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
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
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.
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.
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.
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.
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:
- Sea-level in the LIG: What are the problems?
- Massive ensembles: How to make use of simple models?
- Data assimilation with massive ensembles
- What can we say now on the LIG sea-level?
- 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.
The second day started with a detection and attribution session. The talks ranged from theoretical approaches to the plans for the future large projects in this field. This was followed by a talk on extremes before the next session focussed on teleconnections. In the latter session as expected the EOF analysis got some attention.
After the lunch break I enjoyed a session on the great challenges of climate extremes. Talks therein applied statistics to some interesting real applications, so showed that different methodologies can be really helpful for the community.
The final session of the day was reserved for the poster session. For me posters are always a very important part of a conference and it is good when it is placed at the right time into the schedule. It offers people to talk and get to know each other and helps therewith to make a conference a success. Today some interesting posters were presented on a wide range of topics. Tomorrow, at the halftime of the conference, I got my own talk and so I look forward to the remaining days here in Canmore.