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.

Dataset	Description	Start date	End date
ANNUAL	Annual Summaries	1831-02-01	2013-11-01
GHCND	Daily Summaries	1763-01-01	2014-03-15
GHCNDMS	Monthly Summaries	1763-01-01	2014-01-01
NORMAL_ANN	Normals Annual/Seasonal	2010-01-01	2010-01-01
NORMAL_DLY	Normals Daily	2010-01-01	2010-12-31
NORMAL_HLY	Normals Hourly	2010-01-01	2010-12-31
NORMAL_MLY	Normals Monthly	2010-01-01	2010-12-01
PRECIP_15	Precipitation 15 Minute	1970-05-12	2013-03-01
PRECIP_HLY	Precipitation Hourly	1900-01-01	2013-03-01
NEXRAD2	Nexrad Level II	1991-06-05	2014-03-14
NEXRAD3	Nexrad Level III	1994-05-20	2014-03-11

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

install.packages("devtools")
devtools::install_github("ropensci/rnoaa")
library('rnoaa')

or version with buoy functions on Github

install.packages("devtools")
devtools::install_github("ropensci/rnoaa", ref="buoy")

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] 1657
#> 
#> $meta$pageCount
#> [1] 25
#> 
#> $meta$offset
#> [1] 1
#> 
#> 
#> $data
#>       mindate    maxdate                  name datacoverage            id
#> 1  1892-08-01 2015-05-31            Zwolle, NL       1.0000 CITY:NL000012
#> 2  1901-01-01 2015-06-15            Zurich, SZ       1.0000 CITY:SZ000007
#> 3  1906-01-01 1980-12-31            Zinder, NG       0.8678 CITY:NG000004
#> 4  1938-01-01 2015-06-15         Zhytomyra, UP       0.9731 CITY:UP000025
#> 5  1948-03-01 2015-06-15        Zhezkazgan, KZ       0.9294 CITY:KZ000017
#> 6  1951-01-01 2015-06-15         Zhengzhou, CH       1.0000 CITY:CH000045
#> 7  1941-01-01 2014-12-22          Zaragoza, SP       1.0000 CITY:SP000021
#> 8  1936-01-01 2009-06-16      Zaporiyhzhya, UP       0.9739 CITY:UP000024
#> 9  1893-01-01 2015-06-18     Zanesville, OH US       1.0000 CITY:US390029
#> 10 1912-01-01 1971-12-31             Zahle, LE       0.7972 CITY:LE000004
#> 11 1951-01-01 2010-05-19           Zahedan, IR       0.9930 CITY:IR000019
#> 12 1860-12-01 2013-12-31            Zagreb, HR       1.0000 CITY:HR000002
#> 13 1947-01-01 2015-05-30 Yuzhno-Sakhalinsk, RS       1.0000 CITY:RS000081
#> 14 1893-01-01 2015-06-18           Yuma, AZ US       1.0000 CITY:US040015
#> 15 1942-02-01 2015-06-18   Yucca Valley, CA US       1.0000 CITY:US060048
#> 16 1893-01-01 2015-06-18      Yuba City, CA US       1.0000 CITY:US060047
#> 17 1893-01-01 2015-06-18     Youngstown, OH US       1.0000 CITY:US390028
#> 18 1941-01-01 2015-06-18           York, PA US       1.0000 CITY:US420024
#> 19 1876-01-01 2015-06-18        Yonkers, NY US       1.0000 CITY:US360031
#> 20 1949-01-01 2015-06-15          Yokohama, JA       1.0000 CITY:JA000017
#> 21 1951-01-01 2015-06-15          Yinchuan, CH       1.0000 CITY:CH000044
#> 22 1885-06-01 2015-06-15           Yerevan, AM       0.9751 CITY:AM000001
#> 23 1948-01-01 2015-06-18     Yazoo City, MS US       1.0000 CITY:US280020
#> 24 1959-07-01 1987-05-20         Yaroslavl, RS       0.9850 CITY:RS000080
#> 25 1932-01-01 2015-06-18        Yankton, SD US       1.0000 CITY:US460009
#> 
#> 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 2015-06-16  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 )
#>                  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
#>                     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 2015-06-17           Daily Summaries
#> 3  gov.noaa.ncdc:C00841 1763-01-01 2015-05-01         Monthly Summaries
#> 4  gov.noaa.ncdc:C00345 1991-06-05 2015-06-18  Weather Radar (Level II)
#> 5  gov.noaa.ncdc:C00708 1994-05-20 2015-06-14 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
#>    datacoverage         id
#> 1          1.00     ANNUAL
#> 2          1.00      GHCND
#> 3          1.00    GHCNDMS
#> 4          0.95    NEXRAD2
#> 5          0.95    NEXRAD3
#> 6          1.00 NORMAL_ANN
#> 7          1.00 NORMAL_DLY
#> 8          1.00 NORMAL_HLY
#> 9          1.00 NORMAL_MLY
#> 10         0.25  PRECIP_15
#> 11         1.00 PRECIP_HLY
#> 
#> 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
#>                     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
#> 11           Degree Days            DD
#> 12      Dual-Pol Moments DUALPOLMOMENT
#> 13             Echo Tops       ECHOTOP
#> 14      Hydrometeor Type   HYDROMETEOR
#> 15                 Other         OTHER
#> 16               Overlay       OVERLAY
#> 17         Precipitation          PRCP
#> 18          Reflectivity  REFLECTIVITY
#> 19    Sky cover & clouds           SKY
#> 20   Spring Agricultural         SPAGR
#> 21    Spring Degree Days          SPDD
#> 22  Spring Precipitation        SPPRCP
#> 23    Spring Temperature        SPTEMP
#> 24   Summer Agricultural         SUAGR
#> 25    Summer Degree Days          SUDD
#> 
#> 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
#> It has 21 fields
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
#>                         name  nameType
#> 1   PASO ROBLES MUNICIPAL AP      COOP
#> 2   PASO ROBLES MUNICIPAL AP PRINCIPAL
#> 3 PASO ROBLES MUNICIPAL ARPT       PUB
#> 
#> $`20002078`$identifiers
#>      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
#>                         type
#> 1            NWS COOP INGEST
#> 2                    GENERAL
#> 3 RIVER BASIN (COOP NETWORK)
#>                                                                                                                                                                                                                                                                                remark
#> 1                                                                                                                                                                          REQUIRED 5 YEAR UPDATE\r\nASOS COMMISSIONED 01/18/2001\r\nSERVICE LEVEL "D" ASOS MAINTAINED BY LOX NWS ETS
#> 2 PHOTOS ADDED FOR ASOS EXPOSURE DOCUMENTATION EFFORT (CIRCA 1999+) WHICH TOOK PHOTOS OF THE AREA SURROUNDING COASTAL AND INLAND ASOS SITES IN AREAS SUBJECT TO HURRICANES. THE PHOTOS HELP DOCUMENT STATION EXPOSURE AND IDENTIFY OBSTACLES THAT COULD REDUCE THE WINDS AT THE SITE.
#> 3                                                                                                                                                                                                                                                                             SALINAS
#> 
#> $`20002078`$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
#>   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>
#>   reportingMethod equipment.equipment equipment.equipmentMods
#> 1             ADP                AHTB                RCRD;HTD
#> 2             ADP               PCPNX                    <NA>
#> 3             ADP               TEMPX                    <NA>
#> 4            <NA>                <NA>                    <NA>
#>   equipment.equipmentAzimuth equipment.equipmentDistance
#> 1                        000                           0
#> 2                        000                           0
#> 3                        090                           4
#> 4                       <NA>                        <NA>
#>   equipment.equipmentDistanceUnits          date.beginDate date.endDate
#> 1                               ft 2010-02-11T00:00:00.000      Present
#> 2                               ft 2010-02-11T00:00:00.000      Present
#> 3                               ft 2010-02-11T00:00:00.000      Present
#> 4                             <NA> 2010-02-11T00:00:00.000      Present
#>   equipment
#> 1      <NA>
#> 2      <NA>
#> 3      <NA>
#> 4 ANEMSONIC
#> 
#> $`20002078`$location
#> $`20002078`$location$id
#> [1] "20002078"
#> 
#> $`20002078`$location$description
#>                                                                    description
#> 1 PASO ROBLES MUNICIPAL AIRPORT OUTSIDE AND 5 MILES NE OF PO AT PASO ROBLES CA
#> 
#> $`20002078`$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
#>                   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)

rnoaa

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Data sources used in rnoaa

netcdf data

NOAA NCDC Datasets

NOAA NCDC Attributes

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NCDC v2 API data

Fetch list of city locations in descending order

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

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See a data.frame

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

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Get table of all datasets

Get data category data and metadata

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Storm data

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Functions in rnoaa (0.4.0)