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ISSN : 1225-6692(Print)
ISSN : 2287-4518(Online)
Journal of the Korean earth science society Vol.38 No.5 pp.345-356

Characteristics of Summer Tropospheric Ozone over East Asia in a Chemistry-climate Model Simulation

Hyo-Jin Park1,2, Byung-Kwon Moon2*, Jieun Wie2
1Gunsan Dongsan Middle School, Gunsan 54020, Korea
2Division of Science Education/Institute of Fusion Science, Chonbuk National University, Jeonju 54896, Korea
Corresponding author:
August 12, 2017 September 7, 2017 September 12, 2017


It is important to understand the variability of tropospheric ozone since it is both a major pollutant affecting human health and a greenhouse gas influencing global climate. We analyze the characteristics of East Asia tropospheric ozone simulated in a chemistry-climate model. We use a global chemical transport model, driven by the prescribed meteorological fields from an air-sea coupled climate model simulation. Compared with observed data, the ozone simulation shows differences in distribution and concentration levels; in the vicinity of the Korean Peninsula, a large error occurred in summer. Our analysis reveals that this bias is mainly due to the difference in atmospheric circulation, as the anomalous southerly winds lead to the decrease in tropospheric ozone in this region. In addition, observational data have shown that the western North Pacific subtropical high (WNPSH) reduces tropospheric ozone across the southern China/Korean Peninsula/Japan region. In the model, the ozone changes associated with WNPSH are shifted westward relative to the observations. Our findings suggest that the variations in WNPSH should be considered in predicting tropospheric ozone concentrations.


    the Korea Ministry of Environment


    Tropospheric ozone is a major source of OH radicals and is an important factor affecting the oxidizing capacity of the atmosphere (Levy, 1971). It is not only a greenhouse gas that causes global warming (Shindell et al., 2006) but also a pollutant that causes respiratory diseases and premature mortality (Jerrett et al., 2009; Lelieveld et al., 2015). High ozone concentration could also reduce agricultural production because of its strong oxidative power, damaging plant leaves and hindering growth (Burney and Ramanathan, 2014). Ozone concentrations have been rising steadily in East Asia due to rapid economic development over the last few decades (Tanimoto et al., 2009; Wang et al., 2009), and tropospheric ozone has become a major environmental concern.

    Tropospheric ozone is mainly produced by photochemical reactions involving primary pollutants such as nitrogen oxides (NOx), carbon monoxide (CO), and volatile organic compounds (VOC) in the presence of sunlight. It is also transported from the stratosphere to the troposphere (Boothe and Homeyer, 2017; Yang et al., 2016). Therefore, the level of tropospheric ozone in a region will depend mainly on the precursor, the amount of solar radiation or cloud, and temperature, and so on. In recent years, it has been suggested that climate variability, such as the El Niño Southern Oscillation (ENSO), may also influence the surface ozone concentrations in East Asia (Wie and Moon, 2016) and global total ozone (Yoo and Jeong, 2005). It is very important to understand the relationship between tropospheric ozone and climate variabilities, as the characteristics of the East Asian monsoon and ENSO are expected to alter with future climatic changes (Ogata et al., 2014; Zou and Zhou, 2015).

    The western North Pacific subtropical high (WNPSH) is an important factor of the East Asian climate system in summer, influencing rainfall and tropical storm activity (Sui et al., 2007; Wang et al., 2013). In addition, it is known that when the anticyclonic flow accompanied by WNPSH is weakened, ozone concentration on the Korean Peninsula can increase (Wie and Moon, 2016). This may be due to the weakened influence of ozone-poor and moist tropical air.

    Atmospheric chemical transport models can predict future ozone changes and are therefore considered an essential tool for air quality management and in establishing effective policies to reduce ozone levels. However, the models still contain errors compared to observations, and some improvements, such as more complex physical and chemical processes and higher resolution, are required (Han et al., 2008; Lin et al., 2009). At the same time, it is also necessary to understand the chemistry-climate interactions simulated by current models, but there is little study of this subject.

    The summer season in East Asia has different climatic characteristics from those of North America and Europe, due to the influence of monsoon (Parrish et al., 2013). It can be expected that monsoon will affect atmospheric chemicals such as ozone (He et al., 2008; Lin et al., 2009). In order for models to simulate the East Asian ozone concentration accurately, cloud band, precipitation amount, and atmospheric circulations should be reproduced as accurately as possible (Chatani and Sudo, 2011). The present study investigates the characteristics of summer tropospheric ozone distribution over East Asia, and the effects of the WNPSH on ozone, using observations and model results. We also analyze the performance of recently developed models compared to observational data.

    Model Experiment and Data

    A global three-dimensional (3-D) chemical transport model (GEOS-Chem) was used to simulate tropospheric ozone concentration over East Asia. The model has a fully coupled tropospheric ozone-NOx-VOC-aerosol chemistry (Park et al., 2004; Liao et al., 2007). The GEOS-Chem was originally developed to be driven by the meteorological fields from the Goddard Earth Observing System (GEOS) of the NASA Global Modelling and Assimilation Office (Bey et al., 2001). Meteorological data needed to run the model include 3-hour averaged roughness length, precipitation, albedo, surface solar radiation, wind at 10m height, as well as 6-hour averaged cloud fractions, humidity, winds, temperature. We use GEOS-Chem version 8- 01-03 with 2° ×2.5° horizontal resolution and 26 vertical levels ( index.php/GEOS-Chem_v8-01-03). Rather than using GEOS inputs, the GEOS-Chem code was slightly modified to utilize meteorological data from the Community Climate System Model version 3 (CCSM3) (Collins et al., 2006). To isolate the effect of climate variations on tropospheric ozone, excluding the emission-induced changes, GEOS-Chem was performed using climatological values for biomass and anthropogenic emissions.

    To prepare the meteorological data for GEOSChem, we conducted CCSM3 with a fully coupled component set-up that included atmosphere (CAM3), land (CLM3), ocean (POP) and sea ice (CSIM) models, mutually linked by means of a coupler. The atmospheric model had a finite volume dynamic core with a 2° ×2.5° horizontal grid and 26 vertical levels, and the land component has the same horizontal resolution. The ocean and ice models shared an identical horizontal grid (gx1v3), with the North Pole displaced into Greenland. In the ocean model, there were 40 vertical levels with thicknesses monotonically increasing from approximately 10 to 250 m. A more detailed description of the CCSM3 can be found in a previous study by (Collins et al., 2006). This coupled climate model was run for 280 years and its latest 45- year simulated meteorological fields were used to drive GEOS-Chem, and the result from the GEOSChem is used for analysis. A similar model but with uncoupled atmospheric model was used to examine the aerosol impacts on meteorology due to Siberian forest fires (Youn et al., 2011), and identify the El Nino effects on tropospheric ozone in the tropical Pacific (Moon et al., 2013) and relationship between meteorological conditions and surface ozone in Korea (Wie and Moon, 2016). Note that models including air-sea interactions yield more realistic simulations of precipitation and atmospheric circulations associated with the East Asia summer monsoon in comparison to the atmospheric models (Song and Zhou, 2014). Hence, the use of a coupled model to produce meteorological variables for GEOS-Chem would be a careful choice to understand the tropospheric ozone variations in East Asia region.

    The gridded tropospheric ozone data based on the Aura Ozone Monitoring Instrument (OMI) and Microwave Limb Sounder (MLS) (Ziemke et al., 2006; Ziemke et al., 2011), the NCEP reanalysis-2 (NCEP2) wind and geopotential data (Kanamitsu et al., 2002), and the CMAP precipitation (Xie and Arkin, 1997) for the period 2005–2014 are compared with our model simulation.

    Characteristics of Simulated Summer Ozone

    Fig. 1 compares annual mean tropospheric ozone simulated in the model with that from OMI/MLS observations. Observed ozone concentration is low in the tropics and high in the mid-latitudes. Low concentration of ozone in the troposphere is caused by a decrease in ozone due to active convection (Doherty et al., 2005). This feature is also evident in the model. In the observations, however, tropospheric ozone forms a slantwise band along the northeast–southwest direction near the Korean Peninsula, whereas the simulated ozone is clearly more zonally distributed. Along with this, the anomalous ozone (model minus observation) is also zonally distributed. A similar feature also appears in other atmospheric chemistry and climate models (Young et al., 2013). The main cause is likely to be errors in the meteorological variables produced by the atmospheric model.

    In East Asia, tropospheric ozone is highest in summer, followed by spring and autumn, and lowest in winter, due to more active photochemical reactions to produce ozone in summer (Fig. 2). A similar seasonal cycle can be seen in the model. It is interesting to note that, in the case of surface ozone in East Asia, the summer season shows lower concentrations than in spring and autumn (Ghim and Chang, 2000; Wie and Moon, 2016). This can be attributed to the influence of the East Asian summer monsoon, in which moist and ozone-depleted air blowing from the Western Pacific leads to decrease in surface ozone (He et al., 2008). The bias in simulated ozone is largest in the China–Korea–Japan region during summer. The reason for this will be discussed later.

    The decline in surface ozone concentration due to southerly wind during the summer monsoon season is clearly shown in Fig. 3a. The low-ozone area is extended northward to ~40 °N with southerly flows, which leads to a bimodal seasonal cycle of surface ozone around 30 °N. The discrepancy in the seasonal cycle, between tropospheric ozone and ground ozone, can be reconciled by the ozone variations in the upper troposphere (Fig. 3b). The bimodal cycle of ozone is evident in the lower troposphere, but the upper layers above 500 hPa show a single maximum in summer. The amplitude of ozone change in the upper troposphere is larger than that in the lower layer. Therefore, the seasonal cycle shown in Fig. 2 is mainly due to the upper tropospheric ozone distribution.

    As mentioned above, the simulation shows a large bias in summer tropospheric ozone near the Korean Peninsula. Simultaneously, the area-averaged summer surface ozone over 110°E-145°E, 32 °N-47 °N from the model and observations were statistically different from each other at the 95% confidence level (Fig. 4). It should be noted that the winter averaged values are similar between observations and models, but this is due to the significant cancellation between negative and positive anomalies around the Korean Peninsula (Fig. 2). The model biases in tropospheric ozone over East Asia are mainly due to inaccurately representing monsoon circulations in the atmospheric model (Chatani and Sudo, 2011; Kurokawa et al., 2009). Therefore, it is necessary to examine whether the climate model can realistically reproduce the East Asia summer monsoon system.

    In summer, East Asia is affected by humid anticyclonic circulation from the western North Pacific region (Choi et al., 2015) and by a precipitation band extending from the subtropics (Fig. 5a). This precipitation band is associated with the Mei-yu/Changma/Baiu fronts that appear across the China-Korea-Japan region. The WNPSH in the model simulation appears shifted further west than the observations (Fig. 5b), resulting in negative anomalous precipitation along the monsoon fronts (Fig. 5c). This precipitation bias of the model may be due to the negative sea surface temperature (SST) anomaly in the model simulation of the western North Pacific region. The coupled general circulation models show that the enhanced anticyclonic flows result from cold SST biases (Song and Zhou, 2014). The cold SST bias in our model also confirmed this relationship (Fig. 6c). This cold bias over the western North Pacific curtails evaporation as well as surface latent heat flux into the atmosphere, resulting in reduced precipitation, which will eventually enhance the WNPSH (Sui et al., 2007; Wang et al., 2000).

    Since tropospheric ozone is negatively correlated with southerly winds (Fig. 3a), we investigated whether the vertical profile of the meridional wind might be related to the negative tropospheric ozone anomaly near the Korean Peninsula in summer (Fig. 2). Fig. 7 compares the vertical meridional wind of the model to the observed (NCEP2) data. The model simulated a stronger southerly wind than observations in the troposphere below 300 hPa. This implies that this strong southerly wind transported ozone-poor tropical air masses toward the Korean Peninsula, which in turn leads to lower production of ozone there. Note that southerly winds also inhibit the advection of precursor concentrations, but enhance the transport of moisture from the subtropics, which is associated with the destruction of tropospheric ozone. This negative correlation between the southerly winds and tropospheric ozone can be confirmed by singular value decomposition (SVD) analysis, which is used to identify the coupling mode of two variables (Bretherton et al., 1992). The first two leading modes of meridional wind and vertical ozone over the East Asia have barotropic and baroclinic structures, respectively (Fig. 8). These SVD modes clearly show a negative correlation between southerly wind and tropospheric ozone in East Asia, and also indicate that the lower tropospheric ozone over East Asia during summer (Fig. 4) is caused by strong southerly anomalies.

    Impact of WNPSH on Tropospheric Ozone

    Since the climatology and interannual variability of the East Asian summer monsoon are strongly influenced by the WNPSH, it is important to investigate the effect of WNPSH variations on tropospheric ozone. To represent the interannual variations of WNPSH, the standard deviation of summer mean geopotential height at 850 hPa is shown in Fig. 9 (cf. Lee et al., 2013; Xiang et al., 2013). Although the overall pattern is somewhat different from the observations, particularly in the mid-latitudes, a large variability of the geopotential height is simulated over the western North Pacific region (outlined by the rectangular box), similar to that seen in the observed data. Here we define WNPSH index as the mean geopotential height anomalies at 850 hPa (area 125°E-140°E, 20 °N-30 °N). Note that the regions of maximum variability in observation and model differ slightly in the east-west direction. However, there was no significant difference in the results irrespective of whether this region was analyzed in agreement with the model or the observation area.

    In observation, tropospheric ozone in East Asian is strongly correlated with WNPSH (Fig. 10a); tropospheric ozone decreases across the Indochinese Peninsula to Japan, and increases in the north and the Pacific. Most of these responses are closely linked to changes in the anticyclonic flow and precipitation associated with the WNPSH (Fig. 10c). Evidently, the anomalous southerly winds and precipitation lead to the decrease of tropospheric ozone, and vice versa, which is consistent with the SVD results (Fig. 8). However, this appears to be unrelated to the increase of ozone in the northern part of the continent. The model also shows a similar relationship between circulation, precipitation, and ozone anomalies associated with the WNPSH (Fig. 10b, 10d); however, the ozone anomaly is shifted westward compared to the observations. This bias likely reflects the comparatively strong variability of 850 hPa geopotential height (Fig. 9b). It should be noted that regions in which ozone is decreasing do not exactly match those of increasing precipitation in simulation. This discrepancy indicates that our modeling system still has many deficiencies in simulating chemistry-climate interactions, which may be partly related to uncertainties on the parameterization of convective activities.

    To investigate the simulated relationship between tropospheric ozone and WNPSH in more detail, the regressed vertical cross-section with respect to WNPSH index is shown in Fig. 11. Convective activities and precipitation increase are not seen near 20 °N, although tropospheric ozone is greatly decreased. Instead, there is significant strengthening of southerly wind, indicating again the effect of ozone-poor tropical air masses.

    The negative ozone anomaly in the mid-latitudes (30 °N-40 °N) appears to be tilted northward as altitude increases, which is closely associated with the convection activity around 40 °N. This northward-tilted structure is shown in observations of the monsoon front (Fu and Qian, 2011). Therefore, our model results show that the monsoon front can be considered as an ozone front, with a strong ozone contrast in its vicinity. Finally, it should be noted that tropospheric ozone is the third most important greenhouse gas after CO2 and CH4. Thus, there might be ozone-induced feedback effects on meteorological conditions, but to date the authors are not aware of any studies examining the ozone-climate coupling processes. In this regard, our results suggest that the relationship between meteorology and ozone is complex, and that simulating tropospheric ozone using a chemistry-climate model may require a sophisticated and complex process.


    This study analyzed characteristics of tropospheric ozone over East Asia simulated by a chemistryclimate model. The model consists of an air-sea coupled model (CCSM3) and a chemical transport model (GEOS-Chem). GEOS-Chem is conducted by the prescribed 45-year meteorological fields from CCSM3. The model simulated lower concentration of tropospheric ozone near the Korean Peninsula compared with observations, and showed the most pronounced disparity during summer. The cause of this discrepancy was suggested as anomalous strong southerly wind. The SVD results confirmed this negative correlation between meridional wind and tropospheric ozone in East Asia, as the positive southerly anomalies of the model resulted in the negative ozone anomalies. These southerly winds transport ozone-poor subtropical air masses and also supply water vapor that can destroy ozone. The strong anomalous southerlies in the model were caused by the westward shift of the WNPSH, probably due to the negative SST anomaly in the western North Pacific.

    The WNPSH is known to have a large influence on the climate of East Asia. We also analyzed the change of tropospheric ozone associated with the WNPSH. The observed data show that tropospheric ozone decreased across China-Korea-Japan due to the effects of the WNPSH. This is the result of convection activities and circulation changes caused by the WNPSH; the areas where ozone decreased are consistent with the increase in southerly winds and precipitation. On the other hand, ozone was increased in the western North Pacific, which was associated with anomalous northerlies and suppression of convective activities. In the model, the ozone variations associated with the WNPSH were shifted somewhat to the west compared to the observations, and the western North Pacific region of increased ozone was shifted northward. This is likely due to the fact that the CCSM3 model still shows deficiencies in simulating the atmospheric responses to the WNPSH changes. Therefore, to improve the model’s ability to capture the ozone changes associated with WNPSH variations, the simulation of the summer monsoon needs more improvements such as higher horizontal resolution and implementation of much detailed physical parameterization schemes (e.g., Li et al., 2015; Kang and Hong, 2008).

    The WNPSH circulation system in known to have major influence on the East Asian summer monsoon and typhoon activities, but we also found that it has a significant impact on tropospheric ozone in East Asia and the western North Pacific. Therefore, WNPSH predictability could contribute to predicting tropospheric ozone concentration, beyond forecasting the amount of monsoon precipitation or the number of typhoon occurrences. The study findings are helpful for understanding how long-term changes in circulation in the western North Pacific might modulate tropospheric ozone in the East Asia region.


    We thank Dr. Eun-Jeong Lee and an anonymous reviewer for helpful comments and suggestions. This research was supported by the Korea Ministry of Environment (MOE) as “Climate Change Correspondence Program.”



    Climatological mean tropospheric ozone for observations (OMI/MLS) from 2005 to 2014, model (45-years simulated), and their differences. All data are presented in Dobson Units.


    Seasonal mean tropospheric ozone from observation (OMI/MLS) during 2005-2014, model (45-years simulated), and their differences (model minus observation). Units are ppbv. Rectangular boxes denote the China–Korea–Japan region (110°E– 145°E, 32°N–47°N) considered in the analysis.


    (a) Hovmöller plot for zonal averaged (124°E-132°E) surface ozone (ppbv) and 850 hPa winds (m/s). (b) O3 annual cycle for isobaric surfaces averaged over (124°E- 132°E, 30 °N-40 °N). Both (a) and (b) are from the 45-years model simulation.


    Boxplots for seasonal tropospheric ozone in the 45- years simulation over the study region of China–Korea– Japan (110°E-145°E, 32 °N-47 °N; as denoted by the rectangular box in Fig. 2). The heights of the filled boxes indicate the interquartile range (IQR; 25-75% range) whereas the line and right triangle indicate the median and mean, respectively. The vertical whiskers represent values 1.5 times the IQR of the box. Open circles beyond the whiskers indicate outliers.


    Averaged precipitation (shading, mm/day) and 850 hPa wind vector during summer (June-July-August) for (a) observation (CMAP and NCEP reanalysis, from 2005 to 2014), (b) model result from the 45-years simulation, and (c) their differences. The rectangular box in (c) indicates the study region (110°E-145°E, 32 °N-47 °N) of China-Korea-Japan.


    Sea surface temperature for summer (JJA) from (a) observation (NOAA OI SSTv2) during 2005-2014, (b) model (45-years simulation), and (c) their differences. All units are K.


    Vertical distributions of summer (JJA) meridional winds averaged over (110°E-145°E, 32 °N-47 °N) for observation (NCEP2, 2005-2014) and 45-years simulation in the model.


    SVD results in the 45-years simulation: (a) The first leading mode between the vertical ozone and meridional wind averaged over (110°E-145°E, 32 °N-47 °N), (b) As in (a) but showing the second mode.


    Standard deviation (m) of 850 hPa geopotential heights from (a) NCEP reanalysis (2005-2014) and (b) the 45-years model run. The boxes represent the regions for calculation of WNPSH index: (a) (130°E-145°E, 20 °N-30 °N), (b) (125°E-140°E, 20 °N-30 °N). The WNPSH indices are defined as the normalized time series of the summer (JJA) geopotential height anomalies averaged over each rectangle.


    Regressed tropospheric ozone (DU) against the normalized WNPSH index for (a) observation (2005-2014) and (b) model simulation (45-years period). Dotted areas indicate statistical significance at 90% confidence level (t-test). Panels (c-d) are the same as (a-b), but show regressed precipitation and 850 hPa wind vectors. Boxes are the same as in Fig. 9.


    Vertical cross-section in regressed (a) ozone (ppbv) and (b) temperature (° C), and winds against the normalized WNPSH index along 100°E-120°E in the 45-years model simulation. Note that omega is multiplied by -30 to exaggerate the variations. Green arrows indicate statistical significance at 95% confidence level (t-test).



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