Here comes another challenges, the time is in Julian but the original date is in gregorian format. Looking on the metadata we spotted that the original date for the calender was assigned as julian_day_unit: days since 00:00:00. We can transform this days into the calender once we know the original date that AVISO used. However, in the metadata provide information of the beginning data that we can use to transform this julian day into gregorian calendar that we are familiar with. Printing the time we realized that time is the julian days but we do know the starting of the date. Once we have the file in the console, we are ready to extract the vector and array from the file. Ssh = nc_open("E:/MatlabWorking/Altimetry/old staff/wio_ssh_july_2015.nc") uv = nc_open("E:/MatlabWorking/Altimetry/old staff/wio_geostrophic_uv_july_2015.nc") Once we have identified the variables contained in the netCDF file, we use the nc_open() function to read the the file and assign it with uv name. I prefer the ncdf4 packages because it provide tools and functions to access the netCDF files (Pierce, 2017). There are several packages in CRAN that read and write netCDF files. This dataset provides gridded values of zonal (u) and meridional (v) velocity component. We will use the geostrophic current and sea surface height dataset from AVISO.
Second, I will illustrate how to extract the data and Last, we sill finish with the transformation of the data and organize them as data frames. First, I will show you how to read the metadata contained in the netCDF file, explore the data stored in it and glimpse their internal structures. I have divided this post into three main steps. In this post I will take you through the process of converting a netcdf files into a tabular form widely known as data frame.
This post aimed to extend the approach and overcome the challenges inherited in the previous post. This inability end up obtain a data frame from the of the first matrice of an array dropping out other matrix. One main setback of this approach is its inability to read maltiple matrix in an array from a netcdf file. The approach is simple and straight forward but there flaws in this approach. In the previously post, I covered how to read and convert netCDF files directly into R and convert to data frames.
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