The added value of a visible channel to a geostationary thermal infrared instrument to monitor ozone for air quality

Hache, Emeric; Attié, Jean-Luc; Tourneur, C.; Ricaud, Philippe; Coret, Laurent; Lahoz, W. A.; Amraoui, L. El; Josse, B.; Hamer, P. D.; Warner, J. X.; Liu, Xueliang; Chance, K.; Höpfner, Michael; Spurr, Robert; Natraj, Vijay; Kulawik, S. S.; Eldering, A.; Orphal, J.

doi:10.5194/amt-7-2185-2014

Cited by 17 publications

(13 citation statements)

References 51 publications

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“…Over the last decade, there has been increased use of data assimilation techniques to constrain model forecasts and reanalyses of atmospheric constituents (e.g., Arellano Jr. et al, 2007;Edwards et al, 2009;Claeyman et al, 2011;Lahoz et al, 2012;Pagowski and Grell, 2012;Bowman, 2013;Gaubert et al, 2014;Hache et al, 2014;Saide et al, 2014;Zoogman et al, 2014;Barré et al, 2015;Bousserez et al, 2016;Mizzi et al, 2016). Assimilation of chemicals can be extended to optimize model inputs such as emissions, thereby providing insight into how to improve the processes that govern the model performance (e.g., Elbern et al, 2007;Barbu et al, 2009;Chatterjee et al, 2012;Miyazaki et al, 2012b;Koohkan et al, 2013;Yumimoto, 2013;Cui et al, 2015;Guerrette and Henze, 2015;Turner et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Assimilation of satellite NO<sub>2</sub> observations at high spatial resolution using OSSEs

Mizzi

Anderson

et al. 2017

Atmos. Chem. Phys.

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Abstract. Observations of trace gases from space-based instruments offer the opportunity to constrain chemical and weather forecast and reanalysis models using the tools of data assimilation. In this study, observing system simulation experiments (OSSEs) are performed to investigate the potential of high space-and time-resolution column measurements as constraints on urban NO x emissions. The regional chemistry-meteorology assimilation system where meteorology and chemical variables are simultaneously assimilated is comprised of a chemical transport model, WRF-Chem, the Data Assimilation Research Testbed, and a geostationary observation simulator. We design OSSEs to investigate the sensitivity of emission inversions to the accuracy and uncertainty of the wind analyses and the emission updating scheme. We describe the overall model framework and some initial experiments that point out the first steps toward an optimal configuration for improving our understanding of NO x emissions by combining space-based measurements and data assimilation. Among the findings we describe is the dependence of errors in the estimated NO x emissions on the wind forecast errors, showing that wind vectors with a RMSE below 1 m s −1 allow inference of NO x emissions with a RMSE of less than 30 mol/(km 2 × h) at the 3 km scale of the model we use. We demonstrate that our inference of emissions is more accurate when we simultaneously update both NO x emissions and NO x concentrations instead of solely updating emissions. Furthermore, based on our analyses, we recommend carrying out meteorology assimilations to stabilize NO 2 transport from the initial wind errors before starting the emission assimilation. We show that wind uncertainties (calculated as a spread around a mean wind) are not important for estimating NO x emissions when the wind uncertainties are reduced below 1.5 m s −1 . Finally, we present results assessing the role of separate vs. simultaneous chemical and meteorological assimilation in a model framework without covariance between the meteorology and chemistry.

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Section: Introductionmentioning

confidence: 99%

Assimilation of satellite NO<sub>2</sub> observations at high spatial resolution using OSSEs

Mizzi

Anderson

et al. 2017

Atmos. Chem. Phys.

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“…Ces assimilations sont basées sur des plates-formes LEO (Low Earth Orbit) et il n'existe pas encore actuellement de plate-forme géostationnaire pour ces espèces chimiques. Des études récentes, fondées sur des expériences de simulation de système d'observation (Hache et al, 2014), ont montré l'apport positif qu'aurait ce type d'instrument pour la surveillance de la pollution et la qualité de l'air à l'échelle régionale ; des projets de ce type sont aujourd'hui en préparation.…”

Section: L'assimilation Pour Ré-analyser Des Champs De Concentrationsunclassified

Apport de l'observation satellitaire à l'analyse et à la prévision de la qualité de l'air

Menut¹,

Attié²,

Beekmann³

et al. 2017

Météorologie

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“…Further work in a 3-D framework would be required in order to determine how these ozone forecast errors translate into the context of real air quality forecasting. For instance, it might be possible to calculate the probability of detection or false-alarm rate statistics in a similar way to the work carried out by Hache et al (2014).…”

Section: Observation Errormentioning

confidence: 99%

“…the Chappuis bands for ozone in the visible range (Zoogman et al, 2011) that offer potential novel benefits. The UV and the Chappuis band in the visible range were combined theoretically to determine the benefit of such an approach during the development of the TEMPO instrument (Zoogman et al, 2014) and as part of a European initiative (Hache et al, 2014).…”

Section: P D Hamer Et Al: Observing Characteristics and The Predicmentioning

confidence: 99%

The impact of observing characteristics on the ability to predict ozone under varying polluted photochemical regimes

et al. 2015

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Abstract. We conduct analyses to assess how characteristics of observations of ozone and its precursors affect air quality forecasting and research. To carry out this investigation, we use a photochemical box model and its adjoint integrated with a Lagrangian 4D-variational data assimilation system. Using this framework in conjunction with pseudoobservations, we perform an ozone precursor source inversion and estimate surface emissions. We then assess the resulting improvement in ozone air quality prediction. We use an analytical model to conduct uncertainty analyses. Using this analytical tool, we address some key questions regarding how the characteristics of observations affect ozone precursor emission inversion and in turn ozone prediction. These questions include what the effect is of choosing which species to observe, of varying amounts of observation noise, of changing the observing frequency and the observation time during the diurnal cycle, and of how these different scenarios interact with different photochemical regimes. In our investigation we use three observed species scenarios: CO and NO 2 ; ozone, CO, and NO 2 ; and HCHO, CO and NO 2 . The photochemical model was set up to simulate a range of summertime polluted environments spanning NO x -(NO and NO 2 )-limited to volatile organic compound (VOC)-limited conditions. We find that as the photochemical regime changes, here is a variation in the relative importance of trace gas observations to be able to constrain emission estimates and to improve the subsequent ozone forecasts. For example, adding ozone observations to an NO 2 and CO observing system is found to decrease ozone prediction error under NO x -and VOC-limited regimes, and complementing the NO 2 and CO system with HCHO observations would improve ozone prediction in the transitional regime and under VOC-limited conditions. We found that scenarios observing ozone and HCHO with a relative observing noise of lower than 33 % were able to achieve ozone prediction errors of lower than 5 ppbv (parts per billion by volume). Further, only observing intervals of 3 h or shorter were able to consistently achieve ozone prediction errors of 5 ppbv or lower across all photochemical regimes. Making observations closer to the prediction period and either in the morning or afternoon rush hour periods made greater improvements for ozone prediction: 0.2-0.3 ppbv for the morning rush hour and from 0.3 to 0.8 ppbv for the afternoon compared to only 0-0.1 ppbv for other times of the day. Finally, we made two complementary analyses that show that our conclusions are insensitive to the assumed diurnal emission cycle and to the choice of which VOC species emission to estimate using our framework. These questions will address how different types of observing platform, e.g. geostationary satellites or ground monitoring networks, could support future air quality research and forecasting.

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The added value of a visible channel to a geostationary thermal infrared instrument to monitor ozone for air quality

Cited by 17 publications

References 51 publications

Assimilation of satellite NO<sub>2</sub> observations at high spatial resolution using OSSEs

Assimilation of satellite NO<sub>2</sub> observations at high spatial resolution using OSSEs

Apport de l'observation satellitaire à l'analyse et à la prévision de la qualité de l'air

The impact of observing characteristics on the ability to predict ozone under varying polluted photochemical regimes

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The added value of a visible channel to a geostationary thermal infrared instrument to monitor ozone for air quality

Cited by 17 publications

References 51 publications

Assimilation of satellite NO&lt;sub&gt;2&lt;/sub&gt; observations at high spatial resolution using OSSEs

Assimilation of satellite NO&lt;sub&gt;2&lt;/sub&gt; observations at high spatial resolution using OSSEs

Apport de l'observation satellitaire à l'analyse et à la prévision de la qualité de l'air

The impact of observing characteristics on the ability to predict ozone under varying polluted photochemical regimes

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Product

Resources

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Assimilation of satellite NO<sub>2</sub> observations at high spatial resolution using OSSEs

Assimilation of satellite NO<sub>2</sub> observations at high spatial resolution using OSSEs