Dipole Pattern of Summer Ozone Pollution in the east of China and Its Connection with Climate Variability

Wave Source ◽

Rossby Wave Source ◽

Dipole Pattern

Abstract. Surface O3 pollution has become one of the most severe air pollution problems in China, which makes it of practical importance to understand O3 variability. A south-north dipole pattern of summer-mean O3 concentration in the east of China (DP-O3), which were centered at North China (NC) and the Pearl River Delta (PRD) respectively, has been identified from the simulation of a global 3-D chemical transport model for the period 1980–2019. Large-scale anticyclonic (cyclonic) and cyclonic (anticyclonic) anomalies over NC and the PRD resulted in a sharp contrast of meteorological conditions between the above two regions. The enhanced (restrained) photochemistry and natural emissions of O3 precursors in NC and restrained (enhanced) O3 production in the PRD contributed to the DP-O3. Decreased sea ice anomalies near the Franz Josef Land and associated warm sea surface in May enhanced the Rossby-wave source over northern Europe and West Siberia, which eventually induced an anomalous Eurasia-like pattern to influence the formation of the DP-O3. The thermodynamic signals of the southern Indian Ocean dipole were stored in the subsurface and influenced spatial pattern of O3 pollution in the east of China mainly through the Hadley circulation. The physical mechanisms behind the modulation of the atmospheric circulations and related DP-O3 by these two climate anomalies at different latitudes were evidently verified by large-scale ensemble simulations of the earth system model.

Modeling the transport of very short-lived substances into the tropical upper troposphere and lower stratosphere

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-9-18511-2009 ◽

2009 ◽

Vol 9 (5) ◽

pp. 18511-18543 ◽

Cited By ~ 2

Author(s):

J. Aschmann ◽

B. M. Sinnhuber ◽

E. L. Atlas ◽

S. M. Schauffler

Keyword(s):

Large Scale ◽

Lower Stratosphere ◽

Transport Model ◽

Three Dimensional ◽

Heating Rates ◽

Model Calculations ◽

Upper Troposphere ◽

Mass Fluxes ◽

Tropical Upper Troposphere

Abstract. The transport of very short-lived substances into the tropical upper troposphere and lower stratosphere is investigated by a three-dimensional chemical transport model using archived convective updraft mass fluxes (or detrainment rates) from the European Centre for Medium-Range Weather Forecast's ERA-Interim reanalysis. Large-scale vertical velocities are calculated from diabatic heating rates. With this approach we explicitly model the large scale subsidence in the tropical troposphere with convection taking place in fast and isolated updraft events. The model calculations agree generally well with observations of bromoform and methyl iodide from aircraft campaigns and with ozone and water vapor from sonde and satellite observations. Using a simplified treatment of dehydration and bromine product gas washout we give a range of 1.6 to 3 ppt for the contribution of bromoform to stratospheric bromine, assuming a uniform source in the boundary layer of 1 ppt. We show that the most effective region for VSLS transport into the stratosphere is the West Pacific, accounting for about 55% of the bromine from bromoform transported into the stratosphere under the supposition of a uniformly distributed source.

Aerosol concentrations variability over China: two distinct leading modes

10.5194/acp-2019-1194 ◽

2020 ◽

Author(s):

Juan Feng ◽

Jianlei Zhu ◽

Jianping Li ◽

Hong Liao

Keyword(s):

Transport Model ◽

Eastern China ◽

Practical Importance ◽

Negative Temperature ◽

Northern China ◽

Dipole Mode ◽

Boundary Layer Height ◽

The North ◽

The North Atlantic Oscillation

Abstract. Understanding the variability in aerosol concentrations (AC) over China is a scientific challenge and is of practical importance. The present study explored the month-to-month variability in AC over China based on simulations of an atmospheric chemical transport model with a fixed emissions level. The month-to-month variability in AC over China is dominated by two principal modes: the first leading mono-pole mode and the second meridional dipole mode. The mono-pole mode mainly indicates enhanced AC over eastern China, and the dipole mode displays a south–north out-of-phase pattern. The two leading modes are associated with different climatic systems. The mono-pole mode relates to the 3-month leading El Niño–South Oscillation (ENSO), while the dipole mode connects with the simultaneous variation in the North Atlantic Oscillation (NAO) or the Northern Hemisphere Annular Mode (NAM). The associated anomalous dynamic and thermal impacts of the two climatic variabilities are examined to explain their contributions to the formation of the two modes. For the mono-pole mode, the preceding ENSO is associated with anomalous convergence, decreased planetary boundary layer height (PBLH), and negative temperature anomalies, which are unfavorable for emissions. For the dipole mode, the positive NAO is accompanied by opposite anomalies in the convergence, PBLH, and temperature over southern and northern China, paralleling the spatial formation of the mode. This result suggests that the variations originating from the tropical Pacific and extratropical atmospheric systems contribute to the dominant variabilities of AC over China.

A linear CO chemistry parameterization in a chemistry-transport model: evaluation and application to data assimilation

10.5194/acp-10-6097-2010 ◽

2010 ◽

Vol 10 (13) ◽

pp. 6097-6115 ◽

Cited By ~ 19

Author(s):

M. Claeyman ◽

J.-L. Attié ◽

L. El Amraoui ◽

D. Cariolle ◽

V.-H. Peuch ◽

...

Keyword(s):

Data Assimilation ◽

Large Scale ◽

Lower Stratosphere ◽

Transport Model ◽

Order Approximation ◽

Long Run ◽

Linear Scheme ◽

Mean Differences ◽

First Order Approximation

Abstract. This paper presents an evaluation of a new linear parameterization valid for the troposphere and the stratosphere, based on a first order approximation of the carbon monoxide (CO) continuity equation. This linear scheme (hereinafter noted LINCO) has been implemented in the 3-D Chemical Transport Model (CTM) MOCAGE (MOdèle de Chimie Atmospherique Grande Echelle). First, a one and a half years of LINCO simulation has been compared to output obtained from a detailed chemical scheme output. The mean differences between both schemes are about ±25 ppbv (part per billion by volume) or 15% in the troposphere and ±10 ppbv or 100% in the stratosphere. Second, LINCO has been compared to diverse observations from satellite instruments covering the troposphere (Measurements Of Pollution In The Troposphere: MOPITT) and the stratosphere (Microwave Limb Sounder: MLS) and also from aircraft (Measurements of ozone and water vapour by Airbus in-service aircraft: MOZAIC programme) mostly flying in the upper troposphere and lower stratosphere (UTLS). In the troposphere, the LINCO seasonal variations as well as the vertical and horizontal distributions are quite close to MOPITT CO observations. However, a bias of ~−40 ppbv is observed at 700 Pa between LINCO and MOPITT. In the stratosphere, MLS and LINCO present similar large-scale patterns, except over the poles where the CO concentration is underestimated by the model. In the UTLS, LINCO presents small biases less than 2% compared to independent MOZAIC profiles. Third, we assimilated MOPITT CO using a variational 3D-FGAT (First Guess at Appropriate Time) method in conjunction with MOCAGE for a long run of one and a half years. The data assimilation greatly improves the vertical CO distribution in the troposphere from 700 to 350 hPa compared to independent MOZAIC profiles. At 146 hPa, the assimilated CO distribution is also improved compared to MLS observations by reducing the bias up to a factor of 2 in the tropics. This study confirms that the linear scheme is able to simulate reasonably well the CO distribution in the troposphere and in the lower stratosphere. Therefore, the low computing cost of the linear scheme opens new perspectives to make free runs and CO data assimilation runs at high resolution and over periods of several years.

The role of horizontal model resolution in assessing the transport of CO in a middle latitude cyclone using WRF-Chem

10.5194/acp-14-609-2014 ◽

2014 ◽

Vol 14 (2) ◽

pp. 609-627 ◽

Cited By ~ 12

Author(s):

C. A. Klich ◽

H. E. Fuelberg

Keyword(s):

Large Scale ◽

Transport Model ◽

Deep Convection ◽

Middle Latitude ◽

Convective Transport ◽

Vertical Transport ◽

Squall Line ◽

Grid Spacing ◽

Hysplit Model

Abstract. We use the Weather Research and Forecasting with Chemistry (WRF-Chem) online chemical transport model to simulate a middle latitude cyclone in East Asia at three different horizontal resolutions (45, 15, and 5 km grid spacing). The cyclone contains a typical warm conveyor belt (WCB) with an embedded squall line that passes through an area having large surface concentrations (> 400 ppbv) of carbon monoxide (CO). Model output from WRF-Chem is used to compare differences between the large-scale CO vertical transport by the WCB (the 45 km simulation) with the smaller-scale transport due to its convection (the 5 km simulation). Forward trajectories are calculated from WRF-Chem output using the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model. At 45 km grid spacing, the WCB exhibits gradual ascent, lofting surface CO to 6–7 km. Upon reaching the warm front, the WCB and associated CO ascend more rapidly and later turn eastward over the Pacific Ocean. Convective transport at 5 km resolution with explicitly resolved convection occurs much more rapidly, with surface CO lofted to altitudes greater than 10 km in 1 h or less. We also compute CO vertical mass fluxes over specified areas and times to compare differences in transport due to the different grid spacings. Upward CO flux exceeds 110 000 t h−1 in the domain with explicit convection when the squall line is at peak intensity, while fluxes from the two coarser resolutions are an order of magnitude smaller. Specific areas of interest within the 5 km domain are defined to compare the magnitude of convective transport to that within the entire 5 km region. Although convection encompasses only a small portion of the 5 km domain, it is responsible for ~40% of the upward CO transport. We also examine the vertical transport due to a short wave trough and its associated area of convection, not related to the cyclone, that lofts CO to the upper troposphere. Results indicate that fine-scale resolution with explicitly resolved convection is important when assessing the vertical transport of surface emissions in areas of deep convection.

Error correlation between CO2 and CO as constraint for CO2 flux inversions using satellite data

10.5194/acp-9-7313-2009 ◽

2009 ◽

Vol 9 (19) ◽

pp. 7313-7323 ◽

Cited By ~ 25

Author(s):

H. Wang ◽

D. J. Jacob ◽

M. Kopacz ◽

D. B. A. Jones ◽

P. Suntharalingam ◽

...

Keyword(s):

Inverse Modeling ◽

Large Scale ◽

Transport Model ◽

Meteorological Data ◽

Correlation Coefficients ◽

Surface Fluxes ◽

Satellite Observations ◽

Carbon Surface ◽

Error Correlation

Abstract. Inverse modeling of CO2 satellite observations to better quantify carbon surface fluxes requires a chemical transport model (CTM) to relate the fluxes to the observed column concentrations. CTM transport error is a major source of uncertainty. We show that its effect can be reduced by using CO satellite observations as additional constraint in a joint CO2-CO inversion. CO is measured from space with high precision, is strongly correlated with CO2, and is more sensitive than CO2 to CTM transport errors on synoptic and smaller scales. Exploiting this constraint requires statistics for the CTM transport error correlation between CO2 and CO, which is significantly different from the correlation between the concentrations themselves. We estimate the error correlation globally and for different seasons by a paired-model method (comparing GEOS-Chem CTM simulations of CO2 and CO columns using different assimilated meteorological data sets for the same meteorological year) and a paired-forecast method (comparing 48- vs. 24-h GEOS-5 CTM forecasts of CO2 and CO columns for the same forecast time). We find strong error correlations (r2>0.5) between CO2 and CO columns over much of the extra-tropical Northern Hemisphere throughout the year, and strong consistency between different methods to estimate the error correlation. Application of the averaging kernels used in the retrieval for thermal IR CO measurements weakens the correlation coefficients by 15% on average (mostly due to variability in the averaging kernels) but preserves the large-scale correlation structure. We present a simple inverse modeling application to demonstrate that CO2-CO error correlations can indeed significantly reduce uncertainty on surface carbon fluxes in a joint CO2-CO inversion vs. a CO2-only inversion.

Inversion of long-lived trace gas emissions using combined Eulerian and Lagrangian chemical transport models

10.5194/acp-11-9887-2011 ◽

2011 ◽

Vol 11 (18) ◽

pp. 9887-9898 ◽

Cited By ~ 49

Author(s):

M. Rigby ◽

A. J. Manning ◽

R. G. Prinn

Keyword(s):

High Resolution ◽

Large Scale ◽

Transport Model ◽

Initial Conditions ◽

Dispersion Model ◽

Chemical Transport ◽

Particle Dispersion ◽

Global Network ◽

Lagrangian Model ◽

Chemical Transport Model

Abstract. We present a method for estimating emissions of long-lived trace gases from a sparse global network of high-frequency observatories, using both a global Eulerian chemical transport model and Lagrangian particle dispersion model. Emissions are derived in a single step after determining sensitivities of the observations to initial conditions, the high-resolution emissions field close to observation points, and larger regions further from the measurements. This method has the several advantages over inversions using one type of model alone, in that: high-resolution simulations can be carried out in limited domains close to the measurement sites, with lower resolution being used further from them; the influence of errors due to aggregation of emissions close to the measurement sites can be minimized; assumptions about boundary conditions to the Lagrangian model do not need to be made, since the entire emissions field is estimated; any combination of appropriate models can be used, with no code modification. Because the sensitivity to the entire emissions field is derived, the estimation can be carried out using traditional statistical methods without the need for multiple steps in the inversion. We demonstrate the utility of this approach by determining global SF6 emissions using measurements from the Advanced Global Atmospheric Gases Experiment (AGAGE) between 2007 and 2009. The global total and large-scale patterns of the derived emissions agree well with previous studies, whilst allowing emissions to be determined at higher resolution than has previously been possible, and improving the agreement between the modeled and observed mole fractions at some sites.

Clouds, photolysis and regional tropospheric ozone budgets

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-9-13889-2009 ◽

2009 ◽

Vol 9 (3) ◽

pp. 13889-13916 ◽

Cited By ~ 1

Author(s):

A. Voulgarakis ◽

O. Wild ◽

N. H. Savage ◽

G. D. Carver ◽

J. A. Pyle

Keyword(s):

Tropospheric Ozone ◽

Large Scale ◽

Transport Model ◽

Regional Scale ◽

Three Dimensional ◽

Global Scale ◽

Chemical Production ◽

Photolysis Rates ◽

Boundary Layer Ozone

Abstract. We use a three-dimensional chemical transport model to examine the shortwave radiative effects of clouds on the tropospheric ozone budget. In addition to looking at changes in global concentrations as previous studies have done, we examine changes in ozone chemical production and loss caused by clouds and how these vary in different parts of the troposphere. On a global scale, we find that clouds have a modest effect on ozone chemistry, but on a regional scale their role is much more significant, with the size of the response dependent on the region. The largest averaged changes in chemical budgets (±10–14%) are found in the marine troposphere, where cloud optical depths are high. We demonstrate that cloud effects are small on average in the middle troposphere because this is a transition region between reduction and enhancement in photolysis rates. We show that increases in boundary layer ozone due to clouds are driven by large-scale changes in downward ozone transport from higher in the troposphere rather than by decreases in in-situ ozone chemical loss rates. Increases in upper tropospheric ozone are caused by higher production rates due to backscattering of radiation and consequent increases in photolysis rates, mainly J(NO2). The global radiative effect of clouds on isoprene is stronger than on ozone. Tropospheric isoprene lifetime increases by 7% when taking clouds into account. We compare the importance of clouds in contributing to uncertainties in the global ozone budget with the role of other radiatively-important factors. The budget is most sensitive to the overhead ozone column, while surface albedo and clouds have smaller effects. However, uncertainty in representing the spatial distribution of clouds may lead to a large sensitivity on regional scales.

Potential of multispectral synergism for observing ozone pollution by combining IASI-NG and UVNS measurements from EPS-SG satellite

10.5194/amt-2016-374 ◽

2016 ◽

Author(s):

Lorenzo Costantino ◽

Juan Cuesta ◽

Emanuele Emili ◽

Adriana Coman ◽

Gilles Foret ◽

...

Keyword(s):

Degrees Of Freedom ◽

Transport Model ◽

Lower Troposphere ◽

Real Data ◽

Satellite Observations ◽

Maximum Sensitivity ◽

Ozone Pollution ◽

Near Surface ◽

Multispectral Method

Abstract. Present and future satellite observations offer a great potential for monitoring air quality on daily and global basis. However, measurements from currently in orbit satellites do not allow using a single sensor to probe accurately surface concentrations of gaseous pollutants such as tropospheric ozone (Liu et al., 2010). Using single-band approaches based on spaceborne measurements of either thermal infrared radiance (TIR, Eremenko et al., 2008) or ultraviolet reflectance (UV, Liu et al., 2010) only ozone down to the lower troposphere (3 km) may be observed. A recent multispectral method (referred to as IASI+GOME-2) combining the information of IASI and GOME-2 (both onboard MetOp satellites) spectra, respectively from the TIR and UV, has shown enhanced sensitivity for probing ozone at the lowermost troposphere (LMT, below 3 km of altitude) with maximum sensitivity down to 2.20 km a.s.l. over land, while sensitivity for IASI or GOME-2 only peaks at 3 to 4 km at lowest (Cuesta et al., 2013). Future spatial missions will be launched in the upcoming years, such as EPS-SG, carrying new-generation sensors of IASI and GOME-2 (respectively IASI-NG and UVNS) that will enhance the capacity to observe ozone pollution and particularly by synergism of TIR and UV measurements. In this work we develop a pseudo-observation simulator and evaluate the potential of future EPS-SG satellite observations through IASI-NG+UVNS multispectral method to observer near-surface O3. The pseudo-real state of atmosphere (nature run) is provided by the MOCAGE (MOdèle de Chimie Atmosphérique à Grande Échelle) chemical transport model. Simulations are calibrated by careful comparisons with real data, to ensure the best consistency between pseudo-reality and reality, as well as between the pseudo-observation simulator and existing satellite products. We perform full and accurate forward and inverse radiative transfer calculations for a period of 4 days (8–11 July 2010) over Europe. In the LMT, there is a remarkable agreement in the geographical distribution of O3 partial columns, calculated between the surface and 3 km of altitude, between IASI-NG+UVNS pseudo-observations and the corresponding MOCAGE pseudo-reality. With respect to synthetic IASI+GOME-2 products, IASI-NG+UVNS shows a higher correlation between pseudo-observations and pseudo-reality, enhanced by about 11 %. The bias on high ozone retrieval is reduced and the average accuracy increases by 22 %. The sensitivity to LMT ozone is enhanced on average with 154 % (from 0.29 to 0.75, over land) and 208 % (from 0.21 to 0.66, over ocean) higher degrees of freedom. The mean height of maximum sensitivity for the LMT peaks at 1.43 km over land and 2.02 km over ocean, respectively 1.03 km and 1.30 km below that of IASI+GOME-2. IASI-NG+UVNS shows also good retrieval skill in the surface-2 km altitude range with a mean DOF (degree of freedom) of 0.52 (land) and 0.42 (ocean), and an average Hmax (altitude of maximum sensitivity) of 1.29 km (land) and 1.96 km (ocean). Unique of its kind for retrieving ozone layers of 2–3 km thickness, in the first 2–3 km of the atmosphere, IASI-NG+UVNS is expected to largely enhance the capacity to observe ozone pollution from space.

Error correlation between CO2 and CO as constraint for CO2 flux inversions using satellite data

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-9-11783-2009 ◽

2009 ◽

Vol 9 (3) ◽

pp. 11783-11810

Author(s):

H. Wang ◽

D. J. Jacob ◽

M. Kopacz ◽

D. B. A. Jones ◽

P. Suntharalingam ◽

...

Keyword(s):

Inverse Modeling ◽

Large Scale ◽

Transport Model ◽

Meteorological Data ◽

Co2 Flux ◽

Surface Fluxes ◽

Satellite Observations ◽

Carbon Surface ◽

Error Correlation

Abstract. Inverse modeling of CO2 satellite observations to better quantify carbon surface fluxes requires a forward model such as a chemical transport model (CTM) to relate the fluxes to the observed column concentrations. Model transport error is an important source of observational error. We investigate the potential of using CO satellite observations as additional constraints in a joint CO2–CO inversion to improve CO2 flux estimates, by exploiting the CTM transport error correlations between CO2 and CO. We estimate the error correlation globally and for different seasons by a paired-model method (comparing CTM simulations of CO2 and CO columns using different assimilated meteorological data sets for the same meteorological year) and a paired-forecast method (comparing 48- vs. 24-h CTM forecasts of CO2 and CO columns for the same forecast time). We find strong positive and negative error correlations (r2>0.5) between CO2 and CO columns over much of the world throughout the year, and strong consistency between different methods to estimate the error correlation. Application of the averaging kernels used in the retrieval for thermal IR CO measurements weakens the correlation coefficients by 15% on average (mostly due to variability in the averaging kernels) but preserves the large-scale correlation structure. Results from a testbed inverse modeling application show that CO2–CO error correlations can indeed significantly reduce uncertainty on surface carbon fluxes in a joint CO2–CO inversion vs. a CO2–only inversion.

Ozone pollution during the COVID-19 lockdown in the spring 2020 over Europe analysed from satellite observations, in situ measurements and models

10.5194/acp-2021-785 ◽

2021 ◽

Author(s):

Juan Cuesta ◽

Lorenzo Costantino ◽

Matthias Beekmann ◽

Guillaume Siour ◽

Laurent Menut ◽

...

Keyword(s):

Large Scale ◽

Transport Model ◽

Surface Ozone ◽

In Situ Measurements ◽

Satellite Observations ◽

Emission Inventories ◽

Ozone Pollution ◽

Chemistry Transport Model ◽

Near Surface

Abstract. We present a comprehensive study integrating satellite observations of ozone pollution, in situ measurements and chemistry transport model simulations for quantifying the role of anthropogenic emission reductions during the COVID-19 lockdown in spring 2020 over Europe. Satellite observations are derived from the IASI+GOME2 multispectral synergism, which provides particularly enhanced sensitivity to near-surface ozone pollution. These observations are first analysed in terms of differences between the average on 1–15 April 2020, when the strictest lockdown restrictions took place, and the same period in 2019. They show clear enhancements of near-surface ozone in Central Europe and Northern Italy, and some other hotspots, which are typically characterized by VOC-limited chemical regimes. An overall reduction of ozone is observed elsewhere, where ozone chemistry is limited by the abundance of NOx. The spatial distribution of positive and negative ozone concentration anomalies observed from space is in relatively good quantitative agreement with surface in situ measurements over the continent (a correlation coefficient of 0.55, a root-mean-squared difference of 11 ppb and the same standard deviation and range of variability). An average bias of ∼8 ppb between the two observational datasets is remarked, which can partly be explained by the fact the satellite approach retrieves partial columns of ozone with a peak sensitivity above the surface (near 2 km of altitude). For assessing the impact of the reduction of anthropogenic emissions during the lockdown, we adjust the satellite and in situ surface observations for withdrawing the influence of meteorological conditions in 2020 and 2019. This adjustment is derived from the chemistry transport model simulations using the meteorological fields of each year and identical emission inventories. This observational estimate of the influence of lockdown emission reduction is consistent for both datasets. They both show lockdown-associated ozone enhancements in hotspots over Central Europe and Northern Italy, with a reduced amplitude with respect to the total changes observed between the two years, and an overall reduction elsewhere over Europe and the ocean. Satellite observations additionally highlight the ozone anomalies in the regions remote from in situ sensors, an enhancement over the Mediterranean likely associated with maritime traffic emissions and a marked large-scale reduction of ozone elsewhere over ocean (particularly over the North Sea), in consistency with previous assessments done with ozonesondes measurements in the free troposphere. These observational assessments are compared with model-only estimations, using the CHIMERE chemistry transport model. For analysing the uncertainty of the model estimates, we perform two sets of simulations with different setups, differing in the emission inventories, their modifications to account for changes in anthropogenic activities during the lockdown and the meteorological fields. Whereas a general qualitative consistency of positive and negative ozone anomalies is remarked between all model and observational estimates, significant changes are seen in their amplitudes. Models underestimate the range of variability of the ozone changes by at least a factor 2 with respect to the two observational data sets, both for enhancements and decreases of ozone, while the large-scale ozone decrease is not simulated. With one of the setups, the model simulates ozone enhancements a factor 3 to 6 smaller than with the other configuration. This is partly linked to the emission inventories of ozone precursors (at least a 30 % difference), but mainly to differences in vertical mixing of atmospheric constituents depending on the choice of the meteorological model.