Processed model data for "Cross-shelf Penetrating Fronts in the East China Sea in Summer"

Published: 16 June 2022| Version 1 | DOI: 10.17632/s3c72592bc.1
Contributors:
Zhiwei He,
Dezhou Yang

Description

This dataset is the processed model data for "Cross-shelf Penetrating Fronts in the East China Sea in Summer". The article is intended to submit to JGR: Ocean. The data is the output from a data assimilative model using ROMS 4D-Var. Details of the data assimilative model are shown in He et al. (2022). As the original data accout for too much strorage space, this dataset stores the daily averaged subtidal data. The processed data are in matlab format. Each file contains all variable in a month. The variable "DayNum" represents the time in the format of "days since January 0, 0000". The date can be obtained by the matlab "datestr" function. The grid information is saved in a matlab structure. See the "get_roms_grid" function in the ROMS matlab tools for details. Reference: He, Z., Yang, D., Wang, Y., & Yin, B. (2022). Impact of 4D-Var data assimilation on modelling of the East China Sea dynamics. Ocean Modelling, 102044. doi: https://doi.org/10.1016/j.ocemod.2022.102044

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Steps to reproduce

Details of the data assimilative model are shown in He et al. (2022) He, Z., Yang, D., Wang, Y., & Yin, B. (2022). Impact of 4D-Var data assimilation on modelling of the East China Sea dynamics. Ocean Modelling, 102044. doi: https://doi.org/10.1016/j.ocemod.2022.102044 To get subtidal variability, the model output was first filtered with a 36-h low-pass filter. Then the filtered data were daily-averaged to get the final data.

Institutions

Institute of Oceanology Chinese Academy of Sciences

Categories

Oceanographic Modeling

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