Daily meteorological data were downloaded from TuTiempo.net for the following 4 climatic stations:
#> country location station longitude latitude elevation
#> 1 Laos Phonhong 489410 102.40 18.46 179
#> 2 Laos Thangone 489440 102.63 18.28 185
#> 3 Laos Vientiane 489400 102.56 17.95 171
#> 4 Thailand Nong Khai 483520 102.71 17.86 174
Which, on the map, are located here in red, from left to right and from top to bottom:
After cleaning (see cleaning pipeline), the meteorological data as well and the climatic stations characteristics are available here:
- meteo.csv (905.5 KB)
- stations.csv (211 K)
From where they can be copied and pasted. They can also be downloaded directly from R as so:
if (! "readr" %in% rownames(installed.packages())) install.packages("readr")
meteo <- readr::read_csv("https://raw.githubusercontent.com/ecomore2/meteo/master/data/meteo.csv",
col_types = "iDddddiddddllll")
stations <- readr::read_csv("https://raw.githubusercontent.com/ecomore2/meteo/master/data/stations.csv",
col_types = "cciddi")Dictionary:
- day: date of data colletion
- ta: average temperature (°C)
- tx: maximum temperature (°C)
- tn: minimum temperature (°C)
- slp: atmospheric pressure at sea level (hPa)
- h: average relative humidity (%)
- pp: total rainfall and / or snowmelt (mm)
- vv: average visibility (km)
- v: average wind speed (km / h)
- vm: maximum sustained wind speed (km / h)
- ra: boolean indicating whether there was rain or drizzle
- sn: boolean indicating whether it snowed
- ts: boolean indicating whether there were storm
- fg: boolean indicating whether there was floo
Below is a visual representation of the data per station:
#> [1] 483520
#> [1] 489400
#> [1] 489410
#> [1] 489440
