Is it feasible to estimate radiosonde biases from interlaced measurements?

Upper-air measurements of essential climate variables (ECVs), such as temperature, are crucial for climate monitoring and climate change detection. Because of the internal variability of the climate system, many decades of measurements are typically required to robustly detect any trend in the climate data record. It is imperative for the records to be temporally homogeneous over many decades to confidently estimate any trend. Historically, records of upper-air measurements were primarily made for short-term weather forecasts and as such are seldom suitable for studying long-term climate change as they lack the required continuity and homogeneity. Recognizing this, the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) has been established to provide reference-quality measurements of climate variables, such as temperature, pressure, and humidity, together with well-characterized and traceable estimates of the measurement uncertainty. To ensure that GRUAN data products are suitable to detect climate change, a scientifically robust instrument replacement strategy must always be adopted whenever there is a change in instrumentation. By fully characterizing any systematic differences between the old and new measurement system a temporally homogeneous data series can be created. One strategy is to operate both the old and new instruments in tandem for some overlap period to characterize any inter-instrument biases. However, this strategy can be prohibitively expensive at measurement sites operated by national weather services or research institutes. An alternative strategy that has been proposed is to alternate between the old and new instruments, so-called interlacing, and then statistically derive the systematic biases between the two instruments. Here we investigate the feasibility of such an approach specifically for radiosondes, i.e. flying the old and new instruments on alternating days. Synthetic data sets are used to explore the applicability of this statistical approach to radiosonde change management

Decarbonizing conference travel: testing a multi-hub approach

As the global research enterprise grapples with the challenge of a low carbon future, a key challenge is the future of international conferences. An emerging initiative which combines elements of the traditional in-person and virtual conference is a multi-hub approach. Here we report on a real-world trial of a multi-hub approach, the World Climate Research Programme/Stratosphere-troposphere Processes And their Role in Climate (WCRP/SPARC) General Assembly held in Qingdao-Reading-Boulder during the last week of October 2022 with more than 400 participants. While there are other examples of conferences run in dual-hub or hybrid online and in-person formats, we are not aware of other large atmospheric science conferences held in this format. Based on travel surveys of participants, we estimate that the multi-hub approach reduced the carbon footprint from travel by between a factor of 2.3 and 4.1 times the footprint when hosting the conference in a single location. This resulted in a saving of at least 288 tonnes of carbon dioxide equivalent (tCO2eq) and perhaps as much as 683 tCO2eq, compared to having the conference in one location only. Feedback from participants, collected immediately after the conference, showed that the majority (85%) would again attend another conference in a similar format. There are many ways that the format of the SPARC General Assembly could have been improved, but this proof-of-concept provides an inspiration to other groups to give the multi-hub format a try

Marine Carbonyl Sulfide (OCS) and Carbon Disulfide (CS\u3csub\u3e2\u3c/sub\u3e): A Compilation of Measurements in Seawater and the Marine Boundary Layer

Carbonyl sulfide (OCS) and carbon disulfide (CS2) are volatile sulfur gases that are naturally formed in seawater and exchanged with the atmosphere. OCS is the most abundant sulfur gas in the atmosphere, and CS2 is its most important precursor. They have attracted increased interest due to their direct (OCS) or indirect (CS2 via oxidation to OCS) contribution to the stratospheric sulfate aerosol layer. Furthermore, OCS serves as a proxy to constrain terrestrial CO2uptake by vegetation. Oceanic emissions of both gases contribute a major part to their atmospheric concentration. Here we present a database of previously published and unpublished (mainly shipborne) measurements in seawater and the marine boundary layer for both gases, available at https://doi.org/10.1594/PANGAEA.905430 (Lennartz et al., 2019). The database contains original measurements as well as data digitalized from figures in publications from 42 measurement campaigns, i.e., cruises or time series stations, ranging from 1982 to 2019. OCS data cover all ocean basins except for the Arctic Ocean, as well as all months of the year, while the CS2 dataset shows large gaps in spatial and temporal coverage. Concentrations are consistent across different sampling and analysis techniques for OCS. The database is intended to support the identification of global spatial and temporal patterns and to facilitate the evaluation of model simulations

Marine carbonyl sulfide (OCS) and carbon disulfide (CS2): a compilation of measurements in seawater and the marine boundary layer

Carbonyl sulfide (OCS) and carbon disulfide (CS2) are volatile sulfur gases that are naturally formed in seawater and exchanged with the atmosphere. OCS is the most abundant sulfur gas in the atmosphere, and CS2 is its most important precursor. They have gained interest due to their direct (OCS) or indirect (CS2 via oxidation to OCS) contribution to the stratospheric sulfate aerosol layer. Furthermore, OCS serves as a proxy to constrain terrestrial CO2 uptake by vegetation. Oceanic emissions of both gases contribute a major part to their atmospheric concentration. Here we present a database of previously published and unpublished, mainly ship-borne measurements in seawater and the marine boundary layer for both gases, available at https://doi.pangaea.de/10.1594/PANGAEA.905430 (Lennartz et al., 2019). The database contains original measurements as well as data digitalized from figures in publications from 42 measurement campaigns, i.e. cruises or time series stations, ranging from 1982 to 2019. OCS data cover all ocean basins except for the Arctic Ocean, as well as all months of the year, while the CS2 dataset shows large gaps in spatial and temporal coverage. Concentrations are consistent across different sampling and analysis techniques for OCS. The database is intended to support the identification of global spatial and temporal patterns and to facilitate the evaluation of model simulations

Estimates of ozone return dates from Chemistry-Climate Model Initiative simulations

We analyse simulations performed for the Chemistry-Climate Model Initiative (CCMI) to estimate the return dates of the stratospheric ozone layer from depletion caused by anthropogenic stratospheric chlorine and bromine. We consider a total of 155 simulations from 20 models, including a range of sensitivity studies which examine the impact of climate change on ozone recovery. For the control simulations (unconstrained by nudging towards analysed meteorology) there is a large spread (±20DU in the global average) in the predictions of the absolute ozone column. Therefore, the model results need to be adjusted for biases against historical data. Also, the interannual variability in the model results need to be smoothed in order to provide a reasonably narrow estimate of the range of ozone return dates. Consistent with previous studies, but here for a Representative Concentration Pathway (RCP) of 6.0, these new CCMI simulations project that global total column ozone will return to 1980 values in 2049 (with a 1σ uncertainty of 2043–2055). At Southern Hemisphere mid-latitudes column ozone is projected to return to 1980 values in 2045 (2039–2050), and at Northern Hemisphere mid-latitudes in 2032 (2020–2044). In the polar regions, the return dates are 2060 (2055–2066) in the Antarctic in October and 2034 (2025–2043) in the Arctic in March. The earlier return dates in the Northern Hemisphere reflect the larger sensitivity to dynamical changes. Our estimates of return dates are later than those presented in the 2014 Ozone Assessment by approximately 5–17 years, depending on the region, with the previous best estimates often falling outside of our uncertainty range. In the tropics only around half the models predict a return of ozone to 1980 values, around 2040, while the other half do not reach the 1980 value. All models show a negative trend in tropical total column ozone towards the end of the 21st century. The CCMI models generally agree in their simulation of the time evolution of stratospheric chlorine and bromine, which are the main drivers of ozone loss and recovery. However, there are a few outliers which show that the multi-model mean results for ozone recovery are not as tightly constrained as possible. Throughout the stratosphere the spread of ozone return dates to 1980 values between models tends to correlate with the spread of the return of inorganic chlorine to 1980 values. In the upper stratosphere, greenhouse gas-induced cooling speeds up the return by about 10–20 years. In the lower stratosphere, and for the column, there is a more direct link in the timing of the return dates of ozone and chlorine, especially for the large Antarctic depletion. Comparisons of total column ozone between the models is affected by different predictions of the evolution of tropospheric ozone within the same scenario, presumably due to differing treatment of tropospheric chemistry. Therefore, for many scenarios, clear conclusions can only be drawn for stratospheric ozone columns rather than the total column. As noted by previous studies, the timing of ozone recovery is affected by the evolution of N2O and CH4. However, quantifying the effect in the simulations analysed here is limited by the few realisations available for these experiments compared to internal model variability. The large increase in N2O given in RCP 6.0 extends the ozone return globally by ∼15 years relative to N2O fixed at 1960 abundances, mainly because it allows tropical column ozone to be depleted. The effect in extratropical latitudes is much smaller. The large increase in CH4 given in the RCP 8.5 scenario compared to RCP 6.0 also lengthens ozone return by ∼15 years, again mainly through its impact in the tropics. Overall, our estimates of ozone return dates are uncertain due to both uncertainties in future scenarios, in particular those of greenhouse gases, and uncertainties in models. The scenario uncertainty is small in the short term but increases with time, and becomes large by the end of the century. There are still some model–model differences related to well-known processes which affect ozone recovery. Efforts need to continue to ensure that models used for assessment purposes accurately represent stratospheric chemistry and the prescribed scenarios of ozone-depleting substances, and only those models are used to calculate return dates. For future assessments of single forcing or combined effects of CO2, CH4, and N2O on the stratospheric column ozone return dates, this work suggests that it is more important to have multi-member (at least three) ensembles for each scenario from every established participating model, rather than a large number of individual models

Stratospheric aerosol - Observations, processes, and impact on climate

Interest in stratospheric aerosol and its role in climate have increased over the last decade due to the observed increase in stratospheric aerosol since 2000 and the potential for changes in the sulfur cycle induced by climate change. This review provides an overview about the advances in stratospheric aerosol research since the last comprehensive assessment of stratospheric aerosol was published in 2006. A crucial development since 2006 is the substantial improvement in the agreement between in situ and space-based inferences of stratospheric aerosol properties during volcanically quiescent periods. Furthermore, new measurement systems and techniques, both in situ and space based, have been developed for measuring physical aerosol properties with greater accuracy and for characterizing aerosol composition. However, these changes induce challenges to constructing a long-term stratospheric aerosol climatology. Currently, changes in stratospheric aerosol levels less than 20% cannot be confidently quantified. The volcanic signals tend to mask any nonvolcanically driven change, making them difficult to understand. While the role of carbonyl sulfide as a substantial and relatively constant source of stratospheric sulfur has been confirmed by new observations and model simulations, large uncertainties remain with respect to the contribution from anthropogenic sulfur dioxide emissions. New evidence has been provided that stratospheric aerosol can also contain small amounts of nonsulfate matter such as black carbon and organics. Chemistry-climate models have substantially increased in quantity and sophistication. In many models the implementation of stratospheric aerosol processes is coupled to radiation and/or stratospheric chemistry modules to account for relevant feedback processes

Verbessertes Verständis der polaren Ozonchemie und die Zukunft des antarktischen Ozonlochs

Coupled chemistry-climate models (CCMs) are currently the most appropriate tools for projecting the evolution of the ozone layer through the 21st century and its impact on climate. However, numerous sources of uncertainties in CCM projections of the stratospheric ozone layer were revealed in the past. In this thesis three sources of uncertainty were investigated: (i) uncertainties in the kinetic reaction rates of an important ozone depleting catalytic cycle, (ii) uncertainties resulting from different future greenhouse gas (GHG) emissions, and (iii) uncertainties in the representation of key chemical processes in CCMs. This thesis presents two methods to derived key kinetic reactions rates driving polar ozone depletion from atmospheric measurements, such as ground-based chlorine monoxide (ClO) measurements, thereby focussing on the kinetic reaction rates driving the effectiveness of the ClO dimer cycle during the day. The ClO dimer is one of the most destructive ozone loss processes in polar regions. The derived results are in agreement with previous studies and confirm that a rather higher value of the ratio of kinetic parameters J/kf (where J is the photolysis frequency and kf is the dimer formation rate) than currently recommended is required to explain the atmospheric measurements. The findings of this thesis highlight the need for long-term atmospheric measurements of day and night-time ClO and ClOOCl (referred to as the ClO dimer) and the need to investigate the kinetic reaction rates under stratospheric conditions. The uncertainty in the ozone projections that arises from the uncertainty in future emissions of GHGs has been subject to the second part of this thesis. A semi-empirical model approach which is used to investigate the evolution of stratospheric activated chlorine concentrations and related changes in Antarctic ozone depletion in a changing climate is presented. The sensitivity of the return dates of Antarctic ozone to historic levels (e.g. 1960 or 1980) to GHG emissions scenarios is examined. It was found that the return date is largely insensitive to GHG concentrations. More importantly, this study shows that the tight coupling between ozone and temperature plays an important role in determining the return date of Antarctic ozone and therefore it is imperative that the ozone-temperature coupling is included in numerical models used to project future ozone abundances. The third part of this thesis presents a process-oriented approach to evaluate CCMs. For this purpose a new semi- empirical model, SWIFT, was developed to provide a tool to assess and evaluate the key processes driving polar ozone depletion in CCMs. SWIFT describes the time rate of change of key trace gases governing chlorine activation and deactivation. SWIFT is trained on atmospheric observations of trace gases, providing a set of empirical fit-coefficients. When applying SWIFT to CCM output, and comparing the derived fit-coefficients with those obtained in reality, the ability of the CCM to faithfully simulate key chemical processes can be assessed. Because a number of issues where revealed when applying SWIFT to CCM output, this thesis presents only preliminary results from the application of SWIFT to a selected CCM, EMAC-FUB. It was found that SWIFT reproduces the key processes for chlorine activation and deactivation very well and therefore, if accounting for known model deficiencies in CCMs, SWIFT can provide a powerful tool not only to evaluate key processes but also to estimate the importance of the model deficiencies on the key processes driving polar ozone depletion.Unter Berücksichtigung der Interaktionen zwischen Ozon- und Treibhausgas- induzierten Klimaänderungen sind gekoppelte Klima-Chemie Modelle (engl. chemistry-climate-models, CCMs) geeignete Mittel zur Erstellung von Projektionen der zukünftigen stratosphärischen Ozonentwicklung. Diese Prognosen werden jedoch durch eine Reihe von Unsicherheitsfaktoren beeinflusst. In der vorliegenden Arbeit werden drei Unsicherheitsquellen näher betrachtet: (i) Unsicherheiten in den reaktionskinetischen Parametern, (ii) Unsicherheiten im Verlauf der zukünftigen Treibhausgaskonzentrationen und (iii) Unsicherheiten in der Darstellung verschiedener Schlüssel-Prozesse für den polaren Ozonabbau in CCMs. In der vorliegenden Arbeit werden zwei Methoden vorgestellt, wie man reaktionskinetische Parameter von atmospärischen Messungen ableiten kann. Hierbei konzentrieren sich diese Arbeit auf die reaktionskinetischen Parameter eines der bedeutendsten ozonzerstörenden Zyklen in den polaren Regionen, den ClO-Dimer Zyklus. Die in dieser Arbeit gewonnenen Ergebnisse bestätigen die Ergebnisse früherer Studien, dass im Vergleich zu den derzeit empfohlenen und verwendeten reaktionskinetischen Parametern ein eher größerer Wert benötigt wird, um die atmosphärischen Messungen zu reproduzieren. Die Resultate der Arbeit untersteichen die Notwendigkeit von langfristigen atmosphärischen Tag- und Nachtmessungen von ClO und dem ClO- Dimer sowie die Notwendigkeit, die reaktionskinetischen Parameter unter stratosphärischen Bedingungen zu untersuchen. Die Unsicherheiten in den Ozon- Prognosen - resultierend aus den bestehenden Unsicherheiten im Verlauf der zukünftigen Treibhausgasemissionen - werden im zweiten Teil dieser Arbeit näher betrachtet. Hier wird ein semi-empirischer Modellansatz vorgestellt, um die Entwicklung stratosphärischer Chlorkonzentrationen und die damit verbundene Veränderung im antarktischen Ozon unter den Aspekten des Klimawandels zu prognostizieren. Dabei wurde das Problem der Ozonerholung auf historische Werte (z.B. von 1960 oder 1980) in Abhängigkeit verschiedener Treibhausgasemissions-Szenarien untersucht. Die Untersuchungen machen den Einfluss des Temperatur-Ozon-Feedbacks deutlich: wird dieser nicht berücksichtigt, dann ist der Zeitpunkt der Ozonerholung größtenteils unabhängig von der Treibhausgasentwicklung. Die Bedeutung der engen Kopplung zwischen Temperatur und Ozon und ihre entscheidende Rolle bei der Erstellung von Ozon-Prognosen in der Antarktis werden verdeutlicht. Im dritten Teil der vorliegenden Arbeit wird ein Ansatz zur Prozess-orientierten Evaluierung von CCMs vorgestellt. Hierfür wurde ein semi-empirisches Model entwickelt, SWIFT, welches die zeitliche Änderung von Spurengasen, welche die Chloraktivierung und -deaktivierung regulieren, beschreibt. SWIFT wird an atmosphärischen Messungen verschiedener Spurengase trainiert, woraus empirische Fitkoeffizienten hervorgehen. Wenn SWIFT dann auf CCM Daten angewendet wird, können die berechneten Fitkoeffizienten mit den aus den Beobachtungen gewonnenen Koeffizienten verglichen werden. Dieser Vergleich ermöglicht es abzuschätzen, wie genau die CCMs die chemischen Prozesse simulieren können. In dieser Arbeit werden vorläufige Ergebnisse einer ersten Anwendung von SWIFT auf CCM-Daten vorgestellt