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Aseem R. Sharma and Stephen J. Déry

1. Introduction The area of British Columbia and southeastern Alaska (BCSAK) is affected by the prevailing westerlies commonly observed in the northern midlatitudes ( Hare 1998 ; Stahl et al. 2006 ). BCSAK experiences extreme runoff through different flood-generating mechanisms such as rapid spring snowmelt, rainstorms, rain-on-snow (ROS) events, and occasional ice jams ( Melone 1985 ; Buttle et al. 2016 ; Zahmatkesh et al. 2019 ). Moreover, the complex topography and sharp elevational

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M. Alves, D. F. Nadeau, B. Music, F. Anctil, and A. Parajuli

information at , accessed December 2019). The LSM divides the relatively thin layer of interface between the surface and atmosphere into fractions (tiles), with up to six fractions over land (bare ground, low and high canopy, shaded and exposed snow, and intercepted water) and up to two fractions over sea and freshwater, with separate energy and water budget calculation ( Balsamo et al. 2009 ). It is important to highlight that the

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

, in section 3b , apply our findings to the analysis of full subseasonal forecasts. We examine in particular a series of forecasts (actually a series of hindcasts) produced with the GMAO’s Subseasonal-to-Seasonal (S2S), version 2, prediction system ( Molod et al. 2020 ), which consists of a fully coupled ocean–atmosphere–land–sea ice model initialized through the application of a weakly coupled Atmosphere–Ocean Data Assimilation System. Two aspects of the land model component of the forecast

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Abhishekh Kumar Srivastava, Richard Grotjahn, Paul Aaron Ullrich, and Mojtaba Sadegh

credible climate projections than global climate models (GCMs) ( Giorgi et al. 2016 ; Gutowski et al. 2020 ). RCMs are physically based climate models representing complex components (land, ocean, sea ice) of the Earth system and their interactions at much finer spatial scale than conventional coarse-resolution GCMs. The higher resolution enabled by RCMs improves the representation of local forcings such as topography, coastlines, and complex land structure, as well as anthropogenic forcing such as

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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

–2014), and are prescribed with observed sea surface temperatures, sea-ice concentrations, and all volcanic, solar, and anthropogenic forcings, including atmospheric CO 2 concentrations ( Eyring et al. 2016b ). Our analysis focused on two models, the U.K. Hadley Centre Global Environment Model version 3 (HadGEM3), and the Brazilian Global Atmospheric Model version 1.2 (BAM-1.2), but we later compare these results with AMIP runs from nine additional CMIP6 models, where the necessary data were available

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Xiang Gao, Alexander Avramov, Eri Saikawa, and C. Adam Schlosser

water content within a diameter of a few hectometers (~660 m at sea level) and to a depth of a few decimeters ( Zreda et al. 2008 ), thereby averaging soil moisture heterogeneities. Satellite remote sensing, mostly by microwave sensors, can provide near-surface soil moisture of global coverage at coarse-scale, moderate temporal resolution. Currently several satellite missions provide global surface soil moisture products, including the Soil Moisture Active Passive (SMAP) ( Entekhabi et al. 2010a

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Nevenka Bulovic, Neil McIntyre, and Fiona Johnson

high-density monitoring network in the high-elevation tropical Andes of Peru. The monitoring network consists of 15 weather stations located between 3747 and 4591 m above mean sea level (MSL) in a single 0.1° × 0.1° IMERG grid, making it a gauge network of unprecedented density for this elevation range. The influence of precipitation attributes and auxiliary IMERG data sources/algorithms on performance are also explored to evaluate the sources of uncertainty and determine whether the GPM Core

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Shanshui Yuan, Laiyin Zhu, and Steven M. Quiring

cell (0.1° spatial resolution) and (b) cumulative distribution functions of gauge observation (blue), TMPA (red), regridded IMERG (yellow), and original IMERG (purple). Other theoretical reasons, such as extended microwave channels (up to 183 GHz) and more accurate reference data, may also improve the performance of IMERG on capturing TCP. For example, the newly added 89-GHz channel has been approved to better capture the ice scattering signals related to stratiform precipitation at inner core of

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Enrico Zorzetto and Laifang Li

the Pacific Northwest, where the moisture flux from the Atlantic Ocean can hardly reach. These counterintuitive results can be understood by taking into account the remote factors that impact the NASH western ridge movement. Studies have shown that the SW ridging involves air–sea interaction over the Gulf of Mexico ( Hu et al. 2011 ; L. Li et al. 2012 ; Ryu and Hayhoe 2014 ), while the NW ridge shows association with Pacific decadal oscillation (PDO; L. Li et al. 2012 ). With a positive phase

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Simon R. Osborne and Graham P. Weedon

5d(1) considers how observed and modeled soil moisture responds to rainfall after drought. The final results in section 5d(2) considers bare-soil evaporation after rainfall on to dry ground. 2. Field site and instrumentation The Met Office research site at Cardington (52.105°N, 0.424°E, 29 m above sea level) has been making continuous subsoil and near-surface meteorological observations since 1995. The 18-ha site is laid mainly to manicured grass kept at 5–10-cm height throughout the year

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