scholarly journals Coupled Stratospheric Chemistry-Meteorology Data Assimilation. Part I: Modeling Chemistry-Dynamics Interactions

2019 ◽  
Author(s):  
Richard Ménard ◽  
Simon Chabrillat ◽  
Alain Robichaud ◽  
Jean de Grandpré ◽  
Martin Charron ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
Transport Model ◽  
Model Simulation ◽  
Weather Prediction ◽  
Coupled Model ◽  
Horizontal Resolution ◽  
Chemical Transport Model ◽  
Stratospheric Chemistry ◽  
Temperature Bias ◽  
Meteorological Analysis

A coupled stratospheric chemistry-meteorology model was developed by combining the Canadian operational weather prediction model Global Environmental Multiscale (GEM) with a comprehensive stratospheric photochemistry model from the Belgian Assimilation System for Chemical ObsErvations (BASCOE). The coupled model was called GEM-BACH for GEM-Belgian Atmospheric CHemistry. The coupling was made across a chemical interface that preserves time splitting while being modular, allowing GEM to run with or without chemistry. An evaluation of the coupling was performed by comparing the coupled model, refreshed by meteorological analyses every 6 hours, against the standard offline chemical transport model (CTM) approach. Results show that the dynamical meteorological consistency between meteorological analysis times far outweighs the error created by the jump resulting from the meteorological analysis increments at regular time intervals, irrespective whether a 3D-Var or 4D-Var meteorological analysis is used. GEM-BACH forecast refreshed by meteorological analyses every 6 hours were compared against independent measurements of temperature, long-lived species, ozone and water vapor. The comparison showed a relatively good agreement throughout the stratosphere except for an upper-level warm temperature bias and an ozone deficit of nearly 15%. Arguments in favor of using the same horizontal resolution for chemistry, meteorology, and meteorological analysis increments are also presented. In particular, the coupled model simulation during an ozone hole event gives better ozone concentrations than a 4D-Var chemical assimilation at a lower resolution.

scholarly journals Coupled Stratospheric Chemistry–Meteorology Data Assimilation. Part I: Physical Background and Coupled Modeling Aspects

Atmosphere ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 150 ◽  
Author(s):  
Richard Ménard ◽  
Simon Chabrillat ◽  
Alain Robichaud ◽  
Jean de Grandpré ◽  
Martin Charron ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
Transport Model ◽  
Model Simulation ◽  
Weather Prediction ◽  
Coupled Model ◽  
Horizontal Resolution ◽  
Chemical Transport Model ◽  
Coupled Modeling ◽  
Stratospheric Chemistry ◽  
Meteorological Analysis

A coupled stratospheric chemistry–meteorology model was developed by combining the Canadian operational weather prediction model Global Environmental Multiscale (GEM) with a comprehensive stratospheric photochemistry model from the Belgian Assimilation System for Chemical ObsErvations (BASCOE). The coupled model was called GEM-BACH for GEM-Belgian Atmospheric CHemistry. The coupling was made across a chemical interface that preserves time-splitting while being modular, allowing GEM to run with or without chemistry. An evaluation of the coupling was performed by comparing the coupled model, refreshed by meteorological analyses every 6 h, against the standard offline chemical transport model (CTM) approach. Results show that the dynamical meteorological consistency between meteorological analysis times far outweighs the error created by the jump resulting from the meteorological analysis increments at regular time intervals, irrespective of whether a 3D-Var or 4D-Var meteorological analysis is used. Arguments in favor of using the same horizontal resolution for chemistry, meteorology, and meteorological and chemical analysis increments are also presented. GEM-BACH forecasts refreshed by meteorological analyses every 6 h were compared against independent measurements of temperature, long-lived species, ozone and water vapor. The comparison showed a relatively good agreement throughout the stratosphere except for an upper-level warm temperature bias and an ozone deficit of nearly 15%. In particular, the coupled model simulation during an ozone hole event gives better ozone concentrations than a 4D-Var chemical assimilation at a lower resolution.

scholarly journals Twelve-month, 12 km resolution North American WRF-Chem v3.4 air quality simulation: performance evaluation

2015 ◽  
Vol 8 (4) ◽  
pp. 957-973 ◽  
Author(s):  
C. W. Tessum ◽  
J. D. Hill ◽  
J. D. Marshall
Keyword(s):  
Health Effects ◽  
Atmospheric Chemistry ◽  
Transport Model ◽  
Predictive Performance ◽  
Horizontal Resolution ◽  
Basis Set ◽  
Chemical Transport Model ◽  
High Concentration ◽  
Annual Average ◽  
Simulation Performance

Abstract. We present results from and evaluate the performance of a 12-month, 12 km horizontal resolution year 2005 air pollution simulation for the contiguous United States using the WRF-Chem (Weather Research and Forecasting with Chemistry) meteorology and chemical transport model (CTM). We employ the 2005 US National Emissions Inventory, the Regional Atmospheric Chemistry Mechanism (RACM), and the Modal Aerosol Dynamics Model for Europe (MADE) with a volatility basis set (VBS) secondary aerosol module. Overall, model performance is comparable to contemporary modeling efforts used for regulatory and health-effects analysis, with an annual average daytime ozone (O3) mean fractional bias (MFB) of 12% and an annual average fine particulate matter (PM2.5) MFB of −1%. WRF-Chem, as configured here, tends to overpredict total PM2.5 at some high concentration locations and generally overpredicts average 24 h O3 concentrations. Performance is better at predicting daytime-average and daily peak O3 concentrations, which are more relevant for regulatory and health effects analyses relative to annual average values. Predictive performance for PM2.5 subspecies is mixed: the model overpredicts particulate sulfate (MFB = 36%), underpredicts particulate nitrate (MFB = −110%) and organic carbon (MFB = −29%), and relatively accurately predicts particulate ammonium (MFB = 3%) and elemental carbon (MFB = 3%), so that the accuracy in total PM2.5 predictions is to some extent a function of offsetting over- and underpredictions of PM2.5 subspecies. Model predictive performance for PM2.5 and its subspecies is in general worse in winter and in the western US than in other seasons and regions, suggesting spatial and temporal opportunities for future WRF-Chem model development and evaluation.

scholarly journals Estimation of the error covariance matrix for IASI radiances and its impact on ozone analyses

2020 ◽  
Author(s):  
Mohammad El Aabaribaoune ◽  
Emanuele Emili ◽  
Vincent Guidard
Keyword(s):  
Covariance Matrix ◽  
Atmospheric Chemistry ◽  
Transport Model ◽  
Weather Prediction ◽  
Computational Cost ◽  
Observation Error ◽  
Chemical Transport Model ◽  
Error Covariance Matrix ◽  
Error Covariance ◽  
Estimated Error

Abstract. In atmospheric chemistry retrievals and data assimilation systems, observation errors associated with satellite radiances are chosen empirically and generally treated as uncorrelated. In this work, we estimate inter-channel error covariances for the Infrared Atmospheric Sounding Interferometer (IASI) and evaluate their impact on ozone assimilation with the chemical transport model MOCAGE (MOdèle de Chime Atmospheric à Grand Echelle). The method used to calculate observation errors is a diagnostic based on the observation and analysis residual statistics already adopted in numerical weather prediction centers. We used a subset of 280 channels covering the spectral range between 980 and 1100 cm−1 to estimate the observation error covariance matrix. We computed hourly 3D-Var analyses and compared the resulting O3 fields against ozonesondes and the measurements provided by the Microwave Limb Sounder (MLS). The results show significant differences between using the estimated error covariance matrix with respect to the empirical diagonal matrix employed in previous studies. The validation of the analyses against independent data reports a significant improvement especially in the tropical stratosphere. The computational cost has also been reduced when the estimated covariance is employed in the assimilation system.

scholarly journals Twelve-month, 12 km resolution North American WRF-Chem v3.4 air quality simulation: performance evaluation

2014 ◽  
Vol 7 (6) ◽  
pp. 8433-8476 ◽  
Author(s):  
C. W. Tessum ◽  
J. D. Hill ◽  
J. D. Marshall
Keyword(s):  
Atmospheric Chemistry ◽  
Transport Model ◽  
Model Performance ◽  
Predictive Performance ◽  
Horizontal Resolution ◽  
Basis Set ◽  
Chemical Transport Model ◽  
High Concentration ◽  
Annual Average ◽  
Simulation Performance

Abstract. We present results from and evaluate the performance of a 12 month, 12 km horizontal resolution air pollution simulation for the contiguous United States using the WRF-Chem (Weather Research and Forecasting with Chemistry) meteorology and chemical transport model (CTM). We employ the 2005 US National Emissions Inventory, the Regional Atmospheric Chemistry Mechanism (RACM), and the Modal Aerosol Dynamics Model for Europe (MADE) with a Volatility Basis Set (VBS) secondary aerosol module. Overall, model performance is comparable to contemporary models used for regulatory and health-effects analysis, with an annual average daytime ozone (O3) mean fractional bias (MFB) of 12% and an annual average fine particulate matter (PM2.5) MFB of −1%. WRF-Chem, as configured here, tends to overpredict total PM2.5 at some high concentration locations, and generally overpredicts average 24 h O3 concentrations, with better performance at predicting average daytime and daily peak O3 concentrations. Predictive performance for PM2.5 subspecies is mixed: the model overpredicts particulate sulfate (MFB = 65%), underpredicts particulate nitrate (MFB = −110%) and organic carbon (MFB = −65%), and relatively accurately predicts particulate ammonium (MFB = 3%) and elemental carbon (MFB = 3%), so that the accuracy in total PM2.5 predictions is to some extent a function of offsetting over- and underpredictions of PM2.5 subspecies. Model predictive performance for PM2.5 and its subspecies is in general worse in winter and in the western US than in other seasons and regions, suggesting spatial and temporal opportunities for future WRF-Chem model development and evaluation.

scholarly journals Sunset–sunrise difference in solar occultation ozone measurements (SAGE II, HALOE, and ACE–FTS) and its relationship to tidal vertical winds

2015 ◽  
Vol 15 (2) ◽  
pp. 829-843 ◽  
Author(s):  
T. Sakazaki ◽  
M. Shiotani ◽  
M. Suzuki ◽  
D. Kinnison ◽  
J. M. Zawodny ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
Seasonal Variations ◽  
Climate Model ◽  
Transport Model ◽  
Stratospheric Aerosol ◽  
Data Sets ◽  
Chemical Transport Model ◽  
Latitude Range ◽  
Solar Occultation ◽  
Vertical Winds

Abstract. This paper contains a comprehensive investigation of the sunset–sunrise difference (SSD, i.e., the sunset-minus-sunrise value) of the ozone mixing ratio in the latitude range of 10° S–10° N. SSD values were determined from solar occultation measurements based on data obtained from the Stratospheric Aerosol and Gas Experiment (SAGE) II, the Halogen Occultation Experiment (HALOE), and the Atmospheric Chemistry Experiment–Fourier transform spectrometer (ACE–FTS). The SSD was negative at altitudes of 20–30 km (−0.1 ppmv at 25 km) and positive at 30–50 km (+0.2 ppmv at 40–45 km) for HALOE and ACE–FTS data. SAGE II data also showed a qualitatively similar result, although the SSD in the upper stratosphere was 2 times larger than those derived from the other data sets. On the basis of an analysis of data from the Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES) and a nudged chemical transport model (the specified dynamics version of the Whole Atmosphere Community Climate Model: SD–WACCM), we conclude that the SSD can be explained by diurnal variations in the ozone concentration, particularly those caused by vertical transport by the atmospheric tidal winds. All data sets showed significant seasonal variations in the SSD; the SSD in the upper stratosphere is greatest from December through February, while that in the lower stratosphere reaches a maximum twice: during the periods March–April and September–October. Based on an analysis of SD–WACCM results, we found that these seasonal variations follow those associated with the tidal vertical winds.

scholarly journals Secondary organic aerosol in the global aerosol – chemistry transport model Oslo CTM2

2007 ◽  
Vol 7 (3) ◽  
pp. 9053-9092 ◽  
Author(s):  
C. R. Hoyle ◽  
T. Berntsen ◽  
G. Myhre ◽  
I. S. A. Isaksen
Keyword(s):  
Ammonium Sulphate ◽  
Secondary Organic Aerosol ◽  
Transport Model ◽  
Model Simulation ◽  
Anthropogenic Activities ◽  
Organic Aerosol ◽  
Oxidation Products ◽  
Total Production ◽  
Chemical Transport Model ◽  
Sulphate Aerosol

Abstract. The global chemical transport model Oslo CTM2 has been extended to include the formation, transport and deposition of secondary organic aerosol (SOA). Precursor hydrocarbons which are oxidised to form condensible species include both biogenic species such as terpenes and isoprene, as well as species emitted predominantly by anthropogenic activities (toluene, m-xylene, methylbenzene and other aromatics). A model simulation for 2004 gives an annual global SOA production of approximately 55 Tg. Of this total, 2.5 Tg is found to consist of the oxidation products of anthropogenically emitted hydrocarbons, and about 15 Tg is formed by the oxidation products of isoprene. The global production of SOA is increased to about 76 Tg yr−1 by allowing semi-volatile species to condense on ammonium sulphate aerosol. This brings modelled organic aerosol values closer to those observed, however observations in Europe remain significantly underestimated, raising the possibility of an unaccounted for SOA source. Allowing SOA to form on ammonium sulphate aerosol increases the contribution of anthropogenic SOA from about 4.5% to almost 9% of the total production. The importance of NO3 as an oxidant of SOA precursors is found to vary regionally, causing up to 50%–60% of the total amount of SOA near the surface in polluted regions and less than 25% in more remote areas. This study underscores the need for SOA to be represented in a more realistic way in global aerosol models in order to better reproduce observations of organic aerosol burdens in industrialised and biomass burning regions.

scholarly journals Ethane, ethyne and carbon monoxide concentrations in the upper troposphere and lower stratosphere from ACE and GEOS-Chem: a comparison study

2011 ◽  
Vol 11 (4) ◽  
pp. 13099-13139 ◽  
Author(s):  
G. González Abad ◽  
N. D. C. Allen ◽  
P. F. Bernath ◽  
C. D. Boone ◽  
S. D. McLeod ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Atmospheric Chemistry ◽  
Transport Model ◽  
Chemical Mechanism ◽  
Chemical Transport Model ◽  
Spectrometer Data ◽  
Chemistry Experiment ◽  
Global Mean ◽  
Tropospheric Concentrations ◽  
Good Agreement

Abstract. Near global upper tropospheric concentrations of carbon monoxide (CO), ethane (C2H6) and ethyne (C2H2) from ACE (Atmospheric Chemistry Experiment) Fourier transform spectrometer on board the Canadian satellite SCISAT-1 are presented and compared with the output from the Chemical Transport Model (CTM) GEOS-Chem. The retrievals of ethane and ethyne from ACE have been improved for this paper by using new sets of microwindows compared with those for previous versions of ACE data. With the improved ethyne retrieval we have been able to produce a near global upper tropospheric distribution of C2H2 from space. Carbon monoxide, ethane and ethyne concentrations retrieved using ACE spectra show the expected seasonality linked to variations in the anthropogenic emissions and destruction rates as well as seasonal biomass burning activity. The GEOS-Chem model was run using the dicarbonyl chemistry suite, an extended chemical mechanism in which ethyne is treated explicitly. Seasonal cycles observed from satellite data are well reproduced by the model output, however the simulated CO concentrations are found to be systematically biased low over the Northern Hemisphere. An average negative global mean bias of 12% and 7% of the model relative to the satellite observations has been found for CO and C2H6 respectively and a positive global mean bias of 1% has been found for C2H2. ACE data are compared for validation purposes with MkIV spectrometer data and Global Tropospheric Experiment (GTE) TRACE-A campaign data showing good agreement with all of them.

scholarly journals A three-dimensional model study of long-term mid-high latitude lower stratosphere ozone changes

2003 ◽  
Vol 3 (1) ◽  
pp. 1081-1107 ◽  
Author(s):  
M. P. Chipperfield
Keyword(s):  
High Latitude ◽  
Lower Stratosphere ◽  
Transport Model ◽  
Three Dimensional ◽  
Horizontal Resolution ◽  
Chemical Transport Model ◽  
Three Dimensional Model ◽  
Detailed Chemistry ◽  
Basic Model ◽  
Column Ozone

Abstract. We have used a 3D off-line chemical transport model (CTM) to study the causes of the observed changes in ozone in the mid-high latitude lower stratosphere from 1979–1998. The model was forced by European Centre for Medium Range Weather Forecasts (ECMWF) analyses and contains a detailed chemistry scheme. A series of model runs were performed at a horizontal resolution of 7.5°×7.5° and covered the domain from about 12 km to 30 km. The basic model performs well in reproducing the decadal evolution of the springtime depletion in the northern hemisphere (NH) and southern hemisphere (SH) high latitudes in the 1980s and early 1990s. After about 1994 the modelled interannual variability does not match the observations as well, which is probably due in part to changes in the operational ECMWF analyses – which places limits on using this dataset to diagnose dynamical trends. For mid-latitudes (35°–60°) the basic model reproduces the observed column ozone decreases from 1980 until the early 1990s. Model experiments show that the halogen trends appear to dominate this modelled decrease and of this around 30–50% is due to high-latitude processing on polar stratospheric clouds (PSCs). Dynamically induced ozone variations in the model correlate with observations over the timescale of a few years. Large discrepancies between the modelled and observed variations in the mid 1980s and mid 1990s can be largely resolved by assuming that the 11-year solar cycle (not explicitly included in the 3D model) causes a 2% (min-max) change in mid-latitude column ozone.

scholarly journals Sunset–sunrise difference in solar occultation ozone measurements (SAGE II, HALOE, and ACE–FTS) and its relationship to tidal vertical winds

2014 ◽  
Vol 14 (11) ◽  
pp. 16043-16083
Author(s):  
T. Sakazaki ◽  
M. Shiotani ◽  
M. Suzuki ◽  
D. Kinnison ◽  
J. M. Zawodny ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
Seasonal Variations ◽  
Climate Model ◽  
Transport Model ◽  
Stratospheric Aerosol ◽  
Chemical Transport Model ◽  
Latitude Range ◽  
Solar Occultation ◽  
Vertical Winds ◽  
Chemistry Experiment

Abstract. This paper contains a comprehensive investigation of the sunset–sunrise difference (SSD; i.e., the sunset-minus-sunrise value) of the ozone mixing ratio in the latitude range of 10° S–10° N. SSD values were determined from solar occultation measurements based on data obtained from the Stratospheric Aerosol and Gas Experiment (SAGE) II, the Halogen Occultation Experiment (HALOE), and the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS). The SSD was negative at altitudes of 20–30 km (–0.1 ppmv at 25 km) and positive at 30–50 km (+0.2 ppmv at 40–45 km) for HALOE and ACE–FTS data. SAGE II data also showed a qualitatively similar result, although the SSD in the upper stratosphere was two times larger than those derived from the other datasets. On the basis of an analysis of data from the Superconducting Submillimeter Limb Emission Sounder (SMILES), and a nudged chemical-transport model (the Specified Dynamics version of the Whole Atmosphere Community Climate Model: SD–WACCM), we conclude that the SSD can be explained by diurnal variations in the ozone concentration, particularly those caused by vertical transport by the atmospheric tidal winds. All datasets showed significant seasonal variations in the SSD; the SSD in the upper stratosphere is greatest from December through February, while that in the lower stratosphere reaches a maximum twice: during the periods March–April and September–October. Based on an analysis of SD–WACCM results, we found that these seasonal variations follow those associated with the tidal vertical winds.

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