Total Column O3 Research Articles

Global agricultural N2O emission reduction strategies deliver climate benefits with minimal impact on stratospheric O3 recovery

Agricultural nitrous oxide (N2O) emission reduction strategies are required given the potency of N2O as a greenhouse gas. However, the growing influence of N2O on stratospheric ozone (O3) with declining stratospheric chlorine means the wider atmospheric impact of N2O reductions requires investigation. We calculate a N2O emission reduction of 1.35 TgN2O yr-1 (~5% of 2020 emissions) using spatially separate deployment of nitrification inhibitors ($70–113 tCO2e−1) and crushed basalt (no-cost co-benefit) which also sequesters CO2. In Earth System model simulations for 2025–2075 under high (SSP3-7.0) and low (SSP1-2.6) surface warming scenarios, this N2O mitigation reduces NOx-driven O3 destruction, driving regional stratospheric O3 increases but with minimal impact on total O3 column recovery. By 2075, the radiative forcing of the combined N2O and CO2 reductions equates to a beneficial 9–11 ppm CO2 removal. Our results support targeted agricultural N2O emission reductions for helping nations reach net-zero without hindering O3 recovery.

Understanding the spatial and seasonal variation of the ground-level ozone in Southeast China with an interpretable machine learning and multi-source remote sensing

Ground-level ozone (O3) pollution poses significant threats to both human health and air quality. This study uses ground observations and satellite retrievals to explore the spatiotemporal characteristics of ground-level O3 in Zhejiang Province, China. We created data-driven machine learning models that include meteorological, geographical and atmospheric parameters from multi-source remote sensing products, achieving good performance (Pearson's r of 0.81) in explaining regional O3 dynamics. Analyses revealed the crucial roles of temperature, relative humidity, total column O3, and the distributions and interactions of precursor (volatile organic compounds and nitrogen oxides) in driving the varied O3 patterns observed in Zhejiang. Furthermore, the interpretable modeling quantified multifactor interactions that sustain high O3 levels in spring and autumn, suppress O3 levels in summer, and inhibit O3 formation in winter. This work demonstrates the value of a combined approach using satellite and machine learning as an effective novel tool for regional air quality assessment and control.

Degenerate Interpretations of O3 Spectral Features in Exoplanet Atmosphere Observations Due to Stellar UV Uncertainties: A 3D Case Study with TRAPPIST-1 e

TRAPPIST-1 e is a potentially habitable terrestrial exoplanet orbiting an ultracool M dwarf star and is a key target for observations with the James Webb Space Telescope. One-dimensional photochemical modeling of terrestrial planetary atmospheres has shown the importance of the incoming stellar UV flux in modulating the concentration of chemical species, such as O3 and H2O. In addition, three-dimensional (3D) modeling has demonstrated anisotropy in chemical abundances due to transport in tidally locked exoplanet simulations. We use the Whole Atmosphere Community Climate Model Version 6 (WACCM6), a 3D Earth system model, to investigate how uncertainties in the incident UV flux, combined with transport, affect observational predictions for TRAPPIST-1 e (assuming an initial Earth-like atmospheric composition). We use two semiempirical stellar spectra for TRAPPIST-1 from the literature. The UV flux ratio between them can be as large as a factor of 5000 in some wavelength bins. Consequently, the photochemically produced total O3 columns differ by a factor of 26. Spectral features of O3 in both transmission and emission spectra vary between these simulations (e.g., differences of 20 km in the transmission spectrum effective altitude for O3 at 0.6 μm). This leads to potential ambiguities when interpreting observations, including overlap with scenarios that assume alternative O2 concentrations. Hence, to achieve robust interpretations of terrestrial exoplanetary spectra, characterization of the UV spectra of their host stars is critical. In the absence of such stellar measurements, atmospheric context can still be gained from other spectral features (e.g., H2O), or by comparing direct imaging and transmission spectra in conjunction.

Stratospheric dynamics modulates ozone layer response to molecular oxygen variations

Photolysis of molecular oxygen (O2) sustains the stratospheric ozone layer and is thereby protecting living organisms on Earth by absorbing harmful ultraviolet radiation. In the past, atmospheric O2 levels were not constant, and their variations are thought to be responsible for the extinction of some species due to the thinning of the ozone layer. Over the Phanerozoic Eon (last ∼500 Mio years), the O2 volume mixing ratio ranged between 10% and 35% depending on the level of photosynthetic activity of plants and oceans. Previous estimates, mostly performed by simplified 1-D models, showed different ozone (O3) responses to atmospheric O2 changes within this range, such as monotonically positive or negative correlations, or displaying a maximum in the O3 column around a certain O2 level. Here, we assess the ozone layer sensitivity to atmospheric O2 varying between 5% and 40% with a state-of-the-art 3-D chemistry-climate model (CCM). Our findings show that the O3 layer thickness maximizes around the current mixing ratio of O2, 21% ± 5%, while lower or higher levels of O2 result globally in a reduction of total column O3. At low latitudes, the total column O3 is less sensitive to O2 variations, because of the “self-healing” effect, namely, a vertical dipole in the tropical ozone response. Mid- and high-latitude O3 columns that are largely affected by transport of O3 from the tropics, however, are much more sensitive to O2 with changes up to 20 DU even for small (±5%) O2 perturbations. We show that these variations are largely driven by the radiative impact of O3 on stratospheric temperatures and on the strength of the Brewer-Dobson circulation (BDC), indicating chemistry-radiation-transport feedback. High O2 cases result in an acceleration of the BDC and vice versa, which always works in favor of the negative part of the O3 anomaly dipole in the tropics being more effectively transported to the mid- and high-latitudes than the positive one. Although there are other factors strongly influencing O3/O2 relationship on the Phanerozoic Eon timescales that have not been considered here, our results and the presented mechanism bring useful insights for other studies focusing on the long-term O3/O2 relationship.

Algorithm theoretical basis for ozone and sulfur dioxide retrievals from DSCOVR EPIC

Abstract. On board the Deep Space Climate Observatory (DSCOVR), the first Earth-observing satellite at the L1 point (the first Lagrangian point in the Earth–Sun system), the Earth Polychromatic Imaging Camera (EPIC) continuously observes the entire sunlit face of the Earth. EPIC measures the solar backscattered and reflected radiances in 10 discrete spectral channels, four of which are in the ultraviolet (UV) range. These UV bands are selected primarily for total ozone (O3) and aerosol retrievals based on heritage algorithms developed for the series of Total Ozone Mapping Spectrometers (TOMS). These UV measurements also provide sensitive detection of sulfur dioxide (SO2) and volcanic ash, both of which may be episodically injected into the atmosphere during explosive volcanic eruptions. This paper presents the theoretical basis and mathematical procedures for the direct vertical column fitting (DVCF) algorithm used for retrieving total vertical columns of O3 and SO2 from DSCOVR EPIC. This paper describes algorithm advances, including an improved O3 profile representation that enables profile adjustments from multiple spectral measurements and the spatial optimal estimation (SOE) scheme that reduces O3 artifacts resulting from EPIC's band-to-band misregistrations. Furthermore, this paper discusses detailed error analyses and presents intercomparisons with correlative data to validate O3 and SO2 retrievals from EPIC.

Estimation of surface ozone concentration over Jiangsu province using a high-performance deep learning model

Recently, the global background concentration of ozone (O3) has demonstrated a rising trend. Among various methods, groun-based monitoring of O3 concentrations is highly reliable for research analysis. To obtain information on the spatial characteristics of O3 concentrations, it is necessary that the ground monitoring sites be constructed in sufficient density. In recent years, many researchers have used machine learning models to estimate surface O3 concentrations, which cannot fully provide the spatial and temporal information contained in a sample dataset. To solve this problem, the current study utilized a deep learning model called the Residual connection Convolutional Long Short-Term Memory network (R-ConvLSTM) to estimate daily maximum 8-hr average (MDA8) O3 over Jiangsu province, China during 2020. In this research, the R-ConvLSTM model not only provides the spatiotemporal information of MDA8 O3, but also involves residual connection to avoid the problem of gradient explosion and gradient disappearance with the deepening of network layers. We utilized the TROPOMI total O3 column retrieved from Sentinel-5 Precursor, ERA5 reanalysis meteorological data, and other supplementary data to build a pre-trained dataset. The R-ConvLSTM model achieved an overall sample-base cross-validation (CV) R2 of 0.955 with root mean square error (RMSE) of 9.372 µg/m3. Model estimation also showed a city-based CV R2 of 0.896 with RMSE of 14.029 µg/m3, the highest MDA8 O3 in spring being 122.60 ± 31.60 µg/m3 and the lowest in winter being 69.93 ± 18.48 µg/m3.

New Deep Learning Model to Estimate Ozone Concentrations Found Worrying Exposure Level over Eastern China.

Ozone (O3), whose concentrations have been increasing in eastern China recently, plays a key role in human health, biodiversity, and climate change. Accurate information about the spatiotemporal distribution of O3 is crucial for human exposure studies. We developed a deep learning model based on a long short-term memory (LSTM) network to estimate the daily maximum 8 h average (MDA8) O3 across eastern China in 2020. The proposed model combines LSTM with an attentional mechanism and residual connection structure. The model employed total O3 column product from the Tropospheric Monitoring Instrument, meteorological data, and other covariates as inputs. Then, the estimates from our model were compared with real observations of the China air quality monitoring network. The results indicated that our model performed better than other traditional models, such as the random forest model and deep neural network. The sample-based cross-validation R2 and RMSE of our model were 0.94 and 10.64 μg m−3, respectively. Based on the O3 distribution over eastern China derived from the model, we found that people in this region suffered from excessive O3 exposure. Approximately 81% of the population in eastern China was exposed to MDA8 O3 > 100 μg m−3 for more than 150 days in 2020.

Analysis of significant stratospheric ozone reductions over southern Brazil: A proposal for a diagnostic index for southern South America

AbstractDuring the southern spring, a break of the polar vortex over the Antarctic continent frequently occurs. This results in the advection of ozone‐poor air mass (O3) to mid‐latitudes, characterizing the secondary effect of the Antarctic ozone hole (SEAOH). We present some distinct characteristics the eight greatest reductions of the total O3 column (TOC) over the central region of Rio Grande do Sul (RS, 29.5°S, 54°W), southern Brazil, between August and November from 2012 to 2016 and develop a full scalar diagnostic index of O3 negative anomalies for South America. For developing the index, mean values of the absolute potential vorticity, geopotential height, and wind components were obtained over moving grids with positive and negative O3 anomalies. It was then possible to develop statistical methods to obtain a diagnostic index of the SEAOH (Subantarctic O3 Index), as well as a diagnostic index of incursions of ozone‐poor air masses from the tropics (Subtropical O3 Index). The results show that TOC over the central region of RS, for the most intense O3 reduction episodes, is governed by a wide range of contributions from high and low isentropic levels. Significant interaction of air masses of polar and tropical origin via stratosphere–troposphere exchange was found. Finally, the Subantarctic O3 Index combined with the Subtropical O3 Index showed potential use for prediction centres and was skilful in detecting regions with the most negative O3 anomalies, mainly in the mid‐latitude region, but also in the subtropical region.

Situation of Urban Mobility in Pakistan: Before, during, and after the COVID-19 Lockdown with Climatic Risk Perceptions

The coronavirus pandemic (COVID-19) has impacted the usual global movement patterns, atmospheric pollutants, and climatic parameters. The current study sought to assess the impact of the COVID-19 lockdown on urban mobility, atmospheric pollutants, and Pakistan’s climate. For the air pollution assessment, total column ozone (O3), sulphur dioxide (SO2), and tropospheric column nitrogen dioxide (NO2) data from the Ozone Monitoring Instrument (OMI), aerosol optical depth (AOD) data from the Multi-angle Imaging Spectroradiometer (MISR), and dust column mass density (PM2.5) data from the MERRA-2 satellite were used. Furthermore, these datasets are linked to climatic parameters (temperature, precipitation, wind speed). The Kruskal–Wallis H test (KWt) is used to compare medians among k groups (k > 2), and the Wilcoxon signed-rank sum test (WRST) is for analyzing the differences between the medians of two datasets. To make the analysis more effective, and to justify that the variations in air quality parameters are due to the COVID-19 pandemic, a Generalized Linear Model (GLM) was used. The findings revealed that the limitations on human mobility have lowered emissions, which has improved the air quality in Pakistan. The results of the study showed that the climatic parameters (precipitation, Tmax, Tmin, and Tmean) have a positive correlation and wind speed has a negative correlation with NO2 and AOD. This study found a significant decrease in air pollutants (NO2, SO2, O3, AOD) of 30–40% in Pakistan during the strict lockdown period. In this duration, the highest drop of about 28% in NO2 concentrations has been found in Karachi. Total column O3 did not show any reduction during the strict lockdown, but a minor decline was depicted as 0.38% in Lahore and 0.55% in Islamabad during the loosening lockdown. During strict lockdown, AOD was reduced up to 23% in Islamabad and 14.46% in Lahore. The results of KWt and WRST evident that all the mobility indices are significant (p < 0.05) in nature. The GLM justified that restraining human activities during the lockdown has decreased anthropogenic emissions and, as a result, improved air quality, particularly in metropolitan areas.

Remote Sensing of Atmospheric CO and O3 Anomalies before and after Two Yutian MS7.3 Earthquakes

Satellite remote sensing data were used to extract concentrations and volume mixing ratios (VMR) of CO and O3 and Global Data Assimilation System (GDAS) data associated with Yutian MS7.3 earthquakes on March 21, 2008, and February 12, 2014. Difference value and anomaly index methods and the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model were used to simulate gas backward trajectories and analyze the relations between spatial and temporal variations in total columns of CO and O3 (TotCO and TotO3) and earthquakes. Then, the causes of abnormal changes were examined. Maximum anomalies in TotCO and TotO3 occurred one month before the 2008 earthquake and one month after the 2014 earthquake. Anomalies in TotCO and TotO3 were distributed along or were consistent with the fault zone. Furthermore, during the abnormal period, the coefficient of correlation between CO and O3 was 0.672 in 2008 and 0.638 in 2014, with both values significant at p < 0.05 . The correlation between TotCO and TotO3 was also significant. The abnormal phenomena of TotCO and TotO3 associated with the two earthquakes were attributed to underground gas escape, atmospheric chemical reactions, and atmospheric transportation caused by in situ stress in the generation of earthquakes.

Assessment of variations of air pollutant concentrations during the COVID-19 lockdown and impact on urban air quality in South Asia

Quantifying the variations of atmospheric aerosols and trace gas concentrations with the impact of lockdown due to the Coronavirus disease of 2019 (COVID-19) pandemic is crucial in understanding urban air quality. For this purpose, we utilized the multi-instrumental approach of satellite remote sensing and reanalysis model data to examine the spatial and temporal patterns of major air pollutants during December 2019–June 2020 in South Asia. The lockdown has to lead to a considerable decrease in aerosol optical thickness (AOT) over South China (−18.92%) and Indo-Gangetic Plain (IGP; −24.29%) compared to its ordinary level for a couple of weeks. Noticeable reductions in tropospheric NO2 are observed over the Pearl River Delta (PRD; −0.3/cm2) followed by Central China (CC) with −0.21/cm2and IGP (−0.085/cm2), and the lowest (−0.0008/cm2) in the Tibetan Plateau (TP) region. The changes observed in PM2.5 and SO2 levels (from −58.56% to - 63.64%) are attributed to the decrease in anthropogenic emissions, vehicular exhaust, and industrial activities. However, the BC concentrations are reduced by approximately halved of its ordinary levels in the IGP (−2.28 μg/m3) followed by YRD (−1.56 μg/m3), CC (−1.5 μg/m3), NCP (−1.29 μg/m3), and PRD (−0.78 μg/m3) regions. The total column O3 predominantly increased from 262.68 to 285.53DU, 323.00 to 343.00DU, and 245.00 to 265.00DU in the YRD, NCP, and IGP areas. This is mainly associated with solar radiation, meteorological factors, and an unprecedented reduction in NOx during the lockdown period.

Atmospheric trace gas trends obtained from FTIR column measurements in Toronto, Canada from 2002-2019

Total columns of C2H2, C2H6, CH4, CH3OH, CO, H2CO, HCl, HCN, HCOOH, HF, HNO3, N2O, NH3 and O3 were retrieved from 2002-2019 using a Fourier transform infrared (FTIR) spectrometer at the University of Toronto Atmospheric Observatory (TAO). Trends and enhancement events were determined by fitting trended Fourier series, and bootstrapping was used to identify the statistical significance. Trends from 2002 to 2019 (%/year, with 2σuncertainties) were found for C2H2 (−1.12 ± 0.30), C2H6 (−0.74 ± 0.73 from 2002–2008 and 1.19 ± 0.27 from 2009–2019), CH4 (0.26 ± 0.10 from 2002–2008 and 0.41 ± 0.03 from 2009–2019), CO (−0.90 ± 0.07), HCN (−0.51 ± 0.21), HCOOH (−2.15 ± 0.64), HF (0.59 ± 0.11), HNO3 (0.36 ± 0.13), N2O (0.28 ± 0.02), NH3 (3.56 ± 0.85), and O3 (0.28 ± 0.19 and −0.05 ± 0.07 for tropospheric and stratospheric columns, respectively). The GEOS-Chem chemical transport model showed that wetland emissions were the largest contributor to CH4 columns measured at TAO (average relative contribution of 31.7%), and that CH4 oxidation was a major source of CO (accounting for 30.9%).

Verification of the Atmospheric Infrared Sounder (AIRS) and the Microwave Limb Sounder (MLS) ozone algorithms based on retrieved daytime and night-time ozone

Abstract. Ozone (O3) plays a significant role in weather and climate on regional to global spatial scales. Most studies on the variability in the total column of O3 (TCO) are typically carried out using daytime data. Based on knowledge of the chemistry and transport of O3, significant deviations between daytime and night-time O3 are only expected either in the planetary boundary layer (PBL) or high in the stratosphere or mesosphere, with little effect on the TCO. Hence, we expect the daytime and night-time TCO to be very similar. However, a detailed evaluation of satellite measurements of daytime and night-time TCO is still lacking, despite the existence of long-term records of both. Thus, comparing daytime and night-time TCOs provides a novel approach to verifying the retrieval algorithms of instruments such as the Atmospheric Infrared Sounder (AIRS) and the Microwave Limb Sounder (MLS). In addition, such a comparison also helps to assess the value of night-time TCO for scientific research. Applying this verification on the AIRS and the MLS data, we identified inconsistencies in observations of O3 from both satellite instruments. For AIRS, daytime–night-time differences were found over oceans resembling cloud cover patterns and over land, mostly over dry land areas, which is likely related to infrared surface emissivity. These differences point to issues with the representation of both processes in the AIRS retrieval algorithm. For MLS, a major issue was identified with the “ascending–descending” orbit flag, used to discriminate night-time and daytime MLS measurements. Disregarding this issue, MLS day–night differences were significantly smaller than AIRS day–night differences, providing additional support for the retrieval method origin of AIRS in stratospheric column ozone (SCO) day–night differences. MLS day–night differences are dominated by the upper-stratospheric and mesospheric diurnal O3 cycle. These results provide useful information for improving infrared O3 products.

Observational evidence of energetic particle precipitation NO<sub><i>x</i></sub> (EPP-NO<sub><i>x</i></sub>) interaction with chlorine curbing Antarctic ozone loss

Abstract. We investigate the impact of the so-called energetic particle precipitation (EPP) indirect effect on lower stratospheric ozone, ClO, and ClONO2 in the Antarctic springtime. We use observations from the Microwave Limb Sounder (MLS) and Ozone Monitoring Instrument (OMI) on Aura, the Atmospheric Chemistry Experiment – Fourier Transform Spectrometer (ACE-FTS) on SCISAT, and the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) on Envisat, covering the period from 2005 to 2017. Using the geomagnetic activity index Ap as a proxy for EPP, we find consistent ozone increases with elevated EPP during years with an easterly phase of the quasi-biennial oscillation (QBO) in both OMI and MLS observations. While these increases are the opposite of what has previously been reported at higher altitudes, the pattern in the MLS O3 follows the typical descent patterns of EPP-NOx. The ozone enhancements are also present in the OMI total O3 column observations. Analogous to the descent patterns found in O3, we also found consistent decreases in springtime MLS ClO following winters with elevated EPP. To verify if this is due to a previously proposed mechanism involving the conversion of ClO to the reservoir species ClONO2 in reaction with NO2, we used ClONO2 observations from ACE-FTS and MIPAS. As ClO and NO2 are both catalysts in ozone destruction, the conversion to ClONO2 would result in an ozone increase. We find a positive correlation between EPP and ClONO2 in the upper stratosphere in the early spring and in the lower stratosphere in late spring, providing the first observational evidence supporting the previously proposed mechanism relating to EPP-NOx modulating Clx-driven ozone loss. Our findings suggest that EPP has played an important role in modulating ozone depletion in the last 15 years. As chlorine loading in the polar stratosphere continues to decrease in the future, this buffering mechanism will become less effective, and catalytic ozone destruction by EPP-NOx will likely become a major contributor to Antarctic ozone loss.

Ozone Trends during 1979–2019 over Tibetan Plateau Derived from Satellite Observations

Ozone (O3) is a very important atmospheric component related to many atmospheric processes. Tibetan Plateau (TP) has played an important role to weather and climate in South Asia and was found to modulate the variation of ozone amount, leading to the ozone low over the TP in both the summer and winter. To better understand the changing trend of ozone, a novel statistic method, i.e. the Ensemble Empirical Mode Decomposition (EEMD) method, is used to analyze the trends of total column O3 (TCO) and the ozone deficit after removing the corresponding zonal mean TCO over the TP. Data of TCO over TP is from satellite observations by OMI/Aura, and for comparison the long-term Merged Ozone Data from NASA is used to analyze the trend of TCO in three latitude zones near TP. In consistent with some other studies, slightly recovery of ozone at 1996-1997 is evident from the zonal mean in three latitude zones between 25oN to 40oN in northern hemisphere, however after 2013 only the north of TP shows an increase trend but the zonal mean between 30oN to 40oN show decrease trends. In contrast, TCO over the TP shows a consistent increase trend from 2004 to 2019, and the ozone deficit over the TP has a rapid increase trend after 2013, with a larger increase trend in the winter season than in the summer. Further analysis to the ozone low events in the winter and summer from 2004 to 2019 shows that the ozone low in May is much deeper and lasts longer than that in the winter. These results show the mechanism of ozone low and its trend in winter is more complex and worthy for more investigation.

Annular Solar Eclipse on 26 December 2019 and its Effect on Trace Pollutant Concentrations and Meteorological Parameters in Kannur, India: a Coastal City

This paper highlights the variations of surface ozone (O3), total column ozone (TCO), oxides of nitrogen (NO and NO2), carbon monoxide (CO), sulphur dioxide (SO2), ammonia (NH3), volatile organic compounds (Benzene, Tolune, Ethyle Benzene, Xylenes (collectively called BTEX)), particulate matters (PM10 and PM2.5), and meteorological parameters at the time of an annular solar eclipse on 26 December 2019 at Kannur town in Kerala, South India. The maximum solar obscuration has resulted a decrease in solar radiation by 93%, air temperature by 16.3%, wind speed by 36.1% and an increase in relative humidity by 27.1% at this coastal location. Along with the reduction in solar radiation, the concentration of surface O3 (61.5%) and total column O3 (11.8%) have been observed to decrease at the maximum phase of solar eclipse. CO and NO2 concentration were found to be increased by 28.9% and 42.2%, respectively, while NO exhibited its typical diurnal variation. Further, a decrease in concentrations of SO2 by 17.6%, PM10 by 18.5%, and PM2.5 by 11.3% were observed. NH3 and BTEX were found to be higher than 11.3% and 22.6% of the concentrations in control days. All of these deviated parameters could be seen returning to their normal state after completing the eclipse episode. The variation of photodissociation coefficient j(NO2) values were theoretically calculated from the observed data, which shows a good agreement with the model simulated j(NO2) reduction. This is an extensive second observation on the variation of trace pollutants on solar eclipse, after the partial solar eclipse observed on 15 January 2010 at Kannur.

Comparisons of upper air ozone at a coastal and urban site and the impacts of non-controllable ozone sources

Abstract This study quantified the impact of non-controllable and urban emission sources on the enhancement of ozone (O3) in the troposphere. These enhancements were investigated using data from simultaneous ozonesonde launches at Half Moon Bay (HMB), CA and San Jose (SJ), CA on eleven dates in July and August 2018. The urban O3 enhancement in the SJ vertical profile was derived by subtracting out HMB, which represents baseline O3, from the urban SJ profile. Within the planetary boundary layer (PBL), urban emissions had a large impact on SJ, as SJ O3 was 20–30 ppb higher than HMB for all dates. Above the PBL, most enhancement profiles remained close to zero, indicating little differences aloft between HMB and SJ. The two sites had strong correlation coefficients (CCs), highlighting the influence of baseline O3 on SJ. A major axis regression for all vertical levels between SJ and HMB revealed a slope of 1.00 SJ ppb/HMB ppb and intercept of 0.004 ppb. The percent contribution of mixing layer (ML) O3 to tropospheric O3 and tropospheric O3 to total column O3 demonstrates the predominant influence of baseline O3 on the O3 profile, even over a polluted urban region. The contribution of ML O3 was low for all dates, between 2 and 6%, whereas the tropospheric contribution was 11–18%. These findings emphasize the importance of baseline O3 in regions with reduced vertical mixing; polluted urban air near the surface has minimal impacts on O3 concentrations above the PBL.

Dynamical nature of tropospheric ozone over a tropical location in Peninsular India: Role of transport and water vapour

This paper deals with the temporal changes in the altitude distribution of tropospheric ozone (O3) based on the measurements by balloon-borne O3-sondes during 2011–2014, conducted at the tropical, coastal site Thiruvananthapuram on the south west coast of India. This is the first study from this region addressing the highly dynamic nature of tropospheric O3 profiles (in terms of their vertical structure and short-term changes) and attempting to categorise them based on 121 in-situ measured O3 profiles. The tropospheric O3 profiles could be categorised into four major groups namely (i) those with steady O3 mixing ratio (ii) with increasing mixing ratio, (iii) with mid-tropospheric enhancement and (iv) with multiple layers/laminar nature. The causative mechanisms of these different categories were examined. The observed differences in the tropospheric O3 distribution are attributed to meteorological conditions in particular the synoptic scale systems, long range transport, intrusion from stratosphere and photochemistry, most importantly, the effect of water vapour content. Water vapour and O3 showed complex dependence with positive and negative association depending on the precursor levels and availability of water vapour. The altitudinal changes in O3 also exhibited close association with those of potential temperature and equivalent potential temperature. An analysis of the seasonal characteristics of vertical distribution of tropospheric O3 also carried out along with the altitude-dependent seasonal behaviour. In general, the total column O3 estimated by the integration of O3-sonde retrieved profiles differed by about ±10% with those retrieved by satellite-based measurements. The TCO contributes to about 16% (34 DU) of the total column O3, with minimum of 9% in October and maximum of 27% on March. In general, the OMI retrievals under-estimates the O3-sonde derived TCO by 5–10 DU in all the seasons.

Ozone profile climatology for remote sensing retrieval algorithms

Abstract. New ozone (O3) profile climatologies are created from the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) O3 record between 2005 and 2016, within the period of Aura Microwave Limb Sounder (MLS) and Aura Ozone Monitoring Instrument (OMI) assimilation. These two climatologies consist of monthly mean O3 profiles and the corresponding covariances dependent on the local solar time, longitude (15∘), and latitude (10∘), which are parameterized by tropopause pressure and total O3 column. They are validated through comparisons, which show good agreements with previous O3 profile climatologies. Compared to a monthly zonal mean climatology, both tropopause- and column-dependent climatologies provide improved a priori information for profile and total O3 retrievals from remote sensing measurements. Furthermore, parameterization of the O3 profile with total column O3 usually reduces the natural variability of the resulting climatological profile in the upper stratosphere further than the tropopause parameterization, which usually performs better in the upper troposphere and lower stratosphere (UTLS). Therefore tropopause-dependent climatology is more appropriate for profile O3 retrieval for complementing the vertical resolution of backscattered ultraviolet (UV) spectra, while the column-dependent climatology is more suited for use in total O3 retrieval algorithms, with an advantage of complete profile specification without requiring ancillary information. Compared to previous column-dependent climatologies, the new MERRA-2 column-dependent climatology better captures the diurnal, seasonal, and spatial variations and dynamical changes in O3 profiles with higher resolutions in O3, latitude, longitude, and season. The new MERRA-2 climatologies contain the first quantitative characterization of O3 profile covariances, which facilitate a new approach to improve O3 profiles using the most probable patterns of profile adjustments represented by the empirical orthogonal functions (EOFs) of the covariance matrices. The MERRA-2 daytime column-dependent climatology is used in the combo O3 and SO2 algorithm for retrieval from the Earth Polychromatic Imaging Camera (EPIC) on board the Deep Space Climate Observatory (DSCOVR) satellite, the Ozone Mapping and Profiler Suite Nadir Mapper (OMPS-NM) on the Suomi National Polar Partnership (SNPP), and the Ozone Monitoring Instrument (OMI) on the Aura spacecraft.

Observed response of stratospheric and mesospheric composition to sudden stratospheric warmings

In this study we investigate and quantify the statistical changes that occur in the stratosphere and mesosphere during 37 sudden stratospheric warming (SSW) events from 1989 to 2016. We consider changes in the in-situ ozonesonde observations of the stratosphere from four sites in the northern hemisphere (Ny-Ålesund, Sodankylä, Lerwick, and Boulder). These data are supported by Aura/MLS satellite observations of the ozone volumetric mixing ratio above each site, and also ground-based total-column O3 and NO2, and mesospheric wind measurements, measured at the Sodankylä site. Due to the long-time periods under consideration (weeks/months) we evaluate the observations explicitly in relation to the annual mean of each data set. Following the onset of SSWs we observe an increase in temperature above the mean (for sites usually within the polar vortex) that persists for >∼40 days. During this time the stratospheric and mesospheric ozone (volume mixing ratio and partial pressure) increases by ∼20% as observed by both ozonesonde and satellite instrumentation. Ground-based observations from Sodankylä demonstrate the total column NO2 does not change significantly during SSWs, remaining close to the annual mean. The zonal wind direction in the mesosphere at Sodankylä shows a clear reversal close to SSW onset. Our results have broad implications for understanding the statistical variability of atmospheric changes occurring due to SSWs and provides quantification of such changes for comparison with modelling studies.