Abstract

It is widely accepted that the interannual variability of East Asian summer rainfall is forced by sea surface temperature (SST), and SST anomalies are widely used as predictors of East Asian summer rainfall. But it is still not very clear what percentage of the interannual rainfall variability is contributed by SST anomalies. In this study, Atmospheric general circulation model simulations forced by observed interannual varying SST are compared with those forced by the fixed annual cycle of SST climatology, and their ratios of interannual variance (IAV) are analyzed. The output of 12 models from the 5th Phase of Coupled Model Intercomparison Project (CMIP5) are adopted, and idealized experiments are done by Community Atmosphere Model version 4 (CAM4). Both the multi-model median of CMIP5 models and CAM4 experiments show that only about 18 % of the IAV of rainfall over East Asian land (EAL) is explained by SST, which is significantly lower than the tropical western Pacific, but comparable to the mid-latitude western Pacific. There is no significant difference between the southern part and the northern part of EAL in the percentages of SST contribution. The remote SST anomalies regulates rainfall over EAL probably by modulating the horizontal water vapor transport rather than the vertical motion, since the horizontal water vapor transport into EAL is strongly modulated by SST but the vertical motion over EAL is not. Previous studies argued about the relative importance of tropical Indian Ocean and tropical Pacific Ocean to East Asian summer rainfall anomalies. Our idealized experiments performed by CAM4 suggest that the contributions from these two ocean basins are comparable to each other, both of which account for approximately 6 % of the total IAV of rainfall over EAL.

Highlights

  • Summer is the rainy season for East Asia which is affected by the monsoon

  • Since vertical motion in the mid-troposphere is another direct factor in regulating the rainfall, we examined the value of 1-interannual variance (IAV)(SSTClim)/IAV(AMIP) for vertical velocity at 500 hPa (Fig. 5e–f)

  • Over East Asian land (EAL) region, the regional averaged SSTcontributed fractions are 21.1 and 26.8 % for the zonal and meridional water vapor transport, and 7.9 % for the vertical velocity. These results based on Community Atmosphere Model version 4 (CAM4) confirm that the sea surface temperature (SST) impacts the IAV of rainfall over EAL by modulating horizontal water vapor transport, rather than by modulating the vertical velocity over EAL, consistent with the conclusion drawn based on CMIP5 models

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Summary

Introduction

Summer is the rainy season for East Asia which is affected by the monsoon. The interannual variability of the East Asian summer rainfall is regulated by multiple factors, such as the atmospheric internal dynamics (Lu et al 2006; Kosaka et al 2012; Song et al 2013), the sea surface temperature (SST) forcing (Chang et al 2000; Wang et al 2013; Zuo et al 2013), and land–atmosphere interaction (Zhang et al 2011; Duan et al 2012; Li et al 2015). Studies focused on drought have revealed that the drought events are stochastically generated over most mid-latitude land regions, while SST only plays a secondary role (Ferguson et al 2010; Stevenson et al 2015) Most of these studies are focused on North America or from a global perspective, and it is still unclear to what extent is the interannual variability of East Asian summer rainfall forced by SST. The 5th phase of Coupled Model Intercomparison Project (CMIP5; Taylor et al 2012) has released a large set of simulations performed by multiple models, motivating us to quantitatively assess the contribution of SST to East Asia summer rainfall variability under the multi-model framework. To investigate the relative importance of TIO SST and TPO SST to East Asian summer rainfall, another two experiments named F_TIO and F_TPO are done with

MIROC5
11 MPI-ESM-MR
Model evaluation on the IAV of summer rainfall
SST contribution estimated by CMIP5 models
SST contribution estimated by CAM4 experiments
Findings
Conclusion and discussion
Full Text
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