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ERSST

ersst

Provides for download, archiving and access to Extended Reconstructed Sea Surface Temperature ‘ersst’ online and local datasets.

Citation

Boyin Huang, Peter W. Thorne, Viva F. Banzon, Tim Boyer, Gennady Chepurin, Jay H. Lawrimore, Matthew J. Menne, Thomas M. Smith, Russell S. Vose, and Huai-Min Zhang (2017): NOAA Extended Reconstructed Sea Surface Temperature (ERSST), Version 5. NOAA National Centers for Environmental Information. doi:10.7289/V5T72FNM [access date, monthly from 2021-04-15].

Requirements

From CRAN…

Installation

remotes::install_github("BigelowLab/ersst")

Usage

suppressPackageStartupMessages({
  library(dplyr)
  library(sf)
  library(ersst)
  library(stars)
})

Working with points.

We provide a small example of points from locations associated with buoys off of the US southeast coast.

# read in example South Atlantic Bight points
x <- read_sab()

# generate a ersst url for a given date
url <- ersst_url("2018-12-18")

# download
temp_file <- tempfile(fileext = ".nc")
ok <- download.file(url, temp_file)

# open the resource
X <- ncdf4::nc_open(temp_file)

# extract the data 
covars <- ersst::extract(x, X, varname = ersst_vars(X))

# bind to the input
(y <- dplyr::bind_cols(x, covars))
## Simple feature collection with 5 features and 6 fields
## Geometry type: POINT
## Dimension:     XY
## Bounding box:  xmin: 279.815 ymin: 28.508 xmax: 287.752 ymax: 34.714
## Geodetic CRS:  WGS 84
## # A tibble: 5 × 7
##      id name     depth time                            geom   sst  ssta
## * <dbl> <chr>    <dbl> <dttm>                   <POINT [°]> <dbl> <dbl>
## 1 41009 Canveral  -1.5 2022-06-17 14:05:06 (279.815 28.508)  24.9 0.619
## 2 41010 Canaver…  -1.5 2022-06-29 14:05:06 (281.515 28.878)  25.3 0.708
## 3 41002 South H…  -1.5 2022-06-05 14:05:06 (285.064 31.759)  23.2 0.745
## 4 41001 East Ha…  -2   2022-04-30 14:05:06 (287.752 34.714)  22.2 0.706
## 5 41004 EDISTO    -1.5 2022-07-11 14:05:06 (280.901 32.502)  23.4 0.680

Working with bounding boxes (from points or polygons).

Learn more about working with stars objects in the vignettes. Here we drop time and depth as the ERSST data has only one depth and each file holds one time.

# derive the bounding box of the points and convert to sf coordinates
bb = sf::st_bbox(x) |>
  sf::st_as_sfc()

(covars <- ersst::extract(bb, X, varnames = ersst::ersst_vars(X)))
## stars object with 2 dimensions and 1 attribute
## attribute(s):
##          Min.  1st Qu.   Median     Mean  3rd Qu.     Max. NA's
## sst  16.24087 22.10199 23.56519 22.89823 24.44305 25.33899    7
## dimension(s):
##   from to offset  delta refsys x/y
## x    1  6  279.8  1.323 WGS 84 [x]
## y    1  5  34.71 -1.241 WGS 84 [y]

Now let’s see what it looks like on a quick map.

plot(covars, attr = 'sst', axes = TRUE, reset = FALSE)
plot(sf::st_geometry(x), add = TRUE, col = "orange", 
     pch = 19, cex = 2)

# cleanup
ncdf4::nc_close(X)