read.argo is used to read an Argo file, producing an argo object. The file must be in the ARGO-style NetCDF format described in the Argo documentation (see references 2 and 3).

read.argo(file, debug = getOption("oceDebug"), processingLog, ...)



A character string giving the name of the file to load.


A flag that turns on debugging. Set to 1 to get a moderate amount of debugging information, or to 2 to get more.


If provided, the action item to be stored in the log. (Typically only provided for internal calls; the default that it provides is better for normal calls by a user.)


additional arguments, passed to called routines.


An argo object.


Items are extracted from the data file using ncdf4::ncvar_get(), after which one-column matrices are converted to vectors, and leading and trailing blank space in character values is removed using trimString().

See the Argo documentation (see references 2 and 3) for some details on what files contain. Many items listed in section 2.2.3 of reference 3 are read from the file and stored in the metadata slot, with the exception of longitude and latitude, which are stored in the data slot, alongside hydrographic information.

The following global attributes stored within the netcdf file are stored in the metadata slot: title, institution, source, history, references, userManualVersion, conventions, and featureType. These names are derived from those in the netcdf file, as explained in the “Variable renaming convention” section below.

It is assumed that the profile data are as listed in the NetCDF variable called STATION_PARAMETERS. Each item can have variants, as described in Sections 2.3.4 of reference 3. For example, if "PRES" is found in STATION_PARAMETERS, then PRES (pressure) data are sought in the file, along with PRES_QC, PRES_ADJUSTED, PRES_ADJUSTED_QC, and PRES_ERROR. The same pattern works for other profile data. The variables are stored with names created as explained in the “Variable renaming convention” section below. Note that flags, which are stored variables ending in "_QC" in the netcdf fil, are stored in the flags item within the metadata slot of the returned object; thus, for example, PRES_QC is stored as pressure in flags.

Variable renaming convention

Argo netcdf files employ a "SNAKE_CASE" naming scheme (sometimes using lower case) that is inconsistent with the "camelCase" scheme used in oce. Since argo objects are just a small part of oce, a decision was made to rename argo items. For example, "CYCLE_NUMBER" in the netcdf file becomes "cycleNumber" in the oce object returned by read.argo. The conversion for objects in the data slot often also involves expanding on argo abbreviations, e.g. "PSAL" becomes "salinity". The renaming work is carried out with argoNames2oceNames() for handles both name expansion for several dozen special cases, and with snakeToCamel() with the specialCase argument set to "QC". While this results in variable names that should make sense in the general oce context (where, for example, salinity is expected to be stored in a variable named "salinity"), it may be confusing to argo experts who are just starting to use oce. Such people might find it helpful to use e.g. sort(names(x[["metadata"]])) to get a list of all items in the metadata slot (or similar with "data"), since working in reverse may be easier than simply guessing at what names oce has chosen. (Note that prior to 2020 June 24, some metadata items were stored in "SNAKE_CASE".)

Data sources

Argo data are made available at several websites. A bit of detective work can be required to track down the data.

Some servers provide data for floats that surfaced in a given ocean on a given day, the anonymous FTP server being an example.

Other servers provide data on a per-float basis. A complicating factor is that these data tend to be categorized by "dac" (data archiving centre), which makes it difficult to find a particular float. For example, is the top level of a such a repository. If the ID of a float is known but not the "dac", then a first step is to download the text file and search for the ID. The first few lines of that file are header, and after that the format is simple, with columns separated by slash (/). The dac is in the first such column and the float ID in the second. A simple search will reveal the dac. For example data(argo) is based on float 6900388, and the line containing that token is bodc/6900388/,846,BO,20120225005617, from which the dac is seen to be the British Oceanographic Data Centre (bodc). Armed with that information, visit and see a directory called profiles that contains a NetCDF file for each profile the float made. These can be read with read.argo. It is also possible, and probably more common, to read a NetCDF file containing all the profiles together and for that purpose the file should be downloaded and provided as the file argument to read.argo. This can be automated as in Example 2, although readers are cautioned that URL structures tend to change over time.

Similar steps can be followed on other servers.



  2. Argo User's Manual Version 3.3, Nov 89th, 2019, available at

  3. User's Manual (ar-um-02-01) 13 July 2010, available at, which is the main document describing argo data.

See also

The documentation for the argo class explains the structure of argo objects, and also outlines the other functions dealing with them.

Other things related to argo data: [[,argo-method, [[<-,argo-method, argo-class, argoGrid(), argoNames2oceNames(), argo, as.argo(), handleFlags,argo-method, plot,argo-method, subset,argo-method, summary,argo-method


if (FALSE) { ## Example 1: read from a local file library(oce) d <- read.argo("/data/OAR/") summary(d) plot(d) ## Example 2: construct URL for download (brittle) id <- "6900388" url <- "" if (!length(list.files(pattern="argo_index.txt"))) download.file(paste(url, "ar_index_global_meta.txt", sep="/"), "argo_index.txt") index <- readLines("argo_index.txt") line <- grep(id, index) if (0 == length(line)) stop("id ", id, " not found") if (1 < length(line)) stop("id ", id, " found multiple times") dac <- strsplit(index[line], "/")[[1]][1] profile <- paste(id, "", sep="") float <- paste(url, "dac", dac, id, profile, sep="/") download.file(float, profile) argo <- read.argo(profile) summary(argo) }