Abstract. This study presents an updated assessment of stratospheric and total column ozone trends over the 2000–2024 period using six merged limb-profile datasets and six merged total ozone datasets. Long-term changes were quantified using a multiple linear regression framework that accounts for dynamical and chemical variability. In addition to standard regressors (solar cycle, QBO, ENSO, stratospheric aerosol optical depth), we include Arctic and Antarctic Oscillation indices and the eddy heat flux in each hemisphere as proxies for dynamic variability. Volcanic (and wildfire) aerosol forcing is represented by separate proxies for three periods dominated by the major volcanic events of El Chichón, Pinatubo, and post-2000 volcanic eruptions, including Hunga-Tonga. These period-specific proxies are employed to better account for varying dynamical ozone responses that largely depend on the season and location of the eruptions. All profile datasets consistently show positive trends in the upper stratosphere, with the strongest ozone recovery in southern mid-latitudes, in agreement with other studies. In the lower stratosphere, trends remain weak, spatially heterogeneous, and predominantly negative. A comparison of stratospheric column trends derived from profile data with total ozone trends shows close agreement across latitude bands. Within the trend uncertainties, total column trends since 2000 are largely driven by stratospheric ozone changes, while tropospheric contributions to zonal-mean total ozone trends (the difference between total and stratospheric column trends) appear negligible. The extended regression framework improves the representation of recent dynamical variability and provides an updated perspective on stratospheric ozone recovery through 2024.

We present updated evaluation of stratospheric ozone profile trends in the 60 degrees S-60 degrees N latitude range using long-term ground-based and satellite climate data records, as well as simulations by chemistry-climate models. The trends are evaluated using the LOTUS (Long-term Ozone Trends and Uncertainties in the Stratosphere) regression model.Analyses of satellite data confirm the statistically significant positive ozone trends in the period 2000-2024 in the upper stratosphere of similar to 1-3 % per decade, with larger trends at mid-latitudes compared to the tropics. The trends are slightly positive or close to zero in the middle stratosphere, and mostly negative, -1 to -2 % per decade, in the lower stratosphere, but they are not statistically significant. The morphology and magnitude of ozone trends are similar to previous analyses (2000-2020 trends).Ozone trends in 2000-2024 predicted by chemistry-climate model simulations are in good agreement with combined satellite trends. In the upper stratosphere, models predict a slightly stronger ozone recovery than observations. In the lower stratosphere, both models and satellite observations report negative trends in the tropics, while modelled ozone trends are slightly positive at mid-latitudes.Ozone profile trends over several stations estimated from ground-based records capture the same overall vertical pattern of ozone trends as merged gridded satellite datasets.Analyses of regional ozone profile trends in 2003-2024 using merged satellite datasets confirmed the previous observations of a longitudinal structure in ozone trends in the NH mid-latitude stratosphere, with positive trends over Scandinavia and negative trends over Siberia. However, the magnitude of this dipole-like structure is reduced compared to previous analyses.

Abstract. A variety of chemical and dynamical processes in the troposphere and stratosphere affect tropical total column ozone (TCO), the net effect of which may cause changes in surface UV radiation and impact human and ecosystem health. We use dynamical linear modeling to estimate tropical trends in TCO and partial column ozone (PCO) in the troposphere and three stratospheric layers to assess agreement between satellite observational composites and chemistry–climate model (CCM) simulations from two multi-model experiments (CCMI-1 and CCMI-2022). While both model experiments show tropical TCO increases over 2000–2021, CCMI–2022 trends (+2.5 DU) agree slightly better with observations than CCMI-1 (+1.6 DU). However, this overall agreement obscures multiple systematic differences in PCO trends between the models and observations across atmospheric layers. For example, since 2000 tropical tropospheric PCO increased significantly in CCMI-2022 (+1.5 DU) but not in CCMI–1 (+0.3 DU), largely explaining the difference in TCO trends. Also, despite nearly identical stratospheric PCO trends, CCMI-2022 trends are slightly more negative in the lower stratospheric (by ~0.5 DU), compensated by more positive middle/upper stratosphere trends compared to CCMI-1. Crucially, substantial differences exist across observational PCO trends, particularly in the troposphere and middle/upper stratosphere, and these disagreements limit the ability to evaluate CCM fidelity. Furthermore, while the inter-model correlation between late and early 21st century trends is suggestive of a potential emergent constraint on future ozone trends, the spread in observational trends precludes its observational implementation.

Quantifying chemical and dynamical drivers of Antarctic ozone variability remains important as stratospheric chlorine levels gradually reduce and the ozone hole recovers in response. While chemistry dominates the formation of the ozone hole in September, the role of dynamics grows as the spring season progresses. To improve our ability to characterise the dynamical impacts on Antarctic total column ozone (TCO), we use MLS/Aura observations of carbon monoxide to trace the path of an air parcel that originates in the mesosphere and descends into the springtime polar vortex. We define a new metric, the Mesospheric Parcel Altitude (MPA), which measures the altitude of the descending mesospheric air parcel at the end of October. The MPA is highly correlated with October TCO and functions as a diagnostic tool, capturing the dynamical state of the inner-vortex. Based on the MPA, we classify October ozone holes from 2004–2024 into three mesospheric descent types (Strong, Regular, and Weak) and provide a formula to estimate the magnitude of horizontal ozone transport (poleward of 70° S and between 17–27 km) during a given October. A higher MPA (>26.9 km) indicates Weak descent, reduced ozone transport, and a larger, longer-lived ozone hole. A lower MPA (<24.6 km) indicates Strong descent, increased ozone transport, and a smaller, shorter-lived ozone hole. When the MPA is used as a proxy for polar cap TCO, approximately 63 % of the observed variance during October is explained by the metric.

Abstract. Tropospheric ozone, a key atmospheric pollutant and greenhouse gas, exhibits significant spatio-temporal variability on seasonal, inter-annual, and decadal scales, posing a challenge for satellite observation systems. Methods like the Convective Cloud Differential (CCD) and Cloud Slicing Algorithms (CSA) are standard for Tropospheric Column Ozone (TCO) retrievals but are limited to the tropical band (20° S–20° N). This study presents the first successful global application of CCD retrieval outside the tropical region. We introduce the CHORA-CCD (Cloud Height Ozone Reference Algorithm-CCD) for retrieving near-global TCO from TROPOMI. It utilises a local cloud reference sector (CLCD, CHORA Local Cloud Decision) to determine the stratospheric (above cloud) column ozone (ACCO). The ACCO is subtracted from the total column in clear-sky scenes to determine the TCO. The new approach presented here minimises the impact of stratospheric ozone variability, which is generally higher in the extratropics. An iterative approach is used to automatically select an optimal local cloud reference sector around each retrieval grid box, varying the radius from 60 to a maximum of 600 km, for which a mean TCO is determined until a sufficient number of ground pixels with nearly full cloud cover are found. Due to the prevalence of low-level clouds in mid-latitudes, the TCO calculation is constrained to the column from the surface up to the reference altitude of 450 hPa. There are two independent methods used: (I) CLCD-C, which uses an ozone climatology and (II) CLCD-T, an alternative method which estimates the ACCO at 450 hPa by linear regression (Theil-Sen) in cases where the cloud-top-heights in the local cloud sector vary sufficiently. The Theil-Sen approach is a combination of the CCD and CSA methods. The CLCD algorithm dynamically decides between the CLCD-C and CLCD-T to determine ACCO depending on the cloud characteristics. The CLCD algorithm is further refined by introducing a homogeneity criterion for total ozone to overcome inhomogeneities in stratospheric ozone. Monthly averaged CLCD TCOs have been determined over the tropics and mid-latitudes (60° S–60° N) using TROPOMI data from 2018 to 2022. The method’s accuracy was investigated by comparing spatially collocated SHADOZ/WOUDC/NDACC HEGIFTOM ozonesonde measurements from 36 stations. The validation results reveal that CLCD TCO retrievals are in good agreement with ozonesondes at most stations with an overall statistical bias of 0.6 DU and dispersion of 2.5 DU. Across all stations, the maximum bias and dispersion are around ∼5 DU and 4 DU, respectively. The CLCD approach effectively captures tropospheric ozone enhancements across diverse regions, including Northeast China and North America, with particular sensitivity to areas impacted by significant emission sources. Our results demonstrate the advantage of using the modified local cloud reference sector, providing an important basis for subsequent systematic applications in current and future missions, in particular, geostationary satellites with an emphasis on observing higher latitudes.

Tropospheric ozone, a critical pollutant and greenhouse gas, exhibits spatio-temporal variability, challenging satellite observations. Existing methods like the Convective Cloud Differential (CCD) and Cloud Slicing Algorithms (CSA) are standard for Tropospheric Column Ozone (TCO) retrieval but are limited to the tropics (20°S-20°N). Notably, the CCD approach has proven successful with satellite sensors like Aura OMI, MetOp GOME-2, and Sentinel-5 Precursor TROPOMI.In this study, we present the first successful application of CCD retrieval outside the tropical region. We introduce CHORA-CCD (Cloud Height Ozone Reference Algorithm-CCD) for retrieving TCO from TROPOMI in middle latitudes. It utilises a local cloud reference sector (CLCD, CHORA-CCD Local Cloud Decision) to determine the stratospheric (above cloud) column (ACCO) ozone. This ACCO is later subtracted from the total column in clear-sky scenes to determine the TCO. The new approach minimises the impact of variances in stratospheric ozone.An iterative approach is used to automatically select an optimal local cloud reference sector around each retrieval grid point, varying the radius from 60 to a maximum of 600 km around the grid box, for which a mean TCO is determined until a sufficient number of ground pixels with nearly fill cloud cover are found. Due to the prevalence of low-level clouds in middle latitudes, the estimation of TCO is constrained to the column up to a reference altitude of 450 hPa. An alternative method is introduced to directly estimate the ACCO down to 450 hPa by Theil-Sen regression in cases where the cloud-top heights in the local cloud sector are variable. The algorithm dynamically decides between CCD and Theil-Sen method for ACCO estimation by analysing the cloud characteristics. The CLCD algorithm is further refined by introducing a homogeneity criterion for total ozone to overcome inhomogeneities in stratospheric ozone.Monthly averaged CLCD-TCOs have been determined over the middle latitudes (60◦S-60◦N) from TROPOMI for the time period from 2018 to 2022. The accuracy of the method was investigated by comparisons with spatially collocated SHADOZ/WOUDC/NDACC ozonesondes from thirty-one stations. The validation results reveal that TCO retrievals at 450 hPa using the CLCD algorithm exhibit good agreement with ozonesondes at most stations. At the tropical station Natal (5.4°S, 35.4°W), there is an outstanding agreement between CLCD and ozonesondes, showcasing minimal bias and scatter (0.3 ± 1.0 DU). Similarly, in the subtropics over Irene (25.9°S, 28.2°E), CLCD exhibits a significantly lower bias and scatter (0.0 ± 1.4 DU). Specifically, at one of the northernmost stations, Legionowo (52.4°N, 21°E), bias and dispersion are minimal (0.4 ± 2.2 DU). Across all stations, the maximum observed bias and dispersion are below around 5 DU and 4 DU, respectively. In this presentation, a detailed validation of the new local CCD retrievals will be given, underlining the advantage of using the local cloud reference sector in the middle latitudes, providing an important basis for subsequent systematic applications in current and future missions of geostationary satellites.

About 10% of the total amount of ozone resides in the troposphere, which acts as a potent greenhouse gas. Anthropogenic emissions and biomass burning are the main sources of ozone in the troposphere, and overexposure to this pollutant causes health problems and damages vegetation. A combination of space-borne limb and nadir measurements in the UV-visible spectral range (so-called limb-nadir matching, LNM) provides valuable information on tropospheric ozone. This study uses data from the SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY (SCIAMACHY) (2002-2012) and Ozone Mapping and Profiler Suite on board of Suomi National Polar-Orbiting Partnership (OMPS/NPP, since 2012). Both instruments observe the atmosphere in both limb and nadir geometry. Tropospheric ozone columns are retrieved globally by subtracting the stratospheric ozone column calculated from limb observations from the total ozone column derived from the nadir measurements. Tropospheric ozone retrievals use different upper altitude limits to calculate the tropospheric ozone column. In the case of the LNM technique, the upper limit is defined by the thermal and/or dynamical tropopause. The Convective Clouds Differential technique (CCD) calculates the tropospheric ozone column up to 270 hPa. Phase II of the Tropospheric Ozone Assessment Report (TOAR-II) uses different pressure levels for different latitudes as an upper limit for the tropospheric column. After updating and improving the SCIAMACHY-LNM and the OMPS/NPP-LNM datasets, we obtained a long-term dataset of tropospheric ozone (2002-2023) by merging them. Here, we present this new long-term LNM tropospheric ozone column dataset, which has been converted to the different definitions of column heights as prescribed in TOAR II. The datasets are validated using ozonesondes, and the results for the different column definitions are evaluated and discussed.

This paper presents an intercomparison between existing tropospheric ozone column (TrOC) datasets obtained using combined limb and nadir observations, i.e., exploiting collocated stratospheric profile and total column information retrieved from limb and nadir satellite observations, respectively. In particular, seven datasets have been considered, covering the past 2 decades and consisting of monthly-averaged time series with nearly global coverage. We perform a comparison in terms of climatology and seasonality, investigate the tropopause height used for the construction of each dataset and the related biases, and finally discuss long-term TrOC drifts and trends. The overall goal of the study is to assess the consistency between the datasets and explore possible strategies to reconcile the differences between them. Despite uncertainties associated with the limb–nadir residual methodology and large biases between the mean values of the considered datasets, we identify an overall agreement of TrOC distribution patterns. The different tropopause height definitions used to construct the datasets did not show a relevant role in explaining the biases between them. We demonstrate that a thorough investigation of the drifts with respect to ground-based observations is needed to evaluate TrOC trends from satellite data and that long-term trends in specific regions can be consistently detected, e.g., a positive trend of up to 1.5 DU per decade over China for the 2005–2021 period.

Large-scale meteorological events (e.g. cyclones), referred to as synoptic events, strongly influence weather predictability but still cannot be fully characterised in the Arctic region because of the sparse coverage of measurements. Due to the fact that atmospheric dynamics in the lower stratosphere and troposphere influence the ozone field, one approach to analyse these events further is the use of space-borne measurements of ozone vertical distributions and total columns in addition to conventional parameters such as pressure or wind speed. In this study we investigate the link between cyclones and changes in stratospheric ozone by using a combination of unique measurements during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) ship expedition, ozone profile and total column observations by satellite instruments (OMPS-LP, TROPOMI), and ERA5 reanalysis data. The final goal of the study is to assess whether the satellite ozone data can be used to obtain information about cyclones and provide herewith an additional value in the assimilation by numerical weather prediction models. Three special cases during the MOSAiC expedition were selected and classified for the analysis. They are one “normal” cyclone, where a low surface pressure coincides with a minimum in tropopause height, and two “untypical” cyclones, where this is not observed. The influence of cyclone events on ozone in the upper-troposphere lower-stratosphere (UTLS) region was investigated, using the fact that both are correlated with tropopause height changes. The negative correlation between tropopause height from ERA5 and ozone columns was investigated in the Arctic region for the 3-month period from June to August 2020. This was done using total ozone columns and sub-columns from TROPOMI, OMPS-LP, and MOSAiC ozonesonde data. The greatest influence of tropopause height changes on ozone contour levels occurs at an altitude between 10 and 20 km. Moreover, the lowering of the 250 ppb ozonopause (at about 11 km altitude) below 9 km was used to detect cyclones using OMPS-LP ozone observations. The potential of this approach was demonstrated in two case studies where the boundaries of cyclones could be determined using ozone observations. The results of this study can help improve our understanding of the relationship between cyclones, tropopause height, and ozone in the Arctic and demonstrate the usability of satellite ozone data in addition to the conventional parameters for investigating cyclones in the Arctic.

The Tropospheric Ozone Lidar Network (TOLNet) was used to validate retrievals of ozone (O3) profiles in the troposphere from the TROPOspheric Monitoring Instrument (TROPOMI) ultraviolet (UV), Cross-track Infrared Sounder (CrIS) infrared (IR), and a combined UV + IR wavelength retrieval from TROPOMI/CrIS. Observations from six separate ground-based lidar systems and various locations of ozonesondes distributed throughout North America and in the Netherlands were used to quantify systematic bias and random errors for each satellite retrieval. Furthermore, TOLNet data were used to intercompare idealized UV, IR, and UV + IR convolved lidar profiles of O3 in the troposphere during case studies representative of high-O3 events. This study shows that the improved sensitivity and vertical resolution in UV + IR retrievals in the middle- and upper-troposphere resulted in tropospheric degree of freedom (DOF) values ∼ 33 % higher compared to UV- and IR-only retrievals. The increased DOFs in the UV + IR retrievals allowed for improved reproduction of mid- and upper-tropospheric O3 enhancements and, to a lesser degree, near-surface pollution enhancements compared to single-wavelength satellite products. The validation of O3 profiles in the troposphere retrieved with the UV-only, IR-only, and UV + IR Tikhonov regularised Ozone Profile retrievAl with SCIATRAN (TOPAS) algorithm developed at the Institute for Environmental Physics, University of Bremen, demonstrated the utility of using TOLNet as a satellite evaluation data set. TOPAS UV-only, IR-only, and UV + IR wavelength retrievals had systematic biases, quantified with normalized mean bias, throughout the troposphere of 11.2 ppb (22.1 %), −1.7 ppb (−0.3 %), and 3.5 ppb (7.8 %), respectively, which meet the tropospheric systematic bias requirements defined by the science teams for the TROPOMI and CrIS sensors. The primary drivers of systematic bias were determined to be solar zenith angle, surface albedo, and cloud fraction. Random errors, representative of uncertainty in the retrievals and quantified by root mean squared errors (RMSEs), were large for all three retrievals, with UV-only, IR-only, and UV + IR wavelength retrievals having RMSEs throughout the troposphere of 17.4 ppb (19.8 % of mean tropospheric column values), 10.5 ppb (12.6 % of mean tropospheric column values), and 14.0 ppb (14.6 % of mean tropospheric column values), respectively. TOPAS UV-only profiles did not meet the uncertainty requirements defined for TROPOMI for the troposphere; however, CrIS IR-only retrievals did meet the uncertainty requirements defined by this mission. The larger random errors reflect the challenge of retrieving daily O3 profiles due to the limited sensitivity and vertical resolution of these retrievals in the troposphere. Tropospheric systematic biases and random error were lower in IR-only and combined UV + IR retrievals compared to UV-only products due to the increased sensitivity in the troposphere allowing the retrievals to deviate further from the a priori profiles. Observations from TOLNet demonstrated that the performance of the three satellite products varied by season and altitude in the troposphere. TOLNet was shown to result in similar validation statistics compared to ozonesonde data, which are a commonly used satellite evaluation data source, demonstrating that TOLNet is a sufficient source of satellite O3 profile validation data in the troposphere, which is critical as this data source is the primary product identified for the tropospheric O3 validation of the recently launched Tropospheric Emissions: Monitoring of Pollution (TEMPO) mission.

We present the CHORA (Cloud Height Ozone Reference Algorithm) for retrieving tropospheric-ozone columns from S5P-TROPOMI (Sentinel-5 Precursor-TROPOspheric Monitoring Instrument). The method uses a local-cloud reference sector (CLC - CHORA Local Cloud) to determine the stratospheric (above-cloud) column, which is subtracted from the total column in clear-sky scenes in the same zonal band to retrieve the tropospheric column. The standard CCD (convective cloud differential) approach uses cloud data from the Pacific region (CPC - CHORA Pacific Cloud) instead. An important assumption for the standard method is the zonal invariance of stratospheric ozone. The local-cloud approach is the first step to diminish this constraint in order to extend the CCD method to mid-latitudes, where stratospheric-ozone variability is larger. An iterative approach has been developed for the automatic selection of an optimal local-cloud reference sector around each retrieval grid box varying latitudinally by +/- 1 degrees and longitudinally between +/- 5 and +/- 50 degrees. The optimised CLCT (CHORA Local Cloud Theil-Sen) algorithm, a follow-up from the CLC, employs a homogeneity criterion for total ozone from the cloud reference sector in order to overcome the inhomogeneities in stratospheric ozone. It directly estimates the above-cloud column ozone for a common reference altitude of 270 hPa using the Theil-Sen regression. The latter allows for the combination of the CCD method with the cloud-slicing algorithm that retrieves upper-tropospheric ozone volume mixing ratios. Monthly averaged tropospheric-column ozone (TCO) using the Pacific cloud reference sector (CPC) and the local-cloud reference sector (CLC, CLCT) has been determined over the tropics and subtropics (26 degrees S-22 degrees N) using TROPOMI for the time period from 2018 to 2022. The accuracy of the various methods was investigated by means of comparisons with spatially collocated NASA/GSFC SHADOZ (Southern Hemisphere Additional Ozonesondes) measurements and the ESA TROPOMI level-2 tropospheric-ozone product. At eight out of nine tropical stations, tropospheric-ozone columns using the CLCT yield better agreement with ozonesondes than the CPC. In the tropical region (20 degrees S-20 degrees N), the CLCT shows a significantly lower overall mean bias and dispersion of 1 +/- 7 %, outperforming both the CPC (12 +/- 10 %) and CCD-ESA (22 +/- 10 %). The CLCT surpasses the ESA operational product, providing more accurate tropospheric-ozone retrievals at eight out of nine stations in the tropics. For the Hilo station, with a larger stratospheric-ozone variability due to its proximity to the subtropics, the bias of +30 % (CPC) is effectively reduced to -5 % (CLCT). Similarly, in the subtropics (Reunion, Irene, Hanoi, and King's Park), the CLCT algorithm provides an overall bias and scatter of -11 +/- 9 % with respect to sondes. The CLCT effectively reduces the impact of stratospheric-ozone inhomogeneity, typically at higher latitudes. These results demonstrate the advantage of the local-cloud reference sector in the subtropics. The algorithm is therefore an important basis for subsequent systematic applications in current and future missions of geostationary satellites, like GEMS (Geostationary Environment Monitoring Spectrometer, Korea), ESA Sentinel-4, and NASA TEMPO (Tropospheric Emissions: Monitoring of POllution), predominantly covering the middle latitudes.

For new satellite instruments, specifications of the stability required for climate variables are provided in order to be useful for certain applications – for instance, deriving long-term trends. The stability is usually stated in units of percent per decade (% per decade) and is often associated with or termed instrument drift. A stability requirement of 3 % per decade or better has been recently stated for tropospheric and stratospheric ozone. However, the way this number is derived is not clear. In this study, we use Monte Carlo simulations to investigate how a stability requirement translates into uncertainties in long-term trends depending on the lifetime of individual observing systems, which are merged into time series, and the period of available observations. Depending on the need to observe a certain trend over a given period, e.g., typically +1 % per decade for total ozone and +2 % per decade for stratospheric ozone over 30 years, stability for observation systems can be properly specified and justified in order to achieve statistical significance in the observed long-term trend. Assuming a typical mean lifetime of 7 years for an individual observing system and a stability of 3 % per decade results in a 2 % per decade trend uncertainty over a period of 30 years, which is barely sufficient for stratospheric ozone but too high for total ozone. Having two or three observing systems simultaneously reduces the uncertainty by 30 % and 42 %, respectively. Such redundancies may be more efficient than developing satellite instruments with higher long-term stability to reduce long-term trend uncertainties. The method presented here is applicable to any variable of interest for which long-term changes are to be detected.

Two decision-support tools to assist air traffic controllers in managing challenging weather conditions are presented in this paper. The first provides weather impacts on airport departure routes to improve planning and reopening of routes once weather has passed. The second integrates weather avoidance polygons into a graphical user interface with track data to support evolution of time-based metering for arrivals. The two systems are presented in the perspective of a more weather-aware air traffic management system and a summary of the benefits of the two tools is discussed.

A tropospheric ozone column (TrOC) dataset from the Ozone Mapping and Profiler Suite (OMPS) observations was generated by combining the retrieved total ozone column from OMPS – Nadir Mapper (OMPS-NM) and limb profiles from OMPS – Limb Profiler (OMPS-LP) data. All datasets were generated at the University of Bremen, and the TrOC product was obtained by applying the limb–nadir matching technique (LNM). The retrieval algorithm and a comprehensive analysis of the uncertainty budget are presented here. The OMPS-LNM-TrOC dataset (2012–2018) is analysed and validated through comparison with ozonesondes, tropospheric ozone residual (TOR) data from the combined Ozone Monitoring Instrument/Microwave Limb Sounder (OMI/MLS) observations, and the TROPOspheric Monitoring Instrument (TROPOMI) Convective Cloud Differential technique (CCD) dataset. The OMPS-LNM TrOC is generally lower than the other datasets. The average bias with respect to ozonesondes is −1.7 DU with no significant latitudinal dependence identified. The mean difference with respect to OMI/MLS TOR and TROPOMI CCD is −3.4 and −1.8 DU, respectively. The seasonality and inter-annual variability are in good agreement with all comparison datasets.

This article describes a concept whereby future operational polarimetric phased array radars (PPAR) routinely monitor ice crystal alignment regions caused by thundercloud electric fields with volume scan updates (;12 min -1) sufficient to resolve the temporal variation due to lightning and subsequent rapid electric field regeneration in nonsevere thunderstorms. Routine observations of crystal alignment regions may enhance thunderstorm nowcasting through comparison of their temporal and spatial structure with other polarimetric signatures, integration with lightning detection data, and assimilation into convection resolving numerical weather prediction models. If crystal alignment observations indicate strong electrification well in advance of the first lightning strike and likewise reliably indicate the decay of strong electric fields at the end of a storm, this capability may improve warning for lightning-sensitive activities such as airport ramp operations and space launch. Experimental observations of crystal alignment volumes in central Oklahoma severe storms and their relation to those storms' structures are presented and used to motivate discussion of possible PPAR architectures. In one case-a tornadic supercell-these observations illustrate an important limitation. Even the hypothesized 12 min -1 volume scan update rate would not resolve the temporal variation of the crystal alignment regions in such storms, suggesting that special, adaptive scanning methods may be appropriate for such storms. We describe how future operational phased array radars could support a crystal alignment measurement mode via parallel, time-multiplexed processing and discuss potential impacts on the radar's primary weather observation mission. We conclude by discussing research needed to better understand technical challenges and operational benefits.

This study investigates the origin of the zonal asymmetry in stratospheric ozone trends at northern high latitudes, identified in satellite limb observations over the past two decades. We use a merged dataset consisting of ozone profiles retrieved at the University of Bremen from SCIAMACHY and OMPS-LP measurements to derive ozone trends. We also use TOMCAT chemical transport model (CTM) simulations, forced by ERA5 reanalyses, to investigate the factors which determine the asymmetry observed in the long-term changes. By studying seasonally and longitudinally resolved observation-based ozone trends, we find, especially during spring, a well-pronounced asymmetry at polar latitudes, with values up to +6 % per decade over Greenland and -5 % per decade over western Russia. The control CTM simulation agrees well with these observed trends, whereas sensitivity simulations indicate that chemical mechanisms, involved in the production and removal of ozone, or their changes, are unlikely to explain the observed behaviour. The decomposition of TOMCAT ozone time series and of ERA5 geopotential height into the first two wavenumber components shows a clear correlation between the two variables in the middle stratosphere and demonstrates a weakening and a shift in the wavenumber-1 planetary wave activity over the past two decades. Finally, the analysis of the polar vortex position and strength points to a decadal oscillation with a reversal pattern at the beginning of the century, also found in the ozone trend asymmetry. This further stresses the link between changes in the polar vortex position and the identified ozone trend pattern.