The interanual rainfall variability in Indonesia corresponding to El Niño Southern Oscillation and Indian Ocean Dipole

Hendrawan, I Gede; Asai, Koji; Triwahyuni, Andhita; Lestari, Diah Valentina

doi:10.1007/s13131-019-1457-1

Cited by 28 publications

(26 citation statements)

References 25 publications

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“…The relationship between ENSO and IOD also has been questioned for their independency to each other. While many studies have reported that the IOD is statistically independent to ENSO (e.g., [9,[17][18][19], some studies argued that the ENSO and IOD are not totally independent (e.g., [20][21][22]).…”

Section: Introductionmentioning

confidence: 99%

The Relationship between River Flow Regimes and Climate Indices of ENSO and IOD on Code River, Southern Indonesia

Nugroho

Tamagawa

Harada

2021

Water

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Predicting the streamflow regimes using climate dynamics is important in water resource management. However, in Indonesia, there are few studies targeting climate indices and streamflow. A previous study found difficulty in developing a statistical prediction model for this relationship due to its non-linear nature. This study attempted to address that gap by applying multiple regression (MR) models using second- and third-order polynomial functions to show the non-linear relationship between climate and flow regime indices. First, a correlation analysis was performed to check the variable relationships. There was a good and significant correlation of El Niño Southern Oscillation (ENSO) with the flow regime indices. Secondly, MR models were developed with the same-time variables. The developed model showed that the Indian Ocean Dipole (IOD) had the effect of strongly increasing the high flow in La Niña phases. Finally, time-lagged MRs were developed aiming at forecasting. Lagged MR models with six-month leading climate indices demonstrated a relatively good correlation with the observed data (mostly R > 0.700) with moderate accuracy (root mean square error = 44–51%). It suggests that the forecasting of flow regime may be possible using ENSO and IOD indices.

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Section: Introductionmentioning

confidence: 99%

The Relationship between River Flow Regimes and Climate Indices of ENSO and IOD on Code River, Southern Indonesia

Nugroho

Tamagawa

Harada

2021

Water

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“…Previous researches indicated that Indian Ocean Dipole (IOD) influence crop failure in tropics (Anderson et al, 2019) and Southeast Asia (Gao et al, 2019). The crop failure is related to extreme rainfall associated with IOD (Hendrawan et al, 2019;Krishnaswamy et al, 2015). Hopefully, further research can obtain a new predictor to forecast seasonal rainfall in study area for the second planting season for the 2and 3-month lead time.…”

Section: Discussionmentioning

confidence: 99%

The Use of SST Anomaly to Predict Seasonal Rainfall during the Second Planting Period in the Tanoh Abee Irrigation Area, Aceh Besar

2020

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Irrigation in Tanoh Abee is used for agricultural activities especially during the second planting season during dry season. However, the availability of irrigation water is controlled by total rainfall received. An accurate prediction of rainfall, which traditionally used “keneunong” local wisdom, is urgently required. The objective of the study is to obtain the best predictor of seasonal rainfall based on the Pacific sea surface temperature (SST) anomaly and the monthly lead time of prediction. We employed monthly rainfall from six stations surrounding the study area and combined with principal component analysis to eliminate rainfall autocorrelation. Seasonal rainfall (quarterly average) was calculated from monthly data. The results showed that 1-month lead time strongly correlated to seasonal rainfall in Tanoh Abee (r<-0.7, α=5%) for the second planting period. On other hand, the 2-month and 3-month lead time were useful to predict seasonal rainfall in March-April-May (MAM) only. For April-May-June (AMJ) and May-June-July (MJJ), the correlation between SST anomaly and seasonal rainfall was weak. This finding indicated that the accuracy of prediction decreases with the longer lead time. Based on our analysis, coordinates of 170° E – 175° E; 5° N - 5° S in Niño 4 region have strongly correlated with seasonal rainfall in MAM, AMJ, and MJJ periods. Moreover, further research is necessary to combine any approaches that will improve our prediction skill for another 2- or 3-month lead time.

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“…Curah hujan tertinggi di wilayah utara terjadi pada bulan Februari (331 mm) sedangkan di bagian tengah dan selatan terjadi pada bulan November dengan tinggi hujan 421 dan 461 mm. Hasil ini juga sejalan dengan penelitian Hendrawan et al (2019) yang menyatakan bahwa curah hujan bulan November dipengaruhi persitiwa ENSO positif dan negatif. Wilayah selatan lebih basah dengan jumlah curah hujan 12% lebih banyak dari wilayah utara.…”

Section: Kondisi Iklim Wilayah Kajianunclassified

Pola Spasial Kekeringan di Jawa Barat Pada Kondisi El Nino Berbasis Metode Palmer Drought Severity Index (PDSI)

2021

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Permasalahan hidrometeorologi berupa kekeringan menjadi tantangan yang dihadapi Indonesia, khususnya Jawa Barat. Terjadinya kekeringan di Jawa Barat yang beriklim muson erat kaitannya dengan fenomena El Niño Southern Oscillation (ENSO). Salah satu metode untuk mengukur tingkat kekeringan adalah dengan metode Palmer Drought Severity Index (PDSI). Penelitian ini bertujuan untuk menentukan tingkat kekeringan di wilayah Jawa Barat berdasarkan metode PDSI pada kondisi normal dan El Niño serta membuat peta sebaran tingkat kekeringan. Data curah hujan dari Climate Research Unit (CRU) 2000-2012 digunakan dalam studi ini. Pola spasial penghitungan PDSI kemudian dipetakan berdasarkan musim. Model spasial kekeringan berdasarkan indeks Palmer menunjukkan bahwa puncak kekeringan terjadi pada bulan Juni-Juli-Agustus (JJA) dan September-Oktober-November (SON). Kekeringan merata di seluruh Jawa Barat pada periode Juli hingga Agustus yang berpusat di Jawa Barat bagian utara dari September hingga November. Pada periode Januari hingga Maret, kekeringan hanya terkonsentrasi di sebagian kecil wilayah Jawa Barat bagian barat dan selatan. Peristiwa El Niño pada musim kemarau (Juni-November) meningkatkan parahnya kekeringan di Jawa Barat.

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The interanual rainfall variability in Indonesia corresponding to El Niño Southern Oscillation and Indian Ocean Dipole

Cited by 28 publications

References 25 publications

The Relationship between River Flow Regimes and Climate Indices of ENSO and IOD on Code River, Southern Indonesia

The Relationship between River Flow Regimes and Climate Indices of ENSO and IOD on Code River, Southern Indonesia

The Use of SST Anomaly to Predict Seasonal Rainfall during the Second Planting Period in the Tanoh Abee Irrigation Area, Aceh Besar

Pola Spasial Kekeringan di Jawa Barat Pada Kondisi El Nino Berbasis Metode Palmer Drought Severity Index (PDSI)

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