Advancing Methodological Consistency in CLEWs Modelling: Introducing the Model Development Infrastructure

28 August 2025, Version 1
This content is an early or alternative research output and has not been peer-reviewed by Cambridge University Press at the time of posting.

Abstract

Climate change mitigation, resource security, and economic development are central priorities in global policymaking. Addressing these interconnected challenges requires integrated modelling approaches that capture the interactions between climate, land, energy, and water (CLEWs) systems. While the CLEWs framework provides a structured basis for such analysis, building models from scratch remains time-consuming and error-prone. Recent standardisation initiatives have improved efficiency but remain limited in scope and flexibility. This paper introduces the Model Development Infrastructure (MDI), a modular, Excel-based toolkit that streamlines the creation of CLEWs++ models – an extended version of the CLEWs framework that broadens sectoral coverage to capture nearly all greenhouse gas emissions. The MDI combines pre-loaded global datasets with user-supplied local information, enabling model development for any country while allowing customisation of scope and sectoral detail. Its components guide users through a structured workflow, from base-year calibration to model-ready input data optimised for the Open Source Energy Modelling System (OSeMOSYS). Key features include wide sectoral coverage, adjustable model boundaries, accessibility for non-programmers, and a modular architecture that supports maintenance and future enhancements. Although there is space for future improvements in scalability and data integration, the MDI bridges methodological gaps in previous standardisation efforts, lowers entry barriers, improves reproducibility, and supports more comprehensive CLEWs-based policy analysis.

Keywords

Model standardisation
CLEWs
CLEWS++
MUIO
Model Development Infrastructure (MDI)
OSeMOSYS
Energy modelling

Supplementary weblinks

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Comment number 1, Vladislav Kuchumov: Dec 07, 2025, 18:37

I have a few questions and suggestions for the authors: Interoperability: You mention that MDI outputs are optimized for MUIO/OSeMOSYS. Could you elaborate on the feasibility and effort required to adapt the structured data for other modelling platforms (e.g., TIMES, LEAP)? Are there plans to develop export modules for other formats? Data Quality and Uncertainty: While pre-loaded global datasets provide a great starting point, how does the MDI guide or alert users to the potential uncertainties when default values are used for critical local parameters (e.g., technology costs, demand growth rates)? Including a section on uncertainty communication in the instructions could enhance reproducibility. Scalability Concerns: You rightly note that Excel may strain with very large-scale applications. Have you considered or prototyped a lightweight database backend (e.g., SQLite) for users who might eventually scale to multi-region or high-temporal-resolution models? A minor suggestion: a brief case study or a link to an example of a national model built using MDI in the Zenodo repository would greatly help new users visualize the workflow and outputs. Overall, MDI seems like a pragmatic and much-needed tool that could accelerate robust CLEWs analyses. I look forward to seeing its adoption and future development, especially regarding automation and expanded dataset libraries.