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Jieshun Zhu, Arun Kumar, and Wanqiu Wang

simulated the intraseasonal wind variability resulting in significant biases in latent heat flux and in SST variability. Unrealistic SST variations, in turn, degraded the MJO simulation by affecting SST-modulated heat fluxes and the boundary layer moisture convergence or surface moist static energy (e.g., Flatau et al. 1997 ; Maloney and Sobel 2004 ). Given the critical role of convective parameterization in MJO simulations, it is possible that the large uncertainties in current estimates for MJO

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Ya Yang, Xiang Li, Jing Wang, and Dongliang Yuan

European Centre for Medium-Range Weather Forecasts (ECMWF). A hindcast run was forced with the ECMWF wind stress and heat flux between 1990 and 2001. More detailed description of model configuration can be found in Wang and Yuan (2015) . We extracted equatorial waves by decomposing the results of the hindcast experiment. The wave decomposition method has been explained in Yuan et al. (2004) . The three-dimensional pressure and zonal velocity of the OGCM were projected onto the baroclinic vertical

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Yan Zhu, Tim Li, Ming Zhao, and Tomoe Nasuno

is barotropic energy conversion from ISO flow to higher-frequency eddies. A more challenging aspect of MJO–HFW interaction is HFW feedback to MJO. It has been shown that HFW may exert an upscale feedback to summer ISO through nonlinear modulation of MJO-scale latent heat flux and diabatic heating ( Zhou and Li 2010 ; Hsu and Li 2011 ). Another upscale feedback process is through eddy momentum transport (e.g., Hsu and Li 2011 ; Liu and Wang 2013 ). Most previous studies concentrated either on

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Ming Feng, Yongliang Duan, Susan Wijffels, Je-Yuan Hsu, Chao Li, Huiwu Wang, Yang Yang, Hong Shen, Jianjun Liu, Chunlin Ning, and Weidong Yu

Hendon 2004 ). The strongest large-scale intraseasonal sea surface temperature (SST) variations in austral summer in the tropics are found north of Australia in the Indonesian–Australian Basin, forced by air–sea heat flux and wind-driven current anomalies associated with the MJO ( Vialard et al. 2013 ; Marshall and Hendon 2014 ). In addition, large diurnal variation of SST (DV SST) has been modeled and observed in the region ( Seo et al. 2014 ; Wang and Zhang 2017 ). The air–sea coupling at these

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Chidong Zhang and Jian Ling

model capability of subseasonal prediction. Several possible reasons for the MC barrier effect on MJO propagation have been suggested. If surface fluxes, especially latent heat flux, are important to the MJO ( Maloney and Sobel 2004 ; Sobel et al. 2008 ), then the MJO would be weakened or diminished by the reduction in surface fluxes in the MC region because of its many islands. If moisture convergence of the low-level circulation is essential to the MJO ( Wang 1988 ; 2005 ), then its distortion

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Shijian Hu, Ying Zhang, Ming Feng, Yan Du, Janet Sprintall, Fan Wang, Dunxin Hu, Qiang Xie, and Fei Chai

salinity balance in the Bay of Bengal, while horizontal advection related to the monsoon plays a dominant role in the north Indian Ocean ( Rao and Sivakumar 2003 ). In the tropical Indian Ocean, the seasonal cycle of the mixed layer salinity in the south-central Arabian Sea is mainly due to meridional advection driven by the monsoon winds, while freshwater flux due to precipitation may play an important role in the southwestern tropical Indian Ocean ( Da-Allada et al. 2015 ). Seasonality of the mixed

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Jieshun Zhu, Wanqiu Wang, and Arun Kumar

of air–sea interaction. Observational diagnoses have shown coherent variations in surface heat fluxes, SST, and convection associated with the MJO (e.g., Krishnamurti et al. 1988 ; Shinoda et al. 1998 ; Woolnough et al. 2000 ; Kumar et al. 2013 ). Many numerical studies also noted improved MJO simulations when an atmosphere-only GCM (AGCM) is coupled to an ocean model (e.g., Flatau et al. 1997 ; Waliser et al. 1999 ; Kemball-Cook et al. 2002 ; Inness et al. 2003 ; Zhang et al. 2006

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Kevin E. Trenberth and Yongxin Zhang

; Trenberth et al. 2019 ). Here, we attempt to remedy this situation. The oceans play a major role in the climate system as the main memory of any energy imbalance. The ocean currents and eddies further redistribute the energy, mainly in the form of heat, both vertically and horizontally. Using closure of the energy budget, we can deduce the net surface energy fluxes as a residual of top-of-atmosphere (TOA) measurements and the vertically integrated atmospheric energy divergence ( Trenberth and Solomon

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Hironari Kanamori, Tomo’omi Kumagai, Hatsuki Fujinami, Tetsuya Hiyama, and Tetsuzo Yasunari

propagating convective systems differed between islands. Although these previous studies focused on the relationship between diurnal convection/precipitation and large-scale circulation (i.e., the MJO) over the MC, the processes that deliver heavy precipitation over land remain poorly understood. Deep convection and heavy precipitation throughout the year create a major moisture sink in the MC. Atmospheric water budget analyses over the MC show that moisture flux convergence variability contributes to

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Chu-Chun Chen, Min-Hui Lo, Eun-Soon Im, Jin-Yi Yu, Yu-Chiao Liang, Wei-Ting Chen, Iping Tang, Chia-Wei Lan, Ren-Jie Wu, and Rong-You Chien

, and larger heights than other vegetation types. Therefore, converting rain forest into bare ground or grassland has three major effects on land surface conditions: 1) a reduction in evapotranspiration, 2) an increase in surface albedo, and 3) a decrease in surface roughness. The reduction in evapotranspiration decreases the surface latent heat flux and leads to a surface warming effect. The decrease in roughness reduces the aerodynamic exchanges between the surface and the atmosphere. Furthermore

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