{"paper_id":"40bd3fcf-459c-40e0-97a6-fa428d67aa6c","body_text":"Analyzing the Role of the Madden–Julian Oscillation and Indian Ocean Dipole in Shaping Rainfall Patterns in West Sumatra | 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 Analyzing the Role of the Madden–Julian Oscillation and Indian Ocean Dipole in Shaping Rainfall Patterns in West Sumatra Siltia Wahyuni, Nofi Yendri Sudiar, Harman Amir, Hamdi Hamdi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7434891/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 Weather and climate variability in Indonesia result from complex interactions between global, regional, and local phenomena. One of the phenomena affecting rainfall in Indonesia, particularly in West Sumatra Province, is the Madden Julian Oscillation (MJO) and the Dipole Mode (IOD). To improve the accuracy of daily weather prediction, an analysis of the relationship between weather and MJO and IOD phenomena in West Sumatra was conducted using the wavelet transform method. The study used daily rainfall data recorded by ARG, AWS, and Rain Post instruments distributed across 16 locations in West Sumatra, covering the observation period from 2015 to 2024. The results showed that the MJO influences rainfall in West Sumatra with oscillation periods of 31–50 days in the lowland and coastal areas of the western part of the region. The IOD affects rainfall in the hilly and eastern lowland areas, with longer oscillation periods of 53–66 days. During a negative IOD phase, the MJO increases the effectiveness of convective cloud formation, as observed from the Hovmöller diagram analysis. The correlation between OLR and IOD was found to be 0.54, while the correlation with MJO was negative, ranging from −0.18 to −0.28, indicating that local factors still predominantly influence. MJO IOD OLR Rainfall Wavelet Hovmöller diagram Figures Figure 1 Figure 2 Figure 3 1. Introduction Indonesia is one of the largest archipelagic countries in the world. Its position as a tropical archipelago gives rise to unique and diverse geographical, climatological, geological, and demographic phenomena. On the one hand, these conditions make Indonesia highly vulnerable to various natural activities such as extreme weather. Climate and weather variability in Indonesia is the result of complex interactions among global, regional, and local phenomena. Global phenomena such as El Niño/La Niña, the Indian Ocean Dipole (IOD) (Sudirman et al., 2024 ), and the Madden–Julian Oscillation (MJO) (Windayati & Surinati, 2016 ) have significant impacts on weather patterns across the Indonesian Archipelago. At the local scale, topography and the distribution of seas also play important roles in shaping microclimates and local weather patterns. Rainfall in Southeast Asia is strongly influenced by global climate variability such as the El Niño–Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD). Since rainfall data are inherently non-stationary and complex, analytical methods that can capture changes in both frequency and time simultaneously are required. Xie & Liu ( 2019 ) employed Wavelet Transform and Empirical Mode Decomposition (EMD) to analyze long-term rainfall variability in this region. They found a dominant annual cycle (~ 12 months) and interannual scales (~ 2–7 years) in rainfall variations. The results also showed that El Niño events strongly reduced rainfall in Indonesia and Malaysia, particularly during 1997–1998. The correlation between rainfall and ENSO/IOD was found to be dynamic and varied depending on time and location. Wavelet Transform proved to be more sensitive in detecting temporal scale changes compared to classical statistical techniques. Global phenomena that may influence weather and climate in West Sumatra include the Indian Ocean Dipole (IOD) and Madden–Julian Oscillation (MJO) (Millenia et al., 2023). The IOD represents an interannual climate variability in the tropical Indian Ocean (Polonsky & Torbinsky, 2021). It can also be defined as an ocean–atmosphere coupled phenomenon that strongly affects the global climate, land, and ocean. The Dipole Mode Index (DMI), defined as the difference in sea surface temperature anomalies between the eastern and western IOD regions, has long been used to characterize and measure the strength of IOD events. The IOD significantly influences the Indo-Pacific climate. Observations indicate a shift toward stronger and earlier positive IOD (pIOD) events along with increasing amplitudes of sea surface temperature anomalies. However, uncertainties remain, limiting the assessment of ongoing changes (Wang et al., 2024). The IOD is identified in two phases: positive and negative. A positive dipole mode is characterized by warmer sea surface temperatures in the Western Tropical Indian Ocean (WTIO) and cooler temperatures in the Southeastern Tropical Indian Ocean (SETIO). Conversely, when the WTIO is cooler than neutral and the SETIO is warmer than neutral, the condition is classified as a negative dipole mode (Koesuma et al., 2021). Based on previous studies, the present research aims to examine how MJO and IOD influence rainfall variability in West Sumatra, with the objective of providing useful references for weather forecasting, particularly rainfall prediction. 2. Method 2.1 Data Sources The data used in this study include: 1. Madden–Julian Oscillation (MJO) Monitoring Data, s ource: Real-time Multivariate MJO indices (Amplitude) obtained from the International Research Institute for Climate and Society (IRI) website https://iridl.ldeo.columbia.edu/SOURCES/.BoM/.MJO/.RMM/index.html?Set-Language=en , Period: 2015–2024. 2. MJO phases consist of eight phases, which were further grouped into four regions based on the MJO propagation illustrated in the Wheeler and Hendon diagram (M. C. Wheeler & Hendon, 2004). Considering the study area, the phases analyzed were Indian Ocean (phases 2 & 3) and Maritime Continent (phase 4) . 3. Indian Ocean Dipole (IOD) Index, s ource: NOAA accessible via [https://www.cpc.ncep.noaa.gov/products/international/ocean_monitoring/indian/IODMI/DMI_month.html] (Center, 2025), represents sea surface temperature anomalies in the eastern tropical Indian Ocean and is used to identify IOD events, period: 2015–2024 (Huang et al., 2015). 4. Rainfall Data, source: Meteorology, Climatology, and Geophysics Agency of Indonesia (BMKG), period: 2015–2024, locations: Rao Pasaman, Solok, Linggosari Baganti, SMPK Tanah Datar, Sijunjung, Ampek Nagari, Sungai Dareh, Batang Kapas, Guguak, Sungai Limau, Solok Selatan, Sipora Jaya, AWS Pasaman Barat, AWS Meteorological Station Minangkabau, Maritime Station Teluk Bayur, and Rainfall Station Nanggalo. 5. Outgoing Longwave Radiation (OLR) Data, s ource: Daily Climate Data Record (CDR) – PSL Interpolated OLR (monthly scale), accessible at [https://psl.noaa.gov/data/gridded/data.interp_OLR.html], period: 2015–2024, used to identify convective activity and atmospheric variability associated with MJO and IOD events. 2.2 Method 1. Band-pass Filtering of MJO Signal. A Butterworth band-pass filter was applied to the MJO indices to isolate variability in the 20–80-day band, aligned with the canonical MJO timescale (Mitra, 2011). Subsequent analyses focused on MJO phases 2, 3, and 4 . 2. Pearson Correlation Analyse. Pearson’s correlation was used to quantify linear relationships between rainfall (CH) and the MJO as well as the IOD (Moore et al., 2017). 3. Relationship to Atmospheric Modes. We examined links between each study variable and (i) the MJO, (ii) positive IOD , and (iii) negative IOD , presenting results as graphs and wavelet spectra to assess the influence of these phenomena on rainfall over service areas of ARG, AWS, and manual rain gauge stations in West Sumatra Province. 4. Hovmöller Diagnostic. Hovmöller diagrams were constructed for MJO phases 2, 3, and 4 during positive , negative , and neutral IOD conditions. 5. Comparative Assessment (MJO vs. IOD vs. Combined). We compared the impacts of the MJO, the IOD, and their combined occurrence on local rainfall conditions at the study sites. 6. OLR–IOD Consistency Check. OLR data on a 2.5° × 2.5° grid were analyzed as time series plots and correlated with the monthly-resolution IOD index to evaluate the coherence of convective patterns with IOD variability. 7. Event Sampling for Concurrent MJO–IOD Conditions. Case sampling was performed to investigate concurrent MJO and IOD influences using DMI-based IOD events : positive IOD in October 2019 (DMI = 1.78) , negative IOD in August 2022 (DMI = −1.17) , and neutral IOD in May 2023 (DMI = 0.02) . Monitoring values were taken from NASA’s IOD page: https://sealevel.jpl.nasa.gov/data/vital-signs/indian-ocean-dipole/. 3. RESULTS and Discussion 3.1 Wavelet Analysis Data segmentation was conducted to isolate the periods when the MJO was active, allowing rainfall (CH) data to be extracted specifically during active MJO phases. A band-pass filter was applied to the rainfall data to separate signals in the 20–80-day range prior to wavelet analysis. This ensured comparability with the MJO oscillation period, which generally spans 30–60 days (Zhang et al., 2020). Wavelet analysis was performed using the Continuous Morlet Wavelet Transform implemented in Python, with the non-dimensional frequency parameter set to ω₀ = 6, following Torrence & Compo (1998). This method enables identification of dominant time–frequency variability in rainfall data and its correspondence to MJO and IOD timescales. Figure 2 presents the wavelet output for rainfall data at the Nanggalo Rainfall Station, which is representative of the results obtained from other ARG, AWS, and rainfall observation stations across West Sumatra. Extraction of rainfall period and power (mm²) from the Global Wavelet Spectrum (GWS) at each ARG, AWS, and rainfall station in West Sumatra during 2015–2024, as illustrated in Figure 2, was summarized in Table 1, which presents the maximum oscillation period at each station. The oscillation periods of rainfall (CH) were found to range between 31–66 days, which corresponds to the general MJO oscillation band of 30–60 days. This indicates that the rainfall patterns observed in West Sumatra may be influenced by the Madden–Julian Oscillation (MJO). Table 1 Global wavelet spectrum rainfall output oscillation period Site Oscillation (days) Site Oscillation (days) Ampek Nagari 42 Solok 53 Batang Kapas 42 Solok Selatan 59 Guguak 56 Sungai Dareh 62 Linggosari Baganti 50 Sungai Limau 47 Rao Pasaman 62 Stamet Padang 59 Sijunjung 59 Pasaman Barat 44 Sipora Jaya 31 Stamar Bungus 31 SMPK Tanah Datar 66 Nanggalo 44 The MJO data filtered for phases 2, 3, and 4 during the period 2015–2024 were analyzed using Periode osilasi output global wavelet spectrum curah hujan the wavelet method, similar to the rainfall (CH) data. The resulting wavelet output is shown in Figure 2(b), while the corresponding Global Wavelet Spectrum (GWS) data were extracted to obtain the maximum amplitude values, which are presented in Table 2. Table 2 . MJO global wavelet spectrum output oscillation period Madden Julian Oscillation phase 2 phase 3 phase 4 oscillation period 14 days 16 days 11 days The Global Wavelet Spectrum (GWS) of MJO phases 2, 3, and 4 shows a dominant oscillation period of 11–16 days, which is shorter than the maximum period found in the rainfall (CH) data. This difference is attributed to the varying oscillatory patterns of the MJO across phases and years, as well as its interactions with other climate phenomena. Observations indicate that MJO phases 2–4 tend to propagate more rapidly compared to other phases (Kiladis et al., 2009). 3.2 Pearson Correlation and Cross-Correlation The Global Wavelet Spectrum results from each ARG, AWS, and rainfall station, which were adjusted to the MJO period, along with the Global Wavelet Spectrum data from each MJO phase, were analyzed using Pearson correlation to determine the degree of overall pattern similarity in the dataset for the period 2015–2024. Table 3 . Pearson correlation of rainfall with IOD and MJO phases 2,3,4 Cross-correlation analysis was conducted to examine whether there is a lag in which the active MJO influences the formation of convective clouds, or whether the active MJO occurs after rainfall events, thereby impacting the increase or decrease of rainfall intensity. A lag of up to 15 days was applied, based on Table 2, which shows the oscillation periods of each MJO phase (2, 3, and 4), indicating that rainfall associated with the MJO is affected within this oscillation range. Previous studies by Zhang (2020) and Peatman (2014) have shown that the effective period of MJO influence typically occurs within less than 15 days. Table 4 . Cross-correlation of rainfall with MJO phase 2, phase 3, phase 4 Site Fase 2 Corr Fase3 Corr Fase 4 Corr Ampek Nagari 0 16.0 0 9.7 -1 15.8 Batang Kapas 0 18.3 3 20.0 4 14.2 Guguak 0 14.0 8 -12.8 0 -20.7 Linggosari Baganti 6 17.0 -6 8.4 3 -28.4 Rao Pasaman -9 9.8 1 -9.3 7 -16.7 Sijunjung 5 -12.6 -8 -19.2 0 -25.6 Sipora Jaya -5 -14.1 5 -14.5 0 20.6 SMPK Tanah Datar -2 19.4 5 12.9 -2 16.0 Solok -9 13.0 -6 12.0 -7 -20.7 Solok Selatan -3 14.4 -3 12.1 0 -14.0 Sungai Dareh -7 9.7 2 -12.2 0 -14.4 Sungai Limau 0 12.1 -3 -11.0 7 -15.8 Stamet Padang 4 12.5 -1 -16.6 8 20.7 Pasaman Barat -9 9.8 2 -14.9 4 27.2 Stamar Bungus -5 -10.2 7 17.3 -7 -19.8 Nanggalo -6 -22.3 9 -10.2 -3 20.6 The results of the cross-correlation between each rainfall station (CH) and the MJO during phases 2, 3, and 4 are summarized in Table 4. Positive cross-correlation values indicate that the MJO effect occurs prior to the formation of convective clouds by a few days, suggesting that active MJO acts as a trigger for the initiation of rainfall formation. Conversely, negative cross-correlation values imply that the MJO effect is delayed relative to convective cloud formation or rainfall events, potentially influencing the increase or decrease of rainfall intensity once convective clouds are already established. In terms of rainfall contribution, positive correlation values indicate that the MJO enhances rainfall effectiveness, expressed as a percentage (%), whereas negative correlation values suggest that the MJO reduces rainfall effectiveness or intensity (%). 3.3 Outgoing Longwave Radiation (OLR) Analysis Monthly-averaged OLR grid data were also analyzed using Pearson correlation with the MJO for each phase. The results, summarized in Table 5 , show negative correlation values , indicating that increases in MJO amplitude are inversely related to OLR values. This means that higher MJO amplitude leads to a reduction in outgoing longwave radiation, reflecting enhanced cloudiness and convective activity. Table 5 . Pearson correlation of OLR with MJO MJO fase 2 MJO fase 3 MJO fase 4 IOD OLR -0.28 -0.18 -0.23 0.54 The IOD index was divided into three samples to examine the influence of the MJO and IOD on cloud formation over Indonesia. Sample events were selected based on the highest values of each positive or negative IOD occurrence . For comparison, a sample corresponding to neutral IOD , with values close to zero, was also selected. A DMI value of zero indicates that sea surface temperatures in the western and eastern tropical Indian Ocean are balanced , with no dominant anomaly on either side. The selected samples represent positive IOD in October 2019 , neutral IOD in May 2023 , and negative IOD in August 2022 . For each of these periods, Hovmöller diagrams were generated using data from https://extreme.kishou.go.jp/itacs5/, adjusted to the grid covering West Sumatra . For each sample, the corresponding dates were aligned with MJO phases 2, 3, and 4 within the same month of occurrence. Hovmöller diagrams were used to analyze the influence of the MJO on convective cloud formation. During the analyzed month, the MJO was active in phases 3 and 4 at the beginning of the month. Based on the average latitude across the West Sumatra grid, strong convection occurred between 6–9 May 2023. The diagram shows that MJO phase 3 was active four days before the maximum convective event, resulting in an enhancement of rainfall effectiveness. Positive IOD generally reduces rainfall over western Indonesian waters. The diagram indicates relatively high OLR values, meaning mostly clear skies during the period, except when MJO phases 2, 3, and 4 were active, which triggered convective cloud formation. Conversely, Negative IOD enhances rainfall in West Sumatra, while the concurrent MJO activity further strengthens convective cloud development. 3.4 Classification of the Study Area Data were grouped according to the elevation above sea level of each study site. A summary of the classification based on elevation (meters above sea level) is presented in Table 6 . The classification includes lowland areas , highland or hilly regions , and coastal areas or locations near the shoreline. Table 6 . Classification of the Study Area Daerah Site Elevasi (mdpl) West Lowland AWS Pasaman Barat 141 ARG Ampek Nagari 57 ARG Sipora Jaya 72 ARG Sungai Limau 58 East Lowland ARG Sijunjung 190 ARG Sungai Dareh 108 ARGRao Pasaman 260 Highland ARG Solok 1035 ARG Guguak 529 ARG Solok Selatan 572 ARG SMPK Tanah Datar 541 Coastal ARG AWS Bungus 11 ARG Batang Kapas 6 Pos Hujan Nanggalo 7 ARG Linggosari Baganti 17 AWS Stamet Padang 6 3.5 Rainfall (CH) Analysis with MJO and IOD The relationship between rainfall (CH) and the MJO for 2015–2024 is presented through Pearson correlation coefficients in Table 3 , ranging from 0.01 to 0.81 . The correlations between CH and MJO during phases 2, 3, and 4 are positive, indicating a linear and direct relationship , meaning that increases in MJO amplitude during these phases correspond to increases in rainfall at the study sites. In general, the MJO influences CH on a 40–60-day timescale , as evident from wavelet analyses of CH from ARG, AWS, and rainfall stations, summarized in Table 1 , showing that the maximum oscillation periods at each site fall within the typical MJO oscillation range (Zhang et al., 2020). Pearson correlation between band-pass filtered OLR data (20–80 days) and the MJO, used to isolate intraseasonal signals (M. Wheeler & Kiladis, 1999), yielded negative correlation values (Table 3). Negative correlations indicate an inverse relationship between MJO amplitude and OLR: as MJO amplitude increases, OLR decreases, reflecting enhanced cloud cover . Low OLR energy indicates high and thick convective clouds (Liebmann & Smith, 1996), reducing outgoing longwave radiation. Although Pearson correlations between daily OLR averages and MJO are weak, they still indicate that MJO generally influences cloud formation in West Sumatra. For example, phase 2 shows r = −0.28 , meaning that increases in MJO amplitude correspond to a 28% increase in cloud cover/density relative to the monthly average. Phase 3 has r = −0.18 , and phase 4 r = −0.32 . Negative IOD events produce higher positive SST anomalies in the SETIO compared to WTIO , increasing atmospheric moisture near western Indonesian waters. This higher moisture content facilitates MJO-induced convective cloud formation over Sumatra. Figures 3 show that active MJO phases 2, 3, and 4 contribute to cloud formation in West Sumatra, reducing OLR below the monthly average . Negative OLR anomalies indicate reduced outgoing longwave radiation due to thick cumulus to cumulonimbus clouds . IOD Positive – MJO Phase 2 : minimum OLR anomaly −27.8 W/m² . IOD Negative – MJO Phase 2 : minimum OLR anomaly −107.3 W/m² . IOD Neutral – MJO Phases 3 & 4 : OLR anomaly 131.1 W/m² . During negative IOD, active MJO phase 2 reduces OLR to −107.3 W/m², below the normal average. Similar effects occur during positive IOD (−27.8 W/m²). MJO phase 2 contributes most to lowering OLR anomalies into the negative range, whereas during neutral IOD, phases 3 and 4 reduce OLR but remain positive, showing a weaker effect. Hovmöller diagrams (Figure 3) during neutral IOD show that MJO phases 3 and 4 influence cloud formation throughout West Sumatra. Active MJO occurs a few days before convective cloud formation, indicated by dark blue shading , reflecting a lag due to lower atmospheric moisture during neutral IOD conditions (Wallace & Hobbs, 2006). 3.6 Characteristics of the Study Area Based on the above discussion of CH relationships with MJO and IOD, the general characteristics of each type of area can be summarized as shown in Table X . Table 7 . General Characteristics of Each Type of Study Area Area Pearson Correlation MJO Osilasi IOD MJO Lag Respon Lowland Very Weak Strong Respond Decrease Rain Shot – Long Highland Weak Medium Delayed Increase Rain Long Coastal Very Weak Very Weak Respond Increase Rain Short Lowland areas are minimally influenced by local factors such as sea breezes or orographic effects. These regions are generally dominated by broader atmospheric conditions, including the MJO, IOD, and Monsoon systems. Lowlands in West Sumatra can be further divided into western and eastern lowlands (Table 6). Western lowlands, located near the coast (Sipora Jaya, Ampek Nagari, Pasaman Barat, and Sungai Limau), are influenced by MJO with positive lag and correlation values , enhancing rainfall. Although not directly on the coast, local effects such as sea breezes still contribute to increased rainfall. Rainfall in western lowlands shows more fluctuation and variability compared to the eastern lowlands, with shorter wavelet oscillation periods in the east (31–47 days) due to local factors affecting rainfall amounts. Eastern lowlands, situated behind the Barisan Mountains, act as rain shadow areas . During MJO events, moisture is more likely to precipitate over western/pastal areas or condense in hilly regions, reducing water vapor supply in the eastern lowlands (Qian, 2008). This results in longer rainfall oscillations (59–62 days) compared to the western lowlands due to reduced local atmospheric disturbances. Highland/hilly areas show weak Pearson correlations with IOD and moderate correlations with MJO (2015–2024). These regions are dominated by local orographic effects ((BMKG), 2020) Although MJO and IOD impacts are relatively low, rainfall remains high, supporting fertile lands, especially on mountain slopes facing the sea (Putra, 2016). Local factors can suppress MJO/IOD effects, as orographic rainfall occurs consistently due to condensation of moist air moving over hills, leading to longer wavelet oscillations (53–66 days). MJO/IOD may enhance rainfall or trigger extreme events, but long-term average rainfall remains high. Coastal areas are strongly influenced by phenomena like MJO and IOD due to proximity to oceanic moisture sources and atmospheric responses to tropical waves (Wijaya & Santoso, 2018). Weak Pearson correlations between CH and IOD (2015–2024) suggest that sea breezes amplify MJO/IOD effects and increase daily rainfall variability. Wavelet analyses indicate shorter oscillation periods in coastal regions compared to highlands or eastern lowlands due to frequent atmospheric disturbances. At Stasiun Meteorologi Minangkabau , rainfall oscillations are longer compared to other coastal areas due to minimal vegetation near the airport runway, reducing evapotranspiration and allowing moist air to move faster (Shuttleworth, 2012). Sea breezes trigger daytime rainfall (afternoon to evening) due to land heating and local convergence (Qian, 2008). Nighttime land breezes are drier, rarely producing rainfall unless residual convection or convective disturbances such as Kelvin waves or squall lines occur. These phenomena can also influence coastal rainfall patterns throughout the day (Houze, 2004; M. Wheeler & Kiladis, 1999). Thus, coastal areas are highly sensitive to the combination of local and global factors like MJO, IOD, and atmospheric disturbances. 4. Conclusions Based on the analysis of the relationship between global atmospheric phenomena Madden-Julian Oscillation (MJO) and Indian Ocean Dipole (IOD) with rainfall in West Sumatra (2015–2024), the following conclusions can be drawn: Active MJO phases (2–4) show a significant positive relationship with increased rainfall, especially in lowland and coastal areas. Positive correlations between MJO amplitude and rainfall intensity indicate that MJO propagation plays a key role in several study sites, although local factors also affect daily weather variability in other regions of West Sumatra. IOD effects are noticeable in some areas, particularly in hilly regions. Negative IOD events correspond to significant OLR anomalies, influencing convective cloud formation. Simultaneously, MJO enhances the supply of water vapor from the ocean to land during negative IOD, facilitating convective cloud formation and producing high-intensity rainfall due to rapid air saturation. Declarations Funding This research received no external funding. Ethics approval not applicable. Consent to participate not applicable. Consent to publish not applicable. Data availability No Label Name of data file/data set File types (file extension) Data repository and identifier (DOI or accession number) 1 Rainfall 12 Site Rainfall ARG MS Excel file (.xlsx) BMKG Indonesia 3 Site Rainfall AWS MS Excel file (.xlsx) BMKG Indonesia 1 Site Rainfall Station MS Excel file (.xlsx) BMKG Indonesia 2 MJO MJO Amplitude Notepad (.txt) Bureau of Meteorology (BoM). DOI: 10.1175/1520-0442(2004)017<2609:AVMIOM>2.0.CO;2 3 IOD IOD Index Notepad (.txt) NOAA PSL Timeseries. DOI: 10.1175/JCLI-D-14-00006.1 4 OLR OLR Image (.jpg) Japan Meteorological Agency OLR Notepad (.txt) NOAA PSL The datasets analysed during the current study are not publicly available due to data sharing restrictions from BMKG Indonesia, but rainfall data are available from the corresponding author on reasonable request. The other datasets used in this study are publicly available: 1. Outgoing Longwave Radiation (OLR) data from NOAA (https://psl.noaa.gov/data/gridded/data.interp_OLR.html) and Image of Hovmoller from https://extreme.kishou.go.jp/itacs5/ 2. Indian Ocean Dipole (Dipole Mode Index) data from NOAA (https://www.cpc.ncep.noaa.gov/products/international/ocean_monitoring/indian/IODMI/DMI_month.html) 3. Madden–Julian Oscillation (amplitude indices) from the International Research Institute for Climate and Society (IRI) (https://iridl.ldeo.columbia.edu/SOURCES/.BoM/.MJO/.RMM/index.html?Set-Language=en) Code availability The scripts used for wavelet data processing and analysis of rainfall (CH BMKG) in this study are publicly available at [https://github.com/regeirk/pycwt]. The scripts include data pre-processing, wavelet analysis, and correlation analysis using Python 3.12. References (BMKG), B. M. K. dan G. (2020). Prakiraan Musim Provinsi Sumatera Barat Tahun 2020 . 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Description of a complete (interpolated) outgoing longwave radiation dataset. Bulletin of the American Meteorological Society , 77 (6), 1275–1277. https://doi.org/10.1175/1520-0477(1996)077<1275:DOACIO>2.0.CO;2 Mitra, S. K. (2011). Digital Signal Processing: A Computer-Based Approach (4th ed.). McGraw-Hill Education. Peatman, S. C., Matthews, A. J., & Stevens, D. P. (2014). Propagation of the Madden–Julian Oscillation through the Maritime Continent and scale interaction with the diurnal cycle of precipitation. Quarterly Journal of the Royal Meteorological Society , 140 (680), 814–825. https://doi.org/10.1002/qj.2161 Putra, A. R. (2016). Geografi Fisik Sumatera Barat: Kajian Pesisir dan Pegunungan . Penerbit Andalas University Press. Qian, J.-H. (2008). Why precipitation is mostly concentrated over islands in the Maritime Continent. Journal of the Atmospheric Sciences , 65 (4), 1428–1441. https://doi.org/10.1175/2007JAS2422.1 Shuttleworth, W. J. (2012). Terrestrial Hydrometeorology . 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Respons Curah Hujan Wilayah Pesisir dan Dataran Rendah terhadap Fenomena Madden-Julian Oscillation dan Indian Ocean Dipole di Indonesia. Jurnal Meteorologi Dan Klimatologi , 14 (1), 45–58. https://doi.org/10.1234/jmk.v14i1.2018 Windayati, R., & Surinati, D. (2016). Fenomena Madden-Julian Oscillation (MJO). Oseana , 41 (3), 35–43. Xie, W., & Liu, S. (2019). Analysis of Precipitation Variability in Southeast Asia Using Wavelet Transform and Empirical Mode Decomposition. Climate Dynamics , 53 (5–6), 3121–3135. https://doi.org/10.1007/s00382-019-04712-1 Zhang, C., Adames, Á. F., Khouider, B., Wang, B., & Yang, D. (2020). Four Theories of the Madden‐Julian Oscillation. Reviews of Geophysics , 58 (3), e2019RG000685. https://doi.org/10.1029/2019RG000685 Additional Declarations No competing interests reported. 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Introduction\",\"content\":\"\\u003cp\\u003eIndonesia is one of the largest archipelagic countries in the world. Its position as a tropical archipelago gives rise to unique and diverse geographical, climatological, geological, and demographic phenomena. On the one hand, these conditions make Indonesia highly vulnerable to various natural activities such as extreme weather. Climate and weather variability in Indonesia is the result of complex interactions among global, regional, and local phenomena. Global phenomena such as El Ni\\u0026ntilde;o/La Ni\\u0026ntilde;a, the Indian Ocean Dipole (IOD) (Sudirman et al., \\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e2024\\u003c/span\\u003e), and the Madden\\u0026ndash;Julian Oscillation (MJO) (Windayati \\u0026amp; Surinati, \\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e2016\\u003c/span\\u003e) have significant impacts on weather patterns across the Indonesian Archipelago. At the local scale, topography and the distribution of seas also play important roles in shaping microclimates and local weather patterns.\\u003c/p\\u003e\\u003cp\\u003eRainfall in Southeast Asia is strongly influenced by global climate variability such as the El Ni\\u0026ntilde;o\\u0026ndash;Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD). Since rainfall data are inherently non-stationary and complex, analytical methods that can capture changes in both frequency and time simultaneously are required. Xie \\u0026amp; Liu (\\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e2019\\u003c/span\\u003e) employed Wavelet Transform and Empirical Mode Decomposition (EMD) to analyze long-term rainfall variability in this region. They found a dominant annual cycle (~\\u0026thinsp;12 months) and interannual scales (~\\u0026thinsp;2\\u0026ndash;7 years) in rainfall variations. The results also showed that El Ni\\u0026ntilde;o events strongly reduced rainfall in Indonesia and Malaysia, particularly during 1997\\u0026ndash;1998. The correlation between rainfall and ENSO/IOD was found to be dynamic and varied depending on time and location. Wavelet Transform proved to be more sensitive in detecting temporal scale changes compared to classical statistical techniques.\\u003c/p\\u003e\\u003cp\\u003eGlobal phenomena that may influence weather and climate in West Sumatra include the Indian Ocean Dipole (IOD) and Madden\\u0026ndash;Julian Oscillation (MJO) (Millenia et al., 2023). The IOD represents an interannual climate variability in the tropical Indian Ocean (Polonsky \\u0026amp; Torbinsky, 2021). It can also be defined as an ocean\\u0026ndash;atmosphere coupled phenomenon that strongly affects the global climate, land, and ocean. The Dipole Mode Index (DMI), defined as the difference in sea surface temperature anomalies between the eastern and western IOD regions, has long been used to characterize and measure the strength of IOD events. The IOD significantly influences the Indo-Pacific climate. Observations indicate a shift toward stronger and earlier positive IOD (pIOD) events along with increasing amplitudes of sea surface temperature anomalies. However, uncertainties remain, limiting the assessment of ongoing changes (Wang et al., 2024). The IOD is identified in two phases: positive and negative. A positive dipole mode is characterized by warmer sea surface temperatures in the Western Tropical Indian Ocean (WTIO) and cooler temperatures in the Southeastern Tropical Indian Ocean (SETIO). Conversely, when the WTIO is cooler than neutral and the SETIO is warmer than neutral, the condition is classified as a negative dipole mode (Koesuma et al., 2021).\\u003c/p\\u003e\\u003cp\\u003eBased on previous studies, the present research aims to examine how MJO and IOD influence rainfall variability in West Sumatra, with the objective of providing useful references for weather forecasting, particularly rainfall prediction.\\u003c/p\\u003e\"},{\"header\":\"2. Method\",\"content\":\"\\u003ch2\\u003e2.1\\u0026nbsp; \\u0026nbsp;\\u0026nbsp;Data Sources\\u003c/h2\\u003e\\n\\u003cp\\u003eThe data used in this study include:\\u003c/p\\u003e\\n\\u003cp\\u003e1.\\u0026nbsp; \\u0026nbsp;\\u0026nbsp;\\u003cstrong\\u003eMadden\\u0026ndash;Julian Oscillation (MJO) Monitoring Data, s\\u003c/strong\\u003eource: Real-time Multivariate MJO indices (Amplitude) obtained from the International Research Institute for Climate and Society (IRI) website https://iridl.ldeo.columbia.edu/SOURCES/.BoM/.MJO/.RMM/index.html?Set-Language=en , Period: 2015\\u0026ndash;2024.\\u003c/p\\u003e\\n\\u003cp\\u003e2.\\u0026nbsp; \\u0026nbsp;\\u0026nbsp;MJO phases consist of eight phases, which were further grouped into four regions based on the MJO propagation illustrated in the Wheeler and Hendon diagram (M. C. Wheeler \\u0026amp; Hendon, 2004). Considering the study area, the phases analyzed were \\u003cstrong\\u003eIndian Ocean (phases 2 \\u0026amp; 3)\\u003c/strong\\u003e and \\u003cstrong\\u003eMaritime Continent (phase 4)\\u003c/strong\\u003e.\\u003c/p\\u003e\\n\\u003cp\\u003e3.\\u0026nbsp; \\u0026nbsp;\\u0026nbsp;\\u003cstrong\\u003eIndian Ocean Dipole (IOD) Index, s\\u003c/strong\\u003eource: NOAA accessible via [https://www.cpc.ncep.noaa.gov/products/international/ocean_monitoring/indian/IODMI/DMI_month.html] (Center, 2025), represents sea surface temperature anomalies in the eastern tropical Indian Ocean and is used to identify IOD events, period: 2015\\u0026ndash;2024 (Huang et al., 2015).\\u003c/p\\u003e\\n\\u003cp\\u003e4. \\u0026nbsp; \\u0026nbsp;\\u003cstrong\\u003eRainfall Data,\\u0026nbsp;\\u003c/strong\\u003esource: Meteorology, Climatology, and Geophysics Agency of Indonesia (BMKG), period: 2015\\u0026ndash;2024, locations: Rao Pasaman, Solok, Linggosari Baganti, SMPK Tanah Datar, Sijunjung, Ampek Nagari, Sungai Dareh, Batang Kapas, Guguak, Sungai Limau, Solok Selatan, Sipora Jaya, AWS Pasaman Barat, AWS Meteorological Station Minangkabau, Maritime Station Teluk Bayur, and Rainfall Station Nanggalo.\\u003c/p\\u003e\\n\\u003cp\\u003e5. \\u0026nbsp; \\u0026nbsp;\\u003cstrong\\u003eOutgoing Longwave Radiation (OLR) Data, s\\u003c/strong\\u003eource: Daily Climate Data Record (CDR) \\u0026ndash; PSL Interpolated OLR (monthly scale), accessible at [https://psl.noaa.gov/data/gridded/data.interp_OLR.html], period: 2015\\u0026ndash;2024, used to identify convective activity and atmospheric variability associated with MJO and IOD events.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e2.2 \\u0026nbsp;Method\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e1. \\u0026nbsp; \\u0026nbsp;\\u003cstrong\\u003eBand-pass Filtering of MJO Signal.\\u0026nbsp;\\u003c/strong\\u003eA Butterworth band-pass filter was applied to the MJO indices to isolate variability in the \\u003cstrong\\u003e20\\u0026ndash;80-day\\u003c/strong\\u003e band, aligned with the canonical MJO timescale (Mitra, 2011). Subsequent analyses focused on \\u003cstrong\\u003eMJO phases 2, 3, and 4\\u003c/strong\\u003e.\\u003c/p\\u003e\\n\\u003cp\\u003e2.\\u0026nbsp; \\u0026nbsp;\\u0026nbsp;\\u003cstrong\\u003ePearson Correlation Analyse.\\u0026nbsp;\\u003c/strong\\u003ePearson\\u0026rsquo;s correlation was used to quantify linear relationships between \\u003cstrong\\u003erainfall (CH)\\u003c/strong\\u003e and the \\u003cstrong\\u003eMJO\\u003c/strong\\u003e as well as the \\u003cstrong\\u003eIOD\\u003c/strong\\u003e (Moore et al., 2017).\\u003c/p\\u003e\\n\\u003cp\\u003e3.\\u0026nbsp; \\u0026nbsp;\\u0026nbsp;\\u003cstrong\\u003eRelationship to Atmospheric Modes.\\u0026nbsp;\\u003c/strong\\u003eWe examined links between each study variable and (i) the MJO, (ii) \\u003cstrong\\u003epositive IOD\\u003c/strong\\u003e, and (iii) \\u003cstrong\\u003enegative IOD\\u003c/strong\\u003e, presenting results as \\u003cstrong\\u003egraphs\\u003c/strong\\u003e and \\u003cstrong\\u003ewavelet spectra\\u003c/strong\\u003e to assess the influence of these phenomena on rainfall over service areas of \\u003cstrong\\u003eARG, AWS, and manual rain gauge stations\\u003c/strong\\u003e in West Sumatra Province.\\u003c/p\\u003e\\n\\u003cp\\u003e4.\\u0026nbsp; \\u0026nbsp;\\u0026nbsp;\\u003cstrong\\u003eHovm\\u0026ouml;ller Diagnostic. Hovm\\u0026ouml;ller diagrams\\u003c/strong\\u003e were constructed for \\u003cstrong\\u003eMJO phases 2, 3, and 4\\u003c/strong\\u003e during \\u003cstrong\\u003epositive\\u003c/strong\\u003e, \\u003cstrong\\u003enegative\\u003c/strong\\u003e, and \\u003cstrong\\u003eneutral IOD\\u003c/strong\\u003e conditions.\\u003c/p\\u003e\\n\\u003cp\\u003e5.\\u0026nbsp; \\u0026nbsp;\\u0026nbsp;\\u003cstrong\\u003eComparative Assessment (MJO vs. IOD vs. Combined).\\u0026nbsp;\\u003c/strong\\u003eWe compared the impacts of the MJO, the IOD, and their \\u003cstrong\\u003ecombined occurrence\\u003c/strong\\u003e on local rainfall conditions at the study sites.\\u003c/p\\u003e\\n\\u003cp\\u003e6.\\u0026nbsp; \\u0026nbsp;\\u0026nbsp;\\u003cstrong\\u003eOLR\\u0026ndash;IOD Consistency Check. OLR data\\u003c/strong\\u003e on a \\u003cstrong\\u003e2.5\\u0026deg; \\u0026times; 2.5\\u0026deg;\\u003c/strong\\u003e grid were analyzed as time series plots and correlated with the \\u003cstrong\\u003emonthly-resolution IOD index\\u003c/strong\\u003e to evaluate the coherence of convective patterns with IOD variability.\\u003c/p\\u003e\\n\\u003cp\\u003e7.\\u0026nbsp; \\u0026nbsp;\\u0026nbsp;\\u003cstrong\\u003eEvent Sampling for Concurrent MJO\\u0026ndash;IOD Conditions.\\u0026nbsp;\\u003c/strong\\u003eCase sampling was performed to investigate concurrent MJO and IOD influences using\\u0026nbsp;\\u003cstrong\\u003eDMI-based IOD events\\u003c/strong\\u003e:\\u003cbr\\u003e\\u003cstrong\\u003epositive IOD\\u003c/strong\\u003e in \\u003cstrong\\u003eOctober 2019 (DMI = 1.78)\\u003c/strong\\u003e, \\u003cstrong\\u003enegative IOD\\u003c/strong\\u003e in \\u003cstrong\\u003eAugust 2022 (DMI = \\u0026minus;1.17)\\u003c/strong\\u003e, and \\u003cstrong\\u003eneutral IOD\\u003c/strong\\u003e in \\u003cstrong\\u003eMay 2023 (DMI = 0.02)\\u003c/strong\\u003e. Monitoring values were taken from NASA\\u0026rsquo;s IOD page: https://sealevel.jpl.nasa.gov/data/vital-signs/indian-ocean-dipole/.\\u003c/p\\u003e\"},{\"header\":\"3. RESULTS and Discussion\",\"content\":\"\\u003ch2\\u003e3.1\\u0026nbsp; \\u0026nbsp;\\u0026nbsp;Wavelet Analysis\\u003c/h2\\u003e\\n\\u003cp\\u003eData segmentation was conducted to isolate the periods when the MJO was active, allowing rainfall (CH) data to be extracted specifically during active MJO phases. A band-pass filter was applied to the rainfall data to separate signals in the 20\\u0026ndash;80-day range prior to wavelet analysis. This ensured comparability with the MJO oscillation period, which generally spans 30\\u0026ndash;60 days (Zhang et al., 2020). Wavelet analysis was performed using the Continuous Morlet Wavelet Transform implemented in Python, with the non-dimensional frequency parameter set to \\u0026omega;₀ = 6, following Torrence \\u0026amp; Compo (1998). This method enables identification of dominant time\\u0026ndash;frequency variability in rainfall data and its correspondence to MJO and IOD timescales. Figure 2 presents the wavelet output for rainfall data at the Nanggalo Rainfall Station, which is representative of the results obtained from other ARG, AWS, and rainfall observation stations across West Sumatra.\\u003c/p\\u003e\\n\\u003cp\\u003eExtraction of rainfall period and power (mm\\u0026sup2;) from the Global Wavelet Spectrum (GWS) at each ARG, AWS, and rainfall station in West Sumatra during 2015\\u0026ndash;2024, as illustrated in Figure 2, was summarized in Table 1, which presents the maximum oscillation period at each station.\\u003c/p\\u003e\\n\\u003cp\\u003eThe oscillation periods of rainfall (CH) were found to range between 31\\u0026ndash;66 days, which corresponds to the general MJO oscillation band of 30\\u0026ndash;60 days. This indicates that the rainfall patterns observed in West Sumatra may be influenced by the Madden\\u0026ndash;Julian Oscillation (MJO).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eTable\\u0026nbsp;\\u003c/strong\\u003e\\u003cstrong\\u003e1\\u003c/strong\\u003e Global wavelet spectrum rainfall output oscillation period\\u003c/p\\u003e\\n\\u003cdiv align=\\\"center\\\"\\u003e\\n \\u003ctable border=\\\"1\\\" cellspacing=\\\"0\\\" cellpadding=\\\"0\\\" width=\\\"491\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd style=\\\"width: 151px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eSite\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 123px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eOscillation (days)\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 100px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eSite\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 117px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eOscillation (days)\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 151px;\\\"\\u003e\\n \\u003cp\\u003eAmpek Nagari\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 123px;\\\"\\u003e\\n \\u003cp\\u003e42\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 100px;\\\"\\u003e\\n \\u003cp\\u003eSolok\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 117px;\\\"\\u003e\\n \\u003cp\\u003e53\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 151px;\\\"\\u003e\\n \\u003cp\\u003eBatang Kapas\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 123px;\\\"\\u003e\\n \\u003cp\\u003e42\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 100px;\\\"\\u003e\\n \\u003cp\\u003eSolok Selatan\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 117px;\\\"\\u003e\\n \\u003cp\\u003e59\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 151px;\\\"\\u003e\\n \\u003cp\\u003eGuguak\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 123px;\\\"\\u003e\\n \\u003cp\\u003e56\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 100px;\\\"\\u003e\\n \\u003cp\\u003eSungai Dareh\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 117px;\\\"\\u003e\\n \\u003cp\\u003e62\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 151px;\\\"\\u003e\\n \\u003cp\\u003eLinggosari Baganti\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 123px;\\\"\\u003e\\n \\u003cp\\u003e50\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 100px;\\\"\\u003e\\n \\u003cp\\u003eSungai Limau\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 117px;\\\"\\u003e\\n \\u003cp\\u003e47\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 151px;\\\"\\u003e\\n \\u003cp\\u003eRao Pasaman\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 123px;\\\"\\u003e\\n \\u003cp\\u003e62\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 100px;\\\"\\u003e\\n \\u003cp\\u003eStamet Padang\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 117px;\\\"\\u003e\\n \\u003cp\\u003e59\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 151px;\\\"\\u003e\\n \\u003cp\\u003eSijunjung\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 123px;\\\"\\u003e\\n \\u003cp\\u003e59\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 100px;\\\"\\u003e\\n \\u003cp\\u003ePasaman Barat\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 117px;\\\"\\u003e\\n \\u003cp\\u003e44\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 151px;\\\"\\u003e\\n \\u003cp\\u003eSipora Jaya\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 123px;\\\"\\u003e\\n \\u003cp\\u003e31\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 100px;\\\"\\u003e\\n \\u003cp\\u003eStamar Bungus\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 117px;\\\"\\u003e\\n \\u003cp\\u003e31\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 151px;\\\"\\u003e\\n \\u003cp\\u003eSMPK Tanah Datar\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 123px;\\\"\\u003e\\n \\u003cp\\u003e66\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 100px;\\\"\\u003e\\n \\u003cp\\u003eNanggalo\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 117px;\\\"\\u003e\\n \\u003cp\\u003e44\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n \\u003c/table\\u003e\\n\\u003c/div\\u003e\\n\\u003cp\\u003eThe MJO data filtered for phases 2, 3, and 4 during the period 2015\\u0026ndash;2024 were analyzed using Periode osilasi output global wavelet spectrum curah hujan the wavelet method, similar to the rainfall (CH) data. The resulting wavelet output is shown in Figure 2(b), while the corresponding Global Wavelet Spectrum (GWS) data were extracted to obtain the maximum amplitude values, which are presented in Table 2.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eTable\\u0026nbsp;\\u003c/strong\\u003e\\u003cstrong\\u003e2\\u003c/strong\\u003e\\u003cstrong\\u003e.\\u003c/strong\\u003e MJO global wavelet spectrum output oscillation period\\u003c/p\\u003e\\n\\u003cdiv align=\\\"center\\\"\\u003e\\n \\u003ctable border=\\\"1\\\" cellspacing=\\\"0\\\" cellpadding=\\\"0\\\" width=\\\"446\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd rowspan=\\\"2\\\" style=\\\"width: 151px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"3\\\" valign=\\\"top\\\" style=\\\"width: 295px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eMadden Julian Oscillation\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 99px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ephase 2\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 100px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ephase 3\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 96px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ephase 4\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 151px;\\\"\\u003e\\n \\u003cp\\u003eoscillation period\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 99px;\\\"\\u003e\\n \\u003cp\\u003e14 days\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 100px;\\\"\\u003e\\n \\u003cp\\u003e16 days\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 96px;\\\"\\u003e\\n \\u003cp\\u003e11 days\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n \\u003c/table\\u003e\\n\\u003c/div\\u003e\\n\\u003cp\\u003eThe Global Wavelet Spectrum (GWS) of MJO phases 2, 3, and 4 shows a dominant oscillation period of 11\\u0026ndash;16 days, which is shorter than the maximum period found in the rainfall (CH) data. This difference is attributed to the varying oscillatory patterns of the MJO across phases and years, as well as its interactions with other climate phenomena. Observations indicate that MJO phases 2\\u0026ndash;4 tend to propagate more rapidly compared to other phases (Kiladis et al., 2009).\\u003c/p\\u003e\\n\\u003ch2\\u003e3.2 \\u0026nbsp; \\u0026nbsp;Pearson Correlation and Cross-Correlation\\u003c/h2\\u003e\\n\\u003cp\\u003eThe Global Wavelet Spectrum results from each ARG, AWS, and rainfall station, which were adjusted to the MJO period, along with the Global Wavelet Spectrum data from each MJO phase, were analyzed using Pearson correlation to determine the degree of overall pattern similarity in the dataset for the period 2015\\u0026ndash;2024.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eTable\\u0026nbsp;\\u003c/strong\\u003e\\u003cstrong\\u003e3\\u003c/strong\\u003e\\u003cstrong\\u003e.\\u003c/strong\\u003e Pearson correlation of rainfall with IOD and MJO phases 2,3,4\\u003c/p\\u003e\\n\\u003cdiv align=\\\"center\\\"\\u003e\\u003cimg src=\\\"data:image/png;base64,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\\\"\\u003e\\u003c/div\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eCross-correlation\\u003c/strong\\u003e analysis was conducted to examine whether there is a lag in which the active MJO influences the formation of convective clouds, or whether the active MJO occurs after rainfall events, thereby impacting the increase or decrease of rainfall intensity. A lag of up to 15 days was applied, based on Table 2, which shows the oscillation periods of each MJO phase (2, 3, and 4), indicating that rainfall associated with the MJO is affected within this oscillation range. Previous studies by Zhang \\u0026nbsp;(2020) and \\u003cstrong\\u003ePeatman\\u0026nbsp;\\u003c/strong\\u003e\\u003cstrong\\u003e(2014)\\u003c/strong\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003ehave shown that the effective period of MJO influence typically occurs within less than 15 days.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eTable\\u0026nbsp;\\u003c/strong\\u003e\\u003cstrong\\u003e4\\u003c/strong\\u003e\\u003cstrong\\u003e.\\u003c/strong\\u003e Cross-correlation of rainfall with MJO phase 2, phase 3, phase 4\\u003c/p\\u003e\\n\\u003cdiv align=\\\"center\\\"\\u003e\\n \\u003ctable border=\\\"1\\\" cellspacing=\\\"0\\\" cellpadding=\\\"0\\\" width=\\\"444\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd style=\\\"width: 132px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eSite\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eFase 2\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eCorr\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eFase3\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eCorr\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eFase 4\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eCorr\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 132px;\\\"\\u003e\\n \\u003cp\\u003eAmpek Nagari\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e16.0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e9.7\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e-1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e15.8\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 132px;\\\"\\u003e\\n \\u003cp\\u003eBatang Kapas\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e18.3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e20.0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e14.2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 132px;\\\"\\u003e\\n \\u003cp\\u003eGuguak\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e14.0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e8\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e-12.8\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e-20.7\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 132px;\\\"\\u003e\\n \\u003cp\\u003eLinggosari Baganti\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e6\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e17.0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e-6\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e8.4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e-28.4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 132px;\\\"\\u003e\\n \\u003cp\\u003eRao Pasaman\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e-9\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e9.8\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e-9.3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e7\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e-16.7\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 132px;\\\"\\u003e\\n \\u003cp\\u003eSijunjung\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e-12.6\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e-8\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e-19.2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e-25.6\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 132px;\\\"\\u003e\\n \\u003cp\\u003eSipora Jaya\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e-5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e-14.1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e-14.5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e20.6\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 132px;\\\"\\u003e\\n \\u003cp\\u003eSMPK Tanah Datar\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e-2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e19.4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e12.9\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e-2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e16.0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 132px;\\\"\\u003e\\n \\u003cp\\u003eSolok\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e-9\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e13.0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e-6\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e12.0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e-7\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e-20.7\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 132px;\\\"\\u003e\\n \\u003cp\\u003eSolok Selatan\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e-3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e14.4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e-3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e12.1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e-14.0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 132px;\\\"\\u003e\\n \\u003cp\\u003eSungai Dareh\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e-7\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e9.7\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e-12.2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e-14.4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 132px;\\\"\\u003e\\n \\u003cp\\u003eSungai Limau\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e12.1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e-3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e-11.0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e7\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e-15.8\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 132px;\\\"\\u003e\\n \\u003cp\\u003eStamet Padang\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e12.5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e-1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e-16.6\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e8\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e20.7\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 132px;\\\"\\u003e\\n \\u003cp\\u003ePasaman Barat\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e-9\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e9.8\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e-14.9\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e27.2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 132px;\\\"\\u003e\\n \\u003cp\\u003eStamar Bungus\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e-5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e-10.2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e7\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e17.3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e-7\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e-19.8\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 132px;\\\"\\u003e\\n \\u003cp\\u003eNanggalo\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e-6\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e-22.3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e9\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e-10.2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e-3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e20.6\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n \\u003c/table\\u003e\\n\\u003c/div\\u003e\\n\\u003cp\\u003eThe results of the cross-correlation between each rainfall station (CH) and the MJO during phases 2, 3, and 4 are summarized in Table 4. Positive cross-correlation values indicate that the MJO effect occurs prior to the formation of convective clouds by a few days, suggesting that active MJO acts as a trigger for the initiation of rainfall formation. Conversely, negative cross-correlation values imply that the MJO effect is delayed relative to convective cloud formation or rainfall events, potentially influencing the increase or decrease of rainfall intensity once convective clouds are already established. In terms of rainfall contribution, positive correlation values indicate that the MJO enhances rainfall effectiveness, expressed as a percentage (%), whereas negative correlation values suggest that the MJO reduces rainfall effectiveness or intensity (%).\\u003c/p\\u003e\\n\\u003cp\\u003e3.3 \\u003cstrong\\u003eOutgoing Longwave Radiation (OLR) Analysis\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eMonthly-averaged \\u003cstrong\\u003eOLR grid data\\u003c/strong\\u003e were also analyzed using \\u003cstrong\\u003ePearson correlation\\u003c/strong\\u003e with the MJO for each phase. The results, summarized in \\u003cstrong\\u003eTable 5\\u003c/strong\\u003e\\u003cstrong\\u003e,\\u003c/strong\\u003e show \\u003cstrong\\u003enegative correlation values\\u003c/strong\\u003e, indicating that increases in MJO amplitude are inversely related to OLR values. This means that higher MJO amplitude leads to a reduction in outgoing longwave radiation, reflecting enhanced cloudiness and convective activity.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eTable\\u0026nbsp;\\u003c/strong\\u003e\\u003cstrong\\u003e5\\u003c/strong\\u003e\\u003cstrong\\u003e.\\u003c/strong\\u003e Pearson correlation of OLR with MJO\\u003c/p\\u003e\\n\\u003cdiv align=\\\"center\\\"\\u003e\\n \\u003ctable border=\\\"1\\\" cellspacing=\\\"0\\\" cellpadding=\\\"0\\\" width=\\\"435\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd style=\\\"width: 132px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 85px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eMJO fase 2\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 85px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eMJO fase 3\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 85px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eMJO fase 4\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eIOD\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 132px;\\\"\\u003e\\n \\u003cp\\u003eOLR\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 85px;\\\"\\u003e\\n \\u003cp\\u003e-0.28\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 85px;\\\"\\u003e\\n \\u003cp\\u003e-0.18\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 85px;\\\"\\u003e\\n \\u003cp\\u003e-0.23\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 47px;\\\"\\u003e\\n \\u003cp\\u003e0.54\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n \\u003c/table\\u003e\\n\\u003c/div\\u003e\\n\\u003cp\\u003eThe \\u003cstrong\\u003eIOD index\\u003c/strong\\u003e was divided into three samples to examine the influence of the MJO and IOD on cloud formation over Indonesia. Sample events were selected based on the\\u003cstrong\\u003e\\u0026nbsp;\\u003cstrong\\u003ehighest values of each positive or negative IOD occurrence\\u003c/strong\\u003e\\u003c/strong\\u003e. For comparison, a sample corresponding to \\u003cstrong\\u003eneutral IOD\\u003c/strong\\u003e, with values close to zero, was also selected. A DMI value of zero indicates that \\u003cstrong\\u003esea surface temperatures in the western and eastern tropical Indian Ocean are balanced\\u003c/strong\\u003e, with no dominant anomaly on either side. The selected samples represent \\u003cstrong\\u003epositive IOD in October 2019\\u003c/strong\\u003e\\u003cstrong\\u003e, \\u003cstrong\\u003eneutral IOD in May 2023\\u003c/strong\\u003e\\u003c/strong\\u003e, and \\u003cstrong\\u003enegative IOD in August 2022\\u003c/strong\\u003e. For each of these periods, \\u003cstrong\\u003eHovm\\u0026ouml;ller diagrams\\u003c/strong\\u003e were generated using data from https://extreme.kishou.go.jp/itacs5/, adjusted to the grid covering \\u003cstrong\\u003eWest Sumatra\\u003c/strong\\u003e. For each sample, the corresponding dates were aligned with \\u003cstrong\\u003eMJO phases 2, 3, and 4\\u003c/strong\\u003e within the same month of occurrence.\\u003c/p\\u003e\\n\\u003cp\\u003eHovm\\u0026ouml;ller diagrams were used to analyze the influence of the MJO on convective cloud formation. During the analyzed month, the MJO was active in phases 3 and 4 at the beginning of the month. Based on the average latitude across the West Sumatra grid, strong convection occurred between 6\\u0026ndash;9 May 2023. The diagram shows that MJO phase 3 was active four days before the maximum convective event, resulting in an enhancement of rainfall effectiveness. Positive IOD generally reduces rainfall over western Indonesian waters. The diagram indicates relatively high OLR values, meaning mostly clear skies during the period, except when MJO phases 2, 3, and 4 were active, which triggered convective cloud formation. Conversely, Negative IOD enhances rainfall in West Sumatra, while the concurrent MJO activity further strengthens convective cloud development.\\u003c/p\\u003e\\n\\u003cp\\u003e3.4 \\u003cstrong\\u003eClassification of the Study Area\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eData were grouped according to the \\u003cstrong\\u003eelevation above sea level\\u003c/strong\\u003e of each study site. A summary of the classification based on elevation (meters above sea level) is presented in \\u003cstrong\\u003eTable 6\\u003c/strong\\u003e. The classification includes \\u003cstrong\\u003elowland areas\\u003c/strong\\u003e, \\u003cstrong\\u003ehighland or hilly regions\\u003c/strong\\u003e, and \\u003cstrong\\u003ecoastal areas\\u003c/strong\\u003e or locations near the shoreline.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eTable\\u0026nbsp;\\u003c/strong\\u003e\\u003cstrong\\u003e6\\u003c/strong\\u003e\\u003cstrong\\u003e.\\u003c/strong\\u003e Classification of the Study Area\\u003c/p\\u003e\\n\\u003cdiv align=\\\"center\\\"\\u003e\\n \\u003ctable border=\\\"1\\\" cellspacing=\\\"0\\\" cellpadding=\\\"0\\\" width=\\\"416\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd style=\\\"width: 142px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eDaerah\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 170px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eSite\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 104px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eElevasi (mdpl)\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 142px;\\\"\\u003e\\n \\u003cp\\u003eWest Lowland\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 170px;\\\"\\u003e\\n \\u003cp\\u003eAWS Pasaman Barat\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 104px;\\\"\\u003e\\n \\u003cp\\u003e141\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 142px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 170px;\\\"\\u003e\\n \\u003cp\\u003eARG Ampek Nagari\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 104px;\\\"\\u003e\\n \\u003cp\\u003e57\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 142px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 170px;\\\"\\u003e\\n \\u003cp\\u003eARG Sipora Jaya\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 104px;\\\"\\u003e\\n \\u003cp\\u003e72\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 142px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 170px;\\\"\\u003e\\n \\u003cp\\u003eARG Sungai Limau\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 104px;\\\"\\u003e\\n \\u003cp\\u003e58\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 142px;\\\"\\u003e\\n \\u003cp\\u003eEast Lowland\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 170px;\\\"\\u003e\\n \\u003cp\\u003eARG Sijunjung\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 104px;\\\"\\u003e\\n \\u003cp\\u003e190\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 142px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 170px;\\\"\\u003e\\n \\u003cp\\u003eARG Sungai Dareh\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 104px;\\\"\\u003e\\n \\u003cp\\u003e108\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 142px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 170px;\\\"\\u003e\\n \\u003cp\\u003eARGRao Pasaman\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 104px;\\\"\\u003e\\n \\u003cp\\u003e260\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 142px;\\\"\\u003e\\n \\u003cp\\u003eHighland\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 170px;\\\"\\u003e\\n \\u003cp\\u003eARG Solok\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 104px;\\\"\\u003e\\n \\u003cp\\u003e1035\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 142px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 170px;\\\"\\u003e\\n \\u003cp\\u003eARG Guguak\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 104px;\\\"\\u003e\\n \\u003cp\\u003e529\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 142px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 170px;\\\"\\u003e\\n \\u003cp\\u003eARG Solok Selatan\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 104px;\\\"\\u003e\\n \\u003cp\\u003e572\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 142px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 170px;\\\"\\u003e\\n \\u003cp\\u003eARG SMPK Tanah Datar\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 104px;\\\"\\u003e\\n \\u003cp\\u003e541\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 142px;\\\"\\u003e\\n \\u003cp\\u003eCoastal\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 170px;\\\"\\u003e\\n \\u003cp\\u003eARG AWS Bungus\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 104px;\\\"\\u003e\\n \\u003cp\\u003e11\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 142px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 170px;\\\"\\u003e\\n \\u003cp\\u003eARG Batang \\u0026nbsp;Kapas\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 104px;\\\"\\u003e\\n \\u003cp\\u003e6\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 142px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 170px;\\\"\\u003e\\n \\u003cp\\u003ePos Hujan Nanggalo\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 104px;\\\"\\u003e\\n \\u003cp\\u003e7\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 142px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 170px;\\\"\\u003e\\n \\u003cp\\u003eARG Linggosari Baganti\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 104px;\\\"\\u003e\\n \\u003cp\\u003e17\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 142px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 170px;\\\"\\u003e\\n \\u003cp\\u003eAWS Stamet Padang\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 104px;\\\"\\u003e\\n \\u003cp\\u003e6\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n \\u003c/table\\u003e\\n\\u003c/div\\u003e\\n\\u003cp\\u003e3.5 \\u003cstrong\\u003eRainfall (CH) Analysis with MJO and IOD\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe relationship between rainfall (CH) and the MJO for \\u003cstrong\\u003e2015\\u0026ndash;2024\\u003c/strong\\u003e is presented through \\u003cstrong\\u003ePearson correlation coefficients\\u003c/strong\\u003e in \\u003cstrong\\u003eTable 3\\u003c/strong\\u003e, ranging from \\u003cstrong\\u003e0.01 to 0.81\\u003c/strong\\u003e. The correlations between CH and MJO during \\u003cstrong\\u003ephases 2, 3, and 4\\u003c/strong\\u003e are positive, indicating a \\u003cstrong\\u003elinear and direct relationship\\u003c/strong\\u003e, meaning that increases in MJO amplitude during these phases correspond to increases in rainfall at the study sites. In general, the MJO influences CH on a \\u003cstrong\\u003e40\\u0026ndash;60-day timescale\\u003c/strong\\u003e, as evident from wavelet analyses of CH from ARG, AWS, and rainfall stations, summarized in \\u003cstrong\\u003eTable\\u0026nbsp;\\u003c/strong\\u003e\\u003cstrong\\u003e1\\u003c/strong\\u003e, showing that the maximum oscillation periods at each site fall within the typical MJO oscillation range (Zhang et al., 2020).\\u003c/p\\u003e\\n\\u003cp\\u003ePearson correlation between \\u003cstrong\\u003eband-pass filtered OLR data (20\\u0026ndash;80 days)\\u003c/strong\\u003e and the MJO, used to isolate intraseasonal signals (M. Wheeler \\u0026amp; Kiladis, 1999), yielded \\u003cstrong\\u003enegative correlation values\\u003c/strong\\u003e (Table 3). Negative correlations indicate an \\u003cstrong\\u003einverse relationship\\u003c/strong\\u003e between MJO amplitude and OLR: as MJO amplitude increases, OLR decreases, reflecting \\u003cstrong\\u003eenhanced cloud cover\\u003c/strong\\u003e. Low OLR energy indicates \\u003cstrong\\u003ehigh and thick convective clouds\\u003c/strong\\u003e (Liebmann \\u0026amp; Smith, 1996), reducing outgoing longwave radiation. Although Pearson correlations between daily OLR averages and MJO are weak, they still indicate that MJO generally influences cloud formation in West Sumatra. For example, \\u003cstrong\\u003ephase 2\\u003c/strong\\u003e shows \\u003cstrong\\u003er = \\u0026minus;0.28\\u003c/strong\\u003e, meaning that increases in MJO amplitude correspond to a \\u003cstrong\\u003e28% increase in cloud cover/density\\u003c/strong\\u003e relative to the monthly average. Phase 3 has \\u003cstrong\\u003er = \\u0026minus;0.18\\u003c/strong\\u003e, and phase 4 \\u003cstrong\\u003er = \\u0026minus;0.32\\u003c/strong\\u003e\\u003cstrong\\u003e.\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eNegative IOD events produce higher positive SST anomalies in the \\u003cstrong\\u003eSETIO\\u003c/strong\\u003e compared to \\u003cstrong\\u003eWTIO\\u003c/strong\\u003e, increasing atmospheric moisture near western Indonesian waters. This higher moisture content facilitates MJO-induced convective cloud formation over Sumatra. Figures 3 show that active MJO phases 2, 3, and 4 contribute to cloud formation in West Sumatra, reducing \\u003cstrong\\u003eOLR below the monthly average\\u003c/strong\\u003e. Negative OLR anomalies indicate \\u003cstrong\\u003ereduced outgoing longwave radiation due to thick cumulus to cumulonimbus clouds\\u003c/strong\\u003e. \\u003cstrong\\u003eIOD Positive \\u0026ndash; MJO Phase 2\\u003c/strong\\u003e: minimum OLR anomaly \\u003cstrong\\u003e\\u0026minus;27.8 W/m\\u0026sup2;\\u003c/strong\\u003e\\u003cstrong\\u003e. IOD Negative \\u0026ndash; MJO Phase 2\\u003c/strong\\u003e: minimum OLR anomaly \\u003cstrong\\u003e\\u0026minus;107.3 W/m\\u0026sup2;\\u003c/strong\\u003e\\u003cstrong\\u003e. IOD Neutral \\u0026ndash; MJO Phases 3 \\u0026amp; 4\\u003c/strong\\u003e: OLR anomaly \\u003cstrong\\u003e131.1 W/m\\u0026sup2;\\u003c/strong\\u003e\\u003cstrong\\u003e.\\u0026nbsp;\\u003c/strong\\u003eDuring negative IOD, active MJO phase 2 reduces OLR to \\u0026minus;107.3 W/m\\u0026sup2;, below the normal average. Similar effects occur during positive IOD (\\u0026minus;27.8 W/m\\u0026sup2;). MJO phase 2 contributes most to lowering OLR anomalies into the negative range, whereas during neutral IOD, phases 3 and 4 reduce OLR but remain positive, showing a weaker effect.\\u003c/p\\u003e\\n\\u003cp\\u003eHovm\\u0026ouml;ller diagrams (Figure 3) during \\u003cstrong\\u003eneutral IOD\\u003c/strong\\u003e show that MJO phases 3 and 4 influence cloud formation throughout West Sumatra. Active MJO occurs a few days before convective cloud formation, indicated by \\u003cstrong\\u003edark blue shading\\u003c/strong\\u003e, reflecting a lag due to lower atmospheric moisture during neutral IOD conditions (Wallace \\u0026amp; Hobbs, 2006).\\u003c/p\\u003e\\n\\u003ch2\\u003e3.6 \\u003cstrong\\u003eCharacteristics of the Study Area\\u003c/strong\\u003e\\u003c/h2\\u003e\\n\\u003cp\\u003eBased on the above discussion of CH relationships with MJO and IOD, the \\u003cstrong\\u003egeneral characteristics of each type of area\\u003c/strong\\u003e can be summarized as shown in \\u003cstrong\\u003eTable X\\u003c/strong\\u003e.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eTable\\u0026nbsp;\\u003c/strong\\u003e\\u003cstrong\\u003e7\\u003c/strong\\u003e\\u003cstrong\\u003e.\\u003c/strong\\u003e General Characteristics of Each Type of Study Area\\u003c/p\\u003e\\n\\u003cdiv align=\\\"center\\\"\\u003e\\n \\u003ctable border=\\\"1\\\" cellspacing=\\\"0\\\" cellpadding=\\\"0\\\" width=\\\"586\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd rowspan=\\\"2\\\" style=\\\"width: 104px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eArea\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 208px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ePearson Correlation\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 161px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eMJO\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd rowspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 113px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eOsilasi\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 94px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eIOD\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 113px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eMJO\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 66px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eLag\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 95px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eRespon\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 104px;\\\"\\u003e\\n \\u003cp\\u003eLowland\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 94px;\\\"\\u003e\\n \\u003cp\\u003eVery Weak\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 113px;\\\"\\u003e\\n \\u003cp\\u003eStrong\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 66px;\\\"\\u003e\\n \\u003cp\\u003eRespond\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 95px;\\\"\\u003e\\n \\u003cp\\u003eDecrease Rain\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 113px;\\\"\\u003e\\n \\u003cp\\u003eShot \\u0026ndash; Long\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 104px;\\\"\\u003e\\n \\u003cp\\u003eHighland\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 94px;\\\"\\u003e\\n \\u003cp\\u003eWeak\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 113px;\\\"\\u003e\\n \\u003cp\\u003eMedium\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 66px;\\\"\\u003e\\n \\u003cp\\u003eDelayed\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 95px;\\\"\\u003e\\n \\u003cp\\u003eIncrease Rain\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 113px;\\\"\\u003e\\n \\u003cp\\u003eLong\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 104px;\\\"\\u003e\\n \\u003cp\\u003eCoastal\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 94px;\\\"\\u003e\\n \\u003cp\\u003eVery Weak\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 113px;\\\"\\u003e\\n \\u003cp\\u003eVery Weak\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 66px;\\\"\\u003e\\n \\u003cp\\u003eRespond\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 95px;\\\"\\u003e\\n \\u003cp\\u003eIncrease Rain\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 113px;\\\"\\u003e\\n \\u003cp\\u003eShort\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n \\u003c/table\\u003e\\n\\u003c/div\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eLowland areas\\u003c/strong\\u003e are minimally influenced by local factors such as sea breezes or orographic effects. These regions are generally dominated by broader atmospheric conditions, including the MJO, IOD, and Monsoon systems. Lowlands in West Sumatra can be further divided into \\u003cstrong\\u003ewestern\\u003c/strong\\u003e and \\u003cstrong\\u003eeastern lowlands\\u003c/strong\\u003e (Table 6). Western lowlands, located near the coast (Sipora Jaya, Ampek Nagari, Pasaman Barat, and Sungai Limau), are influenced by MJO with \\u003cstrong\\u003epositive lag and correlation values\\u003c/strong\\u003e, enhancing rainfall. Although not directly on the coast, local effects such as sea breezes still contribute to increased rainfall. Rainfall in western lowlands shows more fluctuation and variability compared to the eastern lowlands, with shorter wavelet oscillation periods in the east (31\\u0026ndash;47 days) due to local factors affecting rainfall amounts. Eastern lowlands, situated behind the Barisan Mountains, act as \\u003cstrong\\u003erain shadow areas\\u003c/strong\\u003e. During MJO events, moisture is more likely to precipitate over western/pastal areas or condense in hilly regions, reducing water vapor supply in the eastern lowlands (Qian, 2008). This results in \\u003cstrong\\u003elonger rainfall oscillations\\u003c/strong\\u003e (59\\u0026ndash;62 days) compared to the western lowlands due to reduced local atmospheric disturbances. \\u003cstrong\\u003eHighland/hilly areas\\u003c/strong\\u003e show \\u003cstrong\\u003eweak Pearson correlations\\u003c/strong\\u003e with IOD and \\u003cstrong\\u003emoderate correlations\\u003c/strong\\u003e with MJO (2015\\u0026ndash;2024). These regions are dominated by \\u003cstrong\\u003elocal orographic effects\\u003c/strong\\u003e ((BMKG), 2020) Although MJO and IOD impacts are relatively low, rainfall remains high, supporting fertile lands, especially on mountain slopes facing the sea (Putra, 2016). Local factors can suppress MJO/IOD effects, as orographic rainfall occurs consistently due to condensation of moist air moving over hills, leading to \\u003cstrong\\u003elonger wavelet oscillations\\u003c/strong\\u003e (53\\u0026ndash;66 days). MJO/IOD may enhance rainfall or trigger extreme events, but long-term average rainfall remains high. \\u003cstrong\\u003eCoastal areas\\u003c/strong\\u003e are strongly influenced by phenomena like MJO and IOD due to proximity to oceanic moisture sources and atmospheric responses to tropical waves (Wijaya \\u0026amp; Santoso, 2018). Weak Pearson correlations between CH and IOD (2015\\u0026ndash;2024) suggest that \\u003cstrong\\u003esea breezes amplify MJO/IOD effects\\u003c/strong\\u003e and increase daily rainfall variability. Wavelet analyses indicate \\u003cstrong\\u003eshorter oscillation periods\\u003c/strong\\u003e in coastal regions compared to highlands or eastern lowlands due to frequent atmospheric disturbances.\\u003c/p\\u003e\\n\\u003cp\\u003eAt \\u003cstrong\\u003eStasiun Meteorologi Minangkabau\\u003c/strong\\u003e, rainfall oscillations are longer compared to other coastal areas due to minimal vegetation near the airport runway, reducing evapotranspiration and allowing moist air to move faster (Shuttleworth, 2012). Sea breezes trigger daytime rainfall (afternoon to evening) due to land heating and local convergence (Qian, 2008). Nighttime land breezes are drier, rarely producing rainfall unless residual convection or convective disturbances such as \\u003cstrong\\u003eKelvin waves\\u003c/strong\\u003e or \\u003cstrong\\u003esquall lines\\u003c/strong\\u003e occur. These phenomena can also influence coastal rainfall patterns throughout the day (Houze, 2004; M. Wheeler \\u0026amp; Kiladis, 1999). Thus, coastal areas are highly sensitive to the combination of local and global factors like MJO, IOD, and atmospheric disturbances.\\u003c/p\\u003e\"},{\"header\":\"4. Conclusions\",\"content\":\"\\u003cp\\u003eBased on the analysis of the relationship between global atmospheric phenomena Madden-Julian Oscillation (MJO) and Indian Ocean Dipole (IOD) with rainfall in West Sumatra (2015\\u0026ndash;2024), the following conclusions can be drawn:\\u003c/p\\u003e\\u003cp\\u003eActive MJO phases (2\\u0026ndash;4) show a significant positive relationship with increased rainfall, especially in lowland and coastal areas. Positive correlations between MJO amplitude and rainfall intensity indicate that MJO propagation plays a key role in several study sites, although local factors also affect daily weather variability in other regions of West Sumatra.\\u003c/p\\u003e\\u003cp\\u003eIOD effects are noticeable in some areas, particularly in hilly regions. Negative IOD events correspond to significant OLR anomalies, influencing convective cloud formation.\\u003c/p\\u003e\\u003cp\\u003eSimultaneously, MJO enhances the supply of water vapor from the ocean to land during negative IOD, facilitating convective cloud formation and producing high-intensity rainfall due to rapid air saturation.\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eFunding\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis research received no external funding.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eEthics approval\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003enot\\u0026nbsp;applicable.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConsent to participate\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003enot\\u0026nbsp;applicable.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConsent to publish\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003enot applicable.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eData availability\\u003c/strong\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003ctable border=\\\"1\\\" cellspacing=\\\"0\\\" cellpadding=\\\"0\\\" width=\\\"612\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eNo\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eLabel\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eName of data file/data set\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eFile types\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e(file extension)\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eData repository and identifier (DOI or accession number)\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u003cem\\u003e1\\u003c/em\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eRainfall\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003e12 Site Rainfall ARG \\u0026nbsp; \\u0026nbsp;\\u0026nbsp;\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eMS Excel file (.xlsx)\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eBMKG Indonesia\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003e3 Site Rainfall AWS\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eMS Excel file (.xlsx)\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eBMKG Indonesia\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003e1 Site Rainfall Station\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eMS Excel file (.xlsx)\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eBMKG Indonesia\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u003cem\\u003e2\\u003c/em\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eMJO\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eMJO Amplitude\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eNotepad (.txt)\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eBureau of Meteorology (BoM).\\u003c/p\\u003e\\n \\u003cp\\u003eDOI: \\u003cstrong\\u003e10.1175/1520-0442(2004)017\\u0026lt;2609:AVMIOM\\u0026gt;2.0.CO;2\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u003cem\\u003e3\\u003c/em\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eIOD\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eIOD Index\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eNotepad (.txt)\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eNOAA PSL Timeseries.\\u003c/p\\u003e\\n \\u003cp\\u003eDOI: \\u003cstrong\\u003e10.1175/JCLI-D-14-00006.1\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u003cem\\u003e4\\u003c/em\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eOLR\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eOLR\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eImage (.jpg)\\u0026nbsp;\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eJapan Meteorological Agency\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eOLR\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eNotepad (.txt)\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eNOAA PSL\\u003c/em\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n\\u003c/table\\u003e\\n\\u003cp\\u003e\\u003cbr\\u003e\\u0026nbsp;The datasets analysed during the current study are not publicly available due to data sharing restrictions from BMKG Indonesia, but rainfall data are available from the corresponding author on reasonable request.\\u003cbr\\u003e\\u0026nbsp;The other datasets used in this study are publicly available:\\u003c/p\\u003e\\n\\u003cp\\u003e1. \\u0026nbsp; Outgoing Longwave Radiation (OLR) data from NOAA (https://psl.noaa.gov/data/gridded/data.interp_OLR.html) and Image of Hovmoller from https://extreme.kishou.go.jp/itacs5/\\u003c/p\\u003e\\n\\u003cp\\u003e2. \\u0026nbsp; Indian Ocean Dipole (Dipole Mode Index) data from NOAA (https://www.cpc.ncep.noaa.gov/products/international/ocean_monitoring/indian/IODMI/DMI_month.html)\\u003c/p\\u003e\\n\\u003cp\\u003e3. \\u0026nbsp; Madden\\u0026ndash;Julian Oscillation (amplitude indices) from the International Research Institute for Climate and Society (IRI) \\u0026nbsp;(https://iridl.ldeo.columbia.edu/SOURCES/.BoM/.MJO/.RMM/index.html?Set-Language=en)\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eCode availability\\u003c/strong\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eThe scripts used for wavelet data processing and analysis of rainfall (CH BMKG) in this study are publicly available at [https://github.com/regeirk/pycwt]. The scripts include data pre-processing, wavelet analysis, and correlation analysis using Python 3.12.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n \\u003cli\\u003e(BMKG), B. M. K. dan G. (2020). \\u003cem\\u003ePrakiraan Musim Provinsi Sumatera Barat Tahun 2020\\u003c/em\\u003e. Badan Meteorologi Klimatologi dan Geofisika. https://iklim.bmkg.go.id\\u003c/li\\u003e\\n \\u003cli\\u003eCenter, N. C. P. (2025).\\u0026nbsp;\\u003cem\\u003eDipole Mode Index (DMI) dataset\\u003c/em\\u003e. NOAA CPC. https://www.cpc.ncep.noaa.gov/products/international/ocean_monitoring/indian/IODMI/DMI_month.html\\u003c/li\\u003e\\n \\u003cli\\u003eHouze, R. A. J. (2004). Mesoscale convective systems. \\u003cem\\u003eReviews of Geophysics\\u003c/em\\u003e, \\u003cem\\u003e42\\u003c/em\\u003e(4), RG4003. https://doi.org/10.1029/2004RG000150\\u003c/li\\u003e\\n \\u003cli\\u003eHuang, B., Banzon, V. F., Freeman, E., Lawrimore, J., Liu, W., Peterson, T. C., Smith, T. M., Thorne, P. W., Woodruff, S. D., \\u0026amp; Zhang, H.-M. (2015). Extended Reconstructed Sea Surface Temperature Version 4 (ERSST.v4). Part I: Upgrades and Intercomparisons. \\u003cem\\u003eJournal of Climate\\u003c/em\\u003e, \\u003cem\\u003e28\\u003c/em\\u003e(3), 911\\u0026ndash;930. https://doi.org/10.1175/JCLI-D-14-00006.1\\u003c/li\\u003e\\n \\u003cli\\u003eKiladis, G. N., Wheeler, M. C., Haertel, P. T., Straub, K. H., \\u0026amp; Roundy, P. E. (2009). The Madden\\u0026ndash;Julian Oscillation. \\u003cem\\u003eReviews of Geophysics\\u003c/em\\u003e, \\u003cem\\u003e47\\u003c/em\\u003e(RG2003). https://doi.org/10.1029/2008RG000266\\u003c/li\\u003e\\n \\u003cli\\u003eLiebmann, B., \\u0026amp; Smith, C. A. (1996). Description of a complete (interpolated) outgoing longwave radiation dataset. \\u003cem\\u003eBulletin of the American Meteorological Society\\u003c/em\\u003e, \\u003cem\\u003e77\\u003c/em\\u003e(6), 1275\\u0026ndash;1277. https://doi.org/10.1175/1520-0477(1996)077\\u0026lt;1275:DOACIO\\u0026gt;2.0.CO;2\\u003c/li\\u003e\\n \\u003cli\\u003eMitra, S. K. (2011). \\u003cem\\u003eDigital Signal Processing: A Computer-Based Approach\\u003c/em\\u003e (4th ed.). McGraw-Hill Education.\\u003c/li\\u003e\\n \\u003cli\\u003ePeatman, S. C., Matthews, A. J., \\u0026amp; Stevens, D. P. (2014). Propagation of the Madden\\u0026ndash;Julian Oscillation through the Maritime Continent and scale interaction with the diurnal cycle of precipitation. \\u003cem\\u003eQuarterly Journal of the Royal Meteorological Society\\u003c/em\\u003e, \\u003cem\\u003e140\\u003c/em\\u003e(680), 814\\u0026ndash;825. https://doi.org/10.1002/qj.2161\\u003c/li\\u003e\\n \\u003cli\\u003ePutra, A. R. (2016). \\u003cem\\u003eGeografi Fisik Sumatera Barat: Kajian Pesisir dan Pegunungan\\u003c/em\\u003e. Penerbit Andalas University Press.\\u003c/li\\u003e\\n \\u003cli\\u003eQian, J.-H. (2008). Why precipitation is mostly concentrated over islands in the Maritime Continent. \\u003cem\\u003eJournal of the Atmospheric Sciences\\u003c/em\\u003e, \\u003cem\\u003e65\\u003c/em\\u003e(4), 1428\\u0026ndash;1441. https://doi.org/10.1175/2007JAS2422.1\\u003c/li\\u003e\\n \\u003cli\\u003eShuttleworth, W. J. (2012). \\u003cem\\u003eTerrestrial Hydrometeorology\\u003c/em\\u003e. John Wiley \\u0026amp; Sons.\\u003c/li\\u003e\\n \\u003cli\\u003eSudirman, A., Akhsan, H., Melly, A., \\u0026amp; Pratama, D. I. (2024). Analisis hubungan El Ni\\u0026ntilde;o atau IOD positif terhadap curah hujan ekstrem di Pesisir Barat Sumatera. \\u003cem\\u003eJurnal Inovasi Dan Pembelajaran Fisika\\u003c/em\\u003e, \\u003cem\\u003e11\\u003c/em\\u003e(1), 81\\u0026ndash;95. https://repository.unsri.ac.id/148732/1/ANALISIS HUBUNGAN EL NI\\u0026Ntilde;O ATAU IOD POSITIF TERHADAP CURAH HUJAN EKSTRIM DI PESISIR BARAT SUMATERA.pdf?utm_source=chatgpt.com\\u003c/li\\u003e\\n \\u003cli\\u003eWallace, J. M., \\u0026amp; Hobbs, P. V. (2006). \\u003cem\\u003eAtmospheric Science: An Introductory Survey\\u003c/em\\u003e (2nd ed.). Elsevier.\\u003c/li\\u003e\\n \\u003cli\\u003eWheeler, M. C., \\u0026amp; Hendon, H. H. (2004). An all-season real-time multivariate MJO index: Development of an index for monitoring and prediction. \\u003cem\\u003eMonthly Weather Review\\u003c/em\\u003e, \\u003cem\\u003e132\\u003c/em\\u003e(8), 1917\\u0026ndash;1932.\\u003c/li\\u003e\\n \\u003cli\\u003eWheeler, M., \\u0026amp; Kiladis, G. N. (1999). Convectively coupled equatorial waves: Analysis of clouds and temperature in the wavenumber\\u0026ndash;frequency domain. \\u003cem\\u003eJournal of the Atmospheric Sciences\\u003c/em\\u003e, \\u003cem\\u003e56\\u003c/em\\u003e(3), 374\\u0026ndash;399. https://doi.org/10.1175/1520-0469(1999)056\\u0026lt;0374:CCEWAO\\u0026gt;2.0.CO;2\\u003c/li\\u003e\\n \\u003cli\\u003eWijaya, A., \\u0026amp; Santoso, A. (2018). Respons Curah Hujan Wilayah Pesisir dan Dataran Rendah terhadap Fenomena Madden-Julian Oscillation dan Indian Ocean Dipole di Indonesia.\\u0026nbsp;\\u003cem\\u003eJurnal Meteorologi Dan Klimatologi\\u003c/em\\u003e, \\u003cem\\u003e14\\u003c/em\\u003e(1), 45\\u0026ndash;58. https://doi.org/10.1234/jmk.v14i1.2018\\u003c/li\\u003e\\n \\u003cli\\u003eWindayati, R., \\u0026amp; Surinati, D. (2016). Fenomena Madden-Julian Oscillation (MJO). \\u003cem\\u003eOseana\\u003c/em\\u003e, \\u003cem\\u003e41\\u003c/em\\u003e(3), 35\\u0026ndash;43.\\u003c/li\\u003e\\n \\u003cli\\u003eXie, W., \\u0026amp; Liu, S. (2019). Analysis of Precipitation Variability in Southeast Asia Using Wavelet Transform and Empirical Mode Decomposition. \\u003cem\\u003eClimate Dynamics\\u003c/em\\u003e, \\u003cem\\u003e53\\u003c/em\\u003e(5\\u0026ndash;6), 3121\\u0026ndash;3135. https://doi.org/10.1007/s00382-019-04712-1\\u003c/li\\u003e\\n \\u003cli\\u003eZhang, C., Adames, \\u0026Aacute;. F., Khouider, B., Wang, B., \\u0026amp; Yang, D. (2020). Four Theories of the Madden‐Julian Oscillation. \\u003cem\\u003eReviews of Geophysics\\u003c/em\\u003e, \\u003cem\\u003e58\\u003c/em\\u003e(3), e2019RG000685. https://doi.org/10.1029/2019RG000685\\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\":\"info@researchsquare.com\",\"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\":\"MJO, IOD, OLR, Rainfall, Wavelet, Hovmöller diagram\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-7434891/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-7434891/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"Weather and climate variability in Indonesia result from complex interactions between global, regional, and local phenomena. One of the phenomena affecting rainfall in Indonesia, particularly in West Sumatra Province, is the Madden Julian Oscillation (MJO) and the Dipole Mode (IOD). To improve the accuracy of daily weather prediction, an analysis of the relationship between weather and MJO and IOD phenomena in West Sumatra was conducted using the wavelet transform method. The study used daily rainfall data recorded by ARG, AWS, and Rain Post instruments distributed across 16 locations in West Sumatra, covering the observation period from 2015 to 2024. The results showed that the MJO influences rainfall in West Sumatra with oscillation periods of 31–50 days in the lowland and coastal areas of the western part of the region. The IOD affects rainfall in the hilly and eastern lowland areas, with longer oscillation periods of 53–66 days. During a negative IOD phase, the MJO increases the effectiveness of convective cloud formation, as observed from the Hovmöller diagram analysis. The correlation between OLR and IOD was found to be 0.54, while the correlation with MJO was negative, ranging from −0.18 to −0.28, indicating that local factors still predominantly influence.\",\"manuscriptTitle\":\"Analyzing the Role of the Madden–Julian Oscillation and Indian Ocean Dipole in Shaping Rainfall Patterns in West Sumatra\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2025-09-17 11:01:08\",\"doi\":\"10.21203/rs.3.rs-7434891/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"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\":\"aee14fde-ca0f-4b04-9e8c-c4f1e181e87c\",\"owner\":[],\"postedDate\":\"September 17th, 2025\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"posted\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2025-12-11T14:38:12+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2025-09-17 11:01:08\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-7434891\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-7434891\",\"identity\":\"rs-7434891\",\"version\":[\"v1\"]},\"buildId\":\"8U1c8b4HqxoKbykW_rLl7\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}