rerddap is a general purpose R client for working with ERDDAP servers.

Installation

From CRAN

install.packages("rerddap")

Or development version from GitHub

devtools::install_github("ropensci/rerddap")
library("rerddap")

Some users may experience an installation error, stating to install 1 or more packages, e.g., you may need DBI, in which case do, for example, install.packages("DBI") before installing rerddap.

Background

ERDDAP is a server built on top of OPenDAP, which serves some NOAA data. You can get gridded data (griddap), which lets you query from gridded datasets, or table data (tabledap) which lets you query from tabular datasets. In terms of how we interface with them, there are similarities, but some differences too. We try to make a similar interface to both data types in rerddap.

NetCDF

rerddap supports NetCDF format, and is the default when using the griddap() function. NetCDF is a binary file format, and will have a much smaller footprint on your disk than csv. The binary file format means it’s harder to inspect, but the ncdf4 package makes it easy to pull data out and write data back into a NetCDF file. Note the the file extension for NetCDF files is .nc. Whether you choose NetCDF or csv for small files won’t make much of a difference, but will with large files.

Caching

Data files downloaded are cached in a single directory on your machine determined by the hoardr package. When you use griddap() or tabledap() functions, we construct a MD5 hash from the base URL, and any query parameters - this way each query is separately cached. Once we have the hash, we look in the cache directory for a matching hash. If there’s a match we use that file on disk - if no match, we make a http request for the data to the ERDDAP server you specify.

ERDDAP servers

You can get a data.frame of ERDDAP servers using the function servers(). Most I think serve some kind of NOAA data, but there are a few that aren’t NOAA data. If you know of more ERDDAP servers, send a pull request, or let us know.

Information

Then you can get information on a single dataset

info("erdMBchla1day")
#> <ERDDAP info> erdMBchla1day
#>  Base URL: https://upwell.pfeg.noaa.gov/erddap/
#>  Dimensions (range):
#>      time: (2006-01-01T12:00:00Z, 2020-01-20T12:00:00Z)
#>      altitude: (0.0, 0.0)
#>      latitude: (-45.0, 65.0)
#>      longitude: (120.0, 320.0)
#>  Variables:
#>      chlorophyll:
#>          Units: mg m-3

griddap (gridded) data

(out <- info("erdMBchla1day"))
#> <ERDDAP info> erdMBchla1day
#>  Base URL: https://upwell.pfeg.noaa.gov/erddap/
#>  Dimensions (range):
#>      time: (2006-01-01T12:00:00Z, 2020-01-20T12:00:00Z)
#>      altitude: (0.0, 0.0)
#>      latitude: (-45.0, 65.0)
#>      longitude: (120.0, 320.0)
#>  Variables:
#>      chlorophyll:
#>          Units: mg m-3
(res <- griddap(out,
  time = c("2015-01-01", "2015-01-03"),
  latitude = c(14, 15),
  longitude = c(125, 126)
))
#> <ERDDAP griddap> erdMBchla1day
#>    Path: [/Users/sckott/Library/Caches/R/rerddap/4d844aa48552049c3717ac94ced5f9b8.nc]
#>    Last updated: [2020-01-22 13:46:39]
#>    File size:    [0.03 mb]
#>    Dimensions (dims/vars):   [4 X 1]
#>    Dim names: time, altitude, latitude, longitude
#>    Variable names: Chlorophyll Concentration in Sea Water
#>    data.frame (rows/columns):   [5043 X 5]
#> # A tibble: 5,043 x 5
#>    time                   lat   lon altitude chlorophyll
#>    <chr>                <dbl> <dbl>    <dbl>       <dbl>
#>  1 2015-01-01T12:00:00Z    14  125         0          NA
#>  2 2015-01-01T12:00:00Z    14  125.        0          NA
#>  3 2015-01-01T12:00:00Z    14  125.        0          NA
#>  4 2015-01-01T12:00:00Z    14  125.        0          NA
#>  5 2015-01-01T12:00:00Z    14  125.        0          NA
#>  6 2015-01-01T12:00:00Z    14  125.        0          NA
#>  7 2015-01-01T12:00:00Z    14  125.        0          NA
#>  8 2015-01-01T12:00:00Z    14  125.        0          NA
#>  9 2015-01-01T12:00:00Z    14  125.        0          NA
#> 10 2015-01-01T12:00:00Z    14  125.        0          NA
#> # … with 5,033 more rows

tabledap (tabular) data

(out <- info("erdCinpKfmBT"))
#> <ERDDAP info> erdCinpKfmBT
#>  Base URL: https://upwell.pfeg.noaa.gov/erddap/
#>  Variables:
#>      Aplysia_californica_Mean_Density:
#>          Range: 0.0, 0.95
#>          Units: m-2
#>      Aplysia_californica_StdDev:
#>          Range: 0.0, 0.35
#>      Aplysia_californica_StdErr:
#>          Range: 0.0, 0.1
#>      Crassedoma_giganteum_Mean_Density:
#>          Range: 0.0, 0.92
#>          Units: m-2
#>      Crassedoma_giganteum_StdDev:
#>          Range: 0.0, 0.71
...
tabledap("erdCinpKfmBT", "time>=2007-06-24", "time<=2007-07-01")
#> <ERDDAP tabledap> erdCinpKfmBT
#>    Path: [/Users/sckott/Library/Caches/R/rerddap/268b2474e9e613336b900d3289304bb0.csv]
#>    Last updated: [2020-01-22 13:46:42]
#>    File size:    [0.01 mb]
#> # A tibble: 37 x 53
#>    station longitude latitude depth time  Aplysia_califor… Aplysia_califor…
#>    <chr>   <chr>     <chr>    <chr> <chr> <chr>                       <dbl>
#>  1 Anacap… -119.416… 34.0     16.0  2007… 0.009722223                  0.01
#>  2 Anacap… -119.383… 34.0     17.0  2007… 0.0                          0
#>  3 Anacap… -119.366… 34.0     6.0   2007… 0.0                          0
#>  4 Anacap… -119.383… 34.0     11.0  2007… 0.16                         0.17
#>  5 Anacap… -119.416… 34.0     11.0  2007… 0.03                         0.01
#>  6 Anacap… -119.35   34.0166… 5.0   2007… 0.0                          0
#>  7 Anacap… -119.35   34.0     8.0   2007… 0.008333334                  0.01
#>  8 SanCle… -118.533… 33.0     11.0  2007… NaN                        NaN
#>  9 SanCle… -118.533… 32.95    10.0  2007… NaN                        NaN
#> 10 SanCle… -118.4    32.8     13.0  2007… NaN                        NaN
#> # … with 27 more rows, and 46 more variables: Aplysia_californica_StdErr <dbl>,
#> #   Crassedoma_giganteum_Mean_Density <chr>, Crassedoma_giganteum_StdDev <dbl>,
#> #   Crassedoma_giganteum_StdErr <dbl>, Haliotis_corrugata_Mean_Density <chr>,
#> #   Haliotis_corrugata_StdDev <dbl>, Haliotis_corrugata_StdErr <dbl>,
#> #   Haliotis_fulgens_Mean_Density <chr>, Haliotis_fulgens_StdDev <dbl>,
#> #   Haliotis_fulgens_StdErr <dbl>, Haliotis_rufescens_Mean_Density <chr>,
#> #   Haliotis_rufescens_StdDev <dbl>, Haliotis_rufescens_StdErr <dbl>,
#> #   Kelletia_kelletii_Mean_Density <chr>, Kelletia_kelletii_StdDev <dbl>,
...

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