Preprints
https://doi.org/10.5194/egusphere-2026-1115
https://doi.org/10.5194/egusphere-2026-1115
04 May 2026
 | 04 May 2026

AQUA v1: The Application for QUality Assessment for the Climate Change Adaptation Digital Twin

Matteo Nurisso, Jost von Hardenberg, Marco Cadau, Silvia Caprioli, Paolo Ghinassi, Supriyo Ghosh, Nikolay Koldunov, Natalia Nazarova, Maqsood Mubarak Rajput, Emanuele Tovazzi, and Paolo Davini

Abstract. The increasing availability of kilometer-scale climate simulations presents major challenges for data access, processing, and analysis due to the unprecedented volume and heterogeneity of the outputs. Different data formats, structures, and metadata conventions, require dedicated solutions to ensure interoperability and usability. We introduce AQUA (Application for QUality Assessment), a Python-based framework developed within the Climate Change Adaptation Digital Twin of the Destination Earth (DestinE) initiative, designed to support the automated evaluation of high-resolution global climate simulations. Although several diagnostic suites for the analysis of global climate model data are already available, AQUA provides a flexible and modular infrastructure for accessing and processing climate model output across various formats. By building on widely adopted Python libraries, it enables scalable, out-of-core computations. Its design supports integration into automated workflows and user-defined pipelines, facilitating both operational and research-oriented applications. This paper focuses on the architecture and core functionalities of the AQUA core, which handles data ingestion, standardization, and pre-processing. AQUA is open source and actively maintained, and aims to serve as a community tool for robust, reproducible, and efficient climate data analysis across projects and institutions.

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Journal article(s) based on this preprint

20 Aug 2026
AQUA v1.0.0: The Application for QUality Assessment for the Climate Change Adaptation Digital Twin – the core engine
Matteo Nurisso, Jost von Hardenberg, Marco Cadau, Silvia Caprioli, Paolo Ghinassi, Supriyo Ghosh, Nikolay Koldunov, Natalia Nazarova, Maqsood Mubarak Rajput, Emanuele Tovazzi, and Paolo Davini
Geosci. Model Dev., 19, 7725–7740, https://doi.org/10.5194/gmd-19-7725-2026,https://doi.org/10.5194/gmd-19-7725-2026, 2026
Short summary
Matteo Nurisso, Jost von Hardenberg, Marco Cadau, Silvia Caprioli, Paolo Ghinassi, Supriyo Ghosh, Nikolay Koldunov, Natalia Nazarova, Maqsood Mubarak Rajput, Emanuele Tovazzi, and Paolo Davini

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Review of the manuscript “AQUA v1: The Application for QUality Assessment for the Climate Change Adaptation Digital Twin”', Anonymous Referee #1, 12 Jun 2026
    • AC1: 'Reply on RC1', Matteo Nurisso, 27 Jul 2026
  • RC2: 'Comment on egusphere-2026-1115', Anonymous Referee #2, 15 Jun 2026
    • AC2: 'Reply on RC2', Matteo Nurisso, 27 Jul 2026

Peer review completion

AR – Author's response | RR – Referee report | ED – Editor decision | EF – Editorial file upload
AR by Matteo Nurisso on behalf of the Authors (31 Jul 2026)  Author's response   Author's tracked changes   Manuscript 
ED: Reconsider after major revisions (03 Aug 2026) by Martina Stockhause
ED: Publish subject to technical corrections (07 Aug 2026) by Martina Stockhause
AR by Matteo Nurisso on behalf of the Authors (13 Aug 2026)  Author's response   Manuscript 

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Review of the manuscript “AQUA v1: The Application for QUality Assessment for the Climate Change Adaptation Digital Twin”', Anonymous Referee #1, 12 Jun 2026
    • AC1: 'Reply on RC1', Matteo Nurisso, 27 Jul 2026
  • RC2: 'Comment on egusphere-2026-1115', Anonymous Referee #2, 15 Jun 2026
    • AC2: 'Reply on RC2', Matteo Nurisso, 27 Jul 2026

Peer review completion

AR – Author's response | RR – Referee report | ED – Editor decision | EF – Editorial file upload
AR by Matteo Nurisso on behalf of the Authors (31 Jul 2026)  Author's response   Author's tracked changes   Manuscript 
ED: Reconsider after major revisions (03 Aug 2026) by Martina Stockhause
ED: Publish subject to technical corrections (07 Aug 2026) by Martina Stockhause
AR by Matteo Nurisso on behalf of the Authors (13 Aug 2026)  Author's response   Manuscript 

Journal article(s) based on this preprint

20 Aug 2026
AQUA v1.0.0: The Application for QUality Assessment for the Climate Change Adaptation Digital Twin – the core engine
Matteo Nurisso, Jost von Hardenberg, Marco Cadau, Silvia Caprioli, Paolo Ghinassi, Supriyo Ghosh, Nikolay Koldunov, Natalia Nazarova, Maqsood Mubarak Rajput, Emanuele Tovazzi, and Paolo Davini
Geosci. Model Dev., 19, 7725–7740, https://doi.org/10.5194/gmd-19-7725-2026,https://doi.org/10.5194/gmd-19-7725-2026, 2026
Short summary
Matteo Nurisso, Jost von Hardenberg, Marco Cadau, Silvia Caprioli, Paolo Ghinassi, Supriyo Ghosh, Nikolay Koldunov, Natalia Nazarova, Maqsood Mubarak Rajput, Emanuele Tovazzi, and Paolo Davini

Model code and software

AQUA Matteo Nurisso, Silvia Caprioli, Paolo Davini, Jost von Hardenberg, Natalia Nazarova, Supriyo Ghosh, Paolo Ghinassi, Marco Cadau, Emanuele Tovazzi, Nikolay Koldunov, Maqsood Mubarak Rajput, and Bruno Kinoshita https://doi.org/10.5281/zenodo.14906075

Interactive computing environment

high_res_data_access Matteo Nurisso https://github.com/koldunovn/high_res_data_access

Matteo Nurisso, Jost von Hardenberg, Marco Cadau, Silvia Caprioli, Paolo Ghinassi, Supriyo Ghosh, Nikolay Koldunov, Natalia Nazarova, Maqsood Mubarak Rajput, Emanuele Tovazzi, and Paolo Davini

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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.

Short summary
We present a new open-source software called AQUA designed to handle and evaluate the vast amounts of data produced by high-resolution climate simulations. As climate models become more detailed, their output can become too large and complex for traditional analysis methods. We introduce a new framework for data access, processing, and comparison that is fast, reliable, and easy to automate. Our results show that it can efficiently manage very large datasets and support real-time quality checks.
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