R – Kai Lochbihler

RStudio Server in Docker with Remote Access

For a lot of applications, running RStudio (desktop edition) locally is the best choice. But what if you want to run more complex statistical analysis or machine learning tasks that require more resources. In that case, it might be interesting for you to run a dedicated RStudio server on adequate hardware and docker offers an easy option to quickly setup and run an instance. A possible scenario is that you have remote access to a more powerful computer (Desktop or HPC). Here, I will give a simple recipe that worked great for me.

Practice my R: Two options to implement the watershed segmentation

High-level scripting languages are great! I mean, you can basically do a complete statistical analysis, including visualizations, with a few lines of code. The thing is that these programming languages, for example R or Python, hide more complex code behind classes, methods and functions. And, very often they call routines that are written in other, lower-level languages, for example C, C++ or even FORTRAN. So what if you want to do something for which there are no existing packages with predefined routines? The answer is simple: do it yourself.

In this exercise, I will show two options of how to implement a specific method in R by using the example of the watershed segmentation. All code and sample data is available on GitHub.

The scaling of extreme rainfall events with surface moisture availability in Germany

Since the beginning of this project I was very curious about the relationship of extreme rainfall event intensity with temperature and the local moisture availability in Germany. And, even more about how this depends on the actual precipitation type. Now there has been previous work about this (Moseley et al. 2013) and I myself did an analysis for the Netherlands (Lochbihler et al. 2017). However, even though Moseley et al (2013) investigated the dependency on precipitation type, they only used two years of data. And, I completely neglected the precipitation type due to a lack of data for the Netherlands.

Here, I will do a scaling analysis for 15 years of data (March to October) and will see how this relates to the precipitation type. All code and data is freely available.

This post is part of the germanRADARanalysis project.

A gridded data set of precipitation types for Germany

In my previous analysis of the event catalog of precipitation events in Germany, I used all available events. And, I already pointed out that the results might be influenced by the type of precipitation event. In this article, I will create a data set that allows us to distinguish between convective and stratiform precipitation events.

This post is part of the germanRADARanalysis project.