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Erin Dougherty, Erin Sherman, and Kristen L. Rasmussen

found that floods and debris flow were associated with ARs during the cool season in Northern California and flash floods not associated with ARs during the warm season in Southern California. Along the West Coast, the top 11 out of 20 counties with the highest proportion of flood damage due to ARs are located in California ( Corringham et al. 2019 ). Given the impact ARs have on California’s precipitation, floods, and water resources, current research has investigated how ARs might change in a

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E. Kerkhoven and T. Y. Gan

model (adapted from Neilson 1995 ). Although the MAPSS water budget model includes most of the processes used in current SVAT schemes, it has some limitations. The process formulations are conceptual and are therefore reliant on calibration. Unlike current SVATs such as the Interaction Soil–Biosphere–Atmosphere (ISBA) of Noilhan and Planton (1989) , modified ISBA (MISBA) of Kerkhoven and Gan (2006) , and others, the water budget model of MAPSS does not calculate an energy budget. Finally, even

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David T. Bolvin, George J. Huffman, Eric J. Nelkin, and Jackson Tan

satellite–gauge estimate. The IMERG V06B record currently covers the period from June 2000 to (delayed) present using the TRMM and GPM core satellites over their respective periods to calibrate the PMW precipitation estimates from the constellation of available partner satellites. The goal is to maintain a homogeneous precipitation record despite changes in the partner satellite constellation over time, as well as the change in the calibration satellite from TRMM to GPM in 2014. Despite the best effort

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Kian Abbasnezhadi, Alain N. Rousseau, Étienne Foulon, and Stéphane Savary

Lannoy et al. 2012 ; Durand and Margulis 2008 ; Huang et al. 2017 ; Magnusson et al. 2014 ; Piazzi et al. 2018 ; Slater and Clark 2006 ; Su et al. 2008 ). Currently, to gain a proper insight into short-term, seasonal, and long-term flow forecasting in northern and midcordilleran alpine, subalpine, and boreal watersheds in Yukon, where the flow regime is dominated by snowpack melt, and also to alleviate the adverse effects of scarce precipitation datasets, two independent DA routines are

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Sho Kawazoe and William J. Gutowski Jr.

Physics Regional Climate Model version 3 (RegCM3; RCM3 in the archive), and the Experimental Climate Prediction Center's Regional Spectral Model (ECP2 in the archive). All models used approximately 0.5° horizontal resolution. Atmospheric boundary conditions, sea surface temperatures (SSTs), and ocean ice fractions came from the reanalysis ( Kanamitsu et al. 2002 ) produced by the National Centers for Environmental Prediction (NCEP) and the U.S. Department of Energy (DOE). Except for the northern side

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Yuning Shi, Kenneth J. Davis, Christopher J. Duffy, and Xuan Yu

processes are critical in the growth of the atmospheric boundary layer (ABL), the formation of clouds and precipitation, and the budgets of heat, momentum, and moisture within the atmosphere. Weather and climate models currently rely on land surface models (LSMs) to represent land surface processes. LSMs provide lower boundary conditions and initialize ground states for numerical weather prediction ( Ookouchi et al. 1984 ; Liang et al. 1994 ; Betts et al. 1997 ; F. Chen et al. 1997 ; Xiu and Pleim

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Jamie Dyer and Andrew Mercer

1. Introduction Substantial soil and vegetation contrasts exist within the lower Mississippi River alluvial valley (LMRAV) because of extensive deforestation before 1940 ( Fig. 1 ; MacDonald et al. 1979 ), and these regional soil and vegetation boundaries have been shown to influence local rainfall and temperature patterns through modification of the sensible and latent heat fluxes ( Dyer 2011 ; Brown and Wax 2007 ; Raymond et al. 1994 ). This influence has been noted in other areas at

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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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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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