Verify this hypothesis by means of data in Bavaria. This federal state reveals the broadest range of topographic heights, from 100m to more than 2800m above Normal-Null (NN). Plot the annual mean temperatures of year 2018 versus altitude for the DWD stations in Bavaria. At first use the altitudes from the station description file [login to view URL] for the data set /annual/kl/recent/.
Do do so create a 'long' Pandas data frame by sequentially appending all time series data from the recent KL (Klima, Climate) data set where the year is 2018 and the state is Bavaria. Finally analyse the column with the mean annual temperature. Have a look at the metadata if you forgot the column name.
You can start with the Jupyter Notebook gdms0641_DWD_Annual_Temp_vs_Altitude_Vnnn in which the analysis is done for NRW. The data format of the KL time series differs significantly from the precipitation data set R1. A respective function is provided in the notebook.
The analysis for NRW yields the following diagram:
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Hello! I'm an atmospheric science master student. I have a lot of experience with weather data and statistics. I would like to do this job. Work with python. Hope you can solve this.