Towards an understanding of uncertainties in the Lagrangian analysis of moisture sources for tropical cyclone precipitation through a study case

Despite the increasing number of atmospheric moisture tracking tools, their validation is challenging due to the lack of observations. This work contributes to a better understanding of uncertainties in the moisture sources analysis for the precipitation of tropical cyclones (TCs) by assessing eight combinations of threshold values in tracking methods based on the Lagrangian water budget equation. We selected as a study case Hurricane Ida that formed in the North Atlantic basin in late August 2021 and extracted the air parcel trajectories from the global outputs of the Lagrangian FLEXPART model. Results indicate that the choice of relative humidity (RH) threshold for filtering precipitating parcels has a noticeable impact on the Lagrangian precipitation estimates. In addition, methods applying the atmospheric boundary layer restriction produce a weaker moisture source pattern than those accounting for moisture uptakes in the whole atmospheric column. In particular, methods imposing an RH restriction along the air parcel trajectories to filter out noise in moisture losses outperform the others, providing more reliable moisture source contributions. We also introduced a simple bias correction approach that further improves the reliability of moisture source representation. • Moisture sources for TCprecipitation are sensitive to the relative humidity threshold in the Lagrangian moisture tracking. • The resulting threshold values provide a more accurate quantification of the Lagrangian estimate of TC precipitation. • The bias-correction approach reduces uncertainties in the moisture source pattern for tropical cyclone precipitation.