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Erin Dougherty and Kristen L. Rasmussen

horizontal scales less than 2000 km and within the boundary level, the flow was allowed to freely evolve, thus enabling changes in sub-synoptic-scale weather to occur. The WRF-CONUS simulations were comprised of two sets of simulations—one of the current climate and the other representing the future climate. The current climate simulations (CTRL) were forced with ERA-Interim (ERA-I) reanalysis data every 6 h over a continuous 13-yr period from 2000 to 2013. The future simulations were also forced every 6

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Yixin Wen, Terry Schuur, Humberto Vergara, and Charles Kuster

, space-based precipitation measurements often have underestimation issues ( Wen et al. 2018 ; Bartsotas et al. 2018 ). Weather radars provide perhaps the best opportunity to collect precipitation with both high spatial and temporal resolutions. The current NWS Weather Surveillance Radar–1988 Doppler (WSR-88D) network has dramatically increased our ability to observe high-resolution precipitation data in space and time. Technically, WSR-88Ds are capable of implementing scanning strategies that would

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Randal D. Koster, Anthony M. DeAngelis, Siegfried D. Schubert, and Andrea M. Molod

1. Introduction a. Background and problem statement The ocean–atmosphere–land system is inherently chaotic ( Shukla 1998 ). Nevertheless, its current state contains information about how it may evolve, and this information, if properly utilized, can provide for skillful Earth system forecasts. Characterizing the evolution of the Earth system from an initial state—characterizing the inherent predictability of Earth system variables at multiple time scales in the face of chaos—continues to be a

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Zhichang Guo and Paul A. Dirmeyer

of transitional climate zones in Europe as a consequence of global warming. The geographic locations of hot spot regions in turn might be changed since they follow the migrated transition zone. These studies have suggested that interannual variability of soil moisture could result in year-to-year variability in land–atmosphere coupling strength. The current study examines the interannual variation in land–atmosphere coupling strength and how it is related to soil moisture anomalies. This is of

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Shida Gao, Pan Liu, and Upmanu Lall

? How well can the leading modes of precipitation for the next season be predicted from the leading modes of the current season’s SST and IVT? Since the SST field represents the slowly evolving boundary conditions for the atmosphere and hence for IVT and precipitation, we are interested in seeing how the SST information translates into the seasonal statistics (specifically the mean field) of IVT and through that to the hemispheric precipitation, at the seasonal time scale. The covariation of these

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Clara Sophie Draper

-consuming model retuning to obtain these forecast benefits, since NWP boundary layer schemes tend to be heavily tuned to their current (deterministic) land model climatology. 5. Conclusions and recommendations A number of conclusions and recommendations can be drawn from this study, starting with those for offline land data assimilation systems. First, the standard method of adding soil moisture perturbations to each ensemble member at regular time intervals produces unrealistic spatial patterns in the

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Patricia Lawston-Parker, Joseph A. Santanello Jr., and Sujay V. Kumar

this manner, the links in the chain that are upstream and/or downstream of the observations used in the calibration can be assessed. Soil hydraulic parameters (SHPs) and/or initial soil moisture (ISM) are calibrated to observations of surface fluxes, 2-m temperature (T2), 2-m humidity (Q2), and PBL height (PBLH). We focus on calibrating SHPs and ISM (i.e., LSM states and fluxes) due to their inherent importance in LA interactions as well as uncertainty in current LSMs. The main questions this work

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Jian Zhang, Lin Tang, Stephen Cocks, Pengfei Zhang, Alexander Ryzhkov, Kenneth Howard, Carrie Langston, and Brian Kaney

1. Introduction High-resolution and high-accuracy quantitative precipitation estimation (QPE) is a key component for many applications in agriculture, manufacturing, flash flood detection, river flood prediction, water resource managements, and climate assessments. The observation of precipitation requires various remote sensing systems and networks encompassing surface rain/snow gauges, radar, and satellite. Among them, ground radar networks currently provide the highest spatial and temporal

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Terence J. Pagano, Duane E. Waliser, Bin Guan, Hengchun Ye, F. Martin Ralph, and Jinwon Kim

cell with the largest onshore IVT is designated as the landfall location of the AR object. An example of AR objects from the global AR detection algorithm for 0000 UTC 18 January 2012 is shown in Fig. 2a . Variables provided by the AR database and used in the current study include the AR’s shape, zonal and meridional IVT, and landfall location. Fig . 2. (a) Atmospheric river objects extracted from the Guan and Waliser (2015) detection algorithm at 0000 UTC on 18 Jan 2012. The red-outlined box

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He Sun, Fengge Su, Zhihua He, Tinghai Ou, Deliang Chen, Zhenhua Li, and Yanping Li

-elevation area in Asia centered on the Tibetan Plateau and the origin of major Asian rivers ( Fig. 1 ). Fig . 1. Topography and boundaries of nine upper river basins in the TP. UYE, UYA, UM, US, UB, UI, UAMD, USRD, and UYK denote the upper regions of the Yellow, Yangtze, Mekong, Salween, Brahmaputra, Indus, Amu Darya, Syr Darya, and Yarkant river basins, respectively. The green dots denote the national meteorological stations used in this study. Gridded datasets obtained by interpolating limited observations

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