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. 2022 Sep 14;49(18):e2022GL099848. doi: 10.1029/2022GL099848

Tropopause‐Level NOx in the Asian Summer Monsoon

Kimberlee Dubé 1,✉, William Randel 2, Adam Bourassa 1, Doug Degenstein 1
PMCID: PMC9539711  PMID: 36246737

Abstract

Deep convection within the Asian summer monsoon (ASM) transports surface level air into the upper troposphere‐lower stratosphere (UTLS). This work aims to understand the distribution of NO2, NO, and NOx in the UTLS ASM anticyclone from satellite measurements. Observations of NO2 from the Optical Spectrograph and InfraRed Imager System, the Atmospheric Chemistry Experiment ‐ Fourier Transform Spectrometer (ACE‐FTS), and the Stratospheric Aerosol and Gas Experiment III on the International Space Station are considered. The PRATMO photochemical box model is used to quantify the NOx photochemistry, and to derive the NOx concentration using OSIRIS NO2 and O3 observations. The satellite data show a relative minimum in NO2 over the ASM in the summer months, while the corresponding NO and NOx anomalies are elevated, mainly due to low O3 and cold temperatures within the ASM. The observations within the ASM show reasonable agreement to simulations from the Whole Atmosphere Community Climate Model.

Keywords: Asian summer monsoon, UTLS, NOx chemistry

Key Points

  • Satellite data show a relative minimum in the NO2 concentration within the Asian summer monsoon (ASM) in the upper troposphere‐lower stratosphere (UTLS)

  • Photochemical box model calculations show corresponding maxima in UTLS NO and NOx, due to low O3 and temperature in the monsoon

  • NO2 and NOx from satellite data and a climate model show good agreement within the ASM

1. Introduction

The Asian summer monsoon (ASM) is a region of persistent deep convection that appears over the southeast Asian region each summer, driving a planetary‐scale anticyclonic circulation in the upper troposphere‐lower stratosphere (UTLS). Important aspects of monsoon convection and circulation include the rapid transport of air from the surface into the UTLS and confinement by anticyclonic circulation (e.g., Bian et al., 2020; Bourassa et al., 2012; Brunamonti et al., 2018; Li et al., 2005; Pan et al., 2016; Randel et al., 2010; von Hobe et al., 2021). These processes provide a pathway for near‐surface air, including pollutants, to influence UTLS chemical processes.

Measurements from satellite limb and occultation instruments are useful for observing the composition of the monsoon, providing complementary information to nadir‐sounding satellite instruments and sparse research aircraft measurements. Numerous studies have used these satellite observations to quantify the chemical composition of the UTLS associated with the ASM, showing enhanced values of chemical constituents that originate in the troposphere, such as CO and HCN (e.g., Li et al., 2005; Park et al., 2008; Randel et al., 2010). On the other hand, O3 and HNO3, which are molecules of stratospheric origin, show decreased concentrations within the monsoon anticyclone (e.g., Park et al., 2007, 2008; Santee et al., 2017). The monsoon anticyclone is also associated with cold temperature anomalies in the UTLS, and warm temperature anomalies in the mid‐troposphere (Randel & Park, 2006).

Nitrogen oxides NO and NO2 (the sum of which is called NOx) play a critical role in the chemistry of the atmosphere. In the troposphere NOx produces O3, while in the stratosphere NOx destroys O3. Roy et al. (2017) linked increases in Chinese and Indian NOx emissions to increased O3 production within the troposphere during the ASM. Fadnavis et al. (2015) modeled enhanced NOx in the ASM, which they associated with the upward transport of pollutants and the production of NOx in the upper troposphere by lightning. Lightning is known to produce NOx (e.g., Tie et al., 2001; Zhang et al., 2000) and the ASM has been associated with high lightning flash rates (Penki & Kamra, 2013). While Fadnavis et al. (2015) found that the transport of emissions to the UTLS is the largest factor affecting NOx in the ASM, Lelieveld et al. (2018) found that lightning is still a key source of NOx in the upper tropospheric monsoon anticyclone. Lelieveld et al. (2018) present the near continuous production of lightning NOx within the ASM convection region as the key factor in the formation of upper tropospheric OH. The OH can then oxidize pollutant gases into forms that are easily removed by precipitation, thus cleansing the atmosphere.

While the above studies have focused on modeling the influence of the ASM on NOx, comparatively little is known about the observed behavior of the individual components of NOx, NO, and NO2. Park et al. (2004) examined NO and NO2 observations from the Halogen Occultation Experiment (HALOE, Russell et al., 1993). Only the HALOE sunset occultations were considered. Park et al. (2004) found that the mean July NO and NO2 mixing ratios at 100 hPa from 1992 to 2002 both displayed maximum values in the ASM anticyclone region. When added together to get NOx the HALOE data showed a maximum of 0.5–0.8 ppmv in the ASM. They suggested that this lower stratospheric NOx maximum is due to the transport of tropospheric NOx produced by lightning. Aside from Park et al. (2004), little observational evidence on the behavior of NOx in the ASM has been reported.

Here we investigate NOx in the ASM using NO2 measurements from the Optical Spectrograph and InfraRed Imager System (OSIRIS, Llewellyn et al., 2004), combined with the PRATMO photochemical box model (McLinden et al., 2000). Additional satellite measurements are provided by the Atmospheric Chemistry Experiment—Fourier Transform Spectrometer (ACE‐FTS, Bernath et al., 2005), and the Stratospheric Aerosol and Gas Experiment on the International Space Station (SAGE III/ISS, Cisewski et al., 2014). We include comparisons with simulations from the Whole Atmosphere Community Climate Model (WACCM, e.g., Gettelman et al., 2019) to inform the satellite data analysis and evaluate model behavior. The focus here is on temporal and spatial averages, rather than the shorter term variability that is a feature of the ASM anticyclone (e.g., Gottschaldt et al., 2018; Vogel et al., 2016). The combination of data from several instruments, along with the models, provides novel information on UTLS NOx behavior and related photochemistry of the ASM.

2. Satellite Data and Models

2.1. OSIRIS

OSIRIS has been operating from a sun‐synchronous orbit aboard the Odin satellite since October 2001 (Llewellyn et al., 2004; Murtagh et al., 2002). The optical spectrograph scans the limb of the atmosphere to measure 100 to 400 vertical profiles of limb‐scattered solar irradiance each day, at wavelengths from 280 to 800 nm. Only the descending node measurements, occurring near a local solar time (LST) of 6:30 a.m., are used here. These form the vast majority of the observations throughout the mission. The exact timing of the measurements varies by about an hour due to the precessing orbit of the spacecraft.

We are using version 7.2 of the OSIRIS NO2 retrieval, which is fully described and validated in Dubé et al. (2022). Earlier versions of the NO2 retrieval were developed by Sioris et al. (2003), Haley et al. (2004), Bourassa et al. (2011), and Sioris et al. (2017). The v7.2 retrieval was designed to improve performance in the UTLS through improved cloud and aerosol filtering, and to reduce a low bias observed in the previous v6.0. The OSIRIS NO2 is available for altitudes from 10.5 to 39.5 km. As we are focused on the UTLS the averaging kernel filter discussed in Dubé et al. (2022) is used here to ensure that only NO2 values with a well‐behaved averaging kernel are included in the analysis. This filter puts a lower bound on the NO2 profiles by determining where the peak of the averaging kernel becomes more than 1.5 km different from the altitude at which information is being retrieved.

2.2. PRATMO

The PRATMO photochemical box model was initially developed by M. Prather and Jaffe (1990) and subsequently updated by McLinden et al. (2000). The reactions included in the model are listed in Logan et al. (1978) and McLinden et al. (2000). PRATMO starts with an input atmospheric state, then computes a set of chemical reactions over 1 day, iterating until the start and end values converge (M. J. Prather, 1992). The result is a 24 hr steady‐state system of all the chemical species included in the model. The inputs required by the model are ozone, temperature, air density, and pressure profiles for a specified latitude, longitude, and date. These parameters are kept constant over the course of the day. OSIRIS measures O3 so those values are used in the PRATMO runs. The model outputs are the NO2 and NO profiles at any predetermined LST.

We use PRATMO results to scale the OSIRIS NO2 observations to a common LST, and to convert the OSIRIS NO2 to NOx. The scaling of NO2 measurements to a different LST is a commonly used process that accounts for variations in the measurement time due to the precessing satellite orbit (e.g., Brohede et al., 2007; Dubé et al., 2020; Park et al., 2017). Here all OSIRIS measurements are scaled to 12:00 p.m. Details of the calculation are given in Dubé et al. (2020). The OSIRIS NO2 is converted to NOx by multiplication with the ratio of PRATMO NOx to NO2, as employed previously by Park et al. (2017) and Dubé et al. (2020).

2.3. WACCM

We perform parallel analyses on simulations from WACCM, which is a comprehensive chemistry‐climate model. WACCM details are discussed at https://www2.acom.ucar.edu/gcm/waccm, and we use the recently updated version 6 (WACCM6) described in Gettelman et al. (2019). The simulation used here has ∼1° horizontal resolution and 88 vertical levels from the surface to 140 km (∼1 km vertical resolution in the UTLS), and uses so‐called specified dynamics (SD) incorporating meteorological fields from Modern‐Era Retrospective analysis for Research and Applications Version 2 (MERRA‐2) reanalyses (Gelaro et al., 2017). The kinetic reaction rates used in WACCM are from Burkholder et al. (2015). We analyze results from one monsoon season covering 15 July–30 August 2020. To analyze diurnal variability, the model output is saved at 3‐hr intervals. The WACCM values were converted from UTC to LST by calculating the solar time in each latitude and longitude bin and interpolating between the 3‐hourly time intervals for each day to get values at a LST of 12:00 p.m.

3. Results

3.1. Photochemistry

The NOx number density and the proportion of NO2 and NO that make up the NOx both depend on the local solar time, and the balances depend on the background photochemical environment, especially O3 and temperature. The diurnal cycles of NOx components inside and outside of the ASM region derived from OSIRIS NO2 measurements and PRATMO calculations are illustrated in Figure 1. There is a sharp decrease in the NO2 concentration at sunrise as it is photolyzed to become NO via the reaction

NO2+hν→NO+O. (1)

Figure 1.

Figure 1

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Mean daily cycle in NO, NO2, and NOx at 17.5 km calculated by PRATMO with OSIRIS inputs from July 2008, contrasting behaviors inside versus outside of the Asian summer monsoon (ASM). The shaded areas are the standard deviation. Inside the ASM is defined as 20°–40°N, 20°–120°E. Outside the ASM is defined as 20°–40°N, 180°–120°W. OSIRIS NO2 measurements occur in the early morning, as indicated by the black dashed oval.

Throughout the daylight hours NO2 and NO are in approximate equilibrium as they interconvert rapidly through the reactions

NO2+O→NO+O2 (2)

and

NO+O3→NO2+O2. (3)

NO is the dominant daytime component of NOx in the UTLS, mainly due to low O3 near the tropopause (slow NO conversion from Reaction 3). At sunset Reaction 1 ceases producing NO, resulting in a rapid increase in the NO2 concentration. Overnight both the NO and NO2 amounts decrease slowly as they are converted to nitrogen containing reservoir species (primarily NO3 and N2O5). Satellite limb observations (e.g., OSIRIS) usually occur near dawn/dusk, and satellite occultation observations (including ACE‐FTS and SAGE III/ISS) occur at sunrise/sunset, so the rapidly changing chemistry at these times of day needs to be considered when interpreting the satellite measurements.

As seen in Figure 1, the relative daytime NO fraction is larger inside of the ASM compared to outside. Sensitivity tests with PRATMO show that these photochemical balances are mostly linked to low O3 in the ASM, with a secondary influence of cold temperatures (because of the temperature dependence of the rate constant in Reaction 3, e.g., Burkholder et al., 2020). For UTLS conditions, a decrease in O3 of about 50% produces 25% less NO2 and 5% more NO, while 4% lower temperatures result in about 4% less NO2 and 15% more NO at 85 hPa. Both low ozone and cold temperatures are accentuated within the UTLS ASM.

While we focus here on the partitioning of NOx between NO and NO2, it should be noted that other nitrogen‐containing compounds could also influence the overall NOx concentration. The presence of the Asian tropopause aerosol layer (Vernier et al., 2011), along with the colder temperatures in the ASM anticyclone, provide an opportunity for enhanced heterogeneous chemistry. This could result in the conversion of NOx to either N2O5 or ClONO2. Solomon et al. (2016) observed enhanced heterogeneous chlorine activation in the ASM within a model simulation, and a corresponding downwind enhancement of ClONO2, so the loss of NOx through this pathway is likely to occur.

3.2. Satellite Observations

The 30‐year average OSIRIS NO2 concentration has a minima in the ASM during the summer months. Figure 2a shows the mean NO2 volume mixing ratio (VMR) at 85 hPa in June‐July‐August (JJA) as measured by OSIRIS. The mean values include NO2 observations from 2002 to 2020. Each OSIRIS NO2 profile was interpolated from altitude to pressure levels and converted from number density to VMR using the temperature and pressure information from MERRA‐2 that is included in the data files. The approximate location of the ASM is given by the 16.75 km geopotential height contour at 100 hPa (e.g., Bourassa et al., 2012).

Figure 2.

Figure 2

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(a) Time average 85 hPa NO2 in JJA for the whole OSIRIS mission, with values scaled to 12:00 p.m. (b) Mean NOx at 85 hPa calculated from OSIRIS NO2 and PRATMO. Corresponding longitudinal anomalies in (c) NO2 and (d) NOx at 85 hPa, calculated as differences from the mean values over the Pacific Ocean (180°–120°W). Circled area is the 16.75 km geopotential height contour at 100 hPa used to identify the Asian summer monsoon.

The ASM minimum in the OSIRIS NO2 observations is most easily seen by removing the large‐scale background latitudinal structure (Figure 2c). The anomaly for a given latitude is the difference from the mean value at that latitude over the Pacific Ocean (180°–120°W), far outside of the monsoon. The NO2 is about 0.1 ppbv lower in the ASM region that it is at other longitudes.

A test was performed to ensure that shifting the OSIRIS NO2 observations to 12:00 p.m. using scale factors derived from O3 and temperature inputs to PRATMO did not produce the signal observed in Figures 2a and 2c. First we calculated the zonal mean NO2. The average PRATMO scale factor in each latitude and longitude bin was then used to scale the zonal mean NO2 to noon. This scaling did not produce significant longitudinal structure that could be associated with the ASM, providing confidence that the ASM signal in the OSIRIS NO2 observations is real, rather than produced by PRATMO.

Figure 2b shows the corresponding time average NOx derived from OSIRIS NO2 and PRATMO, also scaled to 12:00 p.m. local time. The calculated NOx is substantially higher than NO2 at all longitudes, consistent with Figure 1. NOx is relatively high in the monsoon region, as highlighted by removing the background latitudinal structure in Figure 2d. The opposite signed NO2 and NOx anomalies in Figure 2 are explained by the photochemical balances shown in Figure 1, with the result that NO and NOx are enhanced inside the ASM during the daytime, while NO2 is reduced. This behavior is mainly tied to the low O3 and low temperatures observed in the ASM.

The monthly evolution of 85 hPa NOx from the OSIRIS + PRATMO calculations (Figure 3) shows elevated NOx from May to September extending over 0°–120°E. This seasonal variation and longitudinal maximum are clear signatures of links to the ASM during summer. Figure 3 also shows a smaller region of elevated NOx from about 80° to 140°W, which could indicate an influence of the North American monsoon on the UTLS (also seen in Figure 2d).

Figure 3.

Figure 3

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Monthly average 85 hPa NOx as a function of longitude derived from OSIRIS + PRATMO calculations (scaled to 12:00). Data are averaged over 20°–40°N.

We have also examined corresponding NO2 behavior from SAGE III/ISS and ACE‐FTS sunset occultations. Time average anomalies in NO2 from both ACE‐FTS and SAGE III/ISS are negative within the ASM region (Figure S1 in Supporting Information S1), as they are for OSIRIS (Figure 2c). The daily photochemical cycle in NO2 (Section 3.1) makes it challenging to perform quantitative comparisons to OSIRIS. Measurements at the terminator cannot be accurately scaled to a different local solar time because the radiative transfer in PRATMO uses a simplified plane‐parallel atmosphere. This prevents modeling NO2 and NO at the terminator with the precision required for the rapidly changing conditions. The ACE‐FTS NO has a maximum within the ASM anticyclone (bottom panel of Figure S1 in Supporting Information S1), despite having large uncertainties at this pressure level. At sunset, the balance of NO and NO2 starts to switch so there is less NO than NO2, which is why the ACE‐FTS NO anomaly is smaller than the NO2 anomaly.

3.3. WACCM Simulations

The WACCM time average NO2, NO, and NOx anomalies are in good agreement with those from the satellite instruments. Figure 4 shows the WACCM output at 85 hPa and 12:00 p.m. The NO2 anomaly is low in the ASM region, as it is for each of OSIRIS, ACE‐FTS, and SAGE III/ISS. The WACCM NO anomaly has a maxima in the ASM that is substantially larger than the NO2 minimum. The corresponding WACCM NOx has an ASM maximum that is similar in sign and magnitude to the NOx derived from the OSIRIS + PRATMO calculations (Figure 2d).

Figure 4.

Figure 4

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Whole Atmosphere Community Climate Model time average NO, NO2, and NOx at 85 hPa from July 15 to 30 August 2020. Values were interpolated to a local time of 12:00 p.m. in each bin. The anomaly at each latitude is the difference from the mean value at that latitude over the Pacific ocean (180°–120°W). Circled area is the 16.75 km geopotential height contour at 100 hPa.

The vertical structure of the monsoon NOx behavior from OSIRIS observations and WACCM are compared in Figure 5, which shows the percent differences for the NO2 and NOx inside versus outside of the ASM as a function of pressure level. Percent differences are used to highlight UTLS vertical structure and de‐emphasize the background NOx increase with altitude in the stratosphere. We additionally include the corresponding O3 difference profiles in Figure 5 because of their importance in the NOx balances; these show the well‐known reduced UTLS O3 within the ASM (e.g., Park et al., 2007, 2008), with somewhat larger anomalies in OSIRIS compared to WACCM. Both the OSIRIS and WACCM results show negative anomalies in NO2 within the ASM extending from ∼100 to 60 hPa. The maximum relative NO2 difference occurs at the 85 hPa level, overlapping the large negative ozone anomalies within the ASM.

Figure 5.

Figure 5

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Vertical profiles of JJA anomalies in NO2, NOx, and O3 inside versus outside the Asian summer monsoon for OSIRIS and Whole Atmosphere Community Climate Model (WACCM). Results are shown in terms of local percentage anomalies. The Asian monsoon region is defined as inside the 16.75 km WACCM geopotential height contour at 100 hPa, while the outside monsoon region is defined as 20°–40°N, 180°–120°W. NO2 and NOx results are for 12:00 p.m. The black horizontal line marks the 85 hPa level used in the other figures.

The NOx anomaly is positive for both OSIRIS + PRATMO and WACCM throughout the UTLS region. ASM NOx anomalies near the tropopause are ∼25% inside larger than outside, with bigger relative anomalies at lower altitudes (in WACCM). Hence the satellite measurements (above ∼100 hPa) are observing the top of the ASM. Overall, there is reasonable quantitative agreement between the observations and model simulation in terms of profile shape and magnitude.

4. Conclusion

The influence of the ASM anticyclone on NO2, NO, and NOx was investigated using observations from OSIRIS, SAGE III/ISS, and ACE‐FTS, along with the PRATMO box model and chemistry‐climate model output from WACCM. While the OSIRIS, SAGE III/ISS and ACE‐FTS data show a relative minimum in NO2 near the tropopause within the ASM, the PRATMO calculations show enhanced NO and NOx in the monsoon. The enhanced NOx within the monsoon region derived from satellite observations agrees quantitatively with chemistry‐climate model simulations from WACCM, including chemical isolation within the anticyclone and consistent vertical profiles. The enhanced NOx levels in the UTLS ASM likely result from a combination of upwards transport of surface level pollutants and production by lightning, as shown in modeling studies (e.g., Fadnavis et al., 2015; Lelieveld et al., 2018; Roy et al., 2017). Here we find that the low background O3 amounts and cold temperatures in the UTLS, which are accentuated in the ASM, shift the daytime NOx balances toward enhanced NO and reduced NO2. The satellite observations presented here provide a method to evaluate NOx behavior in chemistry‐climate models.

Supporting information

Supporting Information S1

Click here for additional data file. (431.8KB, pdf)

Acknowledgments

The authors thank the Swedish National Space Agency and the Canadian Space Agency for the continued operation and support of Odin‐OSIRIS. The National Center for Atmospheric Research is operated by the University Corporation for Atmospheric Research, under sponsorship of the US National Science Foundation. This work was partially supported by the NASA Aura Science Team under Grant 80NSSC20K0928.

Dubé, K. , Randel, W. , Bourassa, A. , & Degenstein, D. (2022). Tropopause‐level NOx in the Asian summer monsoon. Geophysical Research Letters, 49, e2022GL099848. 10.1029/2022GL099848

Data Availability Statement

OSIRIS data, including the PRATMO derived NOx and values scaled to noon, are available at ftp://odin-osiris.usask.ca/OSIRIS/Level2/. SAGE III/ISS NO2 data accounting for diurnal variations along the line of sight are available at ftp://odin-osiris.usask.ca/SAGEIII_ISS. The WACCM results are available at ftp://odin-osiris.usask.ca/Models. Instructions for downloading the OSIRIS, SAGE III/ISS and WACCM files are at https://research-groups.usask.ca/osiris/data-products.php#Download. ACE data are available by signing up at https://databace.scisat.ca/l2signup.php. The PRATMO python package can be downloaded from https://arg.usask.ca/wheels/ and documentation is available at https://arg.usask.ca/docs/Pratmo/pratmo_boxmodel.html. The WACCM model is available at https://www.cesm.ucar.edu/models/cesm2/.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supporting Information S1

Click here for additional data file. (431.8KB, pdf)

Data Availability Statement

OSIRIS data, including the PRATMO derived NOx and values scaled to noon, are available at ftp://odin-osiris.usask.ca/OSIRIS/Level2/. SAGE III/ISS NO2 data accounting for diurnal variations along the line of sight are available at ftp://odin-osiris.usask.ca/SAGEIII_ISS. The WACCM results are available at ftp://odin-osiris.usask.ca/Models. Instructions for downloading the OSIRIS, SAGE III/ISS and WACCM files are at https://research-groups.usask.ca/osiris/data-products.php#Download. ACE data are available by signing up at https://databace.scisat.ca/l2signup.php. The PRATMO python package can be downloaded from https://arg.usask.ca/wheels/ and documentation is available at https://arg.usask.ca/docs/Pratmo/pratmo_boxmodel.html. The WACCM model is available at https://www.cesm.ucar.edu/models/cesm2/.

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