A 20-year climatology of rainfall events in Germany

After downloading the German radar data set, preprocessing and applying a rain cell tracking to it, it is now finally time to have a look at the created rain event data set. Since the output of the rain cell tracking is quite elaborate, we will boil it down to a neat data base of the characteristics of rain events that I am interested in. We can then have a first look at some statistics. Follow me on this path.

This post is part of the germanRADARanalysis project.

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Apply rain cell tracking to 20 years of rain radar data over Germany

So, I downloaded the 20-year radar data set (Mar to Nov) from the German meteorological service (DWD). It contains about 1.5 million individual radar-derived precipitation fields – one every 5 minutes. And, I was very excited to run a rain cell tracking on it. After handing in my PhD thesis, I was going for a short trip to visit family and friends in Germany. Fortunately, I have a home server and I decided to let it do the heavy work while I am on holidays. It took the full ten days of my absence plus two extra days for the 8-core Intel CPU machine to process all data. So, let’s see how I did it.

This post is part of the germanRADARanalysis project.

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Download German rain radar data and convert it to NetCDF (or what they should provide in the first place)

For a private project, I wanted to have a look at the German radar archive. I found that they have quasi-calibrated 5-minute precipitation data on a 1km2 grid available in the public domain. So, let’s download and process the data set, so that it is easier to use for further data analysis.

This post is part of the germanRADARanalysis project. All code is available on GitHub.

Continue reading “Download German rain radar data and convert it to NetCDF (or what they should provide in the first place)”

Published: Cold Pool Dynamics Shape the Response of Extreme Rainfall Events to Climate Change

I’m happy to announce that we just published another article about the response of small-scale convective precipitation extremes to a warming atmosphere in JAMES.

Abstract

There is increasing evidence that local rainfall extremes can increase with warming at a higher rate than expected from the Clausius-Clapeyron (CC) relation. The exact mechanisms behind this super-CC scaling phenomenon are still unsolved. Recent studies highlight invigorated local dynamics as a contributor to enhanced precipitation rates with warming. Here, cold pools play an important role in the process of organization and deepening of convective clouds. Another known effect of cold pools is the amplification of low-level moisture variability. Yet, how these processes respond to climatic warming and how they relate to enhanced precipitation rates remains largely unanswered. Unlike other studies which use rather simple approaches mimicking climate change, we present a much more comprehensive set of experiments using a high-resolution large eddy simulation (LES) model. We use an idealized but realistically forced case setup, representative for conditions with extreme summer precipitation in midlatitudes. Based on that, we examine how a warmer atmosphere under the assumption of constant and varying relative humidity, lapse rate changes and enhanced large-scale dynamics influence precipitation rates, cold pool dynamics, and the low-level moisture field. Warmer conditions generally lead to larger and more intense events, accompanied by enhanced cold pool dynamics and a concurring moisture accumulation in confined regions. The latter are known as preferred locations for new convective events. Our results show that cold pool dynamics play an increasingly important role in shaping the response of local precipitation extremes to global warming, providing a potential mechanism for super-CC behavior as subject for future research.

Lochbihler, K., Lenderink, G., & Siebesma, A. P. (2021). Cold pool dynamics shape the response of extreme rainfall events to climate change. Journal of Advances in Modeling Earth Systems, 13. https://doi.org/10.1029/2020MS002306