Outreach: bringing science to the next generation

Outreach is fun, at least for me. You are going to an event, present what you do in easy terms and discuss with people about science, what you are working on or why what you do matters at all. These events are usually quite relaxed, filled with young people and a good break out of your usual day job. That is why I was happy to volunteer when we got as a group the question whether we would like to present our field at “Highlights der Physik” (Highlights of physics), a science fair held every year on a market place in a minor town somewhere in Germany.

All started with the question whether we want to do it and what we would like to show. As a meteorologist, I had done several of these events, and the usual stuff to show are measurement instruments and some experiments with water, because that works for 10-12 year old and this is usually the general target group to be able to catch everyone. This time the target group was given by the organizers with 13-15 years old, so the instruments would do it (especially as we are not a working group of meteorologists). Back in the days when we did these shows I always wanted to show something like statistics and ensembles at these events, because that is may daily job, but quite hard to boil down for little kids. This time the chance opened up with some reasonable budget to get it done.

As a group we decided to show the difference between weather forecasting and climate prediction, and of course our group topic, seasonal and decadal prediction. After several brain storming events we decided to develop a Galton board and try our luck how far we can go with it. With a lot of practical help of the one who finally build it, we designed it in a flexible way, so that we can show many different topics with it. Little barriers allow us to deviate the little wooden balls at any place on the board in the direction we want them and having a lot of little balls allow us to make impressive statistical experiments. So all in all, this little toy got us really exciting for the event and of course it helped us to get over the not so funny parts of organising our appearance there (posters, questionnaires, travel etc.).

When the time came, I had a beautiful week in Münster, a university town in the western part of Germany. Within a tent, surrounded by many other physics groups we showed our experiment and talked a lot about the wide field of climatology and weather. We are used to get questions about politics and energy as well, as many connect nowadays with climate the changing environment we are living in. And of course there is the main motivation for founders to send us to such events: talking with pupils, students and teachers about the great career opportunities, when you choose a geoscientific field for study. It also gave us this time again the opportunity to show that geosciences are part of the physics community, which also lead to interesting discussions with other physicists.

Being back I got contact with our PR department and they wrote a lovely piece for their web presence (unfortunately just in german). So all in all it was a lot of time, half a year of preparation and a lot of communicating science. And yes, I am happy that it was with such simple means possible to explain a lot of people a statistical topic in a physical environment.

 

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A look at lecturing: Just before the start

After I had written nearly two months ago how the preparations for the lecture in the new term has started, it is now the time to wrap up the preparations as from next week on the term starts. So what have I achieved up to now? Well, more or less nearly all lectures are prepared, I have one left to do, but this will be done nearer to the actual lecture, because I need one for a bit of wiggle room in the middle (so when I am too slow or I see that students do not get used to my concepts). Also I have managed to have ideas and prepare most of the practical sheets, which the students have to do. So far, I am quite happy with that, but I will only see in the active phase, whether this will really work out as planned. Continue reading

Scientists and holidays

Every worker as a right for holidays. Yes, especially in Europe this promise by the declaration of human rights is seen as very important, while in the US the amount of holidays is generally quite limited. So in Europe most scientists, as most workers, have the right to something around 25 to 30 holidays per calendar year. Many enjoy it, but when you talk to scientist you often hear some form of guilt when they take it. This post should address the reasons for it and are of course only my own observations. Continue reading

A look at lecturing: Preparations months ahead

Part of an academical job is to lecture. Myself am very lucky that this duty is part of my obligations as I really like to do it. In the past I have mainly assisted teaching or did tutoring in various lectures, but next term I will get my own lecture to plan and give in full. I will get important assistance on one or two lectures as my schedule require me to be away for some dates, but apart from that it I will have to fill the four hours a week. The topic will be in a statistical area and so more in my core expertise as my lecturing I did up to now, which was mainly in the physical areas of climate science.

In the upcoming months I will write some posts about this topic, my experience of preparing the lectures and my thoughts about concepts. Of cause I will omit talking about the actual lectures, as students should never fear that they are put on the spot. As the topic of the lecture will be the basis of statistics, it will be not so much about the actual topics, but on how to present them and how to make it an interesting learning experience for the students.

As there are another two month to go I have started to prepare the first lectures. All in all there will be roughly 15 weeks to fill, partly with predefined content and with practicals. The german system sets a fixed numbers of hours the student should work on any lecture and in my case this number can be worked out as 12 hours per week. That is a lot, because even with taking the four hours of presence study not into account, there are eight hours left. So it will be a balance to get enough stuff into the lectures and explaining it in a way that a general unloved topic can be understood. Statistics is for many students like maths and that is in applied physics courses like meteorology/oceanography/geophysics usually not very popular for them. Usually one to two years of mathematical studies, mostly not very connected to the rest of the curriculum, are the beginning of every students life and so the next step with a mostly quite dry topic like statistics is thought to be the same. And unfortunately, therein lies a problem. When you get into statistics too much on the applied side, then you do not give context to the maths lectures given before and it will get harder for the students in the future to get into statistics properly (so not only as an auxiliary subject, but a real tool which is comfortable to handle). On the other side when you do it too mathematically, it is just another hated maths subject. Balancing in the middle of it is certainly an aim, but not really realistic to achieve.

I am looking forward to this experience, but am also aware that all my planning and thoughts might not work out as planned and it ends up it a struggle for the students and myself. That is a challenge and I like challenges.

The burden of maintaining an R-package

During my PhD I worked on Quality Assurance of Environmental Data and how to exchange quality information between scientists. I developed a concept for a possible workflow, which would help all scientists, data creators and re-users, for making data publications much more useful. One major foundation of this were quality tests, which I either taken from existing literature or developed anew.

Part of this work was the development of a proof-of-concept implementation of the methodologies. I used R, which is my prime language for quite a while, to design an as much as possible automisable test workflow. It was quite complex and in retrospect a bit too ambitious for real world applications. Anyway, as I prefer open science, I published it as an extension package for R in 2011: qat – Quality Assurance Toolkit.

The publication process was more challenging as anticipated. For each function, and my package had more than a hundred, a detailed help file was requested, which cost me at that time quite a while to create. I also wanted to add additional information, like an instruction manual, so that at least in theory it would have been possible to use the full functionality (like automatic plotting and saving of the test results) could be understood. Finally, when it was uploaded, I was happy and extended it until my PhD project came to an end.

Unfortunately, with this the work on the package has not stopped. R as a language is constantly changing, not really on the day-to-day tools, but in the background of the packages. New requirements come up now and then, usually associated with a deadline for package maintainers. What is quite simple to solve for small packages, can be a real challenge for complex ones like mine. I had to eliminate my instruction manual when the vignette system changed and created a dedicated website to have it still accessible. Also I had to replace packages I depend on, which is usually associated with quite a bit of change in the code.

All these changes are doable, but the big problems start with the requirement, that a newly uploaded package has to fulfil the current norms of the R packages. A package, which was fine a few months earlier has to change dramatically with the next update. This leads usually to a time problem, as each update needs therewith several days. So minor changes to the original code lead to a heavy workload. This lead to the situation, that I was not able to update it on time when the last deadline turned up and so my package went to archive. Half a year later I found some time and have now brought it back up to the CRAN network.

All in all, this workload is keeping me off to create new R packages. Making them would be feasible, but maintaining them is a pain. With these constant policy changing measures, R gets more and more out of fashion for heavy users and with it, it is in danger to lose out compared to other languages like python in teaching for the next generation of scientists. My personal hope is that future development will lead to a more stable policy on the package policy within R, so that more packages will be available also for the future. As things stand, I am happy to have my package up again, but when the next deadline will enter my mailbox, I will again have to evaluate the threatening workload, before I can afford to schedule a new release.

IMSC2016: Final day

The fifth and last day of the 13th International Meeting on Statistical Climatology (IMSC) has ended and with it a great week here in the Rocky mountains. It started today with the first homogenisation session and the talks covered a wide range. Among this the worldwide organisation of climate data generation, the proposal of a new homogenisation methodology and finally an overview on future challenges for homogenisation. As I had myself worked during my PhD on quality control of data this topic is of special interest for me and I was happy to see this variety of talks in this field.

Low clouds

It was followed with a session on nonlinear methods. As it was the final day, the talks within the sessions covered a wider area, which was good. Finally the day ended for me again with a homogenisation session and as before, the talks were of high quality.

As it was the last day I would like to take a look back on the week. The weather was fantastic, apart from the last day, when the clouds and rain got in. The conference and many talks were really interesting. The mixture of so many different topics gave a great overview on the many flavours of statistical application in climate science. Many scientists, with different backgrounds, on various levels within their career led to a great knowledge exchange and new views on the topics. It was really well organised and so it was easy to concentrate on the good things of a conference. Therefore, the meeting was really worth a visit so perhaps again in three years at the next IMSC.

Background to “Estimating the sea level highstand during the last interglacial: a probabilistic massive ensemble approach”

This post is about the new paper, which got out recently. The title of the paper is “Estimating the sea level highstand during the last interglacial: a probabilistic massive ensemble approach” and was published in Geophysical Journal International. It is an output from the iGlass project I have worked for until last year.

The paper addresses the sea-level evolution over the last interglacial. For this we use a GIA model, which is in model terminology a simple model, and compare it with the help of massive ensembles and a new data assimilation scheme to observations. Apart from introducing and demonstrating the methodology, this papers addresses many problems of this topic. It is designed to offer a different view on the LIG sea-level and on many complications we have, to determine it and its uncertainties.

This post is an introduction to some other background posts, which will be published here in the next couple of weeks. The topics I would like to write on are:

  1. Sea-level in the LIG: What are the problems?
  2. Massive ensembles: How to make use of simple models?
  3. Data assimilation with massive ensembles
  4. What can we say now on the LIG sea-level?
  5. What will the future bring?

With these topics I hope to bring in some personal views on this topic and explain some basic points of this very complex paper. It is not a paper, which has official head line numbers, as it is more a description on problems and introduction of new methodologies. For getting reliable numbers out, we have to rethink the problem, and this will certainly be done in the future.