Southerly Surge Impact on Rainfall Patterns in Southern Indonesia during Winter Monsoon and Madden–Julian Oscillation (MJO)

Abstract

The impact of the southerly surge’s interaction with the MJO on rainfall in this study was investigated using daily rainfall data from 2140 weather-observation stations. The southern surge, which coincided with the MJO, enhanced rainfall in the western research region, with Yogyakarta seeing the greatest increase at 4.69 mm/day. Meanwhile, the southern surge that occurred without the MJO increased rainfall in the eastern region, with West Nusa Tenggara seeing the greatest rise at 3.09 mm/day. However, the southerly surge has the effect of lowering rainfall in Jakarta, reaching −2.21 mm/day when the MJO is active and −1.58 mm/day when the MJO is inactive. The southerly surge causes extreme rainfall to only occur in a small part of certain areas, so it tends to significantly reduce the possibility of extreme rainfall. In the southern part of the Indonesian maritime continent, the southerly surge predominates over the MJO, supporting increased water vapor transport. Rainfall mostly increases in the afternoon and decreases in the morning when the southerly surge occurs, whether there is the MJO or not. Convective instability analysis indicates that SS increases precipitation, most likely by raising vertically integrated moisture flux convergence, with a correlation coefficient value of 0.82.

1. Introduction

The Indonesia Maritime Continent (IMC) is a unique geographical area situated between two oceans (the Pacific and Indian Oceans) and two continents (Asia and Australia). In addition, IMC features a sophisticated mountainous system comprising more than 13,000 small islands and five major islands: Papua, Kalimantan, Sumatra, Sulawesi and Java [1]. Variations in global winds, commonly referred to as monsoon winds in the form of the East and South Asian monsoon and the Australian monsoon, traverse IMC due to its unique geographic location, affecting climatic conditions in the country. Monsoon activity significantly influences weather formation in the areas it passes through and is often associated with synoptic disturbances in these regions. IMC is a transitional zone between the Australian Monsoon (AUM) and Asian Monsoon (AM) systems, according to [2]. As a result, IMC experiences seasonal variations in wind and rainfall patterns. In general, the rainy season in IMC usually coincides with the strengthening of the AM, which is characterized by the strengthening of westerly wind activity in the southern equatorial region of IMC and occurs around the beginning of November and ends at the end of March (NDJFM), which is also known as the Asian Winter Monsoon (AWM) Circulation [3,4]. AWM activity is often associated with the rainy season in most parts of IMC.

During the AWM, cold air masses usually move from the center of high pressure on mainland Asia eastward and southward over IMC waters, surrounded by multiple relatively warm seas. The propagation of this cold air mass is referred to as a cold surge (CS), and it is one of the synoptic-scale weather phenomena that significantly impacted the AWM [5]. Along with the CS phenomenon, there are other meteorological phenomena called the southerly surge (SS) that are like CS and originate from the southern portion of the Indian Ocean, close to Australia. This air mass moved toward Java Island and East Nusa Tenggara from the Indian Ocean on Australia’s west coast. Monsoon activity in the summer is influenced by a surge that originates from Australia’s west coast. The weak east–west pressure gradient surrounding Australia’s west coast is what causes this surge, which is a geostrophic wind flow. At the height of the AUM, convective activity in the region is affected by the convergence of surges from Australia’s west coast [6]. According to research [7], there is a meridional wind wave from the extratropic to the tropics during the SS in eastern India. The southeast-south wind blows around the east Indian Ocean, south of the Bay of Bengal and out of the subtropical Southern Hemisphere at the time of surge onset. This surge’s flow meets the West Asian monsoon flow, which runs from the Philippines to the Arabian Sea. They employ the SS index, which is based on meridional wind parameters, to observe the spread of SS activity. Refs. [6,8,9] have all documented the impact of Australian west coast surges on summertime monsoonal activity. They hypothesized that geostrophic winds resulting from an east–west pressure gradient off Australia’s west coast were responsible for these surges. On the other hand, not much is known about the characteristics of the surges and how they affect rainfall in the IMC, especially the SS that occurs in AWM.

There is currently a severe lack of research on SS, particularly as it relates to Indonesia’s rainfall. The few existing studies on this topic are mostly local Indonesian research. According to Amelia’s [10] final assignment, one reason for reduced rainfall in several IMC areas in January was the spread of SS towards the equator. Nonetheless, the study’s findings do not provide a detailed explanation of how SS composites affect rainfall in the southern IMC’s NDJFM rainy season. In his last work, Hermawanto [11] also demonstrated that a period of monsoon lull during the AWM was caused by a strengthening of southerly winds from Australia’s west coast. In his master’s thesis, Taryono [12] documented how the interplay of CS and SS significantly affects the patterns of precipitation in the IMC. The effect of SS on rainfall patterns in IMC, particularly in the southern part of IMC along Java Island to East Nusa Tenggara, is still unknown based on several earlier research findings that were previously discussed. It would also be interesting to investigate how it interacts with the poorly studied Madden–Julian Oscillation (MJO), which affects rainfall in the southern portion of the IMC. The MJO is the eastward movement of large-scale circulating cells oriented to the equatorial (zonal) plane in the troposphere. On the synoptic scale, the MJO is linked to increased low-level convergence and ascent while upper troposphere winds diverge from the updraft. An increase in deep convection coincides with this circulation. The cycle is divided into eight phases, each of which corresponds to 1/8 of the full cycle. Individual MJO events can last between 30 and 60 days. Depending on the phase, the MJO brings organized convection and related circulation that favor a region for either dry or rainy conditions. According to earlier research [13,14,15,16,17], the MJO can influence the frequency and intensity of global temperature and precipitation phenomena. Numerous earlier studies have examined the relationship between the MJO and other synoptic phenomena influencing the distribution of rainfall in Indonesia. For instance, Trismidianto et al. [18] reported variations in the influence patterns of CS, Cross Equatorial Northerly Surge (CENS) and the Borneo Vortex on rainfall in Indonesia during active and inactive periods of the MJO. On the other hand, no information has been published about how MJO and SS affect Indonesian rainfall patterns, particularly from Java Island to East Nusa Tenggara. Based on this, it is critical to understand how SS activity affects the pattern of rainfall, particularly the extreme rainfall that occurs using observational data from the southern portion of the IMC (from Java Island to East Nusa Tenggara). There have not been any large-scale SS studies using observation data, so one advantage of research is the availability of observation data from 2140 weather-observation stations. More comprehension of SS operations and their effects advances our understanding of rainfall patterns and the forecasting of extreme rainfall, particularly during the occurrence of this phenomenon.

2. Data and Method

2.1. Data Used in This Study

The meridional wind parameter data used to identify southerly surges comes from ERA5 reanalysis data, which are global atmospheric reanalysis data from the European Center for Medium-Range Weather Forecast (ECMWF). The data cover the Earth on a 30 km grid and resolves the atmosphere using 137 levels from the surface up to a height of 80 km [19]. ERA5 includes information about uncertainties for all variables at reduced spatial and temporal resolutions (https://www.ecmwf.int/en/forecasts/dataset/ecmwf-reanalysis-v5, accessed on 1 September 2022). We utilize several additional ERA5 parameters in addition to meridional wind data to measure integrated water vapor transport (IVT), including zonal wind, mean sea level pressure (MSLP), sea surface temperature (SST) and specific humidity. To analyze convective instability, several additional parameters are needed, including surface temperature, dew point temperature, convective inhibition (CINH), vertically integrated moisture flux convergence (VIMFC) and convective available potential energy (CAPE).

As seen in Figure 1a, we use daily rainfall-observation data from 2140 weather-observation stations operated by the Meteorology, Climatology, and Geophysics Agency (BMKG) that are dispersed throughout Java Island to East Nusa Tenggara. Observational data were employed from January 2001 to March 2019 for the NDJFM. Averaging the rainfall values across all stations in each study area was done as part of the observational rainfall analysis. The study area is divided based on the number of provinces from Java to East Nusa Tenggara. The study area is divided into nine provinces: Banten, designated as Region 1 (R1), Jakarta, designated as Region 2 (R2), West Java, designated as Region 3 (R3), Central Java, designated as Region 4 (R4), Yogyakarta, designated as Region 5 (R5), East Java, designated as Region 6 (R6), Bali, designated as Region 7 (R7), West Nusa Tenggara, designated as Region 8 (R8) and East Nusa Tenggara, designated as Region 9 (R9) (Figure 1b). Out of the total number of 2140 weather-observation stations, there are 77 in R1, 27 in R2, 294 in R3, 535 in R4 and 70, 927 and 98 in R5, R6 and R7, respectively. There are 61 and 51 weather-observation stations in R8 and R9, respectively. Satellite data are utilized for diurnal analysis and rainfall analysis along the SS route, as the available observational data only includes daily data on land. The Global Satellite Mapping of Precipitation (GSMaP) gauge version 8, which has a spatial resolution of 0.1° × 0.1°, was used to calibrate the satellite data that the microwave-infrared (IR) combined (MVK) clock meter acquired. GSMaP data from the Japan Aerospace Exploration Agency (JAXA) have been validated and calibrated with both sharp and radar data in Japan with good validation results [20], https://sharaku.eorc.jaxa.jp/GSMaP (accessed on 1 September 2022) is the link to access GSMaP data.

We used the MJO index in conjunction with Outgoing Longwave Radiation (OLR) data to identify MJO events. OLR is long-wave radiation that enters space from the Earth and clouds. A low anomaly value suggests a tall, cold cloud or cold surface when viewed in terms of OLR anomalies, whereas a high anomaly value indicates the opposite phenomenon [21]. OLR data, with its daily average temporal resolution and 2.5° × 2.5° spatial resolution, is the world’s global data. The data can be accessed at https://psl.noaa.gov/data/gridded/data.olrcdr.interp.html (accessed on 1 September 2022) and spans the years 1974 to the present. The MJO index information was sourced from https://www.cpc.ncep.noaa.gov/products/precip/CWlink/MJO/ (accessed on 1 September 2022). Real-time multivariate MJO indexes 1 (RMM1) and 2 (RMM2) are used to define MJO events. Ref. [22] have shown that RMM1 and RMM2 together provide information on the state of the MJO throughout the tropics and are accurate year-round. These indices are then used to calculate the amplitude of the MJO events as follows: √ (RMM1²+ RMM2²). As per the findings of [23,24,25], an MJO is classified as strong or weak based on whether its amplitude is greater or less than 1. In addition, there are eight phases to the MJO event, and the location of the MJO convective center is indicated by each phase. The convective center of the MJO propagates eastward from west Africa (phase 1) to the east, passing over the Indian Ocean (phases 2 and 3), the Maritime Continent (phases 4 and 5), migrating to the western Pacific (phases 6 and 7), and decaying at phase 8. However, in this study, we divided the active MJO and inactive MJO by defining the active and inactive MJO based on [26,27], with a slight modification in the active MJO definition by adding phase 5 during strong conditions. The active MJO is defined during phases 2, 3, 4 and 5, which have an amplitude value greater than or equal to 1, while the inactive is all days with the MJO in phases 2, 3, 4 and 5 with an amplitude value less than 1 added all the days when the MJO is in phases 1 and 5–8.

2.2. Southerly Surge Identification

The identification of SS events in this study was predicated on earlier research by [7], who computed the SS index from the meridional wind value, which at the time was greater than the average daily meridional wind variance value. This approach is used for SS events in western Australia or southern Indonesia since they are comparable and take place in the same area, the Southern Hemisphere. Meanwhile, the selection of SS occurrence areas in the western region of Australia (25–30° S and 105–110° E) was based on research conducted by [9], which stated that wind variations in this region have an important role in monsoon circulation. Taryono [12] also performed SS identification using a similar method. As indicated by the red dotted line in Figure 2a, this study indicates that the daily mean meridional wind variance value at 850 hPa for the western region of Australia (25–30° S and 105–110° E) from January 2001 to March 2019 is approximately 9.5 m/s. During NDJFM, from January 2001 to March 2019, there were 61 SS events with meridional wind values that were higher than the variance value. This SS event may be unusual; Ref. [7] only discovered 62 SS events in the Eastern Indian Ocean over 23 years. Of these 61 SS events, 17 happened during the active MJO with an average meridional wind speed of 10.85 m/s, and 44 happened during the inactive MJO with an average meridional wind speed of 10.79 m/s (Figure 2b). According to Figure 2c, the highest number of SS events overall happened in December (15 events), followed by January (14 events) and November and February (12 events each). With 10 events, SS happened the least in March. Except for January, when it mostly happens during the active MJO, most SS happens when the MJO is dormant. Tropical cyclone events that occurred in northern and western Australia as well as the Indian Ocean along the SS event path have not been included in the filtered SS events examined in this research. Information regarding tropical cyclone events is obtained from the following link: https://tropic.ssec.wisc.edu/storm_archive/aussie.html (accessed on 1 September 2022).

2.3. Extreme Rainfall, Integrated Water Vapor Transport and Convective Instability

To analyze the interaction of SS with MJO on extreme rainfall, the probability of changes in extreme events is used, which is calculated using a modified equation from [14] (Equation (1)).

$$\Delta P=\frac{\left({P_{each condition}-P}_{MJO active or inactive}\right)}{P_{MJO active or inactive}}\times 100\%$$

(1)

where ΔP is the probability of changes in extreme events (hereinafter abbreviated as PCE) for each condition of MJO (active or inactive). Trismidianto et al. [18] investigated how the Borneo Vortex, CENS and CS interact to influence extreme rainfall during MJO over the IMC using a similar formulation.

Moreover, we applied moisture transport analysis by calculating the IVT using the following equation (Equation (2)). We analyzed the composite of IVT to identify the moisture condition in relation to precipitation during certain phenomena and their combinations. Moreover, we obtained the VIMFC data from ERA-5, which are mainly calculated using Equation (3).

$$IVT=\sqrt{{\left(\frac{1}{g} {\int }_a^{b}qu dp\right)}^2+{\left(\frac{1}{g} {\int }_a^{b}qv dp\right)}^2} .$$

(2)

$$VIMFC=\frac{-1}{g}{\int }_a^b\left(\frac{duq}{dx}+\frac{dvq}{dy}\right)dp$$

(3)

where q is specific humidity, u is zonal wind velocity, v is meridional wind velocity and p is pressure level. The limits of integrals, a and b represent the lower and upper pressure levels of IVT and VIMFC calculations, respectively. We integrated the IVT from 1000 hPa to 100 hPa. While the calculation of VIMFC based on ERA5 is from the surface level to the top of the model.

The convective instability is analyzed using several variables, namely lifting condensation level (LCL), level of free convection (LFC), level of neutral buoyancy (LNB), CAPE and CINH. The LCL refers to the height at which an air parcel, when lifted adiabatically, becomes saturated. The LCL formula proposed by [28] is:

$$z_{LCL }=z+\left(20+\frac{T-273.15 K}{5 K}\right)\left(100 \mathrm{m}\right)\left(1-{RH}_l\right)$$

(4)

where z is the parcel’s height, T is its absolute temperature, K denotes units of kelvins, m denotes units of meters and ${RH}_l$ ranges from 0 to 1. The intention of [28] is for this expression to be applied to parcels with 0.5 $\le { RH}_l$ $\le$ 1 and 273 < T < 303 K. The LFC is the level at which the parcel is warmer than its environment and accelerates upward without additional mechanical lifting. The LNB or the Equilibrium Level (EL) is the level where the parcel’s temperature is colder than the environment. The CAPE quantifies the energy accessible to elevate an air parcel to the neutral buoyancy level from a level characterized as the level of free convection [29]. The CAPE is the energy available for the free convective process and is given by the following formula:

$$CAPE=g{\int }_{z_{LFC}}^{z_{LNB}}B dz\approx g{\int }_{z_{LFC}}^{z_{LNB}}\left(\frac{{\theta }_v-{\widehat{\theta }}_v}{{\widehat{\theta }}_v}\right)dz$$

(5)

where g is the acceleration due to gravity, B is the buoyancy force, θ is the virtual potential temperature of the air parcel (denotes that of the environment) and z is the altitude. S denotes Surface, LFC denotes the Level of Free Convection and LNB denotes the Level of Non-Buoyancy [30].

In contrast, the CINH is the energy that must be overcome for the convection process to occur and is given by the following formula [30]:

$$CINH=g{\int }_{z_s}^{z_{LFC}}B dz\approx g{\int }_{z_s}^{z_{LFC}}\left(\frac{{\theta }_v-{\widehat{\theta }}_v}{{\widehat{\theta }}_v}\right)dz$$

(6)

This research began by identifying active SS and MJO events. Next, a combined plot of rainfall distribution in the area under study was created by considering anomalies related to normal conditions as well as SS, active MJO and active SS + MJO days. Under the same conditions, similar plots are created for the 95th percentile of extreme precipitation, including its PCE. Next, an analysis was carried out to determine how SS, MJO and their combined effects influence the distribution of rainfall in various study areas. Apart from that, what was studied was the impact of SS and MJO on daily and monthly rainfall variations. Additionally, further analyses using IVT, and other selected variables were performed to study possible explanations behind the observed changes in rainfall distribution.

3. Result and Discussion

3.1. Climatology of SS and Large-Scale Atmospheric Conditions

3.1.1. Climatology of the Rainfall and SS

The NDJFM seasonal average rainfall and 850 hPa wind speed in the study area, averaged from January 2001 to March 2019, are displayed in Figure 3a,d. The rainfall shown in Figure 3a–c is derived from GSMaP data because observational data are only available on land and cannot indicate the contribution of MJO and SS from the ocean. Certain areas have greater rainfall than other areas, such as the Java Sea along the north coast of Java Island and the Indian Ocean along the west coast of Sumatra Island (Figure 3a). These results support previous research that found consistency and reliability in the observed patterns [18,23,31,32,33]. According to [26,34,35], MJO contributed to the high rainfall experienced on the north coast of Java and the west coast of Sumatra. This emphasizes how important large-scale atmospheric phenomena are to regional rainfall patterns. Higher rainfall also occurs on several islands of Java, apart from the ocean. This observation is corroborated by the existence of strong low-level winds associated with the MJO, demonstrating the coupling of atmospheric circulation and precipitation variability that causes precipitation in the AWM [35]. According to Satiadi et al. [36], the high rainfall that Java Island often experiences is also correlated with the presence of CENS, CS or both. Strong southeasterly low-level winds originate from the west coast of Australia and move towards the Indian Ocean (Figure 3d). According to [18], the existence of the MJO is related to low-level, strong winds observed from the Indian Ocean towards the islands of Sumatra and Java. Higher rainfall in southern Indonesia, especially Java Island, is the result of interactions between large-scale circulation and complex local terrain. This phenomenon, referred to as wind field interaction, emphasizes how important it is to take geographical features into account when analyzing rainfall patterns.

On the day of the SS event, the amount of rainfall and wind speed (850 hPa) are displayed in Figure 3b,e. On SS days, there is an increase in rainfall, particularly in the northern Java Island region, in the western Indian Ocean off the island of Sumatra and in the southern Java region (Figure 3b). On land, there was also a lot of rain in a few locations throughout Java Island, up to R9. The pattern of high rainfall distribution on SS days is nearly identical to that of the NDJFM average rainfall; however, the high rainfall on SS days is more widely distributed. Strong low-level jets are seen moving from the identification areas SS (25–30° S and 105–110° E) toward the Indian Ocean west of Sumatra Island, then following Java Island to R9 (Figure 3e). The distribution of rainfall anomalies during the combined SS event days is the same as what is shown in Figure 3c. This demonstrates how SS modifies the intensity of rainfall, thereby influencing rainfall patterns in southern Indonesia. Rainfall intensity is increasing, as evidenced by positive rainfall anomalies on Java Island’s north coast and in the Indian Ocean to the west and south of Sumatra Island. There has also been a notable increase in rainfall on land in several locations up to R9 along Java Island. On the other hand, there was also a decrease in rainfall in a few locations on the island of Java, R7, R8 and R9, which was indicated by negative rainfall anomalies (Figure 3c). The low-level wind anomaly distribution pattern and the low-level wind distribution pattern on the day of the combined SS event are identical, as shown in Figure 3f. This indicates that wind speed increases along the SS path due to the SS. Ascending to Java Island, Sumatra Island and the western Indian Ocean, up to R9, indicates an increase in wind speed (Figure 3f). The wind deflection from Java to R9 is also visible if there is SS. The NDJFM wind average, on the other hand, only indicates southeast winds that are moving toward the Indian Ocean. Strengthened low-level wind surges cause changes in wind direction from the western coast of Australia, parallel along Java Island, to R9. Wind direction shifts are induced by increased low-level wind surges that originate on Australia’s western coast and travel parallel to the island of Java until reaching R9. Ref. [7] also discovered that cross-equatorial wind direction changes can result from amplified low-level wind surges, extending from subtropical regions to the east Indian Ocean to the southern Bay of Bengal. Ref. [6] assert that the surge from Australia’s west coast influences the summertime monsoon activity. This was backed up by [9], who observed that, while there appears to be a high association between surge and monsoon activity before and during the onset of the Australian monsoon, this relationship fades as the rainy season approaches in the Australian region. However, this study also discovered that the AWM activity at NDJFM was influenced by the surge that began on Australia’s west coast. This finding aligns with the research findings of [12], who revealed that SS can happen concurrently with CS activity or during the AM in addition to the AUM.

Figure 4a,b indicates that the distribution pattern of daily average rainfall on the days of the NDJFM and SS occurrences is nearly identical, based on observational data. These results also validate Figure 3a,b, which indicate that the rainfall pattern during NDJFM and SS days using satellite data is consistent with observation data along Java Island to East Nusa Tenggara. When SS occurs, R2, R3 and R6 distribute low rainfall (Figure 4b); however, specific places from Java to R9 experience heavier rainfall, with the maximum intensity levels on SS and NDJFM days noted in R4 and R5 (Figure 4a). Rainfall intensity in R4, R5 and R7 was greater on the day of the SS event than during the NDJFM. This demonstrates how the presence of SS causes rainfall to vary at various sites throughout the R1 until R9 region. Rainfall increased greatly in R4, R5 and R7, reaching a daily rise of 3 mm/day, but declined in numerous sites in R6 to −3 mm/day, as shown in Figure 4c. This demonstrates that SS contributes to both increased and decreased rainfall intensity in the R1–R9 research area. The pattern of increasing rainfall along Java Island to East Nusa Tenggara from observation data, is consistent with the satellite data presented in Figure 3c. This demonstrates that rainfall data from observational data are consistent with satellite data.

3.1.2. Large-Scale, MJO and Monsoon Conditions Associated with SS

Figure 5a,b illustrate the pattern of MSLP intrusion in the surface layer during NDJFM and the composite SS event, where MSLP intrusion is observed towards the Indian Ocean in the western part of Sumatra Island and along Java Island to East Nusa Tenggara. Low-level jets are made possible along the SS route as a result, as evidenced by the MSLP values decreasing in the direction of Java Island, R7, R8 and R9 (Figure 5c). These results are in line with earlier research [8,37], which contends that a surge, or geostrophic wind flow, is brought on by a weak east–west pressure gradient near Australia’s west coast. Figure 5a,b further demonstrate that, although the distribution of high SST in the Indian Ocean is wider during NDJFM, the pattern of SST value distribution is essentially the same during composite SS events and NDJFM. High SST values were observed to be distributed from Java Island to R9 during the composite SS event. Because a warmer SST will increase the amount of water vapor available to support the formation of rain clouds, the surrounding area will experience more rainfall the higher or warmer the SST value [38]. The wind movement that carries masses of water vapor towards Java Island and its surroundings is made possible by the very significant difference in SST anomalies in the SS route area between the northern part of Java Island and its surroundings. Figure 5d,e depict similar OLR distribution patterns during NDJFM and composite SS events, respectively. However, OLR values during composite SS events are lower along Java Island than R9. This demonstrates that low-level jets from the SS as well as convective clouds connected to the MJO are growing (Figure 5d). Significantly more rain clouds are present along Java Island to R9, as indicated by the negative anomaly from the OLR (Figure 5f).

3.2. Rainfall Response to Southerly Surges

3.2.1. Rainfall Patterns during MJO Condition

In the NDJFM period, the average daily rainfall in the active and inactive MJO periods is displayed in Figure 6a,b. The pattern of rainfall distribution is nearly the same whether the MJO is active or not; that is, the amount of rainfall is more evenly distributed throughout the island of Java and is more intense in R4 and R5. On the other hand, the intensity of the rainfall is higher during an active MJO than during an inactive one. The MJO had an impact on rainfall in the IMC, including on the island of Java and its environs, as evidenced by the extensive distribution of high rainfall that previous researchers [25,39] reported on Java Island. The rainfall intensity around West Java (R1 and R3) and Central Java (R4 and R5) is higher when SS occurs in an active MJO than when an active MJO occurs in NDJFM, as Figure 6c illustrates. An increase in rainfall intensity is evident in most of the distribution of high positive anomalies for rainfall in R1, R3, R4 and R5 (Figure 6e). On the other hand, the intensity of rainfall at R2, R6 and R7 was less than during the MJO’s active period at NDJFM. Nearly all the regions have the same distribution of negative rainfall anomalies (Figure 6e). In an inactive MJO, the SS experiences less intense rainfall, but the pattern of distribution is nearly the same as in an active MJO (Figure 6d). Positive anomalies are smaller in areas R1, R3, R4 and R5 when the SS occurs in an inactive MJO than when an active MJO is present (Figure 6f). In contrast, areas R7, R8 and R9 saw a rise in rainfall during the MJO’s inactive phase as opposed to a fall during its active phase. This indicates that when MJO occurs, SS affects the amount of rainfall that increases in the western part of the study area. On the other hand, when SS coincides with inactive MJO conditions, a greater increase in rainfall is observed in the eastern portion of the study area.

Out of the 17 SS that occurred during active MJO conditions, 6 SS events happened each in phases 3 and 5, and 5 events happened in phase 4. However, there is no SS in phase 2 of the active MJO. Rainfall anomalies during periods 3, 4 and 5 of the active MJO’s SS are shown in Figure 7 based on observational data. This demonstrates how the influence of SS on rainfall varies depending on the active phases of the MJO. Figure 7a illustrates the larger positive rainfall anomalies in the western part of Java Island (R1 and R3) during SS and MJO phase 3 when the MJO convective center is in the Indian Ocean. Conversely, there are more negative rainfall anomalies in Java Island’s central and eastern regions (R2, R4, R5 and R6), including Bali Island (R7). When the location of the MJO convective center is near the South China Sea, positive rainfall anomalies are generally greater in SS and MJO phase 4 (Figure 7b) as opposed to MJO phase 3, especially in the central (R4 and R5) and eastern (R6) regions of Java Island. Furthermore, positive rainfall anomalies further increase in SS and MJO phase 5 (Figure 7c), especially in R2, R4 and R5, including on the island of Bali (R7), except for the southern mountainous region of East Java (R6) when the MJO convective center is around Maluku. The findings indicate that the distribution of rainfall over Java Island is influenced differently by different MJO phases. This phenomenon may be related to the location of the MJO convective center and the associated wind dynamics between the monsoon, SS, MJO and local circulation. Phases 2 and 3 of the MJO are over the Indian Ocean, while phases 4 and 5 are concentrated on the Maritime Continent, according to [23]. Hidayat and Kizu [23] also noted that more rain fell over Sumatra Island and the Indian Ocean during phase 3 of the MJO. Most of Indonesia, including Java Island, experiences increased rainfall during Phase 4 of the MJO, whereas eastern Indonesia experiences increased rainfall during Phase 5 of the MJO. In contrast to the findings of this study, the SS that transpired during the MJO should have been more pronounced during Phase 4 of the MJO; however, Phase 5 significantly impacted rainfall along Java Island up to R9. This indicates that the pattern of MJO impacts on rainfall is altered when SS is present.

As shown in Figure 8, the SS period usually experiences higher rainfall with positive rainfall anomalies during active MJO periods, except for the regions in Jakarta (R2), East Java (R6) and Bali (R7). When the MJO is active, R5 experiences the largest increase in rainfall, reaching an average of 4.69 mm/day; this region may be where the SS and MJO’s westerly winds converge. Furthermore, the western portion of the study area experiences a significantly greater increase in rainfall than the eastern portion does during an MJO. This is because the SS and westerly winds from the MJO interact strongly in the western portion of the study area. Rainfall in the R6 and R7 regions has decreased, reaching −0.87 mm/day and −0.71 mm/day, respectively, and the interaction between the MJO and SS winds may have weakened. However, positive anomalies are detected in the R8 and R9 regions, reaching 2.12 mm/day and 0.74 mm/day, respectively, which could be the result of SS interacting with regional elements and northerly winds, which typically happen in the NDJFM month. High rainfall in the eastern portion of the study area is also observed to be influenced by the presence of regional factors and winds from the north when the MJO is not active. Additionally, during the MJO’s inactive periods, there is a slight increase in rainfall in the R1, R4 and R5 areas, reaching 0.12 mm/day, 0.49 mm/day and 0.67 mm/day respectively, but not as much as during its active periods. Whether the MJO is active or not, SS has a major effect on reducing rainfall in the R2 region, with the rainfall decreasing to −2.21 mm/day when the MJO is active and −1.58 mm/day when the MJO is inactive. This is made possible and influenced by the geographic location of R2, which is behind the R3 region’s orography, as shown in Figure 1b. When the MJO is active, SS has the effect of greatly increasing rainfall in the R3 region, reaching 2.86 mm/day; conversely, when the MJO is inactive, rainfall decreases, reaching −0.34 mm/day. There are also notable variations in the R7 region, where there is a decrease in rainfall during an active MJO but an increase in rainfall during an inactive MJO. Rainfall in the R6 region decreases when the MJO is active due to the SS impact and increases slightly when the MJO is not active. These results show that the impact of MJO on Java Island when SS is present is higher in the western region than the impact of SS alone, which is higher in the eastern region of the island.

The average daily rainfall anomalies based on observation data in each study area between two days before and three days following the SS event in MJO, active or not, are displayed in Figure 9. Consistent with Figure 8 results, SS in an active MJO is accompanied by a notable increase in rainfall in the R1, R3, R4, R5 and R8 regions starting one day before the SS event (Figure 9a). As shown in Figure 9a, rainfall in R5 during the active MJO is significantly higher than it was before the SS days. This shows that the SS and MJO interaction is very significant in the R5 region, which may be the location of the SS and MJO wind convergence. Additionally, the analysis in Figure 8 is strengthened by this statement. Rainfall in this area increased only during the SS, and it started to decrease one day after the SS. Rainfall in the R9 region is also increased by the combination of SS and MJO, as Figure 8 and Figure 9a demonstrate, although the increase is much less than in the other regions. In the R7 region, where the interaction of SS with the MJO reduces rainfall, the consistency of Figure 8 and Figure 9a is also demonstrated. In fact, the R7 region experienced a decrease in precipitation for a few days after the SS. However, the decrease in rainfall in the R6 region caused by the interaction of SS and MJO is not visible in Figure 9a, where rainfall appears to increase slightly from one day before the SS occurred. The R2 region, which should also experience a decrease in rainfall, is not visible in Figure 9a; however, this is possible because there was a significant increase in rainfall in the R2 region until one day after the SS occurred. The increase in rainfall that reached one day after the SS occurred was possible due to the interaction of the SS with local factors and orography, so that the formation of rain clouds was delayed and continuous after the SS event.

Increased rainfall is also observed in several study areas when SS occurs without MJO (Figure 9b), but the intensity of the increase is smaller than when there is MJO. Consistent with Figure 8, the R8 region experienced the largest increase in rainfall. Figure 9b also illustrates the increase in rainfall in R1, R4, R5 and R7. This adds credence to the analysis of Figure 8, which shows that SS influences the region’s increased rainfall in the absence of the MJO. In contrast to the MJO, where rainfall significantly decreased following the SS, there was no significant drop in rainfall in the area one day after the SS without the MJO. In the R2 region, where rainfall decreases when SS occurs on its own without the presence of MJO, Figure 8 and Figure 9b also show consistency. The decrease in rainfall was even more drastic in the area one day after the SS, although it increased again after that. In the R9 region, it appears that there is no correlation between maximum rainfall anomalies and SS events without the presence of MJO when compared with Figure 8. However, overall, the analysis of Figure 9 strengthens the analysis of Figure 8.

Based on observational data, Figure 10a–e displays the distribution of rainfall anomalies on SS event days at NDJFM each month. In November (Figure 10a) and December (Figure 10b), SS increased the amount of rainfall across most of the study area, with Java Island particularly affected. The Central Java region saw the largest increase in rainfall, with 5 mm falling each day in R4 and R5. However, in January (Figure 10c), February (Figure 10d) and March (Figure 10e), SS reduced the amount of rainfall over most of the study area. This confirms the findings of earlier studies that claimed SS was responsible for Java Island’s January rainfall decline [10]. On Java Island, however, this research indicates that February sees the most noticeable decrease in rainfall. In the R7 and R8 areas, there is significantly more rainfall from January to March than there is in November and December. R7 and R8 saw the biggest increase in rainfall in February. These findings indicate that in the western portion of the study area, particularly on Java Island in November and December, SS is more likely to be responsible for an increase in rainfall. But in January, February and March, the amount of rainfall in the study’s eastern region rose.

3.2.2. Extreme Rainfall Response

During an active MJO, high PCE intensities of up to 20% are more commonly seen along the southern portion of Java and Bali (Figure 11a), particularly in R4 and R5. Compared to periods without MJO, the northern coastal regions around Java Island and R7–R9 frequently exhibit high PCE intensity distributions, with values as high as 20% (Figure 11b). PCE values with a negative sign are predominant in the southern regions of Java and Bali. Trimidianto et al. [18] and Satiadi et al. [36] have found that when the MJO is not active, the presence of CENS, CS or both is linked to high PCE in the northern part of Java Island. Based on the explanation above, it can be inferred that MJO influences the likelihood of extremely high rainfall in the southern part of Java Island up to R9. The R4 and R5 areas are more likely to experience intense rainfall. Other than that, it does not seem like MJO has much of an effect on the intense rainfall in the northern coastal regions of Java Island and R7.

Figure 11c,d illustrate how the SS and MJO interact to influence extreme rainfall. In Figure 11c,d, the PCE distribution pattern is nearly the same whether SS occurs with the MJO active or not. The interaction between SS and MJO is more frequently seen in providing the impact of extreme rainfall in the high PCE intensity R4, R5 and R7 regions. In contrast, the distribution of minus PCE is larger than that of positive PCE. Meanwhile, low PCE is predominant in the Java and R7 regions when the SS occurs on its own without the MJO present; high PCE intensity is still observed in several R4, R5 and R8 regions. This demonstrates that, even in the absence of MJO, SS has no discernible effect on excessive rainfall. The predominance of low PCE values on the Java and Bali islands, both for active and inactive MJO, suggests that SS has little effect on the islands’ increased extreme rainfall. Extreme rainfall is only affected by SS in a small number of areas and may only happen in a small number of SS events.

Figure 12 displays the average rainfall for each weather-observation station in the nine study areas during the active and inactive MJO periods. The interaction of SS and MJO is found to have a greater average impact on extreme rainfall in region R5 for each location in each study area (Figure 12a). Compared to other areas, R5 experienced more extreme rainfall with six SS events, followed by the R4 region, which experienced four extreme events. Nevertheless, on the 16th and 17th SS events, R7 and R8 had extremely high average rainfall exceeding 50 mm/day. This is consistent with the analysis described in Figure 11c. It is also noted that, with small average rainfall values, the influence of SS and MJO on extreme rainfall in R2 is not very significant. Figure 11c also shows that the interaction of the SS with the MJO allows extreme rainfall to occur in the R4, R5 and R7 regions due to the large number of high PCE intensities found in these regions; this is also confirmed by Figure 12a. In the case of SS without MJO, regions R4 and R5 also predominate in terms of extreme rainfall (Figure 12b), although there are also periods of extreme rainfall with few SS events in several other areas. This validates the analysis of Figure 11d, which indicates that there is minimal likelihood of extreme rainfall due to SS during the MJO’s inactivity, except for the R4 and R5 regions.

3.2.3. Cross-Section Analysis for Rainfall Diurnal Variations

Utilizing cross-section analysis, Figure 13a–f illustrates the diurnal analysis of the effects of SS and MJO on rainfall. Only Java Island, the largest island in the study area, was subjected to cross-section analysis. This is because the R7–R9 region can be represented by the SS and MJO interaction schemes on rainfall on Java Island. Two cross-section analyses were performed: the time-longitude cross-section and the latitude-time cross-section. The latitude-time cross-section was carried out by averaging the longitude region around 106–115° E, which represents the entire Java Island. Concurrently, the time-longitude cross-section is computed by averaging the latitude region between 6 and 9° S, which corresponds to Java Island’s northern and southern borders. Figure 13a–c illustrates that rainfall predominantly occurs over land in the afternoon until midnight. However, an additional enhancement over the ocean in the morning reflects a diurnal rainfall pattern influenced by the contrast between land and sea. This shows that the influence of SS on rainfall on land occurs in the afternoon until midnight and in the sea in the morning. In addition, it is worth noting that during the day, SS tends to increase rainfall along the north coast of Java. Meanwhile, at night and early in the morning, SS tends to increase rainfall along the south coast. These findings could be elucidated by examining the interplay between local land–sea breeze circulation and broader-scale SS circulation. In daylight hours, the sea breeze along the northern coast opposes the SS, leading to increased convergence and rainfall. Conversely, the sea breeze along the southern coast aligns with the SS, resulting in minimal convergence effects. Furthermore, during nighttime, the land breeze along Java’s southern coast opposes the SS, fostering convergence and rainfall, while along the northern coast, the land breeze aligns with the SS, reducing convergence. Moreover, rainfall along the northern coast also increased in the early morning, likely due to the heightened convergence between the monsoon and land breezes, which peak during this time. When the SS coincides with an active MJO, as shown in Figure 13b, a similar rainfall pattern emerges but with intensified precipitation both over land and sea. This amplification could be attributed to the alignment of the SS circulation with the MJO’s low-level convergence circulation, thereby reinforcing each other. Conversely, during SS occurrences with an inactive MJO, a comparable rainfall pattern emerges but with diminished intensity, as depicted in Figure 13c.

Using a time-longitude cross-section, the diurnal analysis of SS’s effect on rainfall is displayed in Figure 13d–f. The eastern region of Java, which is dominated by R4 and R5 in the morning, afternoon and evening, generally experiences the highest average rainfall for all SS days (Figure 13d). The eastern R8 and R9 regions also experienced heavy morning and afternoon rainfall. During active SS events in the MJO, high rainfall intensity was observed throughout the day from Java to East Nusa Tenggara (Figure 13e). Conversely, when the MJO is not active during SS, rainfall intensity is low, except for R8 (Figure 13f).

Figure 14 illustrates potential interactions between large-scale synoptic circulations, such as SS, MJO and the monsoon, and local land–sea breeze circulations, resulting in the observed spatio-temporal variability of rainfall over Java Island. Increased convergence over land during the day and over the sea at night may explain the typical diurnal rainfall pattern due to land–sea contrast. Additionally, the increased convergence between the monsoon and the land breeze may account for the increased rainfall along the northern coast in the early morning. Enhanced convergence over the northern coast during the day and the southern coast at night may explain increased coastal rainfall due to the SS. Finally, the MJO tends to amplify the effects of the SS even further. This makes it possible to connect SS to diurnal rainfall activity and validates earlier findings that one of the main phenomena in tropical areas is the diurnal cycle of rainfall and convective activity [40]. Most studies have indicated that diurnal rainfall variations in the Tropics have their peaks in the late evening over land regions and in the early morning over adjacent sea regions (e.g., [41,42,43]). Over the ocean, the diurnal cycle of precipitation is generally weak and peaks in the early morning [44].

3.3. Atmospheric Processes of SSs Governing Rainfall Systems

3.3.1. Integrated Water Vapor Transport (IVT)

Figure 15 depicts the moisture transport during NDJFM for the mean conditions of active MJO, inactive MJO, SS and a combination of active/inactive MJO and SS. Contour represents the magnitude, and streamline represents the direction of moisture transport. Streamlines indicate that SS strengthens the southerly wind and moisture transport over the Indian Ocean toward the Maritime Continent, thus resulting in a high moisture concentration over Java and its surrounding area, reaching more than 300 kg/m/s (Figure 15b). The high sea surface temperature over the Indian Ocean (Figure 5b) supports the evaporation process in this area, thus resulting in the high moisture content in this area. The high amount of moisture over the Indian Ocean is transported toward Java and its surroundings and deflected eastward around 10° S (see streamlines in Figure 15b), resulting in decreasing and increasing rainfall in several areas around Java (Figure 4c).

Moreover, the active MJO amplified the moisture transport over the Maritime Continent, as shown by the greater transport of moisture from the Indian Ocean toward Sumatera Island. The eastward propagation of MJO significantly added moisture to the Maritime Continent during the SS event, with eastward moisture transport reaching more than 400 kg/m/s from the Indian Ocean (Figure 15d). The high moisture over the Maritime Continents supports the development of convective clouds, thus resulting in positive rainfall anomalies over this area during SS occurrence with the active MJO (Figure 8). However, a single MJO phenomenon (without SS) increases the eastward moisture transport but is not as significant as if it were coupled with SS (Figure 15c). Furthermore, the inactive MJO is likely not significant in reducing moisture transport over the domain studied during SS, as shown in Figure 15f, which has quite similar moisture transport distribution to SS alone (Figure 15b).

Previous studies show a consistent result on the moistening over the Maritime Continent due to the SS and MJO separately. However, a study combining these two phenomena needs more exploration. A previous study indicates the Tropical Eastern Indian Ocean experienced moistening indicated by high OLR during two to four days before SS phenomena [7]. This moistening is enhanced by evaporation over the sea surface area, which is associated with the surge [7]. The surge can be identified by the streamline over the midlatitude of the Indian Ocean (around 25–30° S), which supports the high moisture (200–300 kg/m/s) over this area to be transported toward the Maritime Continent (Figure 15b,d,f). The development of baroclinic synoptic disturbances in this mid-latitude area induced the development of the surge [45]. Furthermore, the moistening over the Maritime Continent due to MJO is explained by a previous study [46]. This study emphasized that moistening is a consequence of the eastward propagation of MJO. The outward turbulent heat flux, due to advective heat transport in the upper ocean dominating the sea surface warming under the MJO atmospheric convection center (around the Timor Sea), triggers the moistening and instability in the lower atmosphere [46]. Therefore, by considering the impact of each phenomenon on the moistening process, we can generally conclude that higher moisture can be detected when SS and MJO are in occurrence, as in the results presented in this paper (Figure 15d). However, the underlying mechanism behind this moistening remains unclear. Therefore, the atmospheric conditions during these phenomena are examined in the next section.

3.3.2. Convective Instability

During the SS period, surface temperatures generally decreased across all regions, as depicted in Figure 16a, likely due to the inflow of cold air masses from the south. Notably, in the western regions (R1 to R3), surface temperatures experience a more pronounced decline during active MJO phases compared to inactive ones, possibly attributable to heightened convective activity and cloud development. Conversely, the eastern region (R4 to R9) exhibits the opposite trend, suggesting a stronger MJO influence in the western areas. Moreover, Figure 16b indicates a reduction in dew point temperatures across all regions during the SS, concurrent with the decline in surface temperatures. However, during active MJO phases, the decrease in dew point temperature is less pronounced than during inactive phases, likely due to increased moisture content.

The meridional wind anomaly generally decreases during the SS, except for the Jakarta area (R2), as shown in Figure 16c. During active MJO phases, the reduction in meridional wind is more pronounced than during inactive phases, potentially indicating an increase in convergence. Figure 16d illustrates that the SS typically reduces CAPE, especially in the eastern regions. When MJO is active, the reduction is less (more) in the eastern (western) regions. Additionally, Figure 16e indicates a reduction in CINH across all regions during the SS, except in R1 and R8. The anomaly of VIMFC depicted in Figure 16f shows an increase across all regions during the SS, except over Jakarta (R2) during inactive MJO phases. During active MJO phases, the increase in VIMFC is more pronounced in western regions (R1 to R3) than in eastern regions (R4 to R9).

Consequently, the SS tends to reduce surface and dew point temperatures as well as meridional wind speeds across all regions. It also tends to decrease CINH and increase VIMFC, though the effect on CAPE shows regional variability. Overall, the SS enhances rainfall, likely through increased VIMFC and reduced CINH. Furthermore, the MJO generally amplifies the SS’s impact on rainfall, with active MJO exerting a more significant effect than inactive MJO, particularly in the western regions. However, it is important to note that the analysis above utilizes regional averages of all variables, and actual variable values may exhibit substantial spatial variations, such as between coastal and mountainous regions.

To provide a quantitative analysis,

Table 1. Correlation coefficients (R values) between convective parameters and rainfall across regions. Ts, Td and V represent surface temperature, dewpoint temperature and meridional wind anomaly, respectively.

Condition	Ts	Td	V	CAPE	CINH	VIMFC
Inactive MJO + SS	−0.25	−0.72	−0.43	−0.78	−0.29	0.82
Active MJO + SS	−0.31	−0.39	−0.23	0.45	−0.18	0.37

shows the correlation coefficients (R values) between convective parameters and rainfall across regions R1 to R9. Interestingly, during the SS and inactive MJO periods, VIMFC has the highest positive correlation with rainfall (0.82), suggesting it is the main factor regulating rainfall variability due to SS. Additionally, CAPE and Td exhibit the strongest negative correlations with rainfall (−0.78 and −0.72), indicating that decreases in Td and CAPE due to SS correspond with increased rainfall. Ts, V and CINH also tend to decrease as rainfall increases, though their correlations are weaker. However, during the SS and active MJO periods, these correlations, or anti-correlations, significantly weaken, except for Ts and CAPE. Notably, during active MJO, CAPE shows a positive, albeit weak, correlation with rainfall, opposite to its behavior during inactive MJO. These results suggest complex interactions between SS and the MJO and their different impacts across the regions.

4. Conclusions

Throughout the study, 61 SS events were found, with 17 of those taking place during the active MJO and 44 during the inactive MJO. Six SS events, each in phases 3 and 5, and five events in phase 4, but there were no SS events in phase 2 of the active MJO. According to observational data, the impact of SS and MJO interactions on rainfall in the study area varies depending on the active MJO phase. Rainfall increased significantly in several areas along R1 to R9 during the SS that occurred during active MJO phase 5, as compared to phases 3 and 4. Whether or not MJO is present, all SS events have a greater impact on rainfall on Java Island in November and December than in other months. The Central Java region, particularly in R4 and R5, saw the largest increase in rainfall during these two months. On the other hand, the R7 and R8 regions experience significantly more rainfall from January to March due to SS. February saw the biggest increase in rainfall in R7 and R8. These findings indicate a shift in the distribution of rainfall in the area studied, along with the arrival of SS and AWM. A decrease in SST anomalies, a strengthening and modification of wind patterns and an overall increase in rainfall in the southern part of the IMC as the SS moves northward are all signs of the impact of the SS event. Notable features include the strengthening of the low-level jet stream over the southern Indian Ocean to the west of Australia and the wind field’s eastward deflection as it gets closer to Java Island. This demonstrates how the SS’s presence causes the wind speed to increase along its path. Wind speed increases as one rises toward Java Island, Sumatra Island and the western Indian Ocean up to R9. During NDJFM, the wind only blows toward the Indian Ocean; when there is SS, it deflects from Java to R9 and is observable.

The results of this study showed that whether an SS event occurs during an active MJO or not, there is a different response to rainfall in the study area through spatial analysis of observational data. Rainfall has decreased throughout Java Island’s mountains, particularly in the northern portion of East Java, and increased in some areas of the island, particularly Central Java. The intricate interplay between the topography of the Java Islands and the SS wind field may be the source of rainfall variability. Furthermore, this research result observes that when the SS coincides with an active MJO, there is a predominant increase in rainfall in the areas surrounding western Java (R1 and R3) and central Java (R4 and R5), according to the average observed rainfall for each station in each study area. The increase in rainfall is predominantly in the R3, R4 and R5 regions compared to other regions. Here in these three regions, there might be a convergence of westerly winds from the SS and MJO. However, when SS coincides with MJO, rainfall in the R8 and R9 regions also shows a noticeable increase. This is likely because SS interacts with local factors and northern winds, which typically happen in the month of NDJFM. However, the R2, R6 and R7 regions see a decrease in rainfall on the day of the SS but an increase in rainfall the day after the SS due to the interaction of the SS and the MJO. The effects of these three regions’ topography may be the reason for the delay in rising rainfall in these areas. While rainfall is primarily increased in regions R1, R3, R4 and R5 when SS happens on its own without MJO, the increase in intensity is less than when SS occurs concurrently with MJO. In contrast, when SS occurs alone as opposed to when MJO is active, the eastern portion of the study area, specifically R7, R8 and R9, primarily experiences a higher increase in rainfall. This indicates that the western research area’s increasing rainfall is primarily caused by the interaction between SS and MJO. However, the eastern portion of the study area experiences a higher increase in rainfall due to SS, which happens when MJO is absent. Apart from that, SS has a significant impact on lowering rainfall in the R2 region, regardless of whether MJO is active. The geographic position of R2, which is behind the orography of the R3 region, makes this both feasible and influential. In addition, research findings show that there is a tendency for the interaction of SS and MJO to influence the possibility of extreme rainfall in the R4, R5 and R7 regions. SS which occurs simultaneously with MJO, allows slightly higher extreme rainfall to occur than if SS occurred without MJO. The results show that MJO and SS have opposite effects on extreme rainfall. MJO tends to increase the probability of extreme rainfall, while SS reduces it significantly.

The results of this research also show that there is a potential interaction between large-scale synoptic circulations, such as SS, MJO and monsoons, and local land–sea wind circulation, resulting in spatio-temporal variability in rainfall on the island of Java. The increased convergence of land during the day and the ocean at night may account for the typical diurnal rainfall pattern caused by the land–sea contrast. Furthermore, there is a chance that the monsoon and onshore winds will converge more, which could result in more rain falling along the northern coast early in the morning. A possible explanation for the increase in coastal rainfall caused by SS is increased convergence over the north coast during the day and the south coast at night. Finally, the MJO tends to amplify the SS effect even further. According to the integrated water vapor transport analysis, SS considerably raised the water vapor content in the IMC’s southern region and marginally shifted it north of Java Island. This increase is more pronounced when SS and MJO happen at the same time. However, the region’s water vapor content was only marginally elevated by the MJO specifically. The study’s findings indicate that, while SS plays a more prominent role, both MJO and SS have an impact that encourages increased water vapor transport in the southern IMC region. The southern IMC may see an increase in water content because the SS actively pushes water vapor from the Indian Ocean toward the area. Convective instability analysis indicates that, overall, SS increases rainfall, most likely by raising VIMFC, with a correlation coefficient value of 0.82. Furthermore, the influence of SS on rainfall is generally amplified by MJO, with active MJO having a greater effect than inactive MJO, particularly in the western region. It is crucial to remember that the analysis makes use of regional averages for every variable and that actual variable values may exhibit significant regional differences, such as those between coastal and mountainous regions. In conclusion, this study has brought attention to the previously unnoticed impact of SS on patterns of rainfall in the southern IMC region, specifically on the islands of Java, Bali and East Nusa Tenggara. Furthermore, the intricate relationships between the SS, the well-researched MJO and the distinct topography of the islands are revealed by this study, offering important new information about how these factors together affect rainfall variability and extreme events. As a result, this study significantly advances our knowledge of the dynamics of the regional climate and emphasizes the significance of considering the complex interactions that shape weather patterns between atmospheric phenomena and geographic features.