Satellite instruments, such as TROPOMI, are routinely
used to quantify tropospheric nitrogen dioxide (NO2)
based on its narrowband light absorption in the UV/
visible spectral range. The key limitation of such
retrievals is that they can only return the „vertical
column density“ (VCD), defined as the integral of the
NO2 concentration profile. The profile itself, which
describes the vertical distribution of NO2, remains
unknown.
This presentation showcases „NitroNet“, the first NO2
profile retrieval for TROPOMI. NitroNet is a neural
network, which was trained on synthetic NO2 profiles
from the regional chemistry and transport model WRFChem,
operated on a European domain for the month of
May 2019. The neural network receives NO2 VCDs from
TROPOMI alongside ancillary variables (meteorology,
emission data, etc.) as input, from which it estimates NO2
concentration profiles.
The talk covers:
• an introduction to satellite remote sensing of NO2.
• the theoretical underpinnings of NitroNet, how the
model was trained, and how it was validated.
• practical new applications that NitroNet enables.
LOCATION: TRANSP:OPAQUE URL:https://www.weizmann.ac.il/EPS/events END:VEVENT END:VCALENDAR