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Luis E. Pineda and Patrick Willems

December–May daily rainfall over this region. Therefore, an emerging question is whether such skillful seasonal forecasts can be translated into regionwide predictions of daily rainfall statistics, which, if anticipated with a useful lead time, can be used to warn the likelihood of high-impact weather (floods and droughts) by extending hydrological forecasting with rainfall–runoff hydraulic models to longer times. In the PAEP, traditional approaches to seasonal hydroclimatic forecasting have only

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Wenyi Xie, Xiankui Zeng, Dongwei Gui, Jichun Wu, and Dong Wang

(MODFLOW-2005). USGS Techniques and Methods 6-D1, 240 pp., https://pubs.usgs.gov/tm/tm6d1/ . 10.3133/tm6D1 Marsh , P. , 1999 : Snowcover formation and melt: Recent advances and future prospects . Hydrol. Processes , 13 , 2117 – 2134 , https://doi.org/10.1002/(SICI)1099-1085(199910)13:14/15<2117::AID-HYP869>3.0.CO;2-9 . 10.1002/(SICI)1099-1085(199910)13:14/15<2117::AID-HYP869>3.0.CO;2-9 Martinec , J. , 1975 : Snowmelt runoff model for stream flow forecasts . Hydrol. Res. , 6 , 145 – 154

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James Cleverly, Chao Chen, Nicolas Boulain, Randol Villalobos-Vega, Ralph Faux, Nicole Grant, Qiang Yu, and Derek Eamus

partitioning ET into soil and plant components for olive orchards in a semi-arid region . Agric. Water Manage. , 97 , 1769 – 1778 , doi:10.1016/j.agwat.2010.06.009 . Hutley, L. B. , Leuning R. , Beringer J. , and Cleugh H. A. , 2005 : The utility of the eddy covariance techniques as a tool in carbon accounting: Tropical savanna as a case study . Aust. J. Bot. , 53 , 663 – 675 , doi:10.1071/BT04147 . Isaac, P. R. , Leuning R. , Hacker J. M. , Cleugh H. A. , Coppin P. A. , Denmead

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Maxime Turko, Marielle Gosset, Modeste Kacou, Christophe Bouvier, Nanee Chahinian, Aaron Boone, and Matias Alcoba

1. Introduction During the last 10 years, rainfall measurement from commercial microwave link (CML) network has gradually emerged as a useful complement to traditional rainfall measurement based on gauges, weather radar or satellites. Uijlenhoet et al. (2018) and Chwala and Kunstmann (2019) provide a good review of the state of the art and the research developed since the pioneering work of Messer et al. (2006) and Leijnse et al. (2007b) . The CML technique is based on the analysis of

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Fidele Karamage, Yuanbo Liu, and Yongwei Liu

monthly runoff simulations. A consistent time series of gridded monthly calibrated runoff data was obtained based on a second-order polynomial regression (PR) ( BSL 2018 ; Billo 2007 ; Morrison 2015 ) between monthly downscaled (gridded) observed and CN-based runoff simulated data. PR includes explicit mathematical formulations and is acceptable for streamflow forecasting ( Rezaie-Balf and Kisi 2018 ; Giustolisi and Savic 2006 ). The statistical method used for runoff calibration was evaluated

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Pravat Jena, Sourabh Garg, and Sarita Azad

subsequently brings forth the importance of the evaluation of gridded data. Further, satellite estimates are currently being used as an alternate source of data for monitoring and validation purposes since they are available at high spatiotemporal scales as models ( Dinku et al. 2014 ). Some of these products are, Climate Prediction Center Morphing technique (CMORPH), Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Climate Data Record (PERSIANN-CDR), Tropical

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Yanhong Gao, Fei Chen, and Yingsha Jiang

were generated, such as NOAA’s Climate Prediction Center morphing technique (CMORPH) ( Joyce et al. 2004 ), the Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Climate Data Record (PERSIANN-CDR) ( Ashouri et al. 2015 ) products, and the Asian Precipitation–Highly Resolved Observational Data Integration Toward Evaluation of Water Resources (APHRODITE) ( Yatagai et al. 2009 , 2012 ). Satellite remote sensing provides precipitation information for a broader

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Julie M. Thériault, Nicolas R. Leroux, and Roy M. Rasmussen

.g., Groisman et al. 1991 ; Yang et al. 1995 ; Thériault et al. 2012 ) have shown snowfall undercatch to increase with increasing wind speed as a result. In addition, observations show a significant variability in undercatch for a given wind speed due to the wide variety of snow crystal types present in the atmosphere ( Yang et al. 1995 ), as well as with snowfall intensity ( Colli et al. 2020 ). Accurately measuring snowfall precipitation is of importance for hydrological forecasting, water management

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Hua Su, Robert E. Dickinson, Kirsten L. Findell, and Benjamin R. Lintner

. Fig . 16. Flowchart of the mechanisms that explain the observed negative correlation between April snow depth and early warm-season precipitation. Our findings demonstrate that spring snow conditions may contribute to forecasting the early warm-season precipitation over northern continental interior regions. Such snow datasets could become increasingly available via enhanced observational capacity and improved data assimilation techniques ( De Lannoy et al. 2010 ; Su et al. 2010 ). However, the

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Sho Kawazoe and William J. Gutowski Jr.

-rain-producing mesoscale convective systems . Mon. Wea. Rev. , 133 , 961 – 976 . Schumacher, R. S. , and Johnson R. H. , 2006 : Characteristics of U.S. extreme rain events during 1999–2003 . Wea. Forecasting , 21 , 69 – 85 . Shepard, D. S. , 1984 : Computer mapping: The SYMAP interpolation algorithm. Spatial Statistics and Models, G. L Gaile and C. J. Willmott, Eds., D. Reidel, 133–145. von Storch, H. , Langenberg H. , and Feser F. , 2000 : A spectral nudging technique for dynamical downscaling

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