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Processing fvcom files

process-fvcom.Rmd

In this article we will demonstrate how to extract data from fvcom .nc files using similar functions to those for general .nc/.nc4 files.

Alternative Packages

Before we demonstrate the functionality available here, we would like to make it clear that we have not built a package to deal with all possible aspects of an fvcom file. If you are looking for additional functionality then we would recommend one of the following packages:

Extracting Data from fvcom files

For the purpose of this example, we have collected the url for a fvcom file and stored it in a separate .txt file and so we can load the required packages, along with collecting the file to be read in.

library(tidyverse)
library(satpoint)
fvcom_file <- read_lines("fvcom_links.txt")

fvcom files have data constructed on a triangular mesh and the stored variables are either provided in terms of the nodes that form the bounds of each triangle or the centroid of triangle. In the fvcom file these are denoted by the node and nele dimensions respectively.

Within this package we have only built functionality to extract the variables associated with the nodes. To see which variables are available and whether they are recorded at the node or nele level, we can use

nc_obj <- ncdf4::nc_open(fvcom_file)
## Error in R_nc4_open: NetCDF: file not found
## Error in ncdf4::nc_open(fvcom_file): Error in nc_open trying to open file https://thredds.sams.ac.uk/thredds/dodsC/scoats-westcoms2/Archive/netcdf_2020/westcoms2_20200101_0001.nc (return_on_error= FALSE )
collect_variables(nc_obj, nodes = TRUE)
## Error: object 'nc_obj' not found

To extract the variable values themselves, we can choose one of the variables above that are recorded at the node level and run

extract_nodes_fvcom(nc_obj, nc_var_name = "precip")
## Error: object 'nc_obj' not found

Summarising the values across buffers

If we want to extract the data over specific areas, as we did in the vignette("satpoint", package = "satpoint") vignette, we first need to construct the buffers. Taking the same sites as before:

sites <- tibble(
  site = LETTERS[1:4],
  longitude = c(-5.837704, -6.592514, -7.885055, -3.421410),
  latitude = c(57.607846, 57.291280, 56.900022, 58.187849)
)
sites
## # A tibble: 4 × 3
##   site  longitude latitude
##   <chr>     <dbl>    <dbl>
## 1 A         -5.84     57.6
## 2 B         -6.59     57.3
## 3 C         -7.89     56.9
## 4 D         -3.42     58.2

We can create buffers but as the fvcom file is stored at a smaller scale, we want the buffers to be smaller.

buffers <- site_buffers(sites, x_coord = "longitude", y_coord = "latitude", 
                        crs = 4326, buffers = c(2))
buffers
## Simple feature collection with 4 features and 1 field
## Geometry type: POLYGON
## Dimension:     XY
## Bounding box:  xmin: -7.918481 ymin: 56.88169 xmax: -3.386795 ymax: 58.20619
## Geodetic CRS:  WGS 84
## # A tibble: 4 × 2
##   site                                                                       geometry
##   <chr>                                                                 <POLYGON [°]>
## 1 A_2   ((-5.866424 57.59847, -5.866384 57.5983, -5.866304 57.59795, -5.865805 57.59…
## 2 B_2   ((-6.615266 57.27812, -6.615221 57.27795, -6.614972 57.27796, -6.614927 57.2…
## 3 C_2   ((-7.907938 56.88706, -7.907885 56.88689, -7.907636 56.88691, -7.907583 56.8…
## 4 D_2   ((-3.446063 58.17525, -3.445816 58.17525, -3.445792 58.17508, -3.445545 58.1…

We can now extract the data from our fvcom file and average the values across the buffers

extract_site_grids_fvcom(fvcom_file, sites = buffers, 
                         nc_crs = 4326, nc_var_name = "precip")
## Error in R_nc4_open: NetCDF: file not found
## Error in ncdf4::nc_open(nc_file): Error in nc_open trying to open file https://thredds.sams.ac.uk/thredds/dodsC/scoats-westcoms2/Archive/netcdf_2020/westcoms2_20200101_0001.nc (return_on_error= FALSE )