SWDI vignette

SWDI is the Severe Weather Data Inventory. SWDI is an

integrated database of severe weather records for the United States. The records in SWDI come from a variety of sources in the NCDC archive. SWDI provides the ability to search through all of these data to find records covering a particular time period and geographic region, and to download the results of your search in a variety of formats. The formats currently supported are Shapefile (for GIS), KMZ (for Google Earth), CSV (comma-separated), and XML.

Data available in SWDI are:

• Storm Cells from NEXRAD (Level-III Storm Structure Product)
• Hail Signatures from NEXRAD (Level-III Hail Product)
• Mesocyclone Signatures from NEXRAD (Level-III Meso Product)
• Digital Mesocyclone Detection Algorithm from NEXRAD (Level-III MDA Product)
• Tornado Signatures from NEXRAD (Level-III TVS Product)
• Preliminary Local Storm Reports from the NOAA National Weather Service
• Lightning Strikes from Vaisala NLDN

Find out more about SWDI at http://www.ncdc.noaa.gov/swdi/#Intro and the API at http://www.ncdc.noaa.gov/swdiws/.

Install rnoaa

Install and load rnoaa into the R session.

If you're on Windows, you may have to install Rtools. Run devtools::has_devel(). If you get a TRUE, you're okay. If not, install Rtools.

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

library('rnoaa')
library('plyr')

Search for nx3tvs data from 5 May 2006 to 6 May 2006

swdi(dataset='nx3tvs', startdate='20060505', enddate='20060506')

## $meta
## $meta$totalCount
## [1] 25
## 
## $meta$totalTimeInSeconds
## [1] 0.069
## 
## 
## $data
##                   ztime wsr_id cell_id cell_type range azimuth max_shear
## 1  2006-05-05T00:05:50Z   KBMX      Q0       TVS     7     217       403
## 2  2006-05-05T00:10:02Z   KBMX      Q0       TVS     5     208       421
## 3  2006-05-05T00:12:34Z   KSJT      P2       TVS    49     106        17
## 4  2006-05-05T00:17:31Z   KSJT      B4       TVS    40     297        25
## 5  2006-05-05T00:29:13Z   KMAF      H4       TVS    53     333        34
## 6  2006-05-05T00:31:25Z   KLBB      N0       TVS    51     241        24
## 7  2006-05-05T00:33:25Z   KMAF      H4       TVS    52     334        46
## 8  2006-05-05T00:37:37Z   KMAF      H4       TVS    50     334        34
## 9  2006-05-05T00:41:51Z   KMAF      H4       TVS    51     335        29
## 10 2006-05-05T00:44:33Z   KLBB      N0       TVS    46     245        35
## 11 2006-05-05T00:46:03Z   KMAF      H4       TVS    49     335        41
## 12 2006-05-05T00:48:55Z   KLBB      N0       TVS    44     246        44
## 13 2006-05-05T00:50:16Z   KMAF      H4       TVS    49     337        33
## 14 2006-05-05T00:54:29Z   KMAF      H4       TVS    47     337        42
## 15 2006-05-05T00:57:42Z   KLBB      N0       TVS    41     251        46
## 16 2006-05-05T00:58:41Z   KMAF      H4       TVS    46     340        29
## 17 2006-05-05T01:02:04Z   KLBB      N0       TVS    39     251        42
## 18 2006-05-05T01:02:53Z   KMAF      H4       TVS    46     339        35
## 19 2006-05-05T01:02:53Z   KMAF      H4       TVS    50     338        27
## 20 2006-05-05T01:06:26Z   KLBB      N0       TVS    36     251        31
## 21 2006-05-05T01:07:06Z   KMAF      F5       TVS    45     342        44
## 22 2006-05-05T01:10:48Z   KLBB      N0       TVS    36     256        37
## 23 2006-05-05T01:11:18Z   KMAF      F5       TVS    45     343        39
## 24 2006-05-05T01:15:30Z   KMAF      F5       TVS    44     344        30
## 25 2006-05-05T01:15:30Z   KMAF      H4       TVS    49     341        26
##    mxdv
## 1   116
## 2   120
## 3    52
## 4    62
## 5   111
## 6    78
## 7   145
## 8   107
## 9    91
## 10  100
## 11  127
## 12  121
## 13   98
## 14  126
## 15  117
## 16   85
## 17  102
## 18  101
## 19   84
## 20   70
## 21  120
## 22   83
## 23  108
## 24   78
## 25   81
## 
## $shape
##                                         shape
## 1  POINT (-86.8535716274277 33.0786326913943)
## 2  POINT (-86.8165772540846 33.0982820681588)
## 3  POINT (-99.5771091971025 31.1421609654838)
## 4   POINT (-101.188161700093 31.672392833416)
## 5  POINT (-102.664426480293 32.7306917937698)
## 6   POINT (-102.70047613441 33.2380072329615)
## 7    POINT (-102.6393683028 32.7226656893341)
## 8  POINT (-102.621904684258 32.6927081076156)
## 9   POINT (-102.614794815627 32.714139844846)
## 10 POINT (-102.643380529494 33.3266446067682)
## 11 POINT (-102.597961935071 32.6839260102062)
## 12 POINT (-102.613894688178 33.3526192273658)
## 13 POINT (-102.567153417051 32.6956373348052)
## 14  POINT (-102.551596970251 32.664939580306)
## 15 POINT (-102.586119971014 33.4287323151248)
## 16 POINT (-102.499638479193 32.6644438090742)
## 17   POINT (-102.5485490063 33.4398330734778)
## 18  POINT (-102.51446954228 32.6597119240996)
## 19 POINT (-102.559031583693 32.7166090376869)
## 20 POINT (-102.492174522228 33.4564626989719)
## 21 POINT (-102.463540844324 32.6573739036181)
## 22 POINT (-102.510349454162 33.5066366303981)
## 23 POINT (-102.448763863447 32.6613484943994)
## 24   POINT (-102.42842159557 32.649061124799)
## 25 POINT (-102.504158884526 32.7162751126854)
## 
## attr(,"class")
## [1] "swdi"

Get all 'nx3tvs' within 15 miles of latitude = 32.7 and longitude = -102.0

out <- swdi(dataset='nx3tvs', startdate='20060506', enddate='20060507', radius=15, center=c(-102.0,32.7))
list(out$meta, head(out$data), head(out$shape))

## [[1]]
## [[1]]$totalCount
## [1] 25
## 
## [[1]]$totalTimeInSeconds
## [1] 0.169
## 
## 
## [[2]]
##                  ztime wsr_id cell_id cell_type range azimuth max_shear
## 1 2006-05-06T04:04:44Z   KMAF      N4       TVS    41       8        24
## 2 2006-05-06T04:08:57Z   KMAF      N4       TVS    39      12        44
## 3 2006-05-06T03:56:18Z   KMAF      N4       TVS    42       4        20
## 4 2006-05-06T02:32:04Z   KMAF      V4       TVS    39      14        35
## 5 2006-05-06T00:51:54Z   KLBB      S9       TVS    52     184        16
## 6 2006-05-06T04:17:21Z   KMAF      N4       TVS    40      18        37
##   mxdv distance_miles
## 1   62          7.049
## 2  107          8.477
## 3   52          8.607
## 4   86          8.664
## 5   52          9.008
## 6   94          9.021
## 
## [[3]]
##                                        shape
## 1 POINT (-102.076389686189 32.6209390786829)
## 2 POINT (-102.029048513806 32.5799228605874)
## 3 POINT (-102.131167022161 32.6426287452898)
## 4 POINT (-102.002894068974 32.5747739667869)
## 5 POINT (-101.885715970289 32.7878721133706)
## 6 POINT (-101.945174931111 32.5780288736632)

Use an id

out <- swdi(dataset='warn', startdate='20060506', enddate='20060507', id=533623)
list(out$meta, head(out$data), head(out$shape))

## [[1]]
## [[1]]$totalCount
## [1] 25
## 
## [[1]]$totalTimeInSeconds
## [1] 2.405
## 
## 
## [[2]]
##            ztime_start            ztime_end     id         warningtype
## 1 2006-05-05T22:53:00Z 2006-05-06T00:00:00Z 397428 SEVERE THUNDERSTORM
## 2 2006-05-05T22:55:00Z 2006-05-06T00:00:00Z 397429 SEVERE THUNDERSTORM
## 3 2006-05-05T22:55:00Z 2006-05-06T00:00:00Z 397430 SEVERE THUNDERSTORM
## 4 2006-05-05T22:57:00Z 2006-05-06T00:00:00Z 397431 SEVERE THUNDERSTORM
## 5 2006-05-05T23:03:00Z 2006-05-06T00:00:00Z 397434 SEVERE THUNDERSTORM
## 6 2006-05-05T23:14:00Z 2006-05-06T00:15:00Z 397437 SEVERE THUNDERSTORM
##   issuewfo messageid
## 1     KLCH    052252
## 2     KLUB    052256
## 3     KLUB    052256
## 4     KMAF    052258
## 5     KMAF    052305
## 6     KLUB    052315
## 
## [[3]]
##                                                                                                                                                          shape
## 1                                                                             POLYGON ((-93.27 30.38, -93.29 30.18, -93.02 30.18, -93.04 30.37, -93.27 30.38))
## 2                                                                        POLYGON ((-101.93 34.74, -101.96 34.35, -101.48 34.42, -101.49 34.74, -101.93 34.74))
## 3                POLYGON ((-100.36 33.03, -99.99 33.3, -99.99 33.39, -100.28 33.39, -100.5 33.18, -100.51 33.02, -100.45 32.97, -100.37 33.03, -100.36 33.03))
## 4                                            POLYGON ((-102.8 30.74, -102.78 30.57, -102.15 30.61, -102.15 30.66, -101.92 30.68, -102.07 30.83, -102.8 30.74))
## 5                                                                        POLYGON ((-103.02 32.94, -103.03 32.66, -102.21 32.53, -102.22 32.95, -103.02 32.94))
## 6 POLYGON ((-101.6 33.32, -101.57 33.31, -101.57 33.51, -101.65 33.51, -101.66 33.5, -101.75 33.5, -101.77 33.49, -101.84 33.49, -101.84 33.32, -101.6 33.32))

Get all 'plsr' within the bounding box (-91,30,-90,31)

swdi(dataset='plsr', startdate='20060505', enddate='20060510', bbox=c(-91,30,-90,31))

## $meta
## $meta$totalCount
## [1] 5
## 
## $meta$totalTimeInSeconds
## [1] 0.276
## 
## 
## $data
##                  ztime     id        event magnitude            city
## 1 2006-05-09T02:20:00Z 427540         HAIL         1    5 E KENTWOOD
## 2 2006-05-09T02:40:00Z 427536         HAIL         1    MOUNT HERMAN
## 3 2006-05-09T02:40:00Z 427537 TSTM WND DMG     -9999    MOUNT HERMAN
## 4 2006-05-09T03:00:00Z 427199         HAIL         0     FRANKLINTON
## 5 2006-05-09T03:17:00Z 427200      TORNADO     -9999 5 S FRANKLINTON
##       county state          source
## 1 TANGIPAHOA    LA TRAINED SPOTTER
## 2 WASHINGTON    LA TRAINED SPOTTER
## 3 WASHINGTON    LA TRAINED SPOTTER
## 4 WASHINGTON    LA   AMATEUR RADIO
## 5 WASHINGTON    LA LAW ENFORCEMENT
## 
## $shape
##                  shape
## 1 POINT (-90.43 30.93)
## 2  POINT (-90.3 30.96)
## 3  POINT (-90.3 30.96)
## 4 POINT (-90.14 30.85)
## 5 POINT (-90.14 30.78)
## 
## attr(,"class")
## [1] "swdi"

Get all 'nx3tvs' within the tile -102.1/32.6 (-102.15,32.55,-102.25,32.65)

swdi(dataset='nx3tvs', startdate='20060506', enddate='20060507', tile=c(-102.12,32.62))

## $meta
## $meta$totalCount
## [1] 5
## 
## $meta$totalTimeInSeconds
## [1] 0.014
## 
## 
## $data
##                  ztime wsr_id cell_id cell_type range azimuth max_shear
## 1 2006-05-06T00:41:29Z   KMAF      D9       TVS    37       6        39
## 2 2006-05-06T03:56:18Z   KMAF      N4       TVS    39       3        30
## 3 2006-05-06T03:56:18Z   KMAF      N4       TVS    42       4        20
## 4 2006-05-06T04:00:30Z   KMAF      N4       TVS    38       5        35
## 5 2006-05-06T04:04:44Z   KMAF      N4       TVS    41       8        24
##   mxdv
## 1   85
## 2   73
## 3   52
## 4   86
## 5   62
## 
## $shape
##                                        shape
## 1 POINT (-102.112726356403 32.5574494581267)
## 2  POINT (-102.14873079873 32.5933553250156)
## 3 POINT (-102.131167022161 32.6426287452898)
## 4 POINT (-102.123671677514 32.5751241756203)
## 5 POINT (-102.076389686189 32.6209390786829)
## 
## attr(,"class")
## [1] "swdi"

Counts

Notes:

• stat='count' will only return metadata, nothing in the data or shape slots
• stat='tilesum:…' returns counts in the data slot for each date for that tile, and shape data
• Get number of 'nx3tvs' within 15 miles of latitude = 32.7 and longitude = -102.0

swdi(dataset='nx3tvs', startdate='20060505', enddate='20060516', radius=15, center=c(-102.0,32.7), stat='count')

## $meta
## $meta$totalCount
## [1] 1
## 
## $meta$totalTimeInSeconds
## [1] 0.092
## 
## 
## $data
## [1] "37"
## 
## $shape
## data frame with 0 columns and 1 rows
## 
## attr(,"class")
## [1] "swdi"

Get daily count nx3tvs features on .1 degree grid centered at latitude = 32.7 and longitude = -102.0

swdi(dataset='nx3tvs', startdate='20060505', enddate='20090516', stat='tilesum:-102.0,32.7')

## $meta
## $meta$totalCount
## [1] 5
## 
## $meta$totalTimeInSeconds
## [1] 0.139
## 
## 
## $data
##          day centerlat centerlon fcount
## 1 2007-03-29      32.7      -102      2
## 2 2007-09-07      32.7      -102      1
## 3 2008-05-27      32.7      -102      4
## 4 2008-06-20      32.7      -102      2
## 5 2009-04-11      32.7      -102      1
## 
## $shape
##                                                                                   shape
## 1 POLYGON ((-102.05 32.65, -102.05 32.75, -101.95 32.75, -101.95 32.65, -102.05 32.65))
## 2 POLYGON ((-102.05 32.65, -102.05 32.75, -101.95 32.75, -101.95 32.65, -102.05 32.65))
## 3 POLYGON ((-102.05 32.65, -102.05 32.75, -101.95 32.75, -101.95 32.65, -102.05 32.65))
## 4 POLYGON ((-102.05 32.65, -102.05 32.75, -101.95 32.75, -101.95 32.65, -102.05 32.65))
## 5 POLYGON ((-102.05 32.65, -102.05 32.75, -101.95 32.75, -101.95 32.65, -102.05 32.65))
## 
## attr(,"class")
## [1] "swdi"

Get data in different formats

CSV format

head(swdi(dataset='nx3tvs', startdate='20060505', enddate='20060506', format='csv')$data)

##                  ztime wsr_id cell_id cell_type range azimuth max_shear
## 1 2006-05-05T00:05:50Z   KBMX      Q0       TVS     7     217       403
## 2 2006-05-05T00:10:02Z   KBMX      Q0       TVS     5     208       421
## 3 2006-05-05T00:12:34Z   KSJT      P2       TVS    49     106        17
## 4 2006-05-05T00:17:31Z   KSJT      B4       TVS    40     297        25
## 5 2006-05-05T00:29:13Z   KMAF      H4       TVS    53     333        34
## 6 2006-05-05T00:31:25Z   KLBB      N0       TVS    51     241        24
##   mxdv   lat     lon rownumber
## 1  116 33.08  -86.85         1
## 2  120 33.10  -86.82         2
## 3   52 31.14  -99.58         3
## 4   62 31.67 -101.19         4
## 5  111 32.73 -102.66         5
## 6   78 33.24 -102.70         6

SHP format

swdi(dataset='nx3tvs', startdate='20060505', enddate='20060506', format='shp', filepath='myfile')

## Zip file downloaded to myfile.zip

KMZ format

swdi(dataset='nx3tvs', startdate='20060505', enddate='20060506', format='kmz', radius=15, filepath='myfile.kmz')

## kmz file downloaded to myfile.kmz