Variability and teleconnections of South and East Asian summer monsoons in present and future projections of CMIP5 climate models

Preethi, B.; Mujumdar, Milind; Prabhu, Amita; Kripalani, R. H.

doi:10.1007/s13143-017-0034-3

Cited by 47 publications

(27 citation statements)

References 67 publications

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“…Figure 16 illustrates the spatial patterns of the correlation coefficients of precipitation at each grid point with the time series of the SAMP index. The spatial pattern shown on the upper left panel is based on the observations (GPCP data), while the pattern on the upper right is based on an ensemble of about 9 selected CMIP5 models (Preethi et al 2017). In observation, SAMP has a negative relationship with rainfall variability over many part of EAM.…”

Section: Future Changesmentioning

confidence: 99%

Linkages between the South and East Asian summer monsoons: a review and revisit

Seo

Lee

et al. 2017

Clim Dyn

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with decaying El Niño and developing Indian Ocean sea surface temperature (SST) warming anomalies; the other is the negative inter-correlation, resulting from developing El Niño and western Pacific SST cooling. The IODM mode also has a delayed impact on the negative connection by modulating Eurasian snow cover. The observed evidence reveals that the recent intensification of the negative relationship is attributable to the strengthening of the zonal SST gradient along the Indian Ocean, western Pacific, and eastern Pacific. Analysis of experiments in the fifth phase of the Coupled Model Intercomparison Project further indicates a possibility for the negative linkage to be further enhanced under anthropogenic global warming with considerable interdecadal modulation in mid and late twentyfirst century.

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Section: Future Changesmentioning

confidence: 99%

Linkages between the South and East Asian summer monsoons: a review and revisit

Seo

Lee

et al. 2017

Clim Dyn

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“…Long-term changes in the relationship have been identified in previous studies (Guo 1992;Kripalani and Kulkarni 2001;Wu 2002;Wang and Huang 2006;Lin, Lu, and Wu 2017;Ha et al 2017;Preethi et al 2017b). One prominent change in the Indian-North China summer rainfall relationship occurred around the late 1970s (Wu 2002).…”

Section: Perspectives On the Factors Involved In The Changes In The Rmentioning

confidence: 65%

“…The weakened connection after the late 1970s can be attributed to a shift in the distribution of large rainfall variability in India to lower latitudes, which weakened the impacts of anomalous Indian heating on the midlatitude Asian atmospheric circulation (Wu 2002;Wu and Wang 2002). The change in the relationship has also been detected in coupled climate model simulations (Preethi et al 2017b;Wu and Jiao 2017). However, a plausible explanation for the non-stationarity in the above relationship has yet to be determined.…”

Section: Perspectives On the Factors Involved In The Changes In The Rmentioning

confidence: 78%

“…One pathway is atmospheric circulation change over the lower latitudes that modifies the moisture transport from the Indian Ocean to East Asia (Zhang, Sumi, and Kimoto 1999;Krishnan and Indian-East Asian summer rainfall relationship have been confirmed by Wu (2017) and Wu and Jiao (2017) using updated rainfall data. Secular changes have been observed in the relationship between the Indian and Yangtze-Huai River summer rainfall variations, as well as between the Indian and Korea-Japan summer rainfall variations (Ha et al 2017;Preethi et al 2017b).…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, there are also secular variations in the relationship between Indian and KoreaJapan summer rainfall variations in historical simulations and future projections of climate models (Preethi et al 2017b), albeit with the timing of the changes in the relationship differing from model to model and among different simulations of a single model (Wu and Jiao 2017). As an illustration, Figure 2 displays the 21-years running correlation between Indian and North China JJAS rainfall in two members of the CCSM4 and CNRM-CM5 simulations, which are selected from all the simulations shown in Wu and Jiao (2017).…”

Section: Introductionmentioning

confidence: 99%

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Perspectives on the non-stationarity of the relationship between Indian and East Asian summer rainfall variations

Lin

2017

Atmospheric and Oceanic Science Letters

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The relationship between Indian and East Asian summer rainfall variations is non-stationary in observations as well as in historical simulations of climate models. Is this non-stationarity due to changes in effects of external forcing or internal atmospheric processes? Whilst ENSO is an important oceanic forcing of Indian and East Asian summer rainfall variations, its impacts cannot explain the observed long-term changes in the Indian-East Asian summer rainfall relationship. Monte Carlo test indicates that the role of random processes cannot be totally excluded in the observed longterm changes of the relationship. Analysis of climate model outputs shows that the Indian-North China summer rainfall relationship displays obvious temporal variations in both individual and ensemble mean model simulations and large differences among model simulations. This suggests an important role played by atmospheric internal variability in changes of the Indian-East Asian summer rainfall relationship. This point of view is supported by results from a 100-years AGCM simulation with climatological SST specified in the global ocean. The correlation between Indian and North China or southern Japan summer rainfall variations displays large fluctuations in the AGCM simulation.摘要观测和气候模式中印度和东亚夏季降水变化的关系是不稳定的。本文讨论外部强迫和大气内部过程在上述关系变化中的作用。虽然厄尔尼诺-南方涛动在印度和东亚夏季降水变化中有重要作用，但它并不能解释印度-东亚降水关系的长期变化。蒙特卡罗试验说明随机过程的作用不能完全排除。气候模式结果分析表明印度-东亚夏季降水的关系在不同模式之间和同一模式不同模拟之间都有明显变化。这指出了大气内部过程对印度-东亚夏季降水关系变化的影响。此观点为100年气候平均海温强迫的大气环流模式试验结果所支持。

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How well are the downscaled CMIP5 models able to reproduce the monsoon precipitation over seven homogeneous zones of India?

Das

Akhter

2019

Intl Journal of Climatology

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Statistical downscaling through perfect prognosis (PP) method is widely utilized to bridge the gap between large‐scale global climate model (GCM) simulations and regional scale or local scale observed predictands. Present study has assessed the performances of PP‐based downscaled CMIP5 GCMs in simulating observed monsoon precipitation over seven homogeneous zones of India, namely, North Mountainous India (NMI), Northwest India (NWI), North Central India (NCI), Northeast India (NEI), West Peninsular India (WPI), East Peninsular India (EPI) and South Peninsular India (SPI). Firstly, PP models have been constructed through principal component regression (PCR) using large‐scale atmospheric predictors from National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis. Secondly, GCM predictors have been imposed on the PP models to downscale large scale GCM simulations at regional scale. Four performance metrics namely percent bias (PB), interquartile relative fractions (IRF), Perkins skill score (PS) and Kuiper metric (KM) have been considered to evaluate skills of downscaled GCMs in reproducing mean, variance, probability distribution function (PDF) and cumulative distribution functions (CDF) of observed precipitation, respectively. As per results of several metrics, PP models have performed relatively better over NCI and SPI zones. However, they have shown poor skills in reproducing the observed variance over all zones. Further to improve the performances of PP models, quantile mapping has been embedded to form hybrid (PPQM) models, which have shown superior skills over all the zones. In addition, PPQM models have also shown their applicability to provide more reliable added value information over sub‐regional scale compared to raw GCMs.

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Variability and teleconnections of South and East Asian summer monsoons in present and future projections of CMIP5 climate models

Cited by 47 publications

References 67 publications

Linkages between the South and East Asian summer monsoons: a review and revisit

Linkages between the South and East Asian summer monsoons: a review and revisit

Perspectives on the non-stationarity of the relationship between Indian and East Asian summer rainfall variations

How well are the downscaled CMIP5 models able to reproduce the monsoon precipitation over seven homogeneous zones of India?

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