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Marvin Xiang Ce Seow, Yushi Morioka, and Tomoki Tozuka

observational data, reanalysis products, and coupled model experiments. We first provide a description of the data and model experiment designs in sections 2 and 3 , respectively. Section 4 outlines the multivariate empirical orthogonal function (MEOF) method used to capture the coupled air–sea modes of variability. Section 5 discusses the winter atmospheric patterns that control the CT variability via reanalysis and observational data analyses. Section 6 analyzes the relative contributions of

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Chen Li, Jing-Jia Luo, Shuanglin Li, Harry Hendon, Oscar Alves, and Craig MacLachlan

verification datasets are described in section 2 . The multimodel prediction skill of the Somali CEF, MC CEF, CEF seesaw index, and the related monsoonal precipitation pattern are assessed in section 3 . In section 4 , we will explore the possible reasons for the distinct forecast performance of the Somali CEF in the different models. A summary is given in section 5 . 2. Multimodel and verification data a. Multimodel 1) The POAMA-2 model POAMA (version 2) is a fully coupled ocean–atmosphere climate

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D. Argüeso, R. Romero, and V. Homar

instruments (dual-frequency precipitation radar), active and passive microwave measurements, and precipitation gauge analyses. This ensemble of precipitation products provides a range of rainfall values for each time and location, and thus serves as an estimate of the observational uncertainty associated with satellite-derived information. As such, it is a way to incorporate this uncertainty in the model performance evaluation. For comparison purposes, all datasets were interpolated to the highest

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Claire L. Vincent and Todd P. Lane

topographic peaks during the afternoon and evolve into organized offshore-propagating systems during the night. The model skill in reproducing the diurnal precipitation cycle over the land and sea relies on an accurate representation of the relative contribution of orographic forcing, convergence from the main sea–land-breeze disturbances, and far offshore destabilization due to the cooling phase of the land–sea-breeze circulation. Several clear deficiencies in model performance are identified. The

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Jieshun Zhu, Arun Kumar, and Wanqiu Wang

) summarized the latest dynamical MJO prediction capability by evaluating the MJO predictions in models participating in the World Weather Research Program–World Climate Research Program (WWRP–WCRP) Subseasonal to Seasonal Prediction (S2S) Project. In the backdrop of recent advances in MJO prediction skill, it is still an open question as to what extent further gains in dynamical MJO prediction skill remain to be achieved. A methodology to address this question is to estimate the predictability of the MJO

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Jieshun Zhu, Wanqiu Wang, and Arun Kumar

suppressed farther east over the western Pacific. Over the course of the following 30–60 days, the enhanced convective anomaly in the Indian Ocean intensifies and propagates across the Maritime Continent and the western-central Pacific Ocean. The simulation of the MJO has become a benchmark test for the performance of climate models in the tropics. Although many general circulation models (GCMs) have improved representations of the MJO, many shortcomings still remain, for example, in the simulation of

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Claire L. Vincent and Todd P. Lane

circulation models. NASA Tech. Memo. 104606, Vol. 3, 102 pp. Dee , D. P. , and Coauthors , 2011 : The ERA-Interim reanalysis: Configuration and performance of the data assimilation system . Quart. J. Roy. Meteor. Soc. , 137 , 553 – 597 , https://doi.org/10.1002/qj.828 . 10.1002/qj.828 Fujita , M. , K. Yoneyama , S. Mori , T. Nasuno , and M. Satoh , 2011 : Diurnal convection peaks over the eastern Indian Ocean off Sumatra during different MJO phases . J. Meteor. Soc. Japan , 89A

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Jian Ling, Yuqing Zhao, and Guiwan Chen

NOAA/OAR/ESRL. For consistency with model outputs, all observations were interpolated to the same spatial grids (2.5° × 2.5°) as model outputs. Twenty-seven climate simulations are from global multimodel evaluation project on vertical structure and diabatic processes of the MJO launched by the MJOTF/GASS. Most simulations were integrated for 20 years using external forcing from 1991 to 2010. They provided 6-hourly outputs interpolated into 2.5° × 2.5° horizontal resolutions and 22 vertical pressure

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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

sensitivity experiments with various cumulus schemes to decide that using the cumulus scheme of Emanuel (1991) for land grids and the cumulus scheme of Tiedtke (1996) for ocean grids produces the best model performance. As for the land surface scheme, CLM4.5 newly incorporated within RegCM4 is used. Therefore, the land use distributions used for RegCM4 control and deforestation experiments are exactly the same as those from CESM (in terms of the RegCM4 domain) except for the discrepancy caused by the

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Wan-Ling Tseng, Huang-Hsiung Hsu, Noel Keenlyside, Chiung-Wen June Chang, Ben-Jei Tsuang, Chia-Ying Tu, and Li-Chiang Jiang

convection is observed from one region to another when the MJO passed over the MC. Thus, the MJO is characterized by downstream development of deep convection at specific longitudes, such as 95°, 110°, 120°, and 145°E, over the MC, where mountainous islands, such as Sumatra, Borneo, Sulawesi, and New Guinea, are located. The effect of the MC on the MJO has been evaluated through climate model simulations. Inness and Slingo (2006) demonstrate the orographic weakening effect of the MC on MJO convection

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