Virtual Integration of Satellite and In-situ Observation Networks (VISION) v1.0: In-Situ Observations Simulator (ISO_simulator)
<p>This work presents the first step in the development of the VISION toolkit, a set of Python tools that allows easy, efficient, and more meaningful comparison between global atmospheric models and observational data. Whilst observational data and modelling capabilities are expanding in paral...
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Copernicus Publications
2025-01-01
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| Series: | Geoscientific Model Development |
| Online Access: | https://gmd.copernicus.org/articles/18/181/2025/gmd-18-181-2025.pdf |
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| author | M. R. Russo M. R. Russo S. L. Bartholomew S. L. Bartholomew D. Hassell D. Hassell A. M. Mason E. Neininger A. J. Perman D. A. J. Sproson D. Watson-Parris D. Watson-Parris N. L. Abraham N. L. Abraham |
| author_facet | M. R. Russo M. R. Russo S. L. Bartholomew S. L. Bartholomew D. Hassell D. Hassell A. M. Mason E. Neininger A. J. Perman D. A. J. Sproson D. Watson-Parris D. Watson-Parris N. L. Abraham N. L. Abraham |
| author_sort | M. R. Russo |
| collection | DOAJ |
| description | <p>This work presents the first step in the development of the VISION toolkit, a set of Python tools that allows easy, efficient, and more meaningful comparison between global atmospheric models and observational data. Whilst observational data and modelling capabilities are expanding in parallel, there are still barriers preventing these two data sources from being used in synergy. This arises from differences in spatial and temporal sampling between models and observational platforms: observational data from a research aircraft, for example, are sampled on specified flight trajectories at very high temporal resolution. Proper comparison with model data requires generating, storing, and handling a large number of highly temporally resolved model files, resulting in a process which is data-, labour-, and time-intensive. In this paper we focus on comparison between model data and in situ observations (from aircraft, ships, buoys, sondes, etc.). A standalone code, In-Situ Observations Simulator, or ISO_simulator for short, is described here: this software reads modelled variables and observational data files and outputs model data interpolated in space and time to match observations. These model data are then written to NetCDF files that can be efficiently archived due to their small sizes and directly compared to observations. This method achieves a large reduction in the size of model data being produced for comparison with flight and other in situ data. By interpolating global gridded hourly files onto observation locations, we reduce data output for a typical climate resolution run, from <span class="inline-formula">∼3</span> Gb per model variable per month to <span class="inline-formula">∼15</span> Mb per model variable per month (a 200-times reduction in data volume). The VISION toolkit is relatively fast to run and can be automated to process large volumes of data at once, allowing efficient data analysis over a large number of years. Although this code was initially tested within the Unified Model (UM) framework, which is shared by the UK Earth System Model (UKESM), it was written as a flexible tool and it can be extended to work with other models.</p> |
| format | Article |
| id | doaj-art-fb798403d5a946fb91e49ecd341cfdc8 |
| institution | Kabale University |
| issn | 1991-959X 1991-9603 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Copernicus Publications |
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| series | Geoscientific Model Development |
| spelling | doaj-art-fb798403d5a946fb91e49ecd341cfdc82025-01-16T08:56:28ZengCopernicus PublicationsGeoscientific Model Development1991-959X1991-96032025-01-011818119110.5194/gmd-18-181-2025Virtual Integration of Satellite and In-situ Observation Networks (VISION) v1.0: In-Situ Observations Simulator (ISO_simulator)M. R. Russo0M. R. Russo1S. L. Bartholomew2S. L. Bartholomew3D. Hassell4D. Hassell5A. M. Mason6E. Neininger7A. J. Perman8D. A. J. Sproson9D. Watson-Parris10D. Watson-Parris11N. L. Abraham12N. L. Abraham13National Centre for Atmospheric Science, Cambridge, UKYusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, UKNational Centre for Atmospheric Science, Reading, UKDepartment of Meteorology, University of Reading, Reading, UKNational Centre for Atmospheric Science, Reading, UKDepartment of Meteorology, University of Reading, Reading, UKYusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, UKMet Office, Exeter, UKYusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, UKFAAM Airborne Laboratory, National Centre for Atmospheric Science, University of Leeds, Leeds, UKScripps Institution of Oceanography, University of California San Diego, San Diego, USAHalıcıoğlu Data Science Institute, University of California San Diego, San Diego, USANational Centre for Atmospheric Science, Cambridge, UKYusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, UK<p>This work presents the first step in the development of the VISION toolkit, a set of Python tools that allows easy, efficient, and more meaningful comparison between global atmospheric models and observational data. Whilst observational data and modelling capabilities are expanding in parallel, there are still barriers preventing these two data sources from being used in synergy. This arises from differences in spatial and temporal sampling between models and observational platforms: observational data from a research aircraft, for example, are sampled on specified flight trajectories at very high temporal resolution. Proper comparison with model data requires generating, storing, and handling a large number of highly temporally resolved model files, resulting in a process which is data-, labour-, and time-intensive. In this paper we focus on comparison between model data and in situ observations (from aircraft, ships, buoys, sondes, etc.). A standalone code, In-Situ Observations Simulator, or ISO_simulator for short, is described here: this software reads modelled variables and observational data files and outputs model data interpolated in space and time to match observations. These model data are then written to NetCDF files that can be efficiently archived due to their small sizes and directly compared to observations. This method achieves a large reduction in the size of model data being produced for comparison with flight and other in situ data. By interpolating global gridded hourly files onto observation locations, we reduce data output for a typical climate resolution run, from <span class="inline-formula">∼3</span> Gb per model variable per month to <span class="inline-formula">∼15</span> Mb per model variable per month (a 200-times reduction in data volume). The VISION toolkit is relatively fast to run and can be automated to process large volumes of data at once, allowing efficient data analysis over a large number of years. Although this code was initially tested within the Unified Model (UM) framework, which is shared by the UK Earth System Model (UKESM), it was written as a flexible tool and it can be extended to work with other models.</p>https://gmd.copernicus.org/articles/18/181/2025/gmd-18-181-2025.pdf |
| spellingShingle | M. R. Russo M. R. Russo S. L. Bartholomew S. L. Bartholomew D. Hassell D. Hassell A. M. Mason E. Neininger A. J. Perman D. A. J. Sproson D. Watson-Parris D. Watson-Parris N. L. Abraham N. L. Abraham Virtual Integration of Satellite and In-situ Observation Networks (VISION) v1.0: In-Situ Observations Simulator (ISO_simulator) Geoscientific Model Development |
| title | Virtual Integration of Satellite and In-situ Observation Networks (VISION) v1.0: In-Situ Observations Simulator (ISO_simulator) |
| title_full | Virtual Integration of Satellite and In-situ Observation Networks (VISION) v1.0: In-Situ Observations Simulator (ISO_simulator) |
| title_fullStr | Virtual Integration of Satellite and In-situ Observation Networks (VISION) v1.0: In-Situ Observations Simulator (ISO_simulator) |
| title_full_unstemmed | Virtual Integration of Satellite and In-situ Observation Networks (VISION) v1.0: In-Situ Observations Simulator (ISO_simulator) |
| title_short | Virtual Integration of Satellite and In-situ Observation Networks (VISION) v1.0: In-Situ Observations Simulator (ISO_simulator) |
| title_sort | virtual integration of satellite and in situ observation networks vision v1 0 in situ observations simulator iso simulator |
| url | https://gmd.copernicus.org/articles/18/181/2025/gmd-18-181-2025.pdf |
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