Articles | Volume 13, issue 3
Development and technical paper
10 Mar 2020
Development and technical paper |  | 10 Mar 2020

Mitigation of model bias influences on wave data assimilation with multiple assimilation systems using WaveWatch III v5.16 and SWAN v41.20

Jiangyu Li and Shaoqing Zhang

Related authors

Frequent haze events associated with transport and stagnation over the corridor between the North China Plain and Yangtze River Delta
Feifan Yan, Hang Su, Yafang Cheng, Rujin Huang, Hong Liao, Ting Yang, Yuanyuan Zhu, Shaoqing Zhang, Lifang Sheng, Wenbin Kou, Xinran Zeng, Shengnan Xiang, Xiaohong Yao, Huiwang Gao, and Yang Gao
Atmos. Chem. Phys., 24, 2365–2376,,, 2024
Short summary
A Deep Learning-Based Consistency Test Approach for Earth System Models on Heterogeneous Many-Core Systems
Yangyang Yu, Shaoqing Zhang, Haohuan Fu, Dexun Chen, Yang Gao, Xiaopei Lin, Zhao Liu, and Xiaojing Lv
Geosci. Model Dev. Discuss.,,, 2024
Preprint under review for GMD
Short summary
Design and evaluation of an efficient high-precision ocean surface wave model with a multiscale grid system (MSG_Wav1.0)
Jiangyu Li, Shaoqing Zhang, Qingxiang Liu, Xiaolin Yu, and Zhiwei Zhang
Geosci. Model Dev., 16, 6393–6412,,, 2023
Short summary
Substantially positive contributions of new particle formation to cloud condensation nuclei under low supersaturation in China based on numerical model improvements
Chupeng Zhang, Shangfei Hai, Yang Gao, Yuhang Wang, Shaoqing Zhang, Lifang Sheng, Bin Zhao, Shuxiao Wang, Jingkun Jiang, Xin Huang, Xiaojing Shen, Junying Sun, Aura Lupascu, Manish Shrivastava, Jerome D. Fast, Wenxuan Cheng, Xiuwen Guo, Ming Chu, Nan Ma, Juan Hong, Qiaoqiao Wang, Xiaohong Yao, and Huiwang Gao
Atmos. Chem. Phys., 23, 10713–10730,,, 2023
Short summary
Monthly-scale extended predictions using the atmospheric model coupled with a slab ocean
Zhenming Wang, Shaoqing Zhang, Yishuai Jin, Yinglai Jia, Yangyang Yu, Yang Gao, Xiaolin Yu, Mingkui Li, Xiaopei Lin, and Lixin Wu
Geosci. Model Dev., 16, 705–717,,, 2023
Short summary

Related subject area

Intercomparisons of Tracker v1.1 and four other ocean particle-tracking software packages in the Regional Ocean Modeling System
Jilian Xiong and Parker MacCready
Geosci. Model Dev., 17, 3341–3356,,, 2024
Short summary
CAR36, a regional high-resolution ocean forecasting system for improving drift and beaching of Sargassum in the Caribbean archipelago
Sylvain Cailleau, Laurent Bessières, Léonel Chiendje, Flavie Dubost, Guillaume Reffray, Jean-Michel Lellouche, Simon van Gennip, Charly Régnier, Marie Drevillon, Marc Tressol, Matthieu Clavier, Julien Temple-Boyer, and Léo Berline
Geosci. Model Dev., 17, 3157–3173,,, 2024
Short summary
Implementation of additional spectral wave field exchanges in a three-dimensional wave–current coupled WAVEWATCH-III (version 6.07) and CROCO (version 1.2) configuration: assessment of their implications for macro-tidal coastal hydrodynamics
Gaetano Porcile, Anne-Claire Bennis, Martial Boutet, Sophie Le Bot, Franck Dumas, and Swen Jullien
Geosci. Model Dev., 17, 2829–2853,,, 2024
Short summary
Comparison of 4-dimensional variational and ensemble optimal interpolation data assimilation systems using a Regional Ocean Modeling System (v3.4) configuration of the eddy-dominated East Australian Current system
Colette Gabrielle Kerry, Moninya Roughan, Shane Keating, David Gwyther, Gary Brassington, Adil Siripatana, and Joao Marcos A. C. Souza
Geosci. Model Dev., 17, 2359–2386,,, 2024
Short summary
LOCATE v1.0: numerical modelling of floating marine debris dispersion in coastal regions using Parcels v2.4.2
Ivan Hernandez, Leidy M. Castro-Rosero, Manuel Espino, and Jose M. Alsina Torrent
Geosci. Model Dev., 17, 2221–2245,,, 2024
Short summary

Cited articles

Abdalla, S., Bidlot, J., and Janssen, P.: Assimilation of ERS and ENVISAT wave data at ECMWF, Envisat & Ers Symposium,, p. 572, 2013. 
Almeida, S., Rusu, L., and Guedes Soares, C.: Data assimilation with the ensemble Kalman filter in a high-resolution wave forecasting model for coastal areas, J. Operational Oceanogr., 9, 103–114, 2016. 
Anderson, J. L.: An Ensemble Adjustment Kalman Filter for Data Assimilation, Mon. Weather Rev., 129, 2884–2903, 2001. 
Babanin, A. V., Ganopolski, A., and Phillips, W. R. C.: Wave-induced upper-ocean mixing in a climate model of intermediate complexity, Ocean Model., 29, 189–197, 2009. 
Bauer, E., Hasselmann, K., Young, I. R., and Hasselmann, S.: Assimilation of wave data into the wave model WAM using an impulse response function method, J. Geophys. Res., 101, 3801–3816, 1996. 
Short summary
Two assimilation systems developed using two nearly independent wave models are used to study the influences of various error sources including mode bias on wave data assimilation; a statistical method is explored to make full use of the merits of individual assimilation systems for bias correction, thus improving wave analysis greatly. This study opens a door to further our understanding of physical processes in waves and associated air–sea interactions for improving wave modeling.