Ozone in the lower atmosphere can reach harmful levels, especially during summer pollution events. Prolonged exposure irritates the respiratory system and worsens lung diseases. Beyond health, it reduces agricultural productivity and harms ecosystems. Importantly, it is also the third most significant human-driven greenhouse gas, trapping heat and intensifying climate change.
Tracking its global distribution over time is therefore essential but also technically demanding.
The challenge of measuring ozone from space
Satellites provide the only way to observe ozone consistently across the globe over long periods. One widely used method is the Limb-Nadir Matching (LNM) technique, which combines two types of satellite observations:
- Limb measurements capture ozone in the stratosphere
- Nadir measurements capture the total ozone column
Tropospheric ozone is then calculated as the difference between the two.
However, this “residual method” has a critical weakness: since about 90% of ozone resides in the stratosphere, even small errors in stratospheric measurements can lead to large inaccuracies in tropospheric estimates.
A persistent mystery: the “red stripe” artefact
Scientists noticed a recurring anomaly in satellite data, a band of unusually high ozone values stretching across the tropical Pacific. This artefact appeared in datasets from multiple instruments, including those aboard the Suomi NPP satellite operated by NASA and NOAA, as well as European missions such as SCIAMACHY.
The consistency of this anomaly suggested a systematic issue rather than a real atmospheric phenomenon.
The ENFORCE breakthrough
The ENFORCE project was set out to investigate and solve this problem.
Researchers traced the problem to variations in surface reflectivity: specifically, how light reflects off the Earth’s surface and clouds along the satellite’s line of sight.
In regions like the Inter-Tropical Convergence Zone (ITCZ), persistent cloud bands create strong reflectance gradients. These gradients subtly distort limb-viewing measurements, introducing bias into the retrieved ozone profiles.
To address this, the team enhanced the radiative transfer model SCIATRAN, enabling it to account for two-dimensional variations in surface reflectivity along the observation path.
This new “2D mode” incorporates reflectance data from the VIIRS instrument, improving how the model represents real-world conditions.
The impact was immediate and clear: the artificial ozone “stripe” disappeared.
Better accuracy enabling new scientific insights
After extensive validation, the improved algorithm was used to reprocess more than a decade of satellite data (2012–2025). The result is a significantly more accurate global dataset of stratospheric ozone profiles and tropospheric ozone columns.
In line with open science principles, the ENFORCE project has made both the updated datasets and the enhanced SCIATRAN model publicly available under an open-source license.
This ensures that researchers worldwide can build on these advances, supporting better air quality monitoring, climate research, and policy decisions.