Evaluation of ACCMIP ozone simulations and ozonesonde sampling biases using a satellite-based multi-constituent chemical reanalysis

Abstract

Abstract. The Atmospheric Chemistry Climate Model Intercomparison Project (ACCMIP) ensemble ozone simulations for the present day from the 2000 decade simulation results are evaluated by a state-of-the-art multi-constituent atmospheric chemical reanalysis that ingests multiple satellite data including the Tropospheric Emission Spectrometer (TES), the Microwave Limb Sounder (MLS), the Ozone Monitoring Instrument (OMI), and the Measurement of Pollution in the Troposphere (MOPITT) for [2005][2006][2007][2008][2009]. Validation of the chemical reanalysis against global ozonesondes shows good agreement throughout the free troposphere and lower stratosphere for both seasonal and year-to-year variations, with an annual mean bias of less than 0.9 ppb in the middle and upper troposphere at the tropics and midlatitudes. The reanalysis provides comprehensive spatiotemporal evaluation of chemistry-model performance that compliments direct ozonesonde comparisons, which are shown to suffer from significant sampling bias. The reanalysis reveals that the ACCMIP ensemble mean overestimates ozone in the northern extratropics by 6-11 ppb while underestimating by up to 18 ppb in the southern tropics over the Atlantic in the lower troposphere. Most models underestimate the spatial variability of the annual mean lower tropospheric concentrations in the extratropics of both hemispheres by up to 70 %. The ensemble mean also overestimates the seasonal amplitude by 25-70 % in the northern extratropics and overestimates the inter-hemispheric gradient by about 30 % in the lower and middle troposphere. A part of the discrepancies can be attributed to the 5-year reanalysis data for the decadal model simulations. However, these differences are less evident with the current sonde network. To estimate ozonesonde sampling biases, we computed model bias separately for global coverage and the ozonesonde network. The ozonesonde sampling bias in the evaluated model bias for the seasonal mean concentration relative to global coverage is 40-50 % over the western Pacific and east Indian Ocean and reaches 110 % over the equatorial Americas and up to 80 % for the global tropics. In contrast, the ozonesonde sampling bias is typically smaller than 30 % for the Arctic regions in the lower and middle troposphere. These systematic biases have implications for ozone radiative forcing and the response of chemistry to climate that can be further quantified as the satellite observational record extends to multiple decades.

Ozone and carbon monoxide observations over open oceans on R/V Mirai from 67° S to 75° N during 2012 to 2017: testing global chemical reanalysis in terms of Arctic processes, low ozone levels at low latitudes, and pollution transport

“…The first version of tropospheric chemistry reanalysis from JAMSTEC, i.e., TCR-1, which used an ensemble Kalman filter (EnKF) approach with a global atmospheric chemistry model (CHASER) as a base forward model, has been previously described (Miyazaki et al, 2015). Here, the updated version, TCR-2, was used (Miyazaki et al, 2019, https://ebcrpa.jamstec.go.jp/tcr2/about_data.html, last acces: 27 May 2019).…”

“…This has advantages over forward model simulations incorporating a bottom-up emission inventory because realistic emissions are taken into account, even those for recent years, for which a bottom-up emission inventory is not yet ready. TCR-2 was updated from the previous version, TCR-1 (Miyazaki et al, 2015): the spatial resolution has been improved and newer satellite products are used for assimilation. For TCR-1, evaluation against surface, sonde, and aircraft observations was successful (Miyazaki et al, 2015;Miyazaki and Bowman, 2017).…”

“…TCR-2 was updated from the previous version, TCR-1 (Miyazaki et al, 2015): the spatial resolution has been improved and newer satellite products are used for assimilation. For TCR-1, evaluation against surface, sonde, and aircraft observations was successful (Miyazaki et al, 2015;Miyazaki and Bowman, 2017). For TCR-2, the performance has been evaluated using the KORUS-AQ aircraft campaign measurements over east Asia (Miyazaki et al, 2019).…”

An intercomparison of tropospheric ozone reanalysis products from CAMS, CAMS interim, TCR-1, and TCR-2

“…Miyazaki et al (2015) simultaneously estimated concentrations and emissions for the 8-year Tropospheric Chemistry Reanalysis (TCR-1) for the years 2005-2012 obtained from an assimilation of multi-constituent satellite measurements using an ensemble Kalman filter (EnKF). TCR-1 has been used to provide comprehensive information on atmospheric composition variability and elucidate variations in precursor emissions, as well as to evaluate bottom-up emission inventories (Miyazaki et al, 2012a(Miyazaki et al, , 2014(Miyazaki et al, , 2015Ding et al, 2017;Jiang et al, 2018;Tang et al, 2019). A second version of the EnKF-based reanalysis (TCR-2) has been recently produced using an updated model and satellite retrievals for the years 2005-2018 (Kanaya et al, 2019;.…”

Ozone and carbon monoxide observations over open oceans on R/V Mirai from 67° S to 75° N during 2012 to 2017: Testing global chemical reanalysis in terms of Arctic processes, low ozone levels at low latitudes, and pollution transport

“…TCR-2 was updated from the previous version TCR-1 (Miyazaki et al, 2015); the spatial resolution has been improved and newer satellite products are used for assimilation. For TCR-1, evaluation against surface, sonde, and aircraft observations was successful (Miyazaki et al, 2015;Miyazaki and Bowman, 2017). For TCR-2, the performance has been evaluated using the KORUS-AQ aircraft campaign measurements over East Asia (Miyazaki et al, 2018).…”