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Elizabeth M. Douglass and Andrea C. Mask

1. Introduction and background With the advancement of ocean modeling and the proliferation of high-resolution models comes a need for standardized methods of evaluating model output and determining its accuracy. Metrics such as mean error, root-mean-square error, normalized bias, or normalized standard deviation present an objective test of whether a model is accurately representing observations (e.g., Kara and Hurlburt 2006 ; Stopa and Cheung 2014 ). These metrics measure the variability

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Myrto Valari and Laurent Menut

ozone plumes depending on model configuration. We compare model performance with regard to [O 3 ] at each configuration and evaluate the gain associated with the use of a finer resolution (i.e., additional features of ozone chemistry and transport being captured). A zoom to selected sites is then done and we study the temporal evolution of model results at different resolutions. We also discuss how each model configuration triggers air pollution alarms. a. Surface maps of ozone concentration As the

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Chih-Chiang Wei

classification trees (C4.5 and RF) and regression trees (RF). To create categorical-type target labels, the dataset {R} is partitioned into several intervals using C4.5 and RF algorithms ( section 3b ). Step 3: Classify the datasets into training and testing subsets ( section 3b ). The training subset is used to build model structures and parameters, followed by the testing subset that evaluates the performance of the model to verify its generalizability. Step 4: Design the climate scenarios. Scenario 1 uses

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S. Lim, V. Chandrasekar, P. Lee, and A. P. Jayasumana

searching mechanism for integrating data and a multiprocess coordinate mechanism to exploit parallel processing for the computationally intensive reflectivity retrieval algorithm. This paper presents the real-time performance metrics as well as the attenuation correction capability of the NBRR using CASA Integrated Project 1 (IP1) data during 2007–09 field experiments. To evaluate the real-time performance for NBRR, the execution run times are measured and compared with radar data generation time. The

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David Antoine, Pierre Guevel, Jean-François Desté, Guislain Bécu, Francis Louis, Alec J. Scott, and Philippe Bardey

.1175/1520-0426(2000)017<0708:AANASI>2.0.CO;2 Gregg, W. , 2007 : Ocean-colour data merging. Rep. Int. Ocean Color Coordinating Group 6, IOCCG, Dartmouth, Canada, 68 pp . Gregg, W. , and Carder K. L. , 1990 : A simple spectral solar irradiance model for cloudless maritime atmospheres. Limnol. Oceanogr. , 35 , 1657 – 1675 . 10.4319/lo.1990.35.8.1657 Hellan, Ø , Leira B. , Barrholm R. , Erling Heggelund S. , and Lie H. , 2002 : Expert evaluation of Boussole buoy design. Marintek Rep. 700203.00:01, Trondheim

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W. Erick Rogers, Alexander V. Babanin, and David W. Wang

continue—albeit much more slowly—after the spectral density has dropped below the breaking threshold. The new physics implementation is calibrated in section 3 using single-point model (duration limited) simulations with older, well-known models used as a baseline, as opposed to standard fetch-limited growth curve analysis. Four possible variants of the new dissipation source function are calibrated in this manner. The observation-consistent dissipation term is then evaluated in section 4 by

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Robin Tokmakian, Peter Challenor, and Yiannis Andrianakis

does not have to be differentiable, but the outcome at an input point has to be informative about the outcome at a nearby input location. A step in the outcome clearly violates this assumption but can be addressed in a carefully designed experiment. This paper gives two examples of the use of the emulator methodology and how to evaluate its quality. After first describing the methodology, we present the results of the first example, the Stommel model, in section 3 along with a description of the

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Brian K. Blaylock, John D. Horel, and Chris Galli

, including aviation, solar and wind energy, agriculture, severe weather forecasting, and wildland fire management. As described by Blaylock et al. (2017a) , HRRR model datasets are retained and accessible for 48 h from servers at the National Centers for Environmental Prediction and not presently archived by the National Centers for Environmental Information. We began archiving operational HRRR output in April 2015 on the Pando archive system at the University of Utah's Center for High Performance

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Brett T. Hoover and Chris S. Velden

form have been used in other studies investigating the adjoint-derived sensitivity of the forecast intensity of tropical storms ( Hoover 2015 ) and midlatitude cyclones ( Ancell and Mass 2006 ; Chu and Yi 2016 ) to the model initial state, while other studies have used response functions defined by summed three-dimensional volumes of kinetic energy ( Doyle et al. 2012 ) or vorticity ( Vukićević and Raeder 1995 ; Langland and Errico 1996 ) evaluated in a box centered on the cyclone extending from

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Lucy M. Bricheno, Albert Soret, Judith Wolf, Oriol Jorba, and Jose Maria Baldasano

Liverpool Bay. Section 5 assesses the performance of the ocean model, evaluating wave conditions and coastal surge elevations. The main findings are discussed in section 6 with suggestions for future work in section 7 . Finally, the work is summarized in section 8 . 2. Methods Three well-established models have been used: an ocean basin–scale spectral wave model, which has been coupled with a 3D tide and surge model, POLCOMS ( Osuna and Wolf 2005 ). For the atmospheric modeling, a version of the

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