Characterizing potential sources and transport pathways of intense moisture during extreme precipitation events over the Tibetan Plateau

Abstract

Understanding moisture sources and transport mechanisms during extreme precipitation events (EPEs) is imperative for sustainable development. Here, potential moisture sources, contributions, and transport pathways were evaluated during EPEs over Tibet Plateau (TP) between 1951 and 2015, employing three back-trajectory approaches, including Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT), Potential Source Contribution Function (PSCF), and Concentration Weighted Trajectory (CWT). Results showed that all twenty-three selected EPEs occurred within the TP’s southern foothill. Back-trajectories from the EPEs target are then clustered into five, and analysis revealed that moisture sources and pathways showed a similar pattern. Generally, moisture largely originates from three sources, including airflow trajectories from the Arabian Sea, Bay of Bengal, and tropical-subtropical area of the Indian landmass. Besides, local moisture transport within TP also has key influences. For instance, analysis from the first EPEs target showed southwesterly (Cluster 1; 12 %, Cluster 2; 20 %, Cluster 3; 22 %) and southeasterly (Cluster 4; 30 %, Cluster 5; 16 %) moisture paths originating from the Arabian Sea and Northern India, respectively. Moisture transport (IVT) path analysis for this target showed that all IVT clusters in descending order were 3 > 4 > 2 > 5 > 1, with a mean of 243 kg/m/s. Conversely, above-average IVT clusters ranged from 305 to 345 kg/m/s and had a mean of 334 kg/m/s, while cluster 2 had the highest contribution of 37 %. Moisture transport source regions obtained utilizing PSCF and CWT methods naturally share comparable features, proving the credibility and accuracy of the results. Based on the EPEs and back-trajectory analysis in this study, we demonstrated unique moisture sources and dominant moisture pathways for each EPEs target. This is important in modeling, simulating, and predicting extremes in space and time and, consequently, for resource management. This may also aid in mitigating numerous natural disasters arising from EPEs and provide significant scientific references for coordinated atmospheric research.