rnoaa

Help

There is a tutorial on the rOpenSci website, and there are many tutorials in the package itself, available in your R session, or on CRAN. The tutorials:

• NOAA Buoy vignette
• NOAA National Climatic Data Center (NCDC) vignette (examples)
• NOAA NCDC attributes vignette
• NOAA NCDC workflow vignette
• Sea ice vignette
• Severe Weather Data Inventory (SWDI) vignette
• Historical Observing Metadata Repository (HOMR) vignette
• Storms (IBTrACS) vignette

Data sources used in rnoaa

• NOAA NCDC climate data:
  • We are using the NOAA API version 2
  • Docs for the NCDC API are at http://www.ncdc.noaa.gov/cdo-web/webservices/v2
  • GHCN Daily data is available at http://www.ncdc.noaa.gov/oa/climate/ghcn-daily/ via FTP and HTTP
• Severe weather data docs are at http://www.ncdc.noaa.gov/swdiws/
• Sea ice data
• NOAA buoy data
• ERDDAP data
  • Now in package rerddap
• Tornadoes! Data from the NOAA Storm Prediction Center
• HOMR - Historical Observing Metadata Repository - from NOAA NCDC
• Storm data - from the International Best Track Archive for Climate Stewardship (IBTrACS)
• GHCND FTP data - NOAA NCDC API has some/all (not sure really) of this data, but FTP allows to get more data more quickly

netcdf data

Functions to work with buoy data use netcdf files. You'll need the ncdf package for those functions, and those only. ncdf is in Suggests in this package, meaning you only need ncdf if you are using the buoy functions. You'll get an informative error telling you to install ncdf if you don't have it and you try to use the buoy functions. Installation of ncdf should be straightforward on Mac and Windows, but on Linux you may have issues. See http://cran.r-project.org/web/packages/ncdf/INSTALL

NOAA NCDC Datasets

There are many NOAA NCDC datasets. All data sources work, except NEXRAD2 and NEXRAD3, for an unkown reason.

NOAA NCDC Attributes

Each NOAA dataset has a different set of attributes that you can potentially get back in your search. See http://www.ncdc.noaa.gov/cdo-web/datasets for detailed info on each dataset. We provide some information on the attributes in this package; see the vignette for attributes to find out more

Authentication

You'll need an API key to use the NOAA NCDC functions (those starting with ncdc*()) in this package (essentially a password). Go to http://www.ncdc.noaa.gov/cdo-web/token to get one. You can't use this package without an API key.

Once you obtain a key, there are two ways to use it.

a) Pass it inline with each function call (somewhat cumbersome)

ncdc(datasetid = 'PRECIP_HLY', locationid = 'ZIP:28801', datatypeid = 'HPCP', limit = 5, token =  "YOUR_TOKEN")

b) Alternatively, you might find it easier to set this as an option, either by adding this line to the top of a script or somewhere in your .rprofile

options(noaakey = "KEY_EMAILED_TO_YOU")

c) You can always store in permamently in your .Rprofile file.

Installation

GDAL

You'll need GDAL installed first. You may want to use GDAL >= 0.9-1 since that version or later can read TopoJSON format files as well, which aren't required here, but may be useful. Install GDAL:

• OSX - From http://www.kyngchaos.com/software/frameworks
• Linux - run sudo apt-get install gdal-bin reference
• Windows - From http://trac.osgeo.org/osgeo4w/

Then when you install the R package rgdal (rgeos also requires GDAL), you'll most likely need to specify where you're gdal-config file is on your machine, as well as a few other things. I have an OSX Mavericks machine, and this works for me (there's no binary for Mavericks, so install the source version):

install.packages("http://cran.r-project.org/src/contrib/rgdal_0.9-1.tar.gz", repos = NULL, type="source", configure.args = "--with-gdal-config=/Library/Frameworks/GDAL.framework/Versions/1.10/unix/bin/gdal-config --with-proj-include=/Library/Frameworks/PROJ.framework/unix/include --with-proj-lib=/Library/Frameworks/PROJ.framework/unix/lib")

The rest of the installation should be easy. If not, let us know.

Stable version from CRAN

install.packages("rnoaa")

or development version from GitHub

devtools::install_github("ropensci/rnoaa")

Load rnoaa

library('rnoaa')

NCDC v2 API data

Fetch list of city locations in descending order

ncdc_locs(locationcategoryid='CITY', sortfield='name', sortorder='desc')
#> $meta
#> $meta$totalCount
#> [1] 1980
#> 
#> $meta$pageCount
#> [1] 25
#> 
#> $meta$offset
#> [1] 1
#> 
#> 
#> $data
#> Source: local data frame [25 x 5]
#> 
#>       mindate    maxdate             name datacoverage            id
#> 1  1892-08-01 2015-05-31       Zwolle, NL       1.0000 CITY:NL000012
#> 2  1901-01-01 2015-07-04       Zurich, SZ       1.0000 CITY:SZ000007
#> 3  1957-07-01 2015-07-04    Zonguldak, TU       0.8621 CITY:TU000057
#> 4  1906-01-01 2015-07-04       Zinder, NG       0.9019 CITY:NG000004
#> 5  1973-01-01 2015-07-04   Ziguinchor, SG       1.0000 CITY:SG000004
#> 6  1938-01-01 2015-07-04    Zhytomyra, UP       0.9732 CITY:UP000025
#> 7  1948-03-01 2015-07-04   Zhezkazgan, KZ       0.9295 CITY:KZ000017
#> 8  1951-01-01 2015-07-04    Zhengzhou, CH       1.0000 CITY:CH000045
#> 9  1941-01-01 2014-12-22     Zaragoza, SP       1.0000 CITY:SP000021
#> 10 1936-01-01 2009-06-17 Zaporiyhzhya, UP       0.9739 CITY:UP000024
#> ..        ...        ...              ...          ...           ...
#> 
#> attr(,"class")
#> [1] "ncdc_locs"

Get info on a station by specifcying a dataset, locationtype, location, and station

ncdc_stations(datasetid='GHCND', locationid='FIPS:12017', stationid='GHCND:USC00084289')
#> $meta
#> NULL
#> 
#> $data
#>   elevation    mindate    maxdate latitude                  name
#> 1      12.2 1899-02-01 2015-07-05  28.8029 INVERNESS 3 SE, FL US
#>   datacoverage                id elevationUnit longitude
#> 1            1 GHCND:USC00084289        METERS  -82.3126
#> 
#> attr(,"class")
#> [1] "ncdc_stations"

Search for data

out <- ncdc(datasetid='NORMAL_DLY', stationid='GHCND:USW00014895', datatypeid='dly-tmax-normal', startdate = '2010-05-01', enddate = '2010-05-10')

See a data.frame

head( out$data )
#> Source: local data frame [6 x 5]
#> 
#>                  date        datatype           station value fl_c
#> 1 2010-05-01T00:00:00 DLY-TMAX-NORMAL GHCND:USW00014895   652    S
#> 2 2010-05-02T00:00:00 DLY-TMAX-NORMAL GHCND:USW00014895   655    S
#> 3 2010-05-03T00:00:00 DLY-TMAX-NORMAL GHCND:USW00014895   658    S
#> 4 2010-05-04T00:00:00 DLY-TMAX-NORMAL GHCND:USW00014895   661    S
#> 5 2010-05-05T00:00:00 DLY-TMAX-NORMAL GHCND:USW00014895   663    S
#> 6 2010-05-06T00:00:00 DLY-TMAX-NORMAL GHCND:USW00014895   666    S

Plot data, super simple, but it's a start

out <- ncdc(datasetid='GHCND', stationid='GHCND:USW00014895', datatypeid='PRCP', startdate = '2010-05-01', enddate = '2010-10-31', limit=500)
ncdc_plot(out, breaks="1 month", dateformat="%d/%m")

More plotting

You can pass many outputs from calls to the noaa function in to the ncdc_plot function.

out1 <- ncdc(datasetid='GHCND', stationid='GHCND:USW00014895', datatypeid='PRCP', startdate = '2010-03-01', enddate = '2010-05-31', limit=500)
out2 <- ncdc(datasetid='GHCND', stationid='GHCND:USW00014895', datatypeid='PRCP', startdate = '2010-09-01', enddate = '2010-10-31', limit=500)
ncdc_plot(out1, out2, breaks="45 days")

Get table of all datasets

ncdc_datasets()
#> $meta
#> $meta$offset
#> [1] 1
#> 
#> $meta$count
#> [1] 11
#> 
#> $meta$limit
#> [1] 25
#> 
#> 
#> $data
#> Source: local data frame [11 x 6]
#> 
#>                     uid    mindate    maxdate                      name
#> 1  gov.noaa.ncdc:C00040 1831-02-01 2015-01-01          Annual Summaries
#> 2  gov.noaa.ncdc:C00861 1763-01-01 2015-07-06           Daily Summaries
#> 3  gov.noaa.ncdc:C00841 1763-01-01 2015-06-01         Monthly Summaries
#> 4  gov.noaa.ncdc:C00345 1991-06-05 2015-07-07  Weather Radar (Level II)
#> 5  gov.noaa.ncdc:C00708 1994-05-20 2015-07-03 Weather Radar (Level III)
#> 6  gov.noaa.ncdc:C00821 2010-01-01 2010-01-01   Normals Annual/Seasonal
#> 7  gov.noaa.ncdc:C00823 2010-01-01 2010-12-31             Normals Daily
#> 8  gov.noaa.ncdc:C00824 2010-01-01 2010-12-31            Normals Hourly
#> 9  gov.noaa.ncdc:C00822 2010-01-01 2010-12-01           Normals Monthly
#> 10 gov.noaa.ncdc:C00505 1970-05-12 2014-01-01   Precipitation 15 Minute
#> 11 gov.noaa.ncdc:C00313 1900-01-01 2014-01-01      Precipitation Hourly
#> Variables not shown: datacoverage (dbl), id (chr)
#> 
#> attr(,"class")
#> [1] "ncdc_datasets"

Get data category data and metadata

ncdc_datacats(locationid='CITY:US390029')
#> $meta
#> $meta$totalCount
#> [1] 37
#> 
#> $meta$pageCount
#> [1] 25
#> 
#> $meta$offset
#> [1] 1
#> 
#> 
#> $data
#> Source: local data frame [25 x 2]
#> 
#>                     name      id
#> 1    Annual Agricultural  ANNAGR
#> 2     Annual Degree Days   ANNDD
#> 3   Annual Precipitation ANNPRCP
#> 4     Annual Temperature ANNTEMP
#> 5    Autumn Agricultural   AUAGR
#> 6     Autumn Degree Days    AUDD
#> 7   Autumn Precipitation  AUPRCP
#> 8     Autumn Temperature  AUTEMP
#> 9               Computed    COMP
#> 10 Computed Agricultural COMPAGR
#> ..                   ...     ...
#> 
#> attr(,"class")
#> [1] "ncdc_datacats"

Tornado data

The function tornadoes() simply gets all the data. So the call takes a while, but once done, is fun to play with.

shp <- tornadoes()
#> OGR data source with driver: ESRI Shapefile 
#> Source: "/Users/sacmac/.rnoaa/tornadoes/tornadoes", layer: "tornado"
#> with 57988 features and 21 fields
#> Feature type: wkbLineString with 2 dimensions
library('sp')
plot(shp)

HOMR metadata

In this example, search for metadata for a single station ID

homr(qid = 'COOP:046742')
#> $`20002078`
#> $`20002078`$id
#> [1] "20002078"
#> 
#> $`20002078`$head
#>                  preferredName latitude_dec longitude_dec precision
#> 1 PASO ROBLES MUNICIPAL AP, CA      35.6697     -120.6283    DDMMSS
#>             por.beginDate por.endDate
#> 1 1949-10-05T00:00:00.000     Present
#> 
#> $`20002078`$namez
#> Source: local data frame [3 x 2]
#> 
#>                         name  nameType
#> 1   PASO ROBLES MUNICIPAL AP      COOP
#> 2   PASO ROBLES MUNICIPAL AP PRINCIPAL
#> 3 PASO ROBLES MUNICIPAL ARPT       PUB
#> 
#> $`20002078`$identifiers
#> Source: local data frame [8 x 2]
#> 
#>      idType          id
#> 1     GHCND USW00093209
#> 2   GHCNMLT USW00093209
#> 3      COOP      046742
#> 4      WBAN       93209
#> 5       FAA         PRB
#> 6      ICAO        KPRB
#> 7     NWSLI         PRB
#> 8 NCDCSTNID    20002078
#> 
#> $`20002078`$status
#> NULL
#> 
#> $`20002078`$platform
#> [1] "COOP"
#> 
#> $`20002078`$relocations
#>   relocation                    date
#> 1 5.1 mi NNE 1949-10-05T00:00:00.000
#> 
#> $`20002078`$remarks
#> Source: local data frame [3 x 2]
#> 
#>                         type
#> 1            NWS COOP INGEST
#> 2                    GENERAL
#> 3 RIVER BASIN (COOP NETWORK)
#> Variables not shown: remark (chr)
#> 
#> $`20002078`$updates
#>             effectiveDate    providedBy updateSource version
#> 1 2014-08-14T00:00:00.000 NCDC\\KTHOMAS       AD HOC    NONE
#>                                                                                       description
#> 1 ADDING ANEMOMETER HEIGHTS FROM NWS SURFACE OBSERVATIONS PROGRAM LISTING DATED FEBRUARY 11, 2009
#>   enteredBy               enteredDate modifiedBy              modifiedDate
#> 1   KTHOMAS 2014-08-14T10:07:52-04:00   SMCNEILL 2014-09-24T14:56:23-04:00
#> 
#> $`20002078`$elements
#> Source: local data frame [4 x 15]
#> 
#>   dataProgram element frequency observationTime publishedFlag receiver
#> 1    COOP HPD  PRECIP    HOURLY            2400           HPD     NCDC
#> 2    COOP SOD  PRECIP     DAILY            2400            CD     NCDC
#> 3    COOP SOD    TEMP     DAILY            2400            CD     NCDC
#> 4    COOP SOD    WIND    HOURLY            UNKN            NA       NA
#> Variables not shown: reportingMethod (chr), equipment.equipment (chr),
#>   equipment.equipmentMods (chr), equipment.equipmentAzimuth (chr),
#>   equipment.equipmentDistance (chr), equipment.equipmentDistanceUnits
#>   (chr), date.beginDate (chr), date.endDate (chr), equipment (chr)
#> 
#> $`20002078`$location
#> $`20002078`$location$id
#> [1] "20002078"
#> 
#> $`20002078`$location$description
#> Source: local data frame [1 x 1]
#> 
#>                                                                   description
#> 1 PASO ROBLES MUNICIPAL AIRPORT OUTSIDE AND 5 MILES NE OF PO AT PASO ROBLES C
#> 
#> $`20002078`$location$latlon
#>   latitude_dec longitude_dec latitude_dms longitude_dms precision
#> 1      35.6697     -120.6283   35,40,11,N   120,37,42,W    DDMMSS
#>   datum_horiz           source
#> 1       NAD83 ASOS SITE SURVEY
#> 
#> $`20002078`$location$elevation
#>   elevationType elevationFeet elevationMeters groundElevDatum
#> 1        GROUND           810           246.9          NAVD88
#> 
#> $`20002078`$location$topography
#>                   description 
#> "LEVEL VALLEY LOCATION (S-N)" 
#> 
#> $`20002078`$location$obstructions
#> Source: local data frame [1 x 1]
#> 
#>                   description
#> 1 HYGR 090/04 NO OBSTRUCTIONS
#> 
#> $`20002078`$location$geoinfo
#>   ncdstnId       country state          county utcoffset
#> 1 20002078 UNITED STATES    CA SAN LUIS OBISPO        -8
#> 
#> $`20002078`$location$nwsinfo
#>   ncdstnId climateDivisions.stateProvince climateDivisions.climateDivision
#> 1 20002078                             CA                               04
#>   climateDivisions.displayName nwsRegion nwsWfos.nwsWfo
#> 1       Central Coast Drainage   WESTERN            LOX
#>   nwsWfos.displayName
#> 1     LOS ANGELES, CA
#> 
#> 
#> 
#> attr(,"class")
#> [1] "homr"
#> attr(,"combined")
#> [1] FALSE

Storm data

Get storm data for the year 2010

storm_data(year=2010)
#> <NOAA Storm Data>
#> Size: 2855 X 195
#> 
#>       serial_num season num basin sub_basin name            iso_time
#> 1  2009317S10073   2010   1    SI        MM ANJA 2009-11-13 06:00:00
#> 2  2009317S10073   2010   1    SI        MM ANJA 2009-11-13 12:00:00
#> 3  2009317S10073   2010   1    SI        MM ANJA 2009-11-13 18:00:00
#> 4  2009317S10073   2010   1    SI        MM ANJA 2009-11-14 00:00:00
#> 5  2009317S10073   2010   1    SI        MM ANJA 2009-11-14 06:00:00
#> 6  2009317S10073   2010   1    SI        MM ANJA 2009-11-14 12:00:00
#> 7  2009317S10073   2010   1    SI        MM ANJA 2009-11-14 18:00:00
#> 8  2009317S10073   2010   1    SI        MM ANJA 2009-11-15 00:00:00
#> 9  2009317S10073   2010   1    SI        MM ANJA 2009-11-15 06:00:00
#> 10 2009317S10073   2010   1    SI        MM ANJA 2009-11-15 12:00:00
#> ..           ...    ... ...   ...       ...  ...                 ...
#> Variables not shown: nature (chr), latitude (dbl), longitude (dbl),
#>      wind.wmo. (dbl), pres.wmo. (dbl), center (chr), wind.wmo..percentile
#>      (dbl), pres.wmo..percentile (dbl), track_type (chr),
#>      latitude_for_mapping (dbl), longitude_for_mapping (dbl),
#>      current.basin (chr), hurdat_atl_lat (dbl), hurdat_atl_lon (dbl),
#>      hurdat_atl_grade (dbl), hurdat_atl_wind (dbl), hurdat_atl_pres (dbl),
#>      td9636_lat (dbl), td9636_lon (dbl), td9636_grade (dbl), td9636_wind
#>      (dbl), td9636_pres (dbl), reunion_lat (dbl), reunion_lon (dbl),
#>      reunion_grade (dbl), reunion_wind (dbl), reunion_pres (dbl), atcf_lat
#>      (dbl), atcf_lon (dbl), atcf_grade (dbl), atcf_wind (dbl), atcf_pres
#>      (dbl), ds824_sh_lat (dbl), ds824_sh_lon (dbl), ds824_sh_grade (dbl),
#>      ds824_sh_wind (dbl), ds824_sh_pres (dbl), ds824_ni_lat (dbl),
#>      ds824_ni_lon (dbl), ds824_ni_grade (dbl), ds824_ni_wind (dbl),
#>      ds824_ni_pres (dbl), bom_lat (dbl), bom_lon (dbl), bom_grade (dbl),
#>      bom_wind (dbl), bom_pres (dbl), ds824_au_lat (dbl), ds824_au_lon
#>      (dbl), ds824_au_grade (dbl), ds824_au_wind (dbl), ds824_au_pres
#>      (dbl), jtwc_sh_lat (dbl), jtwc_sh_lon (dbl), jtwc_sh_grade (dbl),
#>      jtwc_sh_wind (dbl), jtwc_sh_pres (dbl), jtwc_wp_lat (dbl),
#>      jtwc_wp_lon (dbl), jtwc_wp_grade (dbl), jtwc_wp_wind (dbl),
#>      jtwc_wp_pres (dbl), td9635_lat (dbl), td9635_lon (dbl), td9635_grade
#>      (dbl), td9635_wind (dbl), td9635_pres (dbl), ds824_wp_lat (dbl),
#>      ds824_wp_lon (dbl), ds824_wp_grade (dbl), ds824_wp_wind (dbl),
#>      ds824_wp_pres (dbl), jtwc_io_lat (dbl), jtwc_io_lon (dbl),
#>      jtwc_io_grade (dbl), jtwc_io_wind (dbl), jtwc_io_pres (dbl), cma_lat
#>      (dbl), cma_lon (dbl), cma_grade (dbl), cma_wind (dbl), cma_pres
#>      (dbl), hurdat_epa_lat (dbl), hurdat_epa_lon (dbl), hurdat_epa_grade
#>      (dbl), hurdat_epa_wind (dbl), hurdat_epa_pres (dbl), jtwc_ep_lat
#>      (dbl), jtwc_ep_lon (dbl), jtwc_ep_grade (dbl), jtwc_ep_wind (dbl),
#>      jtwc_ep_pres (dbl), ds824_ep_lat (dbl), ds824_ep_lon (dbl),
#>      ds824_ep_grade (dbl), ds824_ep_wind (dbl), ds824_ep_pres (dbl),
#>      jtwc_cp_lat (dbl), jtwc_cp_lon (dbl), jtwc_cp_grade (dbl),
#>      jtwc_cp_wind (dbl), jtwc_cp_pres (dbl), tokyo_lat (dbl), tokyo_lon
#>      (dbl), tokyo_grade (dbl), tokyo_wind (dbl), tokyo_pres (dbl),
#>      neumann_lat (dbl), neumann_lon (dbl), neumann_grade (dbl),
#>      neumann_wind (dbl), neumann_pres (dbl), hko_lat (dbl), hko_lon (dbl),
#>      hko_grade (dbl), hko_wind (dbl), hko_pres (dbl), cphc_lat (dbl),
#>      cphc_lon (dbl), cphc_grade (dbl), cphc_wind (dbl), cphc_pres (dbl),
#>      wellington_lat (dbl), wellington_lon (dbl), wellington_grade (dbl),
#>      wellington_wind (dbl), wellington_pres (dbl), newdelhi_lat (dbl),
#>      newdelhi_lon (dbl), newdelhi_grade (dbl), newdelhi_wind (dbl),
#>      newdelhi_pres (dbl), nadi_lat (dbl), nadi_lon (dbl), nadi_grade
#>      (dbl), nadi_wind (dbl), nadi_pres (dbl), reunion_rmw (dbl),
#>      reunion_wind_radii_1_ne (dbl), reunion_wind_radii_1_se (dbl),
#>      reunion_wind_radii_1_sw (dbl), reunion_wind_radii_1_nw (dbl),
#>      reunion_wind_radii_2_ne (dbl), reunion_wind_radii_2_se (dbl),
#>      reunion_wind_radii_2_sw (dbl), reunion_wind_radii_2_nw (dbl),
#>      bom_mn_hurr_xtnt (dbl), bom_mn_gale_xtnt (dbl), bom_mn_eye_diam
#>      (dbl), bom_roci (dbl), atcf_rmw (dbl), atcf_poci (dbl), atcf_roci
#>      (dbl), atcf_eye (dbl), atcf_wrad34_rad1 (dbl), atcf_wrad34_rad2
#>      (dbl), atcf_wrad34_rad3 (dbl), atcf_wrad34_rad4 (dbl),
#>      atcf_wrad50_rad1 (dbl), atcf_wrad50_rad2 (dbl), atcf_wrad50_rad3
#>      (dbl), atcf_wrad50_rad4 (dbl), atcf_wrad64_rad1 (dbl),
#>      atcf_wrad64_rad2 (dbl), atcf_wrad64_rad3 (dbl), atcf_wrad64_rad4
#>      (dbl), tokyo_dir50 (dbl), tokyo_long50 (dbl), tokyo_short50 (dbl),
#>      tokyo_dir30 (dbl), tokyo_long30 (dbl), tokyo_short30 (dbl),
#>      jtwc_.._rmw (dbl), jtwc_.._poci (dbl), jtwc_.._roci (dbl),
#>      jtwc_.._eye (dbl), jtwc_.._wrad34_rad1 (dbl), jtwc_.._wrad34_rad2
#>      (dbl), jtwc_.._wrad34_rad3 (dbl), jtwc_.._wrad34_rad4 (dbl),
#>      jtwc_.._wrad50_rad1 (dbl), jtwc_.._wrad50_rad2 (dbl),
#>      jtwc_.._wrad50_rad3 (dbl), jtwc_.._wrad50_rad4 (dbl),
#>      jtwc_.._wrad64_rad1 (dbl), jtwc_.._wrad64_rad2 (dbl),
#>      jtwc_.._wrad64_rad3 (dbl), jtwc_.._wrad64_rad4 (dbl)

Meta

• Please report any issues or bugs.
• License: MIT
• Get citation information for rnoaa in R doing citation(package = 'rnoaa')