Project Description

Understanding the local terrain features is crucial when it comes to interpretation of weather observations (e. g. comparison of wind speeds during a storm event or validation of temperature extrema). The landform classification algorithm described above is applied to the set of automated weather stations run owned by MeteoSwiss. A simple classification by altitude and local landform (figure 2) provides a good overview of station characteristics. Detailed maps allow for a better understanding of local weather/climate processes. The weather station of Buffalora (Grisons, Switzerland) at an altitude of 1970 m AMSL frequently reports the lowest daily minimum temperatures in the whole observation network. Figure 3 exhibits the terrain pattern in this Alpine high-valley. There is a distinct ground depression near the station which permits the formation of nocturnal cold air pool.

Go to demo

Classification of weather station in Switzerland by altitude (colour scheme) and landform (symbols)

Figure 1: Classification of weather station in Switzerland by altitude (colour scheme) and landform (symbols)

Topography and hill shade in a perimeter of 10 x 10 km centred at the weather station of Buffalora (Grisons, Switzerland). See http://myweather.ch/smn/station/BUF.html for more details.

Figure 2: Topography and hill shade in a perimeter of 10 x 10 km centred at the weather station of Buffalora (Grisons, Switzerland). See http://myweather.ch/smn/station/BUF.html for more details.

Landform classes for the same region as in previous figure

Figure 3: Landform classes for the same region as in previous figure

Literature

Jasiewicz, Jarosław & F Stepinski, Tomasz. (2012). Geomorphons - a pattern recognition approach to classification and mapping of landforms. Geomorphology. 182. 10.1016/j.geomorph.2012.11.005. http://dx.doi.org/10.1016/j.geomorph.2012.11.005

Technology

  • R packages: data.table, sf, sp, ggplot2, leaflet, rmarkdown
  • Data: NASA STRM Elevation Model