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Kumar Vijay Mishra, Witold F. Krajewski, Radoslaw Goska, Daniel Ceynar, Bong-Chul Seo, Anton Kruger, James J. Niemeier, Miguel B. Galvez, Merhala Thurai, V. N. Bringi, Leonid Tolstoy, Paul A. Kucera, Walter A. Petersen, Jacopo Grazioli, and Andrew L. Pazmany

in situ measurements ( Ciach and Krajewski 1999a , b ); a detailed exposition of these ground-based methods can be found in Habib et al. (2010) . However, these instruments do not yield precipitation measurements in the space–time continuum. On the other hand, while the wide use of modern weather radar systems has enabled continuous rainfall measurements in the space–time domain ( Doviak and Zrnić 1993 ; Bringi and Chandrasekar 2001 ; Bringi et al. 2007 ), this feature compromises the accuracy

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Munir A. Nayak, Gabriele Villarini, and A. Allen Bradley

40° or 30.5°N, but four out of 17 AR time steps had differences due to the existence of secondary maxima. In each of these cases, we selected the AR major axis by visual examination of the IVT maps. The visual examination to select AR major axes and additional search from south to north were the two modifications that we made to the methodology by Lavers and Villarini (2013b) . The 40°N latitude is chosen to make sure that ARs travel deep into the central United States, and a length from 40° to

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Andrea Thorstensen, Phu Nguyen, Kuolin Hsu, and Soroosh Sorooshian

. , Reed S. , Smith M. , Zhang Z. , and Seo D. J. , 2004 : Hydrology laboratory research modeling system (HL-RMS) of the US National Weather Service . J. Hydrol. , 291 , 297 – 318 , doi: 10.1016/j.jhydrol.2003.12.039 . Koren, V. , Smith M. , Cui Z. , and Cosgrove B. , 2007 : Physically-based modifications to the Sacramento Soil Moisture Accounting model: Modeling the effects of frozen ground on the rainfall–runoff process. NOAA Tech. Rep. NWS 52, 43 pp. [Available online at www

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Huan Wu, Robert F. Adler, Yudong Tian, Guojun Gu, and George J. Huffman

precipitation estimation (QPE) remains very challenging ( Kidd and Levizzani 2011 ). All existing methods for precipitation information estimation have both strengths and weaknesses, with significant uncertainties being reported even in ground-based radar and gauge observations (e.g., Adam et al. 2006 ; Clark and Slater 2006 ). In situ (gauge) observations measure precipitation directly, while they have weakness in spatial coverage and issues of undercatch during windy weather and occasional loss of

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