Articles | Volume 26, issue 9
https://doi.org/10.5194/acp-26-6449-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-26-6449-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Variability of ice supersaturated regions at flight altitudes: evaluation of ERA5 reanalysis using IAGOS in situ measurements
Katarina Grubbe Hildebrandt
CORRESPONDING AUTHOR
Faculty of Aerospace Engineering, Delft University of Technology, Delft, the Netherlands
Federica Castino
Faculty of Aerospace Engineering, Delft University of Technology, Delft, the Netherlands
Vincent Meijer
Faculty of Aerospace Engineering, Delft University of Technology, Delft, the Netherlands
Faculty of Aerospace Engineering, Delft University of Technology, Delft, the Netherlands
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Volker Grewe, Simon Blakey, Florian Linke, Sigrun Matthes, Jan Middel, Radu Mirea, Ayce Celikel, David Raper, Feijia Yin, and Xin Zhao
J. Env. Com. Air Transp. Sys., 1, 1, https://doi.org/10.5194/jecats-1-1-2026, https://doi.org/10.5194/jecats-1-1-2026, 2026
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The Journal of Environmentally Compatible Air Transport System (JECATS) is a not-for-profit international scientific journal dedicated to aspects of the air transport system with a focus on the environmental implications. JECATS combines areas of aerospace engineering, fuels, environmental analysis, climate change, economics, aviation climate mitigation, circularity and policy analysis. It includes aviation transport-related aspects and environmental effects from local to global scales.
Aaron Sarna, Vincent Meijer, Rémi Chevallier, Allie Duncan, Kyle McConnaughay, Scott Geraedts, and Kevin McCloskey
Atmos. Meas. Tech., 18, 3495–3532, https://doi.org/10.5194/amt-18-3495-2025, https://doi.org/10.5194/amt-18-3495-2025, 2025
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Contrails, the clouds formed by aircraft, are have a substantial climate impact. Determining which flight formed each contrail is a critical step to decreasing this impact. We introduce a dataset of synthetic contrail observations with known flight attributions that can be used to develop and assess geostationary-satellite-based contrail-to-flight attribution systems. We additionally introduce a new attribution algorithm and show that it outperforms previous methods.
Vincent R. Meijer, Sebastian D. Eastham, Ian A. Waitz, and Steven R. H. Barrett
Atmos. Meas. Tech., 17, 6145–6162, https://doi.org/10.5194/amt-17-6145-2024, https://doi.org/10.5194/amt-17-6145-2024, 2024
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Aviation's climate impact is partly due to contrails: the clouds that form behind aircraft and which can linger for hours under certain atmospheric conditions. Accurately forecasting these conditions could allow aircraft to avoid forming these contrails and thus reduce their environmental footprint. Our research uses deep learning to identify three-dimensional contrail locations in two-dimensional satellite imagery, which can be used to assess and improve these forecasts.
Federica Castino, Feijia Yin, Volker Grewe, Hiroshi Yamashita, Sigrun Matthes, Simone Dietmüller, Sabine Baumann, Manuel Soler, Abolfazl Simorgh, Maximilian Mendiguchia Meuser, Florian Linke, and Benjamin Lührs
Geosci. Model Dev., 17, 4031–4052, https://doi.org/10.5194/gmd-17-4031-2024, https://doi.org/10.5194/gmd-17-4031-2024, 2024
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We introduce SolFinder 1.0, a decision-making tool to select trade-offs between different objective functions for optimal aircraft trajectories, including fuel use, flight time, NOx emissions, contrail distance, and climate impact. The module is included in the AirTraf 3.0 submodel and uses weather conditions simulated by the EMAC atmospheric model. This paper focuses on the ability of SolFinder to identify eco-efficient trajectories, reducing a flight's climate impact at limited cost penalties.
Sigrun Matthes, Simone Dietmüller, Katrin Dahlmann, Christine Frömming, Patrick Peter, Hiroshi Yamashita, Volker Grewe, Feijia Yin, and Federica Castino
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-92, https://doi.org/10.5194/gmd-2023-92, 2023
Revised manuscript not accepted
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Aviation aims to reduce its climate effect by identifying alternative climate-optimized aircraft trajectories. Such routing strategies requires a dedicated meteorological service in order to inform on regions of the atmosphere where aviation non-CO2 emissions have a large climate effect, e.g. by contrail formation or nitrogen-oxide (NOx)-induced ozone formation. This study presents calibration factors for individual non-CO2 effects by comparing with the climate response model AirClim.
Simone Dietmüller, Sigrun Matthes, Katrin Dahlmann, Hiroshi Yamashita, Abolfazl Simorgh, Manuel Soler, Florian Linke, Benjamin Lührs, Maximilian M. Meuser, Christian Weder, Volker Grewe, Feijia Yin, and Federica Castino
Geosci. Model Dev., 16, 4405–4425, https://doi.org/10.5194/gmd-16-4405-2023, https://doi.org/10.5194/gmd-16-4405-2023, 2023
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Climate-optimized aircraft trajectories avoid atmospheric regions with a large climate impact due to aviation emissions. This requires spatially and temporally resolved information on aviation's climate impact. We propose using algorithmic climate change functions (aCCFs) for CO2 and non-CO2 effects (ozone, methane, water vapor, contrail cirrus). Merged aCCFs combine individual aCCFs by assuming aircraft-specific parameters and climate metrics. Technically this is done with a Python library.
Abolfazl Simorgh, Manuel Soler, Daniel González-Arribas, Florian Linke, Benjamin Lührs, Maximilian M. Meuser, Simone Dietmüller, Sigrun Matthes, Hiroshi Yamashita, Feijia Yin, Federica Castino, Volker Grewe, and Sabine Baumann
Geosci. Model Dev., 16, 3723–3748, https://doi.org/10.5194/gmd-16-3723-2023, https://doi.org/10.5194/gmd-16-3723-2023, 2023
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This paper addresses the robust climate optimal trajectory planning problem under uncertain meteorological conditions within the structured airspace. Based on the optimization methodology, a Python library has been developed, which can be accessed using the following DOI: https://doi.org/10.5281/zenodo.7121862. The developed tool is capable of providing robust trajectories taking into account all probable realizations of meteorological conditions provided by an EPS computationally very fast.
Feijia Yin, Volker Grewe, Federica Castino, Pratik Rao, Sigrun Matthes, Katrin Dahlmann, Simone Dietmüller, Christine Frömming, Hiroshi Yamashita, Patrick Peter, Emma Klingaman, Keith P. Shine, Benjamin Lührs, and Florian Linke
Geosci. Model Dev., 16, 3313–3334, https://doi.org/10.5194/gmd-16-3313-2023, https://doi.org/10.5194/gmd-16-3313-2023, 2023
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This paper describes a newly developed submodel ACCF V1.0 based on the MESSy 2.53.0 infrastructure. The ACCF V1.0 is based on the prototype algorithmic climate change functions (aCCFs) v1.0 to enable climate-optimized flight trajectories. One highlight of this paper is that we describe a consistent full set of aCCFs formulas with respect to fuel scenario and metrics. We demonstrate the usage of the ACCF submodel using AirTraf V2.0 to optimize trajectories for cost and climate impact.
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We evaluate the regional and seasonal variability in the prediction of ice supersaturated region (ISSRS) in the ERA5 reanalysis using in situ measurements. ERA5 shows better ability to predict ISSRs in the extratropics, compared to the tropics, and in colder seasons, such as extratropical winter. While ERA5 generally underestimates the ISSR occurrence, we find an overestimation in tropical regions in seasons associated larger weather variability, such as South Asia in June, July and August.
We evaluate the regional and seasonal variability in the prediction of ice supersaturated region...
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