scholarly journals Updated tropospheric chemistry reanalysis and emission estimates, TCR-2, for 2005–2018

2020 ◽  
Vol 12 (3) ◽  
pp. 2223-2259 ◽  
Author(s):  
Kazuyuki Miyazaki ◽  
Kevin Bowman ◽  
Takashi Sekiya ◽  
Henk Eskes ◽  
Folkert Boersma ◽  
...  
Keyword(s):  
Transport Model ◽  
Horizontal Resolution ◽  
Tropospheric Chemistry ◽  
Atmospheric Composition ◽  
Data Sets ◽  
Vertical Profiles ◽  
Chemical Transport Model ◽  
Near Surface ◽  
Key Species

Abstract. This study presents the results from the Tropospheric Chemistry Reanalysis version 2 (TCR-2) for the period 2005–2018 at 1.1∘ horizontal resolution obtained from the assimilation of multiple updated satellite measurements of ozone, CO, NO2, HNO3, and SO2 from the OMI, SCIAMACHY, GOME-2, TES, MLS, and MOPITT satellite instruments. The reanalysis calculation was conducted using a global chemical transport model MIROC-CHASER and an ensemble Kalman filter technique that optimizes both chemical concentrations of various species and emissions of several precursors, which was efficient for the correction of the entire tropospheric profile of various species and its year-to-year variations. Comparisons against independent aircraft, satellite, and ozonesonde observations demonstrate the quality of the reanalysis fields for numerous key species on regional and global scales, as well as for seasonal, yearly, and decadal scales, from the surface to the lower stratosphere. The multi-constituent data assimilation brought the model vertical profiles and interhemispheric gradient of OH closer to observational estimates, which was important in improving the description of the oxidation capacity of the atmosphere and thus vertical profiles of various species. The evaluation results demonstrate the capability of the chemical reanalysis to improve understanding of the processes controlling variations in atmospheric composition, including long-term changes in near-surface air quality and emissions. The estimated emissions can be employed for the elucidation of detailed distributions of the anthropogenic and biomass burning emissions of co-emitted species (NOx, CO, SO2) in all major regions, as well as their seasonal and decadal variabilities. The data sets are available at https://doi.org/10.25966/9qgv-fe81 (Miyazaki et al., 2019a).

scholarly journals An updated tropospheric chemistry reanalysis and emission estimates, TCR-2, for 2005–2018

2020 ◽  
Author(s):  
Kazuyuki Miyazaki ◽  
Kevin Bowman ◽  
Takashi Sekiya ◽  
Henk Eskes ◽  
Folkert Boersma ◽  
...  
Keyword(s):  
Transport Model ◽  
Horizontal Resolution ◽  
Tropospheric Chemistry ◽  
Atmospheric Composition ◽  
Vertical Profiles ◽  
Chemical Transport Model ◽  
Near Surface ◽  
Key Species

Abstract. This study presents the results from the Tropospheric Chemistry Reanalysis version 2 (TCR-2) for the period 2005–2018 at 1.1° horizontal resolution obtained from the assimilation of multiple updated satellite measurements of ozone, CO, NO2, HNO3, and SO2 from the OMI, SCIAMACHY, GOME-2, TES, MLS, and MOPITT satellite instruments. The reanalysis calculation was conducted using a global chemical transport model MIROC-CHASER and an ensemble Kalman filter technique that optimizes both chemical concentrations of various species and emissions of several precursors, which was efficient for the correction of the entire tropospheric profile of various species and its year-to-year variations. Comparisons against independent aircraft, satellite, and ozonesonde observations demonstrate the quality of the reanalysis fields for numerous key species on regional and global scales, as well as for seasonal, yearly, and decadal scales, from the surface to the lower stratosphere. The multi-constituent data assimilation brought the model vertical profiles and inter-hemispheric gradient of OH closer to observational estimates, which played an important role in improving the description of the oxidation capacity of the atmosphere and thus vertical profiles of various species. The evaluation results demonstrate the capability of the reanalysis products to improve understanding of the processes controlling variations in atmospheric composition, including long-term changes in near-surface air quality and emissions. The estimated emissions can be employed for the elucidation of detailed distributions of the anthropogenic and biomass-burning emissions of co-emitted species (NOx, CO, SO2) in all major regions, as well as their seasonal, and decadal variabilities. The datasets are available at: https://doi.org/10.25966/9qgv-fe81 (Miyazaki et al., 2019a).

scholarly journals NO<sub>2</sub> climatology in the northern subtropical region: diurnal, seasonal and interannual variability

2008 ◽  
Vol 8 (6) ◽  
pp. 1635-1648 ◽  
Author(s):  
M. Gil ◽  
M. Yela ◽  
L. N. Gunn ◽  
A. Richter ◽  
I. Alonso ◽  
...  
Keyword(s):  
Interannual Variability ◽  
Transport Model ◽  
Atmospheric Composition ◽  
Data Sets ◽  
Chemical Transport Model ◽  
Vertical Column ◽  
Stratospheric Temperature ◽  
The Hours ◽  
Vertical Column Density

Abstract. Daily NO2 vertical column density (VCD) has been routinely measured by zenith sky spectroscopy at the subtropical station of Izaña (28° N, 16° W) since 1993 in the framework of the Network for the Detection of Atmospheric Composition Change (NDACC). Based on 14 years of data the first low latitude NO2 VCD climatology has been established and the main characteristics from short timescales of one day to interannual variability are presented. Instrumental descriptions and different sources of errors are described in detail. The observed diurnal cycle follows that expected by gas-phase NOx chemistry, as can be shown by the good agreement with a vertically integrated chemical box model, and is modulated by solar radiation. The seasonal evolution departs from the phase of the hours of daylight, indicating the signature of upper stratospheric temperature changes. From the data record (1993–2006) no significant long-term trends in NO2 VCD can be inferred. Comparison of the ground-based data sets with nadir-viewing satellite spectrometers shows excellent agreement for SCIAMACHY with differences between both datasets of 1.1%. GOME displays unrealistic features with the largest discrepancies during summer. The ground-based data are compared with long-term output of the SLIMCAT 3-D chemical transport model (CTM). The basic model, forced by ECMWF (ERA-40) analyses, captures the observed NO2 annual cycle but significantly underestimates the spring/summer maximum (by 12% at sunset and up to 25% at sunrise). In a model run which uses assimilation of satellite CH4 profiles to constrain the model long-lived tracers the agreement is significantly improved. This improvement in modelled column NO2 is due to better modelled NOy profiles and points to transport errors in the ECMWF ERA-40 reanalyses.

scholarly journals NO<sub>2</sub> climatology in the northern subtropical region: diurnal, seasonal and interannual variability

2007 ◽  
Vol 7 (5) ◽  
pp. 15067-15103 ◽  
Author(s):  
M. Gil ◽  
M. Yela ◽  
L. N. Gunn ◽  
A. Richter ◽  
I. Alonso ◽  
...  
Keyword(s):  
Transport Model ◽  
Atmospheric Composition ◽  
Data Sets ◽  
Chemical Transport Model ◽  
Vertical Column ◽  
Basic Model ◽  
Stratospheric Temperature ◽  
The Hours ◽  
Vertical Column Density

Abstract. Daily NO2 vertical column density (VCD) has been routinely measured by zenith sky spectroscopy at the subtropical station of Izaña (28° N, 16° W) since 1993 in the framework of the Network for the Detection of Atmospheric Composition Change (NDACC). Based on 14 years of data the first low latitudes NO2 VCD climatology has been established and the main characteristics from short scales of one day to inter-annual variability are presented. Instrumental descriptions and different source of errors are described in detail. The observed diurnal cycle follows that expected by gas-phase NOx chemistry, as can be shown by the good agreement with a vertically integrated chemical box model, and is modulated by solar radiation. The seasonal evolution departs from the phase of the hours of daylight, showing the signature of upper stratospheric temperature changes. From the data record no significant long-term trends in NO2 VCD can be inferred. Comparison of the ground-based data sets with nadir looking satellite spectrometers shows excellent agreement for SCIAMACHY with differences between both datasets of 1.1%. GOME displays unrealistic features with largest discrepancies during summer. The ground-based data are compared with long-term output of the SLIMCAT 3-D chemical transport model (CTM). The basic model, forced by ECMWF (ERA-40) analyses, captures the observed NO2 annual cycle but significantly underestimates the spring/summer maximum. In a model run which uses assimilation of satellite CH4 profiles to constrain the model long-lived tracers the agreement is significantly improved. This improvement in modelled column NO2 is due to better modelled NOy profiles and points to transport errors in the ECMWF ERA-40 reanalyses.

scholarly journals A tropospheric chemistry reanalysis for the years 2005–2012 based on an assimilation of OMI, MLS, TES and MOPITT satellite data

2015 ◽  
Vol 15 (6) ◽  
pp. 8687-8770
Author(s):  
K. Miyazaki ◽  
H. J. Eskes ◽  
K. Sudo
Keyword(s):  
Transport Model ◽  
Lower Troposphere ◽  
Tropospheric Chemistry ◽  
Atmospheric Environment ◽  
Data Sets ◽  
Chemical Transport Model ◽  
Observational Estimate ◽  
Multiple Species ◽  
Chemical Fields

Abstract. We present the results from an eight-year tropospheric chemistry reanalysis for the period 2005–2012 obtained by assimilating multiple retrieval data sets from the OMI, MLS, TES, and MOPITT satellite instruments. The reanalysis calculation was conducted using a global chemical transport model and an ensemble Kalman filter technique that simultaneously optimises the chemical concentrations of various species and emissions of several precursors. The optimisation of both the concentration and the emission fields is an efficient method to correct the entire tropospheric profile and its year-to-year variations, and to adjust various tracers chemically linked to the species assimilated. Comparisons against independent aircraft, satellite, and ozonesonde observations demonstrate the quality of the analysed O3, NO2, and CO concentrations on regional and global scales and for both seasonal and year-to-year variations from the lower troposphere to the lower stratosphere. The data assimilation statistics imply persistent reduction of model error and improved representation of emission variability, but also show that discontinuities in the availability of the measurements lead to a degradation of the reanalysis. The decrease in the number of assimilated measurements increased the ozonesonde minus analysis difference after 2010 and caused spurious variations in the estimated emissions. The Northern/Southern Hemisphere OH ratio was modified considerably due to the multiple species assimilation and became closer to an observational estimate, which played an important role in propagating observational information among various chemical fields and affected the emission estimates. The consistent concentration and emission products provide unique information on year-to-year variations of the atmospheric environment.

scholarly journals ML-TOMCAT: machine-learning-based satellite-corrected global stratospheric ozone profile data set from a chemical transport model

2021 ◽  
Vol 13 (12) ◽  
pp. 5711-5729
Author(s):  
Sandip S. Dhomse ◽  
Carlo Arosio ◽  
Wuhu Feng ◽  
Alexei Rozanov ◽  
Mark Weber ◽  
...  
Keyword(s):  
Transport Model ◽  
Stratospheric Ozone ◽  
Chemical Transport ◽  
Data Sets ◽  
Chemical Transport Model ◽  
Profile Data ◽  
Data Set ◽  
Ozone Profile ◽  
Satellite Instruments

Abstract. High-quality stratospheric ozone profile data sets are a key requirement for accurate quantification and attribution of long-term ozone changes. Satellite instruments provide stratospheric ozone profile measurements over typical mission durations of 5–15 years. Various methodologies have then been applied to merge and homogenise the different satellite data in order to create long-term observation-based ozone profile data sets with minimal data gaps. However, individual satellite instruments use different measurement methods, sampling patterns and retrieval algorithms which complicate the merging of these different data sets. In contrast, atmospheric chemical models can produce chemically consistent long-term ozone simulations based on specified changes in external forcings, but they are subject to the deficiencies associated with incomplete understanding of complex atmospheric processes and uncertain photochemical parameters. Here, we use chemically self-consistent output from the TOMCAT 3-D chemical transport model (CTM) and a random-forest (RF) ensemble learning method to create a merged 42-year (1979–2020) stratospheric ozone profile data set (ML-TOMCAT V1.0). The underlying CTM simulation was forced by meteorological reanalyses, specified trends in long-lived source gases, solar flux and aerosol variations. The RF is trained using the Stratospheric Water and OzOne Satellite Homogenized (SWOOSH) data set over the time periods of the Microwave Limb Sounder (MLS) from the Upper Atmosphere Research Satellite (UARS) (1991–1998) and Aura (2005–2016) missions. We find that ML-TOMCAT shows excellent agreement with available independent satellite-based data sets which use pressure as a vertical coordinate (e.g. GOZCARDS, SWOOSH for non-MLS periods) but weaker agreement with the data sets which are altitude-based (e.g. SAGE-CCI-OMPS, SCIAMACHY-OMPS). We find that at almost all stratospheric levels ML-TOMCAT ozone concentrations are well within uncertainties of the observational data sets. The ML-TOMCAT (V1.0) data set is ideally suited for the evaluation of chemical model ozone profiles from the tropopause to 0.1 hPa and is freely available via https://doi.org/10.5281/zenodo.5651194 (Dhomse et al., 2021).

scholarly journals Tropospheric chemistry in the integrated forecasting system of ECMWF

2014 ◽  
Vol 7 (6) ◽  
pp. 7733-7803 ◽  
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.

scholarly journals Description of the long-term ozone data series obtained from different instrumental techniques at a single location: the Observatoire de Haute-Provence (43.9°N, 5.7°E)

2000 ◽  
Vol 18 (10) ◽  
pp. 1325-1339 ◽  
Author(s):  
M. Guirlet ◽  
P. Keckhut ◽  
S. Godin ◽  
G. Mégie
Keyword(s):  
Middle Atmosphere ◽  
Stratospheric Ozone ◽  
Sampling Rate ◽  
Atmospheric Composition ◽  
Structure Evolution ◽  
Data Series ◽  
Data Sets ◽  
Vertical Profiles ◽  
Good Agreement

Abstract. A description of the long-term data series of stratospheric ozone at the Observatoire de Haute-Provence is presented. At this station, data sets with temporal length of a decade or more are provided in the framework of the Network for Detection of Stratospheric Change by ground-based experiments: Dobson spectrophotometer (in both column and Umkehr mode), lidar and ozonesondes. The data time series obtained from these various instruments operated simultaneously at a single site and complemented by SAGE II space-borne measurements are first described with respect to instrumental uncertainties, sampling rate and time evolution. These data series are then compared to each other in terms of sampling rate and average vertical profiles. The difference between the mean ozone profiles of the data sets can partly be explained by the different sampling rate of the instruments. Using the overlap and the complementarity of the various data sets, a preliminary estimate of the long-term evolution of ozone over the last decade over Southern France is conducted. Trend values for both total column and vertical profiles are derived using the multi-regression statistical model AMOUNTS O3. In the 25–40 km altitude range, a similar ozone decrease from –4% to –10% is observed from lidar, Umkehr and SAGE II data series in good agreement with previous estimates. In the lower stratosphere (15–25 km), large negative trends in the ozone vertical profile are observed. In addition, the negative trend of –5.4% in total ozone inferred from the Dobson measurements over the period 1983–1995 is in good agreement with the integrated trend profile.Key words: Atmospheric composition and structure (evolution of the atmosphere; middle atmosphere – composition and chemistry; instruments and techniques)

scholarly journals A tropospheric chemistry reanalysis for the years 2005–2012 based on an assimilation of OMI, MLS, TES, and MOPITT satellite data

2015 ◽  
Vol 15 (14) ◽  
pp. 8315-8348 ◽  
Author(s):  
K. Miyazaki ◽  
H. J. Eskes ◽  
K. Sudo
Keyword(s):  
Transport Model ◽  
Lower Troposphere ◽  
Tropospheric Chemistry ◽  
Atmospheric Environment ◽  
Data Sets ◽  
Chemical Transport Model ◽  
Multiple Data ◽  
Multiple Data Sets ◽  
Observational Estimate ◽  
Multiple Species

Abstract. We present the results from an 8-year tropospheric chemistry reanalysis for the period 2005–2012 obtained by assimilating multiple data sets from the OMI, MLS, TES, and MOPITT satellite instruments. The reanalysis calculation was conducted using a global chemical transport model and an ensemble Kalman filter technique that simultaneously optimises the chemical concentrations of various species and emissions of several precursors. The optimisation of both the concentration and the emission fields is an efficient method to correct the entire tropospheric profile and its year-to-year variations, and to adjust various tracers chemically linked to the species assimilated. Comparisons against independent aircraft, satellite, and ozonesonde observations demonstrate the quality of the analysed O3, NO2, and CO concentrations on regional and global scales and for both seasonal and year-to-year variations from the lower troposphere to the lower stratosphere. The data assimilation statistics imply persistent reduction of model error and improved representation of emission variability, but they also show that discontinuities in the availability of the measurements lead to a degradation of the reanalysis. The decrease in the number of assimilated measurements increased the ozonesonde-minus-analysis difference after 2010 and caused spurious variations in the estimated emissions. The Northern/Southern Hemisphere OH ratio was modified considerably due to the multiple-species assimilation and became closer to an observational estimate, which played an important role in propagating observational information among various chemical fields and affected the emission estimates. The consistent concentration and emission products provide unique information on year-to-year variations in the atmospheric environment.

scholarly journals Tropospheric chemistry in the Integrated Forecasting System of ECMWF

2015 ◽  
Vol 8 (4) ◽  
pp. 975-1003 ◽  
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 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 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 1 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, sulfur 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, and wintertime SO2, and was of a similar accuracy for other evaluated species. C-IFS (CB05) is about 10 times more computationally efficient than IFS-MOZART.

Machine-Learning-Based Satellite-Corrected Global Stratospheric Ozone Profile Dataset from a Chemical Transport Model

2021 ◽  
Author(s):  
Sandip Dhomse ◽  
Martyn Chipperfield
Keyword(s):  
Machine Learning ◽  
Transport Model ◽  
Stratospheric Ozone ◽  
Chemical Transport ◽  
Recovery Phase ◽  
Horizontal Resolution ◽  
Chemical Transport Model ◽  
High Quality ◽  
Ozone Profile

&lt;p&gt;High quality global ozone profile datasets are necessary to monitor changes in stratospheric ozone. Hence, various methodologies have been used to merge and homogenise different satellite datasets in order to create long-term observation-based ozone profile datasets with minimal data gaps. However, individual satellite instruments use different measurement methods and retrieval algorithms that complicate the merging of these different datasets. Furthermore, although atmospheric chemical models are able to simulate chemically consistent long-term datasets, they are prone to the deficiencies associated with the computationally expensive processes that are generally represented by simplified parameterisations or uncertain parameters.&lt;/p&gt;&lt;p&gt;Here, we use chemically consistent output from a 3-D Chemical Transport Model (CTM, TOMCAT) and an ensemble of three machine learning (ML) algorithms (Adaboost, GradBoost, Random Forest), to create a 42-year (1979-2020) stratospheric ozone profile dataset. The ML algorithms are primarily trained using the Stratospheric Water and OzOne Satellite Homogenized (SWOOSH) dataset by selecting the UARS-MLS (1992-1998) and AURA-MLS (2005-2019) time periods. This ML-corrected version of monthly mean zonal mean TOMCAT (hereafter ML-TOMCAT) ozone profile data is available at both pressure (1000 hPa - 1 hPa) and geometric height (surface to 50 km) levels at about 2.5 degree horizontal resolution.&lt;/p&gt;&lt;p&gt;We will present a detailed evaluation of ML-TOMCAT profiles against range of merged satellite datasets (e.g. GOZCARDS, SAGE-CCI-OMPS, and BVertOzone) as well high quality solar occultation observations (e.g. SAGE-II v7.0 (1984-2005), HALOE v19 (1991-2005) and ACE v4.1 (2004-2020). Overall, ML-TOMCAT shows good agreement with the evaluation datasets but with poorer agreement at low latitudes. We also show that, as in different merged satellite data sets, ML-algorithms show larger spread in the tropical middle stratosphere. Finally, we will present a trend analysis from TOMCAT and ML-TOMCAT profiles for the post-1998 ozone recovery phase.&lt;/p&gt;

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