imgw
The goal of imgw is to automatize downloading Polish meteorological and hydrological data from the IMGW-PIB.
Installation
You can install the development version of imgw from GitHub with:
library(remotes)
install_github("bczernecki/imgw")Overview
Meteorological data
meteo() - Downloading hourly, daily, and monthly meteorological data from the SYNOP/CLIMATE/PRECIP stations available in the danepubliczne.imgw.pl collection. It is a wrapper for
meteo_monthly(),meteo_daily(), andmeteo_hourly().meteo_monthly() - Downloading monthly meteorological data from SYNOP/CLIMATE/PRECIP stations made available in the danepubliczne.imgw.pl database
meteo_daily() - Downloading daily meteorological data from SYNOP/CLIMATE/PRECIP stations made available in the danepubliczne.imgw.pl database
meteo_hourly() - Downloading hourly meteorological data from SYNOP/CLIMATE/PRECIP stations made available in the danepubliczne.imgw.pl database
meteo_metadata() - Downloading the description (metadata) of the meteorological data provided in the danepubliczne.imgw.pl database
meteo_sounding() - Downloading the mea (i.e., measurements of the vertical profile of atmosphere) sounding data
meteo_shortening() - Shortening column names of meteorological parameters to improve the readability of downloaded dataset and removing duplicated column names
Hydrological data
hydro() - Downloading hourly, daily, and monthly hydrological data from the SYNOP / CLIMATE / PRECIP stations available in the danepubliczne.imgw.pl collection. It is a wrapper for
hydro_annual(),hydro_monthly(), andhydro_daily().hydro_annual() - Downloading semiannual and annual hydrological data from the danepubliczne.imgw.pl database
hydro_monthly() - Downloading monthly hydrological data from the danepubliczne.imgw.pl database
hydro_daily() - Downloading daily hydrological data from the danepubliczne.imgw.pl database
hydro_metadata() - Downloading the description (metadata) of the hydrological data provided in the danepubliczne.imgw.pl database
hydro_shortening() - Shortening column names of hydrological parameters to improve the readability of downloaded dataset and removing duplicated column names
Examples
library(imgw)
m = meteo_monthly(rank = "synop", year = 2000, coords = TRUE)
head(m)
#> rank id X Y station yy mm tmax_abs
#> 1 SYNOPTYCZNA 349190600 19.00234 49.80671 BIELSKO-BIAŁA 2000 10 26.4
#> 2 SYNOPTYCZNA 349190600 19.00234 49.80671 BIELSKO-BIAŁA 2000 1 7.4
#> 3 SYNOPTYCZNA 349190600 19.00234 49.80671 BIELSKO-BIAŁA 2000 6 32.2
#> 4 SYNOPTYCZNA 349190600 19.00234 49.80671 BIELSKO-BIAŁA 2000 7 28.0
#> 5 SYNOPTYCZNA 349190600 19.00234 49.80671 BIELSKO-BIAŁA 2000 8 32.6
#> 6 SYNOPTYCZNA 349190600 19.00234 49.80671 BIELSKO-BIAŁA 2000 9 25.1
#> tmax_mean tmin_abs tmin_mean t2m_mean_mon t5cm_min rr_monthly
#> 1 17.4 0.6 10.0 13.4 -3.8 39.5
#> 2 0.7 -19.6 -4.5 -1.6 -21.7 38.9
#> 3 22.5 6.1 12.1 17.2 2.4 81.1
#> 4 20.5 6.7 12.0 16.0 5.5 322.5
#> 5 24.1 7.1 13.4 18.6 3.7 62.8
#> 6 17.3 2.7 7.9 12.2 -1.2 46.1
#> rr_max_daily first_day_max_rr last_day_max_rr insolation_monthly
#> 1 11.7 17 NA 0.0
#> 2 9.1 29 NA 0.0
#> 3 22.1 14 NA 271.8
#> 4 69.3 28 NA 0.0
#> 5 33.6 6 NA 0.0
#> 6 19.0 4 NA 0.0
#> snowcover_max snowcover_days rain_days snow_days r_s_days hail_days
#> 1 0 0 11 0 0 0
#> 2 30 26 2 16 2 0
#> 3 0 0 11 0 0 0
#> 4 0 0 20 0 0 0
#> 5 0 0 10 0 0 1
#> 6 0 0 8 0 0 0
#> fog_days fogginess_days rime_days glaze_days snowstorm_low_days
#> 1 8 15 0 0 0
#> 2 2 28 0 0 10
#> 3 0 7 0 0 0
#> 4 1 18 0 0 0
#> 5 2 17 0 0 0
#> 6 1 20 0 0 0
#> snowstorm_high_days hazyness_days ws_10ms_days ws_15ms_days thunder_days
#> 1 0 0 11 2 3
#> 2 4 0 7 1 1
#> 3 0 0 0 0 4
#> 4 0 0 5 0 5
#> 5 0 0 2 0 4
#> 6 0 0 0 0 0
#> dew_days hoarfrost_days cloud_mean_mon ws_mean_mon vapor_press_mean_mon
#> 1 12 2 4.9 3.9 11.4
#> 2 0 0 6.5 4.3 4.6
#> 3 21 0 4.0 2.8 13.1
#> 4 8 0 5.9 3.3 13.9
#> 5 22 0 3.8 2.4 15.5
#> 6 22 0 4.6 3.0 11.2
#> rh_mean_mon press_mean_mon slp_mean_mon rr_daytime rr_nightime
#> 1 74.8 970.3 1017.5 11.8 27.7
#> 2 82.8 971.8 1021.8 16.6 22.3
#> 3 67.2 972.3 1019.0 34.4 46.7
#> 4 77.6 964.4 1010.8 150.9 171.6
#> 5 73.8 971.4 1017.8 6.5 56.3
#> 6 79.2 969.7 1017.1 13.0 33.1
h = hydro_annual(year = 2010)
head(h)
#> id station riv_or_lake hyy idyy Mesu idex H beyy bemm bedd
#> 1 149180020 CHAŁUPKI Odra (1) 2010 13 H 1 135 2009 12 20
#> 2 149180020 CHAŁUPKI Odra (1) 2010 13 H 2 188 NA NA NA
#> 3 149180020 CHAŁUPKI Odra (1) 2010 13 H 3 420 2009 11 12
#> 4 149180020 CHAŁUPKI Odra (1) 2010 14 H 1 137 2010 8 26
#> 5 149180020 CHAŁUPKI Odra (1) 2010 14 H 2 229 NA NA NA
#> 6 149180020 CHAŁUPKI Odra (1) 2010 14 H 3 650 2010 5 17
#> behm
#> 1 NA
#> 2 NA
#> 3 4
#> 4 NA
#> 5 NA
#> 6 15Acknowledgment
Institute of Meteorology and Water Management - National Research Institute is the source of the data.