Title:	Interface to Download Meteorological (and Hydrological) Datasets
Version:	1.2.3
Description:	Automatize downloading of meteorological and hydrological data from publicly available repositories: OGIMET (http://ogimet.com/index.phtml.en), University of Wyoming - atmospheric vertical profiling data (http://weather.uwyo.edu/upperair/), Polish Institute of Meteorology and Water Management - National Research Institute (https://danepubliczne.imgw.pl), and National Oceanic & Atmospheric Administration (NOAA). This package also allows for searching geographical coordinates for each observation and calculate distances to the nearest stations.
License:	MIT + file LICENSE
Encoding:	UTF-8
LazyData:	true
RoxygenNote:	7.3.2
Depends:	R (≥ 4.0.0)
Imports:	archive, curl, data.table, httr, stringi, XML
Suggests:	dplyr, knitr, maps, testthat, tidyr, rmarkdown
URL:	https://github.com/bczernecki/climate
BugReports:	https://github.com/bczernecki/climate/issues
VignetteBuilder:	knitr
NeedsCompilation:	no
Packaged:	2025-04-23 12:21:07 UTC; bartosz
Author:	Bartosz Czernecki [aut, cre], Arkadiusz Głogowski [aut], Jakub Nowosad [aut], IMGW-PIB [ctb] (source of the data)
Maintainer:	Bartosz Czernecki <nwp@amu.edu.pl>
Repository:	CRAN
Date/Publication:	2025-04-23 14:50:02 UTC

climate: Interface to Download Meteorological (and Hydrological) Datasets

Description

Automatize downloading of meteorological and hydrological data from publicly available repositories: OGIMET (http://ogimet.com/index.phtml.en), University of Wyoming - atmospheric vertical profiling data (http://weather.uwyo.edu/upperair/), Polish Institute of Meteorology and Water Management - National Research Institute (https://danepubliczne.imgw.pl), and National Oceanic & Atmospheric Administration (NOAA). This package also allows for searching geographical coordinates for each observation and calculate distances to the nearest stations.

Author(s)

Maintainer: Bartosz Czernecki nwp@amu.edu.pl (ORCID)

Authors:

• Arkadiusz Głogowski arkadiusz.glogowski@upwr.edu.pl (ORCID)

• Jakub Nowosad nowosad.jakub@gmail.com (ORCID)

Other contributors:

• IMGW-PIB (source of the data) [contributor]

See Also

Useful links:

• https://github.com/bczernecki/climate

• Report bugs at https://github.com/bczernecki/climate/issues

Examplary CO2 dataset from Mauna Loa Observatory (NOAA dataset)

Description

The object contains pre-downloaded CO2 dataset from Mauna Loa observatory The snapshot was taken 2020/05/05.

Usage

co2_demo

Format

An object of class data.frame with 745 rows and 7 columns.

Value

data.frame with historical CO2 concentrations data(co2_demo) head(co2_demo)

Hydrological data from IMGW

Description

Downloading daily, and monthly hydrological data from the measurement stations available in the danepubliczne.imgw.pl collection

Usage

hydro_imgw(
  interval,
  year,
  coords = FALSE,
  value = "H",
  station = NULL,
  col_names = "short",
  ...
)

Arguments

Value

A data.frame with columns describing the hydrological parameters (e.g. flow, water level) where each row represent a measurement, depending on the interval, at a given hour, month or year. If coords = TRUE additional two columns with geographic coordinates are added.

Examples

  x = hydro_imgw("monthly", year = 1999)
  head(x)

Daily hydrological data

Description

Downloading daily hydrological data from the danepubliczne.imgw.pl collection

Usage

hydro_imgw_daily(
  year,
  coords = FALSE,
  station = NULL,
  col_names = "short",
  allow_failure = TRUE,
  ...
)

Arguments

Value

data.frame with historical hydrological data for the daily time interval

Examples

  daily = hydro_imgw_daily(year = 2000)

Monthly hydrological data

Description

Downloading monthly hydrological data from the danepubliczne.imgw.pl collection

Usage

hydro_imgw_monthly(
  year,
  coords = FALSE,
  station = NULL,
  col_names = "short",
  allow_failure = TRUE,
  ...
)

Arguments

Value

data.frame with historical hydrological data for the monthly summaries

Examples

  monthly = hydro_imgw_monthly(year = 2000)

Shortening column names for hydrological variables

Description

Shortening column names of hydrological parameters to improve the readability of downloaded dataset from the danepubliczne.imgw.pl collection and removing duplicated column names

Usage

hydro_shortening_imgw(data, col_names = "short", remove_duplicates = TRUE)

Arguments

Value

data.frame with shorten names of hydrological parameters

Examples

  monthly = data = hydro_imgw("monthly", year = 1969, col_names = "polish")
  
  if (is.data.frame(monthly)) {
  abbr = hydro_shortening_imgw(data = monthly,
      col_names = "full",
      remove_duplicates = TRUE)
  head(abbr)
  }

Definitions of hydrological parameters used for shortening column names from the danepubliczne.imgw.pl collection

Description

The object contains 3 columns that are currently used for improving readability of the downloaded dataset: fullname, abbr_eng, and fullname_eng

Usage

imgw_hydro_abbrev

Format

The data contains a data.frame with ca. 20 elements described in three ways:

fullname

original column names as downloaded from the repository

abbr_eng

shorten column names with abbreviations derived from the most popular scheme used for meteorological parameters

fullname_eng

detailed description of downloaded meteorological variables

The object is created mostly to be used altogether with the hydro_shortening_imgw() function

Examples

data(imgw_hydro_abbrev)
head(imgw_hydro_abbrev)

Location of the hydrological stations from the danepubliczne.imgw.pl collection

Description

The object contains weather stations coordinates, ID numbers, and elevations

Usage

imgw_hydro_stations

Format

The data contains a data.frame with 1304 obs. of 3 variables:

id

Station ID

X

Longitude

Y

Latitude

The object is in the geographic coordinates using WGS84 (EPSG:4326).

Examples

data(imgw_hydro_stations)
head(imgw_hydro_stations)

Definitions of meteorological parameters used for shortening column names for the meteorological data from the danepubliczne.imgw.pl collection

Description

The object contains 3 columns that are currently used for improving readability of the downloaded dataset: fullname, abbr_eng, and fullname_eng

Usage

imgw_meteo_abbrev

Format

The data contains a data.frame with ca. 250 elements described in three ways:

fullname

original column names as downloaded from the repository

abbr_eng

shorten column names with abbreviations derived from the most popular scheme used for meteorological parameters

fullname_eng

detailed description of downloaded meteorological variables

The object is created mostly to be used altogether with the meteo_shortening_imgw function

Examples

data(imgw_meteo_abbrev)
head(imgw_meteo_abbrev)

Location of the meteorological stations from the danepubliczne.imgw.pl collection

Description

The object contains weather stations coordinates, ID numbers, and elevations

Usage

imgw_meteo_stations

Format

The data contains a data.frame with 1998 obs. of 3 variables:

id

Station ID

X

Longitude

Y

Latitude

station

Station name

id2

IMGW-PIB ID for station rank

The object is in the geographic coordinates using WGS84 (EPSG:4326).

Examples

data(imgw_meteo_stations)
head(imgw_meteo_stations)

Meteorological data from the IMGW-PIB official repository

Description

Downloading hourly, daily, and monthly meteorological data from the SYNOP / CLIMATE / PRECIP stations available in the danepubliczne.imgw.pl collection.

Usage

meteo_imgw(
  interval,
  rank = "synop",
  year,
  status = FALSE,
  coords = FALSE,
  station = NULL,
  col_names = "short",
  ...
)

Arguments

Value

A data.frame with columns describing the meteorological parameters (e.g. temperature, wind speed, precipitation) where each row represent a measurement, depending on the interval, at a given hour, month or year. If coords = TRUE additional two columns with geographic coordinates are added.

Examples

  x = meteo_imgw("monthly", year = 2018, coords = TRUE)
  head(x)

Daily IMGW meteorological data

Description

Downloading daily (meteorological) data from the SYNOP / CLIMATE / PRECIP stations available in the danepubliczne.imgw.pl collection

Usage

meteo_imgw_daily(
  rank = "synop",
  year,
  status = FALSE,
  coords = FALSE,
  station = NULL,
  col_names = "short",
  allow_failure = TRUE,
  ...
)

Arguments

Value

data.frame with a daily meteorological measurements

Examples

  daily = meteo_imgw_daily(rank = "climate", year = 2000)

IMGW meteorological data from the IMGW datastore repository

Description

Downloading hourly (meteorological) data from the telemetric stations available in the danepubliczne.imgw.pl/datastore collection since 2008. Most parameters are collected with 10 minutes interval and thus it is recommended to download only the mandatory years, parameters or stations. For example, 1 year of data with all available parameters requires processing around 4GB of uncompressed data.

Usage

meteo_imgw_datastore(
  year,
  parameters = NULL,
  stations = NULL,
  coords = TRUE,
  allow_failure = TRUE
)

Arguments

Details

Data from the IMGW automated (telemetry) systems are non validated by experts and may contain invalid values.

Value

data.frame with a raw meteorological measurements in 10-min intervals. Please note that this dataset is not validated by experts and may contain invalid values.

Examples

imgw_telemetry = meteo_imgw_datastore(year = 2022:2023,
                                      parameters = "t2m",
                                      stations = c("HALA GĄSIENICOWA",
                                                   "DOLINA 5 STAWÓW"),
                                      coords = TRUE)

Hourly IMGW meteorological data

Description

Downloading hourly (meteorological) data from the SYNOP / CLIMATE / PRECIP stations available in the danepubliczne.imgw.pl collection

Usage

meteo_imgw_hourly(
  rank = "synop",
  year,
  status = FALSE,
  coords = FALSE,
  station = NULL,
  col_names = "short",
  allow_failure = TRUE,
  ...
)

Arguments

Value

meteorological data for the hourly time interval

Examples

  hourly = meteo_imgw_hourly(rank = "climate", year = 1984)
  head(hourly)

Monthly IMGW meteorological data

Description

Downloading monthly (meteorological) data from the SYNOP / CLIMATE / PRECIP stations available in the danepubliczne.imgw.pl collection

Usage

meteo_imgw_monthly(
  rank = "synop",
  year,
  status = FALSE,
  coords = FALSE,
  station = NULL,
  col_names = "short",
  allow_failure = TRUE,
  ...
)

Arguments

Value

meteorological data with monthly summaries

Examples

  monthly = meteo_imgw_monthly(rank = "climate", year = 1969)
  head(monthly)

  # a descriptive (long) column names:
  monthly2 = meteo_imgw_monthly(rank = "synop", year = 2018,
         col_names = "full")
  head(monthly2)

CO2 Mauna Loa (NOAA) dataset

Description

Carbon Dioxide (CO2) monthly measurements from Mauna Loa observatory. The source file is available at: ftp://aftp.cmdl.noaa.gov/products/trends/co2/co2_mm_mlo.txt with all further details.

Usage

meteo_noaa_co2()

Details

Data from March 1958 through April 1974 have been obtained by C. David Keeling of the Scripps Institution of Oceanography (SIO) and were obtained from the Scripps website (scrippsco2.ucsd.edu).

The "average" column contains the monthly mean CO2 mole fraction determined from daily averages. The mole fraction of CO2, expressed as parts per million (ppm) is the number of molecules of CO2 in every one million molecules of dried air (water vapor removed). If there are missing days concentrated either early or late in the month, the monthly mean is corrected to the middle of the month using the average seasonal cycle. Missing months are denoted by -99.99. The "interpolated" column includes average values from the preceding column and interpolated values where data are missing. Interpolated values are computed in two steps. First, we compute for each month the average seasonal cycle in a 7-year window around each monthly value. In this way the seasonal cycle is allowed to change slowly over time. We then determine the "trend" value for each month by removing the seasonal cycle; this result is shown in the "trend" column. Trend values are linearly interpolated for missing months. The interpolated monthly mean is then the sum of the average seasonal cycle value and the trend value for the missing month. NOTE: In general, the data presented for the last year are subject to change, depending on recalibration of the reference gas mixtures used, and other quality control procedures. Occasionally, earlier years may also be changed for the same reasons. Usually these changes are minor. CO2 expressed as a mole fraction in dry air, micromol/mol, abbreviated as ppm

Value

Data frame with historical CO2 concentrations

Examples

  co2 = meteo_noaa_co2()
  head(co2)

Hourly NOAA Integrated Surface Hourly (ISH) meteorological data

Description

Downloading hourly (meteorological) data from the SYNOP stations available in the NOAA ISD collection. Some stations in the dataset are dated back even up to 1900. By default only records that follow FM-12 (SYNOP) convention are processed. Further details available at: https://www1.ncdc.noaa.gov/pub/data/noaa/readme.txt

Usage

meteo_noaa_hourly(
  station = NULL,
  year = 2019,
  fm12 = TRUE,
  allow_failure = TRUE
)

Arguments

Value

data.frame with historical meteorological data in hourly intervals

Examples

# London-Heathrow, United Kingdom
  noaa = meteo_noaa_hourly(station = "037720-99999", year = 1949)

Scrapping meteorological (Synop) data from the Ogimet webpage

Description

Downloading hourly or daily (meteorological) data from the Synop stations available at https://www.ogimet.com/

Usage

meteo_ogimet(
  interval,
  date = c(Sys.Date() - 30, Sys.Date()),
  coords = FALSE,
  station,
  precip_split = TRUE,
  allow_failure = TRUE
)

Arguments

Value

A data.frame of measured values with columns describing the meteorological parameters (e.g. air temperature, wind speed, cloudines). Depending on the interval, at a given hour or day. Different parameters are returned for daily and hourly datasets.

1. station_ID - WMO station identifier

2. Lon - longitude

3. Lat - latitude

4. Date - date (and time) of observations

5. TC - air temperature at 2 metres above ground level. Values given in Celsius degrees

6. TdC - dew point temperature at 2 metres above ground level. Values given in Celsius degrees

7. TmaxC - maximum air temperature at 2 metres above ground level. Values given in Celsius degrees

8. TminC - minimum air temperature at 2 metres above ground level. Values given in Celsius degrees

9. ddd - wind direction

10. ffkmh - wind speed in km/h

11. Gustkmh - wind gust in km/h

12. P0hpa - air pressure at elevation of the station in hPa

13. PseahPa - sea level pressure in hPa

14. PTnd - pressure tendency in hPa

15. Nt - total cloud cover

16. Nh - cloud cover by high-level cloud fraction

17. HKm - height of cloud base

18. InsoD1 - insolation in hours

19. Viskm - visibility in kilometres

20. Snowcm - depth of snow cover in centimetres

21. pr6 - precicipitation totals in 6 hours

22. pr12 - precicipitation totals in 12 hours

23. pr24 - precicipitation totals in 24 hours

24. TemperatureCAvg - average air temperature at 2 metres above ground level. Values given in Celsius degrees

25. TemperatureCMax - maximum air temperature at 2 metres above ground level. Values given in Celsius degrees

26. TemperatureCMin - minimum air temperature at 2 metres above ground level. Values given in Celsius degrees

27. TdAvgC - average dew point temperature at 2 metres above ground level. Values given in Celsius degrees

28. HrAvg - average relative humidity. Values given in %

29. WindkmhDir - wind direction

30. WindkmhInt - wind speed in km/h

31. WindkmhGust - wind gust in km/h

32. PresslevHp - Sea level pressure in hPa

33. Precmm - precipitation totals in mm

34. TotClOct - total cloudiness in octants

35. lowClOct - cloudiness by low level clouds in octants

36. SunD1h - sunshine duration in hours

37. PreselevHp - atmospheric pressure measured at altitude of station in hPa

38. SnowDepcm - depth of snow cover in centimetres

Examples

  # downloading daily data for New York - La Guardia (last 30 days by default)
  new_york = meteo_ogimet(interval = "daily", 
                          station = 72503, 
                          coords = TRUE)

Shortening column names for meteorological variables

Description

Shortening column names of meteorological parameters to improve the readability of downloaded dataset from the danepubliczne.imgw.pl collection and removing duplicated column names

Usage

meteo_shortening_imgw(data, col_names = "short", remove_duplicates = TRUE)

Arguments

Value

data.frame with modified names of meteorological parameters

Examples

  monthly = meteo_imgw("monthly", rank = "climate", year = 1969)
  
  abbr = meteo_shortening_imgw(data = monthly,
      col_names = "full", 
      remove_duplicates = TRUE)
  head(abbr)

List of nearby meteorological or hydrological IMGW-PIB stations in Poland

Description

Returns a data frame of meteorological or hydrological stations with their coordinates in particular year. The returned object is valid only for a given year and type of stations (e.g. "synop", "climate" or "precip"). If add_map = TRUE additional map of downloaded data is added.

Usage

nearest_stations_imgw(
  type = "meteo",
  rank = "synop",
  year = 2018,
  add_map = TRUE,
  point = NULL,
  no_of_stations = 50,
  allow_failure = TRUE,
  ...
)

Arguments

Value

A data.frame with a list of nearest stations. Each row represents metadata for station which collected measurements in a given year. Particular columns contain stations metadata (e.g. station ID, geographical coordinates, official name, distance in kilometers from a given coordinates).

Examples

  df =  nearest_stations_imgw(type = "meteo", 
  rank = "synop",
  year = 2018,
  point = c(17, 52),
  add_map = TRUE, 
  no_of_stations = 4)

List of nearby SYNOP stations for a defined geographical location

Description

Returns a data frame of meteorological stations with their coordinates and distance from a given location based on the noaa website. The returned list is valid only for a given day.

Usage

nearest_stations_noaa(
  country,
  date = Sys.Date(),
  add_map = TRUE,
  point = NULL,
  no_of_stations = 10,
  allow_failure = TRUE
)

Arguments

Value

A data.frame with number of nearest station according to given point columns describing stations parameters (e.g. ID station, distance from point, geographic coordinates, etc.) where each row represent a measurement, each station which has a measurements on selected date. If add_map = TRUE additional map of downloaded data is added.

Examples

  nearest_stations_noaa(country = "SRI LANKA", 
  point = c(80, 6),
  add_map = TRUE, 
  no_of_stations = 10)
  
  uk_stations = nearest_stations_noaa(country = "UNITED KINGDOM", no_of_stations = 100)

List of nearby synop stations for a defined geographical location

Description

Returns a data frame of meteorological stations with their coordinates and distance from a given location based on the ogimet webpage. The returned list is valid only for a given day.

Usage

nearest_stations_ogimet(
  country = "United Kingdom",
  date = Sys.Date(),
  add_map = FALSE,
  point = c(2, 50),
  no_of_stations = 10,
  allow_failure = TRUE,
  ...
)

Arguments

Value

A data.frame with number of nearest station according to given point columns describing stations parameters (e.g. ID station, distance from point in km, geographic coordinates, etc.). Each row represent a measurement, each station which has a measurements on selected date. If add_map = TRUE additional map of downloaded data is added.

Examples

  nearest_stations_ogimet(country = "United Kingdom", 
                          point = c(-2, 50),
                          add_map = TRUE, 
                          no_of_stations = 50, 
                          allow_failure = TRUE,
                          main = "Meteo stations in UK")

Scrapping daily meteorological (Synop) data from the Ogimet webpage

Description

Downloading daily (meteorological) data from the Synop stations available in the https://www.ogimet.com/ repository. The data are processed only if temperature or precipitation fields are present.

Usage

ogimet_daily(
  date = c(Sys.Date() - 30, Sys.Date()),
  coords = FALSE,
  station = NA,
  hour = 6,
  allow_failure = TRUE
)

Arguments

Value

data.frame with historical meteorological data for the daily summaries

Examples

  # downloading daily summaries for last 30 days. station: New York - La Guardia
  new_york = ogimet_daily(station = 72503, coords = TRUE)

Scrapping hourly meteorological (Synop) data from the Ogimet webpage

Description

Downloading hourly (meteorological) data from the Synop stations available in the https://www.ogimet.com/ repository

Usage

ogimet_hourly(
  date = c(Sys.Date() - 30, Sys.Date()),
  coords = FALSE,
  station = 12330,
  precip_split = TRUE,
  allow_failure = TRUE
)

Arguments

Value

data.frame with historical meteorological data for hourly time interval

Examples

  # downloading data for Poznan-Lawica, Poland
  poznan = ogimet_hourly(station = 12330, coords = TRUE)

Exemplary sounding profile from University of Wyoming dataset

Description

The object contains pre-downloaded atmospheric (sounding) profile for Leba, PL rawinsonde station. The measurement was taken 2000/03/23 at 00 UTC.

Usage

profile_demo

Format

The data contains list of two data.frames as derived using sounding_wyoming() function

Examples

data(profile_demo)
head(profile_demo)

Sounding data

Description

Downloading the measurements of the vertical profile of atmosphere (also known as sounding data). Data can be retrieved using TEMP and BUFR sounding formatting.

Usage

sounding_wyoming(
  wmo_id,
  yy,
  mm,
  dd,
  hh,
  min = 0,
  bufr = FALSE,
  allow_failure = TRUE
)

Arguments

Value

Returns two lists with values described at: weather.uwyo.edu ; The first list contains:

1. PRES - Pressure (hPa)

2. HGHT - Height (metres)

3. TEMP - Temperature (C)

4. DWPT - Dew point (C)

5. RELH - Relative humidity (%)

6. MIXR - Mixing ratio (g/kg)

7. DRCT - Wind direction (deg)

8. SKNT - Wind speed (knots)

9. THTA = (K)

10. THTE = (K)

11. THTV = (K)

The second list contains metadata and calculated thermodynamic / atmospheric instability indices (for TEMP soundings only)

A list of 2 data.frames where first data frame represents parameters of upper parts o with columns describing the meteorogical parameters (e.g. temperature, air pressure) where each row represent a measurement, depending on the height. Second data.frame presents a description of the conditions under which the sounding was carried out.

Source

http://weather.uwyo.edu/upperair/sounding.html

Examples

##############################################################################
# download data for Station 45004 starting 1120Z 11 Jul 2021; Kowloon, HONG KONG, CHINA
# using TEMP and BUFR sounding formats
##############################################################################
  TEMP = sounding_wyoming(wmo_id = 45004, yy = 2021, mm = 07, dd = 17, 
                          hh = 12, min = 00)
  head(TEMP[[1]])
  
  BUFR = sounding_wyoming(wmo_id = 45004, yy = 2021, mm = 07, dd = 17, 
                          hh = 12, min = 00, bufr = TRUE)
  head(BUFR[[1]])


##############################################################################
### example with a random date to download sounding from LEBA, PL station: ###
##############################################################################

  profile = sounding_wyoming(wmo_id = 12120, 
                             yy = sample(2000:2019,1),
                             mm = sample(1:12,1), 
                             dd = sample(1:20,1), 
                             hh = 0)
  # plot(profile[[1]]$HGHT, profile[[1]]$PRES, type = 'l')

Distance between two points on a spheroid

Description

Calculate the distance between two points on the surface of a spheroid using Vincenty's formula. This function can be used when GIS libraries for calculating distance are not available.

Usage

spheroid_dist(p1, p2)

Arguments

Value

numerical vector with distance between two locations (in kilometers)

Examples

 p1 = c(18.633333, 54.366667) # longitude and latitude for Gdansk, PL
 p2 = c(17.016667, 54.466667) # longitude and latitude for Slupsk, PL
 spheroid_dist(p1, p2)
 

IMGW telemetry stations

Description

Retrieving current metadata for stations used in the telemetric systems of the IMGW-PIB datastore (danepubliczne.imgw.pl/datastore)

Usage

stations_meteo_imgw_telemetry()

Value

data table with metadata for over 500 stations. Metadata contains: station ID, station name, river, latitude, longitude, altitude

Examples

  telemetry_stations = stations_meteo_imgw_telemetry()

Scrapping a list of meteorological (Synop) stations for a defined country from the Ogimet webpage

Description

Returns a list of meteorological stations with their coordinates from the Ogimet webpage. The returned list is valid only for a given day

Usage

stations_ogimet(
  country = "United Kingdom",
  date = Sys.Date(),
  add_map = FALSE,
  allow_failure = TRUE
)

Arguments

Value

A data.frame with columns describing the synoptic stations in selected countries where each row represent a statation. If add_map = TRUE additional map of downloaded data is visualized.

Examples

  stations_ogimet(country = "Australia", add_map = TRUE)

Download file in a graceful way

Description

Function for downloading & testing url/internet connection according to CRAN policy Example solution strongly based on https://community.rstudio.com/t/internet-resources-should-fail-gracefully/49199/12 as suggested by kvasilopoulos

Usage

test_url(link, output, quiet = FALSE)

Arguments

Value

No return value, called for side effects

Examples

 link = "https://www1.ncdc.noaa.gov/pub/data/noaa/2019/123300-99999-2019.gz"
 output = tempfile()
 test_url(link = link, output = output)