extract3Ddata_netCDF

R functions to extract environmental values from 2D and 3D netCDF files to point-based observations, supporting surface, bottom, nearest-depth and combined extraction workflows.

Features

• Extract values from:

  • 2D netCDF variables
  • 3D netCDF variables
  • 4D netCDF variables including time

• Extraction methods:

  • Surface layer
  • Bottom available layer
  • Nearest valid depth layer
  • Combined extraction

• Supports:

  • Single netCDF files
  • Multiple netCDF files
  • Lists of netCDF files
  • Opened ncdf4 objects
  • Data frames containing file paths

• Automatically:

  • Detects dimension names
  • Handles different longitude conventions
  • Reads netCDF time metadata
  • Matches nearest spatial and temporal cells
  • Detects variables automatically when var = NULL

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Main functions

Function	Description
extract2d()	Extract values from 2D netCDF variables
extract3d_surface()	Extract the surface layer
extract3d_bottom()	Extract the deepest valid layer
extract3d_nearest()	Extract the nearest valid depth layer
extract3d_all()	Extract combined surface, nearest and bottom values
extract_netcdf()	General extraction interface

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Installation

Currently under development.

Clone the repository:

git clone https://github.com/your_username/extractNetCDF.git

Or source the functions directly:

source("extract_netcdf_package.R")

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Dependencies

ncdf4

Optional:

dplyr

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Important notes

Nearest-depth extraction

extract3d_nearest() extracts the closest valid non-missing depth layer available in the vertical profile.

This behaviour is important in oceanographic products where some depth layers may be missing due to bathymetry.

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Bottom extraction

extract3d_bottom() extracts the deepest non-missing value available in the profile rather than simply the deepest nominal depth layer.

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Automatic variable detection

If var = NULL, the package automatically detects the variable stored in the netCDF file.

This works when the file contains a single environmental variable.

If a netCDF file contains several variables, the user must specify var manually.

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Input requirements

Observation tables should contain at minimum:

Column	Required
Longitude	Yes
Latitude	Yes
Date	Only if netCDF contains time
Depth	Only for nearest-depth extraction

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Supported netCDF inputs

The nc argument accepts:

# One file
nc = "file.nc"

# Several files
nc = c("file1.nc", "file2.nc")

# List of files
nc = list("file1.nc", "file2.nc")

# Opened ncdf4 object
nc = ncdf4::nc_open("file.nc")

# List of opened objects
nc = list(nc1, nc2)

# Data frame with file column
nc = data.frame(file = c("file1.nc", "file2.nc"))

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Future developments

Potential future extensions include:

• Parallel extraction
• Polygon-based extraction
• Interpolation methods

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Author

David Ruiz García

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License

MIT License