Photonsphere Lab is the computational and open-science layer of Photonsphere, bringing together code, data-processing workflows, methodological implementations, and reusable scientific resources developed through my research.
Its purpose is not only to make research outputs accessible, but also to preserve the reasoning and procedures behind them; how observations are processed and quality controlled, how methods are implemented and tested, and how analyses can be reproduced, scrutinised, and extended.
Photonsphere Lab is a developing resource. Materials will be added progressively as methods mature and can be documented in a form that is useful beyond the individual study in which they were created.
What lives in Photonsphere Lab
Scientific methods
Implementations of physically based, statistical, and data-driven methodologies developed or applied in environmental research.
Data workflows
Quality control, harmonisation, processing, validation, and analysis of atmospheric and environmental observations.
Computational tools
Reusable scripts, functions, modelling utilities, and research software developed to support scientific analysis.
Reproducible resources
Documentation, examples, figures, and workflows intended to make analyses transparent, testable, and reusable.
Methods & workflows
Photonsphere Lab develops alongside active research. Methods, scripts, and workflows often begin as tools created to solve a specific scientific problem and are progressively refined, tested, documented, and generalised when they become useful beyond the original study.
The emphasis is on retaining the connection between the scientific question, the underlying assumptions, the data-processing choices, and the resulting implementation.
1. Scientific question
Identify the physical or environmental problem and the information required to address it.
2. Method development
Translate the scientific reasoning into equations, algorithms, processing steps, or modelling approaches.
3. Testing & validation
Evaluate behaviour against observations, independent data, alternative methods, or physically expected limits.
4. Reusable implementation
Document and organise mature components so that they can be reproduced, inspected, and adapted to other applications.
Not every experimental method or research script becomes a public resource; the aim is to release material when its scientific purpose, assumptions, and use can be documented clearly.
Code & Tools
Code in Photonsphere Lab is treated as part of the scientific methodology rather than only as a means of producing results. Reusable components are developed to make data processing, analysis, modelling, and validation more transparent and easier to reproduce across studies.
Resources range from small scientific utilities and analysis functions to more complete processing workflows. Wherever possible, code is accompanied by enough documentation to clarify its scientific purpose, required inputs, assumptions, and expected outputs.
Scientific utilities
Reusable functions and scripts for calculations, transformations, physical quantities, statistical analysis, and other recurring scientific tasks.
Data processing & quality control
Tools for importing, screening, harmonising, filtering, and preparing environmental observations from different instruments, sites, and data sources.
Analysis & model evaluation
Computational resources for fitting methods, validation, uncertainty analysis, model–observation comparison, and quantitative assessment of environmental datasets.
Research workflows
Scripts and structured workflows that connect individual processing and analysis steps into reproducible research pipelines, including workflows designed for larger datasets and computational environments.
Tools are released progressively as they become sufficiently general, documented, and stable for use beyond the research project in which they originated.
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Open Science
Open science in Photonsphere Lab means making scientific work easier to inspect, reproduce, reuse, and build upon. Wherever possible, research developed within Photonsphere Lab is based on openly accessible data and produces outputs that can be shared openly, while recognising that licences, third-party ownership, ethical considerations, or other restrictions may sometimes limit access.
Transparency
Document the assumptions, processing decisions, methodological choices, and data sources that shape an analysis.
Open data & resources
Prefer openly available datasets and release derived data, code, workflows, and supporting resources whenever licensing and other conditions allow.
Reproducibility & reusability
Provide the computational steps and documentation needed to reproduce results and adapt mature methods to new datasets, sites, or research questions.
Open publications
Publish research open access whenever possible. When a journal publication is not immediately open, make an appropriate version available through institutional or disciplinary repositories whenever publisher policies permit.
Openness is most useful when access is accompanied by enough context to understand how a result was produced, what assumptions it depends on, and where its limitations lie.
Projects & repositories
Photonsphere Lab repositories connect research questions with the code, workflows, documentation, and supporting resources developed around them. Some repositories correspond directly to individual studies, while others contain methods or utilities designed for reuse across different projects.
The catalogue will expand progressively as ongoing research reaches a stage at which its computational components can be documented and released independently.
Repositories in development
Computational resources associated with current Photonsphere research are being prepared for release. Repositories will appear here as documentation, licensing, and reproducibility checks are completed.
Explore Photonsphere Lab repositories