Role of equatorially asymmetric sea surface temperature anomalies in the Indian Ocean in the Asian summer monsoon and El Niño‐Southern Oscillation coupling

Kawamura, Ryuichi; Matsuura, Takeshi; Iizuka, Satoshi

doi:10.1029/2000jd900610

Cited by 89 publications

(92 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…5c). Kawamura et al (2001) further reported that the positive wind-evaporation-SST (WES) feedback, proposed by Xie and Philander (1994), contributes to the establishment of such an asymmetric structure in the equatorial region. However, the negative rainfall anomalies over the subcontinent do not persist and disappear in late summer (AS), which is consistent with the model results of Kawamura et al (2004).…”

Section: Resultsmentioning

confidence: 99%

“…Several studies have already shown that a change in the ENSO cycle after the late 1970s has resulted in a change in the ISM-ENSO relationship during its mature and decay phase (Yang et al 1996;Yang and Lau 1998;Kawamura et al 2001). If the recent change in the ENSO cycle is independent of global warming or not, it is necessary to look at the presentday climate models' simulations to see whether these models can reproduce the present shift in the spatial correlation pattern between Indian monsoon rainfall and ENSO.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

On the Recent Change of the Indian Summer Monsoon-ENSO Relationship

Kawamura¹,

Uemura²,

Suppiah

2005

SOLA

Self Cite

View full text Add to dashboard Cite

A remarkable change in the relationship between the El Niño-Southern Oscillation (ENSO) and Indian summer monsoon (ISM) during the last five decades is examined using a fine resolution rainfall data set, ENSO indices and a large-scale monsoon circulation index. Although the all-India monsoon rainfall (IMR) index represents rainfall variations particularly over central and western parts of India, it does not represent rainfall variability in northeast India, which leads to the weakening correlation between IMR and the large-scale monsoon index in recent decades. The relationship between ISM and ENSO was strong in late summer over central and northwest India before the late 1970s but, after the late 1970s, the strongest relationship between ISM and ENSO shifted to early summer and also moved to over northeast India. In effect, the recent weakening relationship between ISM and ENSO based on the use of IMR represents a change in dominance of the spatial correlation pattern, from northwest-central parts to northeast part after the late 1970s.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

On the Recent Change of the Indian Summer Monsoon-ENSO Relationship

Kawamura¹,

Uemura²,

Suppiah

2005

SOLA

Self Cite

View full text Add to dashboard Cite

show abstract

“…The persistence of WES feedback affects the land surface hydrologic processes in the Asian continent through a Rossby wave response to the anomalous convective heating. Kawamura et al [106] also drew a conclusion that the WES feedback in the TIO serves as a bridge between the ENSO prevailing in the preceding winter and the anomalous summer monsoon.…”

Section: Impacts Of Atmospheric Teleconnections Of El Niño On Spring mentioning

confidence: 99%

“…Kawamura et al [106] also drew a conclusion that the WES feedback in the TIO serves as a bridge between the ENSO prevailing in the preceding winter and the anomalous summer monsoon. In Figure 10a, the composite anomalies of tropical rainfall over the BoB are indeed significantly negative during the EP El Niño years in springtime.…”

Section: Impacts Of Atmospheric Teleconnections Of El Niño On Spring mentioning

confidence: 99%

“…Precipitation decreases (increases) with Northeasterly (Northwesterly) wind anomalies in north (south) of the equator over TIO [100]. Kawamura et al [106] further used an ocean general circulation model forced by daily mean wind stresses and heat fluxes to examine possible roles of the TIO in the Asian summer monsoon and ENSO coupling. They found the westward extension of anomalously suppressed convection from the vicinity of the Philippines into the NIO from the preceding winter to spring, which has a signal of ENSO and can be viewed as a developing process of WES feedback.…”

Section: Impacts Of Atmospheric Teleconnections Of El Niño On Spring mentioning

confidence: 99%

See 1 more Smart Citation

Satellite Observations of El Niño Impacts on Eurasian Spring Vegetation Greenness during the Period 1982–2015

Fan

Zhou

2017

Remote Sensing

View full text Add to dashboard Cite

As Earth's most influential naturally-recurring sea and atmospheric oscillation, ENSO results in widespread changes in the climate system not only over much of the tropics and subtropics, but also in high latitudes via atmospheric teleconnections. In the present study, the linkages between springtime vegetation greenness over Eurasia and El Niño are investigated based on two long-term normalized difference vegetation index (NDVI) datasets from 1982 to 2015, and possible physical mechanisms for the teleconnections are explored. Results from the Empirical Orthogonal Function (EOF) and Singular Value Decomposition (SVD) analyses consistently suggest that the spatial patterns of NDVI, with "negative-positive-negative" values, have closer connections to El Niño. In particular, East Russia is identified as the key region with the strongest negative influences from Eastern Pacific (EP) El Niño on spring vegetation growth. During EP El Niño years, suppressed convection over the Bay of Bengal (BoB) may excite a Rossby wave from the BoB to the Far East. East Russia is located in the west of a large cyclone anomaly accompanied by the strong North and Northwesterly wind anomalies and the transport of cold air from Siberia. As a result, surface air temperature decreases significantly over East Russia and thus inhibits the vegetation growth during spring in the EP El Niño years.

show abstract

Assessment of western Indian Ocean SST bias of CMIP5 models

et al. 2017

Self Cite

View full text Add to dashboard Cite

The western Indian Ocean sea surface temperature (SST) is among the key factors that affect precipitation over India and East Africa. This study examined the western Indian Ocean SST biases among the Coupled Model Intercomparison Project phase 5 (CMIP5) models. It was found that the multimodel ensemble‐mean SST biases over the western equatorial Indian Ocean are warmer than the observations during the summer monsoon season. However, about half the models show positive SST biases, whereas negative ones in the other half. The models with warmer SST biases exhibit a pattern similar to the Indian Ocean Dipole, with stronger equatorial easterly wind biases during fall and a deeper thermocline in the western equatorial Indian Ocean. In the models with cooler SST biases, negative SST biases are observed over the entire tropical Indian Ocean throughout the year and the wind biases over the equatorial Indian Ocean are southeasterly during summer and fall. Heat budget analysis revealed the importance of ocean currents in forming the early summer development of SST biases over the western equatorial Indian Ocean. The formation of SST biases is related to surface current biases induced by the weaker biases of southwesterly monsoon winds and SST biases over the southwestern equatorial Indian Ocean, which are advected by the East African Coastal Currents. On the other hand, almost of all the CMIP5 models show prominent cold SST biases over the northern Arabian Sea during the premonsoon season. The SST biases are induced by excess surface cooling during the winter monsoon season.

show abstract

Role of equatorially asymmetric sea surface temperature anomalies in the Indian Ocean in the Asian summer monsoon and El Niño‐Southern Oscillation coupling

Cited by 89 publications

References 24 publications

On the Recent Change of the Indian Summer Monsoon-ENSO Relationship

On the Recent Change of the Indian Summer Monsoon-ENSO Relationship

Satellite Observations of El Niño Impacts on Eurasian Spring Vegetation Greenness during the Period 1982–2015

Assessment of western Indian Ocean SST bias of CMIP5 models

Contact Info

Product

Resources

About