climate modeling

Community Modeling and the Future of Numerical Weather Prediction

A 2024 AMS Summer Community Meeting highlight

The AMS Weather Enterprise Study will provide a comprehensive picture of the shifting landscape of weather-related fields to inform our joint future. At the 2024 Summer Community Meeting, working groups discussed what they’d found about key issues facing the enterprise.

Here are a few takeaways from the Community Modeling working group, as reported by Gretchen Mullendore of the NSF National Center for Atmospheric Research (NCAR). Community modeling employs Earth system model software developed by public-academic partnerships. Community models have open-source components and are freely available for use by anyone with the computing power to run them–for example researchers, students, and private companies.

Photo: Gretchen Mullendore

How has the community modeling landscape changed in recent years, and where are we now?

First, artificial intelligence and machine learning (AI/ML) have become huge players in numerical weather prediction (NWP) model development. Second, a cultural change in weather research and forecasting is taking place; we’re beginning to collaborate much more closely across agencies and industries than we used to, and many people are invested in deepening those collaborations.

What were the main themes that came out of your working group’s discussions?

The NWP community is collaborating more than ever before. However, the community remains spread among many institutions, with each research group working on small pieces of the overall weather prediction challenge. Having many research groups can be a strength in terms of encouraging innovation, but it is a weakness if research isn’t coordinated effectively to fully realize collective benefits. Limited funding and resourcing is an additional barrier to community model development. As a community, we need to continue to prioritize modularity and interoperability across NWP systems and work towards more effective shared governance.

Another major theme is the role of the private sector in NWP. Big tech companies are increasingly getting into NWP and there is a concern that public forecasting efforts are not able to keep pace. The private sector brings agility and innovation to the field, and working to leverage unique contributions across public, academic, and private research entities is valuable. However, if the growing role of the private sector in NWP leads to more observations, simulations, and software being behind proprietary walls, there is risk to accessibility and collaboration.

The NWP community is also facing challenges in workforce development. Universities are teaching people the right skills to work in data assimilation and analytics, but many of those people are being scooped up by private sector companies in other fields offering salaries that employers in the weather industry cannot compete with. We need to better communicate the value of our missions and our work to attract and retain talented early career professionals.

What preliminary recommendations or future directions have you discussed?

We can and should continue to build on community efforts to coordinate across public, academic, and private developers. This coordination should include planning for the appropriate use of AI/ML tools in NWP research and applications. We can also build on efforts to leverage social science research to prioritize our limited resources, e.g., by learning what type of forecasting improvements will most benefit stakeholders. Finally, we need to recognize the importance of the legislature in resourcing model development. It’s important to communicate our successes and the value of a thriving NWP community. In summary, we should strategize to develop intentional communication among ourselves, across disciplines, and most importantly, with legislatures and the public.

What did you hear from the community at the Summer Community Meeting?

My pick for the most important question asked at the SCM is, “What does success look like in NWP development?” The goal that motivates us all in the NWP community is for no more deaths to occur as a result of weather hazards. In order to achieve breakthroughs in prediction that stand to move us closer to that goal, we need to invest in innovation, which requires risk. However, much of the work in NWP development is funded by federal agencies, which tend to be risk-averse. More broadly, the systems in which our scientists work can be an impediment to innovation. For example, the pressure to publish often incentivizes incremental progress over new ideas. Collectively, as an NWP community, we need to build systems that allow researchers to take risks without fear of failure or negative consequences.

What are the main challenges, conflicts, or points of discussion identified by the group (or at the SCM)?

AI/ML could possibly improve the skill and speed of all parts of the NWP system. That said, the challenges are also great. Challenges include a lack of AI/ML expertise in NWP community leadership; a need to invest in AI/ML without additional resources; and a need to keep up with the latest AI/ML research, which is moving incredibly rapidly. The lack of clear AI/ML plans from U.S. institutional leaders in NWP led some to ask at the SCM if leaders were skewed against it. My perception is instead that the community is feeling overwhelmed by these challenges. We can overcome these challenges through innovation and collaboration, leveraging our respective expertise and investments to more efficiently take advantage of the great opportunity that is AI/ML in NWP.

Want to join a Weather Enterprise Study working group? Email [email protected].

About the Weather Enterprise Study

The AMS Policy Program, working closely with the volunteer leadership of the Commission on the Weather, Water, and Climate Enterprise, is conducting a two-year effort (2023-2025) to assess how well the weather enterprise is performing, and to potentially develop new recommendations for how it might serve the public even better. Learn more here, give us your input via Google Forms, or get involved by contacting [email protected].  

About the AMS Summer Community Meeting

The AMS Summer Community Meeting (SCM) is a special time for professionals from academia, industry, government, and NGOs to come together to discuss broader strategic priorities, identify challenges to be addressed and opportunities to collaborate, and share points of view on pressing topics. The SCM provides a unique, informal setting for constructive deliberation of current issues and development of a shared vision for the future. The 2024 Summer Community Meeting took place August 5-6 in Washington, DC, and focused special attention on the Weather Enterprise, with opportunities for the entire community to learn about, discuss, debate, and extend some of the preliminary findings coming from the AMS Weather Enterprise Study.

An Epic Odyssey: Celebrating Warren Washington (1936–2024)

By Anjuli S. Bamzai, AMS President

Dr. Warren Washington passed away last month. The American Meteorological Society was lucky to benefit from a career’s worth of attention from this exceptional individual — a trailblazer in climate modeling, NCAR Distinguished Scholar, advisor to five U.S. presidents, National Science Board chair, and longtime leader of the AMS community. He was among the first to develop and use the pioneering atmospheric general circulation models that underlie our current understanding of climate change, and his research contributed to the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report that received the Nobel Peace Prize in 2007.

Warren joined AMS as an undergraduate student and was actively engaged with the Society his entire career. He served as our AMS President in 1994, our 75th anniversary year. He played a key role in advancing initiatives to enhance diversity in the field, including as a scholarship donor and co-founder of the Board on Women and Minorities. He was named an Honorary Member, and received several prestigious AMS awards. He was a mentor, beloved colleague, and friend to many of us, myself included.

Elucidating the Future Climate

Warren was born in Portland, Oregon. His parents placed a high value on education despite the hostility his mother faced as a nurse when studying at the University of Oregon and the struggles his Talladega College-educated father faced during the Great Depression. Warren earned his undergraduate degree in physics and his master’s degree in meteorology at Oregon State University. He went on to become the second ever African American to earn a doctorate in the atmospheric sciences, which he received from Penn State University in 1964.

<<The cover of Dr. Warren Washington’s autobiography shows a 1930 panoramic photograph (in three parts) of the Portland, Oregon Bethel African Methodist Episcopal Church and its congregation, which represented about 5% of Oregon’s Black population at the time. Warren’s maternal grandfather, Wirt Morton Sr., is fifth from the right in the bottom segment; Warren’s mother, Dorothy Morton, is in the top segment (to the left of the church door and immediately to the left of the man holding a hat in his hand).

In 1963, Warren joined the NSF National Center for Atmospheric Research (NCAR) as a research scientist. He would remain connected with NCAR for over six decades. He was a Distinguished Scholar there at the time of his passing.

In the 1960s, he worked with his colleague Dr. Akira Kasahara to develop one of the first computer models of the atmosphere. His team at NCAR used those models to enhance our understanding of the role of natural processes as well as human activities in the coupled Earth system — over time incorporating oceans, sea ice, surface hydrology, and more into their simulations. This research would go on to inform innumerable contributions in climate science, including the IPCC’s Nobel Peace Prize-winning work.

Dr. Warren Washington with colleagues. Photo at left: Warren Washington and Akira Kasahara, courtesy of NSF NCAR Archives (original work published 1975). Center photo: Warren and Mary Washington with Anjuli Bamzai. Photo at right: NCAR Climate Change Research Section, 2005. Left to right: Warren Washington, Jerry Meehl, Haiyan Teng, Gary Strand, Stephanie Shearer, Dave Lawrence, Vince Wayland, Julie Arblaster, Reto Knutti, Aixue Hu, and Lawrence Buja. Photo courtesy of Jerry Meehl, NSF NCAR.

In 1986, Warren co-authored the book, An Introduction to Three-Dimensional Climate Modeling, with Claire Parkinson. It provided an introduction to the development of three-dimensional climate models and their applications for simulating aspects of the current climate system, from ENSO to the effects of increasing greenhouse gas concentrations on future climate.

I met Warren on my first visit to NCAR back in the 1990s, and then interacted more closely with him when I was program manager of the climate modeling program at the U.S. Department of Energy and he was serving on the DOE Biological and Environmental Research Advisory Committee (BERAC). We also worked closely on an  international workshop, “Challenges in Climate Change Science and the Role of Computing at the Extreme Scale,” which Warren chaired in 2008. In looking back at the workshop’s themes — which focused on computational issues associated with model development, simulations and assessment, decadal predictability, natural variability and prediction — I am struck by what a visionary Warren was to identify several decades ago some of the vexing issues in climate science that we are still addressing today!

A Decorated Life

During the span of his illustrious career, Warren was on numerous federal advisory committees and commissions. He served on the National Science Board (1994–2006); initially as a member and then as the Chair starting in 2002. In 2002, he was elected to the National Academy of Engineering “for pioneering the development of coupled climate models, their use on parallel supercomputing architectures, and their interpretation.” In 2003, he was elected to the American Philosophical Society.

In 1999, Warren received the Charles Anderson Award from the AMS for “pioneering efforts as a mentor and passionate supporter of individuals, educational programs, and outreach initiatives designed to foster a diverse population of atmospheric scientists. Dr. Charles E. Anderson (1919-1994) was a former Tuskegee Airman and the first African American to receive a PhD in meteorology.

<< Dr. Warren Washington receiving the Charles E. Anderson award in 1999, from AMS President George Lawrence Frederick Jr. Photo courtesy of AMS archives.

In 2006, Warren became an Honorary Member of the AMS. In his acceptance speech, for which he received a standing ovation, he advised early career scientists to find personal growth and leadership by taking part in the broader aspects of their field. He also stated that “Scientists should be free to tell the public, media, and policy makers the results of their research. Of course, there is always the need to make sure not to confuse the public, so individual responsibility is important.” He ended his speech by pointing out that scientific debate should be settled at scientific society meetings.

At the following AMS Annual Meeting, he received the Charles Franklin Brooks Award for Outstanding Service to the Society, and a couple of years later, he shared the 2009 AMS Jule G. Charney Medal with his longtime colleague and collaborator Jerry Meehl.

Warren and Jerry Meehl with Marla Meehl and Mary Washington at the 89th AMS Annual Meeting, held January 2009 in Phoenix, AZ. Photo courtesy of Jerry Meehl, NCAR.

Warren Washington with President Barack Obama

In 2010, Warren was also one of the ten eminent researchers to be awarded the National Medal of Science by President Barack Obama, “for his development and use of global climate models to understand climate and explain the role of human activities and natural processes in the Earth’s climate system and for his work to support a diverse science and engineering workforce.” 

<< Warren Washington receives the National Medal of Science from President Barack Obama. Copyright Charles M. Vest (2010), used with permission.

Also in 2010, a symposium was held in Warren’s honor at the AMS Annual Meeting in Atlanta, Georgia. It was attended by many of the legends of climate modeling!

Attendees at Warren Washington symposium
Mary (left) and Warren (right) Washington at Penn State outside the Warren M. Washington building

Left: Group photo at symposium honoring Warren Washington at the 90th AMS Annual Meeting, held January 2010 in Atlanta, Georgia. From left: Kirk Bryan, Syukuro Manabe, Gerald Meehl, Greg Jenkins, Larry Gates, Jane Lubchenco, Steve Schneider, Dave Bader, Warren Washington, John Kutzbach, V. Ramanathan, Jim Hansen, and Bert Semtner. Photo copyright University Corporation for Atmospheric Research (2010). Right: Mary and Warren Washington at the newly named Warren M. Washington building at Penn State University’s Innovation Park. Photo credit: Patrick Mansell/Penn State (Creative Commons license).

Warren was a Distinguished Alumnus of Penn State and in 2019, Penn State named a building in his honor at its campus Innovation Park site.

A Legacy of Empowerment

Warren was instrumental in establishing AMS’s Board on Women and Minorities, now known as AMS BRAID. He and his wife, Mary, also established an AMS undergraduate scholarship to provide support to underrepresented students. Through their generosity, several who otherwise might not have attended the AMS Annual Meeting have been able to do so.

In early 2020, the AMS set up The Warren Washington Research and Leadership Medal to be awarded to individuals recognized for the combination of highly significant research and distinguished scientific leadership in the atmospheric and related sciences.

Warren was a pioneer and true giant in our community. Those of us who were fortunate to interact with him benefited from his sage counsel, vision, and sharp intellect. No question was mundane enough that it didn’t get a deliberate, candid yet considerate response from him. He helped so many realize their full potential to excel. What a great scientist, and a great humanist! His legacy lives on through those he supported, mentored, and inspired.

Dr. Warren Washington was the epitome of a true leader.

Photo at top: Warren Washington with the late Fuqing Zhang (back to camera) and Ruby Leung. Past-President Jenni Evans is in the background on the left. Taken at the 2019 opening of the Warren M. Washington building at Penn State. Photo credit: David Kubarek/Penn State (Creative Commons license).

Asian American and Pacific Islander Heritage Month Spotlight: Dr. Syukuro “Suki” Manabe

By Anjuli S. Bamzai, AMS President

My graduate advisor at George Mason University, Dr. Jagadish Shukla, displayed the photos of four meteorologists in his office: Drs. Norman A. Phillips, Jule Charney, Edward Lorenz, and Syukuro “Suki” Manabe. All giants in their field, they had been his PhD advisers at Massachusetts Institute of Technology (MIT). In the 1990s, as I pursued my graduate degree at Dr. Shukla’s Center for Ocean-Land-Atmosphere Studies (COLA), the scientific family tree remained strongly connected, and so I in turn had the chance to cross paths with luminaries like Manabe in person.

Suki Manabe photo

Circa 1994, I had the privilege of hearing Manabe–or, as I came to refer to him, Suki-san–give the inaugural talk at the newly established COLA. He spoke about the use of dynamical general circulation models to study the atmosphere and its coupling to land, using a simple ‘bucket’ model to discover emergent properties of this complex, chaotic system. He was an animated speaker; it was apparent that he was driven by curiosity and sheer love of the science that he was pursuing.

I was inspired by his ability to explain the properties of such a complex system as the Earth in such elegant terms. Suki-san’s clarity and scientific passion resulted in contributions to our understanding of climate the importance of which cannot be overstated. As I began my own foray into Earth system science, those initial interactions were a formative experience.

Left: Suki-san enjoying his work. Photo courtesy of Dr. V. Ramaswamy.

The models he used were relatively simple compared to the complex Earth system models of today. Yet Manabe and Wetherald (1967), published in the AMS’s Journal of the Atmospheric Sciences, is arguably one of the most influential papers in climate science. It demonstrated a key feature of the atmosphere with an increase in carbon dioxide: rising temperatures closer to the ground while the upper atmosphere got colder. If the variation in solar radiation was primarily responsible for the temperature increase, the entire atmosphere would have gotten warmer.

Graphic from Phys.org, based on Manabe and Wetherald (1967), Figure 16, “Vertical distributions of temperature in radiative convective equilibrium for various values of CO2 content.”

The work that Suki-san and his team conducted comprised a major component of the 1979 report, “Carbon dioxide and climate: A scientific assessment.” Led by Jule Charney from MIT, it is now commonly referred to as the Charney Report. The main result of the succinct 22-page report was that “the most probable global warming for a doubling of [atmospheric] CO2 [is] near 3°C with a probable error of ± 1.5°C.” Perhaps most importantly, the report ruled out the possibility that increasing CO2 would have negligible effects. This estimate of climate sensitivity has pretty much withstood the test of time; in the past forty years, annual average CO2 concentrations increased by ~ 21% and the global average surface temperature increased by ~0.66°C. How prescient!

Suki-san was one of the panelists who shared their insights at a session that the National Academy of Sciences’ Board on Atmospheric Sciences and Climate (BASC) convened during its November 2019 meeting to commemorate the 40th anniversary of the Charney Report. Suki-san’s concluding slide pretty much summed up his philosophy: make your model just as complicated as it needs to be, no more. (See photo below.)

Panelists photo and concluding slide. Slide text says, "Concluding Remarks: [Bullet point one] Satellite observation of outgoing radiation over annual and inter-decadal time scale should provides macroscopic constraint that is likely to be useful for reducing large uncertainty in climate sensitivity. [Bullet point two] It is desirable to make parameterization of subgrid-scale process 'as simple as possible', because simpler parameterization is more testable."
Left: Panelists at the November 21, 2019 session on The Charney Report: Reflections after 40 years at the BASC meeting. (Left to right) Drs. Jagadish Shukla, former student of Jule Charney; D. James Baker, member of the original authoring committee; Jim Hansen and Syukuro Manabe, major contributors to the original report; and John Perry, staff lead for the report. Right: Dr. Manabe’s final slide at the Charney Report session at BASC. Photos courtesy of Anjuli Bamzai.

October 5, 2021, was such an exciting day to wake up to! The Nobel Prize in Physics was shared by Drs. Syukuro Manabe, Klaus Hasselman, and Giorgio Parisi. The citation reads: “The Nobel Prize in Physics 2021 was awarded for groundbreaking contributions to our understanding of complex physical systems” with one half jointly to Syukuro Manabe and Klaus Hasselmann “for the physical modelling of Earth’s climate, quantifying variability and reliably predicting global warming,” and the other half to Giorgio Parisi “for the discovery of the interplay of disorder and fluctuations in physical systems from atomic to planetary scales.”

As he eloquently stated on the momentous day that he received the Nobel Prize, “I did these experiments out of pure scientific curiosity. I never realized that it would become a problem of such wide-ranging concern for all of human society.”

The accompanying press release on the Nobel Prize particularly cites Suki-san’s work at NOAA in the 1960s, noting that “he led the development of physical models of the Earth’s climate and was the first person to explore the interaction between radiation balance and the vertical transport of air masses. His work laid the foundation for the development of current climate models.”

Suki Manabe with Jagadish Shukla and Marcia McNutt.
Suki Manabe with V. Ramaswamy and Whit Anderson.

Left: Event to honor Nobel Laureate Dr. Suki Manabe at National Academy of Sciences. (Left to right) Drs. Jagadish Shukla, Suki Manabe and Marcia McNutt, President National Academy of Sciences. Photo courtesy of Dr. J. Shukla. Right: (Left to right) Drs. V. Ramaswamy, Director, NOAA GFDL, Suki Manabe, and Whit Anderson, Deputy Director, NOAA GFDL, celebrating the big news of Suki-san’s Nobel Prize, October 2021. Photo courtesy of Dr. V. Ramaswamy.

It is no exaggeration to state that the modeling findings by Suki Manabe and, about a decade later, Klaus Hasselman, opened not only an era of climate modeling but also an entirely new subfield of climate science, viz., detection and attribution (D&A) through fingerprinting and other techniques. Observations have provided an important reality check to model simulations through these D&A efforts.

The current torchbearers of the D&A tradition are Drs. Ben Santer, Tim DelSole, Reto Knutti, Francis Zwiers, Xuebin Zhang, Gabi Hegerl, Claudia Tebaldi, Jerry Meehl, Phil Jones, David Karoly, Peter Stott MBE, Tom Knutson, and Michael Wehner, among others. Over the years several of them have also gone on to receive AMS awards—including, in Meehl’s case, the Jule G. Charney Medal. Speaking of awards, Jonathan Gregory is the most recent recipient of AMS’s Syukuro Manabe Climate Research Award, which has also been bestowed on Drs. Joyce Penner and Cecilia Bitz. Next year, consider nominating someone for the Manabe Award, the Charney Medal, or the new Jagadish Shukla Earth System Predictability Prize!

Equations developed by Dr. Suki Manabe, displayed in the Paris subway during the 2015 UN Climate Change Conference (COP21) in Paris. Photos courtesy of Dr. V. Ramaswamy.

Those of us in the atmospheric and related sciences benefit directly from Suki Manabe’s scientific legacy and intellectual passion, and all of human society owes Suki-san a great debt for helping us to understand climate change, one of the greatest challenges humankind has ever faced.

Anjuli is grateful to Katherine ‘Katie’ Pflaumer for providing useful edits.

A Good Climate for Looking at Clouds

How much do we know about clouds and the effects they have on climate change? It’s a lingering source of uncertainty, with as many questions as answers. No wonder the National Science Foundation calls them “The Wild Card of Climate Change” on its new website about the effect of clouds in climate.
The site is good place to start thinking about this complicated issue. The NSF page features videos of cloud experts like David Randall of Colorado State University and AMS President Peggy LeMone of NCAR, as well as a slide show, animations, articles, and other educational material that address some of most salient cloud/climate questions, such as: Will clouds help speed or slow climate change? Why is cloud behavior so difficult to predict? And how are scientists learning to project the behavior of clouds?
The impression one gets from the website about the progress of the science in this area may vary depending on your point of view, but Randall, for one, sounds about as optimistic as you can get. In his video, he admits that optimism is a job requirement for climate modelers, but in his assessment, “We’re not in the infant stages of understanding [clouds] any more; we’re in first or second grade, and on the way to adolescence.” His hope for solving their role in climate and representing cloud effects in climate modeling rests in part on better computers and in part on the numerous bright people entering the field now, ready to overshadow the work of their mentors.
The AMS Annual Meeting in Seattle will be a good occasion to dig deeper at the roots of Randall’s optimism and sample some of the emerging solutions to the cloud/climate relationship. For example, Andrei Sokolov and Erwan Monier of MIT will discuss the influence that adjusting cloud feedback has on climate sensitivity  (Wednesday, 26 January, 11:30 a.m. in Climate Variability and Change). Basically, they’re using small adjustments to the cloud cover used to calculate surface radiation in a model to create a suite of results–an ensemble. The range of results better reflects the sensitivity of climate observed in the 20th century better than some other methods of creating ensembles, such as adjusting the model physics.
Randall says in his video that early predictions about climate change are already coming to pass and this leads to optimism that more predictions will verify well in the coming years as we scrutinize climate more and more closely. This of course presupposes sustained efforts to observe and verify. Laying the groundwork for this task–and for thus better climate models–are Stuart Evans (University of Washington) and colleagues in a study they are presenting in Seattle. According to their abstract, “Improving cloud parameterizations in large scale models hinges on understanding the statistical connection between large scale dynamics and the cloud fields they produce.” Their study focuses on the relationship between synoptic-scale dynamic patterns and cloud properties (Monday, 24 January, 11 a.m. in Climate Variability and Change). Evans et al. dig through 13 years of cloud vertical radar profiles from the US Southern Plains site of the DOE ARM program and relate it to atmospheric “states”, thus providing a metric for evaluating how well climate models relate cloudiness to radiation and other surface properties.
While Evans and colleagues use upward looking remote sensing, Joao Teixeira (JPL/Cal Tech) and coauthors look down at boundary layer cloudiness from above–using satellites. They expect to show how new methodologies with satellite data can improve the way low level clouds are parameterized in climate models (Thursday, 27 January, 9:30 a.m., in Climate Variability and Change). A recent workshop at Cal Tech on space-based studies of this problem stated:

Clouds in the boundary layer, the lowermost region of the atmosphere adjacent to the Earth’s surface, are known to play the key role in climate feedbacks that lead to these large uncertainties. Yet current climate models remain far from realistically representing the cloudy boundary layer, as they are limited by the inability to adequately represent the small-scale physical processes associated with turbulence, convection and clouds.

The lack of realism of the models at this low level is compounded by the lack of global observing of what goes on underneath the critical low-level cloud cover–hence the effort of Teixeira et al. (and others) to “leverage” satellite observing, with its global reach, to improve understanding of low level thermodynamics in the name of improving climate simulations.

From the new NSF web page on clouds and climate, this picture shows a series of mature thunderstorms in southern Brazil. Photo credit: Image Science & Analysis Laboratory, NASA Johnson Space Center

Climatology: Inverting the Infrastructure

Atmospheric science may not seem like a particularly subversive job, but from an information science perspective, it involves continually dismantling the infrastructure that it requires to survive. At least that’s the way Paul Edwards, Associate Professor of Information at the University of Michigan described climatology, and one other sister science, in an interesting hour-long interview on the radio show, “Against the Grain” last week. (Full audio is also available  for download.)
In the interview Edwards describes how the weather observing and forecasting infrastructure works (skip to about the 29 minute mark if that’s familiar), then notes that climatology is the art of undoing all that:

To know anything about the climate of the world as a whole we have to look back at all those old [weather] records. …But then you need to know about how reliable those are. [Climate scientists] unpack all those old records and study them, scrutinize them and find out how they were made and what might be wrong with them–how they compare with each other, how they need to be adjusted, and all kinds of other things–in order to try to get a more precise and definitive record of the history of weather since records have been kept. That’s what I call infrastructural inversion. They take the weather infrastructure and they flip it on its head. They look at its guts.

In his book, The Vast Machine: Computer, Models, Climate Data, and the Politics of Global Warming, Edwards points out that people don’t realize how much of this unpacking—and with it multiple layers of numerical modeling–is necessary to turn observations into usable, consistent data for analysis and (ultimately) numerical weather and climate predictions. The relationship between data and models is complicated:

In all data there are modeled aspects, and in all models, there are lots of data. Now that sounds like it might be something specific to [climate] science, but …in any study of anything large in scope, you’ll find the same thing.

In part because of this “complicated relationship” between observations and models, there’s a lot of misunderstanding about what scientists mean when they talk about “uncertainty” in technical terms rather than in the colloquial sense of “not knowing”. Says Edwards,

We will always keep on finding out more about how people learned about the weather in the past and will always find ways to fix it a little bit. It doesn’t mean [the climate record] will change randomly or in some really unexpected way. That’s very unlikely at this point. It means that it will bounce around within a range…and that range gets narrower and narrower. Our knowledge is getting better. It’s just that we’ll never fix on a single exact set of numbers that describes the history of weather.

Climatology is not alone in this perpetual unpacking of infrastructure. Economists seem like they know all about what’s going on today with their indexes, Gross Domestic Products, inflation rates, and money supply numbers. That’s like meteorology. But to put together an accurate history of the economy, they have to do a huge amount of modeling and historical research to piece together incongruous sources from different countries.

There is a thing called national income accounting that has been standardized by the United Nations. It wasn’t really applied very universally until after the Cold War….Just to find out the GDP of nations you have to compare apples and oranges and find out what the differences are.

And to go back as recently as the 1930s?

You would have to do the same things the climate scientists have to do…invert the infrastructure.