Our latest study, “Feasibility of integrating multiple climate impact estimation models to enhance confidence in environmentally-friendly aircraft trajectory optimization,” has been published in Transportation Research Interdisciplinary Perspectives.
In this work, Abolfazl Simorgh proposes a robust approach to enhance the reliability of climate-optimized flight planning by simultaneously accounting for two key sources of uncertainty:
1. Weather forecast uncertainty, characterized using an ensemble prediction system, and
2. Discrepancies between two climate impact estimation models compatible with flight planning: algorithmic Climate Change Functions (aCCFs) and the gridded Contrail Cirrus Prediction (CoCiP) model.
✅ The objective of this study is to generate flight plans that provide consistent climate benefits across both models, even under meteorological uncertainty.
Feasibility of integrating multiple climate impact estimation models to enhance confidence in environmentally-friendly aircraft trajectory optimization. Abolfazl Simorh, Manuel Soler. Transportation Research Interdisciplinary Perspectives, Volume 34, November 2025, 101692https://doi.org/10.1016/j.trip.2025.101692
Abstract
Contrail cirrus is a major contributor to aviation-induced climate impact, with its formation and radiative effects highly sensitive to atmospheric conditions. This underscores the potential of contrail-informed flight planning to mitigate the corresponding climate effects. However, uncertainties in forecasting persistent contrail-forming areas and their radiative impact pose challenges to the effectiveness of this mitigation measure. In this study, we present a robust approach to enhance the reliability of climate-optimized flight planning by simultaneously accounting for two key sources of uncertainty: (1) weather forecast uncertainty, characterized using an ensemble prediction system, and (2) discrepancies between two state-of-the-art climate impact estimation models suitable for flight planning: algorithmic Climate Change Functions (aCCFs) and the gridded Contrail Cirrus Prediction (CoCiP) model. The objective is to generate flight plans that provide consistent climate benefits across both models, even under meteorological uncertainty. The proposed flight planning problem is formulated considering structured airspace and designed for parallel execution, ensuring its practicality, high computational efficiency, and scalability, accommodating multiple climate impact estimation models and weather data sources without compromising performance. Case studies demonstrate the practical viability of the approach for flight dispatchers, increasing confidence in climate-optimized trajectories even in the presence of significant model disagreements.