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Xiaoyan Zhang, Jianping Huang, Gang Li, Yongwei Wang, Cheng Liu, Kaihui Zhao, Xinyu Tao, Xiao-Ming Hu, and Xuhui Lee

comparison of observed (WPR) and simulated vertical profiles of (a) wind speed and (b) wind direction at 1400 LST (0600 UTC) 12 Jun 2012. Several statistical parameters ( C r , MB, and RMSE) are calculated to evaluate the model performance at different stages of the lake-breeze evolution. The results show that C r is about 0.25 before 1000 LST, then increases to 0.73 during 1200–1700 LST, and finally decreases to approximately 0.45 in the following hours. Accordingly, MB (RMSE) decreases from 2.13 m s

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Diana L. Verseghy and Murray D. MacKay

thousands of small lakes that remain unresolved, and in some areas the fractional coverage of such lakes can exceed 40%. There has therefore been growing interest in investigating the effects of such lakes in climate models. In this paper, we present a study evaluating the performance of the recently developed Canadian Small Lake Model (CSLM), version 2 (MacKay et al. 2016, manuscript submitted to J. Hydrometeor. ), for the first time on a regional scale, and analyzing the effect of adding it in a

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Mehnaz Rashid, Rong-You Chien, Agnès Ducharne, Hyungjun Kim, Pat J.-F. Yeh, Christophe Peugeot, Aaron Boone, Xiaogang He, Luc Séguis, Yutaro Yabu, Moussa Boukari, and Min-Hui Lo

on evaluating the groundwater simulations in these ALMIP2 models in one of the ALMIP2 representative sites, the Donga River basin in northern Benin, where measurements of water table depth (WTD) and streamflow are available from 2005 to 2008 ( Kamagaté et al. 2007 ; Séguis et al. 2011 ; Hector et al. 2015 ). The arborescent stream network is well structured, and stream water is routed to the Atlantic. The rivers are mainly fed by subsurface flow, as well as the permanent water table, which does

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A. F. Stein, F. Ngan, R. R. Draxler, and T. Chai

the six CAPTEX atmospheric tracer releases. Although HYSPLIT has previously been applied in several case studies using different sets of initial conditions and internal model physical parameters to create concentration ensembles ( Draxler 2003 ; Stein et al. 2007 ; Chen et al. 2012 ), no attempt has ever been made to discard redundant ensemble members. In the present analysis, we first evaluate the statistical performance of each member of the ensemble and the full ensemble against the CAPTEX

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Kevin A. Reed, Brian Medeiros, Julio T. Bacmeister, and Peter H. Lauritzen

1. Introduction In an age of increasing computer power, so too comes the capability of routinely running atmospheric general circulation models (AGCMs) at increasingly high horizontal resolutions (i.e., grid spacing less than 50 km). Moving to such resolutions requires understanding, and likely improving, the performance of many components of these AGCMs, such as parameterizations of subgrid-scale physics and the interaction of physics and dynamics. Of particular interest is the role of

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Jian Sun and Guido D. Salvucci

stationarity case and the corresponding calibration case are generally small, with the difference of near 0.1 for LE and 0.2 for H , and the difference of RMSE around 3–4 W m −2 for both LE and H . These results indicate that the relatively poor performance is more likely due to model structure and/or data issues, rather than robustness issues of the stationarity-based method. 6. Discussion We use the error criterion, RMSE, as a general guideline for evaluating the model performance at each site

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Yetang Wang, Minghu Ding, J. M. van Wessem, E. Schlosser, S. Altnau, Michiel R. van den Broeke, Jan T. M. Lenaerts, Elizabeth R. Thomas, Elisabeth Isaksson, Jianhui Wang, and Weijun Sun

observations. Agosta et al. (2013) evaluated the multiyear averaged SMB of a downscaled SMB product using a quality-controlled and updated compilation of SMB field measurements ( Favier et al. 2013 ), but a temporal variability assessment is lacking. We conclude that it is still necessary to make a comprehensive comparison between observed and simulated SMB from recent reanalyses and regional atmospheric models. This will help to reduce the model uncertainty and to support future model development by

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Peter W. Henderson and Robert Pincus

factor, the model may be run at high spatial resolution. When CSRMs are used in global models, however, they are run at much lower resolution, and model performance at these resolutions is not a foregone conclusion. CSRMs used in global models are also subject to a much wider range of atmospheric conditions than are explored in most case studies, and evaluation of the CSRM should logically follow suit. What observations may be used to evaluate CSRMs over such a wide range of conditions? One

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Burkely T. Gallo, Jamie K. Wolff, Adam J. Clark, Israel Jirak, Lindsay R. Blank, Brett Roberts, Yunheng Wang, Chunxi Zhang, Ming Xue, Tim Supinie, Lucas Harris, Linjiong Zhou, and Curtis Alexander

that each verification metric will provide unique insight to the model performance, and that if one model performs better than the others do across all metrics tested herein, it is more likely to be perceived as useful by forecasters. CAMs often use postprocessing methods such as neighborhood-based techniques, since gridpoint-based statistics that use the contingency table may not reflect improvements evident in object-based methods or subjective evaluation due to small-scale displacements (see

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Youlong Xia, David M. Mocko, Shugong Wang, Ming Pan, Sujay V. Kumar, Christa D. Peters-Lidard, Helin Wei, Dagang Wang, and Michael B. Ek

performance is comparable to other NLDAS-2 models for all soil layers except for the top 10-cm soil layer where the VIC model has lower seasonal variability ( Xia et al. 2014 ). Overall, the VIC hydrologic model is a valuable member of the NLDAS model ensemble. Internally, the NLDAS team has over the past few years developed the NLDAS Science Testbed to evaluate the new LSMs—including various versions, model options/configurations, and parameters—against numerous available budget components and variables

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