Paleoclimate time series are often very noisy due to the combined effect of low sedimentation rates, intensive bioturbation and small sample sizes (5-20 foraminifers). Adaptive filters may help to increase the signal-to-noise ratio of such time series where conventional methods such as fixed filters cannot be applied if optimal filtering is to be achieved, because the signal-to-noise ratio is unknown and varies with time. Continue reading “Adaptive Filters in Paleoclimatology – the Python Version”
Detecting, measuring and classifying transitions in climate time series is one of the most important applications in modern time series analysis (Mudelsee, 2000; Trauth et al., 2018, 2021). Three methods are presented here: sigmoid fit, ramp fit and change point detection. Continue reading “Analyzing Climate Transitions with MATLAB”
Variants of a map of northeastern Africa appear in recent publications (e.g., Trauth et al., 2021a, b) using coastlines from the GSHHG data set and topography from the ETOPO1 data set. Here I show how it was made. Continue reading “Creating a Map with Coastlines and Topo Contours with MATLAB”
We wanted to display pulsating circles on a map and save the result in a video. Here is part one, the pulsating circles. The map will come in the next post.
The popular online course on data analysis in the geosciences will be taught bilingual for the first time, using the two leading programming languages and development environments MATLAB and Python in parallel on 18–22 September 2023. The course is based on the 5th edition of my books MATLAB Recipes for Earth Science (Springer 2021) and Python Recipes for Earth Sciences (Springer 2022).
Nearly 30 years ago, I began teaching compact courses on data analysis in the earth sciences. Almost 20 years ago, I started thinking about writing textbooks. Now there are five textbooks and many different course formats for you. Here is an overview of the current options! Continue reading “Online Courses in Modern Data Analysis Methods in Earth Sciences with Python and MATLAB”
A while back I wrote a post about John Aitchison’s Log-Ratio Transformation, Part 1, in the time domain and today Part 2 in the frequency domain. Here’s Part 3 with a MATLAB demonstration of a nice Aitchison example presented in an extended abstract by Pawlowsky-Glahn and Egozcue (2013). Continue reading “MATLAB Example to Illustrate John Aitchison’s Log-Ratio Transformation, Part 3”
A while back I wrote a post about Aitchison’s log-ratio transformation. It was about eliminating the dilution effect of an element 1c on elements 1a and 1b by dividing 1a/1b or log(1a/1b). One can show the effect of the log-ratio transformation also very nicely in the spectral domain. Here is an example. Continue reading “MATLAB Example to Illustrate John Aitchison’s Log-Ratio Transformation, Part 2”