim (2016), the gravity-wave theory by Dennison, Brewer, Arnold (2014), the trio-interaction theory by Wang et al. ( 2016 ), and the skeleton theory by Majda and Stechmann ( 2009 ). Moreover, MJO propagation is also influenced by ENSO during the winter over the Indian Ocean (Li et al. 2022 ). The interannual rainfall variability over South Asia during the winter is influenced by the MJO where strengthened easterly wind controls the convergence of moisture from the Arabian Sea. For example, Xavier et al. ( 2014 ) emphasized that the phases of the MJO which enhance local convection increase the probability of extreme rainfall events over the South Asian region. It is, therefore, of great importance to understand rainfall response to the MJO, given the significance of increasing frequency of the MJO under climate change (Liang et al. 2022 ) . Several studies have documented the influence of the MJO on daily, monthly, and seasonal precipitation in South Asia (Bagtasa 2020 ; Lenka et al. 2023 ; Crook et al. 2024 ; Almazroui 2023 ). Nevertheless, only a limited number of studies have investigated the impact of MJO on rainfall patterns and the associated mechanisms in Sri Lanka (Jayawardena et al. 2020; Yasanayake et al. 2023 ; Deoras et al. 2023 ). Jayawardena et al. (2020) investigated the impact of the MJO on Sri Lankan rainfall and found that the most significant impact is during the second inter-monsoon and southwest monsoon seasons. Likewise, more extreme precipitation events occur in Sri Lanka during the northeast-monsoon and second inter-monsoon seasons than in the southwest monsoon and first inter-monsoon season (Deoras et al. 2023 ). Recent studies emphasized that rainfall exhibits a tendency to increase (decrease) during the P2-P3 (P6-P7) MJO phases, particularly during the spring and autumn seasons (Huang et al. 2024 ). Thus, the present study employs in situ observations along with reanalysis data to investigate the role of the Madden-Julian Oscillation (MJO) on the occurrence of record-breaking rainfall events in Sri Lanka over the past four decades and specifically during the 2014 OND season. This study is organized as follows: section 2 outlines an overview of the datasets utilized and methodology in the present study, and sections 3 and 4 provide the results and a detailed discussion of the findings. Finally, section 5 outlines the conclusions drawn from the analysis. 2 Data and methods 2.1 Data The data on daily precipitation was obtained from Climate Hazards Group InfraRed Precipitation (Funk et al. 2015 ). ERA5 is a fifth-generation reanalysis dataset that provides hourly precipitation, total cloud cover (TCC), and outgoing longwave radiation (OLR) data from the European Centre for Medium-Range Weather Forecasting (ECWMF, Hersbach et al. 2020 ). MJO indices, namely the real-time multivariate MJO (or RMM) index, were obtained from the Australian Bureau of Meteorology (Wheeler and Hendon 2004 ), and the present study period is 43 years (1981–2023) The in-situ observation data is available from the Department of Meteorology, Sri Lanka, and the data can be accessed upon request. 2.2 Method Observation of rainfall data from the ground weather stations of the Sri Lanka Meteorological Department (Fig. 1 a) was used as a reference to validate the CHIRPS and ERA5 daily rainfall data (Fig. S1 ). First, the rainy season with the highest rainfall in Sri Lanka is October–December (OND). This is then used to define the Sri Lanka rainfall index, which is the area-averaged OND rainfall over Sri Lankan land. Second, we identify years with unusually heavy OND seasonal rainfall from 1981 to 2023, linking these to the MJO behaviour. Finally, a composite analysis is conducted to evaluate the influence of MJO on SL precipitation during rainfall events in Sri Lanka. The VIMFC is calculated as horizontal moisture flux convergence integrated from 1000hPa to 300hPa. Moreover, the present study calculated anomalies based on the climatology period 1981–2023 after removing both seasonality and the long-term linear trend. 3 Results 3.1 Rainfall climatology and characteristics of rainfall anomalies over Sri Lanka in 2014. Previous studies have consistently demonstrated that the primary annual peak in rainfall occurs in October, November, and December (OND) with a secondary peak in March, April, and May (MAM), indicating a bimodal rainfall pattern Huang et al. ( 2023 ). Our results (Fig. 1 b) corroborate previous studies showing that Sri Lanka exhibits a bimodal rainfall pattern, with the two rainfall peaks occurring during OND and MAM. Of these two seasons, OND has the larger mean and the higher interannual standard deviation. Therefore, we show the interannual variability of OND rainfall from 1981 to 2023 (Fig. 1 c). The rainfall anomalies exhibit a strong interannual variability but with a significant positive trend. The largest seasonal anomaly was in 2014, following a notable negative rainfall anomaly in 2013. We further show spatial rainfall anomalies during October, November, and December 2014 separately to assess their respective contributions (Fig. 1 d-f). The positive rainfall anomaly exceeded 4 mm/day of precipitation during October over the wet zone of Sri Lanka. However, the whole of Sri Lanka, especially the north-eastern region, experienced the strongest positive rainfall anomaly during December. Sri Lanka experienced reduced December rainfall during El Niño (Yasanayake et al. 2023 ; Zubair, 2002; Koralegedara et al. 2024), and the 2014/15 El Niño was fairly weak (Fig. S2; Dong and McPhaden 2018 ; Mayer and Balmaseda 2021 ). Therefore, the large seasonal rainfall anomaly cannot be linked to El Niño. However, rainfall responses concerning the MJO index were consistent with the above results in October, November, and December 2014, especially in December (Fig. S3). We thus turn to the MJO (Fig. 2 ). 2014 is associated with a larger-than-average number of days in MJO phases 2 and 3 (20%, against the long-term average of 15%), though this is lower than in 2015, also a very heavy rainfall year, where the MJO was in phase 2 or 3 in in over 45% of days. This contrast is even stronger if we only consider phase 3, which constitutes 16% of days in OND 2014, putting it in third place behind 2015 and 2002. This relationship between the MJO and seasonal relationship holds in general across all years, with a correlation of 0.4 between seasonal rainfall and number of days spent in phases 2 and 3. In other words, the asymmetry of the MJO explains about 20% of the interannual variance in Sri Lankan rainfall from October to December. Therefore, the following section focuses on rainfall variability in October- December 2014, hypothesizing that the observed rainfall variability over Sri Lanka may be attributed to the MJO activities during this year. We now analyze the intraseasonal variability within OND 2014 (Fig. 3 a), which exhibits several distinct peaks. The precipitation anomaly did not exceed 15 mm/day on any day in October 2014 but rose above this threshold several times in November, and surpassed it considerably for nearly a whole week during December. Therefore, we further show the MJO phase diagram to understand how it might influence the rainfall (Fig. 3 b). In October 2014, an inactive MJO was present in phase 3 over the Indian Ocean. However, in November 2014, the signal became stronger and propagated over Sri Lanka, where it appeared to stall for a week before propagating eastward over the Maritime Continent. However, it reappeared again over Sri Lanka in late December, where it again remained for over a week, before propagating eastward. The strong rainfall events within this season all occurred during MJO phase 3, consistent with the previous studies that showed more frequent extreme events over Sri Lanka are associated with MJO phases 2 and 3 during the northeast monsoon (Jayawardena et al. 2020). Furthermore, our analysis revealed that during the 2014 period, the MJO remained in Phase 3 for the long periods during November and December, with 15 active days during these two months, but no active days in October (Fig. 3 c), which is a notable departure from the climatological mean. Therefore, it is of the utmost importance to examine the rainfall patterns during October-December. The remainder of this study explores the mechanisms of the rainfall response. 3.2 Possible mechanism for record-breaking ra i nfall The spatial distribution of precipitation over the Indian Ocean (Fig. 4 a-c) and the associated circulation (Fig. 4 d-f) during OND 2014 indicate a very slight positive rainfall anomaly over Sri Lanka during October (Fig. 4 a). The rainfall anomaly then increased in magnitude, particularly over the eastern part of Sri Lanka during November (Fig. 4 b). However, in December, the precipitation anomaly over the wet zone of Sri Lanka becomes very intense and is also enhanced over much of the maritime continent (Fig. 4 c), pointing to the role of synoptic-scale organization in driving the overall seasonal anomaly. Yasanayake et al. ( 2023 ) emphasized that the low-level circulation and transport of moisture is one of the most common factors that determine the rainfall over Sri Lanka during the MJO. Negative OLR anomalies indicate consistent and widespread deep convection, especially in November and December. A weak anomalous cyclonic circulation and convection anomalies were also seen over the Bay of Bengal (BoB) near Sri Lanka during October (Fig. 4 d). This appeared to strengthen throughout both November-December (Fig. 4 e-f). Both the deep convection and low-level cyclonic circulation were strongest in December, resulting in strong moisture convergence from the BoB over Sri Lanka and thus more intense rainfall (Fig. 5 ). This is in line with the following Huang et al. ( 2023 ) which showed that the BoB is the primary source of moisture during the northeast monsoon period. To understand the anomalous Walker circulation over the Indian Ocean, we now look at vertical velocity averaged over Sri Lanka, 5°–10°N (Fig. 6 ). During October, the ascending branch of the anomalous Walker circulation lies over the western Indian Ocean and Sri Lanka, while its descending branch lies over the eastern Indian Ocean during the October (Fig. 6 a). It clearly indicates a weak upward motion over Sri Lanka (79°E–82°E) and a weak downward motion over the maritime continent (90°E–120°E). On the other hand, slightly enhanced upward motion over Sri Lanka and the maritime continent during November (Fig. 6 b). However, there is a strong upward motion in Sri Lanka during December reflecting a strong Walker circulation, convection, and moisture plays a major role in the rainfall over Sri Lanka (Fig. 6 c). Thus, our results are consistent with Huang et al. ( 2024 ) that a persistent, active MJO played a key role in forming and maintaining synoptic-scale cyclonic circulation in the tropics. 4 Discussion The present study highlights the influence of the MJO on Sri Lankan extreme rainfall. However, we have only shown that it is partially responsible, and thus we must acknowledge that other atmospheric variables, including the SST of the tropical Indian and Atlantic Oceans, could also significantly influence seasonal precipitation. Earlier studies have demonstrated that the climate effects of SST warming are widespread over tropical Indian Oceans (Roxy et al. 2015 ; Kajakokulan et al. 2023b ; Yadav and Roxy 2019 ). For example, the SST warming over the western Indian Ocean in the fall season may enhance the effect of the OND rainfall (Kajakokulan et al. 2023a ). Furthermore, Song et al. ( 2024 ) illustrated the influence of Rossby waves in supporting heavy precipitation over the Indo-Pacific rim on monthly to seasonal time scales. Further study is needed to understand the processes behind the formation of Rossby waves in the upper troposphere over Indian Oceans and their interactions with extreme rainfall events in Sri Lanka. Also, future projections of such phenomena based on reliable coupled climate models are important to confirm the present study findings. We advance a potentially valuable perspective on the impact of the Madden-Julian Oscillation (MJO) on Sri Lanka's October-November-December (OND) rainfall. During the second and third phases of the MJO, there is a likelihood of increased efficiency of water in Sri Lanka. On the other hand, during other phases, the efficiency of water is expected to decrease. This may potentially impact significant sectors such as tourism, irrigation, and agriculture, which are supportive factors for the social and economic of the country (Jayawardena et al. 2020; Crook et al. 2024 ; Huang et al. 2024 ). Therefore, it is likely that the findings of this study will help Sri Lanka to better understand and decision making how the country's OND rainfall responds to different phases of the MJO. 5 Conclusion In this study, we examine the variability of precipitation over Sri Lanka during October–December, both on interannual scales over the last forty years and on intraseasonal scales during the record-breaking 2014 season. We argue that an active MJO over Sri Lanka – i.e., in phases 2 and 3 – plays an important role in both. The present results are in line with those of previous studies by Huang et al. ( 2024 ), who found that extreme rainfall in Sri Lanka is associated with the MJO. We associated this with a long-lived synoptic-scale cyclonic circulation that persisted over near Sri Lanka for most of the season (Fig. 7 ). This leads to moisture convergence over and around Sri Lanka, supporting widespread deep convection. We also show that the long-lived active MJO of OND 2014, adjusted the Walker circulation leading to anomalous ascent over Sri Lanka, further supporting heavy seasonal rainfall. Thus, our analysis indicates that the MJO is an important factor significantly modulating rainfall in Sri Lanka. We also analysed 43 years of observational and reanalysis data from 1981 to 2023 to explore the role of the MJO in seasonal OND rainfall over Sri Lanka more generally. We found that seasons with heavier rainfall had significantly more days with an active MJO in phases 2 and 3, including the record-breaking seasons of 2014. Thus, these results have improved our knowledge of the mechanisms that cause heavy rainfall in Sri Lanka and explained the characteristics during 2014. Since we used reanalysis data, the mechanism behind the formation of cyclones in the lower troposphere over BOB during the MJO and its association with extreme rainfall using models needs to be further investigated. Declarations Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Competing Interests The authors have no relevant financial or non-financial interests to disclose. Author Contributions Data collection, formal analysis, investigation, conceptualization, methodology, software, and design were performed by Pathmarasa Kajakokulan. Kieran M R Hunt contributed to the supervision, editing, and validation. The first draft of the manuscript was written by Pathmarasa Kajakokulan, and all authors discussed the study results and reviewed the previous versions of the manuscript. All authors read and approved the final manuscript. Data Availability The CHIRPS dataset is available at https://data.chc.ucsb.edu/products/CHIRPS-2.0/. NCEP/NCAR dataset is from https://psl.noaa.gov/data/gridded/data.ncep.reanalysis.pressure.html. The RMM data is available online at http://www.bom.gov.au/climate/mjo/. 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J Geophys Res Atmos 124:5352–5378. https://doi.org/10.1029/2019JD030258 Supplementary Files MJOSupplementary.docx Cite Share Download PDF Status: Published Journal Publication published 11 Feb, 2026 Read the published version in Natural Hazards → Version 1 posted Editorial decision: Major revisions 21 Sep, 2025 Reviewers agreed at journal 16 Apr, 2025 Reviewers invited by journal 29 Jul, 2024 Editor assigned by journal 24 Jul, 2024 First submitted to journal 23 Jul, 2024 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. 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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-4786918","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":333005009,"identity":"395b11dd-4652-430a-8286-bcb586ba566c","order_by":0,"name":"Pathmarasa Kajakokulan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCUlEQVRIiWNgGAWjYBACCQaGBMYGhgQGPiDH+EcFkGRmbiBOCxuQU8xwBqSFkaAWBriWz4xtDBA+PiDZfuDhxxkVaYlt7GcPbi6cVxvN3w7U8qNiG04t0jwJyZIbzuQktvHkJRvP3HY8d8ZhxgbGnjO3cWqRY0hIkHzYVpHYxpBjZsC77VhuA1ALM2MbHi38D5J/grXwvzH/wTvnWO58QlqkJRLSJDe2AR0mkWNgzNtQk7uBkBbJGQ/SLGecSTNuk3hjYDjj2IHcjUAtB/H5ReJ8TvLNnopk2X7+HAODDzV1ufPOHz744EcFbi0MDDwJyLzDYPIAHvVAwI4iX4df8SgYBaNgFIxIAADE+WBKB0nlygAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0009-0007-7361-9620","institution":"University of Ruhuna","correspondingAuthor":true,"prefix":"","firstName":"Pathmarasa","middleName":"","lastName":"Kajakokulan","suffix":""},{"id":344223544,"identity":"3fff0043-dda6-4780-950b-b6c83db01168","order_by":1,"name":"Kieran M R Hunt","email":"","orcid":"","institution":"Department of Meteorology, University of Reading, Reading, United Kingdom.","correspondingAuthor":false,"prefix":"","firstName":"Kieran","middleName":"M R","lastName":"Hunt","suffix":""}],"badges":[],"createdAt":"2024-07-23 08:26:28","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4786918/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4786918/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s11069-025-07932-7","type":"published","date":"2026-02-11T15:57:11+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":63098800,"identity":"4428477b-bbeb-4b0f-8028-42b9d77ccb14","added_by":"auto","created_at":"2024-08-23 06:29:18","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":551294,"visible":true,"origin":"","legend":"\u003cp\u003ea) Elevation map of SL and rainfall station marked with the red circle, b) climatology of SL rainfall (ERA5: red, CHIRPS: blue) error bar represents the standard deviation, c) time series of OND rainfall anomaly over Sri Lanka. Rainfall anomaly during 2014 d) October, e) November, f) December from CHIRPS data. In addition, the green bar indicates the highest rainfall year (2014 events) from 1981 to 2023.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4786918/v1/19c961e6ed4bb51bcb26923a.png"},{"id":63098232,"identity":"a6688534-d01f-4c74-b9d3-904e1f132edd","added_by":"auto","created_at":"2024-08-23 06:21:18","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":281115,"visible":true,"origin":"","legend":"\u003cp\u003eRole of the MJO in driving seasonal rainfall. Years are sorted by mean OND rainfall over Sri Lanka, then in (a) a stacked histogram shows the number of days in each season spent in each phase of the MJO, and in (b) the seasonal totals are given. Any phase where the normalized amplitude is less than 1 is referred to as MJO phase 0.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-4786918/v1/bcc24f3488051ff686aab4b3.png"},{"id":63098802,"identity":"2762d6bc-a7ac-4c83-ba7b-95d2fc063501","added_by":"auto","created_at":"2024-08-23 06:29:18","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":325791,"visible":true,"origin":"","legend":"\u003cp\u003ea) Time series of October-December rainfall anomaly over Sri Lanka during 2014 using CHIRPS data. The blue and red bars represent rainfall anomalies in November, and December respectively during phase 3. b) MJO phase diagram during October-December 2014, c) number of MJO active days (red bars) in phase 3 during the October-December 2014 and climatological mean (blue bars).\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-4786918/v1/acf6b66e73dd4faa07a895dc.png"},{"id":63098252,"identity":"f400a2d6-7fc9-4d17-a037-e8753692dd60","added_by":"auto","created_at":"2024-08-23 06:21:19","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1637179,"visible":true,"origin":"","legend":"\u003cp\u003ea) Precipitation anomalies during 2014, a) October b) November, c) December. OLR anomalies (color shading) and low-level wind anomalies (850 hPa, vector) during d) October e) November, f) December.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-4786918/v1/4a39c0510ab542fa1288ce57.png"},{"id":63098803,"identity":"9e2a25d9-2f00-4e56-b6a1-6fa5e722b762","added_by":"auto","created_at":"2024-08-23 06:29:18","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":830776,"visible":true,"origin":"","legend":"\u003cp\u003ea) VIMFC anomalies during 2014, a) October, b) November, c) December, d) as a), e) as b) and f) as c) but for TCC.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-4786918/v1/c27e63c7e1f2ff0eb94bf2d5.png"},{"id":63099455,"identity":"7bcbf2de-73c3-497b-9539-443604bfeca4","added_by":"auto","created_at":"2024-08-23 06:37:18","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":443516,"visible":true,"origin":"","legend":"\u003cp\u003ea) Omega (averaged over Sri Lanka, 5\u003csup\u003eo\u003c/sup\u003e - 10\u003csup\u003eo\u003c/sup\u003e N) anomalies during 2014, a) October, b) November, and c) December. The white boxes represent the Sri Lanka region.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-4786918/v1/cb0d80257bb0bead535c26b6.png"},{"id":63098238,"identity":"847a43ee-383d-4ecc-8c11-b495daf9323c","added_by":"auto","created_at":"2024-08-23 06:21:18","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":944303,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic diagram summarizing the mechanism for the impact of MJO on rainfall during November and December 2014. Rainfall is shading, the black arrow represents the MJO phases, and the brown vector represents the walker circulation.\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-4786918/v1/f9263ca1b91ba9b0779ab1b1.png"},{"id":102785272,"identity":"4c3d0bfb-f235-48ee-b1be-f7160b7f978e","added_by":"auto","created_at":"2026-02-16 16:03:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4445362,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4786918/v1/eb724447-7777-45f6-950d-25ed110aa466.pdf"},{"id":63098801,"identity":"4021f4de-d9e9-4461-821e-e232823e29f1","added_by":"auto","created_at":"2024-08-23 06:29:18","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":631341,"visible":true,"origin":"","legend":"","description":"","filename":"MJOSupplementary.docx","url":"https://assets-eu.researchsquare.com/files/rs-4786918/v1/f4a8696af31c97721945b28e.docx"}],"financialInterests":"","formattedTitle":"Record-breaking rainfall in Sri Lanka in 2014 enhanced by the MJO","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eRainfall has a substantial influence on many sectors, including agriculture, water resources, climate, water resource management, and ecological modeling (Cavalcante et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Heavy to extreme rainfall is a natural hazard that frequently results in fatalities, flooding, and erosion (Marengo et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Sri Lanka ranks as the most climate change-vulnerable country in the world, which has an impact on the natural resources of the island (De Silva and Kawasaki \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The central highlands are particularly susceptible to the consequences of climate change, as evidenced by a high frequency of very heavy rainfall (Weerasekara et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Sri Lanka's standing in the Indian Ocean and topographical features make it susceptible to monsoon flooding (Amanda et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The southwest part of Sri Lanka (wet zone) is particularly vulnerable to flooding during the south-west monsoon, which occurs between May and September (Filho \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). On the other hand, the north and east of the island are at risk during the north-east monsoon, which spans from December to February (Kajakokulan et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2023a\u003c/span\u003e). In addition, the north-central, south-eastern, and north-western parts of the island are the most susceptible to drought, primarily due to low rainfall, while floods frequent over the wet zones due to high rainfall (De Silva and Kawasaki \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Rainfall events with a historic two-year return period are becoming more frequent owing to climate change (Myhre et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Sri Lanka, for example, experienced major flooding events during the northeast monsoon seasons of 2010, 2011, and 2014 (Alahacoon and Edirisinghe \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Koralegedara et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) showed that these extreme rainfall events arise from moisture supply from both the Bay of Bengal (BoB) and the Arabian Sea (AS), combined with locally enhanced moisture flux convergence and deep convection. Such events can occur during the first inter-monsoon season (March-April) and the second inter-monsoon season (October\u0026ndash;November) and can arise from low-pressure systems, tropical cyclones, or mesoscale convective systems.\u003c/p\u003e \u003cp\u003eThe El Ni\u0026ntilde;o Southern Oscillation (ENSO) is a major mode over the Pacific Ocean that significantly affects the atmosphere and ocean in both the tropics and extratropics (Mayer and Balmaseda \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). On the other hand, the Madden\u0026ndash;Julian Oscillation (MJO) represents the most significant mode of intraseasonal variability in the tropical Indian Ocean, primarily affecting countries along its edges (Li et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). It is an eastward-propagating phenomenon centered around the equator, with a characteristic time scale of 30\u0026ndash;60 days (Madden and Julian 1972), and the duration of the cycle can extend to 100 days (Zheng and Chang \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Martin et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The MJO has a life cycle divided into eight phases: formation in the western Indian Ocean (Phase 1), still located in the Indian Ocean but has moved south of SL and (Phases 2 and 3), and into the Maritime Continent (Phases 4 and 5), advancing through the western and eastern Pacific (Phases 6 and 7), and decaying in the central Pacific (Phase 8; Huang et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Over the past decade, numerous hypotheses have been developed to explain the dynamics of the MJO, including the moisture-mode theory by Adames and Kim (2016), the gravity-wave theory by Dennison, Brewer, Arnold (2014), the trio-interaction theory by Wang et al. (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), and the skeleton theory by Majda and Stechmann (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Moreover, MJO propagation is also influenced by ENSO during the winter over the Indian Ocean (Li et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The interannual rainfall variability over South Asia during the winter is influenced by the MJO where strengthened easterly wind controls the convergence of moisture from the Arabian Sea. For example, Xavier et al. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) emphasized that the phases of the MJO which enhance local convection increase the probability of extreme rainfall events over the South Asian region. It is, therefore, of great importance to understand rainfall response to the MJO, given the significance of increasing frequency of the MJO under climate change (Liang et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) .\u003c/p\u003e \u003cp\u003eSeveral studies have documented the influence of the MJO on daily, monthly, and seasonal precipitation in South Asia (Bagtasa \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Lenka et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Crook et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Almazroui \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Nevertheless, only a limited number of studies have investigated the impact of MJO on rainfall patterns and the associated mechanisms in Sri Lanka (Jayawardena et al. 2020; Yasanayake et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Deoras et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Jayawardena et al. (2020) investigated the impact of the MJO on Sri Lankan rainfall and found that the most significant impact is during the second inter-monsoon and southwest monsoon seasons. Likewise, more extreme precipitation events occur in Sri Lanka during the northeast-monsoon and second inter-monsoon seasons than in the southwest monsoon and first inter-monsoon season (Deoras et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Recent studies emphasized that rainfall exhibits a tendency to increase (decrease) during the P2-P3 (P6-P7) MJO phases, particularly during the spring and autumn seasons (Huang et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Thus, the present study employs in situ observations along with reanalysis data to investigate the role of the Madden-Julian Oscillation (MJO) on the occurrence of record-breaking rainfall events in Sri Lanka over the past four decades and specifically during the 2014 OND season.\u003c/p\u003e \u003cp\u003eThis study is organized as follows: section \u003cspan refid=\"Sec2\" class=\"InternalRef\"\u003e2\u003c/span\u003e outlines an overview of the datasets utilized and methodology in the present study, and sections \u003cspan refid=\"Sec5\" class=\"InternalRef\"\u003e3\u003c/span\u003e and \u003cspan refid=\"Sec8\" class=\"InternalRef\"\u003e4\u003c/span\u003e provide the results and a detailed discussion of the findings. Finally, section \u003cspan refid=\"Sec9\" class=\"InternalRef\"\u003e5\u003c/span\u003e outlines the conclusions drawn from the analysis.\u003c/p\u003e"},{"header":"2 Data and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Data\u003c/h2\u003e \u003cp\u003eThe data on daily precipitation was obtained from Climate Hazards Group InfraRed Precipitation (Funk et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). ERA5 is a fifth-generation reanalysis dataset that provides hourly precipitation, total cloud cover (TCC), and outgoing longwave radiation (OLR) data from the European Centre for Medium-Range Weather Forecasting (ECWMF, Hersbach et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). MJO indices, namely the real-time multivariate MJO (or RMM) index, were obtained from the Australian Bureau of Meteorology (Wheeler and Hendon \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2004\u003c/span\u003e), and the present study period is 43 years (1981\u0026ndash;2023) The in-situ observation data is available from the Department of Meteorology, Sri Lanka, and the data can be accessed upon request.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Method\u003c/h2\u003e \u003cp\u003eObservation of rainfall data from the ground weather stations of the Sri Lanka Meteorological Department (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea) was used as a reference to validate the CHIRPS and ERA5 daily rainfall data (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). First, the rainy season with the highest rainfall in Sri Lanka is October\u0026ndash;December (OND). This is then used to define the Sri Lanka rainfall index, which is the area-averaged OND rainfall over Sri Lankan land. Second, we identify years with unusually heavy OND seasonal rainfall from 1981 to 2023, linking these to the MJO behaviour. Finally, a composite analysis is conducted to evaluate the influence of MJO on SL precipitation during rainfall events in Sri Lanka. The VIMFC is calculated as horizontal moisture flux convergence integrated from 1000hPa to 300hPa. Moreover, the present study calculated anomalies based on the climatology period 1981\u0026ndash;2023 after removing both seasonality and the long-term linear trend.\u003c/p\u003e \u003c/div\u003e"},{"header":"3 Results","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Rainfall climatology and characteristics of rainfall anomalies over Sri Lanka in 2014.\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003ePrevious studies have consistently demonstrated that the primary annual peak in rainfall occurs in October, November, and December (OND) with a secondary peak in March, April, and May (MAM), indicating a bimodal rainfall pattern Huang et al. (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Our results (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb) corroborate previous studies showing that Sri Lanka exhibits a bimodal rainfall pattern, with the two rainfall peaks occurring during OND and MAM. Of these two seasons, OND has the larger mean and the higher interannual standard deviation. Therefore, we show the interannual variability of OND rainfall from 1981 to 2023 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec). The rainfall anomalies exhibit a strong interannual variability but with a significant positive trend. The largest seasonal anomaly was in 2014, following a notable negative rainfall anomaly in 2013. We further show spatial rainfall anomalies during October, November, and December 2014 separately to assess their respective contributions (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ed-f). The positive rainfall anomaly exceeded 4 mm/day of precipitation during October over the wet zone of Sri Lanka. However, the whole of Sri Lanka, especially the north-eastern region, experienced the strongest positive rainfall anomaly during December. Sri Lanka experienced reduced December rainfall during El Ni\u0026ntilde;o (Yasanayake et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Zubair, 2002; Koralegedara et al. 2024), and the 2014/15 El Ni\u0026ntilde;o was fairly weak (Fig. S2; Dong and McPhaden \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Mayer and Balmaseda \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Therefore, the large seasonal rainfall anomaly cannot be linked to El Ni\u0026ntilde;o. However, rainfall responses concerning the MJO index were consistent with the above results in October, November, and December 2014, especially in December (Fig. S3).\u003c/p\u003e \u003cp\u003eWe thus turn to the MJO (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). 2014 is associated with a larger-than-average number of days in MJO phases 2 and 3 (20%, against the long-term average of 15%), though this is lower than in 2015, also a very heavy rainfall year, where the MJO was in phase 2 or 3 in in over 45% of days. This contrast is even stronger if we only consider phase 3, which constitutes 16% of days in OND 2014, putting it in third place behind 2015 and 2002. This relationship between the MJO and seasonal relationship holds in general across all years, with a correlation of 0.4 between seasonal rainfall and number of days spent in phases 2 and 3. In other words, the asymmetry of the MJO explains about 20% of the interannual variance in Sri Lankan rainfall from October to December. Therefore, the following section focuses on rainfall variability in October- December 2014, hypothesizing that the observed rainfall variability over Sri Lanka may be attributed to the MJO activities during this year.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe now analyze the intraseasonal variability within OND 2014 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea), which exhibits several distinct peaks. The precipitation anomaly did not exceed 15 mm/day on any day in October 2014 but rose above this threshold several times in November, and surpassed it considerably for nearly a whole week during December. Therefore, we further show the MJO phase diagram to understand how it might influence the rainfall (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb). In October 2014, an inactive MJO was present in phase 3 over the Indian Ocean. However, in November 2014, the signal became stronger and propagated over Sri Lanka, where it appeared to stall for a week before propagating eastward over the Maritime Continent. However, it reappeared again over Sri Lanka in late December, where it again remained for over a week, before propagating eastward. The strong rainfall events within this season all occurred during MJO phase 3, consistent with the previous studies that showed more frequent extreme events over Sri Lanka are associated with MJO phases 2 and 3 during the northeast monsoon (Jayawardena et al. 2020). Furthermore, our analysis revealed that during the 2014 period, the MJO remained in Phase 3 for the long periods during November and December, with 15 active days during these two months, but no active days in October (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec), which is a notable departure from the climatological mean. Therefore, it is of the utmost importance to examine the rainfall patterns during October-December. The remainder of this study explores the mechanisms of the rainfall response.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e\u003cb\u003e3.2 Possible mechanism for record-breaking ra\u003c/b\u003ei\u003cb\u003enfall\u003c/b\u003e\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe spatial distribution of precipitation over the Indian Ocean (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea-c) and the associated circulation (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed-f) during OND 2014 indicate a very slight positive rainfall anomaly over Sri Lanka during October (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea). The rainfall anomaly then increased in magnitude, particularly over the eastern part of Sri Lanka during November (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb). However, in December, the precipitation anomaly over the wet zone of Sri Lanka becomes very intense and is also enhanced over much of the maritime continent (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec), pointing to the role of synoptic-scale organization in driving the overall seasonal anomaly. Yasanayake et al. (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) emphasized that the low-level circulation and transport of moisture is one of the most common factors that determine the rainfall over Sri Lanka during the MJO. Negative OLR anomalies indicate consistent and widespread deep convection, especially in November and December. A weak anomalous cyclonic circulation and convection anomalies were also seen over the Bay of Bengal (BoB) near Sri Lanka during October (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed). This appeared to strengthen throughout both November-December (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ee-f). Both the deep convection and low-level cyclonic circulation were strongest in December, resulting in strong moisture convergence from the BoB over Sri Lanka and thus more intense rainfall (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). This is in line with the following Huang et al. (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) which showed that the BoB is the primary source of moisture during the northeast monsoon period.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo understand the anomalous Walker circulation over the Indian Ocean, we now look at vertical velocity averaged over Sri Lanka, 5\u0026deg;\u0026ndash;10\u0026deg;N (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). During October, the ascending branch of the anomalous Walker circulation lies over the western Indian Ocean and Sri Lanka, while its descending branch lies over the eastern Indian Ocean during the October (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea). It clearly indicates a weak upward motion over Sri Lanka (79\u0026deg;E\u0026ndash;82\u0026deg;E) and a weak downward motion over the maritime continent (90\u0026deg;E\u0026ndash;120\u0026deg;E). On the other hand, slightly enhanced upward motion over Sri Lanka and the maritime continent during November (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eb). However, there is a strong upward motion in Sri Lanka during December reflecting a strong Walker circulation, convection, and moisture plays a major role in the rainfall over Sri Lanka (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ec). Thus, our results are consistent with Huang et al. (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) that a persistent, active MJO played a key role in forming and maintaining synoptic-scale cyclonic circulation in the tropics.\u003c/p\u003e \u003c/div\u003e"},{"header":"4 Discussion","content":"\u003cp\u003eThe present study highlights the influence of the MJO on Sri Lankan extreme rainfall. However, we have only shown that it is partially responsible, and thus we must acknowledge that other atmospheric variables, including the SST of the tropical Indian and Atlantic Oceans, could also significantly influence seasonal precipitation. Earlier studies have demonstrated that the climate effects of SST warming are widespread over tropical Indian Oceans (Roxy et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Kajakokulan et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2023b\u003c/span\u003e; Yadav and Roxy \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). For example, the SST warming over the western Indian Ocean in the fall season may enhance the effect of the OND rainfall (Kajakokulan et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2023a\u003c/span\u003e). Furthermore, Song et al. (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) illustrated the influence of Rossby waves in supporting heavy precipitation over the Indo-Pacific rim on monthly to seasonal time scales. Further study is needed to understand the processes behind the formation of Rossby waves in the upper troposphere over Indian Oceans and their interactions with extreme rainfall events in Sri Lanka. Also, future projections of such phenomena based on reliable coupled climate models are important to confirm the present study findings.\u003c/p\u003e \u003cp\u003eWe advance a potentially valuable perspective on the impact of the Madden-Julian Oscillation (MJO) on Sri Lanka's October-November-December (OND) rainfall. During the second and third phases of the MJO, there is a likelihood of increased efficiency of water in Sri Lanka. On the other hand, during other phases, the efficiency of water is expected to decrease. This may potentially impact significant sectors such as tourism, irrigation, and agriculture, which are supportive factors for the social and economic of the country (Jayawardena et al. 2020; Crook et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Huang et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Therefore, it is likely that the findings of this study will help Sri Lanka to better understand and decision making how the country's OND rainfall responds to different phases of the MJO.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"5 Conclusion","content":"\u003cp\u003eIn this study, we examine the variability of precipitation over Sri Lanka during October\u0026ndash;December, both on interannual scales over the last forty years and on intraseasonal scales during the record-breaking 2014 season. We argue that an active MJO over Sri Lanka \u0026ndash; i.e., in phases 2 and 3 \u0026ndash; plays an important role in both. The present results are in line with those of previous studies by Huang et al. (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), who found that extreme rainfall in Sri Lanka is associated with the MJO. We associated this with a long-lived synoptic-scale cyclonic circulation that persisted over near Sri Lanka for most of the season (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). This leads to moisture convergence over and around Sri Lanka, supporting widespread deep convection. We also show that the long-lived active MJO of OND 2014, adjusted the Walker circulation leading to anomalous ascent over Sri Lanka, further supporting heavy seasonal rainfall. Thus, our analysis indicates that the MJO is an important factor significantly modulating rainfall in Sri Lanka. We also analysed 43 years of observational and reanalysis data from 1981 to 2023 to explore the role of the MJO in seasonal OND rainfall over Sri Lanka more generally. We found that seasons with heavier rainfall had significantly more days with an active MJO in phases 2 and 3, including the record-breaking seasons of 2014. Thus, these results have improved our knowledge of the mechanisms that cause heavy rainfall in Sri Lanka and explained the characteristics during 2014. Since we used reanalysis data, the mechanism behind the formation of cyclones in the lower troposphere over BOB during the MJO and its association with extreme rainfall using models needs to be further investigated.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData collection, formal analysis, investigation, conceptualization, methodology, software, and design were performed by Pathmarasa Kajakokulan. Kieran M R Hunt contributed to the supervision, editing, and validation. The first draft of the manuscript was written by Pathmarasa Kajakokulan, and all authors discussed the study results and reviewed the previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe CHIRPS dataset is available at https://data.chc.ucsb.edu/products/CHIRPS-2.0/. NCEP/NCAR dataset is from https://psl.noaa.gov/data/gridded/data.ncep.reanalysis.pressure.html. The RMM data is available online at http://www.bom.gov.au/climate/mjo/. The ERA5 data is available at https://cds.climate.copernicus.eu/#!/. The in-situ observation data is available from the Department of Meteorology, Sri Lanka, and the data can be accessed upon request.\u003c/p\u003e\n\u003cp\u003e\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAlahacoon N, Edirisinghe M (2021) Spatial variability of rainfall trends in sri lanka from 1989 to 2019 as an indication of climate change. ISPRS Int J Geo-Information 10:. https://doi.org/10.3390/ijgi10020084\u003c/li\u003e\n\u003cli\u003eAlmazroui M (2023) The Influence of the Madden\u0026ndash;Julian Oscillation on the Wet Season Rainfall over Saudi Arabia. Earth Syst Environ 7:1\u0026ndash;14. https://doi.org/10.1007/s41748-022-00334-w\u003c/li\u003e\n\u003cli\u003eAmanda MK, Asmath AMM, Niflah MRF (2021) Effects of flood during the last decade in Sri Lanka\u003c/li\u003e\n\u003cli\u003eBagtasa G (2020) Influence of madden-julian oscillation on the intraseasonal variability of summer and winter monsoon rainfall in the Philippines. 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Ecol Econ 185:. https://doi.org/10.1016/j.ecolecon.2021.107043\u003c/li\u003e\n\u003cli\u003eWheeler MC, Hendon HH (2004) An all-season real-time multivariate MJO index: Development of an index for monitoring and prediction. Mon Weather Rev 132:1917\u0026ndash;1932. https://doi.org/10.1175/1520-0493(2004)132\u0026lt;1917:AARMMI\u0026gt;2.0.CO;2\u003c/li\u003e\n\u003cli\u003eXavier P, Rahmat R, Cheong WK, Wallace E (2014) Geophysical Research Letters - 2014 - Xavier - Influence of Madden‐Julian Oscillation on Southeast Asia rainfall extremes .pdf. Geophys. Res. Lett. 41:4406\u0026ndash;4412\u003c/li\u003e\n\u003cli\u003eYadav RK, Roxy MK (2019) On the relationship between north India summer monsoon rainfall and east equatorial Indian Ocean warming. Glob Planet Change 179:23\u0026ndash;32. https://doi.org/10.1016/j.gloplacha.2019.05.001\u003c/li\u003e\n\u003cli\u003eYasanayake CN, Zaitchik BF, Gnanadesikan A (2023) Seasonal Modulation of the Madden\u0026ndash;Julian Oscillation\u0026rsquo;s Impact on Rainfall in Sri Lanka. J Clim 36:7231\u0026ndash;7255. https://doi.org/10.1175/JCLI-D-22-0590.1\u003c/li\u003e\n\u003cli\u003eZheng C, Chang EKM (2019) The Role of MJO Propagation, Lifetime, and Intensity on Modulating the Temporal Evolution of the MJO Extratropical Response. J Geophys Res Atmos 124:5352\u0026ndash;5378. https://doi.org/10.1029/2019JD030258\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"natural-hazards","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nhaz","sideBox":"Learn more about [Natural Hazards](https://www.springer.com/journal/11069)","snPcode":"11069","submissionUrl":"https://submission.nature.com/new-submission/11069/3","title":"Natural Hazards","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Madden Julian Oscillation, moisture convergence, extreme rainfall, Sri Lanka","lastPublishedDoi":"10.21203/rs.3.rs-4786918/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4786918/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSri Lanka has experienced a number of severe floods over the past decades, illustrating the importance of understanding the events leading to extreme rainfall. The Madden-Julian Oscillation (MJO), an intraseasonal phenomenon over the tropical ocean, strongly influences interannual precipitation variability in Sri Lanka. However, the impact of the MJO on rainfall over Sri Lanka during the October-November-December (OND) period is less well understood. In this study, we use reanalysis data to explore the impact of the MJO on Sri Lankan rainfall during this season. We show that OND seasons with heavier-than-usual rainfall typically have more days where an active MJO is in phases 2 and 3 and that this is also true for 2014, where both November and December experienced about a week of strong phase 3 MJO. This led to a persistent synoptic-scale circulation anomaly over Sri Lanka, which increased moisture convergence over the island, leading to widespread and long-lived deep convection. We also argue that the persistent 2014 MJO events adjusted the Walker circulation, leading to anomalous ascent over Sri Lanka, which further amplified the seasonal rainfall. This study shows that a better understanding of the link between the MJO and local thermodynamics is needed to improve extreme precipitation forecasts over Sri Lanka.\u003c/p\u003e","manuscriptTitle":"Record-breaking rainfall in Sri Lanka in 2014 enhanced by the MJO","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-23 06:21:13","doi":"10.21203/rs.3.rs-4786918/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revisions","date":"2025-09-21T07:10:54+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2025-04-16T13:43:10+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-07-29T07:08:07+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-07-24T12:26:33+00:00","index":"","fulltext":""},{"type":"submitted","content":"Natural Hazards","date":"2024-07-23T04:14:34+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"natural-hazards","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nhaz","sideBox":"Learn more about [Natural Hazards](https://www.springer.com/journal/11069)","snPcode":"11069","submissionUrl":"https://submission.nature.com/new-submission/11069/3","title":"Natural Hazards","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"0ef04714-802a-4671-b19d-4124a6e63415","owner":[],"postedDate":"August 23rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-02-16T16:01:17+00:00","versionOfRecord":{"articleIdentity":"rs-4786918","link":"https://doi.org/10.1007/s11069-025-07932-7","journal":{"identity":"natural-hazards","isVorOnly":false,"title":"Natural Hazards"},"publishedOn":"2026-02-11 15:57:11","publishedOnDateReadable":"February 11th, 2026"},"versionCreatedAt":"2024-08-23 06:21:13","video":"","vorDoi":"10.1007/s11069-025-07932-7","vorDoiUrl":"https://doi.org/10.1007/s11069-025-07932-7","workflowStages":[]},"version":"v1","identity":"rs-4786918","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4786918","identity":"rs-4786918","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}