Published in

American Geophysical Union, Journal of Geophysical Research: Atmospheres, 18(126), 2021

DOI: 10.1029/2020jd034481

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Examining CO<sub>2</sub> Model Observation Residuals Using ACT‐America Data

This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Data provided by SHERPA/RoMEO

Abstract

AbstractAtmospheric inversion typically relies on the specification of prior flux and atmospheric model transport errors, which have large uncertainties. Here, we used ACT‐America airborne observations to compare model observation mismatch in the eastern U.S. and during four climatological seasons for the mesoscale WRF(‐Chem) and global scale CarbonTracker/TM5 (CT) models. Models used identical surface carbon fluxes, and CT was used as boundary condition for WRF. Both models showed reasonable agreement with observations, and residuals follow near symmetric peaked (i.e., non‐Gaussian) distribution with near‐zero bias of both models (CT: ppm; WRF: ppm). We also found large magnitude residuals at the tails of the distribution that contribute considerably to overall bias. Atmospheric boundary‐layer biases (1–10 ppm) were much larger than free tropospheric biases (0.5–1 ppm) and were of same magnitude as model‐model differences, whereas free tropospheric biases were mostly governed by background conditions. Results revealed systematic differences in atmospheric transport, most pronounced in the warm and cold sectors of synoptic systems, highlighting the importance of transport for residuals. While CT could reproduce the principal dynamics associated with synoptic systems, WRF showed a clearer distinction for differences across fronts. Variograms were used to quantify spatial correlation of residuals and showed characteristic residual length scales of approximately 100–300 km. Our findings suggest that inclusion of synoptic weather‐dependent and non‐Gaussian error structure may benefit inversion systems.