The Present Day and Future Climate of Greenland

Regional Climate Model Data from HIRHAM5 for Greenland

In this post I am linking to a dataset I have made available for the climate of Greenland. In my day job I run a Regional Climate Model (RCM) over Greenland called HIRHAM5 . I will write a simple post soon to explain what that means in less technical terms but for now I just wanted to post a link to a dataset I have prepared based on output from an earlier simulation.

Mean annual 2m  temperature over Greenland (1989 - 2012) from HIRHAM5 forced by ERA-Interim on the boundaries
Mean annual 2m temperature over Greenland at 5km resolution (1989 – 2012) from HIRHAM5 forced by ERA-Interim on the boundaries [Yes I know it’s a rainbow scale. Sorry! it’s an old image – will update soon honest…]

This tar file gives the annual means for selected variables at 0.05degrees (5.5km) resolution over the Greenland/Iceland domain.

I am currently running a newly updated version of the model but the old run gave us pretty reasonable and could be used for lots of different purposes. I am very happy for other scientists to use it as they see fit, though do please acknowledge us, and we especially like co-authorships (we also have to justify our existence to funding agencies and governments!).

This is just a sample dataset we have lots of other variables and they are available at 3 hourly, daily, monthly, annual, decadal timescales so send me an email (rum [at] dmi [dot] dk) if you would like more/a subset/different/help with analysis of data. This one is for the period 1989 – 2012. I have now updated it to cover up to the end of 2014. The new run starts in 1979 and will continue to the present and has a significantly updated surface scheme plus different SST/sea ice forcing and a better ice mask.

I have also done some simulations of future climate change in Greenland at the same high resolution of 5km using the EC-Earth GCM at the boundaries for RCP4.5 and RCP8.5 scenarios which could be fun to play with if you are interested in climate change impacts in Greenland, Iceland and Arctic Canada.

Mean annual 2m temperature change between control period (1990 - 2010) and end of the century (2081 - 2100) under RCP45 from HIRHAM5 climate model runs forced by EC-Earth GCM at the boundaries
Mean annual 2m temperature change between control period (1990 – 2010) and end of the century (2081 – 2100) under RCP45 from HIRHAM5 climate model runs forced by EC-Earth GCM at the boundaries.  This plot shows the full domain I have data for in the simulations.

This run should be referenced with this paper:

Quantifying energy and mass fluxes controlling Godthåbsfjord freshwater input in a 5 km simulation (1991-2012), Langen, P. L., Mottram, R. H., Christensen, J. H., Boberg, F., Rodehacke, C. B., Stendel, M., van As, D., Ahlstrøm, A. P., Mortensen, J., Rysgaard, S., Petersen, D., Svendsen, K. H., Aðalgeirsdóttir, G.,Cappelen, J., Journal of Climate (2015) 

PDF here

Finally I should acknowledge that this work has been funded by a lot of different projects:


Climate and ice sheet modelling at DMI

I was very honoured to be asked to give a short talk last week to some students at the Danish Technical University. The subject was ice sheet modelling and climate at DMI where I work in the Research department, climate and Arctic section.
I thought this could be interesting for others to look at too, so I have uploaded the powerpoint presentation on my page.

In the presentation I try to explain why we are interested in climate and ice sheets and then give a brief overview of our model systems and the projects we are currently working on. We are mainly interested in the Greenland ice sheet from the perspective of sea level rise. If we are to climate change we need to know how fast and how much of Greenland will melt and how this will change local and regional sea level. There are also studies showing that increased run-off from the ice sheet may change ocean circulation patterns and sea ice. There is lots more stuff to look at so feel free to download it.

I end up with a very brief overview of our biggest project at the moment, ice2ice. This is a large ERC funded project with the Niels Bohr Institute and partners in Bergen at the Bjerknes Climate Research Centre. I may write a brief post on ice2ice soon if I get chance. It’s a really interesting piece of work being focused on past glacial-interglacial climate change rather than present day or the future and I think we have potential to do some great science with it.

At the risk of seeming like I’m blowing the DMI trumpet (something rarely done or even really seen as socially acceptable in Denmark!), I think we at DMI have a lot to be proud of. We are a small group from a small country with limited resources but my colleagues have pioneered high resolution regional climate modelling of the Greenland ice sheet and the development of coupled climate and ice sheet models at both regional and global scales. I was brought in as a glaciologist to work on the interface between ice sheet and atmosphere, needless to say I have learnt a hell of lot here. It’s been an exhilarating few years.

If you have any questions, I will enable comments for this thread (but with moderation so it may take  a while for you to see it).

Finally, here is a little movie of calving icebergs

shot by Jason Amundson, University of Alaska Fairbanks at Jakobshavn Isbrae in West Greenland.




A Svalbard Field Journal, part 1.

This is a piece about field work I did in Svalbard in 2010. I’m not sure it really belongs here, but I hope it is interesting to read about what Arctic fieldwork is really like. I have been tremendously lucky to have had several opportunities to work in the Arctic, but as I hope this makes clear, it’s quite often a big slog with uncertain outcomes.

The sun rises early in March in Svalbard but it is not yet hitting the town, we are before the Solfest in Longyearbyen, and I am lying in bed alternately wishing I could sleep longer and being hugely excited at the prospect of getting out in the field again. With the light comes the cold, it is -26C outside with a fresh wind and some light snow falling, not brilliant weather for fieldwork. I am 12 weeks pregnant and the nausea comes early and remains all day but I hope the cold dry air on the glacier will help. In spite of that, I know my fieldwork opportunities will likely significantly reduce when the baby arrives so I’m determined to do one last big trip.

Down at UNIS (the university centre on Svalbard), our boxes are already packed with equipment, we just need to get them on the sledges, pick up our snowscooters and go. This is prime fieldwork and study time and the logistics centre is bustling with students, excited to be out on their first trip, and the long-termers getting ready to set up experiments. I’ve already got my scooter gear sorted out, huge padded suit, enormous padded boots, crash helmet, thin woollen undergloves, leather gauntlets, neoprene face mask. It feels a bit ridiculous inside but I know I’ll need it later on the scooter and the glacier.

Packing a sledge is an artform, one which, over the course of the week, I will gradually start to master, but for now I’m pretty useless and just try and hold stuff when asked and keep out the way while my colleague C gets on with showing me how it’s done.

Finally, we’re off, later, as usual, than we’d wanted, but all the kit is with us and we’re making good time. Our route intially lies up Adventdalen (named for the old whaler Adventure which explored this area). In summer this is a more-or less impassable morass of braided streams, gravel, mud and silt, glacially scoured rocks brought down by an ever shifting river. When the cold comes, and the river and the soil freeze, and then the snow falls, this is the main highway out of town.

We follow a long straight line of multiple overlaid scooter trails; riding a scooter is like riding a motorbike, fast, loud and exciting. I get up to 80km/h on the straight, in spite of towing a trailer, and wonder vaguely if the foetus can feel the vibrations. I thank UNIS silently for having such good kit, the heated handlebars of the scooter are essential, and in spite of the boots my feet are already getting chilly, I remember to wiggle my toes to keep them warm and, as we peel away from the main trails and slowly motor up ever narrower valleys and gullies, I lift my goggles momentarily to allow the frozen condensation on the inside to clear.

We are heading to Tellbreen (breen meaning the glacier in Norwegian, the “tell” in question being, I suspect, William Tell), a small and rather unimportant glacier about an hour and a half from Longyearbyen. A number of small and unrelated projects are going on there this year and there is a weather station lower down that we will be using. We will be working very high up on the glacier near the col at the top where the glacier divides in two. It falls fairly steeply down from this point and I struggle to get the scooter with the trailer up. I realise too late I haven’t given it enough power and there is a slow inevitable deceleration as the scooter digs itself into the soft snow. Fresh soft snow on a slope is the hardest for a scooter to deal with and I have just made the classic mistake. I determine not to make it worse and wait for my colleague C to return with the spade. You don’t drive anywhere in Svalbard without a spade. It’s not a bad dig-in and within half an hour we’re finally at the top of the glacier.

C and a student came out in late Autumn and put two tarpaulins on the glacier surface. These will be the baselines for our experiments. Their positions marked with 2m long bamboo canes. Very little of the canes are showing through the snow and it takes us a while to locate them. The wind is getting fresher and blowing snow through the pass, we are in an incredibly exposed position and I am even more thankful for UNIS equipment. Our first task is to dig a work trench. This will give us protection from the wind but will also be where we stick our temperature sensors into the snow. We will be placing two large water canisters in the snow pack and letting the water, with a dye added, drip through the snow and refreeze. At the second site the canister will be directly on the glacier surface. The temperature sensors will record the effect the water has on the snow temperature at different depths. At the end of the experiments we will dig through the snow to find the ice, record how far it has run and how thick it is. The dye will tell us on which day the water ran through.

It sounds like a simple and very esoteric set of experiments, but it is actually intended to help us shed light on a very difficult problem. Most of the glaciers in the Arctic melt, at least partly, in summer, but the water does not run off, it refreezes in the snow or on the surface of the glacier, forming superimposed ice. It is almost impossible to distinguish superimposed ice from normal glacier ice remotely so while we can measure melt directly by satellite, we have little idea how much of it remains on the glacier and how much is lost to the ocean. The GRACE and GOCE missions give us another way to measure mass loss over large regions but for climate models like the one I run in Denmark, where we make future projections of glaciated regions, we still need to factor this in. The work C and I are engaged in is aimed at developing an approximation we can put into the model to take this into account. In Antarctica the problem doesn’t occur as most of the glaciers there don’t melt.

We have brought a snow blower with us to plough the snow away and it is making short work of the trench, there is still a lot of digging to do though, and I reflect that whenever I am in the Arctic I seem to find myself doing a lot of digging either for latrine pits, to examine glacier sediments or to clear snow. At the Greenland ice core sites high up on the ice sheet, famously the first thing you’re given when you arrive is a spade.

I try and cut some blocks of snow to use as a wall against the wind but the snow is too soft and my efforts are only partly successful. Thankfully though, C had thought to bring some wide boards and we use these to cover the trench so we can work sheltered from the howling wind. It has taken us almost all day to dig the trench and the hole for the first water canister. Now it’s starting to get dark and we really need to leave before driving down the glacier gets too hazardous. We hurriedly stick the sensors in the snow pack, I’ll have to measure the spacings accurately tomorrow, fill the canister with dye and warm(ish) water and open the tap to a dripping position. As the wind gets even stronger we cover over the trench as far as we can, gather our stuff, shouting at each other to be heard over the wind and get out of there.

By the time we’re off the glacier it’s almost completely dark and I am grateful for the strong headlights on the scooter, even so it’s a much slower trip back as we carefully try to avoid the rocks and hard ice chunks that litter the track. I am exhausted with the work and the fatigue of early pregnancy, but high as a kite with the successful completion of the work we’ve managed today – I wasn’t sure we’d manage as much as we did. Tomorrow we do the second experiment, but for now it’s time for a beer (for C) and an orange juice a big plate of chips and a hamburger in the pub for me. I had barely managed to eat anything all day, it’s too cold and I simply wasn’t hungry enough to attempt it. I am extremely thirsty, the work was physical and sweaty, but in the cold you don’t feel the thirst, and I always forget to drink.

I fall into bed at 10pm, ready to do it all over again tomorrow.

To be continued….

Science under attack

I had planned another subject for todays blog, but having watched the recent Horizon programme on science under attack on BBC iplayer (still available for those with a British IP address) I thought it tied in rather neatly with why I decided to start this blog.

In the first place the idea came to me to start a blog as a way of practicing my own writing skills. Then secondly I thought I might have something interesting to say. When people find out I’m a climate scientist I often get all sorts of questions about climate change ranging from the basic (is it really happening?) to the more nuanced and complex (how do models work?) to, unfortunately, yet another repetition of the usual climate myths (see below). This blog should be a small window on the world where I write about things that interest me and hopefully are interesting to others.

Cartoon from the Union of Concerned Scientists

As I looked in to the world of blogging, and in particular into blogging on climate related themes, a huge number of blogs came up. Unfortunately, many of them are rather weak on science and very overtly political. In fact a quick scan of the google hits brings up rather more blogs and websites by what might (kindly) be called “sceptics” (or otherwise known as “deniers”) than blogs created by scientists. There is some really good material on the web dealing with climate related issues, for example the excellent blog but in many other places there is a lot of dross and the same empty myths endlessly recycled and repeated (for example, “it’s the little ice age”, “it was warmer in the Medieval period”, “it’s sun spots” etc etc), largely I’m afraid due to lazy and/or politically motivated journalism. All of these common myths have been explained over and over again, usually by people far better qualified, and far more skilled in writing than I, yet somehow they seem to persist.

As the Horizon documentary made clear, this is a source of immense frustration to many in the climate field, including myself, so I feel the time has come to stick my head above the parapet so to speak and start broadcasting my own opinions. At least I hope it will be a small addition to the counterbalancing work done by people like Real Climate and maybe it will help open some minds.

The same documentary blamed scientists for being poor communicators and I would tend to agree with that, it’s hard to talk about uncertainties in models for examples when even the word uncertainty is used very differently in science than in everyday life. On the other hand, this article on communication in the journal Nature by Tim Radford suggests that in fact scientists can be good communicators and he cites such luminaries as Carl Sagan, E.O. Wilson, Stephen Jay Gould and even Richard Dawkins (although I fear the latter has alienated a large part of the audience with his agressive approach to atheism). These are all great examples of great communicators of science, and though I fear I couldn’t possibly get close to their talent, I hope that this blog will help to develop my skills further.

One further point, Ben Goldacre, the Guardian’s excellent bad science columnist is a witty, knowledgeable and hard working advocate of good science who works tirelessly against vested interests, quackery, big pharma and other ‘enemies of reason’. In this post about the Copenhagen climate summit he explores the psychology of climate science and why it is so difficult to communicate. He points out that

‘climate science is difficult. We could discuss everything you needed to know about MMR and autism in an hour: the experimental techniques of epidemiology and other disciplines, how they’ve been misrepresented, the results, strengths, and weaknesses of the key studies. Climate change will take two days of your life, for a relatively superficial understanding: if you’re interested, I’d recommend the IPCC website itself, where they have a series of three executive summaries for policy makers, which are perfectly good pieces of humourless popular science writing.’

This is very true and I am certainly not going to use this blog to explain all issues related to climate change research. In fact, I aim to produce pieces about all sorts of scientific curiosities, natural wonders and society’s response to these. I have imposed two other conditions on myself. Firstly, I should not spend more than an hour on any one post and secondly, I want to post at least twice a week. I’ve broken the latter already, but thanks to my friend Heather I’ve been inspired to try again.


Forecasting the weather part 1: Differences between forecasts

This is the first part of an occasional series that I intend to write about why it’s so difficult to forecast the weather. In the UK the forecast can be notoriously wrong but it seems to me that most people have no idea how difficult it is to make a good forecast, especially in a maritime climate with air masses coming from all sides. This first piece is based on something I wrote for an online forum when another forumite complained that there were two different forecasts for their area that never seemed to agree.

The divergence between two weather forecasts for the same area over the same period can actually come from a whole range of differences between the different forecasters. In Europe most forecasters use the same observational dataset provided by the European Centre for Medium Range Weather Forecasting (ECMWF). This cuts out one set of problems as weather is famously chaotic and very small changes in starting conditions can lead to big changes in outcome, otherwise known as the butterfly effect. The famous storm of 1987 which destroyed millions of trees in southern England and caused millions of pounds of damage but which was not forecast accurately turns out to have been a super unpredictable event as shown in this talk given at the American Geophysical Union in San Francisco in December 2010. However, chaos theory is fascinating in it’s own right so perhaps I’ll give it a post to itself another time.

In day to day forecasts, the biggest difference is probably in the resolution of the model (if you imagine that an area, say the UK, is divided up into little squares, the computer model solves a whole lot of equations for each square).
If the square is 5km by 5km in size then some processes, and a lot of the topography will be smoothed out, but if the square is 500m by 500m then a lot more will be captured. Imagine a hill of 1000m rising out of a flat plain only 100m high in a particular location. The elevation of the square is the average of the whole elevation. In the 5km by 5km model, the entire hill and an equal area of plain is captured so in the square the average elevation may be 500m, but in the 500m by 500m model it may need 4 squares to accurately cover the hill alone and each square will have a different elevation.

Temperatures typically go down as you go higher, and rain will fall as the air cools, so if the hill isn’t “resolved” in the model the prediction may be unrealistically warm and dry. This is why forecasters like high resolution models, but that resolution comes at a high cost, because you need to increase the vertical resolution (the number of squares in the atmosphere) and reduce the length of time between each calculation as the horizontal resolution increases.

Another source of difference are the actual equations solved in the model. These can be formulated in different ways and with different approximations and are often “tuned” so a model that works really well in Scotland is unlikely to be so successful in the Sahara (where I imagine forecasting is actually pretty easy – it’ll be hot and sunny). That’s not to say the models are “wrong” just that they perform better in some circumstances than others and are designed for different purposes often.

Finally, a further important difference is the updating of the model with real time observations and at the boundaries. Most models are not run for the whole wold, but only a small portion (the whole world can be run at a resolution of about 20km nowadays, but it takes a lot of very expensive computer power). More effective is running a small section (say the UK), and telling the computer what is happening at the edges of the box based on satellite and ground observations. These can also be fed in to the area within the model to nudge it in the right direction. In practice as I mentioned earlier, in Europe most national agencies get this information from a single source, the ECMWF. Also, the models tend to be “better” than the observations (as measurements can go wrong, instruments might be wrongly calibrated etc), so at any given moment a weighting of about 40% is applied to observations and 60% for the model, depending on what in particular you’re looking at.

So the accuracy of any forecast depends on where you live and also how far in the future you need your weather to be reliable. Most forecasts aren’t bad up to 3 days in advance in general terms but the specifics can change quickly. Beyond that to 5 days is more tricky and depends on the large scale situation, for example is there a stable high pressure dominating or a series of storms and which way will a weather system move. Beyond a week to 10 days the forecasters are basically just guessing (at least in a maritime climate like the UK) and this why the met office has recently discontinued seasonal forecasts as they can be very unhelpful.