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Geosciences Column: climate modelling the world of Game of Thrones

Geosciences Column: climate modelling the world of Game of Thrones

Disclaimer: This article contains minor spoilers for Season 8 of “Game of Thrones.” A basic understanding of the world of Game of Thrones is assumed in this post.

The Game of Thrones world of ice and fire is an unpredictable place both politically and environmentally. While the fate of the Iron Throne is yet to be confirmed, a humble steward has been working diligently to make some sense of the planet’s peculiar climate. The results could help scholars assess when future winters will be coming or how wind patterns may influence where eastern attacks on Westeros from invading dragons and ships would occur.  

It is known that the realms of Westeros and Essos are subject to long-living seasons, with many extending over several years, but Samwell Tarly, the former heir of House Tarly and current steward of the Night’s Watch, has developed a new theory to explain this long seasonal cycle.

His research suggests that the seasons’ extended lifespans could be due to periodic changes in the planet’s tilt as it orbits around the Sun. The results were published in the Philosophical Transactions of the Royal Society of King’s Landing in the Common Tongue, with translations available in Dothraki and High Valyrian.

Tarly carried out his analysis while on sabbatical at the Citadel in Oldtown, Westeros. In the published article he notes that his study was “inspired by the terrible weather on the way here to Oldtown”.

Uncovering climate observations and models

Tarly’s first developed his theory after studying observational climate records stored in the Citadel library’s collections. Many of these manuscripts contain useful information on a number of climate conditions present within the Game of Thrones world, including the multiyear length of seasons.

Seasons occur when regions of a planet receive different levels of sunlight exposure throughout a year. The southern and northern hemispheres experience opposite degrees of sunlight exposure due to the natural tilt of the planet’s axis as it orbits around the Sun. For example, when the southern hemisphere is tilted closer to the Sun it experiences a warmer season; at the same time the northern hemisphere is tilted away from the Sun, so it experiences a colder season.

When a planet is consistently tilted on one side as it orbits around the Sun, the world experiences four seasons during one year. Tarly proposed that seasons could last over several years if the tilt of a planet changes during its orbit: “so that the Earth ‘tumbles’ on its spin axis, a bit like a spinning top”, he explains. If a planet were to only change the side of its tilt once a year, it would experience permanent seasons.

Caption: an example of Earth’s orbit in which (a) the angle of tilt of the spinning axis of the Earth stays constant through the year (Credit: Dan Lunt, University of Bristol)

Caption: an example of Earth’s orbit in which (b) the tilt “tumbles” as the planet rotates round the Sun, such that the angle of tilt changes, so that the same Hemisphere always faces the Sun, giving a permanent season (Credit: Dan Lunt, University of Bristol)

Tarly put this theory to the test with the help of a climate model that he discovered on a computing machine stored in the Citadel cellars. “Luckily I learned how to code when I was back in Horn Hill avoiding sword practice,” Tarly explains in the text.

By running climate simulations with the proposed parameters of his theory, Tarly found that his model was consistent with much of the observational data present within the Citadel library. The models also estimated many climatic features of the world of Game of Thrones, including the seasonal change in temperature, precipitation and wind direction across Westeros.

In the published article, Tarly notes that his theory doesn’t explain how the planet transitions between summer and winter. He guesses that the tumbling pattern of the planet’s tilt persists for a few years, but then flips at one point so that the hemispheres experience new seasons. “The reasons for this flip are unclear, but may be a passing comet, or just the magic of the Seven (or magic of the red Lord of Light if your name is Melisandre),” Tarly writes.

Caption: The Northern Hemisphere winter (top row (a,b,c)) and summer (bottom row (d,e,f)) modelled climate, in terms of surface temperature (◦C; left column (a,d)) precipitation (mm/day; middle column; (b,e)) and surface pressure and winds (mbar; right column (c,f)). (Credit: Dan Lunt, University of Bristol)

The world of Game of Thrones compared to ‘real’ Earth

Tarly then compared the climate of the world of the Game of Thrones to that of a fictional planet called the ‘real’ Earth; Gilly, his partner and research associate, had found records of this planet’s climate in the Citadel library. The analysis revealed that in winter, The Wall, the northern border of the Seven Kingdoms, was similar in climate to many areas of the ‘real’ Earth, including parts of Alaska in the US, Canada, western Greenland, Russia, and the Lapland region in Sweden and Finland. “I always suspected that Maester St. Nicholas was a member of the Night’s Watch,” Tarly noted.

Caption: High-resolution (0.5◦ longitude ×0.5◦ latitude) mountain height for the whole planet. (b) Model-resolution (3.75◦ longitude ×2.5◦ latitude) mountain height for the region of Westeros and western Essos. (Credit: Dan Lunt, University of Bristol)

On the other hand, the models showed that the climate of Casterly Rock, the southern home of House Lannister, was similar to that of the Sahel region in Africa, eastern China, and a small region nearby Houston, Texas in the US.

Climate sensitivity in a world of ice and fire

Finally, Tarly used the climate models to investigate how climate change might impact the world of Game of Thrones. The simulations were done in response to some “worrying reports from monitoring stations on the island of Lys”; the stations have recently observed increasing concentrations of methane and carbon dioxide in the world’s atmosphere. It is suggested that this spike in greenhouse gas emissions could be due to the rising dragon population in Essos, deforestation from global shipbuilding, and excessive wildfire.

Tarly found that, by doubling the level of atmospheric carbon dioxide in his models, the world would warm on average by 2.1°C over 100 years. The results showed that the greatest warming would occur in the polar regions, since warming-induced sea ice and snow melt can trigger additional warming as a positive feedback.

By comparing this level of warming to the Pliocene period of the ‘real’ Earth 3 million years ago, Tarly predicted that the sea level of the world of Game of Thrones could rise by 10 metres in the long term. This degree of sea level rise is sufficient to flood several coastal cities, including King’s Landing.

In the paper, Tarly stresses that climate action from all the Kingdoms is needed to prevent even more social instability and unrest from climate change. He suggests that all governing bodies should work on reducing their greenhouse gas emissions and invest in renewable energy, such as windmills.

If he survives the war for Westeros, Tarly expects that improving his climate analysis will keep him busy for years to come.

By Olivia Trani, EGU Communications Officer

This unfunded work was carried out by Dan Lunt, from the University of Bristol School of Geographical Sciences and Cabot Institute, Carrie Lear from Cardiff University and Gavin Foster from the University of Southampton during their spare time, using supercomputers from the Advanced Centre for Research Computing at the University of Bristol. You can learn more about the climate models online here.

How to forecast the future with climate models

How to forecast the future with climate models

Our climate is constantly changing, and with the help of simulation modelling, scientists are working hard to better understand just how these conditions will change and how it will affect society. Science journalist Conor Paul Purcell has worked on Earth System Models during his time as a PhD student and postdoctoral researcher; today he explains how scientists use these models as tools to forecast the future of our climate.

While we can’t predict everything about our future, climate scientists have a good understanding of how our environment will look and feel like in the coming years. Researchers and climate specialists predict that temperatures will increase dramatically in the 21st century, ranging between 1.5°C and 4°C above pre-industrial levels, depending on your location and the amount of carbon dioxide pumped into the atmosphere in the near future. Forecasts of future drought and flood risk, at both regional and global bases, are also provided by climate experts.

Understanding how such features of Earth’s changing climate may manifest, and ultimately impact on our society, takes considerable international collaboration – a collaboration which is largely based around the results of climate modelling. That’s because climate predictions for the future are made using sophisticated computer models, which are built around mathematical descriptions of the physical and biological processes that govern our planet.

These models have become so complex in recent years that they are now referred to as Earth System Models (ESMs). Using ESMs, climate modellers can create simulations of the planet at different times in the future and the past. ESMs are in fact the only tools we have for simulating the global future in this sense. For instance, if we want to know how our climate may look like one hundred years from now, how ocean acidification levels may change and how this might impact ocean life, or how plants will respond to increasing levels of atmospheric carbon dioxide, ESMs are the only tool available.

The models are built in components, each representing a separate part of the Earth system: the atmosphere, the ocean, the land surface and its vegetation, and the ice-sheets and sea-ice. These are constructed by coding each component with the mathematics that describes the environmental processes at work.

Climate models are systems of differential equations based on the basic laws of physics, fluid motion, chemistry, and biology. Pictured here is a schematic of a global atmospheric model. (Credit: NOAA, via Wikimedia Commons)

For example, the winds in the atmosphere are described by the mathematics of fluid motion. Model developers translate these mathematical equations into code that computers can understand, like giving them a set of instructions to follow. Supercomputers can then interpret the code to simulate how winds, for example, are expected to develop at each global location through time. The results are usually plotted on world maps.

As scientists have learned more about our Earth’s systems over time, the complexity of these individual models has been ramped up dramatically. For example, the land surface and vegetation model components become more sophisticated as plant biologists understand more and more about how plants transfer water and carbon between the land and atmosphere.

And it’s not just one giant solo project either: there are tens of ESMs and hundreds of subcomponent models developed and used at research centres around the globe. Collaboration between these facilities is a necessary part of progress, and information is shared at international conferences ever year, like the American Geophysical Union’s Fall Meeting in the United States and the European Geosciences Union’s General Assembly in Europe.

This means that developments are always been made towards increasing the realism of ESMs. On the horizon such developments will include increasing the resolution of the global models for improving accuracy at regional locations, and also incorporating the results from the latest research in atmospherics, oceanography and ice sheet dynamics. One example is research into plants, specifically how they interact with carbon dioxide and water in the atmosphere. Further understanding of this biological process is expected to increase the realism of models over the coming years and decades. In general, improvements to the accuracy of model simulations can help to help society in the future. For example, models will be able to help predict how climate change may impact, say, water scarcity in South Africa, wildfire risk in the western United States, or crop yields in Asia. Indeed, the ESMs of the future should boast incredibly accurate simulations and prediction capabilities unheard of today.

By Conor Purcell, a Science & Nature Writer with a PhD in Earth Science

Conor Purcell is a science journalist with a PhD in Earth Science. He is also founding-editor of www.wideorbits.com and is on twitter @ConorPPurcell and some of his other articles at cppurcell.tumblr.com.

Imaggeo on Mondays: Monitoring the melt

Automatic weather stations (AWS) play a prominent role in making meteorological measurements in remote areas. These measurements can feed into climate models; providing better projections for rainfall, temperature and more. This peculiarly perched piece of equipment is just such a weather station:

“Alpine Meteorology” by James Thornton, distributed by the EGU under a Creative Commons licence. Wondering where it is? Right here: 46.213546 N, 7.092183 W, sitting in the heart of the Vallon de Nant Natural Reserve, Switzerland.

“Alpine Meteorology” by James Thornton, distributed by the EGU under a Creative Commons licence. Wondering where it is? Right here: 46.213546 N, 7.092183 W, sitting in the heart of the Vallon de Nant Natural Reserve, Switzerland.

Out in the Swiss Alps, this AWS is making measurements of temperature, precipitation, wind speed, relative humidity and solar radiation every 15 minutes. The photographer, James Thornton, says “the data provided by a network of these stations measuring over a period of several years can help us understand how the measured variables change over space and time”. Indeed, the more fine-scale measurements there are; the better meteorologists can make their models – for both short- and long-term changes.

The aim of this station – and the network of others like it in the Swiss Alps – is to obtain a better understanding of how the water cycle is changing in alpine environments. The data from these stations has been incorporated into a complex hydrological model known as WaSiM-ETH and applied to a number of high alpine river catchments to determine the temporal and spatial variation in snowmelt and runoff from glacier-covered regions.

Satellite image of the Swiss Alps, taken in September 2002. The northern peaks are snow covered above 2000 metres, but there is little or no snow on the peaks further south. (Credit: NASA)

Satellite image of the Swiss Alps, taken in September 2002. The northern peaks are snow covered above 2000 metres, but there is little or no snow on the peaks further south. (Credit: NASA)

Since the 1940s, the Alpine basin has had no change land use and relatively constant land cover, making it ideal for investigating how climate variability has influenced hydrological processes in the last century. Daniela Balin and colleagues have found that dominant control on the region’s hydrology is the way in which snow is stored over the course of a year. When more snowpack is preserved into the early summer, there is a greater chance of high river flow. This is because high precipitation at this time of year, together with late snowmelt, combines to produce a large amount of runoff. The effects of this are likely to be amplified in future as convective rainfall events increase. These results mean the Swiss Alps are likely to be sensitive to future climate change, particularly as snowmelt (and therefore temperature), has the biggest influence on the region’s hydrology.

This same model has been used to assess how interaction between glaciers and snow cover affect alpine river basins. Comparing the influence of snowmelt, glacier runoff and other factors that influence hydrology, Mark Verbunt and his team found that snow storage and melting processes had a stronger control on runoff in catchments that had a lot of glacier cover. If the glacier was snow-free, there would be more glacial melt than in the areas of the glacier that were snow-covered. This is because snow covered areas are more reflective (they have a higher albedo). The colour of a glacier is highly variable and because ice is darker than bright white snow it absorbs more solar radiation and melts more readily.

For more on how AWS are being used to monitor atmospheric processes, take a look at the Dust in the Desert series by James King, who is using AWS to collect dust emission data from the African continent.

References:

Balin, D. et al. Temperature-driven ‘meteorological memory’ and hydrological response of an Alpine river basin. Conference abstract (EGU2013-11700)

Verbunt, M. et al. The hydrological role of snow and glaciers in alpine river basins and their distributed modelling. Journal of Hydrology 282, 36–55, 2003

Imaggeo is the EGU’s online open access geosciences image repository. All geoscientists (and others) can submit their images to this repository and since it is open access, these photos can be used by scientists for their presentations or publications as well as by the press and public for educational purposes and otherwise. If you submit your images to Imaggeo, you retain full rights of use, since they are licensed and distributed by the EGU under a Creative Commons licence.