How I tried Climate Modelling and Discovered the Physics Behind Weather Patterns

The Challenge: Making Climate Science Accessible

While studying climate science, I kept encountering references to complex climate models but never saw how they actually worked under the hood. Determined to understand the technical foundations of climate predictions, I decided to get hands-on experience with the same software that researchers use to study our planet's future.

The Technical Journey: From Code to Climate

I started with the MIT General Circulation Model https://github.com/MITgcm/MITgcm, the same software used by climate researchers worldwide. This wasn't a simplified educational tool – this is the real deal used for actual climate research. Working with MITgcm meant diving into a technical stack that included Fortran programming for over 100,000 lines of atmospheric physics code, using GitHub Codespaces for cloud-based high-performance computing, custom compilation processes with gfortran, Python data analysis with NumPy and Matplotlib, and professional Git workflow with proper branching strategies.

The compilation process alone was so complex that required configuring complex makefiles, managing intricate dependencies, and linking hundreds of source files into a working climate model. This experience gave me deep appreciation for the engineering complexity behind climate science tools.

The Held-Suarez Experiment

I implemented the Held-Suarez atmospheric benchmark, which is a standard test case used by climate modeling groups worldwide to validate their code. This simplified atmospheric model captures the essential physics of global atmospheric circulation, including Coriolis effects from planetary rotation, thermal forcing and pressure gradients across 20 vertical atmospheric levels, all represented on a cubed-sphere grid that provides complete global coverage.

The Experiment: What If Earth Rotated Differently?

Once I had a working model, I designed an experiment to test a fundamental question: How does planetary rotation affect climate? I created two identical virtual planets with one crucial difference. The control planet mimicked Earth with its familiar 24-hour rotation, while the experimental planet rotated much more slowly, completing one day every 48 hours. Everything else remained constant between the two worlds: same gravity, same atmospheric composition, same heating patterns from the artificial sun. Each simulation ran for 360 days, generating complete atmospheric datasets including temperature and wind fields across the entire global grid.

Quantitative Results

The results exceeded my expectations, showing dramatic and scientifically meaningful differences between the two planets. The normal Earth developed complex temperature patterns with significant spatial variation of 5.3°C across different regions, reflecting the dynamic heat transport that we experience in real weather systems. In contrast, the slow planet exhibited much more uniform temperatures with only 2.4°C of variation, suggesting that weaker circulation led to less efficient mixing of hot and cold air masses. The maximum temperature difference between corresponding regions reached 19.9°C, demonstrating that this seemingly simple change in rotation rate created profound climate impacts.

Figure: Comprehensive comparison showing how planetary rotation affects both temperature patterns and atmospheric circulation. The slow planet (48-hour days) shows dramatically different climate patterns compared to normal Earth (24-hour days).

The atmospheric circulation patterns were equally striking. Normal Earth generated strong wind circulation with maximum speeds reaching 25.8 m/s, creating the kind of jet streams and weather systems familiar from meteorology. The slow planet, however, developed much weaker circulation with maximum winds of only 16.7 m/s, and the overall pattern of atmospheric flow was completely reorganized compared to the fast-rotating planet.

The Physics Behind the Results

The experiment validated fundamental atmospheric physics in ways that textbooks can describe but simulations can actually demonstrate. The key mechanism at work is the Coriolis effect, where slower rotation creates a weaker Coriolis force, leading to less organized atmospheric circulation. This reduced circulation efficiency means less effective heat transport, resulting in more uniform temperatures as hot and cold regions don't mix as readily. The end result is completely different weather patterns, as different rotation rates fundamentally alter how the atmosphere moves and organizes itself.

This demonstrates why Earth's 24-hour rotation is crucial for our weather patterns and climate zones. The familiar patterns of trade winds, jet streams, and seasonal weather systems all depend on the precise balance of forces that comes from our planet's rotation rate.

Skills Demonstrated and Lessons Learned

This project required developing capabilities across multiple technical domains. The high-performance computing aspect involved compiling and executing complex scientific software in cloud-based environments, while the data processing component required analyzing binary climate data formats using Python and creating quality scientific visualizations. The version control work followed professional Git workflows with proper branching and comprehensive documentation, all while maintaining scientific rigor throughout the experimental process.

Beyond the technical implementation, the project deepened my understanding of climate science fundamentals. Working directly with model physics gave me insight into atmospheric circulation principles, while designing controlled experiments taught me how to isolate climate variables systematically. Interpreting complex atmospheric datasets and translating those results into accessible insights became an essential part of the scientific communication process.

Broader Implications for Climate Science

This project demonstrates several important points about climate science and its broader applications. First, it validates that climate models are trustworthy tools based on real, testable physics rather than speculation. The fact that my experimental results aligned perfectly with known atmospheric physics principles confirms that these models capture genuine physical processes rather than producing arbitrary outputs.

The experiment also illustrates how small changes can have dramatic effects in climate systems. A seemingly minor adjustment in rotation speed created profound atmospheric differences, which helps explain why climate scientists express concern about apparently small changes in greenhouse gas concentrations or other climate parameters. The sensitivity of the climate system to parameter changes isn't theoretical – it's mathematically demonstrable.

Perhaps most importantly, the project shows that climate science is increasingly accessible to broader participation. With modern cloud computing tools and open-source software, the technical barriers to engaging with real climate modeling have decreased significantly, opening opportunities for more people to contribute to climate understanding.

Conclusion: From Curiosity to Capability

What started as curiosity about climate modeling became a comprehensive demonstration of climate data analysis capabilities spanning both theoretical understanding and practical implementation skills. The project bridges academic knowledge with applied skills, showing how to work with professional climate modeling software, design and execute controlled climate experiments, analyze and visualize complex atmospheric data, and communicate scientific results effectively to diverse audiences.

Most importantly, it demonstrates that climate science is both accessible to determined learners and essential for understanding our planet's future. The combination of technical capability with genuine climate science understanding creates a foundation for contributing meaningfully to climate action and sustainability efforts.

Beyond Carbon: Why Critical Material Supply Chains Matter for a Truly Sustainable Future

Hey everyone! Super pumped to get this blog rolling, all about making energy transitions truly sustainable. We’re all jazzed about ditching fossil fuels, but have you ever stopped to think about what stuff goes into those sleek solar panels, massive wind turbines, and the EV batteries everyone’s raving about?

I’m talking about critical materials: lithium, cobalt, rare earth elements  – the unsung heroes of the clean energy revolution. They're absolutely essential, but here's the uncomfortable truth: extracting and processing these materials often comes with severe environmental and social costs that rarely make headlines.

This isn't just about water stress in mining regions (though that's significant). We're witnessing habitat destruction like the Atacama Desert's transformation into lithium extraction zones. We're confronting human rights issues, including labor conditions in the Democratic Republic of Congo's cobalt mines. And environmental contamination? Sulfuric acid, heavy metals, and other pollutants leach into ecosystems, poisoning waterways and devastating wildlife populations.

Region	Critical Material	Environmental & Social Impacts	Data Sources
Atacama Desert, Chile	Lithium	Water stress is impacting local agriculture and indigenous communities’ water access, habitat loss for flamingos and other unique species.	World Resources Institute Aqueduct Water Risk Atlas, UN Human Rights Office reports on water rights.
Democratic Republic of Congo	Cobalt	Water contamination is affecting drinking water and aquatic life, child labor in mines, and unsafe working conditions.	UNICEF reports on child labor, and Amnesty International reports on human rights abuses in cobalt mines.
Inner Mongolia, China	Rare Earth Elements	Desertification, air pollution from processing plants, and soil contamination from mining waste.	Reports from the Chinese Ministry of Ecology and Environment and academic studies on desertification in Inner Mongolia.

Here's what frustrates me: Most environmental assessments of these materials simply identify problems without connecting them to our renewable energy goals. That's precisely where my PhD research comes in! I'm developing models that combine genetic algorithms with multi-dimensional environmental impact analysis to optimize renewable deployment schedules, accounting for the entire critical material supply chain.

My goal is to ensure our clean energy future is actually clean, from mining to manufacturing to deployment. This isn't just environmental idealism (though environmental protection matters enormously). It's about building a circular economy where we recycle and reuse critical materials, creating new jobs and reducing extraction demands. It's about fair labor practices, ethical sourcing, and creating economic opportunities through responsible resource management. Think "Wakanda," but achievable in our lifetime.

I recently toured a solar manufacturing facility and was struck by the mind-boggling complexity of the supply chains involved. That visit crystallized my understanding that true sustainability extends far beyond carbon emissions – it encompasses human well-being, ecosystem health, and creating systems that benefit everyone involved.

So, what can you do to help?

• Support companies that demonstrate transparency: Look beyond marketing claims and support businesses that document ethical sourcing and labor practices with third-party verification

• Advocate for better policies: Contact representatives about legislation supporting responsible mining standards, circular economy initiatives, and extended producer responsibility

• Practice conscious consumption: Choose products designed for longevity, repairability, and end-of-life recyclability – and question whether each purchase is necessary

  
  

Every action matters, no matter how small. I'll be sharing regular updates on my research and analyzing industry developments. What sustainability issues concern you most? Share your thoughts in the comments! Together, we can make this clean energy transition something future generations will thank us for.