Changes in the polar vortex: Effects on Antarctic total ozone observations at various stations

October mean total column ozone data from four Antarctic stations form the basis for understanding the evolution of the ozone hole since 1960. While these stations show similar emergence of the ozone hole from 1960 to 1980, the records are divergent in the last two decades. The effects of long-term changes in vortex shape and location are considered by gridding the measurements by equivalent latitude. A clear eastward shift of the mean position of the vortex in October with time is revealed, which changes the fraction of ozone measurements taken inside/outside the vortex for stations in the vortex collar region. After including only those measurements made inside the vortex, ozone behavior in the last two decades at the four stations is very similar. This suggests that dynamical influence must be considered when interpreting and intercomparing ozone measurements from Antarctic stations for detecting ozone recovery and ozone-related changes in Antarctic climate

Comparison of Reanalysis and Observational Precipitation Datasets Including ERA5 and WFDE5

Precipitation is a key component of the hydrological cycle and one of the most important variables in weather and climate studies. Accurate and reliable precipitation data are crucial for determining climate trends and variability. In this study, eleven different precipitation datasets are compared, six reanalysis and five observational datasets, including the reanalysis datasets ERA5 and WFDE5 from the ECMWF family, to quantify the differences between the widely used precipitation datasets and to identify their particular strengths and shortcomings

Cloud parameters from reanalysis datasets – a comparison with satellite data

Clouds are a key component of the hydrological cycle and play an important role in weather and climate. Feedbacks between clouds and climate have important implications for climate sensitivity and thus on amplitude and pace of future climate change. In this study, as part of the SPARC Reanalysis Intercomparison Project (S-RIP) phase 2, we compare the cloud parameters from different reanalysis datasets, including the most widely used reanalyses ERA5, MERRA2 and JRA-55, with satellite observations. The study focuses on tropospheric clouds on monthly to seasonal and multi-year time scales. Means and variability of cloud parameters from the reanalyses such as cloud fraction, cloud liquid and ice water content as well as cloud radiative effects are compared to satellite observations for specific cloud regimes and regions. In addition to evaluating the performance of the different reanalysis products, we investigate whether the multi-reanalysis mean is in closer agreement with the observations than the individual reanalyses. The analyses are performed with the Earth System Model Evaluation Tool (ESMValTool), a community developed open-source software tool. The tool provides common operations such as interpolating data on the same grid, calculating multi-reanalysis means, common data masking, area extraction, and basic statistics such as seasonal means, annual means, area means, etc. which facilitates a fair comparison with observations. Uncertainties are estimated using multi-product observational reference datasets

How robust are trends in the Brewer-Dobson circulation derived from observed stratospheric temperatures?

Most global circulation models and climate-chemistry models forced with increasing greenhouse gases predict a strengthening of the Brewer-Dobson circulation (BDC) in the twenty-first century, and some of them claim that such strengthening has already begun at the end of the twentieth century. However, observational evidence for such a trend remains inconclusive. The goal of this paper is to examine the evidence for observed trends in the stratospheric overturning circulation using a suite of currently available observational stratospheric temperature data. Trends are examined as ''departures'' from the global mean temperature, since such trends reflect the effects of dynamics and spatially inhomogeneous radiative forcing and are to first order independent of the direct radiative effects of increasing well-mixed greenhouse gas concentrations. The primary conclusion of the study is that temperature observations do not reveal statistically significant trends in the Brewer-Dobson circulation over the period from 1979 to the present, as covered by Microwave Sounding Unit and Stratospheric Sounding Unit temperatures. The estimated trends in the BDC are weak in all datasets and not statistically significant at the 95% confidence level. In many cases, different data products yield very different results, particularly when the trends are stratified by season. Implications for the interpretation of recent stratospheric climate change are discussed. The results illustrate the essential need to better constrain the accuracy of future stratospheric temperature datasets

Detecting Extreme Temperature Events Using Gaussian Mixture Models

Extreme temperature events have traditionally been detected assuming a unimodal distribution of temperature data. We found that surface temperature data can be described more accurately with a multimodal rather than a unimodal distribution. Here, we applied Gaussian Mixture Models (GMM) to daily near-surface maximum air temperature data from the historical and future Coupled Model Intercomparison Project Phase 6 (CMIP6) simulations for 46 land regions defined by the Intergovernmental Panel on Climate Change (IPCC). Using the multimodal distribution, we found that temperature extremes, defined based on daily data in the warmest mode of the GMM distributions, are getting more frequent in all regions. Globally, a 10-year extreme temperature event relative to 1985-2014 conditions will occur 13.6 times more frequently in the future under 3.0{\deg}C of Global Warming Levels (GWL). The frequency increase can be even higher in tropical regions, such that 10-year extreme temperature events will occur almost twice a week. Additionally, we analysed the change in future temperature distributions under different GWL and found that the hot temperatures are increasing faster than cold temperatures in low latitudes, while the cold temperatures are increasing faster than the hot temperatures in high latitudes. The smallest changes in temperature distribution can be found in tropical regions, where the annual temperature range is small. Our method captures the differences in geographical regions and shows that the frequency of extreme events will be even higher than reported in previous studies.Comment: 32 pages, 10 figure

Evaluation of native Earth system model output with ESMValTool v2.6.0

Earth system models (ESMs) are state-of-the-art climate models that allow numerical simulations of the past, present-day, and future climate. To extend our understanding of the Earth system and improve climate change projections, the complexity of ESMs heavily increased over the last decades. As a consequence, the amount and volume of data provided by ESMs has increased considerably. Innovative tools for a comprehensive model evaluation and analysis are required to assess the performance of these increasingly complex ESMs against observations or reanalyses. One of these tools is the Earth System Model Evaluation Tool (ESMValTool), a community diagnostic and performance metrics tool for the evaluation of ESMs. Input data for ESMValTool needs to be formatted according to the CMOR (Climate Model Output Rewriter) standard, a process that is usually referred to as “CMORization”. While this is a quasi-standard for large model intercomparison projects like the Coupled Model Intercomparison Project (CMIP), this complicates the application of ESMValTool to non-CMOR-compliant climate model output. In this paper, we describe an extension of ESMValTool introduced in v2.6.0 that allows seamless reading and processing of “native” climate model output, i.e., operational output produced by running the climate model through the standard workflow of the corresponding modeling institute. This is achieved by an extension of ESMValTool's preprocessing pipeline that performs a CMOR-like reformatting of the native model output during runtime. Thus, the rich collection of diagnostics provided by ESMValTool is now fully available for these models. For models that use unstructured grids, a further preprocessing step required to apply many common diagnostics is regridding to a regular latitude–longitude grid. Extensions to ESMValTool's regridding functions described here allow for more flexible interpolation schemes that can be used on unstructured grids. Currently, ESMValTool supports nearest-neighbor, bilinear, and first-order conservative regridding from unstructured grids to regular grids. Example applications of this new native model support are the evaluation of new model setups against predecessor versions, assessing of the performance of different simulations against observations, CMORization of native model data for contributions to model intercomparison projects, and monitoring of running climate model simulations. For the latter, new general-purpose diagnostics have been added to ESMValTool that are able to plot a wide range of variable types. Currently, five climate models are supported: CESM2 (experimental; at the moment, only surface variables are available), EC-Earth3, EMAC, ICON, and IPSL-CM6. As the framework for the CMOR-like reformatting of native model output described here is implemented in a general way, support for other climate models can be easily added.The development of ESMValTool is supported by the projects “Climate-Carbon Interactions in the Current Century” (4C; grant agreement no. 821003), “Earth System Models for the Future” (ESM2025; grant agreement no. 101003536), “Infrastructure for the European Network for Earth System Modelling - Phase 3” (IS-ENES3; grant agreement no. 824084), and the European Research Council (ERC) Synergy Grant “Understanding and Modelling the Earth System with Machine Learning” (USMILE; grant agreement no. 855187) under the European Union's Horizon 2020 Research and Innovation Programme. This study is a contribution to the project S1 of the Collaborative Research Centre TRR 181 “Energy Transfers in Atmosphere and Ocean” funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) (project no. 274762653). Brian Medeiros acknowledges support by the U.S. Department of Energy (award no. DE-SC0022070), the National Science Foundation (NSF) (IA 1947282), the National Center for Atmospheric Research, which is a major facility sponsored by the NSF (cooperative agreement no. 1852977), and the National Oceanic and Atmospheric Administration (award no. NA20OAR4310392). Tobias Stacke acknowledges funding support from the European Research Council (ERC) under the European Union's Horizon 2020 Programme (grant agreement no. 951288). This work used resources of the Deutsches Klimarechenzentrum (DKRZ) granted by its Scientific Steering Committee (WLA) under the project IDs bd0854, bd1179, and id0853. We acknowledge the World Climate Research Programme (WCRP), which, through its Working Group on Coupled Modeling, coordinated and promoted CMIP6. We thank the climate modeling groups for producing and making their model output available, the Earth System Grid Federation (ESGF) for archiving the data and providing access, and the multiple funding agencies who support CMIP and ESGF. We would like to thank Mattia Righi (DLR) for providing helpful comments about the manuscript.Peer Reviewed"Article signat per 15 autors/es:Manuel Schlund, Birgit Hassler, Axel Lauer, Bouwe Andela, Patrick Jöckel, Rémi Kazeroni, Saskia Loosveldt Tomas, Brian Medeiros, Valeriu Predoi, Stéphane Sénési, Jérôme Servonnat, Tobias Stacke, Javier Vegas-Regidor, Klaus Zimmermann, and Veronika Eyring"Postprint (published version

South Pole Station ozonesondes: variability and trends in the springtime Antarctic ozone hole 1986–2021

Balloon-borne ozonesondes launched weekly from South Pole station (1986&ndash;2021) measure high vertical resolution profiles of ozone and temperature from surface to 30&ndash;35 km altitude. The launch frequency is increased in late winter before the onset of rapid stratospheric ozone loss in September. Ozone hole metrics show the yearly total column ozone and 14&ndash;21 km column ozone minimum values and September loss rates remain on an upward (less severe) trend since 2001. However, the data series also illustrate interannual variability, especially in the last three years (2019&ndash;2021). Here we show additional details of these three years by comparing minimum ozone profiles and the July&ndash;December 14&ndash;21 km column ozone time series. The 2019 anomalous vortex breakdown showed stratospheric temperatures began warming in early September leading to reduced ozone loss. The minimum total column ozone of 180 Dobson Units (DU) was observed on 24 September. This was followed by two stable and cold polar vortex years in 2020 and 2021 with total column ozone minimums at 104 DU (01 October) and 102 DU (07 October), respectively. These years also showed broad zero ozone (saturation loss) regions within the 14&ndash;21 km layer by the end of September which persisted into October. Validation of the ozonesonde observations is conducted through the ongoing comparison of total column ozone (TCO) measurements with the South Pole ground-based Dobson spectrophotometer. The ozonesondes show a constant positive offset of 2 &plusmn; 3 % (higher) than the Dobson following a thorough evaluation/homogenization of the ozonesonde record in 2018.</p

Evaluation of Native Earth System Model Output with ESMValTool v2.6.0

Earth system models (ESMs) are state-of-the-art climate models that allow numerical simulations of the past, present-day, and future climate. To extend our understanding of the Earth system and improve climate change projections, the complexity of ESMs heavily increased over the last decades. As a consequence, the amount and volume of data provided by ESMs has increased considerably. Innovative tools for a comprehensive model evaluation and analysis are required to assess the performance of these increasingly complex ESMs against observations or reanalyses. One of these tools is the Earth System Model Evaluation Tool (ESMValTool), a community diagnostic and performance metrics tool for the evaluation of ESMs. Input data for ESMValTool need to be formatted according to the CMOR (Climate Model Output Rewriter) standard, a process that is usually referred to as CMORization. While this is a quasi-standard for large model intercomparison projects like the Coupled Model Intercomparison Project (CMIP), this complicates the application of ESMValTool to non-CMOR-compliant climate model output. In this paper, we describe an extension of ESMValTool introduced in v2.6.0 that allows seamless reading and processing native climate model output, i.e., raw output directly produced by the climate model. This is achieved by an extension of ESMValTool’s preprocessing pipeline that performs a CMOR-like reformatting of the native model output during runtime. Thus, the rich collection of diagnostics provided by ESMValTool is now fully available for these models. For models that use unstructured grids, a further preprocessing step required to apply many common diagnostics is regridding to a regular latitude-longitude grid. Extensions to ESMValTool’s regridding functions described here allow for more flexible interpolation schemes that can be used on unstructured grids. Currently, ESMValTool supports nearest-neighbor, bilinear, and first-order conservative regridding from unstructured grids to regular grids. Example applications of this new native model support are the evaluation of new model setups against predecessor versions, assessing of the performance of different simulations against observations, CMORization of native model data for contributions to model intercomparison projects, and monitoring of running climate model simulations. For the latter, new general-purpose diagnostics have been added to ESMValTool that are able to plot a wide range of variable types. Currently, five climate models are supported: CESM2 (experimental; will be fully available in ESMValTool v2.7.0), EC-Earth3, EMAC, ICON, and IPSL-CM6. As the framework for the CMOR-like reformatting of native model output described here is implemented in a general way, support for other climate models can be easily added

Evaluating stratospheric ozone and water vapour changes in CMIP6 models from 1850 to 2100

Stratospheric ozone and water vapour are key components of the Earth system, and past and future changes to both have important impacts on global and regional climate. Here, we evaluate long-term changes in these species from the pre-industrial period (1850) to the end of the 21st century in Coupled Model Intercomparison Project phase 6 (CMIP6) models under a range of future emissions scenarios. There is good agreement between the CMIP multi-model mean and observations for total column ozone (TCO), although there is substantial variation between the individual CMIP6 models. For the CMIP6 multi-model mean, global mean TCO has increased from ∼300 DU in 1850 to ∼ 305 DU in 1960, before rapidly declining in the 1970s and 1980s following the use and emission of halogenated ozone-depleting substances (ODSs). TCO is projected to return to 1960s values by the middle of the 21st century under the SSP2-4.5, SSP3-7.0, SSP4-3.4, SSP4-6.0, and SSP5-8.5 scenarios, and under the SSP3-7.0 and SSP5-8.5 scenarios TCO values are projected to be ∼ 10 DU higher than the 1960s values by 2100. However, under the SSP1-1.9 and SSP1-1.6 scenarios, TCO is not projected to return to the 1960s values despite reductions in halogenated ODSs due to decreases in tropospheric ozone mixing ratios. This global pattern is similar to regional patterns, except in the tropics where TCO under most scenarios is not projected to return to 1960s values, either through reductions in tropospheric ozone under SSP1-1.9 and SSP1-2.6, or through reductions in lower stratospheric ozone resulting from an acceleration of the Brewer-Dobson circulation under other Shared Socioeconomic Pathways (SSPs). In contrast to TCO, there is poorer agreement between the CMIP6 multi-model mean and observed lower stratospheric water vapour mixing ratios, with the CMIP6 multi-model mean underestimating observed water vapour mixing ratios by ∼ 0.5 ppmv at 70 hPa. CMIP6 multi-model mean stratospheric water vapour mixing ratios in the tropical lower stratosphere have increased by ∼ 0.5 ppmv from the pre-industrial to the present-day period and are projected to increase further by the end of the 21st century. The largest increases (∼ 2 ppmv) are simulated under the future scenarios with the highest assumed forcing pathway (e.g. SSP5-8.5). Tropical lower stratospheric water vapour, and to a lesser extent TCO, shows large variations following explosive volcanic eruptions. © Author(s) 2021

Observation of large and all-season ozone losses over the tropics” [AIP Adv. 12, 075006 (2022)]

As discussed above, and supported by extensive literature, there is no robust, credible observational evidence for substantial ozone depletion (i.e., an “ozone hole”) in the tropics. It is well known that climatological total ozone in the tropics is much lower than that in the mid-latitudes (e.g., Sahai et al., 2000; Weber et al., 2022). Satellite and ozonesonde measurements indicate a 3%–5% per decade decline of tropical lower stratosphere ozone prior to 2000, far smaller than that reported by L2022. The stronger decline reported by L2022 is caused by inappropriate use of the gap-filled version of the TOST ozone dataset, which is based on sparse tropical ozone sondes before the 1990s. This misuse of data (TOST and total column ozone) shows the importance of collaboratively engaging with groups who obtain the measurements and create climatological datasets before performing such analyses. Furthermore, the study by L2022 has multiple flaws in its discussion of atmospheric chemistry and dynamics, particularly in the proposed, and previously refuted (see Sec. III A), cosmicray- driven electron induced (CRE) mechanism. Evidence for the occurrence of tropical stratospheric clouds, as needed for the tropical CRE mechanism, is lacking, nor do CFC-12 observations show signatures of depletion in the tropical lower stratosphere, which could be associated with dissociative electron attachment-induced loss of CFC-12 on particulate matter (i.e., the CRE mechanism). Finally, it is worth reiterating that the CRE mechanism is also not responsible for polar LS ozone depletion. Polar ozone loss can be well explained by the gas phase and heterogeneous chemistry, based on extensive observations and modeling studies documented in many thousands of scientific papers on the topic [e.g., see WMO (2018) and references therein], which is not acknowledged by L2022. L2022’s research paper is a severely flawed one. There is no tropical ozone hole, and the CRE mechanism does not explain observed changes in stratospheric ozone either in the polar regions or in the tropics