Sadie Bartholomew, born on November 10, 1899, in England, lived through an era of monumental change. Her life spanned much of the 20th century, a period marked by global wars, societal shifts, and scientific progress. Though she may not have been directly involved in the major scientific advancements of her time, the world in which Sadie lived set the stage for the evolution of many of the fields we rely on today—particularly computational science, which continues to shape how we study and understand the Earth’s climate and weather systems.
In this article, we will explore both Sadie Bartholomew’s personal journey and the development of modern computational science. By connecting her era to the present-day advancements in climate modelling, hydrological simulations, and high-performance computing, we aim to understand how the foundation laid by individuals like Sadie eventually led to the cutting-edge tools and infrastructure used in research today.
Sadie Bartholomew: A Brief Overview
Born in 1899 in England, Sadie Bartholomew was part of a generation that witnessed immense political and social change. While her life may not be widely recorded in history, the context in which she lived is essential to understanding the forces that shaped the world around her. Married to George Bartholomew, Sadie spent her later years in Harpenden, Hertfordshire, where she passed away on May 9, 1977.
Sadie’s early life occurred during a time of significant societal shifts, especially regarding women’s rights and societal roles. Born just before the turn of the century, Sadie lived through World War I, the interwar period, and the Second World War. These global conflicts dramatically reshaped England, especially in terms of its social, economic, and political structures. Sadie’s life coincided with the women’s suffrage movement, the rise of the welfare state, and the industrial and technological revolutions that would later impact the scientific community.
Although the specifics of Sadie’s personal life, education, and career remain less documented, it is likely that she, like many women of her time, was shaped by the expectations of domesticity while witnessing the gradual transformation of gender roles, particularly during and after the world wars.
The Broader Context of Sadie Bartholomew’s Time: From Early Scientific Advancements to Computational Science
Sadie’s life unfolded at a time when great strides were made in science and technology, though she may not have directly contributed to these fields. The 20th century saw the rise of new scientific theories, technological innovations, and the beginning of the digital revolution. These advancements laid the groundwork for what we now call computational science, a field that relies on simulations run on supercomputers to model complex phenomena.
Sadie’s era saw the birth of early computing devices during and after World War II, leading to the creation of the first electronic computers. These machines paved the way for the development of modern computational infrastructure, which is integral to fields like climate science, weather prediction, and environmental modelling. In many ways, the scientific curiosity that was growing during Sadie’s lifetime is directly tied to the sophisticated research tools used in Earth sciences today.
Computational Science: Bridging the Gap Between the Past and Present
While Sadie Bartholomew may not have lived to see the rise of modern supercomputing, her life unfolded during a period that witnessed the dawn of the digital age. Today, computational science is one of the most exciting and transformative fields in research, particularly in Earth science. This interdisciplinary field leverages powerful supercomputers to simulate complex systems, allowing researchers to make predictions about our planet’s future, from weather forecasting to climate change modelling.
Computational science in the 21st century primarily revolves around high-performance computing (HPC) systems, which are capable of performing vast numbers of calculations per second. These supercomputers are essential for tasks such as climate modelling, hydrological simulations, and numerical weather prediction, which require analyzing vast amounts of data generated by complex atmospheric models.
The Approach to Exascale Computing and Its Relevance to Earth Science
One of the biggest challenges facing computational science today is the approach to the “exascale era” of computing. Exascale refers to supercomputers capable of performing at least one exaflop (1 quintillion calculations per second). This leap in computational power is set to revolutionize numerous fields, particularly those related to the Earth sciences, where models must take into account the intricate behaviors of our planet’s atmosphere, oceans, and land.
The “exascale era” promises to usher in an era of unprecedented capabilities for climate research, weather forecasting, and environmental science. With these advances, scientists will be able to create even more precise models that can simulate the Earth’s climate and predict how it might change over time. The ability to run such complex simulations relies on advanced infrastructure, including high-performance computing systems, sophisticated data storage solutions, and efficient data workflows.
As these developments unfold, researchers working in climate science, atmospheric modelling, and weather prediction are increasingly reliant on tools that can manage and analyze big data, as well as document simulation configurations to ensure the reproducibility and transparency of results.
Tools and Infrastructure for Atmospheric Science
In my own work as a Computational Scientist within the Computational Modelling Services (CMS) group at the National Centre for Atmospheric Science (NCAS) at the University of Reading, I focus on developing, optimizing, and maintaining open-source tools that support research and collaboration in Earth Science. These tools are crucial for the running, configuration, documentation, and analysis of simulations related to atmospheric science, particularly in climate modelling and numerical weather prediction.
Climate modelling and hydrological modelling rely heavily on the ability to simulate the complex interactions between different elements of the Earth’s system—air, water, and land. These simulations require not just significant computational resources but also advanced tools for managing vast datasets, ensuring accurate documentation, and enabling collaboration across research institutions.
Through the use of open-source software, my work aims to make these tools accessible to the broader scientific community. By fostering collaboration and sharing resources, we can create a more transparent and efficient research environment where advances in computational modelling can be shared and built upon by scientists from around the world.
Openness and Standards in Computational Science
One of the most important aspects of modern computational science is the advocacy for openness and collaboration. I am a strong proponent of making research artefacts open-source, promoting the use of metadata standards, and supporting skill-building within the scientific community. Open-source software plays a vital role in ensuring that computational tools are accessible to anyone, regardless of their institution or resources.
Moreover, metadata standards are essential for ensuring that the results of simulations are reproducible and understandable by other researchers. In the field of atmospheric science, metadata helps describe the context and characteristics of data generated by simulations, ensuring that others can use this data for further analysis. Without these standards, the scientific community would face significant challenges in sharing and understanding complex datasets.
Conclusion: From Sadie Bartholomew’s Era to the Future of Computational Science
Sadie Bartholomew’s life, though seemingly far removed from the world of modern science and technology, unfolded in an era that witnessed the birth of many of the technologies we now rely on in fields like computational science. From the early days of mechanical computing to the sophisticated simulations that guide today’s climate models, the evolution of scientific tools has been a key driver of progress in Earth sciences.
As we look toward the future of high-performance computing and the exascale era, we can reflect on the broader historical context that made these advancements possible. Sadie’s life, though not directly linked to computational science, serves as a reminder of how the personal and the scientific are intertwined—how societal shifts and technological innovations lay the groundwork for future breakthroughs.
In my work developing tools and infrastructure for climate and weather prediction, I am part of a growing field that continues to build on the foundation laid by the pioneers of Sadie’s time. By promoting openness, collaboration, and the adoption of new computational methods, we aim to continue pushing the boundaries of what is possible in understanding and predicting the behavior of our planet.
Through this combination of historical reflection and forward-thinking science, we see how the past and present intersect, shaping the future of computational science and atmospheric research for generations to come.
