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Positive trends in tropical free-tropospheric (FT) ozone are frequently ascribed to emissions growth, but less is known about the effects of changing dynamics. Extending a prior study (Thompson et al., 2021; https://doi.org/10.1029/2021JD034691; “T21”), we re-examine Southern Hemisphere Additional Ozonesondes (SHADOZ) ozone trends over equatorial Southeast Asia (ESEA), one of Earth's most convectively active regions, using 25 years (1998–2022) of ozone soundings. T21 posited that early-year positive FT ozone trends at equatorial SHADOZ stations are related to decreasing convection. The 25-year analysis of Kuala Lumpur and Watukosek SHADOZ records finds that FT ozone trends of +5 % to +15 % (+2 to +6 nmol mol−1) per decade from ∼ February–April coincide with large increases in satellite infrared brightness temperatures and outgoing longwave radiation, indicators of declining convective activity. MERRA-2 reanalyses exhibit increases in upper-tropospheric velocity potential and decreases in precipitable water, also indicating diminished convection. In contrast, trends in ozone and convective indicators are weak the rest of the year. These results suggest that decreases in convective intensity and frequency are primary drivers of FT ozone build-up over ESEA early in the year; i.e., waning convection suppresses lofting and dilution of ozone. Decreasing convection promotes accumulation of biomass burning emissions typical of boreal spring even though satellite FT carbon monoxide trends (2002–2022) over ESEA follow a global decrease pattern. Finally, our results demonstrate the advantages of monthly or seasonally resolved analyses over annual means for robust attribution of observed ozone trends, challenging models to reproduce these detailed features in simulations of the past 25 years.

The Fires, Asian, and Stratospheric Transport–Las Vegas Ozone Study (FAST-LVOS) was conducted in May and June of 2017 to study the transport of ozone (O3) to Clark County, Nevada, a marginal non-attainment area in the southwestern United States (SWUS). This 6-week (20 May–30 June 2017) field campaign used lidar, ozonesonde, aircraft, and in situ measurements in conjunction with a variety of models to characterize the distribution of O3 and related species above southern Nevada and neighboring California and to probe the influence of stratospheric intrusions and wildfires as well as local, regional, and Asian pollution on surface O3 concentrations in the Las Vegas Valley (≈ 900 m above sea level, a.s.l.). In this paper, we describe the FAST-LVOS campaign and present case studies illustrating the influence of different transport processes on background O3 in Clark County and southern Nevada. The companion paper by Zhang et al. (2020) describes the use of the AM4 and GEOS-Chem global models to simulate the measurements and estimate the impacts of transported O3 on surface air quality across the greater southwestern US and Intermountain West. The FAST-LVOS measurements found elevated O3 layers above Las Vegas on more than 75 % (35 of 45) of the sample days and show that entrainment of these layers contributed to mean 8 h average regional background O3 concentrations of 50–55 parts per billion by volume (ppbv), or about 85–95 µg m−3. These high background concentrations constitute 70 %–80 % of the current US National Ambient Air Quality Standard (NAAQS) of 70 ppbv (≈ 120 µg m−3 at 900 m a.s.l.) for the daily maximum 8 h average (MDA8) and will make attainment of the more stringent standards of 60 or 65 ppbv currently being considered extremely difficult in the interior SWUS.

NOAA's program of long-term monitoring of the vertical distribution of ozone with electrochemical concentration cell (ECC) ozonesondes has undergone a number of changes over the 50-year record. In order to produce a homogenous data set, these changes must be documented and, where necessary, appropriate corrections applied. This is the first comprehensive and consistent reprocessing of NOAA's ozonesonde data records that corrects for these changes using the rawest form of the data (cell current and pump temperature) in native resolution as well as a point-by-point uncertainty calculation that is unique to each sounding. The reprocessing is carried out uniformly at all eight ozonesonde sites in NOAA's network with differences in sensing solution and ozonesonde types accounted for in the same way at all sites. The corrections used to homogenize the NOAA ozonesonde data records greatly improve the ozonesonde measurements with an average one sigma uncertainty of +/- 4-6% in the stratosphere and +/- 5-20% in the troposphere. A comparison of the integrated column ozone from the ozonesonde profile with co-located Dobson spectrophotometers total column ozone measurements shows agreement within +/- 5% for >70% of the profiles. Very good agreement is also found in the stratosphere between ozonesonde profiles and profiles retrieved from the Solar Backscatter Ultraviolet (SBUV) instruments.

Ozone in the troposphere affects humans and ecosystems as a pollutant and as a greenhouse gas. Observing, understanding and modelling this dual role, as well as monitoring effects of international regulations on air quality and climate change, however, challenge measurement systems to operate at opposite ends of the spatio-temporal scale ladder. Aboard the ESA/EU Copernicus Sentinel-5 Precursor (S5P) satellite launched in October 2017, the TROPOspheric Monitoring Instrument (TROPOMI) aspires to take the next leap forward by measuring ozone and its precursors at unprecedented horizontal resolution until at least the mid-2020s. In this work, we assess the quality of TROPOMI's first release (V01.01.05–08) of tropical tropospheric ozone column (TrOC) data. Derived with the convective cloud differential (CCD) method, TROPOMI daily TrOC data represent the 3 d moving mean ozone column between the surface and 270 hPa under clear-sky conditions gridded at 0.5∘ latitude by 1∘ longitude resolution. Comparisons to almost 2 years of co-located SHADOZ ozonesonde and satellite data (Aura OMI and MetOp-B GOME-2) conclude to TROPOMI biases between −0.1 and +2.3 DU (<+13 %) when averaged over the tropical belt. The field of the bias is essentially uniform in space (deviations <1 DU) and stable in time at the 1.5–2.5 DU level. However, the record is still fairly short, and continued monitoring will be key to clarify whether observed patterns and stability persist, alter behaviour or disappear. Biases are partially due to TROPOMI and the reference data records themselves, but they can also be linked to systematic effects of the non-perfect co-locations. Random uncertainty due to co-location mismatch contributes considerably to the 2.6–4.6 DU (∼14 %–23 %) statistical dispersion observed in the difference time series. We circumvent part of this problem by employing the triple co-location analysis technique and infer that TROPOMI single-measurement precision is better than 1.5–2.5 DU (∼8 %–13 %), in line with uncertainty estimates reported in the data files. Hence, the TROPOMI precision is judged to be 20 %–25 % better than for its predecessors OMI and GOME-2B, while sampling at 4 times better spatial resolution and almost 2 times better temporal resolution. Using TROPOMI tropospheric ozone columns at maximal resolution nevertheless requires consideration of correlated errors at small scales of up to 5 DU due to the inevitable interplay of satellite orbit and cloud coverage. Two particular types of sampling error are investigated, and we suggest how these can be identified or remedied. Our study confirms that major known geophysical patterns and signals of the tropical tropospheric ozone field are imprinted in TROPOMI's 2-year data record. These include the permanent zonal wave-one pattern, the pervasive annual and semiannual cycles, the high levels of ozone due to biomass burning around the Atlantic basin, and enhanced convective activity cycles associated with the Madden–Julian Oscillation over the Indo-Pacific warm pool. TROPOMI's combination of higher precision and higher resolution reveals details of these patterns and the processes involved, at considerably smaller spatial and temporal scales and with more complete coverage than contemporary satellite sounders. If the accuracy of future TROPOMI data proves to remain stable with time, these hold great potential to be included in Climate Data Records, as well as serve as a travelling standard to interconnect the upcoming constellation of air quality satellites in geostationary and low Earth orbits.

The recent Assessment of Standard Operating Procedures for OzoneSondes (ASOPOS 2.0; WMO/GAW Report #268) addressed questions of homogeneity and long-term stability in global electrochemical concentration cell (ECC) ozone sounding network time series. Among its recommendations was adoption of a standard for evaluating data quality in ozonesonde time series. Total column ozone (TCO) derived from the sondes compared to TCO from Aura’s Ozone Monitoring Instrument (OMI) is a primary quality indicator. Comparisons of sonde ozone with Aura’s Microwave Limb Sounder (MLS) are used to assess the stability of stratospheric ozone. This paper provides a comprehensive examination of global ozonesonde network data stability and accuracy since 2004 in light of the sudden post-2013 TCO “dropoff” of ~3-4% that was reported previously at select stations (Stauffer et al., 2020). Comparisons with Aura OMI TCO averaged across the network of 60 stations are stable within about ±2% over the past 18 years. Sonde TCO has similar stability compared to three other TCO satellite instruments, and the stratospheric ozone measurements average to within ±5% of MLS from 50 to 10 hPa. Thus, sonde data are reliable for trends, but with a caveat applied for a subset of dropoff stations in the tropics and subtropics. The dropoff is associated with only one of two major ECC instrument types. A detailed examination of ECC serial numbers pinpoints the timing of the dropoff. However, we find that overall, ozonesonde data are stable and accurate compared to independent measurements over the past two decades.

This study presents an updated evaluation of stratospheric ozone profile trends at Arosa/Davos/Hohenpeißenberg, Switzerland/Germany; Observatory de Haute-Provence (OHP), France; Boulder, Colorado, Mauna Loa Observatory (MLO) and Hilo, Hawaii; and Lauder, Aotearoa / New Zealand, with a focus on the ozone recovery period post-2000. Trends are derived using vertical ozone profiles from NOAA's Dobson network via the Umkehr method (with a recent new homogenization), ozonesondes, and the NOAA COHesive Solar Backscatter Ultraviolet Instrument (SBUV)/Ozone Mapping and Profiler Suite (OMPS) satellite-based record (COH) sampled to match the geographical coordinates of the ground-based stations used in this study. Analyses of long-term changes in stratospheric ozone time series were performed using the updated version (0.8.0) of the Long-term Ozone Trends and Uncertainties in the Stratosphere (LOTUS) independent linear trend (ILT) regression model. This study finds consistency between the trends derived from the different observational records, which is a key factor to the understanding of the recovery of the ozone layer after the implementation of the Montreal Protocol and its amendments that control ozone-depleting substance production and release into the atmosphere. The northern hemispheric Umkehr records of Arosa/Davos, OHP, and MLO all show positive trends in the mid- to upper stratosphere, with trends peaking at ∼ +2 % per decade. Although the upper-stratospheric ozone trends derived from COH satellite records are more positive than those detected by the Umkehr system, the agreement is within the 2 times the standard error uncertainty. Umkehr trends in the upper stratosphere at Boulder and Lauder are positive but not statistically significant, while COH trends are larger and statistically significant (within 2 times the standard error uncertainty). In the lower stratosphere, trends derived from Umkehr and ozonesonde records are mostly negative (except for positive ozonesonde trends at OHP); however, the uncertainties are quite large. Additional dynamical proxies were investigated in the LOTUS model at five ground-based sites. The use of additional proxies did not significantly change trends, but the equivalent latitude reduced the uncertainty in the Umkehr and COH trends in the upper stratosphere and at higher latitudes. In lower layers, additional predictors (tropopause pressure for all stations; two extra components of Quasi-Biennial Oscillation at MLO; Arctic Oscillation at Arosa/Davos, OHP, and MLO) improve the model fit and reduce trend uncertainties as seen by Umkehr and sonde.

Understanding variations in atmospheric ozone in the Arctic is difficult because there are only a few long-term records of vertical ozone profiles in this region. We present 12 years of ozone profiles from February 2005 to February 2017 at four sites: Summit Station, Greenland; Ny-Ålesund, Svalbard, Norway; and Alert and Eureka, Nunavut, Canada. These profiles are created by combining ozonesonde measurements with ozone profile retrievals using data from the Microwave Limb Sounder (MLS). This combination creates a high-quality dataset with low uncertainty values by relying on in situ measurements of the maximum altitude of the ozonesondes (∼30 km) and satellite retrievals in the upper atmosphere (up to 60 km). For each station, the total column ozone (TCO) and the partial column ozone (PCO) in four atmospheric layers (troposphere to upper stratosphere) are analyzed. Overall, the seasonal cycles are similar at these sites. However, the TCO over Ny-Ålesund starts to decline 2 months later than at the other sites. In summer, the PCO in the upper stratosphere over Summit Station is slightly higher than at the other sites and exhibits a higher standard deviation. The decrease in PCO in the middle and upper stratosphere during fall is also lower over Summit Station. The maximum value of the lower- and middle-stratospheric PCO is reached earlier in the year over Eureka. Trend analysis over the 12-year period shows significant trends in most of the layers over Summit and Ny-Ålesund during summer and fall. To understand deseasonalized ozone variations, we identify the most important dynamical drivers of Arctic ozone at each level. These drivers are chosen based on mutual selected proxies at the four sites using stepwise multiple regression (SMR) analysis of various dynamical parameters with deseasonalized data. The final regression model is able to explain more than 80 % of the TCO and more than 70 % of the PCO in almost all of the layers. The regression model provides the greatest explanatory value in the middle stratosphere. The important proxies of the deseasonalized ozone time series at the four sites are tropopause pressure (TP) and equivalent latitude (EQL) at 370 K in the troposphere, the quasi-biennial oscillation (QBO) in the troposphere and lower stratosphere, the equivalent latitude at 550 K in the middle and upper stratosphere, and the eddy heat flux (EHF) and volume of polar stratospheric clouds throughout the stratosphere.