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Kyle Chudler, Weixin Xu, and Steven A. Rutledge

TRMM PR data and groups together near-surface raining pixels that are contiguous in space. Once a feature is outlined, the location of the PF is determined as the centroid of an ellipse surrounding the raining pixels. In addition to the three-dimensional PR radar data, measurements from other TRMM instruments ( Kummerow et al. 1998 ) such as the Lightning Imaging Sensor (LIS), Visible and Infrared Scanner (VIRS), and Microwave Imager (TMI) can then be collocated with the PF. Therefore, information

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Michael B. Natoli and Eric D. Maloney

employed in this study is from CMORPH ( Joyce et al. 2004 ; Xie et al. 2017 ). Precipitation accumulation estimates are provided at 30-min temporal resolution and 8-km spatial resolution (at the equator), covering 60°S–60°N. This technique uses microwave precipitation estimates from satellites in low-Earth orbit to identify specific precipitation features, and then tracks them through time and space using infrared retrievals from geostationary satellites. Successive microwave estimates are morphed

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

and December 2013 was chosen to compute OLR climatology. The OLR for December 2016 is obtained from NOAA Climate Data Record (CDR) of OLR version 1.2 ( Lee and NOAA CDR Program 2011 ), which is estimated from High-Resolution Infrared Radiation Sounder (HIRS) radiance observations with a 2-day lag. It is given daily with 1° × 1° horizontal resolution. The European Centre for Medium-Range Weather Forecasts interim reanalysis (ERA-Interim, hereinafter ERA-Int; Dee et al. 2011 ) is utilized for zonal

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

propagation of the MJO through the MC region when fixed versus diurnally varying solar radiation was used in their cloud-permitting regional simulations of the November 2011 MJO event. Both studies reason that the absence of the DCP frees up moisture to enhance MJO convection and its ability to traverse the MC thereby suggesting that the DC is key to understanding the different behavior of MJO maintenance and propagation over the MC, impacts that are also likely to manifest during boreal summer ISOs

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

; Huffman et al. 2010 ) from 1998 to 2015. GPCP precipitation is based on microwave, infrared, and rain gauge observations ( Huffman et al. 1997 ), with a horizontal resolution of 1° × 1°. TRMM 3B42 is the merged microwave, Precipitation Radar (PR), and infrared level-3 rainfall product at a horizontal resolution of 0.25° × 0.25°, with the calibration of rain gauge data on a monthly basis. We used two precipitation estimates here to provide the possible range of observational uncertainty. The model

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

major findings. 2. Data and methods a. Data Tracing the magnitude and location of MJO events requires a multivariate analysis. Wheeler and Hendon (2004) introduced a seasonally independent index based on the empirical orthogonal functions (EOFs) of 850- and 200-hPa zonal winds and satellite-observed outgoing longwave radiation (OLR). The pair of principal component time series that Wheeler and Hendon (2004) extracted is called the Real-time Multivariate MJO Series 1 (RMM1) and Series 2 (RMM2

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