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Ambiguïtés numériques

The Storm Map as Digital Ambiguity

Political and Scientific Authority in the Information Age of Disasters
Ambiguïtés dans la représentation des ouragans : légitimité politique et scientifique à l’ère de l’information et des ouragans
Andrew Deener, Black Hawk Hancock et Zoe Folsom
p. 125-141


Cet article interroge des dissensions sur ce qui constitue une connaissance légitime au sujet du développement en cours de catastrophes naturelles, telles qu’elles sont médiées sur des plateformes numériques sous la forme de storm maps – des représentations visuelles de la circulation des ouragans. Pour ce faire, nous nous centrons sur la circulation de storm maps liées à l’ouragan Dorian, un des ouragans les plus dévastateurs relevés à ce jour mais aussi un événement qui a très largement suscité l’intérêt du grand public. Les storm maps sont devenues un artéfact important à l’ère de l’information. Les outils numériques viennent complexifier les usages plus traditionnels des storm maps comme guide à la prévention des catastrophes, en donnant forme à deux types d’ambiguïtés numériques : une ambiguïté hégémonique et une ambiguïté plus commune ou ordinaire. L’ambiguïté hégémonique se réfère aux usages d’outils numériques par le pouvoir politique avec pour objectif de perturber la circulation de la connaissance et la légitimité scientifique. L’ambiguïté commune ou ordinaire implique un recours à des technologies numériques qui multiplient le nombre de perspectives disponibles sur la catastrophe. Des acteurs hétéroclites articulent l’usage de smartphone, de drones, de systèmes photogrammétriques, de télédétection, et autres systèmes d’information géographique (SIG) dans la représentation des storm maps. La comparaison entre ces deux formes d’ambiguïté montre à la fois comment les plateformes numériques transforment la structure sous-jacente à ce qui fait autorité lorsqu’une catastrophe naturelle est en cours, modifie les relations entre la production et la circulation des connaissances, et multiplie les façons dont des évènements liés à une catastrophe naturelle sont représentés et interprétés dans la société.

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Politics, Science, and Digital Ambiguities

1The proliferation of digital imagery has shaped human relationships with the environment. Even mundane aspects of social interactions with the environment are often mediated through digital platforms and information technologies. Storm tracking, heat maps, soil erosion, flood zones, and ground water, among many other indicators disseminated widely across contexts, have become common visual representations in the information age of climate change. Yet such visual representations are also assembled and incorporated in the everyday interactions and settings of political and scientific authorities (Arènes et al., 2018; Grevsmühl, 2016). The process of creating environmental representations and circulating them for public consumption, far from resulting in the uniform expression of objective information, often results in heterogeneity, conflict, and ambiguity in various scientific and political worlds.

2In this paper, we focus on the competing dynamics of mapping and representing a catastrophic hurricane. We address the dissemination of storm maps during Hurricane Dorian, one of the most severe hurricanes on record, as an example of a disaster event in which digital platforms mediated a wide range of representations of the storm map for public consumption. Hurricane Dorian was a Category 5 Atlantic Hurricane, which took place between 24 August and 10 September 2019. Due to climate change, large storms like Hurricane Dorian have become more likely to stay in place for longer durations, creating a dangerous pattern of “stalled storms” that increase rainfall and overall destruction (Hall and Kossin, 2019). Hurricane Dorian caused immense damage and despair, first in the Bahamas, where it was classified as the worst disaster in the island’s history, and then in the southeastern seaboard of the United States, where multiple states issued emergency evacuation orders.

3The storm map has become one of the most significant artifacts of the information age. Despite the dispersion of mapping as agreed upon documentation of objective information, ambiguities occur regarding how the maps should be constructed, what layers and information should be included, and how they should be interpreted. Digital platforms have made it possible for a wide range of innovative tools, software, and applications to alter the preparation, circulation, and assessment of maps for addressing immediate and long-term problems. Digital technologies made it easier to represent pertinent information about Hurricane Dorian in real time, but such technologies also set in motion competing accounts regarding the path, the scale, and the local effects of the storm.

4Digital platforms have dramatically transformed the underlying structure of authority regarding knowledge circulation. Changing communication infrastructures have facilitated innovations in digital technology, in turn, leading to the radical decentering of knowledge dissemination about disaster-related events. Platform transformations have raised questions about who should create and coordinate the information and who has the influence to assert the most meaningful representations of a storm and its effects. One of the ramifications of the dominance of digital platforms is that the changing circuits between encoding and decoding—the interdependencies between the production, circulation, distribution, consumption, and the reproduction of information and ideology—multiply the very articulations of information (Hall, 2019a).

5In this paper, we address the interpretive challenges related to disseminating information about Hurricane Dorian in the United States, reflecting the storm map as digital ambiguity. The traditional circuits of authority were undermined both during the hurricane event and in its aftermath. We specify two forms of digital ambiguity: hegemonic ambiguity and popular ambiguity. Hegemonic ambiguity follows from the Gramscian tradition of cultural hegemony. In this perspective, ideology is not automatically imposed by centralized positions of power and authority, but rather, it arises through a process of contestation and consent. In the case of hegemonic ambiguity, opposing positions of institutional authority represented the unfolding disaster in real time. Digital platforms unsettled the institutional process of encoding and decoding information by blurring the boundaries between political and scientific authorities. These conditions enabled then-US President Donald Trump to propagate incorrect information and challenge traditional forms of expertise. As a result, different governmental agencies struggled over how to portray the storm path as it unfolded, and they continued to debate the event’s narrative sequence in the aftermath of the disaster.

6This example of hegemonic ambiguity demonstrates both exotic and mundane elements of encoding and decoding information. The circulation of information about mundane events, like a storm track, typically lacks controversy. Institutional experts coordinate the portrayal of weather patterns and risk potential by circulating maps and other visual images. Many different institutions contribute to this coordination: climatologists, meteorologists, oceanographers, geologists, and communication specialists at universities, the National Aeronautics and Space Administration (NASA), the National Weather Service (NWS), the US Geological Survey (USGS), and the Federal Emergency Management Agency (FEMA). These experts are trained to address competing scales and layers of empirical specificity of storms in relationship to territories. They construct maps and other visual images that track the paths of storms, the flow of rainfall, or coastal erosion, and they predict the distribution of risk. Building institutional expertise involves a complex series of steps and diverse forms of knowledge, which then is funneled into the dissemination of information to the public. Shared political and scientific goals, cohering in a public narrative, help to mitigate damage and despair.

7In such cases, ready consumers of pertinent maps and visual information rarely reflect on the construction of the maps and the complex layers of information needed to make them legible. Yet, in the days leading up to Hurricane Dorian, President Trump presented incorrect information about the scientifically agreed upon storm track. For most political leaders in a democracy, an incorrect statement about a dire event would be followed by an immediate retraction and correction to repair the legibility of the storm representation. The goal would be to restore the narrative order to maintain public safety. In this case, however, Trump dug deeper into the incorrect information, refusing to be challenged by the media or scientific experts. He also spread multiple types of information simultaneously—both accurate and inaccurate—that confused the public reception. He attempted to restructure the overall narrative of the storm event, even hand-crafting incorrect information with a Sharpie pen onto a storm map and presenting it to the public. By physically adding in a contrived path of the storm, Trump’s actions drew closer scrutiny. The analogue fabrication of the map—then circulated through digital platforms—raised questions about the political and scientific consensus about the storm, its path, and its potential effects. The media dubbed the controversy over the representation of the storm path as “Sharpie-Gate.”

8The second form is “popular ambiguity.” As Hall (2019b) notes, there is no uniform interpretation of popular culture, because the concept of “the popular” occurs in the context of its making. The notion of popular culture is often ambiguous, because of the uncertainty of tracing where culture comes from. A classic distinction occurs between culture imposed onto subordinates by positions of power, like media corporations and the state, and culture as the product of experience, something that is made in relatively autonomous situations. People in their daily lives are never entirely independent of the dominant culture, but they can remain separate enough to incorporate meaningful applications and construct alternative representations (O’Sullivan et al., 1993; Fiske, 2010).

  • 1 Fiske J. (1995), “Popular Culture” in Lentrichchia F., McLaughlin, T. (eds.), Critical Terms for L (...)

9Just as the proliferation of digital platforms obscured the structure of political and scientific authority in disseminating an event to the masses, it also gave rise to the possibility of constructing localized perspectives about the storm and its effects from the ground up, further challenging the boundaries of expertise. As with other forms of popular culture, the making of digital maps and representations regarding the storm was “bound up with the products and technology of mass culture.”1 In such cases, those on the ground did not create the technologies and platforms available to them, but they developed creative uses and applications to address specific circumstances. Popular ambiguity entails the configuration of the dominant and subordinate in practice, thus generating hybrid formations and frictions in their uses on the ground.

10Popular ambiguity in the case of disaster representation and response is also related to the rise of citizen science, an expanding framework for social innovation and problem-solving. In wide-ranging disasters related to earthquakes, nuclear energy leaks, oil spills, and hurricanes (McCormick, 2012; Hultquist and Cervone, 2018), local activists and organizations crowdsource information, leading to new forms of collective representations and problem-solving strategies. Citizen science, and its dependence on collective intelligence, can produce important new findings and practical solutions on the ground, but it can also create contradictions about who has the authority to shape the debates and representations of a disaster. Collective intelligence once again blurs the distinction between politics and science, but popular ambiguity and hegemonic ambiguity create different configurations. Hegemonic ambiguity stems from competitions among established political and scientific points of centrality. Popular ambiguity is emergent, arising from the spatial distribution by assembling actors, technologies, organizations, and information to construct heterogeneous accounts.

11In this case of popular ambiguity, digital map-making technologies enabled actors to incorporate smart phones, drones, and photogrammetric, remote-sensing, and GIS software, thus localizing manifestations of the storm map. As in the citizen-science framework, people were empowered to compile their own data points and information layers, combine geographic coordinates with crowdsourced images, and develop emergent and novel ways to systematize information about the disaster as it took place. The process further complicated what it means to do disaster response on the ground, as well as obscured the very meaning of the storm and its effects by configuring complex layers of data. To this end, citizen science and collective intelligence efforts produced important new findings and strategies, but they also created contradictions about who held the legitimate authority to shape the debates.

12Like in the form of hegemonic ambiguity, popular ambiguity restructures the circuitry of encoding and decoding information. Those with privileged positions of power and direct access to mass audiences can challenge what is “real,” yet simultaneously, people in their everyday lives can use mapping technologies to proliferate new types of objective representations. The remainder of the paper unpacks the distinctions between hegemonic and popular ambiguities in representing Hurricane Dorian. We conclude by revisiting how digital platforms and technologies manufacture ambiguities, underscoring ramifications for responding to specific events, and more broadly, for understanding the information age of disasters.

Hegemonic Ambiguity: Digital Platforms and Competing Authorities

13Hegemonic ambiguity occurs when there are competing platforms and institutional information sources, creating the conditions for different parts of the government, news agencies, and other communicants to fight over the clarity of a shared event and its representation as it unfolds. Multiple digital platforms, as well as participation on the same platforms by different actors—as in the uses of Twitter, Facebook, and YouTube—have carved out numerous circuits between the production and reception of information. Hegemonic ambiguity is the more conventional form of ambiguity in politics, as it reframes the cultural dichotomy of “real” and “fake” by situating the categories in unfolding events through the struggle over their meaning.

14In this case, as scientists warned of Hurricane Dorian’s approach, digital representations instigated a debate over the reality of the storm itself, including how to interpret the path of the storm and the proper authority channels to communicate to the public about territory and security. Hegemony is not pure domination, a straight line from power to population. In the digital age, as the competitions over the channels of information are made more diverse, hegemony operates as a struggle between multiple sides and circuits. Unfolding events can provoke highly contested and ambiguous communication situations in need of resolution.

15The digital platform conditions allowed Donald Trump, holding arguably the most powerful office in the world, to influence the encoding process of something as mundane as weather forecasting, putting the authority of science into limbo. A major part of creating the ambiguity of the event was the back and forth between “order and disorder.” Information was occasionally clarified during the storm’s unfolding to display the scientifically verified path of the storm. Nonetheless, continuing alternatives and residual circumstances arose during and well into the aftermath of the storm, with government leaders and media sources multiplying the representation of the same event and Trump continuing to amplify his own voice and perspective.

16As the storm gained momentum, various channels circulated information and warned the public about emergency preparation protocols. The confusion began as the storm approached the Bahamas, even though at that point, the path became clearer. The National Weather Service out of Birmingham, Alabama Tweeted on 31 August at 11:19 am, “The forecast track for #Dorian continues to shift a bit farther east. If this track verifies, we’ll be looking at dry conditions here in Central [Alabama].” At 8:00 am the next morning, the National Hurricane Center (2019) of the National Weather Service issued an update on their YouTube channel, articulating their high-tech efforts to monitor and categorize the storm size and its path.

What’s the latest information that we have?... [W]inds are up a little bit to 160 miles per hour. The aircraft has been flying right through the center [of the storm] and out of the center, trying to get information on the winds…[and] the eye. About 14 miles across is the eye, but 160 miles per hour puts it into the Category 5 range… The message is the same: powerful hurricane… We don’t just focus on the center track… because two thirds of the time, you can get the center anywhere in here [the vast cone of the storm], and that includes portions of the Florida coast, and even inland in time, and then northward into Georgia and South Carolina [over subsequent days]… But more immediately, we still have that slow speed… 30 hours plus of very slow movement [as it approaches the Bahamas].

17Representing the “cone” of the storm gave meteorologists some leeway in their predictions of the storm’s size, but not necessarily it’s track. After the National Weather Service warning, however, Trump Tweeted at 10:51 am that “in addition to Florida - South Carolina, North Carolina, Georgia, and Alabama, will most likely be hit (much) harder than anticipated.” Trump mentions both Alabama and the Carolinas, an unlikely scenario, given the established history of hurricane tracking. Storms typically either head toward the Gulf of Mexico, with ramifications for Alabama, or move up the East Coast with dangers facing the Carolinas. The National Weather Service already clarified the trajectory of the storm as going up the coast. Over the next hours, a conflict unfolded over the path, creating confusions on the ground about who and where would be hit the hardest. Concerns especially grew in Alabama, where a National Weather Service station received dire phone calls from local constituents (Bogel-Burroughs and Eder, 2019). At 11:11am, the Birmingham, Alabama National Weather Service Station tweeted, “Alabama will NOT see any impacts from #Dorian. We repeat, no impacts from Hurricane #Dorian will be felt across Alabama. The system will remain too far east.”

18News agencies exploded around the confusion, which enraged Trump, and turned the representation of the storm path into a spectacle over subsequent days. As the objective conditions on the ground were becoming a matter of security and safety for those impacted by the storm, two digital media events unfolded and obscured the local reality. The first was an event about the contested representation of the accuracy of Trump’s earlier predictions of the storm; the second was the mundane yet more pertinent representation of forecasting the actual storm path. On 2 September, Trump argued that he was shown by his emergency response team earlier projections that included Alabama in the path. He tweeted, “I suggested yesterday at FEMA that, along with Florida, Georgia, South Carolina and North Carolina, even Alabama could possibly come into play, which WAS true. They made a big deal about this.” Trump then, in a more mundane fashion, retweeted the National Hurricane Center update about dangerous conditions approaching Florida, Georgia, South Carolina, and North Carolina, that also included the actual storm map with no reference to Alabama.

19Two days later, Trump continued to challenge the representation of the storm’s path. On 4 September, he showed a forecast map from the National Oceanic and Atmospheric Administration (NOAA), in which he drew with a Sharpie pen, a black semicircle appended to the white cone of the predicted storm track (See Figure 1). He included a small corner of Alabama. In video footage of Trump’s presentation, which was widely circulated on YouTube and Twitter, other hurricane forecast projection maps are on his desk, showing the storm turning right and moving up the coast without affecting Alabama. At 6:23pm, Trump then tweeted a different map from much earlier forecasts: “This was the originally projected path of the Hurricane in its early stages. As you can see, almost all models predicted it to go through Florida also hitting Georgia and Alabama. I accept the Fake News apologies!” This statement created further ambiguity on the ground. Trump presented himself as the arbiter of truth, bolstering his own story and undermining a clear message about the storm’s actual path.

Figure 1: President Trump Receives a Hurricane Dorian Update. Trump Whitehouse Archived

Figure 1: President Trump Receives a Hurricane Dorian Update. Trump Whitehouse Archived​wiki/​File:Trump_holding_altered_Dorian_forecast_map.png

20In this case, the simple analogue tool of a pen, when applied by the office of the President through Twitter or YouTube, could reach an audience of 80 million or more. Not only did Trump upend the representation of an objective event, but he demonstrated the simplicity of disrupting scientific models compiled by experts who use the most sophisticated technologies. The conflict continued, drawing in other agencies and leaders as well. On 5 September, Rear Admiral Peter Brown of the US Department of Homeland Security, released a statement supporting Trump. He said that Trump’s original statements were based on a briefing that included the interpretation of multiple maps and models. Brown’s statement circulated widely on Twitter: “These products showed multiple storm impacts well outside the official forecast cone,” including the possibility of Tropical Storm-force winds in Alabama. He suggested that Trump’s comment referred to that possibility. Brown also emphasized that projections of the storm trajectory changed, implying that Trump’s interpretation was not a mistake.

21The saga between the order and disorder of the event continued the next day, when NOAA released an unsigned statement countering the earlier Alabama National Weather Service forecast that had cleared Alabama from the storm path. NOAA claimed that the Alabama office did not act in accordance with the best projections available at the time (NOAA 2019). Right wing blogs and media sources also contested the event, even as Trump continued to retweet posts relevant to the growing emergency on the ground caused by the actual path of the storm. His Tweets within hours of each other once again included both accurate information from the National Hurricane Center and inaccurate information about his representation of the event.

Trump: Alabama was going to be hit or grazed, and then Hurricane Dorian took a different path (up along the East Coast). The Fake News knows this very well. That’s why they’re the Fake News!

Trump: RT @NHC_Atlantic: Here are the 5pm EDT Key Messages on Hurricane #Dorian. Life-threatening storm surge and dangerous winds and flash flooding is expected across portions of South Carolina, North Carolina, and southeast Virginia through tonight. More info at

22What became labeled as “Sharpie-Gate,” was a matter of Trump exploiting digital platforms to generate ambiguity in the communication about a risky event. By claiming inaccurately that Alabama “was going to be hit or grazed” and then showing accurate information, he portrayed the potential of two (or more) realities. The sheer volume of different maps, models, and projections circulated by experts and the volume of misinformation as the storm unfolded created the conditions for ambiguity of a shared event in real time. With popular ambiguity, a different type of struggle unfolded, one that is no longer grounded in hegemony and power, but is based on the vast proliferation of representations and interpretations.

Popular Ambiguity: Localizing Digital Representations

23As the storm made landfall in the Bahamas and then in the Southeastern United States, it was no longer only an abstraction. The storm was also a traumatic event felt by many on the ground. The local conditions of the storm raised a different set of circumstances about its meaning, including how to document and represent the storm’s impact. Digital map-making through photogrammetric technologies, remote-sensing, and Geographic Information Systems (GIS) is certainly not as common as digital photography. However, increasingly, these applications assume some of the same characteristics.

  • 2 Barthes R. (1981), Camera Lucida: Reflections on Photography, New York, Macmillan, p. 26-28.

24Barthes, in his account of “camera lucida,” draws a distinction between studium and punctum, the former referring to the semiotic and “vague” context of an image, while the latter asserts the particularity of it. This connection between context and point creates the contingency of observing a photograph, an “accident” that “pricks” the observer2. Due to the increasing availability of digital tools—cameras, drones, photography, remote-sensing, and GIS software—the art and science of map-making has also enabled people to reconfigure the representations of historical context and specific points. On one hand, more people can develop technical skills and expertise to document and represent an event. On the other hand, the availability of tools raises the question of which layers, data points, and information to include in an “accurate” portrayal. This hyper-localization—an emphasis on mapping the specificity and the particular—generates popular ambiguity.

  • 3 Latour B. (2021), After Lockdown: A Metamorphosis, Medford, MA, Polity Press, p. 124-125.

25As Latour3 notes, we can distinguish between “localization from above” and “localization from below.” Digital ambiguities operate as localization from above through decentered expertise, and as localization from below by crowdsourcing information. In the immediate aftermath of Hurricane Dorian, private companies, non-profit organizations, and governmental agencies responded to the disaster and recovery in the Bahamas and in the United States. The decentering of digital technology and expertise raised the question about who was charged with disaster representation and response, and what data points should be incorporated. For example, Air Data Solutions (ADS) (2022), an aerial mapping company, worked with public and private partners to collect information and represent the situation. On their website, they assert, “When disaster strikes, immediate and accurate assessment of the damage is the key [to] coordinating and deploying response efforts. When most are moving out, ADS is moving in.” They collected digital information that was needed “to hit the ground running, saving lives, returning power, restoring water, and rebuilding infrastructure.”

26In the aftermath of the storm in Florida, ADS worked with SimActive, Inc, a developer of photogrammetry software. The American Society for Photogrammetry and Remote Sensing (ASPRS 2022) defines photogrammetry as “the art, science and technology of obtaining reliable information about physical objects and the environment through processes of recording, measuring, and interpreting images and patterns of electromagnetic radiant energy and other phenomena.” It works by taking 3-dimensional measurements in 2-dimensional photos. According to geographer Linder (2009), photogrammetry reconstructs 3-dimensional coordinates out of photography. It requires having “two (or more) photos of the same object but taken from different positions.” This allows practitioners to “easily calculate the three-dimensional co-ordinates of any point…represented in both photos.”

27ADS and SimActive partnered in Florida to digitally map the damage to housing and property to “determine financial assistance following Hurricane Dorian.” To make their assessments, they drew on pre-storm and post-storm aerial images. By drone, ADS flew an aerial digital camera, a high-powered Phase One 100MP, to collect “high resolution images of the affected area.” The SimActive software generated “mosaics of orthophotos,” which are photographic images corrected for scale (Drone Life 2019). Although the emergency response was decentered and privatized, the team operated through “localization from above,” with experts and technicians constructing particularity on the ground. In Florida, this process was used to assess financial assistance, by tracking property damage and creating maps about neighborhood and housing conditions.

28In the Bahamas, this localization from above was applied to emergency response. A company called Pix4D developed software to “stitch maps” together out of digital images. Immediately after collecting aerial data points, they downloaded images and shared the information with NGOs and government authorities, giving them “almost real-time information about the situation on the ground.” Even without access to broadband internet during the storm, the team was able to run the software from a cellular hotspot, then process the data offline. They immediately applied the software’s “slider feature,” toggling back and forth between satellite images and the current images of the impacted area. By the end of a workday, they had maps available to share with authorities, even providing hyper-local data points. In their mapping of a farm, for example, they pinpointed a little girl’s lost dead horse. As one of the technicians reported, ‘With this job, you’re not only helping the government. You’re helping that little girl, and that family” (Pix4D 2019).

29As these examples show, the expertise of map-making is no longer housed in the traditional centers of scientific authority. Yet an even more extreme form of popular ambiguity comes in the form of “localization from below” through map-making by way of crowdsourcing. With the democratization of technology comes the diffusion of these tools into the hands of everyday people making sense of their own worlds. During the storm, humanitarian organizations enrolled volunteers to accumulate information coming from specific locations and integrated them into maps that local rescue teams applied to solve problems. As reported by National Public Radio (NPR), in the Bahamas, the disaster was massive, leaving many injured or missing. Homes, roads, and infrastructures were destroyed or flooded. Figuring out how to reach people and provide food and water on the Bahamian Abaco islands, in particular, was more difficult because maps accurately detailing roads and buildings were never completed. 107 volunteers from around the world used Open Street Map, an open-resource website, where they accessed “satellite imagery and mapping software to identify and draw more than 1,600 roads and 9,000 buildings.” By filling this “data gap,” rescue teams on the ground had more reliable maps (Lu 2019). What the institutional authorities failed to provide with their official maps, the people supplemented with local maps of their own making.

30Ironically, these maps solved ambiguities as much as they created them. On one hand, they offered precise data points for real-time responses. Simultaneously, they raised questions about who was supposed to coordinate the emergency response, which data points should represent the problems, and what information should be collected, thus complicating the meaning of the storm and its effects. In the United States, the National Alliance for Public Safety GIS (NAPSG) Foundation enrolled a range of non-profit and humanitarian organizations to focus on “situational awareness for emergency managers and first responders in affected areas” (GISCorps 2019). Volunteers combed through “social media, webcams, and news outlets for on-the-ground photos and videos” of the storm (Lu, 2019). After assembling and documenting the images, they geocoded them (FEMA 2019). Inserting the images into a map, they created a heterogeneous texture of the storm from the ground up. It enabled new ways to categorize the data and represent the storm as a problem. As you can see in Figure 3, they tagged photos by contributors and by “community lifelines,” applying inductive categories around experiential problems: shelter, health and medical, energy, hazardous materials, and safety.

Figure 2: 2019 Crowdsource Dashboard by FEMA lifeline

Figure 2: 2019 Crowdsource Dashboard by FEMA lifeline​napsg-dorian-275/​

  • 4 Fiske J. (1995), “Popular Culture” in Lentrichchia F., McLaughlin, T. (eds.), Critical Terms for L (...)

31This approach to crowdsourcing the meaning, conditions, and effects of a disaster operated as a distinct form of popular culture. As Fiske4 (1995) points out, in industrial societies, popular culture may not be “pure and authentic,” because it is “made from cultural resources that are opposed to it.” It is “always contradictory and inscribed with traces.” Just like hegemonic ambiguity, there are elements of struggle, but when the work is from the ground up, it is always a matter of “making do rather than one of making.” These problem-solving efforts, making use of the tools available, are not ultimate solutions to disasters and emergencies. Instead, they raise new questions about defining emergencies, as volunteers employ creativity in applying technologies, but not necessarily having the means to develop long-term planning solutions to the growing number of disasters.

32Moreover, the textual relations—the photos and maps alike—take on a blurred meaning of many people doing the work of taking pictures, assembling information, and building perspectives that captures how the storm is affecting lives on the ground. This form of participatory map-making is another way to localize the meanings and effects of disasters, and in this regard, it poses questions and even disruptions to the scientific authority of representing the storm. Whereas hegemonic ambiguity is about challenging the “real” representation, that is, defining the voice of true authority, popular ambiguity is about posing many real representations. It raises the possibility of challenging institutional authority through seemingly endless portrayals that seek solutions by coordinating information and images in new ways.

The Information Age of Disasters

33In this article, we showed how digital platforms mediated the representations of storm maps, which provided a lens into struggles over knowledge and authority. We focused on two forms of ambiguity. The first, hegemonic ambiguity, involved the situation of political power disrupting scientific authority by dismantling the coherence of the storm map and the narrative structure of the disaster event. In traditional information circuitry about disaster planning, authorities funnel complex information and sources into clearly articulated narratives to make them legible for the public and to mitigate danger. As digital platforms reconfigured the circuitry between production and reception, however, they destabilized the shared conditions of cultural dissemination and the objectivity of information. In the case of Hurricane Dorian, digital platforms provided avenues to politicize emergency expertise by drawing on the cultural repertoire of “real and fake” knowledge.

34Yet the digital structure of hegemonic ambiguity also meant that interacting and interpenetrating circuits never fully convinced the public. In the framework of cultural hegemony, contestation and consent were both at play. During the unfolding event, journalists and experts called out President Trump for efforts to sow confusion, creating contestation over the facts and working to restabilize the legibility of the correct storm path. Despite the overwhelming thrust toward a power grab, the strength of the institutions maintained the mundane order of authority, at least for the time being, to correct the record about the storm path.

35Nonetheless, knowledge construction is no longer contained in durable institutions of expertise. The decentering of technology and scientific authority meant that the circuitry created information silos. In the aftermath of the storm, President Trump continued to use various media sources to revise the narrative structure and push back against the pervasive media timeline and representation. Digital platforms enabled Trump to rewrite the story of the disaster, based on a different timeline, with different audiences receiving different narratives, in effect, remixing the meaning of the disaster and how the planning and protocol of the event took place.

36Digital platforms and innovative technologies also enabled a wide range of actors to represent the storm experience and its effects in locally distinct ways. In both hegemonic and popular ambiguity, extreme conditions facilitated confusions over the meaning of the storm map. In this second, more participatory type, actors also challenged the authority of science. Here, localization was embraced by institutional authorities, creating new collaborations between dominant and subordinate positions. This hybrid process raised new popular ambiguities about the authority of disaster response, what information matters most in representing a storm map, and who contributes to the production of knowledge. Citizen science through crowdsourcing became fundamental to problem-solving. With dozens of volunteers combing through thousands of data points, the array of available information raised a new type of ambiguity in terms of selection, representativeness, and scale. Digital circulation and image proliferation meant that the attempt to reassert local territory onto the map turned heterogeneity into a principle of tracking storms.

37Hegemonic ambiguity conjured up the totalitarian mindset, as an attempt to sow confusion. Popular ambiguity evoked the search for precision. As Borges wrote in his short fictional account, “On Exactitude in Science,” the “Cartographers Guilds struck a map of the empire whose size was that of the empire, and which coincided point for point with it.” This precision was deemed “useless.” The hope, of course, is that the growing precision of localized knowledge does not become useless in its popular ambiguity, but rather, that this information can be harnessed in ways that reconfigure strategy, preparation, and territory.

38Storms are easily seen and felt on the ground—they can be subjectively verified. One perversion of the information age of disasters is that, for the most part, the public is not tuned in when the extremes are absent in their own lives. Another perversion, however, is that, in the context of climate change, the extremes are increasingly common forms of public consumption and local experience. The relationship between climate change, disaster, and community is no longer only about accurately representing the historical context of scientific authority and territory. It is also about mapping the contingent, as newfound questions are raised about how to resolve, represent, and intervene into a multi-scalar emergency. Maybe the growing ambiguities of competing levels of abstraction—between the whole Earth, geopolitical territories, and countless points of localization—are not only constraints of the “hyper-real,” but also serve as openings for the study of the information age of climate change and disasters.

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1 Fiske J. (1995), “Popular Culture” in Lentrichchia F., McLaughlin, T. (eds.), Critical Terms for Literary Study, Chicago, The University of Chicago Press, p. 321-335, here p. 325.

2 Barthes R. (1981), Camera Lucida: Reflections on Photography, New York, Macmillan, p. 26-28.

3 Latour B. (2021), After Lockdown: A Metamorphosis, Medford, MA, Polity Press, p. 124-125.

4 Fiske J. (1995), “Popular Culture” in Lentrichchia F., McLaughlin, T. (eds.), Critical Terms for Literary Study, Chicago, The University of Chicago Press, p. 321-335.

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Table des illustrations

Titre Figure 1: President Trump Receives a Hurricane Dorian Update. Trump Whitehouse Archived
Fichier image/png, 1,2M
Titre Figure 2: 2019 Crowdsource Dashboard by FEMA lifeline
Fichier image/png, 333k
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Andrew Deener, Black Hawk Hancock et Zoe Folsom, « The Storm Map as Digital Ambiguity »Socio-anthropologie, 46 | -1, 125-141.

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Andrew Deener, Black Hawk Hancock et Zoe Folsom, « The Storm Map as Digital Ambiguity »Socio-anthropologie [En ligne], 46 | 2022, mis en ligne le 15 décembre 2022, consulté le 01 juin 2023. URL : ; DOI :

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Andrew Deener

Andrew Deener is a professor of sociology at the University of Connecticut. He is the author of Venice: A Contested Bohemia in Los Angeles (University of Chicago Press 2012) and The Problem with Feeding Cities: The Social Transformation of Infrastructure, Abundance, and Inequality in America (University of Chicago Press 2020). His current research focuses on the connections between the politics of urban development, infrastructure planning, and social and environmental consequences.

Black Hawk Hancock

Black Hawk Hancock is an associate professor of sociology at Depaul University. He is the author of American Allegory: Lindy Hop and the Racial Imagination (University of Chicago Press, 2013) and coauthor with Roberta Garner of Changing Theories: New Direction in Sociology. His main research interests are in ethnography, race and ethnicity, and social theory. His work has appeared in Ethnography, Journal of Contemporary Ethnography, Qualitative Sociology, and Sociological Perspectives.

Zoe Folsom

Zoe Folsom is a graduate student in sociology at the University of Connecticut. Her main research interests include political economy of climate change, corporate governance, and the social dimensions of climate science. She is currently working on a thesis investigating the governance and mythology of the American voluntary carbon offset market. 

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