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001032065 037__ $$aFZJ-2024-05969
001032065 1001_ $$0P:(DE-HGF)0$$aPlatt, John$$b0
001032065 245__ $$aThe effect of uncertainty in humidity and model parameters on the prediction of contrail energy forcing
001032065 260__ $$bZenodo$$c2024
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001032065 520__ $$aPrevious work has shown that while the net effect of aircraft condensation trails (contrails) on theclimate is warming, the exact magnitude of the energy forcing per meter of contrail remains uncertain.In this paper, we explore the skill of a Lagrangian contrail model (CoCiP) in identifying flightsegments with high contrail energy forcing. We find that skill is greater than climatologicalpredictions alone, even accounting for uncertainty in weather fields and model parameters. We estimate the uncertainty in weather by using the ensemble ERA5 weather reanalysis from the EuropeanCentre for Medium-Range Weather Forecasts (ECMWF) as Monte Carlo inputs to CoCiP. We unbias and correctunder-dispersion on the ERA5 humidity data by forcing a match to the distribution of in situ humiditymeasurements taken at cruising altitude. We set aside CoCiP energy forcing estimates calculated usingone of the ensemble members as a proxy for ground truth, and report the skill of CoCiP in identifyingsegments with large positive proxy energy forcing. We further estimate the uncertainty in the modelparameters in CoCiP by performing Monte Carlo simulations with CoCiP model parameters drawn fromuncertainty distributions consistent with the literature. When CoCiP outputs are averaged over seasons to form climatological predictions, the skill inpredicting the proxy is 44%, while the skill of per-flight CoCiP outputs is 84%. If these results carryover to the true (unknown) contrail EF, they indicate that per-flight energy forcing predictions canreduce the number of potential contrail avoidance route adjustments by 2x, hence reducing both the costand fuel impact of contrail avoidance.
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001032065 7001_ $$00000-0003-0864-6394$$aShapiro, Marc$$b1
001032065 7001_ $$0P:(DE-HGF)0$$aEngberg, Zeb$$b2
001032065 7001_ $$0P:(DE-HGF)0$$aMcCloskey, Kevin$$b3
001032065 7001_ $$0P:(DE-HGF)0$$aGeraedts, Scott$$b4
001032065 7001_ $$0P:(DE-HGF)0$$aSankar, Tharun$$b5
001032065 7001_ $$00000-0002-2066-9380$$aStettler, Marc$$b6
001032065 7001_ $$0P:(DE-HGF)0$$aTeoh, Roger$$b7
001032065 7001_ $$0P:(DE-HGF)0$$aSchumann, Ulrich$$b8
001032065 7001_ $$0P:(DE-Juel1)129146$$aRohs, Susanne$$b9$$ufzj
001032065 7001_ $$0P:(DE-HGF)0$$aBrand, Erica$$b10
001032065 7001_ $$0P:(DE-HGF)0$$aVan Arsdale, Christopher$$b11
001032065 773__ $$a10.5281/ZENODO.12746362
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001032065 9141_ $$y2024
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