Search Results (11)

The severe ozone depletion over the Southern polar region, known as the “ozone hole,” is a stark example of global ozone depletion caused by human-made chemicals. This has implications for climate change and increased harmful surface solar UV. Several Chemistry–Climate models (CCMs) tend to underestimate total column ozone (TCO) against satellite measurements over the Southern polar region. This underestimation can reach up to 50% in monthly mean zonally averaged biases during cold seasons. The most significant discrepancies were found in the CCM SOlar Climate Ozone Links version 3 (SOCOLv3). We use SOCOLv3 to study the sensitivity of Antarctic TCO to three key factors: (1) stratospheric heterogeneous reaction efficiency, (2) meridional flux intensity into polar regions from sub-grid scale mixing, and (3) photodissociation rate calculation accuracy. We compared the model results with satellite data from Infrared Fourier Spectrometer-2 (IKFS-2), Microwave Limb Sounder (MLS), and Michelson Interferometer for Passive Atmospheric Sounding (MIPAS). The most effective processes for improving polar ozone simulation are photolysis and horizontal mixing. Increasing horizontal mixing improves the simulated TCO seasonal cycle but negatively impacts CH₄ and N₂O distributions. Using the Cloud-J v.8.0 photolysis module has improved photolysis rate calculations and the seasonal ozone cycle representation over the Southern polar region. This paper outlines how different processes impact chemistry–climate model performance in the southern polar stratosphere, with potential implications for future advancements. Full article

The strong Antarctic vortex plays a crucial role in forming an expansive region with significant stratospheric ozone depletion during austral spring, commonly referred to as the Antarctic “ozone hole”. This study examines daily ozone column behavior during this phenomenon using ERA5 reanalysis data and ground-based observations from 10 Antarctic stations collected between September and December from 2008 to 2022. A preliminary analysis of these datasets revealed smoothly varying patterns with quasi-uniform gradients in the ozone distribution within the ozone hole. This observation led to the hypothesis that average ozone columns over zones, defined as concentric areas around the South Pole, can be estimated using mean values of the measurements derived from station observations. This study aims to evaluate the validity of this hypothesis. The results indicate that the mean ozone levels calculated from daily measurements at two stations—Belgrano and Dome Concordia, or Belgrano and Arrival Heights—provide a reliable approximation of the average ozone levels over the zone spanning 70°S to 90°S. Including additional stations extended the zone of reliable approximation northward to 58°S. The approximation error was estimated to range from 5% to 7% at 1σ and from 6% to 8% at the 10th–90th percentile levels. Furthermore, the geographical distribution of the stations enabled a schematic reconstruction of the ozone hole’s position and shape. On the other hand, the high frequency of ground-based measurements contributed to studying the ozone hole variability in both the inner area and edges on an hourly time scale. These findings have practical implications for the near-real-time monitoring of ozone hole development, along with satellite observations, considering ground-based measurements as a source of information about ozone layer in the South Pole region. The results also suggest the possible role of observations from the ground in the analyses of pre-satellite-era hole behavior. Additionally, this study found a high degree of consistency between ground-based measurements and corresponding ERA5 reanalysis data, further supporting the reliability of the observations. Full article

Nitrous oxide (N₂O) is the fourth most important greenhouse gas in the atmosphere and is considered the most important current source gas emission for global stratospheric ozone depletion (O₃). It has natural and anthropogenic sources, mainly as an unintended by-product of food production activities. This work examines the identification and quantification of trends in the N₂O concentration from the middle troposphere to the middle stratosphere (MTMS) by in situ and remote sensing observations. The temporal variability of N₂O is addressed using a comprehensive dataset of in situ and remote sensing N₂O concentrations based on aircraft and balloon measurements in the MTMS from 1987 to 2018. We determine N₂O trends in the MTMS, based on observations. This consistent dataset was also used to study the N₂O seasonal cycle to investigate the relationship between abundances and its emission sources through zonal means. The results show a long-term increase in global N₂O concentration in the MTMS with an average of 0.89 ± 0.07 ppb/yr in the troposphere and 0.96 ± 0.15 ppb/yr in the stratosphere, consistent with 0.80 ppb/yr derived from ground-based measurements and 0.799 ± 0.024 ppb/yr ACE-FTS (Atmospheric Chemistry Experiment Fourier Transform Spectrometer) satellite measurements. Full article

Based on environmental monitoring data and meteorological observation data of the Chinese major energy province, Shanxi, from 2015 to 2020, using the satellite remote sensing data of Atmospheric Infrared Sounder Instrument (AIRS) and Ozone Monitoring Instrument (OMI) in 2017, we analyzed the characteristics of surface ozone (O₃) pollution and its correlation with meteorological factors, as well as the vertical distribution of O₃ in typical pollution cities in Shanxi Province. The results showed that surface O₃ became the primary pollutant in Shanxi. Surface O₃ has shown a zonal distribution with a high level in the south and a low level in the north region since 2017. Surface O₃ pollution was severe in 2019, and the maximum daily 8 h running average of O₃ (MDA8 O₃) decreased, but annual mean O₃ in northern and central regions showed a slow rising trend in 2020. Comprehensive analyses of the influence of meteorological factors on surface O₃ indicated that O₃ pollution in Linfen, Yuncheng and Taiyuan was mainly caused by local photochemical reactions, while that in Jincheng, Xinzhou, Lvliang and Yangquan resulted from regional transports. O₃ volume mixing ratios (VMR) in the middle and lower troposphere generally increased with altitude, peaking at 120 ppbv at approximately 400 hPa. The positive vertical gradient of O₃ in the boundary layer was obvious in Taiyuan in summer and significant in the surface layer in Taiyuan and Linfen during winter and spring, which was associated with greater atmospheric dynamic stability and suppressed vertical mixing. Due to the lack of direct detection of O₃ in the lower troposphere in this region, O₃ vertical distribution retrieved by satellite observation is critical for the study of vertical mixing and transport of local O₃, as well as its regional transport characteristics. Full article

The present study examines a long-term statistical trend analysis of Total Ozone Content (TOC) data from the AURA satellite for latitudes 60° and 60° S. A methodology for eliminating the strong dependence on the season has been applied by introducing the relative deviation of the average monthly TOC from the climatological average. The analysis presents comparisons of the trends of the zonal average values of TOC and its relative values. In addition, the standard error of both parameters is calculated. The course of the obtained mass of Ozone (O₃) and its trend for the period 2005–2020 is presented, and a division is made into three areas: (i) from 30° S to 30° N, (ii) from 30° S to 60° S, and (iii) from 30° N to 60° N. The last part of this study demonstrates the trends of TOC and relative TOC for Bulgaria in the period 1996–2020. The main results of this study show that (a) in the considered latitude range, a slow but steady increase in O₃ prevails, (b) the main part of the O₃ mass is in low and mid-latitudes, and (c) the general trend in O₃ mass for both hemispheres is determined by the positive trend in the southern hemisphere. Full article

The purpose of this work is to study Rossby wave parameters in total ozone over the Arctic in 2000–2021. We consider the averages in the January–March period, when stratospheric trace gases (including ozone) in sudden stratospheric warming events are strongly disturbed by planetary waves. To characterize the wave parameters, we analyzed ozone data at the latitudes of 50°N (the sub-vortex area), 60°N (the polar vortex edge) and 70°N (inner region of the polar vortex). Total ozone column (TOC) measurements over a 22-year time interval were used from the Total Ozone Mapping Spectrometer/Earth Probe and Ozone Mapping Instrument/Aura satellite observations. The TOC zonal distribution and variations in the Fourier spectral components with zonal wave numbers m = 1–5 are presented. The daily and interannual variations in TOC, amplitudes and phases of the spectral wave components, as well as linear trends in the amplitudes of the dominant quasi-stationary wave 1 (QSW1), are discussed. The positive TOC peaks inside the vortex in 2010 and 2018 alternate with negative ones in 2011 and 2020. The extremely low TOC at 70°N in 2020 corresponds to severe depletion of stratospheric ozone over the Arctic in strong vortex conditions due to anomalously low planetary wave activity and a high positive phase of the Arctic Oscillation. Interannual TOC variations in the sub-vortex region at 50°N are accompanied by a negative trend of −4.8 Dobson Units per decade in the QSW1 amplitude, statistically significant at 90% confidence level, while the trend is statistically insignificant in the vortex edge region and inside the vortex due to the increased variability in TOC and QSW1. The processes associated with quasi-circumpolar migration and quasi-stationary oscillation of the wave-1 phase depending on the polar vortex strength in 2020 and 2021 are discussed. Full article

Two existing double-difference (DD) methods, using either a 3rdSensor or Radiative Transfer Modeling (RTM) as a transfer, are applicable primarily for limited regions and channels, and, thus critical in capturing inter-sensor calibration radiometric bias features. A supplementary method is also desirable for estimating inter-sensor calibration biases at the window and lower sounding channels where the DD methods have non-negligible errors. In this study, using the Suomi National Polar-orbiting Partnership (SNPP) and Joint Polar Satellite System (JPSS)-1 (alias NOAA-20) as an example, we present a new inter-sensor bias statistical method by calculating 32-day averaged differences (32D-AD) of radiometric measurements between the same instrument onboard two satellites. In the new method, a quality control (QC) scheme using one-sigma (for radiance difference), or two-sigma (for radiance) thresholds are established to remove outliers that are significantly affected by diurnal biases within the 32-day temporal coverage. The performance of the method is assessed by applying it to estimate inter-sensor calibration radiometric biases for four instruments onboard SNPP and NOAA-20, i.e., Advanced Technology Microwave Sounder (ATMS), Cross-track Infrared Sounder (CrIS), Nadir Profiler (NP) within the Ozone Mapping and Profiler Suite (OMPS), and Visible Infrared Imaging Radiometer Suite (VIIRS). Our analyses indicate that the globally-averaged inter-sensor differences using the 32D-AD method agree with those using the existing DD methods for available channels, with margins partially due to remaining diurnal errors. In addition, the new method shows its capability in assessing zonal mean features of inter-sensor calibration biases at upper sounding channels. It also detects the solar intrusion anomaly occurring on NOAA-20 OMPS NP at wavelengths below 300 nm over the Northern Hemisphere. Currently, the new method is being operationally adopted to monitor the long-term trends of (globally-averaged) inter-sensor calibration radiometric biases at all channels for the above sensors in the Integrated Calibration/Validation System (ICVS). It is valuable in demonstrating the quality consistencies of the SDR data at the four instruments between SNPP and NOAA-20 in long-term statistics. The methodology is also applicable for other POES cross-sensor calibration bias assessments with minor changes. Full article

The rapid economic development in East Asia has led to serious air pollution problems in the near-surface layer. Studies have shown that there is an interaction between air pollution and the East Asian upper-level jet, which is an important weather system controlling the climate in East Asia. Therefore, it is of great significance to study the relationship between the surface layer air pollutants and the upper-level jet stream in East Asia. Based on the daily wind and vertical velocity data provided by the National Centers for Environmental Prediction/National Center for Atmospheric Research as well as the surface pollutant and meteorological variable data provided by the Science Data Bank, we use statistical analysis methods to study the relationship between the East Asian upper-level jet and the high-concentration area of near-surface air pollutants in summer. Meanwhile, the mechanisms of the interaction are preliminarily discussed. The results show that the North China Plain and the Tarim Basin are the high-value areas of the particulate matter (PM) in summer during 2013–2018, and the ozone (O₃) concentration in the near-surface atmospheric layer in the North China Plain is also high. The average concentrations of the PM_2.5, PM₁₀ and O₃ in the North China Plain are 45.09, 70.28 and 131.27 μg·m⁻³, respectively, and the days with the concentration exceeding the standard reach 401, 461 and 488, respectively. During this period, there is an increasing trend in the O₃ concentration and a decreasing trend in the PM concentration. The average ratio of the PM_2.5 to PM₁₀ is approximately 0.65 with a decreasing trend. The air pollutant concentration in this region has a significant relationship with the location of the East Asian upper-level jet. The low wind speed at the surface level under the control of the upper-level jet is the main reason for the high pollutant concentration besides the pollutant emission. They relate to each other through the surface humidity and the meridional and zonal wind. Meanwhile, the concentrations of the PM_2.5 and PM₁₀ are high in the near-surface layer in the Tarim Basin, and the average concentrations are 45.19 and 49.08 μg·m⁻³, respectively. The days with the concentration exceeding the standard are 265 and 193, respectively. The interannual variation in the PM concentration shows an increasing trend first and then a decreasing trend. The average ratio of PM_2.5 to PM₁₀ in this region reaches approximately 0.9. The ratio reaches the highest in 2013 and 2014 and then decreases to and maintains at approximately 0.85. The concentration of air pollutants in the basin has a significant relationship with the intensity of the upper-level jet in East Asia. The weakening of the upper-level jet will lead to a decrease in the surface humidity in the northern part of the basin, an increase in the surface temperature in the western part of the basin and a decrease in the surface zonal wind in the eastern part of the basin, which will result in a higher PM concentration. Full article

Estimates of the global warming potential (GWP) of methane rely on the predictions from global chemistry-transport models. These models employ many uncertain input parameters representing the sources and sinks for methane and those for the tropospheric ozone, which is formed as a by-product of the methane sink process. Five thousand quasi-randomly Monte Carlo sampled model runs employing a zonally averaged global model were completed, each with a base case and a pulse case that differed from the base case only in having an additional 149 Tg (1Tg = 10⁹ kg) emission pulse of methane. Each of the five thousand pulse case experiments had a small excess of methane that decayed away throughout the twenty-year model experiment. The radiative forcing consequences of this excess methane, and the excess tropospheric ozone formed from it, were integrated over a 100-year time horizon. The GWP was calculated in each of the five thousand model experiments from the sum of the radiative forcing consequences of methane and tropospheric ozone, by expressing them relative to the radiative forcing consequences of an identical emission pulse of carbon dioxide. The 2-sigma confidence range surrounding the methane atmospheric lifetime estimated in the Monte Carlo analysis was considerably wider than that derived from observations, suggesting that some of the input parameter combinations may have been unrealistic. The rejection of the unrealistic Monte Carlo replicates increased the mean methane GWP and narrowed its 2-sigma confidence interval to 37 ± 10 over a 100-year time horizon for emission pulses of the order of 1 Tg. Multiple linear regression was used to attribute the uncertainty in the output GWPs to each of the 183 uncertain input parameters, which represented emission source sectors, chemical kinetic rate coefficients, dry deposition velocities and biases in temperature and water vapour concentrations. Overall, the only significant contributions to the uncertainty in the methane GWP came from the chemical kinetic parameters representing the CH₄ + OH, CH₃O₂ + HO₂, CH₃O₂ + NO and the terpene + O₃ reaction rate coefficients. Full article

The ability of meteorological models to accurately characterise regional meteorology plays a crucial role in the performance of photochemical simulations of air pollution. As part of the research funded by the Australian government’s Department of the Environment Clean Air and Urban Landscape hub, this study set out to complete an intercomparison of air quality models over the Sydney region. This intercomparison would test existing modelling capabilities, identify any problems and provide the necessary validation of models in the region. The first component of the intercomparison study was to assess the ability of the models to reproduce meteorological observations, since it is a significant driver of air quality. To evaluate the meteorological component of these air quality modelling systems, seven different simulations based on varying configurations of inputs, integrations and physical parameterizations of two meteorological models (the Weather Research and Forecasting (WRF) and Conformal Cubic Atmospheric Model (CCAM)) were examined. The modelling was conducted for three periods coinciding with comprehensive air quality measurement campaigns (the Sydney Particle Studies (SPS) 1 and 2 and the Measurement of Urban, Marine and Biogenic Air (MUMBA)). The analysis focuses on meteorological variables (temperature, mixing ratio of water, wind (via wind speed and zonal wind components), precipitation and planetary boundary layer height), that are relevant to air quality. The surface meteorology simulations were evaluated against observations from seven Bureau of Meteorology (BoM) Automatic Weather Stations through composite diurnal plots, Taylor plots and paired mean bias plots. Simulated vertical profiles of temperature, mixing ratio of water and wind (via wind speed and zonal wind components) were assessed through comparison with radiosonde data from the Sydney Airport BoM site. The statistical comparisons with observations identified systematic overestimations of wind speeds that were more pronounced overnight. The temperature was well simulated, with biases generally between ±2 °C and the largest biases seen overnight (up to 4 °C). The models tend to have a drier lower atmosphere than observed, implying that better representations of soil moisture and surface moisture fluxes would improve the subsequent air quality simulations. On average the models captured local-scale meteorological features, like the sea breeze, which is a critical feature driving ozone formation in the Sydney Basin. The overall performance and model biases were generally within the recommended benchmark values (e.g., ±1 °C mean bias in temperature, ±1 g/kg mean bias of water vapour mixing ratio and ±1.5 m s⁻¹ mean bias of wind speed) except at either end of the scale, where the bias tends to be larger. The model biases reported here are similar to those seen in other model intercomparisons. Full article

Climate modification by stratospheric SO₂ injections, to form sulfate aerosols, may alter the spectral and angular distributions of the solar ultraviolet and visible radiation that reach the Earth’s surface, with potential consequences to environmental photobiology and photochemistry. We used modeling results from the CESM1(WACCM) stratospheric aerosol geoengineering large ensemble (GLENS) project, following the RCP8.5 emission scenario, and one geoengineering experiment with SO₂ injections in the stratosphere, designed to keep surface temperatures at 2020 levels. Zonally and monthly averaged vertical profiles of O₃, SO₂, and sulfate aerosols, at 30 N and 70 N, served as input into a radiative transfer model, to compute biologically active irradiances for DNA damage (i_DNA), UV index (UVI), photosynthetically active radiation (PAR), and two key tropospheric photodissociation coefficients (j_O1D for O₃ + hν (λ < 330 nm) → O(¹D) + O₂; and j_NO2 for NO₂ + hν (λ < 420 nm) → O(³P) + NO). We show that the geoengineering scenario is accompanied by substantial reductions in UV radiation. For example, comparing March 2080 to March 2020, i_DNA decreased by 25% to 29% in the subtropics (30 N) and by 26% to 33% in the polar regions (70 N); UVI decreased by 19% to 20% at 30 N and 23% to 26% at 70 N; and j_O1D decreased by 22% to 24% at 30 N and 35% to 40% at 70 N, with comparable contributions from sulfate scattering and stratospheric O₃ recovery. Different responses were found for processes that depend on longer UV and visible wavelengths, as these are minimally affected by ozone; PAR and j_NO2 were only slightly lower (9–12%) at 30 N, but much lower at 70 N (35–40%). Similar reductions were estimated for other months (June, September, and December). Large increases in the PAR diffuse-direct ratio occurred in agreement with previous studies. Absorption by SO₂ gas had a small (~1%) effect on j_O1D, i_DNA, and UVI, and no effect on j_NO2 and PAR. Full article