Research towards weather induced uncertainties for contrail persistence and mitigation strategies for contrail impact
Better Contrail Mitigation (BeCoM)
F. Yin (TU Delft - Aircraft Noise and Climate Effects)
V. Grewe (TU Delft - Aircraft Noise and Climate Effects)
K. Gierens (Deutsches Zentrum für Luft- und Raumfahrt (DLR))
F. Linke (Deutsches Zentrum für Luft- und Raumfahrt (DLR))
Alexander Lau (Deutsches Zentrum für Luft- und Raumfahrt (DLR))
Malte Niklaβ (Deutsches Zentrum für Luft- und Raumfahrt (DLR))
Roland Potthast (German Weather Forecast (DWD))
Bjoen Beckmann (German Weather Forecast (DWD))
Phillippe Keckhut (Centre National de la Recherche Scientifique (CNRS))
undefined More Authors (External organisation)
More Info
expand_more
Abstract
Aviation contributes to about 3.5% of the total anthropogenic climate change when including non-CO2 effects, e.g., contrail formation and the impact of NOx emissions on ozone and methane. Among various non-CO2 effects, the contrail-cirrus radiative forcing is the largest (~2/3) with large uncertainties. The most critical affecting factor is the huge weather-induced variability of the radiative impact of individual contrails, which imposes challenges on formulating adequate mitigation measures and develop policy-driven implementation schemes, stressing relevance of reliable forecasts.
The newly funded EU project BeCoM intends to address the uncertainties related to the forecasting of persistent contrails and their weather-dependent individual radiative effects. The project will focus on: 1) obtaining a larger and higher resolution database of relative humidity and ice supersaturation at cruise levels for assimilation into numerical weather prediction (NWP) models; 2) providing more adequate representation of ice clouds in their supersaturated environment in the NWP models; and 3) validation of the predictions to determine and reduce the remaining uncertainties of contrail forecasts. To facilitate the assimilation and validation process, a novel hybrid artificial intelligence algorithm will be developed. Based on the contrail prediction, the project will develop a policy framework for effective contrail avoidance through a trajectory optimization approach. The results will enable a better understanding of contrail’s climate impact and formulate recommendations on how to implement strategies to enable air traffic management to reduce aviation's climate impact.
No files available
Metadata only record. There are no files for this record.