Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 18, issue 1
Articles | Volume 18, issue 1
https://doi.org/10.5194/gmd-18-181-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-18-181-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 18, issue 1
Methods for assessment of models
 | 
16 Jan 2025
Methods for assessment of models |  | 16 Jan 2025

Virtual Integration of Satellite and In-situ Observation Networks (VISION) v1.0: In-Situ Observations Simulator (ISO_simulator)

Maria R. Russo, Sadie L. Bartholomew, David Hassell, Alex M. Mason, Erica Neininger, A. James Perman, David A. J. Sproson, Duncan Watson-Parris, and Nathan Luke Abraham

Data sets

UKESM1 hourly modelled ozone for comparison to observations N. L. Abraham and M. R. Russo https://catalogue.ceda.ac.uk/uuid/300046500aeb4af080337ff86ae8e776

Continuous Cape Verde Atmospheric Observatory Observations L. J. Carpenter et al. https://catalogue.ceda.ac.uk/uuid/81693aad69409100b1b9a247b9ae75d5

FAAM ozone dataset 2010 to 2020. NERC EDS Centre for Environmental Data Analysis M. R. Russo, N. L. Abraham, and FAAM Airborne Laboratory https://catalogue.ceda.ac.uk/uuid/8df2e81dbfc2499983aa87781fb3fd5a

ATom: Merged Atmospheric Chemistry, Trace Gases, and Aerosols, Version 2 S. C. Wofsy et al. https://doi.org/10.3334/ORNLDAAC/1925

VISION: Collated subset of FAAM ozone data 2010 to 2020 Facility for Airborne Atmospheric Measurements et al. https://catalogue.ceda.ac.uk/uuid/8df2e81dbfc2499983aa87781fb3fd5a/

Model code and software

NCAS-VISION/VISION-toolkit: 1.0 M. R. Russo and S. L. Bartholomew https://doi.org/10.5281/ZENODO.10927302

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Short summary
Observational data and modelling capabilities have expanded in recent years, but there are still barriers preventing these two data sources from being used in synergy. Proper comparison requires generating, storing, and handling a large amount of data. This work describes the first step in the development of a new set of software tools, the VISION toolkit, which can enable the easy and efficient integration of observational and model data required for model evaluation.

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