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Deploying a Django Website as a confused Earth Science programmer
Published:
Deploying a Django website is hard, especially if you don’t know anything about linux, web servers, or front-end/back-end. In my case of setting up a website for a lake research project, it was impossible. Thankfully, leveraging a couple of very cool tutorials and taking shameless advantage of AWS free tier (which can then be transitioned to a free/cheap non-profit account cuz research is non-profit), we can deploy a Django website in HTTP! HTTPS - which has an extra S - has security, so you need to buy a domain (not free!) and get a free security certificate from something like Let’s Encrypt - a company!
projects
Sub-Merged Conflicts
In this co-op deep-sea adventure game, you are part of a team of underwater explorers on a mission to find the treasure! Navigate through treacherous currents, encounter dangerous creatures, and use your teamwork skills to keep your submarine safe and strike gold! 
Global Lake Hydrology Explorer
Global Lake Hydrology Explorer will be a tool for visualizing lake data worldwide using global precipitation, evaporation, and runoff data. Theoretically, it allows users to select any lake and obtain a snapshot of its water balance. The tool will hopefully be easy to add to and can be used for watershed modeling or water resource management. 
Mono Lake Water Balance Model
Data, Model, and Visualization for the Large Lake Statistical Water Balance Model (L2SWBM) fit to the terminal lake, Mono Lake. 
Apostle Islands Ice Cover Model
Repository housing the code and data used to develop the Apostle Islands Ice Cover Model (APIM), featured in this research paper. 
CrocoDash
| A Python software package for setting up regional MOM6 (Modular Ocean Model 6) configurations within the Community Earth System Model (CESM). Developed at NCAR to streamline regional ocean modeling workflows for climate research. Docs | DOI: 10.5281/zenodo.17342302 |
publications
Combining Satellite, Teleconnection, and In Situ Data to Improve Understanding of Multi-Decadal Coastal Ice Cover Dynamics on Earth’s Largest Freshwater Lake
Published in Earth and Space Science, 2024
To differentiate and understand drivers behind coastal ice cover trends and variability, we advance development of a model combining satellite, in situ, and teleconnection data along the shoreline of Earth’s largest freshwater lake (Lake Superior).
Recommended citation: Venumuddula, M., Kirchner, K., Chen, A., Rood, R. B., & Gronewold, A. D. (2024). Combining satellite, teleconnection, and in situ data to improve understanding of multi-decadal coastal ice cover dynamics on Earth's largest freshwater lake. Earth and Space Science, 11, e2024EA003845. https://doi.org/10.1029/2024EA003845
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Differentiating Diversions and Drought to Understand Drivers of Water Loss from a North American Terminal Lake
Published in Journal of Water Resources Planning and Management, 2025
A reconstruction of the water balance of Mono Lake, a North American terminal lake, to disentangle the drivers of water loss between human water diversions and drought.
Recommended citation: Gossard, A., Venumuddula, M., VanDeWeghe, A., Wegener, C., & Gronewold, A. D. (2025). Differentiating diversions and drought to understand drivers of water loss from a North American terminal lake. Journal of Water Resources Planning and Management. https://doi.org/10.1061/JWRMD5.WRENG-6782
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CrocoDash: A Software Package for Setting Up Regional MOM6 in CESM
Published in Zenodo, 2025
CrocoDash is a Python software package that streamlines the configuration of regional MOM6 (Modular Ocean Model 6) within the Community Earth System Model (CESM).
Recommended citation: Venumuddula, M., Altuntas, A., Levy, M., Janney, A., Kwong, A., & Hung, N. (2025). CrocoDash (v0.1.0-beta). Zenodo. https://doi.org/10.5281/zenodo.17342302
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visualCaseGen: An SMT-based Experiment Configurator for Community Earth System Model
Published in Journal of Open Source Software, 2026
visualCaseGen is a Python/Jupyter-based tool using SMT constraint solvers to guide users through configuring CESM model experiments, reducing setup errors and lowering the barrier to running climate simulations.
Recommended citation: Altuntas, A., Simpson, I. R., Bachman, S. D., Venumuddula, M., Levis, S., Dobbins, B., Sacks, W. J., & Danabasoglu, G. (2026). visualCaseGen: An SMT-based experiment configurator for Community Earth System Model. Journal of Open Source Software. https://doi.org/10.21105/joss.09130
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