Multi-parameter dynamical diagnostics for upper tropospheric and lower stratospheric studies

Millán, L. F., Manney, G. L., Boenisch, H., Hegglin, M. I. ORCID: https://orcid.org/0000-0003-2820-9044, Hoor, P., Kunkel, D., Leblanc, T., Petropavloskikh, I., Walker, K., Wargan, K. and Zahn, A. (2023) Multi-parameter dynamical diagnostics for upper tropospheric and lower stratospheric studies. Atmospheric Measurement Techniques, 16 (11). pp. 2957-2988. ISSN 1867-8548 doi: 10.5194/amt-16-2957-2023

Abstract/Summary

Ozone trend estimates have shown large uncertainties in the upper troposphere–lower stratosphere (UTLS) region despite multi-decadal observations available from ground-based, balloon, aircraft, and satellite platforms. These uncertainties arise from large natural variability driven by dynamics (reflected in tropopause and jet variations) as well as the strength in constituent transport and mixing. Additionally, despite all the community efforts there is still a lack of representative high-quality global UTLS measurements to capture this variability. The Stratosphere-troposphere Processes And their Role in Climate (SPARC) Observed Composition Trends and Variability in the UTLS (OCTAV-UTLS) activity aims to reduce uncertainties in UTLS composition trend estimates by accounting for this dynamically induced variability. In this paper, we describe the production of dynamical diagnostics using meteorological information from reanalysis fields that facilitate mapping observations from several platforms into numerous geophysically based coordinates (including tropopause and upper tropospheric jet relative coordinates). Suitable coordinates should increase the homogeneity of the air masses analyzed together, thus reducing the uncertainty caused by spatiotemporal sampling biases in the quantification of UTLS composition trends. This approach thus provides a framework for comparing measurements with diverse sampling patterns and leverages the meteorological context to derive maximum information on UTLS composition and trends and its relationships to dynamical variability. The dynamical diagnostics presented here are the first comprehensive set describing the meteorological context for multi-decadal observations by ozonesondes, lidar, aircraft, and satellite measurements in order to study the impact of dynamical processes on observed UTLS trends by different sensors on different platforms. Examples using these diagnostics to map multi-platform datasets into different geophysically based coordinate systems are provided. The diagnostics presented can also be applied to analysis of greenhouse gases other than ozone that are relevant to surface climate and UTLS chemistry.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/120150
Identification Number/DOI	10.5194/amt-16-2957-2023
Refereed	Yes
Divisions	Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher	Copernicus
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