Comparison of Near‐Surface NO2 Pollution With Pandora Total Column NO2 During the Korea‐United States Ocean Color (KORUS OC) Campaign

Thompson, A. M.; Stauffer, Ryan M.; Boyle, Tyler P.; Kollonige, Debra E.; Miyazaki, Kazuyuki; Tzortziou, Maria; Herman, J. R.; Abuhassan, Nader; Jordan, Carolyn E.; Lamb, Berton L.

doi:10.1029/2019jd030765

Cited by 27 publications

(36 citation statements)

References 57 publications

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“…A high-resolution version of the MIROC-Chem model, with a horizontal resolution of T106 (1.1° x 1.1°) and 32 hybrid (eta) vertical levels, MIROC-Chem-H (Sekiya et al, 2018), was also used. This model utilizes the same chemical and transport module as the MIROC-Chem (c.f., Section 2.2.3) and has been used to study processes controlling air quality in east Asia during the KORUS-AQ aircraft campaign (Miyazaki et al, 2019;Thompson et al, 2019) and conduct the second tropospheric chemical reanalysis Miyazaki et al,in prep) for 2005-2018. Kanaya et al (2019) demonstrated the overall good performance of the ozone and CO analyses in TCR-2 over remote oceans using observations from research vessels.…”

Section: Miroc-chem-hmentioning

confidence: 99%

Evaluation of a multi-model, multi-constituent assimilation framework for tropospheric chemical reanalysis

Miyazaki¹,

Bowman²,

Yumimoto³

et al. 2019

Preprint

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Abstract. We introduce a Multi-mOdel Multi-cOnstituent Chemical data assimilation (MOMO-Chem) framework that directly accounts for model error in transport and chemistry by integrating a portfolio of forward chemical transport models (GEOS-Chem, AGCM-CHASER, MIROC-Chem, MIROC-Chem-H) into a state-of-the-art ensemble Kalman filter data assimilation system that simultaneously optimizes both concentrations and emissions of multiple species through ingestion of a suite of measurements (ozone, NO2, CO, HNO3) from multiple satellite sensors. In spite of substantial model differences, the observational density and accuracy was sufficient for the assimilation to reduce the multi-model spread by 20&#8211;85&#8201;% for ozone, and annual mean bias by 39&#8211;97&#8201;% for ozone in the middle troposphere, while simultaneously reducing the tropospheric NO2 column biases by more than 40&#8201;%, and the negative biases of surface CO in the Northern Hemisphere by 41&#8211;94&#8201;%. For tropospheric mean OH, the multi-model mean meridional hemispheric gradient was reduced from 1.32&#8201;&#177;&#8201;0.03 to 1.19&#8201;&#177;&#8201;0.03, while the multi-model spread was reduced by 24&#8211;58&#8201;% over polluted areas. These improvements extended to emissions where uncertainty ranges in the a posteriori emissions due to model errors were quantified in 4&#8211;31&#8201;% for NOx and 13&#8211;35&#8201;% for CO regional emissions. Harnessing assimilation increments in both NOx and ozone, we show that the sensitivity of ozone and NO2 surface concentrations to NOx emissions varied by a factor of 2 for end-member models revealing fundamental differences in the representation of fast chemical and dynamical processes. Consequently, diagnostic information readily available from MOMO-Chem has the potential to improve chemical predictions through relationships such as emergent constraints.

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Section: Miroc-chem-hmentioning

confidence: 99%

Evaluation of a multi-model, multi-constituent assimilation framework for tropospheric chemical reanalysis

Miyazaki¹,

Bowman²,

Yumimoto³

et al. 2019

Preprint

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“…Chandra, 2003, Inness et al, 2015). Other processes that potentially influence tropospheric ozone, which are generally considered of minor importance, are the Quasi-biennial Oscillation (Neu et al, 2014) and the North Atlantic Oscillation (Thouret et al, 2006).…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2020

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Global tropospheric ozone reanalyses constructed using different state-of-the-art satellite data assimilation systems, prepared as part of the Copernicus Atmosphere Monitoring Service (CAMS-iRean and CAMS-Rean) as well as two fully independent reanalyses (TCR-1 and TCR-2, Tropospheric Chemistry Reanalysis), have been intercompared and evaluated for the past decade. The updated reanalyses (CAMS-Rean and TCR-2) generally show substantially improved agreements with independent ground and ozonesonde observations over their predecessor versions (CAMS-iRean and TCR-1) for diurnal, synoptical, seasonal, and interannual variabilities. For instance, for the Northern Hemisphere (NH) mid-latitudes the tropospheric ozone columns (surface to 300 hPa) from the updated reanalyses show mean biases to within 0.8 DU (Dobson units, 3 % relative to the observed column) with respect to the ozone-sonde observations. The improved performance can likely be attributed to a mixture of various upgrades, such as revisions in the chemical data assimilation, including the assimilated measurements, and the forecast model performance. The updated chemical reanalyses agree well with each other for most cases, which highlights the usefulness of the current chemical reanalyses in a variety of studies. Meanwhile, significant temporal changes in the reanalysis quality in all the systems can be attributed to discontinuities in the observing systems. To improve the temporal consistency, a careful assessment of changes in the assimilation configuration, such as a detailed assessment of biases between various retrieval products, is needed. Our comparison suggests that improving the observational constraints, including the continued development of satellite observing systems, together with the optimization of model parameterizations such as deposition and chemical reactions, will lead to increasingly consistent long-term reanalyses in the future.Published by Copernicus Publications on behalf of the European Geosciences Union.

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“…An updated CTM and satellite retrievals are used in TCR-2 (Kanaya et al, 2019;Miyazaki et al, 2019aMiyazaki et al, , 2019bThompson et al, 2019). A high-resolution version of the MIROC-Chem model with a horizontal resolution of T106 (1.1° x 1.1°) was used.…”

Section: Updated Tropospheric Chemistry Reanalysis (Tcr-2)mentioning

confidence: 99%

“…Kanaya et al (2019) demonstrated the TCR-2 ozone and CO performance using research vessel observations over open oceans. Thompson et al (2019) used the TCR-2 data to help understanding of near surface NO 2 pollutions observed during the KORUS-OC campaign. Both for TCR-1 and TCR-2 the reanalysis data is archived on a twohourly output frequency.…”

Section: Updated Tropospheric Chemistry Reanalysis (Tcr-2)mentioning

confidence: 99%

“…TCR-1 has been used to provide comprehensive information on atmospheric composition variability and elucidate variations in precursor emissions, and to evaluate bottom-up emission inventories (Miyazaki et al, 2012(Miyazaki et al, , 2014(Miyazaki et al, , 2015(Miyazaki et al, , 2017Ding et al, 2017;Jiang et al, 2019;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;Miyazaki et al, 2019a;Thompson et al, 2019). For stratospheric constituents, several studies have been conducted to produce and compare stratospheric chemical reanalysis products (Davis et al, 2017;Errera et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

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An inter-comparison of tropospheric ozone reanalysis products from CAMS, CAMS-Interim, TCR-1 and TCR-2

Huijnen¹,

Miyazaki²,

Flemming³

et al. 2019

Preprint

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Abstract. Global tropospheric ozone reanalyses constructed using different state-of-the-art satellite data assimilation systems, prepared as part of the Copernicus Atmosphere Monitoring Service (CAMS-iRean and CAMS-Rean) as well as two fully independent Tropospheric Chemistry Reanalyses (TCR-1 and TCR-2), have been inter-compared and evaluated for the past decade. The updated reanalyses (CAMS-Rean and TCR-2) generally show substantially improved agreements with independent ground and ozonesonde observations over their predecessor versions (CAMS-iRean and TCR-1) for the diurnal, synoptical, seasonal, and decadal variability. The improved performance can be attributed to a mixture of various upgrades, such as revisions in the chemical data assimilation, including the assimilated measurements, and the forecast model performance. The updated chemical reanalyses agree well with each other for most cases, which highlights the usefulness of the current chemical reanalyses in a variety of studies. Meanwhile, significant temporal changes in the reanalysis quality in all the systems can be attributed to discontinuities in the observing systems. To improve the temporal consistency, a careful assessment of changes in the assimilation configuration, such as a detailed assessment of biases between various retrieval products, is needed. Even though the assimilation of multi-species data influences the representation of the trace gases in all the systems and also the precursors’ emissions in the TCR reanalyses, the influence of persistent model errors remains a concern, especially for the lower troposphere. Our comparison suggests that improving the observational constraints, including the continued development of satellite observing systems, together with the optimization of model parameterisations, such as deposition and chemical reactions, will lead to increasingly consistent long-term reanalyses in the future.

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Comparison of Near‐Surface NO₂ Pollution With Pandora Total Column NO₂ During the Korea‐United States Ocean Color (KORUS OC) Campaign

Cited by 27 publications

References 57 publications

Evaluation of a multi-model, multi-constituent assimilation framework for tropospheric chemical reanalysis

Evaluation of a multi-model, multi-constituent assimilation framework for tropospheric chemical reanalysis

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

An inter-comparison of tropospheric ozone reanalysis products from CAMS, CAMS-Interim, TCR-1 and TCR-2

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