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Observational records are more often than not influenced by residual non-climatic factors which must be detected and adjusted for prior to their usage. In this work, we present a novel approach, named Radiosounding HARMonization (RHARM), providing a homogenized data set of temperature, humidity and wind profiles along with an estimation of the measurement uncertainties for 697 radiosounding stations globally. The RHARM method has been used to adjust twice daily (0000 and 1200 UTC) radiosonde data holdings at 16 pressure levels in the range 1,000–10 hPa, from 1978 to present, provided by the Integrated Global Radiosonde Archive. Relative humidity (RH) data are limited to 250 hPa. The applied adjustments are interpolated to all reported levels. RHARM is the first data set to provide homogenized time series with an estimation of the observational uncertainty at each sounding pressure level. By construction, RHARM adjusted fields are not affected by cross-contamination of biases across stations and are fully independent of reanalysis data. Analysis of trends for temperature, RH and winds highlights increased geographical coherency of trends over 1978–2000 globally, but especially in the Northern Hemisphere and South America. RHARM shows warming trends of 0.39 K/decade at 300 hPa in the Northern Hemisphere and of 0.25 K/ decade in the tropics. The RHARM adjustments also reduce differences with the European Centre for Medium-Range Weather Forecast ERA5 reanalysis, with the strongest effect in the Northern Hemisphere for temperature and relative humidity. For wind speed, the comparison indicates a good agreement with ERA5 in the troposphere.

The RHARM (Radiosounding HARMonization) algorithm is the first to provide homogenized radiosonde-based records of temperature, relative humidity and wind profiles since 1978, alongside an estimatio...

The Quasi-biennial Oscillation (QBO) dominates the interannual variability of the tropical stratosphere and influences other regions of the atmosphere. The high predictability of the QBO implies that its teleconnections could lead to increased skill of seasonal and decadal forecasts provided the relevant mechanisms are accurately represented in models. Here modelling and sampling uncertainties of QBO teleconnections are examined using a multi-model ensemble of QBO-resolving atmospheric general circulation models that have carried out a set of coordinated experiments as part of the Stratosphere-troposphere Processes And their Role in Climate (SPARC) QBO initiative (QBOi). During Northern Hemisphere winter, the stratospheric polar vortex in most of these models strengthens when the QBO near 50 hPa is westerly and weakens when it is easterly, consistent with, but weaker than, the observed response. These weak responses are likely due to model errors, such as systematically weak QBO amplitudes near 50 hPa, affecting the teleconnection. The teleconnection to the North Atlantic Oscillation is less well captured overall, but of similar strength to the observed signal in the few models that do show it. The models do not show clear evidence of a QBO teleconnection to the Northern Hemisphere Pacific-sector subtropical jet. We acknowledge the UK's Centre for Environmental Data Analysis (CEDA) for hosting the QBOi data archive. This work was supported by the National Center for Atmospheric Research, which is a major facility sponsored by the National Science Foundation under Cooperative Agreement no. 1852977. Portions of this study were supported by the Regional and Global Model Analysis (RGMA) component of the Earth and Environmental System Modeling Program of the U.S. Department of Energy's Office of Biological & Environmental Research (BER) via National Science Foundation IA 1844590. NB was supported by the Met Office Hadley Centre Programme funded by BEIS and Defra. SO and LG were supported by the National Centre for Atmospheric Science and the Natural Environment Research Council (NE/P006779/1, NE/N018001/1). FL and SO were supported by the JPI-Climate/Belmont Forum 423 project GOTHAM (ANR-15-JCLI-0004-01, NERC NE/P006779/1). CC and FS were supported by the Copernicus Climate Change Service, funded by the EU and implemented by ECMWF. HN was supported by the Environment Research and Technology Development Fund (S-12) of the Environmental Restoration and Conservation Agency of Japan and by Grant-in-Aid (JP18K03748, JP20H05171) for Science Research (KAKENHI) from the Ministry of Education, Culture, Sports, Science, and Technology of Japan. For the EMAC simulations, PB, TK, and SV acknowledge support by the state of Baden-Württemberg through bwHPC. YK was supported by the Japan Society for Promotion of Science (JSPS) KAKENHI (grant nos. JP15KK0178, JP17K18816, JP18H01286 and 19H05702) and by the Environment Research and Technology Development Fund (JPMEERF20192004) of the Environmental Restoration and Conservation Agency of Japan. YK and KH were supported by the Japan Agency for Marine-Earth Science and Technology (JAMSTEC) through its sponsorship of research at the International Pacific Research Center. SW and YK were partly supported by the “Integrated Research Program for Advancing Climate Models (TOUGOU program)” from the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan. The Earth Simulator was used for MIROC-ESM and MIROC-AGCM-LL simulations. We acknowledge the scientific guidance of the World Climate Research Programme (WCRP) for helping motivate this work, coordinated under the framework of the Stratosphere-troposphere Processes And their Role in Climate (SPARC) QBO initiative (QBOi) led by JA, NB, KH and SO. Peer Reviewed "Article signat per 29 autors/es: James A. Anstey, Isla R. Simpson, Jadwiga H. Richter, Hiroaki Naoe, Masakazu Taguchi, Federico Serva, Lesley J. Gray, Neal Butchart, Kevin Hamilton, Scott Osprey, Omar Bellprat, Peter Braesicke, Andrew C. Bushell, Chiara Cagnazzo, Chih-Chieh Chen, Hye-Yeong Chun, Rolando R. Garcia, Laura Holt, Yoshio Kawatani, Tobias Kerzenmacher, Young-Ha Kim, Francois Lott, Charles McLandress, John Scinocca, Timothy N. Stockdale, Stefan Versick, Shingo Watanabe, Kohei Yoshida, Seiji Yukimoto"

The Earth System Model EC-Earth3 for contributions to CMIP6 is documented here, with its flexible coupling framework, major model configurations, a methodology for ensuring the simulations are comparable across different HPC systems, and with the physical performance of base configurations over the historical period. The variety of possible configurations and sub-models reflects the broad interests in the EC-Earth community. EC-Earth3 key performance metrics demonstrate physical behaviour and biases well within the frame known from recent CMIP models. With improved physical and dynamic features, new ESM components, community tools, and largely improved physical performance compared to the CMIP5 version, EC-Earth3 represents a clear step forward for the only European community ESM. We demonstrate here that EC-Earth3 is suited for a range of tasks in CMIP6 and beyond.

Several studies investigated the possible impacts of the restriction measures related to the containment of the spread of the COrona VIrus Disease (COVID-19) to atmospheric ozone (O3) at global, regional, and local scales during 2020. O3 is a secondary pollutant with adverse effects on population health and ecosystems and with negative impacts on climate, acting as greenhouse gas. Most of these studies focused on spring 2020 (i.e. March–May) and on observations in the planetary boundary layer (PBL), mostly in the vicinity of urban agglomerates. Here, we analyzed the variability of O3 above the PBL of northern Italy in 2020 by using continuous observations carried out at a high mountain WMO/GAW global station in Italy (Mt. Cimone–CMN; 44°12' N, 10°42' E, 2165 m a.s.l.). Low O3 monthly anomalies were observed during spring (MAM) and summer (JJA), when periods of low O3 intertwined with periods with higher O3, within climatological ranges. A similar variability was observed for O3 precursors like NO2 and 15 anthropogenic non-methane volatile organic carbons, but the systematic O3 anomalies were not reflected in these variables. The analysis of meteorological variables and diel O3 cycles did not suggest major changes in the vertical transport related to the thermal circulation system in the mountain area. The analysis of five days back-trajectories suggested that the observed O3 anomalies cannot be explained by differences in the synoptic-scale circulation with respect to the previous years alone. On the other hand, the characterization of two transport patterns (i.e. air masses from the regional PBL or from the free troposphere) and the analysis of back-trajectories suggested an important contribution of transport from the continental PBL during the periods with the lowest O3 at CMN. When proxies of air mass transport from the regional PBL are considered, a lower NOx content was pointed out with respect to the previous years, suggesting a lower O3 production in a NOx-limited atmosphere. Our study suggested for the first time that, during MAM and JJA 2020, the reduced anthropogenic emissions related to the COVID-19 restrictions lowered the amount of this short-lived climate forcer/pollutant at remote locations above the PBL over northern Italy. This work suggests the importance of limiting anthropogenic precursor emissions for decreasing the O3 amount at remote locations and in upper atmospheric layers., Environmental Research Letters, 16 (7), ISSN:1748-9326, ISSN:1748-9318

Observational records are essential for assessing long-term changes in our climate. However, these records are more often than not influenced by residual non‐climatic factors which must be detected and adjusted prior to their usage. Ideally, measurement uncertainties should be properly quantified and validated. In the context of the Copernicus Climate Change Service (C3S), a novel approach, named RHARM (Radiosounding HARMonization), has been developed to provide a harmonized dataset of temperature, humidity and wind profiles along with an estimation of the measurement uncertainties for about 650 radiosounding stations globally. The RHARM method has been applied to IGRA daily (0000 and 1200 UTC) radiosonde data holdings on 16 standard pressure levels (from 1000 to 10 hPa) from 1978 to present. Relative humidity adjustment and data provision has been limited to 250 hPa owing to pervasive issues on sensors' performance in the upper troposphere and lower stratosphere. The applied adjustments are interpolated to all reported significant levels to retain information content contained within each individual ascent profile. Each historical station time series is harmonized using two distinct methods. Firstly, the most recent period of the records when modern radiosonde models have been in operation at each station (typically starting between 2004 and 2010 but varying on a station-by-station basis) are post-processed and adjusted using reference datasets from the GCOS Reference Upper Air Network (GRUAN) and from the 2010 WMO/CIMO (World Meteorological Organization/Commission for Instruments and Methods of Observation) radiosonde intercomparison. Subsequently, at each mandatory pressure level, the remaining historical data are scanned backward in time to detect structural breaks due to prolonged systematic effects in the measurements and then adjusted to homogenize the time series. This paper describes the dataset portion related to the adjustment of post-2004 measurements only. A step-by-step description of the algorithm is reported and comparisons with GRUAN and atmospheric reanalysis data for temperature and relative humidity data are discussed. The evaluation shows that the strongest benefit of RHARM compared to existing products is related to the substantive adjustments applied to relative humidity time series for values below 15 % and above 55 % as well as to the provision of the uncertainties for all variables. Uncertainties have been validated using the ECMWF reanalysis short-range forecast outputs. The RHARM algorithm is the first to provide homogenized time series of temperature, relative humidity and wind profiles alongside an estimation of the observational uncertainty for each single observation at each pressure level. A subset of RHARM dataisavailable at https://doi.org/10.5281/zenodo.3973353 (Madonnaet al., 2020a)

The equatorial Quasi-Biennial Oscillation (QBO) and the El Niño-Southern Oscillation (ENSO) are major patterns of climate variability. Mutual interactions between these two modes have been highlighted in the observational record, but this has not been much tested using climate model simulations. In observations, the amplitude is larger during cold and smaller during warm events, while the descent rate is slower during cold and faster during warm events. Here we discuss how climate models represent this relationship, in terms of the changes of the QBO properties. The results for a multi-model ensemble, with atmosphere-only and ocean-atmosphere simulations, are discussed. The phase alignment of the QBO after the 1997/98 warm ENSO, already documented in previous works, is also present in a large ensemble of uncoupled experiments. It is found that a high horizontal resolution is needed to realistically reproduce the observed modulation of the QBO descent rate under strong ENSO events. The QBO amplitude response is instead weak at any horizontal resolution. Robust changes emerging in the projections and aspects of the modelled stratosphere-troposphere coupling in the tropics are presented.

The Quasi‐Biennial Oscillation initiative (QBOi) is a model intercomparison programme that specifically targets simulation of the QBO in current global climate models. Eleven of the models or model versions that participated in a QBOi intercomparison study have upper boundaries in or above the mesosphere and therefore simulate the region where the stratopause semiannual oscillation (SAO) is the dominant mode of variability of zonal winds in the tropical upper stratosphere. Comparisons of the SAO simulations in these models are presented here. These show that the model simulations of the amplitudes and phases of the SAO in zonal‐mean zonal wind near the stratopause agree well with the information derived from available observations. However, most of the models simulate time‐average zonal winds that are more westward than determined from observations, in some cases by several tens of m·s$^{–1}$. Validation of wave activity in the models is hampered by the limited observations of tropical waves in the upper stratosphere but suggests a deficit of eastward forcing either by large‐scale waves, such as Kelvin waves, or by gravity waves.

We compare the response of the Quasi‐Biennial Oscillation (QBO) to a warming climate in eleven atmosphere general circulation models that performed time‐slice simulations for present‐day, doubled, and quadrupled CO2 climates. No consistency was found among the models for the QBO period response, with the period decreasing by 8 months in some models and lengthening by up to 13 months in others in the doubled CO2 simulations. In the quadrupled CO2 simulations, a reduction in QBO period of 14 months was found in some models, whereas in several others the tropical oscillation no longer resembled the present‐day QBO, although it could still be identified in the deseasonalized zonal mean zonal wind timeseries. In contrast, all the models projected a decrease in the QBO amplitude in a warmer climate with the largest relative decrease near 60 hPa. In simulations with doubled and quadrupled CO2, the multi‐model mean QBO amplitudes decreased by 36 and 51%, respectively. Across the models the differences in the QBO period response were most strongly related to how the gravity wave momentum flux entering the stratosphere and tropical vertical residual velocity responded to the increases in CO2 amounts. Likewise it was found that the robust decrease in QBO amplitudes was correlated across the models to changes in vertical residual velocity, parametrized gravity wave momentum fluxes, and to some degree the resolved upward wave flux. We argue that uncertainty in the representation of the parameterized gravity waves is the most likely cause of the spread among the eleven models in the QBO's response to climate change.

The Quasi‐Biennial Oscillation initiative (QBOi) is a model intercomparison programme that specifically targets simulation of the QBO in current global climate models. Eleven of the models or model versions that participated in a QBOi intercomparison study have upper boundaries in or above the mesosphere and therefore simulate the region where the stratopause semiannual oscillation (SAO) is the dominant mode of variability of zonal winds in the tropical upper stratosphere. Comparisons of the SAO simulations in these models are presented here. These show that the model simulations of the amplitudes and phases of the SAO in zonal‐mean zonal wind near the stratopause agree well with the information derived from available observations. However, most of the models simulate time‐average zonal winds that are more westward than determined from observations, in some cases by several tens of m·s–1. Validation of wave activity in the models is hampered by the limited observations of tropical waves in the upper stratosphere but suggests a deficit of eastward forcing either by large‐scale waves, such as Kelvin waves, or by gravity waves.

The general circulation of the middle atmosphere, particularly of the mesosphere, is strongly dependent on the forcing arising from gravity wave processes. Their sources in the troposphere are both orographic and nonorographic, the latter being strongly intermittent. In climate models, the effects of gravity waves need to be parameterized, often assuming that their properties are constant. In this work we focus on the changes of the middle atmosphere due to the introduction of intermittency in a parameterization of nonorographic gravity waves, using a stochastic version of the Hines scheme. The stochastic approach is tailored to the diagnosed sensitivity of the model to this forcing, and peculiar changes emerge even if a relatively small amount of intermittency is prescribed. We analyze in detail the changes of the stratospheric dynamics in the tropical region and the global circulation of the middle atmosphere, when the stochastic parameterization is employed in place of the deterministic one. The mean state and variability of the model, realistic also in the default version, are preserved when stochasticity is added. Significant changes are observed in the mesosphere due to an enhanced poleward transport, leading to warming in the winter season. While there are some improvements of the mean state, the interannual variability is not significantly affected in the extratropics. The impacts on the simulated equatorial stratosphere are evident, as the stochasticity reduces the overall period of the quasi-biennial oscillation but also leads to a net reduction of the variability between cycles. ©2018. The Authors.

The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool designed to improve comprehensive and routine evaluation of Earth System Models (ESMs) participating in the Coupled Model Intercomparison Project (CMIP). It has undergone rapid development since the first release in 2016 and is now a well-tested tool that provides end-to-end provenance tracking to ensure reproducibility. It consists of an easy-to-install, well documented Python package providing the core functionalities (ESMValCore) that performs common pre-processing operations and a diagnostic part that includes tailored diagnostics and performance metrics for specific scientific applications. Here we describe large-scale diagnostics of the second major release of the tool that supports the evaluation of ESMs participating in CMIP Phase 6 (CMIP6). ESMValTool v2.0 includes a large collection of diagnostics and performance metrics for atmospheric, oceanic, and terrestrial variables for the mean state, trends, and variability. ESMValTool v2.0 also successfully reproduces figures from the evaluation and projections chapters of the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) and incorporates updates from targeted analysis packages, such as the NCAR Climate Variability Diagnostics Package for the evaluation of modes of variability the Thermodynamic Diagnostic Tool (TheDiaTo) to evaluate the energetics of the climate system, as well as parts of AutoAssess that contains a mix of top-down performance metrics. The tool has been fully integrated into the Earth System Grid Federation (ESGF) infrastructure at the Deutsches Klima Rechenzentrum (DKRZ) to provide evaluation results from CMIP6 model simulations shortly after the output is published to the CMIP archive. A result browser has been implemented that enables advanced monitoring of the evaluation results by a broad user community at much faster timescales than what was possible in CMIP5.

If climate services are to lead to effective use of climate information in decision-making to enable the transition to a climate-smart, climate-ready world, then the question of trust in the products and services is of paramount importance. The Copernicus Climate Change Service (C3S) has been actively grappling with how to build such trust: provision of demonstrably independent assessments of the quality of products, which was deemed an important element in such trust-building processes. C3S provides access to essential climate variables (ECVs) from multiple sources to a broad set of users ranging from scientists to private companies and decision-makers. Here we outline the approach undertaken to coherently assess the quality of a suite of observation- and reanalysis-based ECV products covering the atmosphere, ocean, land, and cryosphere. The assessment is based on four pillars: basic data checks, maturity of the datasets, fitness for purpose (scientific use cases and climate studies), and guidance to users. It is undertaken independently by scientific experts and presented alongside the datasets in a fully traceable, replicable, and transparent manner. The methodology deployed is detailed, and example assessments are given. These independent scientific quality assessments are intended to guide users to ensure they use tools and datasets that are fit for purpose to answer their specific needs rather than simply use the first product they alight on. This is the first such effort to develop and apply an assessment framework consistently to all ECVs. Lessons learned and future perspectives are outlined to potentially improve future assessment activities and thus climate services., Bulletin of the American Meteorological Society, 103 (9), ISSN:0003-0007, ISSN:1520-0477