Speaker
Description
The Complete Data Fusion (CDF) technique combines measurements from multiple instruments or data sources into a unified dataset, leveraging the unique strengths of each to create a more accurate and comprehensive representation of the target phenomenon. Observational instruments provide complementary information due to differences in sensing capabilities, spectral coverage, vertical sensitivity (technical requirements), and spatial-temporal resolution (geophysical requirements). CDF integrates these complementary datasets, maximizing information content while minimizing uncertainties.
This project applies the CDF method to data from the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS-Envisat) and the Infrared Atmospheric Sounding Interferometer (IASI-MetOP) to detect Stratospheric Intrusions (SI) of ozone-rich air into the troposphere, focusing on the Himalayan region. SI events impact the troposphere by introducing ozone, a regulated pollutant and greenhouse gas, affecting atmospheric processes. Recent studies show an increase in stratospheric ozone intrusion, linked globally to the strengthening of the Brewer-Dobson Circulation (BDC). At a regional level, other factors may also play a role. The unique meteorological conditions in the Himalayas make this region a hotspot of ozone intrusions.
Understanding these events is critical for improving tropospheric ozone climatology, which is currently measured using a combination of in-situ and remote sensing techniques. However, biases between model simulations and observations persist, requiring better vertical resolution and broader spatial-temporal coverage, particularly in the Upper Troposphere-Lower Stratosphere (UTLS) region. Using advanced satellite instruments and innovative data exploitation methods, this project aims to reduce uncertainties and enhance our understanding of ozone dynamics.
