EGU 2017: Complications of interdisciplinarity

The third day of the EGU is over and my day got busier than yesterday. It started with a look into a sea-ice session with an interesting view of predicting its decline. A key is not to look at the time as the decisive variable, but on the development of greenhouse gases in the atmosphere. The second half of the first session I went into a more applied geological session, which mainly asked questions about how boulders get onshore. Quite interesting were the implications on potential storm climate during the last interglacial. The second session I paid a visit to precipitation its retrieval and the resulting products. Precipitation is one of the most complicated variables to predict as well as to measure and has therefore always interesting developments to offer.

After lunch my next stop was again a medal lecture, this time on chaos and the presenter had some really nice examples. The remaining session was on ENSO, before I decided to visit the open session on ocean science. Some interesting talks, for example on the uncertainty of deep ocean heat content made it an interesting session. The final of the day was as always the poster session.

Conferences like the EGU are always great for researchers like me, who prefer to take look into different fields (as I personally focus on the developments of statistical methodologies, which do not require to stick to one field). Unfortunately, this leads even more to the problem that you have to decide what you would like to see. While often schedulers take care to give a consistent schedule for one discipline (even when it does not really work every time),  having several different divisions to follow needs some extra care. When I look onto the first three days, I have visited sessions of the following divisions (only the first division on the list): OS, GM, G, CL, AS, GI, CR, NP and NH. I am not quite sure, which division I belong to myself, but I have learned that it would be simpler to stick to one division only. Often the computer systems/apps are not designed to assist in the search of session of many (or all) divisions and it requires some extra work to do it properly. There is always a session you felt you have missed. Anyway, it is worth the effort and everyone has problems to get their ideal scheduling done. The current app is a nice feature, but there is still the question on how it will get better to really assist every type of scientist at such a huge conference.

EGU 2017: Medal lectures

The second day of the conference was a quiet day for me, as no must see sessions were scheduled for me today. It started again with the North Atlantic session, which this time focussed more on the oscillations, like NAO. Afterwards, I visited a medal lecture on SAR. This topic is quite far away from my daily work, but such conferences are always a chance to see things you are usually not confronted with. Important for me was the statement that in times in which data can be generated in huge numbers, data management gets more and more important. Big data requires new ideas on workflows, might have to include cloud services and poses new questions on data availability.

After lunch I visited a palaeo session on the common era, which also addressed in many points the long-term variabilities of our climate system. In a last session another medal lecture was scheduled and again the southern ocean was the topic. This time it was the circular current and a good overview on the methods used to understand this important part of the global circulation was illustrated in this talk. A good thing about medal lectures is that you can see in a compact way a whole topic. Even when you now bits and pieces about it, it helps to get deeper into it to by getting it introduced by a real expert of the research field. The final stage of the day was then the traditional poster session. Tomorrow will be half time, and it will start the busy part of this week for me.

EGU 2017: Start of the conference

Here we are. My fourth time at the EGU and as always there is a new record in the number of participants (somewhere around 14,000). The last time I attended this conference was 2014 and so a lot has changed. A symbol for this are the tents on the former meeting area in front of the main building, which are really a pity (I certainly will complain about it a lot this week ;)). My personal contributions will be all on Friday, so I have some days to look around and enjoy some chit-chat in the poster sessions. Continue reading

Statistics is subjective… always!

From time to time you listen to talks and in a moment you do not expect any surprises you hear the argument that statistics is objective. It is often used to strengthen other arguments and tries to prevent doubts in them. Much to often statistics is given a credibility it does not deserve and so the times it gets usefully applied get devalued. With this in mind, one thing have to be clear: Statistics is subjective…. always!

Quite often the words on objectivity are used in haste, often also from scientists who should know it better. Many arguments on the objectivity of statistics comes from the past, where frequentist statistics was the norm and its application for nearly every problem was seen as appropriate and therefore objective. But many forget, that by using frequentist statistics they make a choice. A choice on assumptions many have learnt years ago and are long forgotten.

May it be an assumption on normal distributions, on stationarity or ergodicity. Let’s be honest, those are never fulfilled, but always accepted indirectly by choosing a standard methodology. And when you doubt that you have a choice on your statistical methodology, then the answer is in nearly ever case that there is one. You do not have to go all the way to Bayesian statistics, there are many steps in between. The start is usually to think about the assumptions you are currently making in your methodology and then go the extra step to think what happens when one of these fails.

Most important is that we start to teach the students that statistics is based on assumptions. For myself it is a game of assumptions and usually you have a lot of freedom to make them. That does not mean that standard methods should not be taught, yes, for everyone who works in geoscience a foundation in statistical techniques is necessary. But it is important at the same time that we make clear that each methodology has its disadvantages and that alternatives exist. They are not necessarily easily to calculate, but they are certainly at least some seconds worth to think about.

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.