Ocean Amplification is a video montage that offers visualizations and simulations of ocean waves, waves whose heights are growing in some parts of the Southern Hemisphere owing to the effects of climate change, which include intensified storms and latitudinal shifts in wind patterns. Developed by cultural anthropologist Stefan Helmreich and artist Francisco Alarcon, the video frames increasing wave heights in the Oceanic South as avatars of changing human-inhuman political ecologies.
Inequalities marked by latitude and amplitude
By Stefan Helmreich
The distribution of worldwide wind wave heights is transforming. According to a 2019 report in Science, wind-speed increases over the Earth’s southernmost oceans—a consequence of surface warming—have led to amplifications in wave height of some 30 centimeters since 1985, for the largest 10 percent of waves (Barras 2019). And although rising wave heights are also manifesting in the Northern Hemisphere, particularly in high latitude locations, amplification in southern seas is more intense because the Southern Hemisphere hosts more uninterrupted ocean surface than the northern, giving waves longer fetches over which to grow in size and strength. This is significant for maritime worlds in the Southern Hemisphere, with bigger waves arriving at harbors and coastlines, but also elsewhere, as the Southern Ocean is the source for many swell patterns worldwide. The Southern Hemisphere, with more “oceanicity” than the north, may also be a harbinger of what is to come (and what is, in fact, already happening) on an increasingly climate-morphing, sea-surfaced planet.
In Theory from the South (2012), Jean and John Comaroff argue that Northern (i.e., European and American) social histories, tendencies, and theories may be inadequate to apprehending the motivating forces of the world today, which they see most starkly represented in the countries of the Global South. Meg Samuelson and Charne Lavery seek to develop a parallel account for what they call “The Oceanic South” (2019). They write:
“The southern region of the globe is most readily conceived of as what is bound by the longitudinal lines of imperial and metropolitan domination or described by the curvier Brandt Line as comprising the ‘poorer nations.’ But it might also be defined by the relatively vast maritime expanses that distinguish the Southern Hemisphere.”—(Samuelson and Lavery 2019, 37).
The Comaroffs suggest that the Global South and its geographies have been treated in social theory as “a place of parochial wisdom, of antiquarian traditions, of exotic ways and means,” and, “above all, of unprocessed data . . . reservoirs of raw fact” (Comaroff 2012, 1), rather than, as they might instead be, prescient pointers to the directions that world affairs might be taking.
Think, then, of the rising wave heights in the Oceanic South as phenomena that underscore the changes coming in the global ocean—stronger storms, surges that inundate coastal communities.
Waves, of course, are often treated as symbols for fast arriving, inevitable futures—think of any number of wave disaster movies (Helmreich 2018). The futures that waves bring are not, of course, only environmentally animated ones, but also curled together with the effects of human overreaching, greed, and denial. Today’s Anthropocene, Plantationocene, Capitalocene, and Military-ocene oceans (see DeLoughrey 2019)—overfished, acidifying, warming, irradiated—are nothing if not hybrid nature-culture, material-semiotic forces that churn political-economic processes into the stir, surge, and spray of the sea.
I skipped a step. How do oceanographers arrive at knowledge of increasing wave heights? Answer: through environmental observation and computer modeling (Helmreich 2014). Wave heights are measured by buoys and satellites, whose emplaced distributions, at sea and in orbit, are shaped by political, economic, and military histories—with Europe and the United States being dominant players in this domain. Wave measurements are turned into statistics and fed into descriptive and predictive computer models, making known wave height data a layering of the actual and the virtual. Higher wave heights in the Southern Hemisphere, then, are not so much “unprocessed data” from the south as data made legible through theory from the north.
Such data emerges from computer models trained on wind-speeds from northern seas—and, in fact, often, from the North Sea. If theory, in its etymology, points us to the ancient Greek for “to see” (θεωρός), wave spectra are often seen through theory from the north. In fact, back in the year 2000, one European ocean model had been found to underestimate wave heights by 20 percent in the Southern Hemisphere (Janssen 2000). In 2014, Nature Climate Change published on mis-estimations of southern sea surface temperatures in most climate models, assuming too-low cloud cover over southern oceans (Wang et al. 2014).
Wave modelers in recent years have become increasingly aware of these matters—and a thoroughgoing epistemological critique of wave theory from the north would dig into the histories of the kinds of waves that were early on relevant to colonial desires for speed in seafaring. Think, then, of increasing wave heights in the south as following from ongoing militarism, extractivism, pollution—their sizes serving as signatures of rising carbon dioxide levels.
Artist Francisco Alarcon has imagined illustrating such redistribution in a piece of provocative art—and you can see concept sketches for such a piece in the video embedded in this article. He envisions a machine-learning AI program that would generate digital images of waves—images whose realist verisimilitude would be improved as the program is trained on photographs of waves. As the AI network “learns,” it would, like many such pattern-recognition algorithms, use more and more electricity. Employing the magnitude of that energy usage—the carbon footprint of the calculation—as an input to grow the height of the virtual waves, the work would become an allegorical enactment of the electroanthropogenic driving of climate-changed wave power and an aesthetic double for scientific assessments, which also depend on the consumption of computing power— consumption that is right now intensifying as digital telecommunication and videoconferencing surge alongside the uneven and global growth of the coronavirus pandemic.
In 1957, oceanographers Roger Revelle and Hans Suess wrote, in a watershed paper on rising atmospheric CO2, that “within a few centuries we are returning to the atmosphere and oceans the concentrated organic carbon stored in sedimentary rocks over hundreds of millions of years.” The “we” and the mode of “returning” here need to be constantly specified—“we,” for example, as global North extractivist racial capitalism and authoritarian command economies, and “returning” as the generation of pollution through the plantation complex, the long history of mining, and the rapid expenditure of fossil fuels. Such a “returning to the atmosphere and oceans” of carbon must also be understood as itself now returning, in the waves, which carry messages of growing north-south asymmetry, of political-ecological inequalities marked by differences of latitude and amplitude.
The project was originally presented at #Distribute, the 2020 Biennial Conference of the Society for Cultural Anthropology and the Society for Visual Anthropology, hybrid virtual/in-person event, May 7-9; Panel: Cosmopolitics at Sea. We thank Nikolas Kosmatopoulos for organizing the session. The video posted here is a record of our panel presentation.
Ocean Amplification: Behind the Screen
By Francisco Alarcon
The moving digital images in the Ocean Amplification film provide a visual accompaniment to, but also a commentary on, the paper’s arguments. In a conversation with MIT anthropologist Stefan Helmreich in January 2020, I learned from him about changing worldwide wave heights, and immediately thought of my research in computational wave imaging in video games, which was part of my PhD study in the Department of Visual and Environmental Studies at Harvard University. I wondered whether there might be a way to approach wave simulations with sharper attention to the materiality of the computing process behind them. Having already been interested in the physicality of people’s perceptual and haptic experiences of interfaces, I thought I could dive deeper into questions of energy infrastructure. And so came the idea of a machine learning algorithm based on a Generative Adversarial Network that might take a library of photographic images of waves as a database from which to “learn” to reproduce wave images. I thought further: maybe as the algorithm consumed energy, it could translate that into an increase in the height of the waves depicted.
As Stefan and I talked about collaborating on a video, he told me that while he found this an interesting thought experiment, he was uncomfortable with translating it into actual action, since the notion of deliberately consuming energy for what might be perceived as an aesthetic stunt seemed to him to make such an illustration itself part of the problem (see Karen Hao’s 2019 article in the MIT Technology Review, “Training A Single AI Model Can Emit As Much Carbon As Five Cars In Their Lifetimes”). I decided instead to follow research questions I was already pursuing—about how computer simulations that aimed at realist verisimilitude, particularly in the representation of waves, operated as a mix of the cinematic and the scientific. But I also decided, as I continued the work, that I would track the energy usage that followed from those wave simulations with which I experimented, simulations I created using platforms widely employed for imaging waves in Hollywood, in gaming, and in professional fluid dynamics.
Let me explain what technologies I employed to create the images in Ocean Amplification, discussing along the way the technicians, software, hardware, and platforms implicated in creating the video.
I began by interviewing computational fluid dynamic engineers and computer scientists about what they thought were the best ocean wave simulations. I started that work in February 2020 and ended up compiling a set of different platforms I could work with for simulating waves on the Southern Ocean: RealFlow, Houdini, Blender, the Autodesk Maya BiFrost particle system, and Siemens CFD.
For the film’s first segment, I began with RealFlow, developed in 1998 by a Madrid-based company. This product uses “particle-based” simulations, which are informed in “various ways by point-based nodes (daemons), which can perform various tasks such as to simulate gravity.” I contacted Boris Konik, a motion graphic expert based in Ukraine, who collaborated with me as a consultant and helped me set up an “ocean” that resembled images found on Google of the Southern Ocean. We created a simulation in RealFlow and imported it into Autodesk 3D Max, with the goal of creating photorealistic images from the simulation using my local computer. After setting up the scene, I decided to keep the computer rendering indefinitely using different cameras, so I could assemble a montage.
A few weeks before the deadline for presenting the film at the virtual meetings of the Society for Cultural Anthropology to which it had been accepted, I realized that the simulation was very repetitive, as its length was short. If Konik and I decided to increase the length of the simulation using RealFlow, it would also increase energy consumption. We were already having issues processing the 70 gigabytes of the simulation. My computer was getting hot. I decided to move to a new simulation, made using Houdini.
Houdini is an animation software developed by SideFX, a Toronto-based company. As with RealFlow, it is an application used in the visual effects industry. Among its different applications, Houdini has specific nodes to simulate the sea.
Another segment of Ocean Amplification was done in Blender, an open-source, free licensed piece of software that comes with a built-in wave simulator called “Ocean Modifier,” which is “a tool to simulate and generate a deforming ocean surface, and associated texture used to render the simulation data. It is intended to simulate deep ocean waves and foam.” I decided to create an ocean “out of the box” from Blender, to transition from the more realistic simulations created in RealFlow and Houdini to simulations that would make “raw” digital data more visible. My efforts to construct the illusion of a deep ocean, operating with detailed foam, waves, and shaders, shifted into more schematic simulations, ones in which the “digital” surfaced visually, with a thin gridded mesh representing the water surface making it evident that the modeling was following a mathematical equation.
For the fourth section of the film, I experimented with tools dedicated to creating accurate hydrodynamic simulations for engineering applications. I turned to Simcenter STAR-CCM+, a tool used to “predict the real-world performance of your product” (think of boats, the struts of bridges) by capturing all of the physics that would influence a product’s performance during its operational life. The application has dedicated Fluid Simulation tools to predict the reaction of products (e.g., ships, port infrastructures) to fluids. This software is the leading computational fluid dynamics software, and as part of its package, includes access to Simcenter’s computational cloud system to process fluid simulation data.
For guidance in using Simcenter STAR-CCM+, I contacted Guillaume Jolly, a French engineer based in Australia, an expert in computational fluid simulations. We decided to create two-wave simulations that would obtain data from the article at Science Magazine to which Helmreich had pointed me in the first place.
The workflow for the final segment of the film followed these next steps: we first created a “parametric”—a drawing with constraints that could serve as a digital model of the Ocean Domain. At first, we fancifully imagined simulating waves for the entire Southern Ocean, though we knew that was computationally impossible. Instead, we designed a small portion of a proxy ocean, which we called Ocean Domain. We then created a computational fluid dynamic mesh, which would pixelate the domain. That is, it would simplify the three-dimensional model of the portion of the ocean we were simulating. The next step was to select a physical model and establish the parameters required to model the interface between a liquid and a gas phase. After the setup, the computational fluid simulation was processed and raw data for each time step saved. The raw data was post-processed to bring it to the screen and assign a color texture to the different values of wave height. The cloud system provided by Siemens was used to process the simulation data of this portion of the video, which I obtained from engineer Guillaume in a video format.
All the cuts were assembled in the final film, following this order: RealFlow, Houdini, Blender, Maya, and Siemens. What resulted was a montage of simulations of the Southern Ocean that, perhaps, could serve a machine learning algorithm as data for “learning” to generate its own depictions of waves. So, the film starts with cinematic aesthetics, realized with software used in the film industry, and ends with more accurate scientific depictions of fluids. The viewer may, across these moving images, experience more and less of the feeling of the “uncanny.” If the “uncanny valley” is the phenomenological space of unease that some people feel when encountering humanoid robots that only partially resemble living humans, the “uncanny waves” we created here offer up questions about what is real and what is imagined in our perceptions of waves. All this uncanniness, it bears repeating, has an ecological footprint—one that may feed back into the real worlds of waves and energies themselves.