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  • 12th International Precipitation Conference (IPC12) x
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Phu Nguyen, Mohammed Ombadi, Vesta Afzali Gorooh, Eric J. Shearer, Mojtaba Sadeghi, Soroosh Sorooshian, Kuolin Hsu, David Bolvin, and Martin F. Ralph

the performance of PDIR-Now in capturing the seasonal cycle of precipitation, based on monthly precipitation, with GPCP 1DD precipitation being used as a baseline for evaluation. We carry out the analysis at two regions with distinct rainfall seasonal cycles. The first region (location 1) is a rectangular region bounded by the latitudes (1°–6°N) and the longitudes (16°–21°E). This region lies at the northwestern part of the Congo River basin with elevation in the range of 0–700 m above sea level

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Allison E. Goodwell

summer, TE is dominantly from north or west, with very broad distributions in some regions, reflecting the large variety of precipitation causes in this season ( Kunkel et al. 2012 ). Southwest (California, Lower Colorado, Rio Grande): Here, TE is dominantly from south or southwest in winter. This reflects precipitation events due to atmospheric rivers that convey moisture from the Pacific Ocean during this season ( Gershunov et al. 2017 ). In the summer when conditions are relatively drier in most

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Samantha H. Hartke, Daniel B. Wright, Dalia B. Kirschbaum, Thomas A. Stanley, and Zhe Li

. 2015 ). These can result from tropical cyclones, mesoscale convective systems, orographic uplift, and atmospheric rivers that interact with the region’s complex terrain ( Barros et al. 2014 ; Mahoney et al. 2016 ; Moore et al. 2015 ). Hurricane Frances was followed by Hurricane Ivan within a 2-week period in September 2004, for example, and caused approximately 400 landslides, 11 deaths, and widespread property damage ( Boyle 2014 ). Landslides continue to pose a threat to the region, with three

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Zhe Li, Daniel B. Wright, Sara Q. Zhang, Dalia B. Kirschbaum, and Samantha H. Hartke

.1175/JHM-D-15-0094.1 Mahoney , K. , and Coauthors , 2016 : Understanding the role of atmospheric rivers in heavy precipitation in the southeast United States . Mon. Wea. Rev. , 144 , 1617 – 1632 , https://doi.org/10.1175/MWR-D-15-0279.1 . 10.1175/MWR-D-15-0279.1 Matsui , T. , and Coauthors , 2014 : Introducing multisensor satellite radiance-based evaluation for regional Earth System modeling . J. Geophys. Res. Atmos. , 119 , 8450 – 8475 , https://doi.org/10.1002/2013JD021424 . 10

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