rerddap - Blended Sea Winds data from NOAA

noaa
wind
rnoaa
data
Tags: #<Tag:0x00007f57f90516c8> #<Tag:0x00007f57f90513d0> #<Tag:0x00007f57f9051010> #<Tag:0x00007f57f9050bb0>

#1

A user asked if there’s a way to get Blended Sea Winds data from NOAA.

The dataset: http://www.ncdc.noaa.gov/oa/rsad/air-sea/seawinds.html

It can be found in various places, including an OpenDAP server, and Thredds.

Luckily, it’s I think also available on NOAA’s ERDDAP server, for which we already have a general purpose R client.

Install rerddap if you don’t have it:

install.packages("rerddap")
library("rerddap")

Metadata on the dataset

(inf <- info('ncdcOwDly'))
#> <ERDDAP info> ncdcOwDly 
#>  Dimensions (range):  
#>      time: (1987-07-09T09:00:00Z, 2016-09-15T09:00:00Z) 
#>      altitude: (10.0, 10.0) 
#>      latitude: (-89.75, 89.75) 
#>      longitude: (0.0, 359.75) 
#>  Variables:  
#>      u: 
#>          Units: m s-1 
#>      v: 
#>          Units: m s-1 
#>      w: 
#>          Units: m s-1

Get some gridded data

(res2 <- griddap(
  inf,
  time = c('2016-06-15','2016-09-15'),
  latitude = c(-17, -15),
  longitude = c(162, 172)
))
#> <ERDDAP griddap> ncdcOwDly
#>    Path: [~/.rerddap/79801eac6145197f84d6541ce1550e32.nc]
#>    Last updated: [2016-09-19 21:38:15]
#>    File size:    [0.42 mb]
#>    Dimensions (dims/vars):   [4 X 3]
#>    Dim names: time, altitude, latitude, longitude
#>    Variable names: Sea Surface Wind: x-component, Sea Surface Wind: y-component, Sea Surface Wind: speed as scalar means
#>    data.frame (rows/columns):   [34317 X 6]
#> # A tibble: 34,317 × 6
#>                    time   lat    lon         u        v        w
#>                   <chr> <dbl>  <dbl>     <dbl>    <dbl>    <dbl>
#> 1  2016-06-15T09:00:00Z   -17 162.00 -7.735556 2.643484 8.198017
#> 2  2016-06-15T09:00:00Z   -17 162.25 -7.624533 2.593606 8.075055
#> 3  2016-06-15T09:00:00Z   -17 162.50 -7.741753 2.607672 8.188147
#> 4  2016-06-15T09:00:00Z   -17 162.75 -7.945904 2.697658 8.404979
#> 5  2016-06-15T09:00:00Z   -17 163.00 -8.011187 2.878768 8.526998
#> 6  2016-06-15T09:00:00Z   -17 163.25 -7.982147 3.102287 8.583776
#> 7  2016-06-15T09:00:00Z   -17 163.50 -7.919921 3.231742 8.579941
#> 8  2016-06-15T09:00:00Z   -17 163.75 -7.916622 3.274787 8.605670
#> 9  2016-06-15T09:00:00Z   -17 164.00 -7.951212 3.442466 8.706610
#> 10 2016-06-15T09:00:00Z   -17 164.25 -7.992957 3.654139 8.823740
#> # ... with 34,307 more rows