Find Stations in or near Toowoomba, Queensland, Australia

GSODR provides lists of weather station locations and elevation values. It’s easy to find all stations in Australia.

library("GSODR")

load(system.file("extdata", "isd_history.rda", package = "GSODR"))

# create data.frame for Australia only
Oz <- subset(isd_history, COUNTRY_NAME == "AUSTRALIA")

Oz

##              STNID                         NAME    LAT   LON CTRY
##    1: 695023-99999          HORN ISLAND   (HID) -10.58 142.3   AS
##    2: 749430-99999           AIDELAIDE RIVER SE -13.30 131.1   AS
##    3: 749432-99999    BATCHELOR FIELD AUSTRALIA -13.05 131.1   AS
##    4: 749438-99999         IRON RANGE AUSTRALIA -12.70 143.3   AS
##    5: 749439-99999     MAREEBA AS/HOEVETT FIELD -17.05 145.4   AS
##   ---                                                            
## 1038: 959890-99999      BICHENO (COUNCIL DEPOT) -41.87 148.3   AS
## 1039: 959950-99999 LORD HOWE ISLAND WINDY POINT -31.53 159.1   AS
## 1040: 959970-99999    HEARD ISLAND (ATLAS COVE) -53.02  73.4   AS
## 1041: 996600-99999          ENVIRONM BUOY 55011 -40.80 144.3   AS
## 1042: 999999-82101               NORTHWEST CAPE -22.33 114.0   AS
##       STATE    BEGIN      END COUNTRY_NAME ISO2C ISO3C
##    1:       19420804 20030816    AUSTRALIA    AU   AUS
##    2:       19430228 19440821    AUSTRALIA    AU   AUS
##    3:       19421231 19430610    AUSTRALIA    AU   AUS
##    4:       19420917 19440930    AUSTRALIA    AU   AUS
##    5:       19420630 19440630    AUSTRALIA    AU   AUS
##   ---                                                 
## 1038:       19650101 20200606    AUSTRALIA    AU   AUS
## 1039:       20120920 20200607    AUSTRALIA    AU   AUS
## 1040:       19980301 20121220    AUSTRALIA    AU   AUS
## 1041:       19930221 19970403    AUSTRALIA    AU   AUS
## 1042:       19680305 19680430    AUSTRALIA    AU   AUS

# Look for a specific town in Australia
subset(Oz, grepl("TOOWOOMBA", NAME))

##           STNID              NAME    LAT   LON CTRY STATE    BEGIN
## 1: 945510-99999         TOOWOOMBA -27.58 151.9   AS       19561231
## 2: 955510-99999 TOOWOOMBA AIRPORT -27.55 151.9   AS       19980301
##         END COUNTRY_NAME ISO2C ISO3C
## 1: 20120503    AUSTRALIA    AU   AUS
## 2: 20200607    AUSTRALIA    AU   AUS

Download a Single Station and Year Using get_GSOD()

Now that we’ve seen where the reporting stations are located, we can download weather data from the station Toowoomba, Queensland, Australia for 2010 by using the STNID in the station parameter of get_GSOD().

tbar <- get_GSOD(years = 2010, station = "955510-99999")
str(tbar)

## Classes 'data.table' and 'data.frame':   365 obs. of  44 variables:
##  $ STNID           : chr  "955510-99999" "955510-99999" "955510-99999" "955510-99999" ...
##  $ NAME            : chr  "TOOWOOMBA AIRPORT" "TOOWOOMBA AIRPORT" "TOOWOOMBA AIRPORT" "TOOWOOMBA AIRPORT" ...
##  $ CTRY            : chr  "AS" "AS" "AS" "AS" ...
##  $ STATE           : chr  "" "" "" "" ...
##  $ LATITUDE        : num  -27.6 -27.6 -27.6 -27.6 -27.6 ...
##  $ LONGITUDE       : num  152 152 152 152 152 ...
##  $ ELEVATION       : num  642 642 642 642 642 642 642 642 642 642 ...
##  $ BEGIN           : int  19980301 19980301 19980301 19980301 19980301 19980301 19980301 19980301 19980301 19980301 ...
##  $ END             : int  20200607 20200607 20200607 20200607 20200607 20200607 20200607 20200607 20200607 20200607 ...
##  $ YEARMODA        : Date, format: "2010-01-01" ...
##  $ YEAR            : int  2010 2010 2010 2010 2010 2010 2010 2010 2010 2010 ...
##  $ MONTH           : int  1 1 1 1 1 1 1 1 1 1 ...
##  $ DAY             : int  1 2 3 4 5 6 7 8 9 10 ...
##  $ YDAY            : int  1 2 3 4 5 6 7 8 9 10 ...
##  $ TEMP            : num  21.2 23.2 21.4 18.9 20.5 21.9 21.3 20.9 21.9 22.3 ...
##  $ TEMP_ATTRIBUTES : chr  " 8" " 8" " 8" " 8" ...
##  $ DEWP            : num  17.9 19.4 18.9 16.4 16.4 18.7 17.4 17.1 16.2 14.9 ...
##  $ DEWP_ATTRIBUTES : chr  " 8" " 8" " 8" " 8" ...
##  $ SLP             : num  1013 1010 1012 1016 1016 ...
##  $ SLP_ATTRIBUTES  : chr  " 8" " 8" " 8" " 8" ...
##  $ STP             : num  942 939 941 944 944 ...
##  $ STP_ATTRIBUTES  : chr  " 8" " 8" " 8" " 8" ...
##  $ VISIB           : num  NA NA 14.3 23.3 NA NA NA NA NA NA ...
##  $ VISIB_ATTRIBUTES: chr  " 0" " 0" " 6" " 4" ...
##  $ WDSP            : num  4.3 3.7 7.6 8.7 7.5 6.3 7.8 7.5 6.8 6.3 ...
##  $ WDSP_ATTRIBUTES : chr  " 8" " 8" " 8" " 8" ...
##  $ MXSPD           : num  6.7 5.1 10.3 10.3 10.8 7.7 8.7 8.7 8.2 7.2 ...
##  $ GUST            : num  NA NA NA NA NA NA NA NA NA NA ...
##  $ MAX             : num  25.8 26.5 28.7 24.1 24.6 26.8 26.1 26.5 27.4 28.7 ...
##  $ MAX_ATTRIBUTES  : chr  NA NA NA NA ...
##  $ MIN             : num  17.8 19.1 19.3 16.9 16.7 17.5 19.1 18.5 17.8 17.7 ...
##  $ MIN_ATTRIBUTES  : chr  NA NA "*" "*" ...
##  $ PRCP            : num  1.5 0.3 19.8 1 0.3 0 0.3 2.5 0 0 ...
##  $ PRCP_ATTRIBUTES : chr  "G" "G" "G" "G" ...
##  $ SNDP            : num  NA NA NA NA NA NA NA NA NA NA ...
##  $ I_FOG           : int  NA NA NA NA NA NA NA NA NA NA ...
##  $ I_RAIN_DRIZZLE  : int  NA NA NA NA NA NA NA NA NA NA ...
##  $ I_SNOW_ICE      : int  NA NA NA NA NA NA NA NA NA NA ...
##  $ I_HAIL          : int  NA NA NA NA NA NA NA NA NA NA ...
##  $ I_THUNDER       : int  NA NA NA NA NA NA NA NA NA NA ...
##  $ I_TORNADO_FUNNEL: int  NA NA NA NA NA NA NA NA NA NA ...
##  $ EA              : num  2 2.2 2.2 1.9 1.9 2.2 2 1.9 1.8 1.7 ...
##  $ ES              : num  2.5 2.8 2.5 2.2 2.4 2.6 2.5 2.5 2.6 2.7 ...
##  $ RH              : num  81.5 79.2 85.7 85.4 77.3 82.1 78.5 78.9 70.1 62.9 ...
##  - attr(*, ".internal.selfref")=<externalptr>

Using nearest_stations() to Download Multiple Stations at Once

Using the nearest_stations() function, you can find stations closest to a given point specified by latitude and longitude in decimal degrees. This can be used to generate a vector to pass along to get_GSOD() and download the stations of interest.

tbar_stations <- nearest_stations(LAT = -27.5598,
                                  LON = 151.9507,
                                  distance = 50)

tbar <- get_GSOD(years = 2010, station = tbar_stations)
str(tbar)

## Classes 'data.table' and 'data.frame':   1095 obs. of  44 variables:
##  $ STNID           : chr  "945520-99999" "945520-99999" "945520-99999" "945520-99999" ...
##  $ NAME            : chr  "OAKEY" "OAKEY" "OAKEY" "OAKEY" ...
##  $ CTRY            : chr  "AS" "AS" "AS" "AS" ...
##  $ STATE           : chr  "" "" "" "" ...
##  $ LATITUDE        : num  -27.4 -27.4 -27.4 -27.4 -27.4 ...
##  $ LONGITUDE       : num  152 152 152 152 152 ...
##  $ ELEVATION       : num  407 407 407 407 407 ...
##  $ BEGIN           : int  19730430 19730430 19730430 19730430 19730430 19730430 19730430 19730430 19730430 19730430 ...
##  $ END             : int  20200607 20200607 20200607 20200607 20200607 20200607 20200607 20200607 20200607 20200607 ...
##  $ YEARMODA        : Date, format: "2010-01-01" ...
##  $ YEAR            : int  2010 2010 2010 2010 2010 2010 2010 2010 2010 2010 ...
##  $ MONTH           : int  1 1 1 1 1 1 1 1 1 1 ...
##  $ DAY             : int  1 2 3 4 5 6 7 8 9 10 ...
##  $ YDAY            : int  1 2 3 4 5 6 7 8 9 10 ...
##  $ TEMP            : num  23.4 26.2 24.5 21.6 22.6 24.7 24 23.3 24.4 25.1 ...
##  $ TEMP_ATTRIBUTES : chr  "16" "16" "16" "16" ...
##  $ DEWP            : num  18.4 19.4 19.4 16.8 16.9 18.7 17.1 17.1 15.7 13.6 ...
##  $ DEWP_ATTRIBUTES : chr  "16" "16" "16" "16" ...
##  $ SLP             : num  1012 1009 1011 1015 1015 ...
##  $ SLP_ATTRIBUTES  : chr  "16" "16" "16" "16" ...
##  $ STP             : num  967 964 966 969 969 ...
##  $ STP_ATTRIBUTES  : chr  "16" "16" "16" "16" ...
##  $ VISIB           : num  NA NA NA NA NA NA NA NA NA NA ...
##  $ VISIB_ATTRIBUTES: chr  " 0" " 0" " 0" " 0" ...
##  $ WDSP            : num  4.3 4.1 6.1 7.5 4.4 4.3 5.8 6.2 5.6 4.5 ...
##  $ WDSP_ATTRIBUTES : chr  "16" "16" "16" "16" ...
##  $ MXSPD           : num  7.2 6.2 8.7 9.8 7.7 6.2 8.2 9.3 7.7 7.2 ...
##  $ GUST            : num  NA NA NA NA NA NA NA NA NA NA ...
##  $ MAX             : num  28.5 31.2 33.6 27.1 27.8 30.4 30 30.5 31.9 33.2 ...
##  $ MAX_ATTRIBUTES  : chr  NA NA NA NA ...
##  $ MIN             : num  19.5 20.5 21.3 18.8 18.4 18.6 20.6 18.6 17.2 16.2 ...
##  $ MIN_ATTRIBUTES  : chr  NA NA "*" "*" ...
##  $ PRCP            : num  0.5 0 3.3 0 0 0 0 0.3 0 0 ...
##  $ PRCP_ATTRIBUTES : chr  "G" "G" "G" "G" ...
##  $ SNDP            : num  NA NA NA NA NA NA NA NA NA NA ...
##  $ I_FOG           : int  NA NA NA NA NA NA NA NA NA NA ...
##  $ I_RAIN_DRIZZLE  : int  NA NA NA NA NA NA NA NA NA NA ...
##  $ I_SNOW_ICE      : int  NA NA NA NA NA NA NA NA NA NA ...
##  $ I_HAIL          : int  NA NA NA NA NA NA NA NA NA NA ...
##  $ I_THUNDER       : int  NA NA NA NA NA NA NA NA NA NA ...
##  $ I_TORNADO_FUNNEL: int  NA NA NA NA NA NA NA NA NA NA ...
##  $ EA              : num  2.1 2.2 2.2 1.9 1.9 2.2 1.9 1.9 1.8 1.6 ...
##  $ ES              : num  2.9 3.4 3.1 2.6 2.7 3.1 3 2.9 3.1 3.2 ...
##  $ RH              : num  73.5 66.2 73.3 74.2 70.2 69.3 65.3 68.2 58.4 48.9 ...
##  - attr(*, ".internal.selfref")=<externalptr>

Plot Maximum and Minimum Temperature Values

Using the first data downloaded for a single station, 955510-99999, plot the temperature for 2010.

library("ggplot2")
library("tidyr")

# Create a dataframe of just the date and temperature values that we want to
# plot
tbar_temps <- tbar[, c("YEARMODA", "TEMP", "MAX", "MIN")]

# Gather the data from wide to long
tbar_temps <-
  pivot_longer(tbar_temps, cols = TEMP:MIN, names_to = "Measurement")

ggplot(data = tbar_temps, aes(x = YEARMODA,
                              y = value,
                              colour = Measurement)) +
  geom_line() +
  scale_color_brewer(type = "qual", na.value = "black") +
  scale_y_continuous(name = "Temperature") +
  scale_x_date(name = "Date") +
  ggtitle(label = "Max, min and mean temperatures for Toowoomba, Qld, AU",
          subtitle = "Data: U.S. NCEI GSOD") +
  theme_classic()

Download and Process Files in Parallel

GSODR supports the future package for parallel processing on varied platforms with the user determining the parallel back end to be used. The most simple way is to use multisession as an argument for future::plan(), which will default to available local cores as workers for the run. This can greatly reduce the time necessary to process GSOD files.

future::plan("multisession")
global <- get_GSOD(years = 2010:2011)

str(global)

## Classes 'data.table' and 'data.frame':   11193950 obs. of  44 variables:
##  $ STNID           : chr  "008260-99999" "008260-99999" "008260-99999" "008260-99999" ...
##  $ NAME            : chr  NA NA NA NA ...
##  $ CTRY            : chr  NA NA NA NA ...
##  $ STATE           : chr  NA NA NA NA ...
##  $ LATITUDE        : num  NA NA NA NA NA NA NA NA NA NA ...
##  $ LONGITUDE       : num  NA NA NA NA NA NA NA NA NA NA ...
##  $ ELEVATION       : num  0 0 0 0 0 0 0 0 0 0 ...
##  $ BEGIN           : int  NA NA NA NA NA NA NA NA NA NA ...
##  $ END             : int  NA NA NA NA NA NA NA NA NA NA ...
##  $ YEARMODA        : Date, format: "2010-01-01" ...
##  $ YEAR            : int  2010 2010 2010 2010 2010 2010 2010 2010 2010 2010 ...
##  $ MONTH           : int  1 1 1 1 1 1 1 1 1 1 ...
##  $ DAY             : int  1 2 3 4 5 6 7 8 9 10 ...
##  $ YDAY            : int  1 2 3 4 5 6 7 8 9 10 ...
##  $ TEMP            : num  0.6 -0.4 -1.9 -2.4 -3.1 -1.2 2.4 -3.2 -5.6 -7.2 ...
##  $ TEMP_ATTRIBUTES : chr  "24" "24" "23" "24" ...
##  $ DEWP            : num  -0.4 -1.1 -4.5 -6.3 -7.8 -6.7 -5.3 -5.9 -11.3 -15.2 ...
##  $ DEWP_ATTRIBUTES : chr  "24" "24" "22" "24" ...
##  $ SLP             : num  NA NA 1021 NA NA ...
##  $ SLP_ATTRIBUTES  : chr  " 0" " 0" " 5" " 0" ...
##  $ STP             : num  NA NA NA NA NA NA NA NA NA NA ...
##  $ STP_ATTRIBUTES  : chr  " 0" " 0" " 0" " 0" ...
##  $ VISIB           : num  11.4 6.1 5.6 15.4 15.1 14.6 10.6 13.7 15.6 16.1 ...
##  $ VISIB_ATTRIBUTES: chr  "24" "24" "23" "24" ...
##  $ WDSP            : num  2.6 4 7.8 6.2 2.4 4.3 4.4 2.6 4.1 2.3 ...
##  $ WDSP_ATTRIBUTES : chr  "24" "24" "23" "24" ...
##  $ MXSPD           : num  6.7 7.7 13.4 9.3 4.6 7.2 11.3 8.2 6.7 5.1 ...
##  $ GUST            : num  10.8 11.3 19.5 14.4 NA 9.3 17 10.8 8.7 7.2 ...
##  $ MAX             : num  4.4 6 12 0 5 10.6 9 0 -3 4 ...
##  $ MAX_ATTRIBUTES  : chr  NA "*" "*" "*" ...
##  $ MIN             : num  -7 -7 -9 -10 -9 -11.7 -6 -9.4 -14 -13 ...
##  $ MIN_ATTRIBUTES  : chr  "*" "*" "*" "*" ...
##  $ PRCP            : num  2.3 0.3 0 0.3 0 NA 1.3 0 0.3 0.3 ...
##  $ PRCP_ATTRIBUTES : chr  "G" "G" "G" "G" ...
##  $ SNDP            : num  NA NA NA NA NA NA NA NA NA NA ...
##  $ I_FOG           : int  1 1 1 1 1 1 1 1 1 1 ...
##  $ I_RAIN_DRIZZLE  : int  NA NA NA NA NA NA NA NA NA NA ...
##  $ I_SNOW_ICE      : int  NA NA NA NA NA NA NA NA NA NA ...
##  $ I_HAIL          : int  NA NA NA NA NA NA NA NA NA NA ...
##  $ I_THUNDER       : int  NA NA NA NA NA NA NA NA NA NA ...
##  $ I_TORNADO_FUNNEL: int  NA NA NA NA NA NA NA NA NA NA ...
##  $ EA              : num  0.6 0.6 0.4 0.4 0.3 0.4 0.4 0.4 0.3 0.2 ...
##  $ ES              : num  0.6 0.6 0.5 0.5 0.5 0.6 0.7 0.5 0.4 0.4 ...
##  $ RH              : num  93 95 82.4 74.6 70 66.2 56.8 81.6 64.2 52.8 ...
##  - attr(*, ".internal.selfref")=<externalptr>

Reformat a List of Local Files

In this example two STATION.csv files are in subdirectories of user’s home directory and are listed for reformatting as a string.

y <- c("~/GSOD/gsod_1960/20049099999.csv",
       "~/GSOD/gsod_1961/20049099999.csv")
x <- reformat_GSOD(file_list = y)

Reformat all Local Files Found in Directory

In this example all STATION.csv files in the sub-folder GSOD/gsod_1960 will be imported and reformatted.

x <- reformat_GSOD(dsn = "~/GSOD/gsod_1960")

WMO Resolution 40. NOAA Policy

Users of these data should take into account the following (from the NCEI website):

“The following data and products may have conditions placed on their international commercial use. They can be used within the U.S. or for non-commercial international activities without restriction. The non-U.S. data cannot be redistributed for commercial purposes. Re-distribution of these data by others must provide this same notification.” WMO Resolution 40. NOAA Policy

Appendix 1: GSODR Final Data Format, Contents and Units

GSODR formatted data include the following fields and units:

• STNID - Station number (WMO/DATSAV3 number) for the location;

• NAME - Unique text identifier;

• CTRY - Country in which the station is located;

• LAT - Latitude. Station dropped in cases where values are < -90 or > 90 degrees or Lat = 0 and Lon = 0;

• LON - Longitude. Station dropped in cases where values are < -180 or > 180 degrees or Lat = 0 and Lon = 0;

• ELEVATION - Elevation in metres;

• YEARMODA - Date in YYYY-mm-dd format;

• YEAR - The year (YYYY);

• MONTH - The month (mm);

• DAY - The day (dd);

• YDAY - Sequential day of year (not in original GSOD);

• TEMP - Mean daily temperature converted to degrees C to tenths. Missing = NA;

• TEMP_ATTRIBUTES - Number of observations used in calculating mean daily temperature;

• DEWP - Mean daily dew point converted to degrees C to tenths. Missing = NA;

• DEWP_ATTRIBUTES - Number of observations used in calculating mean daily dew point;

• SLP - Mean sea level pressure in millibars to tenths. Missing = NA;

• SLP_ATTRIBUTES - Number of observations used in calculating mean sea level pressure;

• STP - Mean station pressure for the day in millibars to tenths. Missing = NA;

• STP_ATTRIBUTES - Number of observations used in calculating mean station pressure;

• VISIB - Mean visibility for the day converted to kilometres to tenths. Missing = NA;

• VISIB_ATTRIBUTES - Number of observations used in calculating mean daily visibility;

• WDSP - Mean daily wind speed value converted to metres/second to tenths. Missing = NA;

• WDSP_ATTRIBUTES - Number of observations used in calculating mean daily wind speed;

• MXSPD - Maximum sustained wind speed reported for the day converted to metres/second to tenths. Missing = NA;

• GUST - Maximum wind gust reported for the day converted to metres/second to tenths. Missing = NA;

• MAX - Maximum temperature reported during the day converted to Celsius to tenths–time of max temp report varies by country and region, so this will sometimes not be the max for the calendar day. Missing = NA;

• MAX_ATTRIBUTES - Blank indicates max temp was taken from the explicit max temp report and not from the ‘hourly’ data. An “*” indicates max temp was derived from the hourly data (i.e., highest hourly or synoptic-reported temperature);

• MIN - Minimum temperature reported during the day converted to Celsius to tenths–time of min temp report varies by country and region, so this will sometimes not be the max for the calendar day. Missing = NA;

• MIN_ATTRIBUTES - Blank indicates max temp was taken from the explicit min temp report and not from the ‘hourly’ data. An “*” indicates min temp was derived from the hourly data (i.e., highest hourly or synoptic-reported temperature);

• PRCP - Total precipitation (rain and/or melted snow) reported during the day converted to millimetres to hundredths; will usually not end with the midnight observation, i.e., may include latter part of previous day. A value of “.00” indicates no measurable precipitation (includes a trace). Missing = NA; Note: Many stations do not report ‘0’ on days with no precipitation– therefore, NA will often appear on these days. For example, a station may only report a 6-hour amount for the period during which rain fell. See FLAGS_PRCP column for source of data;

• PRCP_ATTRIBUTES -

  • A = 1 report of 6-hour precipitation amount;

  • B = Summation of 2 reports of 6-hour precipitation amount;

  • C = Summation of 3 reports of 6-hour precipitation amount;

  • D = Summation of 4 reports of 6-hour precipitation amount;

  • E = 1 report of 12-hour precipitation amount;

  • F = Summation of 2 reports of 12-hour precipitation amount;

  • G = 1 report of 24-hour precipitation amount;

  • H = Station reported ‘0’ as the amount for the day (e.g. from 6-hour reports), but also reported at least one occurrence of precipitation in hourly observations–this could indicate a rrace occurred, but should be considered as incomplete data for the day;

  • I = Station did not report any precipitation data for the day and did not report any occurrences of precipitation in its hourly observations–it’s still possible that precipitation occurred but was not reported;

• SNDP - Snow depth in millimetres to tenths. Missing = NA;

• I_FOG - Indicator for fog, (1 = yes, 0 = no/not reported) for the occurrence during the day;

• I_RAIN_DRIZZLE - Indicator for rain or drizzle, (1 = yes, 0 = no/not reported) for the occurrence during the day;

• I_SNOW_ICE - Indicator for snow or ice pellets, (1 = yes, 0 = no/not reported) for the occurrence during the day;

• I_HAIL - Indicator for hail, (1 = yes, 0 = no/not reported) for the occurrence during the day;

• I_THUNDER - Indicator for thunder, (1 = yes, 0 = no/not reported) for the occurrence during the day;

• I_TORNADO_FUNNEL - Indicator for tornado or funnel cloud, (1 = yes, 0 = no/not reported) for the occurrence during the day;

• EA - Mean daily actual vapour pressure as calculated using improved August-Roche-Magnus approximation (Alduchov and Eskridge 1996). Missing = NA;

• ES - Mean daily saturation vapour pressure as calculated using improved August-Roche-Magnus approximation (Alduchov and Eskridge 1996). Missing = NA;

• RH - Mean daily relative humidity as calculated using improved August-Roche-Magnus approximation (Alduchov and Eskridge 1996). Missing = NA.

Appendix 2: Map of Current GSOD Station Locations