Summary I’ve built a number of Shiny apps in the past already. Even though they had a lot of common features, I found it difficult to migrate functionality from one to the next project. Often times, different data structure and variable names made it necessary it to re-write a large portion of the code. Fortunately, there are a number of tools available within the R framework (packages and concepts) which allow for a high level of reusability.
Homogeneous data series since 1864 are provided by MeteoSwiss through the opendata.swiss platform. The series consist of monthly means of temperature and precipitation for a total of 14 weather stations in Switzerland. To allow for a comparison of different months and stations a standard score is applied to these series. For a reference period (e. g. the climatological normal period 1980 - 2010) mean and standard deviation are determined per month of the year and station.
Project Description MeteoSwiss weather observations are available through the opendata.swiss platform. Current project is about a simple R Shiny user interface that produces customised time series plots of various meteorological parameters. It features a dropdown menu with pre-defined reports (see figure 1). A change in this selector triggers an update of the whole UI, filling in the report selections. Go to Demo Figure 1: Screenshot of the UI. 1: Report selection, 2: Station selection, 3: Parameter, 4: Time picker, 5: Time inverval, 6: Aggregation function, 6: Perspective (absolute or change by time), 7: Time lag when perspective = change, 8: Download button Figure 2: Example of a time series plot for two stations (Altdorf and Magadino) Technology MySQL DB R packages: data.
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.
Project Description Current project features a static markdown report that is updated every ten minutes and rendered into a HTML file. The reports shows the data completeness status of MeteoSwiss’ observation network (SwissMetNet). Data is made available through the opendata.swiss platform. A leaflet map provides an overview of current situtation, the colour scheme stands for the duration of the interruption. Customised map markers provide detailed information on the duration by type of sensor.