Conference Agenda

Cloud and building shadows frequently appear in high spatial resolution satellite images in the visible channels. During a solar eclipse, the shadow of the Moon can be identified in satellite imagery. Typically, shadows are removed or ignored when deriving satellite products, such as cloud properties, aerosol optical thickness, atmospheric composition. We have analyzed the impacts of shadows on the satellite products and utilised the shadows to derive new satellite products. In our analyses the shadows include cloud shadows, building shadows, and the shadow of the Moon.

We have developed an automated cloud shadow detection algorithm for TROPOMI, called DARCLOS (Trees et al., 2022). This algorithm has been used in deriving the TROPOMI surface directional Lambertian Equivalent reflection (DLER) product (Tilstra et al., 2023). We analysed TROPOMI absorbing aerosol product (AAI) and NO₂ products for pixels inside and outside the cloud shadows. However, we did not find significant bias in the AAI (Trees et al., 2024b) and NO₂ products in the cloud shadows.

We restored the TROPOMI and GOME-2 satellite measurements during solar eclipses, consequently the artefact of high AAI values in TROPOMI and GOME-2 AAI products disappeared (Trees et al., 2021). We analysed TROPOMI NO₂ products during solar eclipse and found the increasing NO₂ column densities with increasing obscuration fractions during the solar eclipse (Schrijver, 2024).

Solar eclipse can be detected in multiple time slots of geostationary satellite images. We found shallow cumulus clouds over land disappeared rapidly during solar eclipses and simulated this process using a LES mdoel (Trees et al., 2024a).

Cloud shadows and building shadows in satellite images have also been used to derive cloud optical thickness. We derived aerosol optical thickness at selected locations using building shadows in GF-2 images (Qiao et al., 2024). The cloud shadows in Sentinel-2 images were used to derive aerosol optical thickness and compared with MODIS measurements.

In the presentation, we will show some highlights of the papers and provide a summary of the project.

References

Qiao Congcong，Zhou ying，Zong Xuemei, Huo Juan, Sun Bin, Duan Minzheng, 2024a，A Novel Algorithm for Deriving Aerosol Optical Depth over Cities using the Building Shadows of High-resolution Satellite Imagery paper, Submitted to TGRS, 2024

Schrijver, Impact of solar eclipses on NO₂ in the Earth's atmosphere as measured from space by TROPOMI, master thesis, TU Delft, 2024.

Tilstra, L. G., de Graaf, M., Trees, V., Litvinov, P., Dubovik, O., and Stammes, P.: A directional surface reflectance climatology determined from TROPOMI observations, Atmos. Meas. Tech. Discuss. [preprint], https://doi.org/10.5194/amt-2023-222, accepted, 2023.

Trees, V., Wang, P. & Stammes, P. Restoring the top-of-atmosphere reflectance during solar eclipses: a proof of concept with the UV absorbing aerosol index measured by TROPOMI. Atmos. Chem. Phys. 21, 8593–8614 (2021).

Trees, V. J. H., Wang, P., Stammes, P., Tilstra, L. G., Donovan, D. P., and Siebesma, A. P.: DARCLOS: a cloud shadow detection algorithm for TROPOMI, Atmos. Meas. Tech., 15, 3121–3140, https://doi.org/10.5194/amt-15-3121-2022, 2022.

Trees, V.J.H., Stephan R. de Roode, Job I. Wiltink, Jan Fokke Meirink, Ping Wang, Piet Stammes and A. Pier Siebesma. Clouds dissipate quickly during solar eclipses as the land surface cools. Nature Communications Earth & Environment. 12 February 2024a.

Trees, V. J. H. et al., Cancellation of cloud shadow effects in the absorbing aerosol index retrieval algorithm of TROPOMI, submitted to AMTD, 2024b.

Abstract: The global transition towards renewable energy sources is crucial for combating climate change and advancing sustainable development worldwide. In the United Kingdom (UK) and Ireland, this transition holds significant importance not only for environmental reasons but also as a strategic approach to ensuring long-term economic stability and energy security. This study investigates the effect of implementing renewable energy sources (RES) on greenhouse gas (GHG) reduction in the UK and Ireland, utilizing satellite data for analysis.

The research focuses on analyzing satellite-derived GHG emissions data spanning from 1990 to 2022 over specific geolocations in the UK and Ireland. This validated data, provided by project partners, offers valuable insights into GHG emissions trends and variations over time. The study employs advanced analytical techniques to assess the impact of renewable energy implementation, particularly wind power, on GHG reduction in regions where RES deployment is prominent.

By leveraging satellite data, this research aims to provide a comprehensive understanding of the relationship between renewable energy deployment and GHG emissions reduction in the UK and Ireland. The findings will inform decision-making processes for policymakers and stakeholders, facilitating the development of effective strategies to accelerate the transition towards a low-carbon future.