Statistically related coupled modes of South Asian summer monsoon interannual variability in the tropics

Syed, F. S.; Kucharski, Fred

doi:10.1002/asl.641

Cited by 12 publications

(13 citation statements)

References 28 publications

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“…The addition of significant 850 hPa correlations, shows lower heights over northwestern India (Figure 3g), which is consistent with a warm troposphere, convective instability and rainfall in the western GBM (Figure 3a). A similar result was also found by [28] when they regressed 850 hPa heights with the regional maximum covariance analysis of tropical Atlantic SST and South Asia precipitation [28]. Interestingly, significant PC2-850 hPa correlation values extend from India into the surrounding areas over the Arabian Sea, Iran and an eastward extension into the western portion of the GBM (Figure 3g).…”

Section: Global Climate Analysissupporting

confidence: 78%

A Hydroclimatological Analysis of Precipitation in the Ganges–Brahmaputra–Meghna River Basin

Curtis

Crawford

Rahman

et al. 2018

Water

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Understanding seasonal precipitation input into river basins is important for linking large-scale climate drivers with societal water resources and the occurrence of hydrologic hazards such as floods and riverbank erosion. Using satellite data at 0.25-degree resolution, spatial patterns of monsoon (June-July-August-September) precipitation variability between 1983 and 2015 within the Ganges-Brahmaputra-Meghna (GBM) river basin are analyzed with Principal Component (PC) analysis and the first three modes (PC1, PC2 and PC3) are related to global atmospheric-oceanic fields. PC1 explains 88.7% of the variance in monsoonal precipitation and resembles climatology with the center of action over Bangladesh. The eigenvector coefficients show a downward trend consistent with studies reporting a recent decline in monsoon rainfall, but little interannual variability. PC2 explains 2.9% of the variance and shows rainfall maxima to the far western and eastern portions of the basin. PC2 has an apparent decadal cycle and surface and upper-air atmospheric height fields suggest the pattern could be forced by tropical South Atlantic heating and a Rossby wave train stemming from the North Atlantic, consistent with previous studies. Finally, PC3 explains 1.5% of the variance and has high spatial variability. The distribution of precipitation is somewhat zonal, with highest values at the southern border and at the Himalayan ridge. There is strong interannual variability associated with PC3, related to the El Nino/Southern Oscillation (ENSO). Next, we perform a hydroclimatological downscaling, as precipitation attributed to the three PCs was averaged over the Pfafstetter level-04 sub-basins obtained from the World Wildlife Fund (Gland, Switzerland). While PC1 was the principal contributor of rainfall for all sub-basins, PC2 contributed the most to rainfall in the western Ganges sub-basin (4524) and PC3 contributed the most to the rainfall in the northern Brahmaputra (4529). Monsoon rainfall within these two sub-basins were the only ones to show a significant relationship (negative) with ENSO, whereas four of the eight sub-basins had a significant relationship (positive) with sea surface temperature (SST) anomalies in the tropical South Atlantic. This work demonstrates a geographic dependence on climate teleconnections in the GBM that deserves further study.

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Section: Global Climate Analysissupporting

confidence: 78%

A Hydroclimatological Analysis of Precipitation in the Ganges–Brahmaputra–Meghna River Basin

Curtis

Crawford

Rahman

et al. 2018

Water

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“…Cash et al () cite correlation coefficient values of −0.45 and −0.52 (99% level), while Syed and Kucharski (), Jha et al (), and Preethi et al () suggest values in the range −0.2 to >−0.5 (95% level) across most of North and South India, Pakistan, Nepal, and Sri Lanka, for June–September. No significant correlation is found across Bangladesh (Ahmed et al, ; Syed & Kucharski, ). Although some authors suggest that these relationships have been strengthening over time (e.g., Wu et al, ), B.…”

Section: Atmospheric Hazardsmentioning

confidence: 99%

“…Future modeling capability will rely on accurate representation of low-level atmospheric flow patterns and the subtropical jet to predict moisture transport in this region. (Ahmed et al, 2016;Syed & Kucharski, 2016). Although some authors suggest that these relationships have been strengthening over time (e.g., Wu et al, 2012), B.…”

Section: South Africa Rainfallmentioning

confidence: 99%

“…B. Cash et al (2016 cite correlation coefficient values of −0.45 and −0.52 (99% level), whileSyed and Kucharski (2016),Jha et al (2016), andPreethi et al (2016) suggest values in the range −0.2 to > −0.5 (95% level) across most of North and South India, Pakistan, Nepal, and Sri Lanka, for June-September. No significant correlation is found across Bangladesh…”

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confidence: 99%

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Correlations Between Extreme Atmospheric Hazards and Global Teleconnections: Implications for Multihazard Resilience

Steptoe

Jones

Fox

2018

Reviews of Geophysics

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Occurrences of concurrent extreme atmospheric hazards represent a significant area of uncertainty for organizations involved in disaster mitigation and risk management. Understanding risks posed by natural disasters and their relationship with global climate drivers is crucial in preparing for extreme events. In this review we quantify the strength of the physical mechanisms linking hazards and atmosphere‐ocean processes. We demonstrate how research from the science community may be used to support disaster risk reduction and global sustainable development efforts. We examine peer‐reviewed literature connecting 16 regions affected by extreme atmospheric hazards and eight key global drivers of weather and climate. We summarize current understanding of multihazard disaster risk in each of these regions and identify aspects of the global climate system that require further investigation to strengthen our resilience in these areas. We show that some drivers can increase the risk of concurrent hazards across different regions. Organizations that support disaster risk reduction, or underwrite exposure, in multiple regions may have a heightened risk of facing multihazard losses. We find that 15 regional hazards share connections via the El Niño–Southern Oscillation, with the Indian Ocean Dipole, North Atlantic Oscillation, and the Southern Annular Mode being secondary sources of significant regional interconnectivity. From a hazard perspective, rainfall over China shares the most connections with global drivers and has links to both Northern and Southern Hemisphere modes of variability. We use these connections to assess the global likelihood of concurrent hazard occurrence in support of multihazard resilience and disaster risk reduction goals.

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“…The present day generation of coupled models appear to be capable of reproducing the observed robust correlation between the SASD and SAOD indices: 54 of the 63 different CMIP3/5 models analysed have significant coefficients at P < 0.001 in all seasons. However, the multimodel mean SST anomalies associated with the SAOD index better represents the observed amplitudes in the Benguela-equatorial Niño region, often considered vital for climate fluctuations over tropical Atlantic and further afield (Losada et al, 2012;Syed and Kucharski, 2016;Kucharski and Joshi, 2017). Nonetheless, the subtropical SAO variability represented by the SASD affects climate variability in this region (Morioka et al, 2011;Rodrigues et al, 2015).…”

Section: Summary and Discussionmentioning

confidence: 99%

Analogous seasonal evolution of the South Atlantic SST dipole indices

Nnamchi

Kucharski

Keenlyside

et al. 2017

Atmospheric Science Letters

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Statistically related coupled modes of South Asian summer monsoon interannual variability in the tropics

Cited by 12 publications

References 28 publications

A Hydroclimatological Analysis of Precipitation in the Ganges–Brahmaputra–Meghna River Basin

A Hydroclimatological Analysis of Precipitation in the Ganges–Brahmaputra–Meghna River Basin

Correlations Between Extreme Atmospheric Hazards and Global Teleconnections: Implications for Multihazard Resilience

Analogous seasonal evolution of the South Atlantic SST dipole indices

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