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Guoqiang Tang, Martyn P. Clark, and Simon Michael Papalexiou

Tmin occurs during the night and represents the temperature of the nocturnal boundary layer, which is thicker than the daytime mixed layer ( Klotzbach et al. 2009 ). Local factors such as land-cover types have more impact on Tmin and its variability than Tmax ( Pena-Angulo et al. 2015 ). The spatial correlation length of Tmin could also be shorter than that of Tmax ( Pena-Angulo et al. 2015 ; Tang et al. 2020 ). Therefore, Tmax could be less demanding for station densities in spatial interpolation

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Natalie Teale and David A. Robinson

study period (14 245 days) and was adjusted over 10 000 iterations. The study area used for the SOM classification was the same as the ERA-Interim reanalysis-derived IVT (30°–50°N and 60°–90°W boundary, 2.5° × 2.5° spatial resolution). A pilot study indicated that a smaller area focused directly over the Northeast did not sufficiently capture the character of the moisture fluxes influencing the area. Midlevel atmospheric pressure composites of 500 mb geopotential height from ECMWF ERA

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Omar V. Müller, Pier Luigi Vidale, Benoît Vannière, Reinhard Schiemann, and Patrick C. McGuire

due to the better definition of coastlines and orography. This enhancement of surface boundary conditions constitutes an improvement in the simulated precipitation in areas like the Maritime Continent ( Schiemann et al. 2014 ; Johnson et al. 2016 ). The southern part of the Andes Chain is a region exposed to westerlies that bring moisture from the Pacific, raining over the western slopes and drying over the eastern side ( Viale et al. 2019 ), a process that is magnified at HR (see 5a). The

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Dayal Wijayarathne, Paulin Coulibaly, Sudesh Boodoo, and David Sills

precipitation forcing for the hydrological model in operational flood forecasting. Further research is essential to fill these niche areas before using radar QPEs for operational flood forecasting in urban and semiurban watersheds with confidence. The current study involves implementing a flood forecasting framework that allows connecting hydrological and hydraulic models in one platform using both rain gauge and weather radar QPEs derived from U.S. and Canadian weather radar to assess the benefit of radar

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Pradeep V. Mandapaka and Edmond Y. M. Lo

1600 UTC current day) scales. Fig . 1. Map showing eight GPM 0.1° grid cells and the daily and hourly gauge networks used for evaluation of GPM IMERG rainfall estimates. The version 06B dataset extends back to June 2000 and contains IMERG products, which have been retrospectively generated for the TRMM era. We used these retrospectively generated products for the hourly analysis period of January 2005–December 2010. Despite significant efforts to create a continuous and homogenous dataset across

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Fidele Karamage, Yuanbo Liu, and Yongwei Liu

were selected based on their long time series of data availability and recent versioning with improved accuracies. Modified CN-based runoff was simulated using five main datasets including, precipitation, land use and land cover (LULC), soil texture (sand, silt, and clay), digital elevation model (DEM), and water withdrawal related to human population data. Calibration of the simulated runoff was performed by employing two datasets (river discharges and major basin boundaries). Analysis of the

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Ryan A. Zamora, Benjamin F. Zaitchik, Matthew Rodell, Augusto Getirana, Sujay Kumar, Kristi Arsenault, and Ethan Gutmann

impact response ( Wilhite and Svoboda 2000 ), yet most seasonal drought prediction systems are currently working only in a research capacity, with few dynamically based systems applied operationally to drought preparation and management. Research and interest in subseasonal to seasonal (S2S) meteorological prediction has risen over the past two decades, as is evident in the appearance of multiple intermodel comparison projects and operational forecast ensembles. These include the North American

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Yanan Meng, Jianhua Sun, Yuanchun Zhang, and Shenming Fu

parameters, precipitation, and background circulations for all MCS categories are presented in section 3 ; and finally, section 4 presents a conclusion and discusses the results. Fig . 1. Geographic distribution of elevations in southwestern China (shading; m). The blue box is the study region, while the extended area (red box) denotes the MCS formation area. The purple lines represent the boundaries of the Tibetan Plateau and the Yungui Plateau. 2. Data and methods a. Data Hourly 0.05° × 0

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Jessica C. A. Baker, Dayana Castilho de Souza, Paulo Y. Kubota, Wolfgang Buermann, Caio A. S. Coelho, Martin B. Andrews, Manuel Gloor, Luis Garcia-Carreras, Silvio N. Figueroa, and Dominick V. Spracklen

magnitude of SM–ET relationships, representation of variables impacting land–atmosphere interactions over the Caatinga in ERA5-Land, HadGEM3, and BAM-1.2 could still be improved. d. Tracing surface-to-atmosphere moisture pathways When considering land–atmosphere moisture transfer pathways, it can be helpful to distinguish between processes that operate at the land–atmosphere interface and processes that occur in the atmospheric boundary layer. For example, the coupling between the land surface and

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K. Haleakala, M. Gebremichael, J. Dozier, and D. P. Lettenmaier

retention or discharge of rainfall. In some cases, a rainfall event may refreeze entirely in the snowpack with no immediate runoff or snowmelt. However, the degree to which these and the abovementioned factors govern ROS response may be muffled by inconsistent thresholds used to define rainfall or preexisting snow. Moreover, few studies have observed the boundary governing whether SWE accumulates or ablates during winter ROS, or events in which the in-storm temperature is near or above the melting point

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