Empirical Calibration of Contrail Models based on LIDAR Observations

Abstract

Aircraft induced cirrus clouds are estimated to account for 57% of aviation’s current-day climate impact, but this value is highly uncertain with the fidelity and biases in meteorological data being significant contributing factors. Our work aims to address this uncertainty and to provide empirical evaluation of multiple contrail modeling approaches. First, we use a dataset of contrail cross sections observed from the CALIOP orbital LIDAR that were attributed to specific flights to calibrate parameterizations for the initial widths and depths of contrails. We then examine the effect of systematic biases in wind, humidity and temperature, analyzing which modifications to the data provide the best agreement between a simulated contrail (using the APCEMM contrail model) and observations. Finally, we evaluate the degree of accuracy of the calibrated APCEMM model across a larger dataset and compare the results to those from the widely-used CoCiP model.