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To better understand possible reasons for the diverse modeling results and large discrepancies of the detected solar fingerprints, we took one step back and assessed the "initial" solar signals in the middle atmosphere based on large ensemble simulations with multiple climate models — FOCI, EMAC, and MPI-ESM-HR. Consistent with previous work, we find that the 11-year solar cycle signals in the short wave heating rate (SWHR) and ozone anomalies are robust and statistically significant in all three models. These "initial" solar cycle signals in SWHR, ozone, and temperature anomalies are sensitive to the strength of the solar forcing. Correlation coefficients of the solar cycle with the SWHR, ozone, and temperature anomalies linearly increase along with the enhancement of the solar cycle amplitude, and this reliance becomes more complex when the solar cycle amplitude exceeds a certain threshold. In addition, the cold bias in the tropical stratopause of EMAC dampens the subsequent results of the "initial" solar signal. The warm pole bias in MPI-ESM-HR leads to a weak polar night jet (PNJ), which may limit the top-down propagation of the initial solar signal. Although FOCI simulated a so-called top-down response as revealed in previous studies in a period with large solar cycle amplitudes, its warm bias in the tropical upper stratosphere results in a positive bias in PNJ and can lead to a "reversed" response in some extreme cases. We suggest a careful interpretation of the single model result and further re-examination of the solar signal based on more climate models.

We examine the impact of horizontal resolution and model time step on the climate of the OpenIFS version 43r3 atmospheric general circulation model. A series of simulations for the period 1979–2019 are conducted with various horizontal resolutions (i.e. ∼100, ∼50, and ∼25 km) while maintaining the same time step (i.e. 15 min) and using different time steps (i.e. 60, 30, and 15 min) at 100 km horizontal resolution. We find that the surface zonal wind bias is significantly reduced over certain regions such as the Southern Ocean and the Northern Hemisphere mid-latitudes and in tropical and subtropical regions at a high horizontal resolution (i.e. ∼25 km). Similar improvement is evident too when using a coarse-resolution model (∼100 km) with a smaller time step (i.e. 30 and 15 min). We also find improvements in Rossby wave amplitude and phase speed, as well as in weather regime patterns, when a smaller time step or higher horizontal resolution is used. The improvement in the wind bias when using the shorter time step is mostly due to an increase in shallow and mid-level convection that enhances vertical mixing in the lower troposphere. The enhanced mixing allows frictional effects to influence a deeper layer and reduces wind and wind speed throughout the troposphere. However, precipitation biases generally increase with higher horizontal resolutions or smaller time steps, whereas the surface air temperature bias exhibits a small improvement over North America and the eastern Eurasian continent. We argue that the bias improvement in the highest-horizontal-resolution (i.e. ∼25 km) configuration benefits from a combination of both the enhanced horizontal resolution and the shorter time step. In summary, we demonstrate that, by reducing the time step in the coarse-resolution (∼100 km) OpenIFS model, one can alleviate some climate biases at a lower cost than by increasing the horizontal resolution.

Key Points: - North Atlantic biases are alleviated by an eddying nested ocean configuration embedded in a global climate model, FOCI-VIKING10 - It is indicated that reduction of the North Atlantic biases could improve the representation of NAO sub-decadal (8 years) variability - For detecting weak external imprints with limited computational resources, an ensemble with a coarse-resolution model is favorable Increasing the horizontal resolution of an ocean model is frequently seen as a way to reduce the model biases in the North Atlantic, but we are often limited by computational resources. Here, a two-way nested ocean model configuration (VIKING10) that consists of a high-resolution (1/10°) component and covers the northern North Atlantic, is embedded in a 1/2° ocean grid as part of the global chemistry-climate model, FOCI (called FOCI-VIKING10). This configuration yields a significantly improved path of the North Atlantic current (NAC), which here reduces the North Atlantic cold bias by ∼50%. Compared with the coarse-resolution, non-eddying model, the improved thermal state of upper ocean layers and surface heat fluxes in a historical simulation based on FOCI-VIKING10 are beneficial for simulating the subdecadal North Atlantic Oscillation (NAO) variability (i.e., a period of 8 years). A northward drift of the NAO-forced ocean thermal anomalies as seen in observations and the eddying FOCI-VIKING10, provide a lagged ocean feedback to the NAO via changes in the net surface heat flux, leading to the NAO periodicity of 8 years. This lagged feedback and the 8 years variability of the NAO cannot be captured by the non-eddying standard FOCI historical simulation. Furthermore, the argumentative responses of the North Atlantic to the 11-year solar cycle are re-examined in this study. The reported solar-induced NAO-like responses are confirmed in the 9-member ensemble mean based on FOCI but with low robustness among individual members. A lagged NAO-like response is only found

El Niño–Southern Oscillation (ENSO) is a major source for teleconnections, including towards the tropical North Atlantic (TNA) region, whereby TNA sea surface temperatures (SSTs) are positively correlated with ENSO in boreal spring following an ENSO event. However, the Pacific–Atlantic connection can be impacted by different ENSO characteristics, such as the amplitude, location, and timing of Pacific SST anomalies (SSTAs). Indeed, the TNA SSTAs may respond nonlinearly to strong and extreme El Niño events. However, observational data for the number of extreme ENSO events remain limited, restricting our ability to investigate the influence of observed extreme ENSO events. To overcome this issue and to further evaluate the nonlinearity of the TNA SSTA response, two coupled climate models are used, namely the Community Earth System Model version 1 – Whole Atmosphere Community Climate Model (CESM-WACCM) and the Flexible Ocean and Climate Infrastructure version 1 (FOCI). In both models the TNA SSTAs respond linearly to ENSO during extreme El Niño events but nonlinearly to extreme La Niña events for CESM-WACCM. We investigate differences by using indices for all major mechanisms that connect ENSO to the TNA and compare them with reanalysis. CESM-WACCM and FOCI overall represent the teleconnection well, including that the tropical and extratropical pathways are similar to observations. Our results also show that a large portion of the nonlinearity during La Niña is explained by the interaction between Pacific SSTAs and the overlying upper-level divergence.

Machine learning (ML) and in particular deep learning (DL) methods push state-of-the-art solutions for many hard problems, for example, image classification, speech recognition, or time series forecasting. In the domain of climate science, ML and DL are known to be effective for identifying causally linked modes of climate variability as key to understand the climate system and to improve the predictive skills of forecast systems. To attribute climate events in a data-driven way, we need sufficient training data, which is often limited for real-world measurements. The data science community provides standard data sets for many applications. As a new data set, we introduce a consistent and comprehensive collection of climate indices typically used to describe Earth System dynamics. Therefore, we use 1000-year control simulations from Earth System Models. The data set is provided as an open-source framework that can be extended and customized to individual needs. It allows users to develop new ML methodologies and to compare results to existing methods and models as benchmark. For example, we use the data set to predict rainfall in the African Sahel region and El Niño Southern Oscillation with various ML models. Our aim is to build a bridge between the data science community and researchers and practitioners from the domain of climate science to jointly improve our understanding of the climate system.

We examine the impact of horizontal resolution and model time step on climate of the OpenIFS version 43R3 atmosphere general circulation model. A series of simulations for the period 1979–2019 are conducted with various horizontal resolutions (i.e., ~100, ~50, and ~25 km) while maintaining the same time step (i.e., 15 minutes) and using different time steps (i.e., 60, 30 and 15 minutes) at 100 km horizontal resolution. We find that the surface zonal wind bias reduces significantly over certain regions such as the Southern Ocean, the Northern Hemisphere mid-latitudes, and in tropical and subtropical regions at high horizontal resolution (i.e., ~25 km). Similar improvement is evident too when using a coarse resolution model (~100 km) with a smaller time step (i.e., 30 and 15 minutes). We also find improvements in Rossby wave amplitude and phase speed as well as weather regime patterns when a smaller time step or higher horizontal resolution is used. The improvement in the wind bias when using the shorter time step is mostly due to an increase in shallow and mid-level convection that enhances vertical mixing in the lower troposphere. The enhanced mixing allows frictional effects to influence a deeper layer and reduces wind and wind speed throughout the troposphere. However, precipitation biases generally increase with higher horizontal resolution or smaller time step, whereas the surface-air temperature bias exhibits a small improvement over North America and the Eastern Eurasian continent. We argue that the bias improvement in the highest horizontal resolution (i.e., ~25 km) configuration benefits from a combination of both the enhanced horizontal resolution and the shorter time step. In summary, we demonstrate that by reducing the time step in the OpenIFS model, one can alleviate some climate biases at a lower cost than by increasing the horizontal resolution.

The recent severe European summer heat waves of 2015 and 2018 co-occurred with cold subpolar North Atlantic (NA) sea surface temperatures (SSTs). However, a significant connection between this oceanic state and European heat waves was not yet established. We performed two AMIP-like model experiments: (a) employing daily 2018 SSTs as observed and (b) applying a novel approach to remove the negative NA SST anomaly, while keeping SST daily and small-scale variability. Comparing these experiments, we find that cold subpolar NA SSTs significantly increase heat wave duration and magnitude downstream over the European continent. Surface temperature and circulation anomalies are connected by the upper-tropospheric summer wave pattern of meridional winds over the North Atlantic European sector, which is enhanced with cold NA SSTs. Our results highlight the relevance of the subpolar NA region for European summer conditions, a region that is marked by large biases in current coupled climate model simulations. Key Points: - Model study designed to investigate the ocean impact on European heat waves by prescribing observed and realistic ocean surface conditions - Cold subpolar North Atlantic sea surface temperatures significantly enhance heat wave intensity and duration over the European continent - North Atlantic ocean and European surface temperature and circulation anomalies are bridged by the upper-tropospheric summer mean wave

The consideration of marine biogeochemistry is essential for simulating the carbon cycle in an Earth system model. Here we present the implementation and evaluation of a marine biogeochemical model, Model of Oceanic Pelagic Stoichiometry (MOPS) in the Flexible Ocean and Climate Infrastructure (FOCI) climate model. FOCI-MOPS enables the simulation of marine biological processes, the marine carbon, nitrogen and oxygen cycles, air-sea gas exchange of CO2 and O2, and simulations with prescribed atmospheric CO2 or CO2 emissions. A series of experiments covering the historical period (1850–2014) were performed following the DECK (Diagnostic, Evaluation and Characterization of Klima) and CMIP6 (Coupled Model Intercomparison Project 6) protocols. Overall, modelled biogeochemical tracer distributions and fluxes, as well as transient evolution in surface air temperature, air-sea CO2 fluxes, and changes of ocean carbon and heat, are in good agreement with observations. Modelled inorganic and organic tracer distributions are quantitatively evaluated by statistically-derived metrics. Results of the FOCI-MOPS model, also including sea surface temperature, surface pH, oxygen (100–600 m), nitrate (0–100 m), and primary production, are within the range of other CMIP6 model results. Overall, the evaluation of FOCI-MOPS indicates its suitability for Earth climate system simulations

Ridging South Atlantic Anticyclones contribute an important amount of precipitation over South Africa. Here, we use a global coupled climate model and the ERA5 reanalysis to separate for the first time ridging highs (RHs) based on whether they occur together with Rossby wave breaking (RWB) or not. We show that the former type of RHs are associated with more precipitation than the latter type. The mean sea level pressure anomalies caused by the two types of RHs are characterized by distinct patterns, leading to differences in the flow of moisture-laden air onto land. We additionally find that RWB mediates the effect of climate change on RHs during the twenty-first century. Consequently, RHs occurring without RWB exhibit little change, while those occurring with RWB contribute more precipitation over the southern and less precipitation over the northeastern South Africa in the future. Key Points: - Ridging South Atlantic Anticyclones are accompanied by Rossby wave breaking (RWB) aloft in 44% of the cases - Ridging highs that are accompanied by RWB lead to more precipitation over South Africa than those that are not - Ridging highs bring more precipitation over the southern and less precipitation over the northeastern part of South Africa in the future

Changes in stratospheric ozone concentrations and increasing concentrations of greenhouse gases (GHGs) alter the temperature structure of the atmosphere and drive changes in the atmospheric and oceanic circulation. We systematically investigate the impacts of ozone recovery and increasing GHGs on the atmospheric and oceanic circulation in the Southern Hemisphere during the twenty-first century using a unique coupled ocean–atmosphere climate model with interactive ozone chemistry and enhanced oceanic resolution. We use the high-emission scenario SSP5-8.5 for GHGs under which the springtime Antarctic total column ozone returns to 1980s levels by 2048 in our model, warming the lower stratosphere and strengthening the stratospheric westerly winds. We perform a spatial analysis and show for the first time that the austral spring stratospheric response to GHGs exhibits a marked planetary wavenumber 1 (PW1) pattern, which reinforces the response to ozone recovery over the Western Hemisphere and weakens it over the Eastern Hemisphere. These changes, which imply an eastward phase shift in the PW1, largely cancel out in the zonal mean. The Southern Hemisphere residual circulation strengthens during most of the year due to the increase in GHGs and weakens in spring due to ozone recovery. However, we find that in November the GHGs also drive a weakening of the residual circulation, reinforcing the effect of ozone recovery, which represents another novel result. At the surface, the westerly winds weaken and shift equatorward due to ozone recovery, driving a weak decrease in the transport of the Antarctic Circumpolar Current and in the Agulhas leakage and a cooling of the upper ocean, which is most pronounced in the latitudinal band 35–45∘ S. The increasing GHGs drive changes in the opposite direction that overwhelm the ozone effect. The total changes at the surface and in the oceanic circulation are nevertheless weaker in the presence of ozone recovery than those induced by GHGs