Developing configuration of WRF model for long-term high-resolution wind wave hindcast over the North Atlantic with WAVEWATCH III Margarita Markina 1,2 & Alexander Gavrikov 1 & Sergey Gulev 1,2 & Bernard Barnier 1,3 Received: 11 April 2018 /Accepted: 12 August 2018 /Published online: 24 August 2018 # Springer-Verlag GmbH Germany, part of Springer Nature 2018 Abstract The spatial resolution of wind forcing fields is critical for modeling ocean surface waves. We analyze here the performance of the non-hydrostatic numerical weather prediction system WRF-ARW (Weather Research and Forecasting) run with a 14-km reso- lution for hindcasting wind waves in the North Atlantic. The regional atmospheric model was run in the domain from 20° N to 70° N in the North Atlantic and was forced with ERA-Interim reanalysis as initial and boundary conditions in a spectral nudging mode. Here, we present the analysis of the impact of spectral nudging formulation (cutoff wavelengths and depth through which full weighting from reanalysis data is applied) onto the performance of the modeled 10-m wind speed and wind wave fields for 1 year (2010). For modeling waves, we use the third-generation spectral wave model WAVEWATCH III. The sensitivity of the atmospheric and wave models to the spectral nudging formulation is investigated via the comparison with reanalysis and observational data. The results reveal strong and persistent agreement with reanalysis data during all seasons within the year with well-simulated annual cycle and regional patterns independently of the nudging parameters that were tested. Thus, the proposed formulation of the nudging provides a reliable framework for future long-term experiments aiming at hindcasting climate variability in the North Atlantic wave field. At the same time, dynamical downscaling allows for simulation of higher waves in coastal regions, specifically near the Greenland east coast likely due to a better representation of the mesoscale atmospheric dynamics in this area. Keywords Wind wave modeling . Wind wave hindcast . WAVEWATCH . WRF 1 Introduction Accurate knowledge of wind waves is important for many sci- entific and practical purposes, such as climate studies, ocean forecasting, naval architect, and operations of marine structures. Robust estimation of wind wave statistics requires long-term time series of wave parameters. Satellite records of wave characteristics cover now several decades (Zieger et al. 2009); however, these data still require continuous validation efforts (Young et al. 2017). Voluntary Observing Ship (VOS) records provide data for the longest period going back to the nineteenth century (e.g., Gulev and Grigorieva 2004, 2006). However, VOS data suffer from sampling biases and high observational errors (Gulev et al. 2003). In this respect, ocean wind wave modeling driven by high-resolution atmospheric forcing pro- vides a perspective framework for studying wave variability. Over the last decades, progress in numerical wave model- ing resulted in a number of global and regional model hindcasts widely used for the analysis of wave climate vari- ability and assessment of extreme wave statistics (Cox and Swail 2001; Caires and Sterl 2005; Chawla et al. 2013; Rascle and Ardhuin 2013; Guo and Sheng 2015). However, the accuracy of the wind wave hindcasts is mainly dependent on the reliability of forcing fields with the effect of the phys- ical parameterizations and the numerical schemes used to in- tegrate the wave energy balance equation being respectively moderate and minor (Bidlot et al. 2007; Ardhuin et al. 2010, This article is part of the Topical Collection on the 15th International Workshop on Wave Hindcasting and Forecasting in Liverpool, UK, September 10-15, 2017 Responsible Editor: Jenny M Brown * Margarita Markina markina@sail.msk.ru 1 Shirshov Institute of Oceanology, Russian Academy of Sciences, Moscow, Russia 2 Lomonosov Moscow State University, Moscow, Russia 3 LGGE, UMR 5183 CNRS-UGA, Grenoble, France Ocean Dynamics (2018) 68:1593–1604 https://doi.org/10.1007/s10236-018-1215-z