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Youcun Qi and Jian Zhang

neighboring radars are at far ranges. To generate an accurate surface precipitation intensity estimation in a regional or national domain, the main goal of this study is to optimally merge radar observations with two considerations: mitigate nonprecipitation echoes’ impact, and mitigate/reduce the impacts of the observations from the melting layer and ice region. Multiple radars can scan different levels of the same storm structure at the given WSR-88D network density ( Fig. 2 ). To obtain the accurate

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F. Joseph Turk, Sarah E. Ringerud, Yalei You, Andrea Camplani, Daniele Casella, Giulia Panegrossi, Paolo Sanò, Ardeshir Ebtehaj, Clement Guilloteau, Nobuyuki Utsumi, Catherine Prigent, and Christa Peters-Lidard

dynamics, rather than atmospheric-related reasons (i.e., enhanced emission from the cloud liquid water and/or water vapor). It is therefore necessary to be able to account for the frozen background surface conditions at the time of the overpass in the snowfall retrieval process, rather than relying on the use of climatological microwave emissivity datasets ( Prigent et al. 2008 ), often used in conjunction with daily products for snow cover extent (and sea ice concentration) (as in GPROF, see section

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Vasubandhu Misra

from the climatological diurnal cycle. The observed SST is from the Met Office Hadley Center Sea Ice and Sea Surface Temperature dataset (HadISST; Rayner et al. 2002 ). 3. Results a. Precipitation In Fig. 1a the precipitation anomalies obtained from regressing the mean DJF TRMM precipitation on the contemporaneous-observed Niño-3 (5°N–5°S, 150°–90°W) SST index (normalized by its standard deviation) is shown. The distinct precipitation anomalies over the EA and the anomalies with opposite sign

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Emanuel Dutra, Pedro Viterbo, Pedro M. A. Miranda, and Gianpaolo Balsamo

the behavior of the newly developed snow scheme. A three-member 30-yr-long ensemble was carried out with each one of the snow schemes activated in EC-EARTH. The simulations were performed with prescribed sea surface temperature and sea ice cover from the ECMWF reanalysis. This simulation setup guarantees an identical coupling of the different snow schemes with the atmosphere and soil. The evaluation of the performance of the three snow schemes in EC-EARTH is performed by comparing the simulations

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Christoph Schär, Lyudmila Vasilina, Felix Pertziger, and Sébastien Dirren

1. Introduction and objectives The hydrology of central Asia is dominated by the Amudarya and Syrdarya rivers. These have their source regions in the Hindukush, Pamir, and the Tian Shan Mountains and flow across the Kyzylkum and Karakum Deserts to finally feed the Aral Sea more than 1000 km downstream (see Fig. 1 ). The economy and ecology of the central Asian region heavily relies on the two rivers, and the exploitation of this precious but limited resource has led to the dramatic dessication

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R. D. Koster and G. K. Walker

discussion provided in section 4 . 2. Framework for analysis a. Modeling system The Global Modeling and Assimilation Office of NASA GSFC hosts GEOS-5, a state-of-the-art Earth system model ( Molod et al. 2012 ). In its complete form, the GEOS-5 modeling system consists of coupled atmosphere, ocean, land, and sea ice models. When run with full data assimilation machinery, GEOS-5 has produced, among other things, a well-utilized climate reanalysis ( Rienecker et al. 2011 ). Data assimilation is also used

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Marika Koukoula, Efthymios I. Nikolopoulos, Jonilda Kushta, Nikolaos S. Bartsotas, George Kallos, and Emmanouil N. Anagnostou

during the spring. The nearby Mediterranean Sea acts as an energy and moisture source for the lower layers of the atmosphere, leading to frequent flood-inducing storm events in the region. Moreover, the complex terrain of the wider area surrounded by the Alps, Pyrenees, and Massif Central Mountains contributes to convection triggering and channels the low-level flows, enhancing convective instability. The average depth in the region does not exceed 55 cm ( Anquetin et al. 2009 ), and the average

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Yanhong Wu, Hongxing Zheng, Bing Zhang, Dongmei Chen, and Liping Lei

Sheet altimetry data V001. National Snow and Ice Data Center, Boulder, CO, digital media. [Available online at http://nsidc.org/data/icesat/data.html .] Zwally, H. J. , Yi D. , Kwok R. , and Zhao Y. , 2008 : ICESat measurements of sea ice freeboard and estimates of sea ice thickness in the Weddell Sea. J. Geophys. Res., 113, C02S15 , doi: 10.1029/2007JC004284 .

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Isidora Jankov, Lewis D. Grasso, Manajit Sengupta, Paul J. Neiman, Dusanka Zupanski, Milija Zupanski, Daniel Lindsey, Donald W. Hillger, Daniel L. Birkenheuer, Renate Brummer, and Huiling Yuan

properties of several new hydrometeor species: pristine ice, snow, aggregates, graupel, hail, and rainwater. All hydrometeor types were computed using two-moment microphysics except cloud liquid. Grasso and Greenwald (2004) reported on the performance of the expanded system for an idealized thunderstorm simulation. The same observational operator is exploited in the current study. The main goal of the present study is to assess the evaluation of the performance of a numerical model through the use of

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Jason P. Giovannettone and Ana P. Barros

as a “continental” orographic monsoon regime because of the affect of the large landmass that separates the mountains from the Bay of Bengal to the east and the Arabian Sea to the west ( Lang and Barros 2002 ). In Mexico, however, the mountains are aligned along the coast, with minimal land–atmosphere interactions with approaching air masses prior to reaching the mountains, and thus it can be described as a “maritime” orographic regime, in the sense that rainfall events are directly dependent on

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