erddapDownload: Download SST, NPP, and Chlorophyll Data from NOAA (ERDDAP)
In dbarneche/noaaErddap: SST, NPP, and Chlorophyll Data from NOAA (ERDDAP)

Description Usage Arguments Details Value Author(s) Examples

Download NOAA ERDDAP Data.

1	erddapDownload(year, month, type, overwrite = FALSE, ...)

`year`	A `numeric` or `character` string (YYYY) informing the year.
`month`	A `numeric` (integer) or `character` string (MM) informing the month (from 1 to 12).
`type`	Type of environmental layer to be downloaded. Currently takes 3 possible values: `'productivity'`, `'chlorophyll'` and `'sst'`. See `details` below.
`overwrite`	Should the layer of interest be overwritten?
`...`	further arguments to `GET`.

Net Primary Productivity (NPP) data from http://coastwatch.pfeg.noaa.gov/erddap/griddap/erdPPbfp18day.html NOAA ERDDAP > griddap > Data Access Form metadata in http://coastwatch.pfeg.noaa.gov/erddap/info/erdPPbfp18day/index.html. Primary Productivity, SeaWiFS and Pathfinder, Global, 1997-2010, EXPERIMENTAL (8 Day Composite) From 1997 - Nov - 29 to 2007 - Nov - 29 NPP is an 8-day composite product, so every consecutive eight days should produce an independent time step. Note that this time series is not perfectly even. Data input should be in the format of year and month.

Chlorophyll-a (CHL) data from http://coastwatch.pfeg.noaa.gov/erddap/griddap/erdSW1chla8day.html NOAA ERDDAP > griddap > Data Access Form metadata in http://coastwatch.pfeg.noaa.gov/erddap/info/erdSW1chla8day/index.html Chlorophyll-a, Orbview-2 SeaWiFS, R2014.0, 0.1°, Global, 1997-2010 (8 Day Composite) From 1997 - Nov - 29 to 2007 - Nov - 29 Chlorophyll-a is an 8-day composite product, so every consecutive eight days should produce an independent time step. Note that this time series is not perfectly even. Data input should be in the format of year and month.

Sea Surface Temperature (SST) data from http://www.esrl.noaa.gov/psd/data/gridded/data.noaa.oisst.v2.highres.html Brief Description: NOAA High-resolution Blended Analysis of Daily SST and Ice. Data is from Sep 1981 and is on a 1/4 deg global grid. Temporal Coverage: Daily values from 1981/09 to present Spatial Coverage: 0.25 degree latitude x 0.25 degree longitude global grid (1440x720). 89.875S - 89.875N,0.125E to 359.875E. Main ref: Reynolds, Richard W., Thomas M. Smith, Chunying Liu, Dudley B. Chelton, Kenneth S. Casey, Michael G. Schlax, 2007: Daily H'igh-Resolution-Blended Analyses for Sea Surface Temperature. J. Climate, 20, 5473-5496. Reynolds, Richard W., Thomas M. Smith, Chunying Liu, Dudley B. Chelton, Kenneth S. Casey, Michael G. Schlax, 2007: Daily High-Resolution-Blended Analyses for Sea Surface Temperature. J. Climate, 20, 5473-5496. Note that different from NPP and CHL, SST is provided on a yearly basis. Thus, inputs such as erddapDownload(year = 2006, month = 1, type = 'productivity') and erddapDownload(year = 2006, month = 10, type = 'productivity') will yield the same layer, provided that the combination year-month falls within the currently supported Date limits. This happens because internal methods ignore the month argument to download SST layers downstream, also affecting the naming of the output file in the cache folder.

A character vector containing the path where files have been saved to.

Diego Barneche.

# download productivity data for Jan 2006
pathToDownloadedFile  <-  erddapDownload(year = 2006, month = 1, type = 'productivity')
# download productivity data for all months between 1998-2008
library(plyr)
dat  <-  expand.grid(year = 1998:2008, month = 1:12)
tableOfPaths  <-  ddply(dat, .(year, month), function (x, type) {
    erddapDownload(x$year, x$month, type, overwrite = TRUE)
}, type = 'productivity')
# check outputs
pathToDownloadedFile; tableOfPaths