Using networked Pandora observations to capture spatiotemporal changes in total column ozone associated with stratosphere-to-troposphere transport
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Author/Creator ORCID
Date
2020-01-21
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Citation of Original Publication
Robinson J, Kotsakis A, Santos F, Swap R, Knowland K.E, Labow G, Connors V, Tzortziou M, Abuhassan N, Tiefengraber M, Cede A, Using networked Pandora observations to capture spatiotemporal changes in total column ozone associated with stratosphere-to-troposphere transport, https://doi.org/10.1016/j.atmosres.2020.104872
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Public Domain Mark 1.0
This work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.
Public Domain Mark 1.0
This work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.
Subjects
Abstract
Accurately capturing the evolution of episodic stratosphere-to-troposphere transport is critical due to the potential impacts on both climate and air quality. Until now, investigating associated spatiotemporal gradients in total column ozone (TCO) has primarily been the task of observations from polar-orbiting satellites as well as high-resolution models. We explore how a network of five ground-based Pandora spectrometer systems can be utilized in a similar fashion. The passage of a strong mid-latitude cyclone in March 2018 and its associated stratospheric intrusion is used as a case demonstrating the ability of networked Pandora observations to contextualize these regions of transport across space and time. Results show that the high temporal resolution of Pandora observations and the networked approach were able to resolve increases in TCO associated with stratosphere-to-troposphere transport and to capture the spatial context of the chosen episode. The use of networked Pandora observations shows promise for additional transport studies and for supporting future geostationary atmospheric composition satellite missions and modeling efforts.