With the objective of understanding how terrestrial precipitation in Southeast Asia (SEA) responds to both temporal and spatial variations in sea-surface temperature (SST) of the western Pacific Ocean, we first used the North–South and zonal SST variation analyses for the data set named A Group for High-Resolution Sea-Surface Temperature (GHRSST) Level 4 Multiscale Ultrahigh Resolution (MUR). Second, we applied a localized correlation analysis to the SST data set and rainfall data (Integrated Multi-satellitE Retrievals for Global precipitation measurement (IMERG)) in order to determine the boundaries and characteristics of the complex interactions between SST and rainfall variations. The zonal SST variation analysis result suggested that the warm pool in the North of western Pacific zones close to SEA (120 °E–150 °E) was more sustained and less varied than that in the South zones. In terms of the western Pacific SST impact on rainfall in SEA, the correlation analysis confirmed the well-established concept that the SST of the ocean part close to the SEA land, in general, has more influence on SEA rainfall than does the SST of the ocean part far away from SEA. Still, there were some parts of SEA whose rainfall was not governed by the sea–land juxtaposition.

  • Change in SST in the western Pacific areas, in particular those situated close to the SEA region, might not bring about the uniform changes in precipitation throughout the entire region.

  • Rainfall in some areas of the SEA region, albeit longitudinally close to the western Pacific, did not have the strongest correlation with SST, suggesting the limited influence of sea–land proximity.

Graphical Abstract

Graphical Abstract
Graphical Abstract

Embodying the warmest pool of the ocean, the western Pacific Ocean is regarded as crucial chiefly due to its powerful role in influencing Earth's climate, including that in Southeast Asia (SEA). One of the mechanisms that makes the warm pool1 of the western Pacific so powerful is its intense evaporation, also known as convection, which serves as the incessant, dominant supply of moisture into the atmosphere (De Garidel-Thoron et al. 2005; De Deckker 2016; Jones & Ricketts 2019). Because of this strong evaporation process, the warm pool of the western Pacific Ocean can lead to intense precipitation (sometimes in excess of 2,000–3,000 mm/year), particularly in nearby lands (Delcroix et al. 1996; Chen 2004). By the same token, changes of sea-surface temperature (SST) in the western Pacific warm pool can also result in changes in large-scale precipitation patterns (Palmer & Mansfield 1984; Cronin & McPhaden 1997). This is evidenced by the occurrences of the El Niño-Southern Oscillation (ENSO) (Philander 1985; Ropelewski & Halpert 1987; Halpert & Ropelewski 1992; Linsley et al. 2010). Specifically, during the incidents of the El Niño, the warm pool expands further eastward following the relaxation of the trade winds in the eastern and central Pacific, whereas during the times of the La Niña events, the warm pool is limited to the western margin of the equatorial Pacific following the reinforcement of the trade winds (Yan et al. 1992; Neelin & Latif 1998). These changes in SST, manifested in terms of the relocations of the western Pacific warm pool, bring about changes in rainfall patterns in areas of lands close to the western Pacific Ocean. In case of SEA, the El Niño tends to bring to drought to the region, while the La Niña is likely to bring heavy rain to SEA (Aldrian & Dwi Susanto 2013; Juneng & Tangang 2005; Lau & Wang 2006). Therefore, although there are other factors that can affect precipitation in SEA, for instance, terrain heights and characteristics (Wang & Chang 2012; Mandapaka et al. 2017), the SEA monsoon (IPCC 2013; Misra & DiNapoli 2014; Loo et al. 2015), the SST of the western Pacific Ocean remains crucial. This is also pointed out in some studies. Dayem et al. (2007) indicated that SEA areas of high precipitation rates correlate with high SST. Another study (Niedermeyer et al. 2007) described that the Maritime Continent (approximately 10 °S–20 °N and 90 °E–130 °E) – largely within the SEA boundary — is situated within the Indo-Pacific Warm Pool. Its hydrological characteristics, in particular considered from the seasonal perspective, are therefore influenced by the relocation of the Intertropical Convergence Zone (ITCZ) as well as changes in the monsoonal wind flow. Soman & Slingo (1997) pointed out that warm SST anomalies in the west Pacific Ocean enhanced the tropical convection over Indonesia, and this in situ response to the convection leads to an early occurrence of and more intense monsoon.

However, among all known potential factors that could affect SEA precipitation, it is still unclear that rainfall in which particular areas within SEA are significantly impacted by the warmer SST of the western Pacific Ocean. The answer to this question is very important as it is unlikely that rainfall in every spot of SEA is equally affected by warmer SST of the western Pacific. Likewise, since it is also unlikely that SST of the entire area of the western Pacific Ocean equally affects SEA rainfall, due largely to the influence of the trade winds, it would be very important to determine the approximate scope of the western Pacific area whose SST would play a significant role in SEA precipitation. Even though some studies (Meehl et al. 2007; Diffenbaugh & Scherer 2011; IPCC 2011; Anderson 2012; Mora et al. 2013) suggested that tropical systems will face unusual warming and significant alteration in the timing and amount of rainfall within a few decades, those studies were too generalized to gain an insight into the impact of SST in the western Pacific on SEA rainfall. Moreover, while Singh & Xiaosheng (2019a, 2019b) suggested that over the period between 1951 and 2014, there was a significant increase in rainfall amount in most of SEA regions, it is unclear how or whether SST, particularly in which areas of the western Pacific Ocean, plays a role.

Knowing rainfall in which area of the region is likely to be affected by the warmer SST of which zone within the western Pacific Ocean would be crucial for the impact assessment of how future warming of western Pacific SST could affect SEA rainfall and would also serve as crucial information for the managements of water resources in the region. With this premise, we applied the highly localized correlation analysis to the data sets to identify the boundary of both the land (SEA region) and the ocean (the western Pacific) in which its rainfall and SST closely interact. The objectives of the study are to (i) determine the boundary of the western Pacific area whose SST variations can significantly affect precipitation in the SEA region and (ii) to identify areas within the SEA region, whose precipitation could be sensitive to the warmer SST of the impactful zones of the western Pacific.

There were two sets of data used in the analysis: the Group for High Resolution Sea-Surface Temperature (GHRSST) Level 4 Multiscale Ultrahigh Resolution (MUR) (JPL 2015) for SST2 and GPM Integrated Multi-satellitE Retrievals for Global precipitation measurement (IMERG) Final Precipitation L3 (Huffman et al. 2019) for monthly rainfall3. Both of the datasets were gathered by the US National Aeronautics and Space Administration (NASA). The GHRSST Level 4 MUR has a spatial resolution of approximately 1 km × 1 km. The entire set of the SST data used in the analysis extended from June 1, 2002 to November 30, 2020, accounting for the total of 6,758 files to be processed (all the files in the SST dataset were originally available in a daily basis). In order to make the data temporally consistent with rainfall data, the monthly-average SST was used, covering 222 months. Furthermore, for each month, the original data, which had a global coverage, were clipped to cover only the western Pacific Ocean, which is defined by the longitude of 120 °E–150 °W and the latitude of 20 °S–20 °N.

To determine how SST of the western Pacific Ocean would vary along the latitude line, the western Pacific was divided into two parts: the ocean area within the latitude of 0 (the equator) to 20 °N, referred herein as North and 0 °S–20 °S, as South (Figure 1). Such North–South division would allow us to perceive to what extent SST in those two ocean areas would affect rainfall in SEA and to determine whether their SST influences on SEA precipitation would be similar or distinct as well as whether SST in these two areas would be working in tandem or restraining each other when it came to their impacts on SEA rainfall.
Figure 1

Study areas: SEA (green) and western Pacific Ocean (white). Please refer to the online version of this paper to see this figure in colour: http://dx.doi.org/10.2166/hydro.2022.015 .

Figure 1

Study areas: SEA (green) and western Pacific Ocean (white). Please refer to the online version of this paper to see this figure in colour: http://dx.doi.org/10.2166/hydro.2022.015 .

Close modal

Aside from dividing the western part of the Pacific Ocean into the North and the South, it was also crucial that each part of the longitude of 120 °E–150 °W be thoroughly analyzed. This zonal analysis along the longitude line could enable us to see the spatial variations of SST within the western Pacific Ocean and also their respective roles in SEA rainfall. Therefore, in this study, the longitude of 120 °E–150 °W, which determines the boundary of the western Pacific, was further divided into nine zones along the longitude line. As a result, 18 zones were obtained (Figure 1).

To determine the warming rate within each ocean zone, the study applied the approach used by Alexandrov et al. (2012) for trend extractions. The approach is based on the notion that there are three key components that contribute to SST at a particular time step, namely seasonality4, trend5, and irregularities6 (or noises). These three components are related under a time-series model called the addictive model. This model was adopted since it is assumed that the seasonal and irregularity components change the trend by an amount that is independent of the value of trend. The equation of the addictive model is shown as follows:
formula
(1)
where SSTi is the observed SST at the ith time step, Ti is the trend component at the ith time step, Si is the seasonal component at the ith time step, and Ni is the the noise component at the ith time step.
From Equation (1), the trend is derived from the following equation:
formula
(2)

Based on Equation (2), in order to determine the trend, seasonal and noise components were removed from the observed SST time-series. This study used the classical decomposition presented by Brockwell & Davis (2002) to solve Equation (2). After the trend had been obtained, the linear regression was applied to derive the linear equation that best fitted the trend line. Then, the warming rate was finally estimated from the slope value of the linear equation. This trend extraction process was applied for all ocean zones. Additionally, this analysis was performed for three statistical parameters, namely mean, minimum, and maximum SST. All of these, therefore, allowed us to compare yearly warming rates in different zones of the western Pacific Ocean.

With regard to precipitation data, precipitation in SEA from January 2002 until November 2020 was used, accounting for the total of 222 files (months) to be processed. First, the data were derived from GPM IMERG Final Precipitation L3 — 1 month 0.1° × 0.1° V06 (GPM_3IMERGM). These data had a resolution of roughly 10 km × 10 km and a temporal resolution of 1 month. The original data were in HDF5 format, which was later transformed to the Geo-tiff format by using GDAL python7. After that, since the data had a global coverage, the tiff (raster) file was clipped in the ESRI ArcGIS Pro to ensure the extension of the SEA area. Then, this data set was divided into 36,903 segments (based on the spatial resolution of the GPM IMERG) before it was used to assess how sensitive rainfall in each segment was to SST variations in each zone using correlation analysis. All information about the imagery inputs and the research methodology is summarized in Table 1 and Figure 2.
Table 1

Information on imagery used for the study

Data retrievedProduct usedSpatial resolutionTemporal resolutionTemporal coverageSpatial coverage
Sea surface temperature (°C) GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analysis (V4.1) 0.01° × 0.01° (roughly 1 km × 1 km) 1 month From June 2002 to November 2020 Western Pacific Ocean 
Monthly precipitation (m3GPM IMERG Final Precipitation L3 0.1° × 0.1° (approximately 10 km × 10 km) 1 month From June 2002 to November 2020 Southeast Asia 
Data retrievedProduct usedSpatial resolutionTemporal resolutionTemporal coverageSpatial coverage
Sea surface temperature (°C) GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analysis (V4.1) 0.01° × 0.01° (roughly 1 km × 1 km) 1 month From June 2002 to November 2020 Western Pacific Ocean 
Monthly precipitation (m3GPM IMERG Final Precipitation L3 0.1° × 0.1° (approximately 10 km × 10 km) 1 month From June 2002 to November 2020 Southeast Asia 
Figure 2

Research methodology.

Figure 2

Research methodology.

Close modal

The North–South SST variation analysis

To determine the relationship between SST of the western Pacific Ocean and SEA rainfall, it is vital to understand both temporal and spatial variations in SST across the western Pacific. The North–South division of the western Pacific Ocean leads to the finding that mean SST in the North can range from around 27 to 29.5 °C, while in the South, it can vary from approximately 27.2 to nearly 30 °C. Furthermore, the standard deviation of North SST can range from 0.5 to almost 1.5 °C, whereas that in the South SST exists between about 0.5 and nearly 2 °C. This probably suggests that even within the North or South, SST is hardly uniform. Also, it is found that notwithstanding the intrinsic heterogeneity within both the ocean areas, one regular pattern was found: mean SST in the North and South varied in an opposite direction and maintained this pattern of variations throughout the study period (Figure 3). Whenever the North SST was increasing, the South SST was decreasing, and vice versa, a phenomenon also referred herein as the NorthSouth oscillation. In addition, it was found that SST in the South peaked around March every year, whereas the North SST reached a peak in around August. This is crucial as it could suggest that the warm pool in the North and South formed at different periods. Also, this pattern of variation demonstrates that although located within the boundary of the western Pacific Ocean, the self-conflicting changes of the NorthSouth SST can exist. Additionally, this opposite SST variations between the North and the South are reflected in the standard deviation (Figure 3), except that the South of the western Pacific Ocean had higher peak deviations than those in the North.
Figure 3

Monthly SST in the North and South of the western Pacific Ocean.

Figure 3

Monthly SST in the North and South of the western Pacific Ocean.

Close modal

This NorthSouth variation pattern might serve as one of the factors that contribute to the SEA precipitation variability, in particular that between the northern SEA and its southern counterpart. Moreover, this NorthSouth oscillation is significant because it indicates that the impact of SST of the western Pacific Ocean on the SEA rainfall cannot focus merely on the ‘horizontal’ proximity — or the longitudinal distance from the SEA land — as in cases of the El Niño and La Niña events. It is well-established that the movements or spreading of the western Pacific warm pools along the longitudinal positions can have an important impact on the SEA rainfall. However, the results from Figure 3 also suggest that the western Pacific warm pool can re-locate along the latitudinal line, and this latitudinal movement is also marked by seasonal variations. Hence, in order to gain more complete picture into how SST of the western Pacific Ocean affects SEA precipitation, the existence of the NorthSouth SST variation must be acknowledged and taken into consideration.

Zonal SST variation analysis

In addition to dividing the western Pacific Ocean into the North and South, we also looked deeper into SST variations in each part along the longitude line by further dividing the western Pacific into 18 zones: nine in the North and the other nine in the South. This enables us to obtain a deeper understanding of how different SST is in the zones both close to the SEA landmass and distant away. The result shows that the changes of SST in the North zones were wave-like, ranging from 25 to 31 °C. The peak and lowest SST in each North zone tended to occur at a regular interval. Additionally, in the North, though not perfectly uniform, the overall trend is clear: the SST dropped as moving further away from the continent (Figure 4), indicating the potential formation of warm pool in the North zones close to SEA. Even so, in many occasions, it is hard to distinguish the SST of the North zones 1–3, demonstrating that the SST in the North zones close to the SEA region is likely to be subject to more or less the same level of variability. Furthermore, the SST in the North zones 1–3 rarely went below 28 °C. This suggests that the warm pool in the ZONE 1–3N was not affected by seasonal variability. However, this does not mean that the warm pool is limited only to the ZONE 1–3N because in some occasions, the warm pool could stretch into the North zones distant from the SEA area (ZONEs 8 and 9). From the perspective of warm pool sustainability, the ZONE 1–3N was able to keep their SST above 28 °C almost throughout the study period. In other words, the warm-pool characteristic is well-preserved in the ocean zones of the North western Pacific close to SEA.
Figure 4

The distribution of monthly mean SST in nine zones in the North (upper) and those in the South (lower).

Figure 4

The distribution of monthly mean SST in nine zones in the North (upper) and those in the South (lower).

Close modal

On the other hand, despite the seasonal variability ranging between approximately 30.6 and 25.5 °C, the SST in each zone of the South is different from that in its North counterpart. The most noticeable is that the warm-pool conditions in the South zones adjacent to SEA were not sustained. From Figure 4, after the SST peaks in the ZONE 1–3S, they were followed by the significant decrease in SST to the point that could no longer be considered as warm pool. This after-peak decrease could bring SST in the ZONE 1–3S down to as low as around 25.8 °C. This makes the warm pool in the ZONE 1–3S less sustained, compared to that in the North. Also, unlike that in the North, the minimum SST in the South occurred in the ocean zones close to the land (ZONE 2S or 3S). Therefore, in the South, it is not true that the more distant the ocean zones from the SEA continent, the lower SST.

Trends and warming rates of SST

Additionally, in order to determine how much the mean SST of the entire western Pacific has changed, time-series analysis or TSA was applied. The result from the analysis demonstrates that from around 2003 to 2007, the mean SST of the entire western Pacific was stable around 28.50 °C. After that, it kept fluctuating during the mid-2007 until 2013 before it has been slowly increasing since 2013 (Figure 5(a)). Still, the minimum SST did not reveal any particular trend since it was marked largely by fluctuations (Figure 5(b)), while the trend for the maximum SST showed a sign of increasing, from around 31.25 °C in 2013 to about 31.5 °C in 2020 (Figure 5(c)). We also found that the trend of WPWP sizes8 (Figure 5(d)) was similar to that of the mean SST. Figure 5(d) also suggests that the size of WPWP has also been increasing slowly since 2013, increasing from around 23 million km2 in 2013 to about 25 million km2 in 2020.
Figure 5

The trends of SST-related parameters, namely mean (a), minimum (b), maximum SST (c), and WPWP sizes (d) of the entire western Pacific.

Figure 5

The trends of SST-related parameters, namely mean (a), minimum (b), maximum SST (c), and WPWP sizes (d) of the entire western Pacific.

Close modal
As discussed hitherto, the SST of the western Pacific is not uniform. In addition, we found that the annual warming rate in the western Pacific Ocean is also far from uniform (Figure 6(a)–6(c)) — which might also mirror the possibility that the dominant mechanisms governing the SSTs are more than merely the trade winds and air temperatures. If the trade winds were the single dominant forces, the negative warming rate (cooling down) of the mean SST in the ZONE 1 South should not be existent (Figure 6(a)). We also found that the ocean zones closest to the continents do not have the highest warming rates; instead, those with the greatest annual warming rates are located further away from the continents, namely the ZONE 7 North and ZONE 6 South.
Figure 6

Annual warming rates for mean (a), minimum (b), and maximum SST (c) of each zone in the North and the South.

Figure 6

Annual warming rates for mean (a), minimum (b), and maximum SST (c) of each zone in the North and the South.

Close modal

Additionally, we discovered that the minimum SST in the ZONEs 1, 2, and 3 South shows negative rates, which suggests that these sea areas have been getting even lower minimum SST since 2013, while the same ZONEs in the North have a distinct pattern, for their minimum SST increased (Figure 6(b)). Still, as the sea areas move further away from the SEA continent, the warming trends in the minimum SST in the South were higher than that in the North as seen in ZONEs 6–9 (Figure 6(b)). Moreover, we found that all the ocean zones showed the positive rates for their maximum SST, which have been higher since 2013 (Figure 6(c)). All these results show different warming rates in different parts of the western Pacific, some of which was not even warmer; instead, it was colder. This implies that the assessment of its SST impact on SEA rainfall should be highly discrete or zone-specific.

SST–rainfall relations

It is likely that the location of the ocean segment (zone) can play an important role in the SEA precipitation and that not all parts of the western Pacific share the same level of such influence. To determine to what extent precipitation in each part of the SEA region is sensitive to SST variations in each zone inside the western Pacific Ocean, the highly localized correlation maps were created (Figures 7 and 8). We found that all nine ocean zones in the North have a direct correlation with rainfall in the northern part of the SEA area (above 5 °N of the Earth's equatorial line); still, they have reverse correlations with precipitation in the southern SEA (below 5 °N of the Earth's equatorial line) (Figure 7). Moreover, the degree of correlations diminishes in the ocean zones further away from the SEA landmass. This likely indicates that increases in SST in the North could lead to more rainfall in the northern part of SEA and less precipitation in the southern part of SEA. On the contrary, SST in the nine zones in the South has a direct correlation with precipitation in the southern SEA, particularly below the Earth's equatorial line; however, they show a reverse correlation with precipitation in the northern SEA, especially above 10 °N of the Earth's equatorial line (Figure 8). These phenomena might happen owing to the North–South oscillation mentioned during the NorthSouth SST variation analysis: when the North warms, the South cools down, and vice versa. This oscillation might be the key reason why the reverse correlations are found.
Figure 7

The correlation between terrestrial rainfall in SEA and SST in each of the nine zones in the North.

Figure 7

The correlation between terrestrial rainfall in SEA and SST in each of the nine zones in the North.

Close modal
Figure 8

The correlation between terrestrial rainfall in SEA and SST in each of the nine zones in the South.

Figure 8

The correlation between terrestrial rainfall in SEA and SST in each of the nine zones in the South.

Close modal

Although the sea–land proximity can influence the precipitation in some parts of SEA as described above, there is rainfall in other part of SEA that is not correlated with SST of the ocean zones close to them. In Figure 7, the SEA area that is located between approximately 120 °E–127 °E and 5 °N–18 °N, despite its closeness to the ocean, did not show a strong correlation with SST. Not only that, rainfall in the small islands (123 °E–127 °E and 5 °N–18 °N) had very weak negative correlation with SST even though these islands are located next to the ocean. Moreover, the SEA landmass between 0 °N and 5 °N, albeit situated close to the ocean, had very weak correlation with SST. Furthermore, the influence of the SST in ocean ZONE 2 North was less strong than that in ZONE 3 North although ZONE 2 is closer to the SEA region. Likewise, in Figure 8, the SEA land of roughly between 125 °E–140 °E and 0 °S–5 °S, in spite of its close proximity to the sea, did not have strong correlation with SST. Also, the SEA area of about 0 °N–5 °N also had weak correlation with SST in all the ocean zones in the South.

Even in the SEA area whose precipitation tends to fall under the influence of the sea–land proximity, its extent of rainfall could be also be affected by the sustainability of the warm pool formed. Based on the result in Figure 4, the warm pool formed in the North is more sustained than that in the South. This also could affect the rainfall amount in the northern and southern SEA as rainfall in northern SEA would be subject to less variability than that in southern SEA because of the more sustained warm-pool condition. Additionally, the result from Figure 6 revealed that mean SST in the ZONE 1 South and minimum SST in the ZONE 1–3 South were subject to cooling, suggesting that if these cooling rates continue, some southern parts of SEA would likely have less precipitation.

The relationship between SEA precipitation and SST of the western Pacific is complex. The NorthSouth and zonal SST variation analyses indicated that SST in the North and South peaked in different times. This suggests that the warm pool of the western Pacific Ocean, which usually occurs near the SEA landmass, did not form simultaneously across the North and South. There was seasonal variability involved in the peak-SST times and thus the period and location in which the warm pool forms. Furthermore, the zonal SST variation analysis suggested that the warm pool in the North of western Pacific zones close to SEA (120 °E–150 °E) was more sustained and less varied than that in the South zones. In terms of the western Pacific SST impact on rainfall in SEA, the correlation analysis confirmed the well-established concept that the SST of the ocean part close to the SEA land, in general, has more influence on SEA rainfall than does the SST of the ocean zones far away from SEA. This is particularly true when considered from the latitudinal proximity standpoint. The SST in the North and South of the western Pacific tends to affect the precipitation in the northern and southern parts of SEA, respectively, although such influence on the northern and southern SEA rainfall happens at different times. However, the significance of sea–land longitudinal proximity is less definitive in determining how much rain SEA would have. The analysis showed that rainfall in some areas of the SEA region, albeit longitudinally close to the western Pacific, did not have the strongest correlation with SST. Moreover, rainfall in some SEA areas, in particular those are located between 0 °N and 5 °N, had a weak correlation with the SST of the ocean part close to it. Therefore, the idea that closer longitudinal proximity means stronger correlation is not true in some areas of SEA. The result from the correlation analysis, designed to be highly localized in terrestrial rainfall pixels, leads to the possibility that change in SST in the western Pacific areas, in particular those situated close to the SEA region, might not bring about the uniform changes in precipitation throughout the entire region. And even in SEA areas whose rainfall is governed by the influences of the sea–land juxtaposition, rainfall can also be influenced by how sustained the warm pool is. From the zonal SST variation analysis and correlation results, it is believed that precipitation in the northern SEA might be subjected to less variability because of the more sustained warm pool in the North of the western Pacific Ocean than in the South.

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.

1

The warm pool is commonly defined as the region where the SST exceeds 28 °C (Picaut et al. 1996), trade winds are weak, and atmospheric convection is intense (Bjerknes 1969; Graham and Barnett 1987). Furthermore, the warm pool of the western Pacific can reach the depths of 100 m and cover a large surface area of roughly 1,590 km2 (Wyrtki 1989).

2

All the datasets of GHRSST Level 4 MUR Global Foundation Sea Surface Temperature can be assessed at https://doi.org/10.5067/GHGMR-4FJ04.

3

The entire dataset of GPM IMERG Final Precipitation L3 for monthly rainfall is available at https://disc.gsfc.nasa.gov/datasets/GPM_3IMERGM_06/summary.

4

Seasonality is defined as regular variations that occur from year to year with about the same timing and level of intensity.

5

Trend means tendencies of data to increase or decrease fairly steadily over time.

6

Irregularities or noises are any fluctuations that are not marked by seasonal traits or trends. This component of the time-series is unpredictable.

7

Geospatial Data Abstraction Library or GDAL is a computational software library for reading and writing raster and vector geospatial data formats.

8

WPWP stands for Western Pacific Warm Pool, which is the sea area, where SST is greater than 28 °C.

Alexandrov
T.
,
Bianconcini
S.
,
Dagum
E. B.
,
Maass
P.
&
McElroy
T. S.
2012
A review of some modern approaches to the problem of trend extraction
.
Econometric Reviews
31
,
593
624
.
Bjerknes
J.
1969
Atmospheric teleconnections from the equatorial pacific
.
Monthly Weather Review
97
,
163
172
.
Brockwell
P. J.
&
Davis
R. A.
2002
Introduction to Time Series and Forecasting
.
Springer
,
New York
.
Cronin
M. F.
&
McPhaden
M. J.
1997
The upper ocean heat balance in the western equatorial pacific warm pool during September-December 1992
.
Journal of Geophysical Research: Oceans
102
,
8533
8553
.
De Garidel-Thoron
T.
,
Rosenthal
Y.
,
Bassinot
F.
&
Beaufort
L.
2005
Stable Sea surface temperatures in the western Pacific warm pool over the past 1.75 million years
.
Nature
433
,
294
298
.
Delcroix
T.
,
Henin
C.
,
Porte
V.
&
Arkin
P.
1996
Precipitation and sea-surface salinity in the tropical Pacific Ocean
.
Deep Sea Research Part I: Oceanographic Research Papers
43
(
7
),
1123
1141
.
Halpert
M. S.
&
Ropelewski
C. F.
1992
Surface temperature patterns associated with the southern oscillation
.
Journal of Climate
5
,
577
593
.
Huffman
G. J.
,
Stocker
E. F.
,
Bolvin
D. T.
,
Nelkin
E. J.
&
Tan
J.
2019
GPM IMERG Final Precipitation L3 1 month 0.1-degree x 0.1-degree V06
.
Goddard Earth Sciences Data and Information Services Centre (GES DISC)
,
Greenbelt, MD
.
IPCC
2011
Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (SREX). Summary for Policymakers
.
Intergovernmental Panel on Climate Change Secretariat
,
Geneva
,
Switzerland
.
IPCC Climate Change
2013
The physical science basis
. In:
Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change
(
Stocker
T. F.
,
Qin
D.
,
Plattner
G.-K.
,
Tignor
M.
,
Allen
S. K.
,
Boschung
J.
,
Nauels
A.
,
Xia
Y.
,
Bex
V.
&
Midgley
P. M.
, eds).
Cambridge University Press
,
Cambridge
,
United Kingdom
, p.
1535
.
Jet Propulsion Laboratory (JPL) MUR MEaSUREs Project
2015
GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analysis (v4.1). Ver. 4.1. PO. DAAC, CA, USA. Dataset (accessed 01 December 2020)
.
Jones
R. N.
&
Ricketts
J. H.
2019
The Pacific Ocean heat engine: global climate's regulator, Earth System Dynamics. Discuss. [preprint], in review
.
Lau
N. C.
&
Wang
B.
2006
Interactions between the Asian monsoon and the El Nino/Southern oscillation
. In:
B. Wang, ed.
The Asian Monsoon. Springer
,
Berlin, Heidelberg
, pp.
479
512
.
Linsley
B. K.
,
Rosenthal
Y.
&
Oppo
D. W.
2010
Holocene evolution of the Indonesian throughflow and the western Pacific warm pool
.
Nature Geoscience
3
,
578
583
.
Mandapaka
P. V.
,
Qin
X.
&
Lo
E. Y.
2017
Analysis of spatial patterns of daily precipitation and wet spell extremes in Southeast Asia
.
International Journal of Climatology
37
,
1161
1179
.
Meehl
G. A.
,
Stocker
T. F.
,
Collins
W. D.
,
Friedlingstein
P.
,
Gaye
A. T.
,
Gregory
J. M.
,
Kitoh
A.
,
Knutti
R.
,
Murphy
J. M.
,
Noda
A.
,
Raper
S. C. B.
,
Watterson
I. G.
,
Weaver
A. J.
&
Zhao
Z. C.
2007
Global climate projections
. In:
S. Solomon, D. Qin, M. Manning, Z. Chen, M. Marquis, K. B. Averyt, M. Tignor & H. L. Miller, eds.
Climate Change 2007: The Physical Science Basis
.
Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA
.
Misra
V.
&
DiNapoli
S.
2014
The variability of the Southeast Asian summer monsoon
.
International Journal of Climatology
34
,
893
901
.
Mora
C.
,
Frazier
A. G.
,
Longman
R. J.
,
Dacks
R. S.
,
Walton
M. M.
,
Tong
E. J.
,
Sanchez
J. J.
,
Kaiser
L. R.
,
Stender
Y. O.
&
Anderson
J. M.
2013
The projected timing of climate departure from recent variability
.
Nature
502
,
183
187
.
Neelin
J. D.
&
Latif
M.
1998
El Nino dynamics
.
Physics Today
51
,
32
36
.
Niedermeyer
E. M.
,
Sessions
A. L.
,
Feakins
S. J.
&
Mohtadi
M.
2007
Hydroclimate of the western Indo-Pacific warm pool during the past 24,000 years
.
Proceedings of the National Academy of Sciences
111
,
9402
9406
.
Philander
S. G. H.
1985
El Niño and La Niña
.
Journal of the Atmospheric Sciences
42
,
2652
2662
.
Picaut
J.
,
Ioualalen
M.
,
Menkes
C.
,
Declcroix
T.
&
McPhaden
M. J.
1996
Mechanism of the zonal displacements of the Pacific warm pool: implications for ENSO
.
Science
274
,
1486
1489
.
Soman
M. K.
&
Slingo
J.
1997
Sensitivity of the Asian summer monsoon to aspects of sea-surface-temperature anomalies in the tropical Pacific Ocean
.
Quarterly Journal of the Royal Meteorological Society
123
,
309
336
.
Wyrtki
K.
1989
Some thoughts about the west Pacific warm pool
. In:
Paper Presented at West Pacific Int. Meeting and Workshop on TOGA COARE, ORSTOM
,
Noume ́a, New Cale ́donia
.
Yan
X.-H.
,
Ho
C.-R.
,
Zheng
Q.
&
Klemas
V.
1992
Temperature and size variabilities of the Western Pacific warm pool
.
Science
258
,
1643
1645
.
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