Interannual variability of summer monsoon precipitation over the Indochina Peninsula in association with ENSO

Ge, Fei; Zhi, Xiefei; Babar, Zaheer Ahmad; Wei-wei, Tang; Chen, Peng

doi:10.1007/s00704-015-1729-y

Cited by 53 publications

(31 citation statements)

References 48 publications

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“…. Given that ENSO has a significant influence on the SCSSM [3,[10][11][12][13][14], the question naturally arises as to whether ENSO could also have an impact on the relationship between the VM and SCSSM. To answer this question, we computed the partial correlation between the FMA VMI and the following JAS SCSSMI by removing the effect of the previous winter (DJF)'s ENSO signal (represented by the Niño3.4 index).…”

Section: Relationship Between the Vm And Scssmmentioning

confidence: 99%

“…The mechanisms by which the extratropical atmospheric variability over the North Pacific influences the tropical Pacific SST anomalies have been extensively discussed [42][43][44][45][46][47]. It is proposed that the extratropical atmospheric variability can initiate a basin-scale SST structure Given that ENSO has a significant influence on the SCSSM [3,[10][11][12][13][14], the question naturally arises as to whether ENSO could also have an impact on the relationship between the VM and SCSSM. To answer this question, we computed the partial correlation between the FMA VMI and the following JAS SCSSMI by removing the effect of the previous winter (DJF)'s ENSO signal (represented by the Niño3.4 index).…”

Section: Mechanismsmentioning

confidence: 99%

“…The SCSSM exhibits considerable interannual variability [3,8,9]. Many studies suggest that El Niño-Southern Oscillation (ENSO) is the dominant factor that influences the interannual variation of the SCSSM [3,[10][11][12][13][14]. They found that ENSO exerts substantial influences on the SCSSM not only during its developing phase but also during its decaying phase.…”

Section: Introductionmentioning

confidence: 99%

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Influences of the North Pacific Victoria Mode on the South China Sea Summer Monsoon

Ding

Tseng

et al. 2018

Atmosphere

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Using the reanalysis data and the numerical experiments of a coupled general circulation model (CGCM), we illustrated that perturbations in the second dominant mode (EOF2) of springtime North Pacific sea surface temperature (SST) variability, referred to as the Victoria mode (VM), are closely linked to variations in the intensity of the South China Sea summer monsoon (SCSSM). The underlying physical mechanism through which the VM affects the SCSSM is similar to the seasonal footprinting mechanism (SFM). Thermodynamic ocean-atmosphere coupling helps the springtime SST anomalies in the subtropics associated with the VM to persist into summer and to develop gradually toward the equator, leading to a weakened zonal SST gradient across the western North Pacific (WNP) to central equatorial Pacific, which in turn induces an anomalous cyclonic flow over the WNP and westerly anomalies in the western equatorial Pacific that tend to strengthen the WNP summer monsoon (WNPSM) as well as the SCSSM. The VM influence on both the WNPSM and SCSSM is intimately tied to its influence on ENSO through westerly anomalies in the western equatorial Pacific.Atmosphere 2018, 9, 229 2 of 15 due to the El Niño warming can lead to a strong SCSSM. In contrast, during the summer following El Niño, an anomalous WNP anticyclone, which develops rapidly during the El Niño developing fall and persists until the following summer possibly because of a local positive thermodynamic feedback [15], Indian Ocean capacitor effect [16], or nonlinear interactions between ENSO and the Western Pacific warm pool annual cycle [17], can affect the SCS's climate and hence SCSSM. In addition to ENSO, other factors have also been shown to play a role in the year-to-year variations in the SCSSM intensity or onset, including the Indian Ocean sea surface temperature (SST) forcing [18][19][20][21], local air-sea interaction [22,23], and the extratropical-tropical interaction [24,25].Recent studies reported that the spring Victoria mode (VM), defined as the second empirical orthogonal function mode (EOF2) of North Pacific SST anomalies poleward of 20 • N [26], has a significant impact on the Pacific Intertropical Convergence Zone (ITCZ) precipitation during the following summer [27] and ENSO during the following winter [28]. Given that the developing ENSO exerts a forcing effect on the SCSSM, it is very likely that the spring VM could also have an impact on the SCSSM. However, the influences of the VM on the SCSSM have not been documented in the literature. The focus of this paper is to establish the delayed influence of the VM on the SCSSM. Specific questions of interest: Is there a close connection between the spring VM and the subsequent SCSSM? If so, how does the VM affect the SCSSM? Is there any relationship between influences of the VM on the SCSSM and ENSO? Data, Model, and Indices Observed DatasetsWe used atmospheric fields from the National Centers for Environmental Prediction-Department of Energy (NCEP-DOE) reanalysis version 2 (NCEP2) [29]. We used SST from t...

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Section: Relationship Between the Vm And Scssmmentioning

confidence: 99%

Section: Mechanismsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Influences of the North Pacific Victoria Mode on the South China Sea Summer Monsoon

Ding

Tseng

et al. 2018

Atmosphere

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“…Many studies have concentrated on the assessment of different reanalysis products and have shown that reanalysis data sets can effectively reduce the biases caused by the inhomogeneous distribution of observation stations (Simmons et al, 2004;Sylla et al, 2010;Cai et al, 2014). The performance of reanalysis data sets have been evaluated and compared with data from observation stations or other reliable sources (Screen and Simmonds, 2011;Cornes and Jones, 2013;Ge et al, 2017).…”

mentioning

confidence: 99%

Assessment of ECMWF reanalysis data in complex terrain: Can the CERA‐20C and ERA‐Interim data sets replicate the variation in surface air temperatures over Sichuan, China?

Luo

Yang³

et al. 2019

Intl Journal of Climatology

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Surface air temperatures (SATs) derived from the European Centre for Medium‐Range Weather Forecasts (ECMWF) ERA‐Interim and CERA‐20C reanalysis data sets are compared with data from 43 observation stations in Sichuan for 1979–2010. The results show (a) the temperatures from the ERA‐Interim and CERA‐20C data sets are strongly correlated with those from the observation stations, although significant cold biases are seen on both annual and seasonal timescales. (b) The biases in SATs are predominately influenced by the differences between the actual topography and the topography used in the reanalysis models. Larger differences in temperature are observed in the plateau and mountainous regions of Sichuan. We confirmed larger SAT biases at high altitudes by categorizing the elevation into four bands, each with a spacing of 1,000 m. (c) We reduced the biases resulting from elevation by using an elevation correction method with internal lapse rates derived from different reanalysis pressure levels. The annual mean bias was reduced from −2.86 to −0.75°C for the ERA‐Interim data set and from −5.27 to −2.21°C for the CERA‐20C data set. After calibration, the correlation coefficients between the difference in SAT (observed minus reanalysis data) and the difference in elevation (station elevation minus model elevation) decreased from −0.97 and −0.91 to −0.29 and −0.30 for the ERA‐Interim and CERA‐20C data sets, respectively. These significant differences should not be ignored in the application of reanalysis data sets to climate research. The evaluation and calibration of reanalysis data sets are essential before making assessments of regional climate change, especially over regions with complex topography.

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“…Many researchers indicated that the El Niño -Southern Oscillation (ENSO) cycles have influenced Thailand monsoon rainfall on interannual scales [5][6][7][8], [10][11][12][13][14]. The variations in the position and intensity of the ITCZ are associated with climate phenomena known as the ENSO.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Rainfall in the Eastern Thailand

Nounmusig¹

2018

GEOMATE

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Eastern Thailand needs for water increases daily due to population growth, economic developments, and urbanization. The main source of water in the region is mainly from the rain. Therefore, understanding of rainfall pattern in this region is required to support the planning of water management. In this study, the patterns of rainfall in eastern Thailand are analyzed by using statistical analysis. The data used from 15 rain gauge stations (the period in 1969-2008) of Thai Meteorological Department (TMD). The 40-year average of rainfall is found 1921mm.The region has abundant of rainfall during May to September due to Southwest monsoon, especially in windward location. The highest of rainfall and rain day found in August at Khlong Yai with exceeding 1000mm and exceed 25day, respectively. The results show yearly rainfall has been a tendency to decrease. The significant correlation between monthly rainfall and ENSO indices has the largest number in the transitional period (April, May, and October).

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Interannual variability of summer monsoon precipitation over the Indochina Peninsula in association with ENSO

Cited by 53 publications

References 48 publications

Influences of the North Pacific Victoria Mode on the South China Sea Summer Monsoon

Influences of the North Pacific Victoria Mode on the South China Sea Summer Monsoon

Assessment of ECMWF reanalysis data in complex terrain: Can the CERA‐20C and ERA‐Interim data sets replicate the variation in surface air temperatures over Sichuan, China?

Analysis of Rainfall in the Eastern Thailand

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