Analysing the relationship between ocean indices and rainfall in the Chao Phraya River Basin

Rangsiwanichpong, Prem; Kazama, So; Ekkawatpanit, Chaiwat

doi:10.1002/joc.4997

Cited by 6 publications

(6 citation statements)

References 28 publications

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“…According to Rangsiwanichpong et al . (2017), rainfall in the Chao Phraya River basin shows a strong correlation to the ENSO index, such as SOI: the orographic rain mechanism is consistent with this, finding. The southerly wind may be the major driver in the orographic lift there.…”

Section: Resultssupporting

confidence: 75%

“…The primary function of the southerly wind in this area may include transferring moisture from the South China Sea to the inner coastal region of Thailand. According to Rangsiwanichpong et al (2017), rainfall in the Chao Phraya River basin shows a strong correlation to the ENSO index, such as SOI: the orographic rain mechanism is consistent with this, finding. The southerly wind may be the major driver in the orographic lift there.…”

Section: Overview Of Rainfall In Thailandsupporting

confidence: 66%

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Influence and variability of monsoon trough and front on rainfall in Thailand

Tomkratoke

Sirisup

2021

Intl Journal of Climatology

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High variabilities in rainfall and the subsequent consequences have caused severe water-related issues for Thailand over recent decades. In this study, the factors that affect rainfall variability over Thailand were determined. The spatio-temporal structures of the monthly rainfall in Thailand between 1979 and 2018 were extracted via an empirical orthogonal function (EOF) analysis.With a unimodal temporal structure, the first EOF mode suggests the overall phenomenon governing rain characteristics in Thailand. The higher modes, consisting of bimodal temporal structures, indicate different rain phenomena in various regions. A significantly high correlation between the 3-month average of the monsoon trough index and rainfall was observed, while wet adiabatic front and convective available potential energy (CAPE) data had a moderately high correlation. Only the local front index, within the Gulf of Thailand, correlated to the rain characteristics along the east coast of southern Thailand. The cross-wavelet analysis indicated that most of the rainfall variability correlates with monsoon trough. However, the front can involve extreme events. The interannual variability of monsoon trough and rainfall with a dominant time scale between 3.0 and 6.0 years has significantly increased since 1995. Meanwhile, the intra-annual variability is more intermittent, indicating rare intensified strong tropical cyclones along the monsoon troughs in Thailand. The interannual variability of the monsoon trough and front indices also intermittently connects with the Southern Oscillation Index (SOI). However, the relationship in annual and intra-annual cycles is mostly weak. Therefore, the dependence of interannual variability of rainfall in Thailand on SOI or monsoon trough is comparable. Notably, the intra-annual rainfall variability is heavily influenced by the monsoon trough and front. This study is the first to identify the crucial factors behind the seasonal rain phenomena in Thailand. This information will benefit seasonal rainfall predictors and increase preparedness for hydro-climatic related disasters in the Indo-China region.

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Section: Resultssupporting

confidence: 75%

Section: Overview Of Rainfall In Thailandsupporting

confidence: 66%

Influence and variability of monsoon trough and front on rainfall in Thailand

Tomkratoke

Sirisup

2021

Intl Journal of Climatology

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“…The above results support our decision to perform further investigation on the effect of Niño1+2 and Niño3 on the amount of NTR in Section 4.5. Note, that these two variables were used as the main factors to study the relationships or variabilities of rainfall in China [22], Thailand [43] and India [44].…”

Section: Rainfall and Oceanic Indicesmentioning

confidence: 99%

Predictive Model for Northern Thailand Rainfall Using Niño Indexes and Sea Surface Height Anomalies in the South China Sea

Buathong,

Moonchai,

Saenton

et al. 2023

JMSE

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Northern Thailand rainfall (NTR) plays a crucial role in supplying surface water resources for downstream regions that millions of Thais rely on. The NTR has been reported to be adversely affected by the recent climate change making it impossible to accurately predict rainfall for better water management. In this work, we attempt to find an indicator that can be used to predict monthly NTR using an oceanic index based on sea surface height anomaly (SSHA) called the South China Sea Index (SCSI). First, we investigate the lead-lag relationships between NTR and several well-known indices. Relationships of NTR-Niño1+2 and NTR-Niño3 appear to be relatively strong. We then perform empirical orthogonal function (EOF) analysis on SSHA in the South China Sea and observe that the 2nd principal component (PC) time series and NTR strongly correlate. However, direct use of PC time series is computationally costly. Instead, we use SSHA information relating to the second EOF mode to create SCSI without performing EOF analysis. The correlation of SCSI-NTR is negatively strong. Lastly, we forecast NTR using SARIMAX models with Niño1+2, Niño3, and SCSI as inputs. The best model was SARIMAX (1, 0, 1)(0, 0, 2)12 using SCSI and Nino3 as inputs with AIC = 2368.705, RMSE = 51.167 mm per month and R2 = 0.732. Result raises capacity for effective climate change-related planning and management in the area.

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“…This analysis was conducted to determine the relationship between ocean water level changes and rainfall in the Chao Phraya River Basin in Thailand (Figure 10.) [13]. The analysis was performed to evaluate the extent to which the increase in the sea level indicators (southern oscillation index, SOI) and NINO sea surface temperature indices within the box 0°-10°S, 90°-80°W (which is NINO3) is correlated with precipitation.…”

Section: Level IV Of Raps Applicationmentioning

confidence: 99%

Application of Rescaled Adjusted Partial Sums (Raps) Method in Hydrology – An Overview

Đurin¹,

Kranjčić²,

Kanga³

et al. 2022

ACAE

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To describe the behaviour of watercourses, numerous parameters should be considered, such as water flow, depth/water level, velocity, and the amount of deposit in a waterbed. In addition, many other parameters should be analysed to understand the mechanism of specific watercourses. The most typical parameters are those associated with water quality, such as water temperature, and pH value, and temperature, as well as various climate parameters, such as precipitation, evaporation, and insolation, which are visualised in the form of a time series. The measurement frequency can differ for each parameter. Depending on the number of available measurements, hourly, daily, monthly, and yearly data can be obtained, which can then be used to form a time series. Many well-established and applicable procedures and models for time-series analyses exist, including the rescaled adjusted partial sums method (RAPS). This method is devised to detect possible irregularities and/or fluctuations within the original time series, which cannot be achieved using typical time-series analysis methods. This paper presents a comprehensive review of the application of the RAPS method in hydrology, where the advantages and disadvantages of the method are discussed.

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Analysing the relationship between ocean indices and rainfall in the Chao Phraya River Basin

Cited by 6 publications

References 28 publications

Influence and variability of monsoon trough and front on rainfall in Thailand

Influence and variability of monsoon trough and front on rainfall in Thailand

Predictive Model for Northern Thailand Rainfall Using Niño Indexes and Sea Surface Height Anomalies in the South China Sea

Application of Rescaled Adjusted Partial Sums (Raps) Method in Hydrology – An Overview

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