GeoLog

Geoscientific Methods

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.

GeoTalk: To understand how ice sheets flow, look at the bedrock below

GeoTalk: To understand how ice sheets flow, look at the bedrock below

Geotalk is a regular feature highlighting early career researchers and their work. In this interview we speak to Mathieu Morlighem, an associate professor of Earth System Science at the University of California, Irvine who uses models to better understand ongoing changes in the Cryosphere. At the General Assembly he was the recipient of a 2018 Arne Richter Award for Outstanding Early Career Scientists.  

Could you start by introducing yourself and telling us a little more about your career path so far?

Mathieu Morlighem (Credit: Mathieu Morlighem)

I am an associate professor at the University of California Irvine (UCI), in the department of Earth System Science. My current research focuses on better understanding and explaining ongoing changes in Greenland and Antarctica using numerical modelling.

I actually started glaciology by accident… I was trained as an engineer, at Ecole Centrale Paris in France, and was interested in aeronautics and space research. I contacted someone at the NASA Jet Propulsion Laboratory (JPL) in the US to do a six-month internship at the end of my master’s degree, thinking that I would be designing spacecrafts. This person was actually a famous glaciologist (Eric Rignot), which I did not know. He explained that I was knocking on the wrong door, but that he was looking for students to build a new generation ice sheet model. I decided to accept this offer and worked on developing a new ice sheet model (ISSM) from scratch.

Even though this was not what I was anticipating as a career path, I truly loved this experience. My initial six-month internship became a PhD, and I then moved to UCI as a project scientist, before getting a faculty position two years later. Looking back, I feel incredibly lucky to have seized that opportunity. I came to the right place, at the right time, surrounded by wonderful people.

This year you received an Arne Richter Award for Outstanding Early Career Scientists for your innovative research in ice-sheet modelling. Could you give us a quick summary of your work in this area?

The Earth’s ice sheets are losing mass at an increasing rate, causing sea levels to rise, and we still don’t know how quickly they could change over the coming centuries. It is a big uncertainty in sea level rise projections and the only way to reduce this uncertainty is to improve ice flow models, which would help policy makers in terms of coastal planning or choosing mitigation strategies.

I am interested in understanding the interactions of ice and climate by combining state-of-the-art numerical modelling with data collected by satellite and airplanes (remote sensing) or directly on-site (in situ).  Modelling ice sheet flow at the scale of Greenland and Antarctica remains scientifically and technically challenging. Important processes are still poorly understood or missing in models so we have a lot to do.

I have been developing the UCI/JPL Ice Sheet System Model, a new generation, open source, high-resolution, higher-order physics ice sheet model with two colleagues at the Jet Propulsion Laboratory over the past 10 years. I am still actively developing ISSM and it is the primary tool of my research.

More specifically, I am working on improving our understanding of ice sheet dynamics and the interactions between the ice and the other components of the Earth system, as well as improving current data assimilation capability to correctly initialize ice sheet models and capture current trends. My work also involves improving our knowledge of the topography of Greenland and Antarctica’s bedrock (through the development of new algorithms and datasets). Knowing the shape of the ground beneath the two ice sheets is key for understanding how an ice sheet’s grounding line (the point where floating ice meets bedrock) changes and how quickly chunks of ice will break from the sheet, also known as calving.

Steensby Glacier flows around a sharp bend in a deep canyon. (Credit: NASA/ Michael Studinger)

At the General Assembly, you presented a new, comprehensive map of Greenland’s bedrock topography beneath its ice and the surrounding ocean’s depths. What is the importance of this kind of information for scientists?

I ended up working on developing this new map because we could not make any reliable simulations with the bedrock maps that were available a few years ago: they were missing key features, such as deep fjords that extend 10s of km under the ice sheet, ridges that stabilize the retreat, underwater sills (that act as sea floor barriers) that may block warm ocean waters at depth from interacting with the ice, etc.

Subglacial bed topography is probably the most important input parameter in an ice sheet model and remains challenging to measure. The bed controls the flow of ice and its discharge into the ocean through a set of narrow valleys occupied by outlet glaciers. I am hoping that the new product that I developed, called BedMachine, will help reduce the uncertainty in numerical models, and help explain current trends.

3D view of the bed topography and ocean bathymetry of the Greenland Ice Sheet from BedMachine v3 (Credit: Peter Fretwell, BAS)

How did you and your colleagues create this map, and how does it compare to previous models?

The key ingredient in this map, is that a lot of it is based on physics instead of a simple “blind” interpolation. Bedrock elevation is measured by airborne radars, which send electromagnetic pulses into the Earth’s immediate sub-surface and collect information on how this energy is reflected back. By analyzing the echo of the electromagnetic wave, we can determine the ice thickness along the radar’s flight lines. Unfortunately, we cannot determine the topography away from these lines and the bed needs to be interpolated between these flight lines in order to provide complete maps.

During my PhD, I developed a new method to infer the bed topography beneath the ice sheets at high resolution based on the conservation of mass and optimization algorithms. Instead of relying solely on bedrock measurements, I combine them with data on ice flow speed that we get from satellite observations, how much snow falls onto the ice sheet and how much melts, as well as how quickly the ice is thinning or thickening. I then use the principle of conservation of mass to map the bed between flight lines. This method is not free of error, of course! But it does capture features that could not be detected with other existing mapping techniques.

3D view of the ocean bathymetry and ice sheet speed (yellow/red) of Greenland’s Northwest coast (Credit: Mathieu Morlighem, UCI)

What are some of the largest discoveries that have been made with this model? 

Looking at the bed topography alone, we found that many fjords beneath the ice, all around Greenland, extend for 10s and 100s of kilometers in some cases and remain below sea level. Scientists had previously thought some years ago that the glaciers would not have to retreat much to reach higher ground, subsequently avoiding additional ice melt from exposure to warmer ocean currents. However, with this new description of the bed under the ice sheet, we see that this is not true. Many glaciers will not detach from the ocean any time soon, and so the ice sheet is more vulnerable to ice melt than we thought.

More recently, a team of geologists in Denmark discovered a meteorite impact crater hidden underneath the ice sheet! I initially thought that it was an artifact of the map, but it is actually a very real feature.

More importantly maybe, this map has been developed by an ice sheet modeller, for ice sheet modellers, in order to improve the reliability of numerical simulations. There are still many places where it has to be improved, but the models are now really starting to look promising: we not only understand the variability in changes in ice dynamics and retreat all around the ice sheet thanks to this map, we are now able to model it! We still have a long way to go, but it is an exciting time to be in this field.

Interview by Olivia Trani, EGU Communications Officer

Imaggeo on Mondays: Hints of an eruption

Imaggeo on Mondays: Hints of an eruption

The photograph shows water that accumulated in a depression on the ice surface of Vatnajökull glacier in southeastern Iceland. This 700m wide and 30m deep depression [1], scientifically called an ‘ice cauldron’, is surrounded by circular crevasses on the ice surface and is located on the glacier tongue Dyngjujökull, an outlet glacier of Vatnajökull.

The photo was taken on 4 June 2016, less than 22 months after the Holuhraun eruption, which started on 29 August 2014 in the flood plain north of the Dyngjujökull glacier and this depression. The lava flow field that formed in the eruption was the largest Iceland has seen in 200 years, covering 84km2 [2] equal to the total size of Manhattan .

A number of geologic processes occurred leading up the Holuhraun eruption. For example, preceding the volcanic event, a kilometre-wide area surrounding the Bárðarbunga volcano, the source of the eruption, experienced deformation. Additionally, elevated and migrating seismicity at three to eight km beneath the glacier was observed for nearly two weeks before the eruption [3]. At the same time, seven cauldrons, like the one in this photo, were detected on the ice surface (a second water filled depression is visible in the upper right corner of the photo). They are interpreted as indicators for subglacial eruptions, since these cauldrons usually form when geothermal or volcanic activity induces ice melt at the bottom of a glacier [4].

Fracturing of the Earth’s crust led up to a small subglacial eruption at the base of the ice beneath the photographed depression on 3 September 2014. This fracturing was further suggested as the source of long-lasting ground vibrations (called volcanic tremor) [5].

My colleagues and I studied the signals that preceded and accompanied the Holuhraun eruption using GPS instruments, satellites and seismic ground vibrations recorded by an array of seismometers [2, 5]. The research was conducted through a collaboration between University College Dublin and Dublin Institute for Advanced Studies in Ireland, the Icelandic Meteorological Office and University of Iceland in Iceland, and the GeoForschungsZentrum in Germany.

The FP7-funded FutureVolc project financed the above mentioned research and further research on early-warning of eruptions and other natural hazards such as sub-glacial floods.

By Eva Eibl, researcher at the GeoForschungsZentrum

Thanks go to www.volcanoheli.is who organised this trip.

Imaggeo is the EGU’s online open access geosciences image repository. All geoscientists (and others) can submit their photographs and videos to this repository and, since it is open access, these images can be used for free by scientists for their presentations or publications, by educators and the general public, and some images can even be used freely for commercial purposes. Photographers also retain full rights of use, as Imaggeo images are licensed and distributed by the EGU under a Creative Commons licence. Submit your photos at http://imaggeo.egu.eu/upload/.

Imaggeo on Mondays: Probing the Pliocene

Imaggeo on Mondays: Probing the Pliocene

The heights we go to for science…

This photograph shows a member of our team preparing to abseil down a cliff in the Charyn Canyon, in the Ili River basin of southeast Kazakhstan. The Charyn River and its tributaries, a branch of the Ili River north of the Tien Shan Mountains, have cut canyons up to 300 metres deep, carving through rocks of different geologic ages, some as old as 540 million years.

The name “Charyn” may derive from local Uighur or Turkic words for “ash tree” or “precipice” respectively, both of which are common in the area.

Charyn Canyon is presently characterized by a cold semi-arid climate, with dry summers and cold winters. However, these conditions are likely to have varied through time, becoming wetter, drier, warmer and cooler in response to major climate systems’ changing intensity and influence over the region.

Our research team investigates the past and present climate systems of the Cenozoic era, our current geological era which began 66 million years ago; the most recent 2.6 million years have been characterised by alternating ice ages and warmer so-called “interglacial” phases, and saw the evolution of humans. More specifically, we study climate systems in one of the most remote regions of Central Asia, known as the Eurasian Continental Pole of Inaccessibility. The area is a challenging place for climate research since it has no marine or ice core records, the most common calendars of ancient climate.

This region is poorly understood yet important within the global climate system, since it lies at the boundaries of the major northern hemispheric climate systems. These systems, such as the Siberian high pressure system and Asian monsoons, are likely to have shifted, expanded and contracted over time. These changes occur in response to factors like mountain uplift, and changes in the Earth’s orbital patterns and incoming solar radiation.

The aim of our study is to reconstruct climatic change over this period. By analysing various chemical and physical characteristics of the sediments, such as their age, magnetism, grain size and chemistry, we can reconstruct quantitative palaeoclimatic variability through time.

Here we focus on an 80-metre thick layer of sediment, which alternates between layers of river-transported gravels and wind-blown dust deposits, known as loess. Younger sedimentary layers have thicker dust deposits, reflecting a long-term aridification trend in the Ili Basin and, more broadly, Central Asia.

Our preliminary results from our fieldwork indicate that the canyon’s sediments represent an uninterrupted representation of the region’s climate from the Pliocene to early Pleistocene (from approximately 4.5 to 1 million years ago).

Achieving a comprehensive geological sampling of the Charyn Canyon was only possible by abseil. Our fieldwork, undertaken from May to June 2017, was a hot and dusty business, but ultimately a lot of fun. Definitely not for those with a fear of heights!

By Kathryn Fitzsimmons, Max Planck Institute for Chemistry, Germany and Giancarlo Scardia, São Paulo State University, Brazil