Extending methane profiles from aircraft into the stratosphere for satellite total column validation using the ECMWF C-IFS and TOMCAT/SLIMCAT 3-D model

Abstract. Airborne observations of greenhouse gases are a very useful reference for validation of satellite-based column-averaged dry air mole fraction data. However, since the aircraft data are available only up to about 9–13 km altitude, these profiles do not fully represent the depth of the atmosphere observed by satellites and therefore need to be extended synthetically into the stratosphere. In the near future, observations of CO2 and CH4 made from passenger aircraft are expected to be available through the In-Service Aircraft for a Global Observing System (IAGOS) project. In this study, we analyse three different data sources that are available for the stratospheric extension of aircraft profiles by comparing the error introduced by each of them into the total column and provide recommendations regarding the best approach. First, we analyse CH4 fields from two different models of atmospheric composition – the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System for Composition (C-IFS) and the TOMCAT/SLIMCAT 3-D chemical transport model. Secondly, we consider scenarios that simulate the effect of using CH4 climatologies such as those based on balloons or satellite limb soundings. Thirdly, we assess the impact of using a priori profiles used in the satellite retrievals for the stratospheric part of the total column. We find that the models considered in this study have a better estimation of the stratospheric CH4 as compared to the climatology-based data and the satellite a priori profiles. Both the C-IFS and TOMCAT models have a bias of about −9 ppb at the locations where tropospheric vertical profiles will be measured by IAGOS. The C-IFS model, however, has a lower random error (6.5 ppb) than TOMCAT (12.8 ppb). These values are well within the minimum desired accuracy and precision of satellite total column XCH4 retrievals (10 and 34 ppb, respectively). In comparison, the a priori profile from the University of Leicester Greenhouse Gases Observing Satellite (GOSAT) Proxy XCH4 retrieval and climatology-based data introduce larger random errors in the total column, being limited in spatial coverage and temporal variability. Furthermore, we find that the bias in the models varies with latitude and season. Therefore, applying appropriate bias correction to the model fields before using them for profile extension is expected to further decrease the error contributed by the stratospheric part of the profile to the total column.

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Extending methane profiles from aircraft into the stratosphere for satellite total column validation: A comparative analysis of different data sources

10.5194/acp-2016-704 ◽

2016 ◽

Cited By ~ 1

Author(s):

Shreeya Verma ◽

Julia Marshall ◽

Mark Parrington ◽

Anna Agusti-Panareda ◽

Sebastien Massart ◽

...

Keyword(s):

Greenhouse Gases ◽

Transport Model ◽

A Priori ◽

Data Sources ◽

Atmospheric Composition ◽

Random Errors ◽

Chemical Transport Model ◽

Spatial Coverage ◽

The Impact ◽

Total Column

Abstract. Airborne observations of greenhouse gases are a very useful reference for validation of satellite-based column-averaged dry air mole fraction data. However, since the aircraft data are available only up to about 9–13 km altitude, these profiles do not fully represent the depth of the atmosphere observed by satellites and therefore need to be extended synthetically into the stratosphere. In the near future, observations of CO2 and CH4 made from passenger aircraft are expected to be available through the In-Service Aircraft for a Global Observing System (IAGOS) project. In this study, we analyse three different data sources that are available for the stratospheric extension of aircraft profiles by comparing the error introduced by each of them into the total column and provide recommendations regarding the best approach. First, we analyse CH4 fields from two different models of atmospheric composition – the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System for Composition (C-IFS) and the TOMCAT/SLIMCAT 3-D chemical transport model. Secondly, we consider scenarios that simulate the effect of using CH4 climatologies such as those based on balloons or satellite limb soundings. Thirdly, we assess the impact of using a-priori profiles used in the satellite retrievals for the stratospheric part of the total column. We find that the models considered in this study have a better estimation of the stratospheric CH4 as compared to the climatology-based data and the satellite a-priori profiles. Both the C-IFS and TOMCAT models have a bias of about −9 ppb at the locations where tropospheric vertical profiles will be measured by IAGOS. The C-IFS model, however, has a lower random error (6.5 ppb) than TOMCAT (12.8 ppb). These values are well within the minimum desired accuracy and precision of satellite total column XCH4 retrievals (10 ppb and 34 ppb, respectively). In comparison, the a-priori profile from the University of Leicester Greenhouse Gases Observing Satellite (GOSAT) Proxy XCH4 retrieval and climatology-based data introduce larger random errors in the total column, being limited in spatial coverage and temporal variability. Furthermore, we find that the bias in the models varies with latitude and season. Therefore, applying appropriate bias correction to the model fields before using them for profile extension is expected to further decrease the error contributed by the stratospheric part of the profile to the total column.

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Ammonia in the summertime Arctic marine boundary layer: sources, sinks, and implications

Atmospheric Chemistry and Physics ◽

10.5194/acp-16-1937-2016 ◽

2016 ◽

Vol 16 (4) ◽

pp. 1937-1953 ◽

Cited By ~ 36

Author(s):

Gregory R. Wentworth ◽

Jennifer G. Murphy ◽

Betty Croft ◽

Randall V. Martin ◽

Jeffrey R. Pierce ◽

...

Keyword(s):

Boundary Layer ◽

Transport Model ◽

Canadian Arctic ◽

Atmospheric Composition ◽

Chemical Transport Model ◽

Data Set ◽

Baffin Bay ◽

Melt Ponds ◽

Ambient Nh3 ◽

The Impact

Abstract. Continuous hourly measurements of gas-phase ammonia (NH3(g)) were taken from 13 July to 7 August 2014 on a research cruise throughout Baffin Bay and the eastern Canadian Arctic Archipelago. Concentrations ranged from 30 to 650 ng m−3 (40–870 pptv) with the highest values recorded in Lancaster Sound (74°13′ N, 84°00′ W). Simultaneous measurements of total ammonium ([NHx]), pH and temperature in the ocean and in melt ponds were used to compute the compensation point (χ), which is the ambient NH3(g) concentration at which surface–air fluxes change direction. Ambient NH3(g) was usually several orders of magnitude larger than both χocean and χMP (< 0.4–10 ng m3) indicating these surface pools are net sinks of NH3. Flux calculations estimate average net downward fluxes of 1.4 and 1.1 ng m−2 s−1 for the open ocean and melt ponds, respectively. Sufficient NH3(g) was present to neutralize non-sea-salt sulfate (nss-SO42−) in the boundary layer during most of the study. This finding was corroborated with a historical data set of PM2.5 composition from Alert, Nunavut (82°30′ N, 62°20′ W) wherein the median ratio of NH4+/nss-SO42− equivalents was greater than 0.75 in June, July and August. The GEOS-Chem chemical transport model was employed to examine the impact of NH3(g) emissions from seabird guano on boundary-layer composition and nss-SO42− neutralization. A GEOS-Chem simulation without seabird emissions underestimated boundary layer NH3(g) by several orders of magnitude and yielded highly acidic aerosol. A simulation that included seabird NH3 emissions was in better agreement with observations for both NH3(g) concentrations and nss-SO42− neutralization. This is strong evidence that seabird colonies are significant sources of NH3 in the summertime Arctic, and are ubiquitous enough to impact atmospheric composition across the entire Baffin Bay region. Large wildfires in the Northwest Territories were likely an important source of NH3, but their influence was probably limited to the Central Canadian Arctic. Implications of seabird-derived N-deposition to terrestrial and aquatic ecosystems are also discussed.

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Measured and modelled air quality trends in Italy over the period 2003–2010

10.5194/acp-2020-1058 ◽

2021 ◽

Author(s):

Ilaria D'Elia ◽

Gino Briganti ◽

Lina Vitali ◽

Antonio Piersanti ◽

Gaia Righini ◽

...

Keyword(s):

Air Pollution ◽

Air Quality ◽

Air Pollutants ◽

Transport Model ◽

Statistical Significance ◽

Average Concentration ◽

Chemical Transport Model ◽

Spatial Coverage ◽

Significant Downward Trend ◽

The Impact

Abstract. Air pollution harms human health and the environment. Several regulatory efforts and different actions have been taken in the last decades by authorities. Air quality trend analysis represents a valid tool in assessing the impact of these actions taken both at national and local levels. This paper presents for the first time the capability of the Italian national chemical transport model, AMS-MINNI, in capturing the observed concentration trends of three air pollutants, NO2, inhalable particles having diameter less than 10 micrometres (PM10) and O3, in Italy over the period 2003–2010. We firstly analyse the model performance finding it in line with the state of the art of regional models applications. The modelled trends result in a general significant downward trend for the three pollutants and, in comparison with observations, the values of the simulated slopes show the same magnitude for NO2 (in the range −3.0 ÷ −0.5 ug m−3 yr−1), while a smaller variability is detected for PM10 (−1.5 ÷ −0.5 ug m−3 yr−1) and O3-maximum daily 8-hour average concentration (−2.0 ÷ −0.5 ug m−3 yr−1). As a general result, we find a good agreement between modelled and observed trends; moreover, the model allowed to extend both the spatial coverage and the statistical significance of pollutants' concentrations trends with respect to observations, in particular for NO2. We also conduct a qualitative attempt to correlate the temporal concentration trends to meteorological and emission variability. Since no clear tendency in yearly meteorological anomalies (temperature, precipitation, geopotential height) was observed for the period investigated, we focus the discussion of concentrations trends on emissions variations. We point out that, due to the complex links between precursors emissions and air pollutants concentrations, emission reductions do not always result in a corresponding decrease in atmospheric concentrations, especially for those pollutants that are formed in the atmosphere such as O3 and the major fraction of PM10. These complex phenomena are still uncertain and their understanding is of the utmost importance in planning future policies for reducing air pollution and its impacts on health and ecosystems.

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Development and implementation of a new biomass burning emissions injection height scheme (BBEIH v1.0) for the GEOS-Chem model (v9-01-01)

Geoscientific Model Development ◽

10.5194/gmd-11-4103-2018 ◽

2018 ◽

Vol 11 (10) ◽

pp. 4103-4116 ◽

Cited By ~ 15

Author(s):

Liye Zhu ◽

Maria Val Martin ◽

Luciana V. Gatti ◽

Ralph Kahn ◽

Arsineh Hecobian ◽

...

Keyword(s):

Biomass Burning ◽

Amazon Basin ◽

Transport Model ◽

Meteorological Data ◽

Atmospheric Composition ◽

Chemical Transport Model ◽

Model Driven ◽

Injection Scheme ◽

Large Fires ◽

The Impact

Abstract. Biomass burning is a significant source of trace gases and aerosols to the atmosphere, and the evolution of these species depends acutely on where they are injected into the atmosphere. GEOS-Chem is a chemical transport model driven by assimilated meteorological data that is used to probe a variety of scientific questions related to atmospheric composition, including the role of biomass burning. This paper presents the development and implementation of a new global biomass burning emissions injection scheme in the GEOS-Chem model. The new injection scheme is based on monthly gridded Multi-angle Imaging SpectroRadiometer (MISR) global plume-height stereoscopic observations in 2008. To provide specific examples of the impact of the model updates, we compare the output from simulations with and without the new MISR-based injection height scheme to several sets of observations from regions with active fires. Our comparisons with Arctic Research on the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) aircraft observations show that the updated injection height scheme can improve the ability of the model to simulate the vertical distribution of peroxyacetyl nitrate (PAN) and carbon monoxide (CO) over North American boreal regions in summer. We also compare a simulation for October 2010 and 2011 to vertical profiles of CO over the Amazon Basin. When coupled with larger emission factors for CO, a simulation that includes the new injection scheme also better matches selected observations in this region. Finally, the improved injection height improves the simulation of monthly mean surface CO over California during July 2008, a period with large fires.

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Total column water vapor retrieval for GOME-2 visible blue observations

10.5194/amt-2020-96 ◽

2020 ◽

Author(s):

Ka Lok Chan ◽

Pieter Valks ◽

Sander Slijkhuis ◽

Claas Köhler ◽

Diego Loyola

Keyword(s):

Water Vapor ◽

Transport Model ◽

A Priori ◽

Spectral Band ◽

Atmospheric Composition ◽

Retrieval Algorithm ◽

Blue Band ◽

Data Set ◽

Ozone Monitoring ◽

Total Column

Abstract. We present a new total column water vapor (TCWV) retrieval algorithm in the visible blue spectral band for the Global Ozone Monitoring Experience 2 (GOME-2) instruments on board the EUMETSAT MetOp satellites. The blue band algorithm allows retrieval of water vapor from sensors which do not cover longer wavelengths, such as Ozone Monitoring Instrument (OMI) and the Copernicus atmospheric composition missions Sentinel-5 Precursor (S5P), Sentinel-4 (S4) and Sentinel-5 (S5). The blue band algorithm uses the differential optical absorption spectroscopic (DOAS) technique to retrieve water vapor slant columns. The measured water vapor slant columns are converted to vertical column using air mass factors (AMFs). The new algorithm has an iterative optimization module to dynamically find the optimal a priori water vapor profile. This makes it better suited for climate studies than usual satellite retrievals with static a priori or vertical profile information from chemistry transport model (CTM). The dynamic a priori algorithm makes use of the fact that the vertical distribution of water vapor is strongly correlated to the total column. The new algorithm is applied to GOME-2A and GOME-2B observations to retrieve TCWV. The data set is validated by comparing to the operational product retrieved in the red spectral band, sun-photometer and radiosonde measurements. Water vapor columns retrieved in the blue band are in good agreement with the other data sets, indicating that the new algorithm derives precise results, and can be used for the current and forthcoming Copernicus Sentinel missions S4 and S5.

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Total column water vapor retrieval for Global Ozone Monitoring Experience-2 (GOME-2) visible blue observations

Atmospheric Measurement Techniques ◽

10.5194/amt-13-4169-2020 ◽

2020 ◽

Vol 13 (8) ◽

pp. 4169-4193

Author(s):

Ka Lok Chan ◽

Pieter Valks ◽

Sander Slijkhuis ◽

Claas Köhler ◽

Diego Loyola

Keyword(s):

Water Vapor ◽

Transport Model ◽

A Priori ◽

Spectral Band ◽

Atmospheric Composition ◽

Retrieval Algorithm ◽

Blue Band ◽

Data Set ◽

Ozone Monitoring ◽

Total Column

Abstract. We present a new total column water vapor (TCWV) retrieval algorithm in the visible blue spectral band for the Global Ozone Monitoring Experience 2 (GOME-2) instruments on board the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Metop satellites. The blue band algorithm allows the retrieval of water vapor from sensors which do not cover longer wavelengths, such as the Ozone Monitoring Instrument (OMI) and the Copernicus atmospheric composition missions Sentinel-5 Precursor (S5P), Sentinel-4 (S4) and Sentinel-5 (S5). The blue band algorithm uses the differential optical absorption spectroscopic (DOAS) technique to retrieve water vapor slant columns. The measured water vapor slant columns are converted to vertical columns using air mass factors (AMFs). The new algorithm has an iterative optimization module to dynamically find the optimal a priori water vapor profile. This makes it better suited for climate studies than usual satellite retrievals with static a priori or vertical profile information from the chemistry transport model (CTM). The dynamic a priori algorithm makes use of the fact that the vertical distribution of water vapor is strongly correlated to the total column. The new algorithm is applied to GOME-2A and GOME-2B observations to retrieve TCWV. The data set is validated by comparing it to the operational product retrieved in the red spectral band, sun photometer and radiosonde measurements. Water vapor columns retrieved in the blue band are in good agreement with the other data sets, indicating that the new algorithm derives precise results and can be used for the current and forthcoming Copernicus Sentinel missions S4 and S5.

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NDACC harmonized formaldehyde time series from 21 FTIR stations covering a wide range of column abundances

Atmospheric Measurement Techniques ◽

10.5194/amt-11-5049-2018 ◽

2018 ◽

Vol 11 (9) ◽

pp. 5049-5073 ◽

Cited By ~ 9

Author(s):

Corinne Vigouroux ◽

Carlos Augusto Bauer Aquino ◽

Maite Bauwens ◽

Cornelis Becker ◽

Thomas Blumenstock ◽

...

Keyword(s):

Time Series ◽

Transport Model ◽

Limit Of Detection ◽

Atmospheric Composition ◽

Good Precision ◽

Data Set ◽

Spatial Coverage ◽

Combining Data ◽

Wide Range ◽

Total Column

Abstract. Among the more than 20 ground-based FTIR (Fourier transform infrared) stations currently operating around the globe, only a few have provided formaldehyde (HCHO) total column time series until now. Although several independent studies have shown that the FTIR measurements can provide formaldehyde total columns with good precision, the spatial coverage has not been optimal for providing good diagnostics for satellite or model validation. Furthermore, these past studies used different retrieval settings, and biases as large as 50 % can be observed in the HCHO total columns depending on these retrieval choices, which is also a weakness for validation studies combining data from different ground-based stations.For the present work, the HCHO retrieval settings have been optimized based on experience gained from past studies and have been applied consistently at the 21 participating stations. Most of them are either part of the Network for the Detection of Atmospheric Composition Change (NDACC) or under consideration for membership. We provide the harmonized settings and a characterization of the HCHO FTIR products. Depending on the station, the total systematic and random uncertainties of an individual HCHO total column measurement lie between 12 % and 27 % and between 1 and 11×1014 molec cm−2, respectively. The median values among all stations are 13 % and 2.9×1014 molec cm−2 for the total systematic and random uncertainties.This unprecedented harmonized formaldehyde data set from 21 ground-based FTIR stations is presented and its comparison with a global chemistry transport model shows consistency in absolute values as well as in seasonal cycles. The network covers very different concentration levels of formaldehyde, from very clean levels at the limit of detection (few 1013 molec cm−2) to highly polluted levels (7×1016 molec cm−2). Because the measurements can be made at any time during daylight, the diurnal cycle can be observed and is found to be significant at many stations. These HCHO time series, some of them starting in the 1990s, are crucial for past and present satellite validation and will be extended in the coming years for the next generation of satellite missions.

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Tropospheric chemistry in the integrated forecasting system of ECMWF

Geoscientific Model Development Discussions ◽

10.5194/gmdd-7-7733-2014 ◽

2014 ◽

Vol 7 (6) ◽

pp. 7733-7803 ◽

Cited By ~ 6

Author(s):

J. Flemming ◽

V. Huijnen ◽

J. Arteta ◽

P. Bechtold ◽

A. Beljaars ◽

...

Keyword(s):

Atmospheric Chemistry ◽

Transport Model ◽

Nitrogen Monoxide ◽

Coupled System ◽

Tropospheric Chemistry ◽

Chemical Mechanism ◽

Atmospheric Composition ◽

Chemical Transport Model ◽

Data Set ◽

Forecasting System

Abstract. A representation of atmospheric chemistry has been included in the Integrated Forecasting System (IFS) of the European Centre for Medium-range Weather Forecasts (ECMWF). The new chemistry modules complement the aerosol modules of the IFS for atmospheric composition, which is named C-IFS. C-IFS for chemistry supersedes a coupled system, in which the Chemical Transport Model (CTM) Model for OZone and Related chemical Tracers 3 was two-way coupled to the IFS (IFS-MOZART). This paper contains a description of the new on-line implementation, an evaluation with observations and a comparison of the performance of C-IFS with MOZART and with a re-analysis of atmospheric composition produced by IFS-MOZART within the Monitoring Atmospheric Composition and Climate (MACC) project. The chemical mechanism of C-IFS is an extended version of the Carbon Bond 2005 (CB05) chemical mechanism as implemented in the CTM Transport Model 5 (TM5). CB05 describes tropospheric chemistry with 54 species and 126 reactions. Wet deposition and lightning nitrogen monoxide (NO) emissions are modelled in C-IFS using the detailed input of the IFS physics package. A one-year simulation by C-IFS, MOZART and the MACC re-analysis is evaluated against ozonesondes, carbon monoxide (CO) aircraft profiles, European surface observations of ozone (O3), CO, sulphur dioxide (SO2) and nitrogen dioxide (NO2) as well as satellite retrievals of CO, tropospheric NO2 and formaldehyde. Anthropogenic emissions from the MACC/CityZen (MACCity) inventory and biomass burning emissions from the Global Fire Assimilation System (GFAS) data set were used in the simulations by both C-IFS and MOZART. C-IFS (CB05) showed an improved performance with respect to MOZART for CO, upper tropospheric O3, winter time SO2 and was of a similar accuracy for other evaluated species. C-IFS (CB05) is about ten times more computationally efficient than IFS-MOZART.

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Comparison between the assimilation of IASI Level 2 retrievals and Level 1 radiances for ozone reanalyses

10.5194/amt-2018-426 ◽

2019 ◽

Author(s):

Emanuele Emili ◽

Brice Barret ◽

Eric Le Flochmoën ◽

Daniel Cariolle

Keyword(s):

Transport Model ◽

Atmospheric Composition ◽

Chemical Transport Model ◽

Atmospheric Sounding ◽

Level 1 ◽

The Tropics ◽

L1 And L2 ◽

The Impact ◽

Level 2

Abstract. The prior information used for Level 2 (L2) retrievals in the thermal infrared can influence the quality of the retrievals themselves and, therefore, their further assimilation in atmospheric composition models. In this study we evaluate the differences between assimilating L2 ozone profiles and Level 1 (L1) radiances from the Infrared Atmospheric Sounding Interferometer (IASI). We minimized potential differences between the two approaches by employing the same radiative transfer code (RTTOV) and a very similar setup for both the L2 retrievals (1D-Var) and the L1 assimilation (3D-Var). We computed hourly 3D-Var reanalyses assimilating respectively L1 and L2 data in the chemical transport model MOCAGE and compared the resulting O3 fields among each other and against ozonesondes. We also evaluated the joint assimilation of limb measurements from the Microwave Limb Sounder (MLS) on top of IASI to assess the impact of stratospheric O3 on tropospheric reanalyses. Results indicate that significant differences can arise between L2 and L1 assimilation, especially in regions where the L2 prior is biased (at the tropics and in the southern hemisphere in this study). L1 and L2 assimilation give instead very similar results in the northern hemisphere, especially when MLS measurements are used to constrain the stratospheric O3 column. We conclude this study by listing remaining issues that are common to both the L1 and L2 approaches and that deserve further research.

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Development and implementation of a new biomass burning emissions injection height scheme for the GEOSChem model

10.5194/gmd-2018-93 ◽

2018 ◽

Cited By ~ 1

Author(s):

Liye Zhu ◽

Maria Val Martin ◽

Arsineh Hecobian ◽

Luciana V. Gatti ◽

Ralph Kahn ◽

...

Keyword(s):

Biomass Burning ◽

Amazon Basin ◽

Transport Model ◽

Meteorological Data ◽

Atmospheric Composition ◽

Chemical Transport Model ◽

Model Driven ◽

Injection Scheme ◽

Large Fires ◽

The Impact

Abstract. Biomass burning is a significant source of trace gases and aerosols to the atmosphere, and the evolution of these species depends acutely on where they are injected into the atmosphere. GEOS-Chem is a chemical transport model driven by assimilated meteorological data that is used to probe a variety of scientific questions related to atmospheric composition, including the role of biomass burning. This paper presents the development and implementation of a new global biomass burning emissions injection scheme in the GEOS-Chem model. The new injection scheme is based on monthly gridded Multi-Angle Imaging Spectro Radiometer (MISR) global plume-height stereoscopic observations in 2008. To provide specific examples of the impact of the model updates, we compare the output from simulations with and without the new MISR-based injection height scheme to several sets of observations from regions with active fires. Our comparisons with ARCTAS aircraft observations show that the updated injection height scheme improves the ability of the model to simulate the vertical distribution of peroxyacetyl nitrate (PAN) and carbon monoxide (CO) over North American boreal regions in summer. We also compare a simulation for October 2010 and 2011 to vertical profiles of CO over the Amazon Basin. When coupled with larger emission factors for CO, a simulation that includes the new injection scheme also better matches selected observations in this region. Finally the improved injection height also improves the simulation of monthly mean surface CO over California during July 2008, a period with large fires.

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