After seeing so many nice pictures of our topography and the glowing bright green current field around it in the tank, let’s go back to the basics today and talk about how this relates to reality outside of our rotating tank.
Figure 1 or Darelius, Fer & Nicholls (2016): Map. Location map shows the moorings (coloured dots), Halley station (black, 75°350 S, 26°340 W), bathymetry and the circulation in the area: the blue arrow indicates the flow of cold ISW towards the Filchner sill and the red arrows the path of the coastal/slope front current. The indicated place names are: Filchner Depression (FD), Filchner Ice Shelf (FIS), Luipold coast (LC) and Ronne Ice Shelf (RIS).
Above you see the red arrows indicating the coastal/slope front currents. Where the current begins in the top right, we have placed our “source” in our experiments. And the three arms the current splits into are the three arms we also see in our experiments: One turning after reaching the first corner and crossing the shelf, one turning at the second corner and entering the canyon, and a third continuing straight ahead. And we are trying to investigate which pathway is taken depending on a couple of different parameters.
The reason why we are interested in this specific setup is that the warm water, if it turns around the corner and flows into the canyon, is reaching the Filchner Ice Shelf. The more warm water reaches the ice shelf, the faster it will melt, contributing to sea level rise, which will in turn increase melt rates.
In her recent article (Darelius, Fer & Nicholls, 2016), Elin discusses observations from that area that show that pulses of warm water have indeed reached far as far south as the ice front into the Filchner Depression (our canyon). In the observations, the strength of that current is directly linked to the strength of the wind-driven coastal current (the strength of our source). So future changes in wind forcing (for example because a decreased sea ice cover means that there are larger areas where momentum can be transferred into the surface ocean) can have a large effect on melt rates of the Filchner Ice Shelf, which might introduce a lot of fresh water in an area where Antarctic Bottom Waters are formed, influencing the properties of the water masses formed in the area and hence potentially large-scale ocean circulation and climate.
The challenge is that there are only very few actual observations of the area. Especially during winter, it’s hard to go there with research ships. Satellite observations of the sea surface require the sea surface to be visible — so ice and cloud free, which is also not happening a lot in the area. Moorings give great time series, but only of a single point in the ocean. So there is still a lot of uncertainty connected to what is actually going on in the ocean. And since there are so few observations, even though numerical models can produce a very detailed image of the area, it is very difficult how well their estimates actually are. So this is where our tank experiments come in: Even though they are idealised (the shape of the topography looks nothing like “real” Antarctica etc.), we can measure precisely how currents behave under those circumstances, and that we can use to discuss observations and model results against.
You probably know that I have recently changed my research focus quite dramatically, from physical oceanography to science communication research. What that means is that I am a total newbie (well, not total any more, but still on a very steep learning curve), and that I really appreciate listening to talks from a broad range of topics in my new field to get a feel for the lay of the land, so to speak. We do have institute seminars at my current work place, but they only take place like once a month, and I just realized how much I miss getting input on many different things on at least a weekly basis without having to explicitly seek them out. To be fair, it’s also summer vacation time and nobody seems to be around right now…
I don’t really know how it happened, but by my fourth year at university, I was absolutely determined to work on how this teeny tiny process, double-diffusive mixing (that I had seen in tank experiments in a class), would influence the results of an ocean model (as I was working as student research assistant in the modelling group). And luckily I found a supervisor who would not only let me do it, but excitedly supported me in doing it.
Double-diffusive mixing, for those of you who don’t recall, looks something like this when done in a tank experiment:
And yep, that’s me in the reflection right there :-)
Why should anyone care about something so tiny?
Obviously, there is a lot of value in doing research to satisfy curiosity. But for a lot of climate sciences, one important motivation for the research is that ultimately, we want to be able to predict climate, and that means that we need good climate models. Climate models are used as basis for policy decisions and therefore should represent the past as well as the present and future (under given forcing scenarios) as accurately as possible.
Why do we need to know about double-diffusive mixing if we want to model climate?
Many processes are not actually resolved in the model, but rather “parameterized”, i.e. represented by functions that estimate the influence of the process. And one process that is parameterized is double-diffusive mixing, because its scale (even though in the ocean the scale is typically larger than in the picture above) is too small to be represented.
Mixing, both in ocean models and in the real world, influences many things:
By mixing temperature and salinity (not with each other, obviously, but warmer waters with colder, and at the same time more salty waters with less salty), we change density of the water, which is a function of both temperature and salinity. By changing density, we are possibly changing ocean currents.
At the same, other tracers are influenced: Waters with more nutrients mix with waters with less, for example. Also changed currents might now supply nutrient-rich waters to other regions than they did before. This has an impact on biogeochemistry — stuff (yes, I am a physical oceanographer) grows in other regions than before, or gets remineralized in different places and at different rates, etc.
A change in biogeochemistry combined with a changed circulation can lead to changed air-sea fluxes of, for example, oxygen, CO2, nitrous oxide, or other trace gases, and then you have your influence on the atmosphere right there.
What are the benefits of including tiny processes in climate models?
Obviously, studying the influence of individual processes leads to a better understanding of ocean physics, which is a great goal in itself. But that can also ultimately lead to better models, better predictions, better foundation for policies. But my main point here isn’t even what exactly we need to include or not, it is that we need a better flow of information, and a better culture of exchange.
Talk to each other!
And this is where this tale connects to me missing institute seminars: I feel like there are too few opportunities for exchange of ideas across research groups, for learning about stuff that doesn’t seem to have a direct relevance to my own research (so I wouldn’t know that I should be reading up on it) but that I should still be aware of in case it suddenly becomes relevant.
What we need is that, staying in the example of my double-diffusive mixing article, is that modellers keep exploring the impact of seemingly irrelevant changes to parameterizations or even the way things are coded. And if you aren’t doing it yourself, still keep it in the back of your head that really small changes might have a big influence, and listen to people working on all kinds of stuff that doesn’t seem to have a direct impact on your own research. In case of including the parameterization of double-diffusive mixing, oceanic CO2 uptake is enhanced by approximately 7% of the anthropogenic CO2 signal compared to a control run! And then there might be a climate sensitivity of processes, i.e. double-diffusive mixing happening in many ore places under a climate that has lead to a different oceanic stratification. If we aren’t even aware of this process, how can we possibly hope that our model will produce at least semi-sensible results? And what we also need are that the sea going and/or experimental oceanographers keep pushing their research to the attention of modellers. Or, if we want less pushing: more opportunities for and interest in exchanging with people from slightly different niches than our own!
One opportunity just like that is coming up soon, when I and others will be writing from Grenoble about Elin Darelius and her team’s research on Antarctic stuff in a 12-m-diameter rotating tank. Imagine that. A water tank of that size, rotating! To simulate the influence of Earth’s rotation on ocean current. And we’ll be putting topography in that! Stay tuned, it will get really exciting for all of us, and all of you! :-)
P.S.: My #COMPASSMessageBox for this blogpost below. I really like working with this tool! Read more about the #COMPASSMessageBox.
And here is the full citation: Glessmer, M. S., Oschlies, A., & Yool, A. (2008). Simulated impact of double‐diffusive mixing on physical and biogeochemical upper ocean properties. Journal of Geophysical Research: Oceans, 113(C8).
I’ve been working in science communication research for a good half a year now, and my views on outreach are constantly evolving. When I applied for this job, I was convinced that if only the public knew what we (the scientists) know, they would take better decisions. So all we need to do is inform the public, preferably using entertaining and engaging methods. However, I soon came to learn that this is known as the “deficit model” and that there is a lot of research saying that life isn’t that easy. Like, at all.
One article I really like makes it very clear that knowledge about what science says is not at all the same as believing in what science says. The article Climate-Science Communication and the Measurement Problem by Kahan (2015) (btw, a really entertaining read!) describes how changing a question on a questionnaire from “Human beings, as we know them today, developed from earlier species of animals” to “According to the theory of evolution, human beings, as we know them today, developed from earlier species of animals” has a big impact: While in the first case, religiosity of the respondents had a huge impact and even highly educated religious people are very likely to answer “no”, in the second case religious and non-religious people answer similarly correctly. So clearly the knowledge of what evolution theory says is there in both cases, but only in the latter case that knowledge becomes relevant in answering the question. In the first case, the respondents cultural identity dictates a different answer than in the second case, where the question is only about science comprehension, not about beliefs and identity. As the author says: a question about ““belief in” evolution measures “who one is” rather than “what one knows””.
The author then moves on to study knowledge and beliefs about climate change and finds the same thing: the relationship between science comprehension and belief in climate change depends on the respondents’ identities. The more concerned someone is about climate change due to their cultural background, the more concerned they become as their level of science comprehension increases. The more sceptical someone is, the more sceptical he becomes with increasing science comprehension: “Far from increasing the likelihood that individuals will agree that human activity is causing climate change, higher science comprehension just makes the response that a person gives to a “global- warming belief” item an even more reliable indicator of who he or she is.”
So knowledge (or lack thereof) clearly isn’t the problem we face in climate change communication — the problem is the entanglement of knowledge and identity. What can we do to disentangle the two? According to the article, it is most important to not reinforce the association of opposing positions with membership in competing groups. The higher-profile the communicators on the front lines, the more they force individuals to construe evidence that supports the claims of those high-profile members of their group in order to feel as part of that group and protect their identity. Which is pretty much the opposite of how climate science has been communicated in the last years. Stay tuned while we work on developing good alternatives, but don’t hold your breath just yet ;-)
— Kahan, D. M. (2015). Climate-Science Communication and the Measurement Problem Political Psychology, 36, 1-43
What is the impact of this blog? And who am I writing it for?
Those are not questions I regularly ask myself. The main reason I started blogging was to organise all the interesting stuff I was collecting for my introduction to oceanography lecture at the University of Bergen in one place, so I would be able to find it when I needed it again. And I wanted to share it with friends who were interested in teaching oceanography or teaching themselves.
Another of the reasons why I blog is that I notice a lot of exciting features in everyday life that relate to oceanography and/or physics, that other people would just walk past and not notice, and that I would like to share the wonder of all those things with others. And noticing all this stuff is so much FUN! The blog “gives me permission” to play, to regularly do weekend trips to weirs or ship lifts or other weird landmarks that I would probably not seek out as often otherwise.
But the other day I was browsing the literature on science blogging in order to come up with recommendations for the design of what is to become the Kiel Science Outreach Campus’ (KiSOC) blog. I came across a paper that resonated with me on so many levels: “Science blogs as boundary layers: Creating and understanding new writer and reader interactions through science blogging” by M-C Shanahan (2011). First, I really liked to see the term “boundary layer” in the title, since it brings to mind exciting fluid mechanics. Then second, I read that the boundary phenomena I was thinking of were really where the term “boundary layer” came from even in this context. And then I realised that I have had “boundary layer” experiences with this blog, too!
So what are those boundary layers about? Well, in fluid mechanics, they are the regions within fluids that interact with “something else” — the boundary of a flow, e.g. a pipe, or a second fluid of different properties. They are a measure for the region over which temperature or salinity or momentum or any other property is influenced by the boundary. But the same construct can be used for social groups, i.e. in my case oceanographers and non-oceanographers. (You should, btw, totally check out the original article! Her example is even more awesome than mine)
But here is my own boundary layer experience: My sister sent me an email with the subject “double-diffusive mixing” and a picture she had taken! My sister is not an oceanographer, and I wasn’t even aware that she associated the term “double-diffusive mixing” with anything in particular other than me writing my Diplom thesis about it and probably talking about a lot. But that she would recognise it? Blew my mind!
Turns out what she saw is actually convection, but it doesn’t look that dissimilar from salt fingers, and how awesome is it that she notices this stuff and thinks of oceanography?
Day 1. The remaining pink soap starts making its way up through the refill of clear soap.
Obviously I asked for follow-up pictures:
Day 2. A lot of the pink soap has reached the top, passing through the clear refill.
Day 3. All of the “old” pink soap is now on its way up through the clear refill.
And I had another boundary layer experience recently: A sailor on the Norwegian research vessel Håkon Mosby with many many years experience at sea had seen my book and told me that he now looks at waves in a new way. How awesome is that? That’s the biggest compliment my book could get, to teach something new about visual observations of the ocean to someone who looks at the ocean every single day!
Anyway. Reading this article made me think about how happy both those boundary layer experiences made me, and that maybe I should actually start aiming at creating more of those. Maybe not with this blog, that I kinda want to keep as my personal brain dump, but there are so many different ways to interact more with people who would potentially be super interested in oceanography if only they knew about it… I guess there is a reason why I am working the job I am :-)
— Shanahan, M. (2011). Science blogs as boundary layers: Creating and understanding new writer and reader interactions through science blogging Journalism, 12 (7), 903-919 DOI: 10.1177/1464884911412844
What’s discussed in that article is that while many wave interactions can be seen as (more or less) linear, sometimes there are nonlinear effects that can be replicated in a model. So far so not surprising. But I got fascinated because the phenomenon they look at I have seen over and over again and never really paid any attention to it: Wave crests forming X or Y shapes. But looking through my archives, I even had dozens of pictures of this exact phenomenon! (Actually, I didn’t have to look further back than to a beautiful day last November, when I also observed the wavelength dependency of wave-object interactions)
Take for example the picture below: Do you see the H shape in the waves closest to shore? (In the article they would probably call it a more-complex shape, since it’s a double Y shape…)
Below I’ve drawn into the picture what I mean by H-shape in green, and the typical kind of linear wave interaction in red (all crests just move on without influencing each other except in the spot where they occur at the same time, there they just add to each other):
Or below, I spot an X-shape:
And here are several X- and Y-shapes
And the picture below just to give you an orientation of where you are: Yep, it’s the same spot where we usually observe foam stripes, funny waves, or ice…
— Mark J. Ablowitz, & Douglas E. Baldwin (2012). Nonlinear shallow ocean wave soliton interactions on flat beaches Physical Review E, vol. 86(3), pp. 036305 (2012) arXiv: 1208.2904v1
In most of my blog posts on outreach I focus on how to run the _perfect_ experiment. And while I still think that’s awesome, I recently read an article by Johanna Varner (“Scientific Outreach: Toward Effective Public Engagement with Biological Science”, 2014) that made a lot of points that I have definitely not stressed enough on my blog, and probably not even considered enough.
Outreach is often modeled on scientific communication and intuition. Of course, since that is what we’ve learned over the years and gotten good at, and what we are most comfortable with. But when we are trying to engage the “general public”, those are mostly people who have a very different background from us. Speaking of backgrounds — there is a problem with the concept of “the general public”, as there is no _one_ general public. The general public is very very diverse, and it is important to consider each audience individually. And there is the next thing: “Audience” then often implies that a scientist talks and “the general public” listens, which is not the best model. One-way communication that we often use in outreach, more often than not using simplified, sensationalized stories, is just not effective. For retention of facts as well as for building enthusiasm and for engaging in deep thinking, the public needs to be actively engaged, not talked to.
To also consider is that the reliability of a source is not judged by how many PhDs a speaker has, but by how well it supports the listener’s preconceptions. Any new information is interpreted in such a way that it supports existing ideas. And even if ideas could be “objectively transferred”: new knowledge does not change attitudes or behaviour. And even the intention to act is a poor predictor of future behaviour!
So what can we do?
The article provides a structure for planning outreach activities which is basically backward design: Start with what you want people to learn, then think about what you would take as evidence that they actually learned it, and then plan the activity. Check out the article if you are not familiar with the concept, it’s a really nice introduction. And it is always important to remember that effectiveness of any activity depends on an explicit definition of the goals.
Then, there are a couple of design elements we can use. All of those come from the article originally, but I give my own interpretation and examples.
Use “trusted resources” to help us share our message. Instead of doing our outreach activity as a self-organized event, use local churches, artists, any institution or person whom the community trusts to invite you and set the stage for you, this will make it much more likely that people will not only listen to, but actually consider taking on your message.
Know your audience. This is super difficult! But since you will want to create personal relevance for your audience (since personal relevance is essential for engagement), you need to know about what your audience’s knowledge, attitudes, values are. And it goes without saying that every outreach activity needs to be tailored to each audience specifically.
Establish common ground with your audience, this makes your message more likely to be accepted. Don’t be the scientist who nobody can relate to, be the person who lives in the same neighbourhood, who supports the same sports team, who likes the same kind of music, whatever is applicable in your case.
Use appropriate language! Don’t alienate by speaking to science-y, and also beware that words carry a very different meaning in science than in everyday language sometimes (And if you have never seen those tables that tell you that the term “alcohol”, vor example, means “booze” to the general public, when you use it to mean “solvent”, definitely check out examples of such tables here or here!)
Get into dialogue instead of just “preaching” in a one-way manner. Ask for questions and feedback, offer to follow-up by email, engage with the people there!
Frame your science in a storyline. It makes it much easier to follow and to digest as well as to remember.
Click to enlarge
Use “vivid hooks”, i.e. present your research question as an actual question or puzzle to solve, ask people to brainstorm hypotheses, show them the real data, let them get actively involved! Experiential learning and personal experience influence attitudes and beliefs strongly. This might be easiest if you had animals to show, but even just a good question works. Sometimes it’s actually surprising to see what works: The other day I had a blog post showing an empty bottle and one filled with water and asked whether people knew which one was which. And I got so many private messages with people’s answers, asking me to confirm they were correct! I had never thought that this particular blog post would raise such interest.
Emphasize benefits of action rather than risks of inaction. Fear appeals can backfire, since they lead to feelings of helplessness, which then lead to denial, apathy, resignation. And all of those prevent engagement.
Provide action resources. Enthusiasm and active engagement don’t stay up for very long after you are done with your outreach experiment if you don’t do something to keep them up. Therefore, provide action resources! Let people know when your next event will be, or the schedule of public events at your institution. Hand out take-home activities. Provide online resources or lists of other people’s online resources. Make sure that those who would like to stay engaged have a very low threshold to do so!
And now, go read the original research where all of these ideas came from:
Varner (2014) “Scientific Outreach: Toward Effective Public Engagement with Biological Science”
The author describes research on how, why and when explaining leads to new learning. You should go check out the original blog post, too, but here is what I am taking away from it: When you explain, you are looking for general pattern.
The author cites research that shows that explaining to yourself is not the best strategy for all kind of learning outcomes — only for those that are related to the causal effects you were explaining to yourself. For other details, it might be a better strategy to just observe, or describe what you are seeing.
How is this relevant for our teaching? There are several ways.
Explaining to themselves is a strategy we can recommend to our students. I remember studying for my oral examinations at Vordiplom (now equivalent to Bachelor) level. I used to come up with questions and try and answer them late at night when I couldn’t go to sleep (Why is the Atlantic ocean more salty than the Pacific ocean? This kind of stuff). Those were questions that I didn’t know the correct answer of at the time (and some of my questions there might not be an answer) and it definitely helped me when I was then asked what geometry of sound receivers I would use if I were to build an array for SOFAR floats, and it made me feel safer going into the exam, knowing that I had answered all questions that I could come up with previously as well as I could.
And of course you can just tell students that they will have to teach about a topic, since anticipating having to teach already leads to improved learning. Then you can reflect later on how thinking they would have to teach led them to use different learning strategies, and whether they might want to use those in the future even when they were not expecting having to teach.
I even see a similar effect with having a blog. Now, when I take pictures of water somewhere, I observe pretty carefully, anticipating that I will write about what I saw and that someone might ask questions about it. That definitely makes me put a little extra effort into observing and thinking about what might be going on there!
Have you ever worked as student tutor? Then you’ve probably felt like you understood the content of the course you tutored a million times better after tutoring it. Or at least that’s what I hear over and over again: People feel like they understood a topic. Then they prepare to teach it, and realise how much more there was to understand and that they actually understood it.
And there is research that shows that you don’t actually need to teach in order to get the deeper understanding, it is enough to anticipate that you will teach: “Expecting to teach enhances learning and organization of knowledge in free recall of text passages” by Nestojko, Bui, Kornell & Bjork (2014).
In that article, two groups of participants are given texts that they are to study. One group is told that they will be tested on the text, the other one that they will have to teach someone else who then will be tested. After all participants study the text, they are then all tested (and nobody gets to teach). But it turns out that even expecting to teach had similar benefits to what we see in student tutors who actually taught: Participants expecting to teach have a better recall of the text they had to study, can answer more questions about it and especially questions regarding main points.
So what does that mean for teaching? As the authors say: “Instilling an expectation to teach […] seems to be a simple, inexpensive intervention with the potential to increase learning efficiency at home and in the classroom.” And we should definitely use that to our advantage! :-)