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  • Air–Sea Interactions from the Diurnal to the Intraseasonal during the PISTON, MISOBOB, and CAMP2Ex Observational Campaigns in the Tropics x
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Kyle Chudler, Weixin Xu, and Steven A. Rutledge

radar measurements with sufficient detail to accurately resolve the salient differences between land and ocean precipitation. Importantly, these products also provide vertical profiles of radar reflectivity (TRMM 250 m and GPM 125-m resolution). Previous studies in the region using only surface rainfall estimates (i.e., Natoli and Maloney 2019 ) cannot provide information on the vertical structure of storms, so this is a novel component of this research. While surface rainfall statistics are

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Michael B. Natoli and Eric D. Maloney

through a weighted linear interpolation. As a result, infrared information is only used to track systems identified by microwave estimates rather than adding additional calibrated precipitation estimates. Estimates are then bias corrected using gauge data over land and the Global Precipitation Climatology Project over ocean ( Xie et al. 2017 ). While such bias correction improves the accuracy of satellite precipitation estimates over complex terrain, there are still quantitative weaknesses in products

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Emily M. Riley Dellaripa, Eric D. Maloney, Benjamin A. Toms, Stephen M. Saleeby, and Susan C. van den Heever

. Other studies have focused on the changes in amplitude and phase of the DCP over the MC through different MJO large-scale conditions. Using TRMM observations, Peatman et al. (2014) found that the DCP amplitude over MC land peaks just prior to the arrival of large-scale active MJO convection. Birch et al. (2016) reached a similar conclusion with TRMM observations and regional climate model simulations, but focused on the DCP over Sumatra during different large-scale MJO conditions. Cloud

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Wei-Ting Chen, Chien-Ming Wu, and Hsi-Yen Ma

.S. Department of Energy Cloud Associated Parameterizations Testbed (CAPT) following Ma et al. (2013 , 2014 , 2015 ). The CAPT hindcasts analyzed in this study were carried out using the CAM5 (version cesm1_0_5) with finite-volume dynamical core, a horizontal resolution of 0.9° × 1.25° (latitude by longitude), 30 vertical levels, prescribed SST, and the Community Land Model, version 4.0 (CLM4). The physics package pertinent to the hindcast simulations consist of the deep convection scheme ( Zhang and

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Corinne B. Trott, Bulusu Subrahmanyam, Heather L. Roman-Stork, V. S. N. Murty, and C. Gnanaseelan

. 2016 ). NASA’s Jet Propulsion Laboratory provides daily SMAP SSS data starting 1 April 2015, interpolated using the 8-day running mean. We use the most recent SMAP version 4.0, which accounts for galaxy and land contamination corrections and reduced brightness temperature biases ( Fore et al. 2016 ). Soil Moisture and Ocean Salinity (SMOS) data used in this study are the most up-to-date debiased SMOS SSS level 3 data generated by the Ocean Salinity Center of Expertise at the Centre Aval de

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Wei-Ting Chen, Shih-Pei Hsu, Yuan-Huai Tsai, and Chung-Hsiung Sui

TC genesis to take place. Tropical waves can also interact with the prominent diurnal variability over the MC and SCS. In MJO events, the mean and diurnal amplitude of land precipitations over the MC are enhanced 6 days ahead of the MJO convection envelope, while the precipitation over the coastal ocean is largely suppressed ( Peatman et al. 2014 ; Birch et al. 2016 ; Hung and Sui 2018 ). Baranowski et al. (2016b) tracked the KW events passing MC using satellite observations to identify the

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Benjamin A. Toms, Susan C. van den Heever, Emily M. Riley Dellaripa, Stephen M. Saleeby, and Eric D. Maloney

important for understanding the role of moist convection in climate in general, and particularly as it relates to the MJO. Fig . 1. Pentad OLR anomalies for the simulated MJO event based on OMI, reconstructed using the OMI principal components for each pentad. The anomalies shown are only for the 20–96-day anomalies represented by OMI and therefore do not directly consider the mesoscale convective structure of the MJO. Positive (negative) OLR anomalies correspond to suppressed (enhanced) convection

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