Next‐Generation Isoprene Measurements From Space: Detecting Daily Variability at High Resolution. Issue 5 (14th March 2022)

• Record Type: Journal Article
• Authors: Wells, K. C.; Millet, D. B.; Payne, V. H.; Vigouroux, C.; Aquino, C. A. B.; De Mazière, M.; de Gouw, J. A.; Graus, M.; Kurosu, T.; Warneke, C.; Wisthaler, A.
• Is Part Of: Journal of geophysical research. Volume 127:Issue 5(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-03-14
• Subjects: isoprene -- remote sensing -- CrIS -- neural network; Atmospheric physics -- Periodicals; Geophysics -- Periodicals; 551.5
• DOI: 10.1029/2021JD036181
• Languages: English
• ISSNs: 2169-897X

Abstract

Abstract: Isoprene is the dominant nonmethane organic compound emitted to the atmosphere, where it drives ozone and aerosol production, modulates atmospheric oxidation, and interacts with the global nitrogen cycle. Isoprene emissions are highly variable and uncertain, as is the nonlinear chemistry coupling isoprene and its primary sink, the hydroxyl radical. Space‐based isoprene measurements can help close the gap on these uncertainties, and when combined with concurrent formaldehyde data provide a new constraint on atmospheric oxidation regimes. Here, we present a next‐generation machine‐learning isoprene retrieval for the Cross‐track Infrared Sounder (CrIS) that provides improved sensitivity, lower noise, and thus higher space‐time resolution than earlier approaches. The Retrieval of Organics from CrIS Radiances (ROCR) isoprene measurements compare well with previous space‐based retrievals as well as with the first‐ever ground‐based isoprene column measurements, with 20%–50% discrepancies that reflect differing sources of systematic uncertainty. An ensemble of sensitivity tests points to the spectral background and isoprene profile specification as the most relevant uncertainty sources in the ROCR framework. We apply the ROCR isoprene algorithm to the full CrIS record from 2012 to 2020, showing that it can resolve fine‐scale spatial gradients at daily resolution over the world's isoprene hotspots. Results over North America and Amazonia highlight emergent connections between isoprene abundance and daily‐to‐interannual variations in temperature and nitrogen oxides. Plain Language Summary: Isoprene is a naturally occurring trace gas emitted primarily from the leaves of woody plants. Isoprene has important impacts on both air quality and climate; however, these impacts are difficult to assess and predict given large uncertainties in its sources and atmospheric chemistry. Space‐based measurements can help to address these uncertainties. Here, we present new satellite measurements of isoprene from the Cross‐track Infrared Sounder (CrIS), using a computationally efficient machine‐learning framework (Retrieval of Organics from CrIS Radiances; ROCR). ROCR measurements provide improved sensitivity and richer spatiotemporal information on atmospheric isoprene than was previously available. Results compare well to previous satellite‐based approaches and to new ground‐based observations. We apply the ROCR framework to measure daily, global isoprene distributions from 2012 to 2020. Results over North America and Amazonia highlight the processes controlling isoprene abundances and their variability over time. Key Points: We present a next‐generation spaced‐based isoprene retrieval with higher sensitivity and resolution than previous approaches Global, daily isoprene distributions are derived from 2012 to 2020 that compare well with the first ground‐based isoprene column observations High‐resolution results over isoprene hotspots highlight processes controlling isoprene abundance and its daily‐to‐interannual variability