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The particle flux in the near-Earth environment can increase by orders of magnitude during geomagnetically active periods. This leads to intensification of particle precipitation into Earth's atmosphere. The process potentially further affects atmospheric chemistry and temperature. In this research, we concentrate on ring current electrons and investigate precipitation mechanisms on a time scale comparable to the cadence of satellites on low Earth orbit (LEO) using a numerical model based on the Fokker-Planck equation. We focus on investigation of the precipitation mechanisms and their connection with atmospheric parameters.In this study, we investigate a time period that covers 4 corotating interaction region (CIR) and 2 coronal mass ejection (CME) storm events. For all storms we quantify impact on the electron ring current and the resulting electron precipitation. Our results are validated against observations from the POES satellite mission, low Earth orbiting meteorological satellites, and Van Allen Probes, producing a dataset of precipitated fluxes that covers energy range from 1 keV to 1 MeV. Maps of precipitating fluxes for different energies allow us to understand in which regions on Earth precipitation is the most intensive. The output of the model is further used for calculation of ionization rates at different altitudes, allowing it to estimate effects of geomagnetically active periods on chemical and physical variability near the poles., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

Mean age of air (AoA) is a common diagnostic for the strength of the stratospheric overturning circulation in both climate models and observations. AoA climatologies and AoA trends over the recent decades of model simulations and proxies derived from observations of long-lived tracers do not agree. Satellite observations show much older air than climate models, and while most models compute a clear decrease in AoA over the last decades, a 30-year time series from measurements shows a statistically nonsignificant positive trend in the Northern Hemisphere extratropical middle stratosphere. Measurement-based AoA derivations are often founded on observations of the trace gas sulfur hexafluoride (SF6), a fairly long-lived gas with a near-linear increase in emissions during recent decades. However, SF6 has chemical sinks in the mesosphere that are not considered in most model studies. In this study, we explicitly compute the chemical SF6 sinks based on chemical processes in the global chemistry climate model EMAC (ECHAM/MESSy Atmospheric Chemistry). We show that good agreement between stratospheric AoA in EMAC and MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) is reached through the inclusion of chemical SF6 sinks, as these sinks lead to a strong increase in the stratospheric AoA and, therefore, to a better agreement with MIPAS satellite observations. Remaining larger differences at high latitudes are addressed, and possible reasons for these differences are discussed. Subsequently, we demonstrate that the AoA trends are also strongly influenced by the chemical SF6 sinks. Under consideration of the SF6 sinks, the AoA trends over the recent decades reverse sign from negative to positive. We conduct sensitivity simulations which reveal that this sign reversal does not result from trends in the stratospheric circulation strength nor from changes in the strength of the SF6 sinks. We illustrate that even a constant SF6 destruction rate causes a positive trend in the derived AoA, as the amount of depleted SF6 scales with increasing SF6 abundance itself. In our simulations, this effect overcompensates for the impact of the accelerating stratospheric circulation which naturally decreases AoA. Although various sources of uncertainties cannot be quantified in detail in this study, our results suggest that the inclusion of SF6 depletion in models has the potential to reconcile the AoA trends of models and observations. We conclude the study with a first approach towards a correction to account for SF6 loss and deduce that a linear correction might be applicable to values of AoA of up to 4 years.

Mean age of air (AoA) is a common diagnostic for the strength of the stratospheric overturning circulation in both climate models and observations. AoA climatologies and AoA trends over the recent decades of model simulations and proxies derived from observations of long-lived tracers do not agree. Satellite observations show much older air than climate models, and while most models compute a clear decrease in AoA over the last decades, a 30-year time series from measurements shows a statistically nonsignificant positive trend in the Northern Hemisphere extratropical middle stratosphere. Measurement-based AoA derivations are often founded on observations of the trace gas sulfur hexafluoride (SF$_{6}$), a fairly long-lived gas with a near-linear increase in emissions during recent decades. However, SF$_{6}$ has chemical sinks in the mesosphere that are not considered in most model studies. In this study, we explicitly compute the chemical SF$_{6}$ sinks based on chemical processes in the global chemistry climate model EMAC (ECHAM/MESSy Atmospheric Chemistry). We show that good agreement between stratospheric AoA in EMAC and MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) is reached through the inclusion of chemical SF$_{6}$ sinks, as these sinks lead to a strong increase in the stratospheric AoA and, therefore, to a better agreement with MIPAS satellite observations. Remaining larger differences at high latitudes are addressed, and possible reasons for these differences are discussed. Subsequently, we demonstrate that the AoA trends are also strongly influenced by the chemical SF6 sinks. Under consideration of the SF$_{6}$ sinks, the AoA trends over the recent decades reverse sign from negative to positive. We conduct sensitivity simulations which reveal that this sign reversal does not result from trends in the stratospheric circulation strength nor from changes in the strength of the SF$_{6}$ sinks. We illustrate that even a constant SF$_{6}$ destruction rate causes a positive trend in the derived AoA, as the amount of depleted SF$_{6}$ scales with increasing SF$_{6}$ abundance itself. In our simulations, this effect overcompensates for the impact of the accelerating stratospheric circulation which naturally decreases AoA. Although various sources of uncertainties cannot be quantified in detail in this study, our results suggest that the inclusion of SF$_{6}$ depletion in models has the potential to reconcile the AoA trends of models and observations. We conclude the study with a first approach towards a correction to account for SF$_{6}$ loss and deduce that a linear correction might be applicable to values of AoA of up to 4 years.

We present the first observational dataset of vertically resolved global stratospheric BrONO2 distributions from July 2002 until April 2012, and compare them to results of the atmospheric chemical climate model EMAC. The retrieved distributions are based on space-borne measurements of infrared limb-emission spectra recorded by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) on Envisat. The derived vertical profiles of BrONO2 volume mixing ratios represent 10° latitude bins and three-day means, separated into sunlit and observations in the dark. The estimated uncertainties are around 1–4 pptv caused by spectral noise for single profiles as well as for further parameter and systematic errors which may not improve by averaging. Vertical resolutions range from 3 to 8 km between 15 and 35 km altitude. All leading modes of spatial and temporal variability of stratospheric BrONO2 in the observations are well replicated by the model simulations: the large diurnal variability, the low values during polar winter as well as the maximum values at mid- and high latitudes during summer. Three major differences between observations and model results are observed: (1) a model underestimation of enhanced BrONO2 in the polar winter stratosphere above about 30 km of up to 15 pptv, (2) up to 8 pptv higher modelled values than observed globally in the lower stratosphere up to 25 km most obvious during night, and (3) up to 5 pptv lower modelled concentrations at tropical latitudes between 27 and 32 km during sunlit conditions. (1) is explained by the model missing enhanced NOx produced in the mesosphere and lower thermosphere subsiding at high latitudes in winter. This is the first time that observational evidence for enhancement of BrONO2 caused by mesospheric NOx production is reported. The other major inconsistencies (2,3) between EMAC model results and observations are studied by sensitivity runs with a 1d model. These tentatively hint to a model underestimation of heterogeneous loss of BrONO2 in the lower stratosphere, a too low simulated production of BrONO2 during day as well as strongly underestimated BrONO2 volume mixing ratios when loss via reaction with O(3P) is considered additionally to photolysis. However, considering the uncertainty ranges of model parameters and of measurements, an unambiguous identification of the causes for the differences remains difficult. The observations have also been used to derive the total stratospheric bromine content relative to years of stratospheric entry between 1997 and 2007. With an average value of 21.2 ± 1.4 pptv of Bry at mid-latitudes where the modelled adjustment from BrONO2 to Bry is lowest, the MIPAS data agree with estimates of Bry derived from observations of BrO as well as from MIPAS-Balloon measurements of BrONO2.

Mean age of air (AoA) is a common diagnostic for the strength of the stratospheric overturning circulation in both climate models and observations. AoA climatologies and its trends over the recent decades of model simulations and proxies derived from observations of long-lived tracers do not agree. Satellite observations show much older air than climate models and while most models compute a clear decrease of AoA over the last decades, a thirty-year timeseries from measurements shows a statistically non-significant positive trend. Measurement-based AoA derivations are often based on observations of the trace gas SF6, a fairly long-lived gas with a near-linear increase of emissions during the recent decades. However, SF6 has chemical sinks in the mesosphere, which are not considered in most model studies. In this study, we explicitly compute the chemical SF6 sinks based on chemical processes in the global chemistry-climate model EMAC. We show that good agreement of stratospheric AoA in EMAC and MIPAS is reached through the inclusion of chemical SF6 sinks, as those lead to a strong increase of the stratospheric AoA and thereby to a better agreement with MIPAS satellite observations. Remaining larger differences in high latitudes are addressed and possible reasons are discussed. Subsequently, we demonstrate that also the AoA trends are strongly influenced by the chemical SF6 sinks. Under consideration of the SF6 sinks, the AoA trends over the recent decades reverse sign from negative to positive. We conduct sensitivity simulations which reveal that this sign reversal results neither from trends of the stratospheric circulation strength, nor from changes in the strength of the SF6 sinks. We illustrate that even a constant SF6 destruction rate causes a positive trend in the derived AoA, since the amount of depleted SF6 scales with the increasing SF6 abundance itself. In our simulations, this effect overcompensates the impact of the accelerating stratospheric circulation which naturally decreases AoA. Although various sources of uncertainties cannot be quantified in detail in this study, our results suggest that the inclusion of SF6 depletion in models has the potential to reconcile the AoA trends of models and observations.

We present the first observational dataset of vertically resolved global stratospheric BrONO2 distributions from July 2002 until April 2012 and compare them to results of the atmospheric chemical climate model ECHAM/MESSy Atmospheric Chemistry (EMAC). The retrieved distributions are based on space-borne measurements of infrared limb-emission spectra recorded by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) on Envisat. The derived vertical profiles of BrONO2 volume mixing ratios represent 10∘ latitude bins and 3 d means, separated into sunlit observations and observations in the dark. The estimated uncertainties are around 1–4 pptv, caused by spectral noise for single profiles as well as for further parameter and systematic errors which may not improve by averaging. Vertical resolutions range from 3 to 8 km between 15 and 35 km altitude. All leading modes of spatial and temporal variability of stratospheric BrONO2 in the observations are well replicated by the model simulations: the large diurnal variability, the low values during polar winter as well as the maximum values at mid and high latitudes during summer. Three major differences between observations and model results are observed: (1) a model underestimation of enhanced BrONO2 in the polar winter stratosphere above about 30 km of up to 15 pptv, (2) up to 8 pptv higher modelled values than observed globally in the lower stratosphere up to 25 km, most obvious during night, and (3) up to 5 pptv lower modelled concentrations at tropical latitudes between 27 and 32 km during sunlit conditions. (1) is explained by the model missing enhanced NOx produced in the mesosphere and lower thermosphere subsiding at high latitudes in winter. This is the first time that observational evidence for enhancement of BrONO2 caused by mesospheric NOx production is reported. The other major inconsistencies (2, 3) between EMAC model results and observations are studied by sensitivity runs with a 1D model. These tentatively hint at a model underestimation of heterogeneous loss of BrONO2 in the lower stratosphere, a simulated production of BrONO2 that is too low during the day as well as strongly underestimated BrONO2 volume mixing ratios when loss via reaction with O(3P) is considered in addition to photolysis. However, considering the uncertainty ranges of model parameters and of measurements, an unambiguous identification of the causes of the differences remains difficult. The observations have also been used to derive the total stratospheric bromine content relative to years of stratospheric entry between 1997 and 2007. With an average value of 21.2±1.4 pptv of Bry at mid latitudes where the modelled adjustment from BrONO2 to Bry is smallest, the MIPAS data agree with estimates of Bry derived from observations of BrO as well as from MIPAS-Balloon measurements of BrONO2.

The distribution of methane (CH4) in the stratosphere can be a major driver of spatial variability in the dry-air column-averaged CH4 mixing ratio (XCH4), which is being measured increasingly for the assessment of CH4 surface emissions. Chemistry-transport models (CTMs) therefore need to simulate the tropospheric and stratospheric fractional columns of XCH4 accurately for estimating surface emissions from XCH4. Simulations from three CTMs are tested against XCH4 observations from the Total Carbon Column Network (TCCON). We analyze how the model-TCCON agreement in XCH4 depends on the model representation of stratospheric CH4 distributions. Model equivalents of TCCON XCH4 are computed with stratospheric CH4 fields from both the model simulations and from satellite-based CH4 distributions from MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) and MIPAS CH4 fields adjusted to ACE-FTS (Atmospheric Chemistry Experiment Fourier Transform Spectrometer) observations. Using MIPAS-based stratospheric CH4 fields in place of model simulations improves the model-TCCON XCH4 agreement for all models. For the Atmospheric Chemistry Transport Model (ACTM) the average XCH4 bias is significantly reduced from 38.1 to 13.7 ppb, whereas small improvements are found for the models TM5 (Transport Model, version 5; from 8.7 to 4.3 ppb) and LMDz (Laboratoire de Météorologie Dynamique model with zooming capability; from 6.8 to 4.3 ppb). Replacing model simulations with MIPAS stratospheric CH4 fields adjusted to ACE-FTS reduces the average XCH4 bias for ACTM (3.3 ppb), but increases the average XCH4 bias for TM5 (10.8 ppb) and LMDz (20.0 ppb). These findings imply that model errors in simulating stratospheric CH4 contribute to model biases. Current satellite instruments cannot definitively measure stratospheric CH4 to sufficient accuracy to eliminate these biases. Applying transport diagnostics to the models indicates that model-to-model differences in the simulation of stratospheric transport, notably the age of stratospheric air, can largely explain the inter-model spread in stratospheric CH4 and, hence, its contribution to XCH4. Therefore, it would be worthwhile to analyze how individual model components (e.g., physical parameterization, meteorological data sets, model horizontal/vertical resolution) impact the simulation of stratospheric CH4 and XCH4.

A new and improved setup of the SF6 retrieval together with a newly calibrated version of MIPAS-ENVISAT level 1b spectra (version 5, ESA data version 5.02/5.06) was used to obtain a new global data set of vertically resolved SF6 mixing ratios, covering the total observational period of MIPAS from July 2002 to April 2012 for the first time. This data set was validated with balloon-borne in-situ measurements as well as with data from the other renowned satellite instrument measuring SF6, the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS). Monthly and zonally averaged SF6 vertical profiles were converted into mean age of air (AoA) using a tropospheric SF6 reference curve. The obtained data set of age of air was compared to airborne age of air measurements. The temporal evolution of the mean age of air was then investigated in 10° latitude and 1-2 km altitude bins. A regression model consisting of a constant and a linear trend term, two proxies for the quasi-biennial oscillation variation, sinusoidal terms for the seasonal and semiannual variation and overtones was fitted to the age of air time series. The annual cycle of age of air for particular regions in the stratosphere was investigated and compared to other studies. The age of air trend over the total MIPAS period consisting of the linear term was assessed and compared to previous findings of Stiller et al. [2012]. While the linear increase of mean age is confirmed to be positive for the northern midlatitudes and southern polar middle stratosphere, differences are found in the northern polar upper stratosphere, where the mean age is now found to increase as well. The magnitude of trends in the northern midlatitude middle stratosphere is slightly lower compared to the previous results and the trends fit remarkably well to the trend derived by Engel et al. [2009] for northern midlatitudes. Negative age of air trends found by Stiller et al. [2012] are confirmed for the lowermost tropical and southern midlatitudinal stratosphere. Differences to the previous data versions occur in the middle tropical stratosphere around 25 km, where the age trends are now negative. Overall, the new latitude-altitude distribution of trends appears to be less patchy and more coherent than the previous one. In addition, different sensitivity studies on the calculation of age of air have been carried out, including a further developed non-linearity correction with simulated age of air spectra as opposed to the traditional method where an inverse Gaussian function was used to parametrise the age spectrum as a function of the mean age. Age of air trend patterns were found to be robust with respect to these variations of the analysis method. Applying the same methods as for MIPAS, it was tried to infer decadal age of air trends also from ACE-FTS SF6 data. Even though data coverage is very sparse, significant positive decadal trends for the northern midlatitudes were found also for this data set. The hemispheric asymmetry of negative age of air trends in the Southern Hemisphere, and positive trends in the Northern Hemisphere was found to be consistent with simulations by the Lagrangian chemistry transport model CLaMS driven by ERA-Interim data. The decadal trends are also compared to trends calculated from SF6 mixing ratios simulated by the Karlsruhe Simulation Model of the Middle Atmosphere (KASIMA) and good agreement is found. While CLaMS model calculations for the MIPAS period have shown that trends in AoA can often be attributed to trends in mixing processes and not necessarily to circulation changes, the negative AoA trends in the southern midlatitudinal lowermost stratosphere could unambiguously be attributed to an accelerating shallow branch of the Brewer-Dobson circulation.

The distribution of methane (CH4) in the stratosphere can be a major driver of spatial variability in the dry-air column-averaged CH4 mixing ratio (XCH4), which is being measured increasingly for the assessment of CH4 surface emissions. Chemistry-transport models (CTMs) therefore need to simulate the tropospheric and stratospheric fractional columns of XCH4 accurately for estimating surface emissions from XCH4. Simulations from three CTMs are tested against XCH4 observations from the Total Carbon Column Network (TCCON). We analyze how the model–TCCON agreement in XCH4 depends on the model representation of stratospheric CH4 distributions. Model equivalents of TCCON XCH4 are computed with stratospheric CH4 fields from both the model simulations and from satellite-based CH4 distributions from MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) and MIPAS CH4 fields adjusted to ACE-FTS (Atmospheric Chemistry Experiment Fourier Transform Spectrometer) observations. Using MIPAS-based stratospheric CH4 fields in place of model simulations improves the model–TCCON XCH4 agreement for all models. For the Atmospheric Chemistry Transport Model (ACTM) the average XCH4 bias is significantly reduced from 38.1 to 13.7 ppb, whereas small improvements are found for the models TM5 (Transport Model, version 5; from 8.7 to 4.3 ppb) and LMDz (Laboratoire de Météorologie Dynamique model with zooming capability; from 6.8 to 4.3 ppb). Replacing model simulations with MIPAS stratospheric CH4 fields adjusted to ACE-FTS reduces the average XCH4 bias for ACTM (3.3 ppb), but increases the average XCH4 bias for TM5 (10.8 ppb) and LMDz (20.0 ppb). These findings imply that model errors in simulating stratospheric CH4 contribute to model biases. Current satellite instruments cannot definitively measure stratospheric CH4 to sufficient accuracy to eliminate these biases. Applying transport diagnostics to the models indicates that model-to-model differences in the simulation of stratospheric transport, notably the age of stratospheric air, can largely explain the inter-model spread in stratospheric CH4 and, hence, its contribution to XCH4. Therefore, it would be worthwhile to analyze how individual model components (e.g., physical parameterization, meteorological data sets, model horizontal/vertical resolution) impact the simulation of stratospheric CH4 and XCH4.

The distribution of gases such as ozone and water vapour in the stratosphere - which affect surface climate - is influenced by the meridional overturning of mass in the stratosphere, the Brewer-Dobson circulation. However, observation-based estimates of its global strength are difficult to obtain. Here we present two calculations of the mean strength of the meridional overturning of the stratosphere. We analyze satellite data that document the global diabatic circulation between 2007- 2011, and compare these to three re-analysis data sets and to simulations with a state-of-the-art chemistry-climate model. Using measurements of sulfur hexafluoride (SF6) and nitrous oxide, we calculate the global mean diabatic overturning mass flux throughout the stratosphere. In the lower stratosphere, these two estimates agree, and at a potential temperature level of 460 K (about 20 km or 60 hPa in tropics), the global circulation strength is 6.3-7.6 × 109 kg/s. Higher in the atmosphere, only the SF6-based estimate is available, and it diverges from the re-analysis data and simulations. Interpretation of the SF6 data-based estimate is limited because of a mesospheric sink of SF6; however, the reanalyses also differ substantially from each other. We conclude that the uncertainty in the mean meridional overturning circulation strength at upper levels of the stratosphere amounts to at least 100 %.

The distribution of methane (CH4) in the stratosphere can be a major driver of spatial variability in the dry-air column-averaged CH4 mixing ratio (XCH4), which is being measured increasingly for the assessment of CH4 surface emissions. Chemistry-transport models (CTMs) therefore need to simulate the tropospheric and stratospheric fractional columns of XCH4 accurately for estimating surface emissions from XCH4. Simulations from three CTMs are tested against XCH4 observations from the Total Carbon Column Network (TCCON). We analyze how the model–TCCON agreement in XCH4 depends on the model representation of stratospheric CH4 distributions. Model equivalents of TCCON XCH4 are computed with stratospheric CH4 fields from both the model simulations and from satellite-based CH4 distributions from MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) and MIPAS CH4 fields adjusted to ACE-FTS (Atmospheric Chemistry Experiment Fourier Transform Spectrometer) observations. Using MIPAS-based stratospheric CH4 fields in place of model simulations improves the model–TCCON XCH4 agreement for all models. For the Atmospheric Chemistry Transport Model (ACTM) the average XCH4 bias is significantly reduced from 38.1 to 13.7 ppb, whereas small improvements are found for the models TM5 (Transport Model, version 5; from 8.7 to 4.3 ppb) and LMDz (Laboratoire de Météorologie Dynamique model with zooming capability; from 6.8 to 4.3 ppb). Replacing model simulations with MIPAS stratospheric CH4 fields adjusted to ACE-FTS reduces the average XCH4 bias for ACTM (3.3 ppb), but increases the average XCH4 bias for TM5 (10.8 ppb) and LMDz (20.0 ppb). These findings imply that model errors in simulating stratospheric CH4 contribute to model biases. Current satellite instruments cannot definitively measure stratospheric CH4 to sufficient accuracy to eliminate these biases. Applying transport diagnostics to the models indicates that model-to-model differences in the simulation of stratospheric transport, notably the age of stratospheric air, can largely explain the inter-model spread in stratospheric CH4 and, hence, its contribution to XCH4. Therefore, it would be worthwhile to analyze how individual model components (e.g., physical parameterization, meteorological data sets, model horizontal/vertical resolution) impact the simulation of stratospheric CH4 and XCH4.