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Alejandro Hermoso, Victor Homar, and Arnau Amengual

influence of SST on the thermodynamic environment and moisture availability, a set of experiments with a uniform change in SST is designed. Experiment labeled as SST − 1 features a sea surface temperature 1°C lower than the analysis used in CNTL from ECMWF. This SST analysis field is taken from the global, high-resolution, operational sea surface temperature and sea ice analysis system (OSTIA; Stark et al. 2007 ; Mogensen et al. 2012 ). Analogously, a positive perturbation is introduced in the SST + 1

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Kalimur Rahman and Firat Y. Testik

black-ice formation, power outages due to power lines broken by the added ice weight, airflow alteration in the aircraft wings due to the added ice load, which eventually increases drag and alters the aerodynamic lift, damages to the aircraft engines due to break off of the icicle formations (e.g., Symons and Perry 1997 ; Rauber et al. 2000 ; Jung et al. 2012 ). Similarly, aircraft ground-based deicing fluids may have functional issues due to the presence of frozen raindrops (FAA Notice N 8000

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Chris Kidd, Erin Dawkins, and George Huffman

type, and mean elevation above mean sea level. The model includes both convective and stratiform precipitation via parameterization; convective precipitation forms within an updraft if the amount of condensate exceeds the amount that can be sustained by the upward velocity. If this condensate is at or above 0°C, it is defined as being water. If at a lower temperature, it is defined as snow or a mixture of snow and ice. The convection schemes calculate the vertical transport of moisture and momentum

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Nasrin Nasrollahi, Kuolin Hsu, and Soroosh Sorooshian

Column algorithm ( Haynes 2011 ) provides information about the presence of surface precipitation. The determination of surface precipitation occurrence is based on the radar reflectivity data near the surface and the surface reflection characteristics (i.e., the Precip_flag variable in the Precipitation Column dataset). The Precip_flag is available over land, ocean, and sea ice and categorizes precipitation into nine different groups: no precipitation, uncertain, rain possible, rain probable, rain

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A. Senatore, S. Davolio, L. Furnari, and G. Mendicino

representation, both ERA-Interim and ERA5 rely on the Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) product ( Stark et al. 2007 ). Therefore, the mean SST values are very similar. Focusing on the innermost domains of both mesoscale models, average SST values for the ERA5 and ERA-Interim fields providing initial conditions are within 0.1°C for all the three analyzed events. On the contrary, the Medspiration SST product shows some noteworthy variations. Specifically, in the innermost domains

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Anil Kumar, Robert A. Houze Jr., Kristen L. Rasmussen, and Christa Peters-Lidard

for this storm. They arrived at a conceptual model of the storm in which cells generated by diurnal heating over the high terrain of the Tibetan Plateau gathered into a mesoscale convective system (MCS), which the 500-hPa winds then steered over the bank of the Plateau such that the storm could then draw upon low-level moisture arriving from the Arabian Sea and Bay of Bengal. They hypothesized that the ingestion of this moisture then energized the MCS just as it was passing over Leh and thus

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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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Rasool Porhemmat, Heather Purdie, Peyman Zawar-Reza, Christian Zammit, and Tim Kerr

prediction models to produce atmospheric reanalysis data ( Lavers et al. 2012 ). ERA-Interim data were retrieved at 6-hourly temporal resolution and 0.5° × 0.5° spatial resolution for a geographic window spanning of 10°–60°S and 130°E–160°W (see Fig. 1b ). The data used in this study include sea level pressure (SLP; hPa), geopotential height at 500 hPa (Z500; m), temperature ( T ; °C), specific humidity ( q ; g kg −1 ), specific cloud ice water content (g kg −1 ), zonal and meridional wind fields ( u

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Rui Mei, Guiling Wang, and Huanghe Gu

-Emanuel scheme ( Emanuel 1991 ); and the land surface process described by the Biosphere–Atmosphere Transfer Scheme (BATS; Dickinson et al. 1993 ). RegCM4 differs from RegCM3 with the following major improvements: a prognostic SST scheme ( Zeng and Beljaars 2005 ) was implemented to improve the calculation of diurnal fluxes over the ocean, sea ice was introduced in SST boundary conditions, aerosol and dust models were improved following Laurent et al. (2008) and Alfaro and Gomes (2001) , and Community

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Klaus Vormoor and Thomas Skaugen

because of the coarse spatial resolution of the model. Temperature in a HIRLAM grid cell depends on its most dominant land cover type (water, ice, bedrock, low vegetation, or wood). Furuneset is physically located on a peninsula in the North Sea. The HIRLAM grid cell that covers Furuneset, however, is probably characterized by dominating bedrock and low vegetation cover, which would lead to an overestimation of continentality. The tendency to underestimate low temperatures and overestimate high

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