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Adam V. Rydbeck, Tommy G. Jensen, and Matthew R. Igel

-level precipitable water (LPW), and rain ( Fig. 12 ). The daily and meridionally averaged surface vapor flux and 10-m wind speed for days 1, 3, and 5 are shown in Figs. 12a and 12c . Line thickness increases with increasing time (i.e., day 5 is thicker than day 3, and day 3 is thicker than day 1). On day 1, the surface vapor fluxes in the respective simulations are similar in magnitude because of increased surface wind speed that compensates for the reduced surface temperature in the downwelling simulation

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

connection between convective cell morphology and intraseasonal variability in the atmospheric state was considered using the bulk parameters of vertical wind shear, convective available potential energy (CAPE), and convective inhibition (CIN). We calculated the low-frequency evolution of these bulk parameters according to the following method. First, low-frequency anomalies in atmospheric state variables such as temperature, water vapor mixing ratio, and zonal and meridional wind were calculated. These

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Michael B. Natoli and Eric D. Maloney

; Copernicus Climate Change Service (C3S; C3S 2017 )] is used for surface downwelling solar radiation, surface wind, and total column water vapor. In addition, reanalyses of specific humidity and wind are used at pressure levels every 50 hPa from 1000 to 100 hPa. All variables are considered at 1-h temporal resolution on a 0.125° spatial grid from 1998 to 2018 to be consistent with the CMORPH period of record. While there are known weaknesses to reanalyses (i.e., Birch et al. 2015 ), the high resolution

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

. Neelin , 2010 : Temporal relations of column water vapor and tropical precipitation . J. Atmos. Sci. , 67 , 1091 – 1105 , https://doi.org/10.1175/2009JAS3284.1 . 10.1175/2009JAS3284.1 Hong , S.-Y. , and H.-L. Pan , 1998 : Convective trigger function for a mass-flux cumulus parameterization scheme . Mon. Wea. Rev. , 126 , 2599 – 2620 , https://doi.org/10.1175/1520-0493(1998)126<2599:CTFFAM>2.0.CO;2 . 10.1175/1520-0493(1998)126<2599:CTFFAM>2.0.CO;2 Houze , R. A. , S. G. Geotis , F

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

terrain height to study the effects of topography on precipitation (e.g., Barthlott and Kirshbaum 2013 ; Rasmussen and Houze 2016 ; Zhu et al. 2017 ). All simulations used observed weekly averaged NOAA optimum interpolation sea surface temperatures (OI SSTs; Reynolds et al. 2002 ). Each simulation is initiated with horizontal winds, temperature, pressure (Exner function), water vapor mixing ratio, and soil moisture and temperature from the fifth generation of the European Centre for Medium

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