README.md
In BigelowLab/nam218grads: Provides grads-served opendap access to NAM218 forecast data
nam218grads
This package simplifies access to the NCEP NOMADS grads
server for the
NAM
forecast models.
Requirements
Installation
remotes::install_github("BigelowLab/nam218grads")
Usage
Retrieve a URL for a resource
Retrieve a URL for a resource by date, like yesterday’s forecast at
0000H. Note that the NCEP/NOMADS grads server only maintains the current
forecast plus the prior 6.
library(stars)
library(nam218grads)
uri <- grads_uri(date = Sys.Date()-1, product = "nam_00z")
uri
## [1] "http://nomads.ncep.noaa.gov:80/dods/nam/nam20210307/nam_00z"
Get a handle to a resource
It’s just a ncdf4 object,
but we wrapped common tasks in friendly functions.
x <- open_grads(uri)
# File http://nomads.ncep.noaa.gov:80/dods/nam/nam20210303/nam_00z (NC_FORMAT_CLASSIC):
#
# 141 variables (excluding dimension variables):
# float absvprs[lon,lat,lev,time]
# _FillValue: 9.99900026055401e+20
# missing_value: 9.99900026055401e+20
# long_name: ** (1000 850 700 500 250) absolute vorticity [1/s]
# float no4lftx180_0mb[lon,lat,time]
# _FillValue: 9.99900026055401e+20
# missing_value: 9.99900026055401e+20
# long_name: ** 180-0 mb above ground best (4 layer) lifted index [k]
# ...
# 4 global attributes:
# title: NAM every 3 hours fcst staring from 00Z03mar2021, download Mar 03 02:38 UTC
# Conventions: COARDS GrADS
# dataType: Grid
# history: Wed Mar 03 22:27:39 GMT 2021 : imported by GrADS Data Server 2.0
You can explore the contents of the resource.
times <- get_time(x)
times
## [1] "2021-03-09 00:00:00 UTC" "2021-03-09 03:00:00 UTC"
## [3] "2021-03-09 06:00:00 UTC" "2021-03-09 09:00:00 UTC"
## [5] "2021-03-09 12:00:00 UTC" "2021-03-09 15:00:00 UTC"
## [7] "2021-03-09 18:00:00 UTC" "2021-03-09 21:00:00 UTC"
## [9] "2021-03-10 00:00:00 UTC" "2021-03-10 03:00:00 UTC"
## [11] "2021-03-10 06:00:00 UTC" "2021-03-10 09:00:00 UTC"
## [13] "2021-03-10 12:00:00 UTC" "2021-03-10 15:00:00 UTC"
## [15] "2021-03-10 18:00:00 UTC" "2021-03-10 21:00:00 UTC"
## [17] "2021-03-11 00:00:00 UTC" "2021-03-11 03:00:00 UTC"
## [19] "2021-03-11 06:00:00 UTC" "2021-03-11 09:00:00 UTC"
## [21] "2021-03-11 12:00:00 UTC" "2021-03-11 15:00:00 UTC"
## [23] "2021-03-11 18:00:00 UTC" "2021-03-11 21:00:00 UTC"
## [25] "2021-03-12 00:00:00 UTC" "2021-03-12 03:00:00 UTC"
## [27] "2021-03-12 06:00:00 UTC" "2021-03-12 09:00:00 UTC"
## [29] "2021-03-12 12:00:00 UTC"
levels <- get_lev(x)
levels
## [1] 1000 975 950 925 900 875 850 825 800 775 750 725 700 675 650
## [16] 625 600 575 550 525 500 475 450 425 400 375 350 325 300 275
## [31] 250 225 200 175 150 125 100 75 50 20 10 5
vars <- get_varnames(x)
vars
## [1] "absvprs" "no4lftx180_0mb" "acpcpsfc" "albdosfc"
## [5] "apcpsfc" "bmixlhy1" "capesfc" "cape180_0mb"
## [9] "cdsfc" "cfrzrsfc" "cicepsfc" "cinsfc"
## [13] "cin180_0mb" "cnwatsfc" "crainsfc" "csnowsfc"
## [17] "dlwrfsfc" "dpt2m" "dswrfsfc" "dzdtprs"
## [21] "fricvsfc" "gustsfc" "hgtsfc" "hgtprs"
## [25] "hgtclb" "hgtpbl" "hgtlwb0" "hgt0c"
## [29] "hindexsfc" "hlcy3000_0m" "hpblsfc" "icecsfc"
## [33] "landsfc" "lftxl100_100" "lhtflsfc" "ltngsfc"
## [37] "maxrh2m" "maxuw10m" "maxvw10m" "minrh2m"
## [41] "msletmsl" "mstav0_100cm" "pli30_0mb" "porossfc"
## [45] "pressfc" "pres80m" "presmwl" "prestrop"
## [49] "prmslmsl" "pwatclm" "refcclm" "refd4000m"
## [53] "refd1000m" "refdhy1" "retopclm" "rhprs"
## [57] "rh2m" "rhsg330_1000" "rh30_0mb" "rh60_30mb"
## [61] "rh90_60mb" "rh120_90mb" "rh150_120mb" "rh180_150mb"
## [65] "rh0c" "rlyrssfc" "sfcrsfc" "shtflsfc"
## [69] "smdrysfc" "smrefsfc" "snodsfc" "snowcsfc"
## [73] "soill0_10cm" "soill10_40cm" "soill40_100cm" "soill100_200cm"
## [77] "soilm0_200cm" "soilw0_10cm" "soilw10_40cm" "soilw40_100cm"
## [81] "soilw100_200cm" "sotypsfc" "spfh2m" "spfh80m"
## [85] "tcdcclm" "tkeprs" "tmax2m" "tmin2m"
## [89] "tmpsfc" "tmpprs" "tmp2m" "tmp80m"
## [93] "tmp30_0mb" "tmp60_30mb" "tmp90_60mb" "tmp120_90mb"
## [97] "tmp150_120mb" "tmp180_150mb" "tmptrop" "tsoil0_10cm"
## [101] "tsoil10_40cm" "tsoil40_100cm" "tsoil100_200cm" "tsoil300cm"
## [105] "ugrdprs" "ugrd10m" "ugrd80m" "ugrd30_0mb"
## [109] "ugrd60_30mb" "ugrd90_60mb" "ugrd120_90mb" "ugrd150_120mb"
## [113] "ugrd180_150mb" "ugrdpbl" "ugrdmwl" "ugrdtrop"
## [117] "ulwrfsfc" "uswrfsfc" "vegsfc" "vgrdprs"
## [121] "vgrd10m" "vgrd80m" "vgrd30_0mb" "vgrd60_30mb"
## [125] "vgrd90_60mb" "vgrd120_90mb" "vgrd150_120mb" "vgrd180_150mb"
## [129] "vgrdpbl" "vgrdmwl" "vgrdtrop" "vgtypsfc"
## [133] "vissfc" "visclt" "vratepbl" "vucsh0_6000m"
## [137] "vvcsh0_6000m" "vvelprs" "weasdaccsfc" "weasdsfc"
## [141] "wiltsfc"
dims <- get_dims(x)
dims
## lat lev lon time
## 443 42 913 29
Retrieve data
As an array
Retrieving data will return contiguous arrays of data. We provide a
function get_var_array that expects the slab coordinates in integer
run-length encoding for each dimension as [start_index, count]. This
function returns an array of cell values - for range of pressure levels
at different times.
a <- nam218grads::get_var_array(x, "tmpprs",
list(lon = c(110, 100),
lat = c(150, 75),
lev = c(3, 5),
time = c(1, 12)))
str(a)
## num [1:100, 1:75, 1:5, 1:12] NA NA NA NA NA NA NA NA NA NA ...
As a stars object
The get_var function is a convenient wrapper around the
get_var_array function. Users specify the slab limits with ‘real
world’ units, and a stars
object is returned (although returning an array is an option).
s <- nam218grads::get_var(x, "tmpprs",
bb = c(-77.0, -51.5, 37.9, 56.7),
time = times[1:12],
lev = levels[3:5])
s
## stars object with 4 dimensions and 1 attribute
## attribute(s), summary of first 1e+05 cells:
## tmpprs
## Min. :248.1
## 1st Qu.:260.9
## Median :263.7
## Mean :263.6
## 3rd Qu.:266.0
## Max. :281.8
## NA's :11260
## dimension(s):
## from to offset delta refsys point values x/y
## x 1 226 -77.0816 0.113384 WGS 84 NA NULL [x]
## y 1 170 56.7171 -0.110827 WGS 84 NA NULL [y]
## z 1 3 950 -25 NA NA NULL
## time 1 12 2021-03-09 UTC 3 hours POSIXct NA NULL
You can also retrieve multiple variables. Note in the example below that
ugrd10m and vgrd10m (wind component speeds at 10m above surface) do
not have a lev dimension so we can ignore the lev argument.
winds <- nam218grads::get_var(x, c("ugrd10m", "vgrd10m"),
bb = c(-77.0, -51.5, 37.9, 56.7),
time = times[5:7])
winds
## stars object with 3 dimensions and 2 attributes
## attribute(s):
## ugrd10m vgrd10m
## Min. :-4.802 Min. :-10.953
## 1st Qu.: 2.641 1st Qu.: -2.560
## Median : 3.813 Median : -1.062
## Mean : 4.019 Mean : -0.320
## 3rd Qu.: 5.056 3rd Qu.: 1.710
## Max. :15.156 Max. : 11.797
## NA's :14664 NA's :14664
## dimension(s):
## from to offset delta refsys point values x/y
## x 1 226 -77.0816 0.113384 WGS 84 NA NULL [x]
## y 1 170 56.7171 -0.110827 WGS 84 NA NULL [y]
## time 1 3 2021-03-09 12:00:00 UTC 3 hours POSIXct NA NULL
Close the handle
The resource is a ncdf4 object - be sure to close it when done.
close_grads(x)
Plot the levels at different times
Let’s use the temperature at various pressure levels in variable s for
some plotting. First time slice…
if (require(maps)){
time_string <- format(times[1], "%Y-%m-%d %H:%M:%S")
overlay_fun <- function() {
map(col = 'red', add = TRUE)
mtext(time_string, side = 1, line = -1)
}
plot(s, axes = TRUE, hook = overlay_fun)
}
## Loading required package: maps
And the last time slice…
if (require(maps)){
time_string <- format(times[12], "%Y-%m-%d %H:%M:%S")
plot(s[,,,,12], axes = TRUE, hook = overlay_fun)
}
BigelowLab/nam218grads documentation built on Oct. 4, 2022, 2:01 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
nam218grads
This package simplifies access to the NCEP NOMADS grads server for the NAM forecast models.
Requirements
Installation
remotes::install_github("BigelowLab/nam218grads")
Usage
Retrieve a URL for a resource
Retrieve a URL for a resource by date, like yesterday’s forecast at 0000H. Note that the NCEP/NOMADS grads server only maintains the current forecast plus the prior 6.
library(stars)
library(nam218grads)
uri <- grads_uri(date = Sys.Date()-1, product = "nam_00z")
uri
## [1] "http://nomads.ncep.noaa.gov:80/dods/nam/nam20210307/nam_00z"
Get a handle to a resource
It’s just a ncdf4 object, but we wrapped common tasks in friendly functions.
x <- open_grads(uri)
# File http://nomads.ncep.noaa.gov:80/dods/nam/nam20210303/nam_00z (NC_FORMAT_CLASSIC):
#
# 141 variables (excluding dimension variables):
# float absvprs[lon,lat,lev,time]
# _FillValue: 9.99900026055401e+20
# missing_value: 9.99900026055401e+20
# long_name: ** (1000 850 700 500 250) absolute vorticity [1/s]
# float no4lftx180_0mb[lon,lat,time]
# _FillValue: 9.99900026055401e+20
# missing_value: 9.99900026055401e+20
# long_name: ** 180-0 mb above ground best (4 layer) lifted index [k]
# ...
# 4 global attributes:
# title: NAM every 3 hours fcst staring from 00Z03mar2021, download Mar 03 02:38 UTC
# Conventions: COARDS GrADS
# dataType: Grid
# history: Wed Mar 03 22:27:39 GMT 2021 : imported by GrADS Data Server 2.0
You can explore the contents of the resource.
times <- get_time(x)
times
## [1] "2021-03-09 00:00:00 UTC" "2021-03-09 03:00:00 UTC"
## [3] "2021-03-09 06:00:00 UTC" "2021-03-09 09:00:00 UTC"
## [5] "2021-03-09 12:00:00 UTC" "2021-03-09 15:00:00 UTC"
## [7] "2021-03-09 18:00:00 UTC" "2021-03-09 21:00:00 UTC"
## [9] "2021-03-10 00:00:00 UTC" "2021-03-10 03:00:00 UTC"
## [11] "2021-03-10 06:00:00 UTC" "2021-03-10 09:00:00 UTC"
## [13] "2021-03-10 12:00:00 UTC" "2021-03-10 15:00:00 UTC"
## [15] "2021-03-10 18:00:00 UTC" "2021-03-10 21:00:00 UTC"
## [17] "2021-03-11 00:00:00 UTC" "2021-03-11 03:00:00 UTC"
## [19] "2021-03-11 06:00:00 UTC" "2021-03-11 09:00:00 UTC"
## [21] "2021-03-11 12:00:00 UTC" "2021-03-11 15:00:00 UTC"
## [23] "2021-03-11 18:00:00 UTC" "2021-03-11 21:00:00 UTC"
## [25] "2021-03-12 00:00:00 UTC" "2021-03-12 03:00:00 UTC"
## [27] "2021-03-12 06:00:00 UTC" "2021-03-12 09:00:00 UTC"
## [29] "2021-03-12 12:00:00 UTC"
levels <- get_lev(x)
levels
## [1] 1000 975 950 925 900 875 850 825 800 775 750 725 700 675 650
## [16] 625 600 575 550 525 500 475 450 425 400 375 350 325 300 275
## [31] 250 225 200 175 150 125 100 75 50 20 10 5
vars <- get_varnames(x)
vars
## [1] "absvprs" "no4lftx180_0mb" "acpcpsfc" "albdosfc"
## [5] "apcpsfc" "bmixlhy1" "capesfc" "cape180_0mb"
## [9] "cdsfc" "cfrzrsfc" "cicepsfc" "cinsfc"
## [13] "cin180_0mb" "cnwatsfc" "crainsfc" "csnowsfc"
## [17] "dlwrfsfc" "dpt2m" "dswrfsfc" "dzdtprs"
## [21] "fricvsfc" "gustsfc" "hgtsfc" "hgtprs"
## [25] "hgtclb" "hgtpbl" "hgtlwb0" "hgt0c"
## [29] "hindexsfc" "hlcy3000_0m" "hpblsfc" "icecsfc"
## [33] "landsfc" "lftxl100_100" "lhtflsfc" "ltngsfc"
## [37] "maxrh2m" "maxuw10m" "maxvw10m" "minrh2m"
## [41] "msletmsl" "mstav0_100cm" "pli30_0mb" "porossfc"
## [45] "pressfc" "pres80m" "presmwl" "prestrop"
## [49] "prmslmsl" "pwatclm" "refcclm" "refd4000m"
## [53] "refd1000m" "refdhy1" "retopclm" "rhprs"
## [57] "rh2m" "rhsg330_1000" "rh30_0mb" "rh60_30mb"
## [61] "rh90_60mb" "rh120_90mb" "rh150_120mb" "rh180_150mb"
## [65] "rh0c" "rlyrssfc" "sfcrsfc" "shtflsfc"
## [69] "smdrysfc" "smrefsfc" "snodsfc" "snowcsfc"
## [73] "soill0_10cm" "soill10_40cm" "soill40_100cm" "soill100_200cm"
## [77] "soilm0_200cm" "soilw0_10cm" "soilw10_40cm" "soilw40_100cm"
## [81] "soilw100_200cm" "sotypsfc" "spfh2m" "spfh80m"
## [85] "tcdcclm" "tkeprs" "tmax2m" "tmin2m"
## [89] "tmpsfc" "tmpprs" "tmp2m" "tmp80m"
## [93] "tmp30_0mb" "tmp60_30mb" "tmp90_60mb" "tmp120_90mb"
## [97] "tmp150_120mb" "tmp180_150mb" "tmptrop" "tsoil0_10cm"
## [101] "tsoil10_40cm" "tsoil40_100cm" "tsoil100_200cm" "tsoil300cm"
## [105] "ugrdprs" "ugrd10m" "ugrd80m" "ugrd30_0mb"
## [109] "ugrd60_30mb" "ugrd90_60mb" "ugrd120_90mb" "ugrd150_120mb"
## [113] "ugrd180_150mb" "ugrdpbl" "ugrdmwl" "ugrdtrop"
## [117] "ulwrfsfc" "uswrfsfc" "vegsfc" "vgrdprs"
## [121] "vgrd10m" "vgrd80m" "vgrd30_0mb" "vgrd60_30mb"
## [125] "vgrd90_60mb" "vgrd120_90mb" "vgrd150_120mb" "vgrd180_150mb"
## [129] "vgrdpbl" "vgrdmwl" "vgrdtrop" "vgtypsfc"
## [133] "vissfc" "visclt" "vratepbl" "vucsh0_6000m"
## [137] "vvcsh0_6000m" "vvelprs" "weasdaccsfc" "weasdsfc"
## [141] "wiltsfc"
dims <- get_dims(x)
dims
## lat lev lon time
## 443 42 913 29
Retrieve data
As an array
Retrieving data will return contiguous arrays of data. We provide a
function get_var_array that expects the slab coordinates in integer
run-length encoding for each dimension as [start_index, count]. This
function returns an array of cell values - for range of pressure levels
at different times.
a <- nam218grads::get_var_array(x, "tmpprs",
list(lon = c(110, 100),
lat = c(150, 75),
lev = c(3, 5),
time = c(1, 12)))
str(a)
## num [1:100, 1:75, 1:5, 1:12] NA NA NA NA NA NA NA NA NA NA ...
As a stars object
The get_var function is a convenient wrapper around the
get_var_array function. Users specify the slab limits with ‘real
world’ units, and a stars
object is returned (although returning an array is an option).
s <- nam218grads::get_var(x, "tmpprs",
bb = c(-77.0, -51.5, 37.9, 56.7),
time = times[1:12],
lev = levels[3:5])
s
## stars object with 4 dimensions and 1 attribute
## attribute(s), summary of first 1e+05 cells:
## tmpprs
## Min. :248.1
## 1st Qu.:260.9
## Median :263.7
## Mean :263.6
## 3rd Qu.:266.0
## Max. :281.8
## NA's :11260
## dimension(s):
## from to offset delta refsys point values x/y
## x 1 226 -77.0816 0.113384 WGS 84 NA NULL [x]
## y 1 170 56.7171 -0.110827 WGS 84 NA NULL [y]
## z 1 3 950 -25 NA NA NULL
## time 1 12 2021-03-09 UTC 3 hours POSIXct NA NULL
You can also retrieve multiple variables. Note in the example below that
ugrd10m and vgrd10m (wind component speeds at 10m above surface) do
not have a lev dimension so we can ignore the lev argument.
winds <- nam218grads::get_var(x, c("ugrd10m", "vgrd10m"),
bb = c(-77.0, -51.5, 37.9, 56.7),
time = times[5:7])
winds
## stars object with 3 dimensions and 2 attributes
## attribute(s):
## ugrd10m vgrd10m
## Min. :-4.802 Min. :-10.953
## 1st Qu.: 2.641 1st Qu.: -2.560
## Median : 3.813 Median : -1.062
## Mean : 4.019 Mean : -0.320
## 3rd Qu.: 5.056 3rd Qu.: 1.710
## Max. :15.156 Max. : 11.797
## NA's :14664 NA's :14664
## dimension(s):
## from to offset delta refsys point values x/y
## x 1 226 -77.0816 0.113384 WGS 84 NA NULL [x]
## y 1 170 56.7171 -0.110827 WGS 84 NA NULL [y]
## time 1 3 2021-03-09 12:00:00 UTC 3 hours POSIXct NA NULL
Close the handle
The resource is a ncdf4 object - be sure to close it when done.
close_grads(x)
Plot the levels at different times
Let’s use the temperature at various pressure levels in variable s for
some plotting. First time slice…
if (require(maps)){
time_string <- format(times[1], "%Y-%m-%d %H:%M:%S")
overlay_fun <- function() {
map(col = 'red', add = TRUE)
mtext(time_string, side = 1, line = -1)
}
plot(s, axes = TRUE, hook = overlay_fun)
}
## Loading required package: maps
And the last time slice…
if (require(maps)){
time_string <- format(times[12], "%Y-%m-%d %H:%M:%S")
plot(s[,,,,12], axes = TRUE, hook = overlay_fun)
}
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.