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Adam J. Clark, Michael C. Coniglio, Brice E. Coffer, Greg Thompson, Ming Xue, and Fanyou Kong

local MYJ and QNSE schemes produce PBLs that are generally too shallow and moist while the nonlocal ACM2 and YSU schemes produce PBLs that are too deep and dry. The best results were found for MYNN, which was nearly unbiased in PBL depth, moisture, and potential temperature, with forecasts comparable to those from the operational North American Mesoscale Forecast System (NAM; Rogers et al. 2009 ). Coniglio et al. (2013) conclude that these results give confidence in the use of MYNN over MYJ in

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Gregory R. Herman and Russ S. Schumacher

assimilation input in association with operational upgrades made in May 2012 ( Hamill et al. 2013 ); the NSSL-WRF has only one change of note: an update of the WRF version from 3.1.1 to 3.4.1 in April 2013. The long record of unchanged model data allows for a robust diagnosis of model performance characteristics. A broader comparison of several convection allowing models (CAMs) was conducted for 6-h AIs over the shorter 2014–15 period comparing the NSSL-WRF, the North American Mesoscale 4-km nest (NAM

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Joshua P. Hacker, E. Scott Krayenhoff, and Roland B. Stull

contributing to the failure of this forecast are 1) initial condition (IC) error, 2) model error for a particularly nonlinear or sensitive event, and 3) sympathetic data denial. Determining the possible contribution of each factor to the bust can help to evaluate the state of NWP in the North Pacific and western North America and possibly to indicate how much improvement may be gained by improving observation networks in the North Pacific “data void.” Short-range ensemble forecasting (SREF) techniques that

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Brian Etherton and Pablo Santos

analyses. In addition to evaluating the impact of the LAPS initialization on the WRF forecasts, comparisons of these forecasts to WRF forecasts initialized from the National Centers for Environmental Prediction (NCEP) North American Mesoscale model (NAM) and to forecasts from the NAM model are also presented. Intercomparisons of WRF forecasts using either NAM or LAPS for initial conditions were evaluated using 10-m winds, 2-m temperature, moisture information, and sea level pressure. Model performance

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Eric A. Aligo, William A. Gallus Jr., and Moti Segal

forecast spread in weakly forced and strongly forced events in an ensemble initialized with different soil moisture analyses by providing pertinent illustrative features and quantitative analyses. The impact of the uncertainties in the National Weather Service (NWS) Rapid Update Cycle (RUC), North American Model (NAM; formerly known as the Eta Model), and Global Forecasting System (GFS) soil moisture analyses on forecasted rainfall is also examined. As such, the paper provides an extension and

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Steven M. Lazarus, Samuel T. Wilson, Michael E. Splitt, and Gary A. Zarillo

improve (and may actually degrade) a highly tuned model (e.g., Cavaleri 2009 ). Regardless of these and other issues, it is reasonable to expect that a wave model should be driven with an accurate wind field. In Lazarus et al. (2013 , hereafter Part I ), the focus was on the evaluation of the TC wind analyses created from a combination of National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) North American Regional Reanalysis (NARR; Kalnay et al. 1996

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William A. Gallus Jr., Michael E. Baldwin, and Kimberly L. Elmore

accumulated precipitation interpolated to a 40-km grid from the National Centers for Environmental Prediction (NCEP) Eta [now referred to as the North American Mesoscale (NAM)] model ( Mesinger et al. 1988 ; Janjic 1994 ; Rogers et al. 2001 ) and Aviation [AVN, now referred to as the Global Forecast System (GFS)] models ( Global Climate and Weather Modeling Branch 2003 ) for a 1-yr period running from 1 September 2002 to 31 August 2003 is examined to determine the relationship between QPF amount and the

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Timothy Marchok, Robert Rogers, and Robert Tuleya

-total rainfall fields for Hurricane Isabel (2003) produced by four models [i.e., Geophysical Fluid Dynamics Laboratory (GFDL), Global Forecast System (GFS), North American Mesoscale (NAM), and R-CLIPER] that have varying resolutions and complexities, are compared with observations in Fig. 1 . All forecast and observed rainfall data in this figure have been interpolated onto a common 0.1° latitude–longitude grid. This case is highlighted here because the forecast track errors from the different model

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Kristin M. Calhoun, Travis M. Smith, Darrel M. Kingfield, Jidong Gao, and David J. Stensrud

). For this experiment, data from nearby WSR-88D and National Centers for Environmental Prediction (NCEP) North American Mesoscale (NAM) model 12-km-resolution numerical weather prediction products (used as a background field) were included in the analysis evaluated by forecasters in the HWT; a more detailed description of this system is provided by both Gao et al. (2013) and Smith et al. (2013) . Four separate moveable 200 km × 200 km 3DVAR domains with 1-km resolution were maintained throughout

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Derek R. Stratman, Michael C. Coniglio, Steven E. Koch, and Ming Xue

ensemble members for both years, two members of interest used the Advanced Research core of the WRF (WRF-ARW): one member directly used the 0000 UTC 12-km North American Mesoscale Model (NAM) analyses at the initial conditions and the other member used the three-dimensional variational data assimilation (3DVAR) cloud analysis ( Xue et al. 2003 ; Hu et al. 2006a , b ) initial conditions that assimilated radar and other high-resolution observations (from surface stations and wind profilers). The NAM

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