Vertically integrated moisture transport : trends over Nepal and the Pamir

Context : Understanding precipitation variability and long-term trends in High Mountain Asia (HMA) remains a major scientific challenge. The region lies at the intersection of two dominant circulation systems—the Asian monsoon and the Western disturbances—which control the timing and intensity of moisture advection toward the Himalayas and the Pamir. However, the scarcity of local observations and the steep topographic gradients hinder the quantification of long-term humidity transport and its influence on precipitation trends.
Global reanalyses such as ERA5 provide consistent large-scale information on atmospheric circulation and moisture fields, but they often fail to capture the fine-scale spatial variability of temperature and precipitation over complex terrain. High-resolution regional models such as MAR (Modèle Atmosphérique Régional) can bridge this gap by dynamically downscaling the large-scale circulation to resolve local climatic conditions and precipitation processes.

Objective : The intern will analyze vertically integrated moisture transport (IVT) over HMA, focusing on Nepal and Pamir. Using ERA5 reanalysis, the candidate will quantify mean seasonal patterns and recent trends of IVT and assess their relationship with precipitation and large-scale circulation indices (NAO, IPO, etc…). The analysis will then be extended to MAR-ERA5 regional simulations to investigate moisture transport and precipitation at the local scale. If time allows, the study may include additional analyses using IPSL model simulations (historical and DAMIP ocean-atmosphere coupled experiments) to separate externally forced signals from internal climate variability. Overall, the internship aims to link large-scale humidity transport dynamics with local-scale precipitation responses, improving our understanding of the hydroclimatic evolution of HMA under climate change.

Desired skills
● Background in climate science and/or atmospheric dynamics
● Experience handling gridded datasets (e.g. reanalysis or model output)
● Proficiency in Python and data analysis with NetCDF files
● Interest in large-scale circulation and mountain climate processes

Contact : María Santolaria-Otín (maria.santolaria-otin univ-grenoble-alpes.fr)