Scenario-based approaches, including the concept of storylines, were introduced in climate science to provide unity of discourse, integrate the physical and socioeconomic components of phenomena, and make climate evolution more tangible. The use of storylines by multiple scholar communities and the novelty of some of its applications renders the concept ambiguous nonetheless, because the term hides behind a wide range of understandings and methodologies that often collide ontologically and epistemically. This semi-systematic literature review identifies three approaches that use storylines as a keystone concept: scenarios –familiar for their use in IPCC reports, discourse-analytical approaches, and physical climate storylines. After screening all peer-reviewed articles that mention climate and storylines, we selected 270 articles, with 158, 55, and 57 in each category. Results indicate that each community works with different methods and understandings. Moreover, these approaches have received criticism in their assembly of storylines: either for lacking explicitness or for the homogeneity of expertise involved. We propose that cross-pollination amongst the approaches could improve the goal to support climate action. Good practices are the involvement of a broader range of disciplines, use of mixed-methods, storyline assessment against a wider set of quality criteria, and stakeholder participation in key stages of the process.

How to cite: Baulenas, E., Versteeg, G., Terrado, M., Mindlin, J., and Bojovic, D.: Assembling the climate story: use of storyline approaches in climate-related science, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1417, https://doi.org/10.5194/egusphere-egu23-1417, 2023.

The heatwave of 2003, the flooding of 2005, the drought of 2018, or the snow-scarce winter of 2019/2020 are vivid examples of extreme weather events affecting Switzerland. The CH2018 climate scenarios for Switzerland show that such kind of events will become more intense in the future, depending on the future emission pathway and the considered time horizon. So far, CH2018-based information is typically communicated as changes in the mean or extremes of a climate variable, including the uncertainty of these changes. Presenting information in this manner is scientifically correct, but not tangible for everyone. Interested stakeholders often have difficulties to imagine what the future climate, and in particular how future extreme conditions might look like.

To enhance the uptake of CH2018 scenario information by stakeholders we here present a newly developed method to create similarity-based storylines and apply it to a historic heatwave event. The resulting storylines show local impacts in four different sectors at individual locations in Switzerland. In each case, the historical record-breaking heat summer of 2003 is related to a future extreme summer represented by the CH2018 scenarios assuming the RCP8.5 emission scenario. Specific indicators help to create unique heat-related storylines. In the alpine setting of Davos, the number of dry hiking weather days increases in a future extreme summer to the delight of hikers and alpine summer tourism. In contrast, the southern cities of Sion and Geneva face less favorable prospects. The fire danger massively increases in dry locations such as Sion. The population in Geneva will encounter an even stronger heat exposure compared to 2003. Finally, the living conditions for a potent agricultural pest considerably improve throughout Switzerland, threatening agriculture during a similar future extreme.

The new similarity-based storylines facilitate the understanding of locally relevant processes linked to climate extremes, provide an improved insight into how extreme events quantitatively change with climate change, give examples of possible impacts, and finally try to stimulate public awareness for possible consequences of future climate change.

How to cite: Kotlarski, S., Mastai, A., Wehrli, K., and Fischer, E. M.: Similarity-based storylines of future climate extremes in Switzerland, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5133, https://doi.org/10.5194/egusphere-egu23-5133, 2023.

While polar amplification has been established as a defining feature of Arctic climate change, poor quantitative agreement among models remains when assessing its magnitude and spatial pattern. Here, we apply the storyline approach to a large ensemble of CMIP6 models, with the aim of distilling the wide spread in model predictions into four physically plausible outcomes of Arctic climate change. This is made possible by leveraging strong covariability in the climate system: specifically, we find that differences in Barents Sea warming and lower tropospheric warming among CMIP6 models explain most of the intermodel variability in pan-Arctic surface climate response to global warming. Based on this novel finding, we compare regional disparities in climate change across the four storylines, and discuss potential implications for modeling climate change impacts on ecosystems and human activities. 

How to cite: Levine, X., Williams, R., Seland Graff, L., and Mooney, P.: Devising storylines of Arctic climate change from a large ensemble of CMIP6 models, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7398, https://doi.org/10.5194/egusphere-egu23-7398, 2023.

Extreme precipitation events cause major ecological and societal hazards (e.g. river flooding and landslides). Aggravatingly, climate change will likely exacerbate extreme precipitation events on a global scale. Scientifically even more concerning, however, are remaining major uncertainties in projections of regional extreme precipitation events, which hamper and complicate local adaptation measurements around the globe. The arguably largest source of these remaining uncertainties stems from climate models feuding about the dynamic evolution of atmospheric circulation; atmospheric circulation governs moisture transport and profoundly affects the location of extreme precipitation events as well as their severity around the globe. We exploit this feud among climate models to narrow down the arguably largest source of uncertainttiesin projections of extreme precipitation events through a storyline approach. For a given location, the approach: (i) unravels the properties of driving weather systems that repeatedly gave rise to extreme precipitation events in the past, (ii) assesses the fidelity of a large suite of models, participating in the Coupled Model Intercomparison Project 6 (CMIP6), in representing these driving weather systems in historical simulations (1950-2015), and (iii) constrains regional projections of extreme precipitation events based on the ascertained fidelity of models.

Here, we present such a storyline approach that dynamically constrains regional projections of extreme precipitation events. Accompanying the outline of the approach, we identify regions that are particularly plagued by uncertain projections of extreme precipitation events and showcase for a subset of these regions how to track down weather systems that repeatedly gave rise to extreme precipitation events in the past.

How to cite: Pieper, P., Zhu, D., Fischer, E., and Pfahl, S.: Dynamical Constraints on regional Projections of Extreme Precipitation Events, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8561, https://doi.org/10.5194/egusphere-egu23-8561, 2023.

Siberia experienced an exceptionally warm first half of 2020, with temperatures peaking on 20th June, when the weather station at Verkhoyansk registered 38ºC – the highest-ever temperature recorded north of the Arctic Circle. This event led to a state of emergency declaration due to a wide range of natural and human disasters, including permafrost collapse or wildfires. Several previous attribution studies have found anomalous synoptic atmospheric circulation and human-caused climate change as major drivers of this event. However, it remains unclear how such an event would unfold in warmer climates.

In this work, we have constructed analogues of this extreme event in past and future climates, so-called “storylines”, employing spectral nudging experiments using the coupled climate model AWI-CM1. In these simulations, large-scale free-troposphere winds are constrained toward ERA5 data, and the model is run for different boundary and initial conditions (pre-industrial, present, +2K, +3K, +4K climates). By doing so, this approach focuses on the less uncertain thermodynamic influence of climate on extreme events, constraining the much more uncertain dynamical changes.

Our present-climate simulations realistically reproduce the observed Siberian heatwave and the exceptionally warm conditions before the event. When the different background climates are considered, on the one hand, a robust global warming amplification is obtained until spring. On the other hand, a future global warming dampening or even local cooling is observed in phase with the heatwave peak. We examine the mechanisms that damp warming during the heatwave analogue, especially changes in soil moisture and radiative fluxes. 

How to cite: Sánchez Benítez, A., Athanase, M., Jung, T., Pithan, F., and Goessling, H.: Storyline simulations suggest dampening of 2020 Siberian heatwave analogues in warmer climates, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9368, https://doi.org/10.5194/egusphere-egu23-9368, 2023.

The manifestation of regional changes in climate at high latitudes is notoriously uncertain according to climate models, aside from the expected polar amplification of the global warming trend. This poses a particular issue for policymakers in designing targeted adaptation and mitigation strategies, in limiting the impact of human-induced climate change. The leading mode of uncertainty arises from the unknown response of the atmospheric circulation to global warming, resulting from inconsistencies in the model representation of key physical processes, which are typically parameterised as they operate on sub-grid spatial scales. 

Using the latest suite of state-of-the-art climate models as part of the sixth phase of the Coupled Model Intercomparison Project (CMIP6), a storyline approach is adopted to derive physically plausible scenarios of climate change over Antarctica and adjacent regions of the Southern Ocean for the end-of-the-century (2070-2099), according to both emission scenarios SSP3-7.0 and SSP5-8.5. We identify two robust features of climate change simulated across all models known to lead to a strengthening and poleward displacement of the eddy-driven mid-latitude jet: (1) the decline in Southern Hemisphere sea ice extent and (2) the strengthening of the wintertime stratospheric polar vortex and delayed summertime breakdown. Whilst the response of these two aspects is consistent in sign, a large intermodel spread exists in terms of magnitude. Using a multi-linear regression framework, we generate storylines of climate change conditional upon the magnitude of change in each driver centred around the multi-model mean response. We examine the response of both the near-surface climate (Southern Annular Mode, air temperature, precipitation) and Southern Ocean (SSTs, salinity and mixed layer depth) for both an extended austral summer (DJFM) and winter season (JJA). Through ancillary evaluations of model historical performance with respect to ERA-5 reanalysis over the 1985-2014 period, including investigation of both prognostic and diagnostic variables, the presented storylines are refined to help minimise the impact of model deficiencies in affecting the realism of the generated storylines. Our results highlight the merit of using the storyline approach to identify future potential scenarios of regional climate response and constrain uncertainty in Antarctic climate predictions. Storyline impact assessments for the Southern Ocean marine ecosystem, particularly the ecologically sensitive South Scotia Sea region, will later be investigated within the EU Horizon 2020 ‘PolarRES’ project through storyline-guided downscaling experiments using regional climate models.  

How to cite: Williams, R., Marshall, G., Levine, X., Graff, L., and Mooney, P.: Storylines of Southern Hemisphere climate change from CMIP6: Antarctica and the Southern Ocean, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13928, https://doi.org/10.5194/egusphere-egu23-13928, 2023.

Climate is defined by the statistics of the weather. We are thus used to the notion that weather depends on climate in the sense that a weather state is a quasi random realization drawn from the climatological distribution of weather states. Consequently, weather obviously also depends on climate change. Here it is argued that it can be very instructive to consider this dependence the other way around and to investigate how climate change depends on the weather. More specifically, the question is how different parts of the climatological distribution change, depending on certain relevant characteristics of the weather. For example, one may ask how the climate at some time of the year and at some location changes between a pre-industrial and a globally +4K warmer climate, considering only days where the local winds at some height blow from a specific direction. Alternatively, one may investigate how the climate change pattern differs between certain large-scale atmospheric circulation regimes, such as NAO⁺ and NAO^- situations. While such conditional climate change analyses can be based for example on reanalysis or CMIP-type climate model data, a more extreme variant are storyline simulations where the evolution of the large-scale circulation is imposed in a climate model using different climate backgrounds, allowing to assess climate change conditional on a specific evolution of the large-scale circulation. Storyline simulations inevitably ignore possible changes in the likelihood of circulation patters. In contrast, analyses based on sufficiently large samples of reanalysis or CMIP-type data also allow for quantifying changes in likelihoods and constitute a proper decomposition of the complete (unconditional) climate change signal. Here the concept of weather-dependent climate change is explained and its potential to help unravel the complexities of climate change is demonstrated.

How to cite: Goessling, H.: Weather-dependent climate change, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15532, https://doi.org/10.5194/egusphere-egu23-15532, 2023.

The Beaufort Gyre is a major reservoir of freshwater in the Arctic Ocean and plays an important role in shaping the sea ice distribution. The variations in Beaufort Gyre strength, and its capacity to accumulate or release freshwater, are primarily determined by the stationary Beaufort High pressure system. Multiple studies have suggested a potential future weakening of the Beaufort High, thus driving a projected weakening of the Beaufort Gyre. Yet, in contrast, the ongoing reduction and thinning of the Arctic sea ice has been shown to strengthen the Gyre in recent years – a trend likely to continue into the future. 

We investigate these potentially competing effects of projected sea ice decline and changing atmospheric patterns on the Beaufort Gyre location, extent, and strength. To this end, we employ a novel storyline approach to identify plausible fates of the Beaufort Gyre in a warming climate, generated from the suite of available CMIP6 models. The different storylines are determined based on the strong or weak modelled response to these two local drivers - Arctic sea ice decline and Beaufort High pressure system weakening - on changes in Beaufort Gyre strength. While the CMIP6 multi-model mean response in the location, extent and strength of the Beaufort Gyre does not exhibit any distinct future changes under emission scenario SSP585, the storylines however reveal contrasting futures. For example, in a future with strong sea ice decline but only a weak decrease of Beaufort High pressure, the storyline indicates a spin-up of the Beaufort Gyre alongside a strong Arctic-wide surface salinity reduction. In contrast, a future with weak sea ice decline but a strong Beaufort High pressure decrease is characterised by a slow-down of the Beaufort Gyre and more regionally confined surface salinity changes. The storyline approach thus highlights that we urgently need to better constrain our model projections in order to reliably predict changes in upper Arctic ocean circulation and freshwater distribution, which play a crucial role for the future Arctic climate and response of both marine and terrestrial ecosystems. 

How to cite: Köhler, R., Athanase, M., Levine, X., Williams, R., and Heuzé, C.: Fates of the Beaufort Gyre: Location, Extent and Strength, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7889, https://doi.org/10.5194/egusphere-egu23-7889, 2023.