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The Model Intercomparison Project on the climatic response to Volcanic forcing (VolMIP) is a protocol-driven international initiative under the umbrella of the sixth phase of the Coupled Model Intercomparison Project (CMIP6) aiming at coordinating the activities of different Research Institutes involved in numerical climate modelling focused on a multi-model assessment of climate models' performance under strong volcanic forcing conditions. The main objective of the initiative is to assess to what extent responses of the coupled ocean-atmosphere system to the same applied strong volcanic forcing are robustly simulated across state-of-the-art coupled climate models and identify the causes that limit robust simulated behavior, especially differences in their treatment of physical processes. To this purpose, four Tier-1 (mandatory) experiments branched into two main sets, named “volc-pinatubo” and “volc-long” were defined, together with eight more lower-priority experiments. Six years since the definition of the VolMIP protocol (Zanchettin et al., 2016), ensemble simulations of most of the mandatory VolMIP experiments have been completed and made publicly available through the Earth System Grid Federation open platform, with the first VolMIP results being currently published and several analyses in progress. The long turnover time between the experiment design, the integration of the simulations and the analysis of the output motivates an assessment of the overall effectiveness of the VolMIP strategy, particularly in the light of a possible second phase of the initiative.In this contribution, we will illustrate the status of the initiative, highlight its major achievements and discuss its future perspective in the light of emergent scientific questions regarding volcanically forced climate variability.Zanchettin, D., Khodri, M., Timmreck, C., Toohey, M., Schmidt, A., Gerber, E. P., Hegerl, G., Robock, A., Pausata, F. S. R., Ball, W. T., Bauer, S. E., Bekki, S., Dhomse, S. S., LeGrande, A. N., Mann, G. W., Marshall, L., Mills, M., Marchand, M., Niemeier, U., Poulain, V., Rozanov, E., Rubino, A., Stenke, A., Tsigaridis, K., and Tummon, F.: The Model Intercomparison Project on the climatic response to Volcanic forcing (VolMIP): experimental design and forcing input data for CMIP6, Geosci. Model Dev., 9, 2701–2719, https://doi.org/10.5194/gmd-9-2701-2016, 2

The European Climate Prediction system (EUCP) project aimed to lay the foundation for a future regional climate prediction system for Europe. An important element of this is the role of narrative or storylines approaches in data production and scientific investigation, as well as a user product. We will present the results of our investigations which sought to understand the potential advantages and challenges in developing physically based climate storylines as part of a climate service by addressing the questionsWhat are climate storylines and where are they useful? How could storylines bring together various outputs of EUCP state-of-the-art climate science attempting to reduce uncertainty and complexity in climate projections, and seamlessly combine them with decadal predictions? What are the challenges of producing them as a service? The body of EUCP work included two case studies of co-producing storylines as a user product, revealing the potential usefulness for applications. These included the heritage and water supply management sectors which are at different stages of adaptation management. We also reflect on the potential of event-based future storylines: one using a convection-permitting model to provide attribution statements for the Copenhagen flooding event in July 2011 and another using large ensembles to construct storylines of the European summer 2018 drought under different pseudo-global warming. Novel scientific studies were also performed which could form the scientific building blocks of climate storylines including an algorithmic clustering approach and approaches to producing more realistic climate variability. Finally, we will present a tool for performing multiple lines of evidence assessments that could aid storylines development.

Skillful, reliable and seamless climate information for the next 1-40 years is crucial for policy- and other decision makers to develop suitable planning strategies. This poses a challenge for the scientific community, which is split up into the prediction community (developing initialized predictions up to multi-annual time scales, e.g. 10 years), and the climate projection community (providing long-term projections). As predictions are initialized with the observed climate state at the start of the integration, they are often more skillful for lead times of a few years (depending on variable and region) compared to uninitialized climate projections, which can provide information beyond 10 years. Thus, most useful climate information for the next 1-40 years would likely need to draw upon information from both sources. However, temporal merging from different sources is challenging, e.g., it can lead to discontinuities in the central estimates at the respective transition points, which pose problems for interpretation and communication alike.The aim of this study is to explore if skillful and seamless climate information can be provided by applying a model weighting scheme to initialized decadal predictions and projections. The model specific weights are based on the respective past model performance compared to observations. Whereas for climate projections each model is assigned a single weight, for initialized decadal predictions these weights are calculated for each forecast year separately. Here, we apply the weighting technique to CMIP6 decadal predictions and climate projections from 8 different models.

The central United States experienced the hottest summers of the twentieth century in 1934 and 1936, with over 40 heat wave days and maximum temperatures surpassing 44°C at some locations like Kansas and Oklahoma. In fact, as of 2019, the summer of 1936 is still the hottest on record. The heat waves coincided with the decade-long Dust Bowl drought, that caused wide-spread crop failures, dust storms that penetrated to New York and considerable out-migration. In a very-large ensemble regional modelling framework, we show that greenhouse gas increases slightly enhanced the frequency and duration of the Dust Bowl heat waves, and would strongly enhance similar heat waves in the present day under current, further elevated greenhouse gas levels. Specifically, present-day atmospheric greenhouse gas forcing would reduce the return period of a rare (less than once in a century) heat wave summer as observed in 1936 to about 1-in 40-years, with further contribution by sea surface warming. Here, we show that a key driver of this elevated heat wave risk is the reduction in evaporative cooling and increase in sensible heating during dry springs and summers. Hence, we conclude that a warmer world is creating the potential for future extreme heat in moisture-limited regions, with potentially very damaging impacts.

Water isotope-enabled coupled atmosphere–ocean climate models allow for exploration of the relative contributions to coral stable oxygen isotope (δ18Ocoral) variability arising from sea surface temperature (SST) and the isotopic composition of seawater (δ18Osw). The unforced behaviour of the isotope-enabled HadCM3 coupled general circulation model suggests that the extent to which inter-annual δ18Osw variability contributes to that in model δ18Ocoral is strongly spatially dependent, ranging from being negligible in the eastern equatorial Pacific to accounting for 50% of δ18Ocoral variance in parts of the western Pacific. In these latter cases, a significant component of the inter-annual δ18Osw variability is correlated to that in SST, meaning that local calibrations of the effective local δ18Ocoral–SST relationships are likely to be essential. Furthermore, the relationship between δ18Osw and SST can be non-linear, such that the model interpretation of central and western equatorial Pacific δ18Ocoral in the context of a linear dependence on SST alone leads to overestimation (by up to 20%) of the SST anomalies associated with large El Niño events. Intra-model evaluation of a salinity-based pseudo-coral approach shows that such an approach captures the first-order features of the model δ18Osw behaviour. However, the utility of the pseudo-corals is limited by the extent of spatial variability seen within the modelled slopes of the temporal salinity–δ18Osw relationship.