@article{AshrafVaghefi2021,

title = {Using Decision Making under Deep Uncertainty (DMDU) approaches to support climate change adaptation of Swiss Ski Resorts},

author = {Saeid Ashraf Vaghefi and Veruska Muccione and Kees C. H. Ginkel and Marjolijn Haasnoot},

url = {https://linkinghub.elsevier.com/retrieve/pii/S1462901121002513},

doi = {10.1016/j.envsci.2021.09.005},

issn = {14629011},

year  = {2021},

date = {2021-12-01},

journal = {Environmental Science & Policy},

volume = {126},

pages = {65--78},

publisher = {Elsevier},

abstract = {Climate change threatens winter tourism in the Alps severely, and ski resorts are struggling to cope under uncertain climate change. We aim to identify under what conditions physical and economic tipping points for ski resorts may occur under changing climate in six Swiss ski resorts representing low, medium, and high elevation in the Alps. We use exploratory modeling (EMA) to assess climate change impacts on ski resorts under a range of futures adaptation options: (1) snowmaking and (2) diversifying the ski resorts' activities throughout the year. High-resolution climate projections (CH2018) were used to represent climate uncertainty. To improve the coverage of the uncertainty space and account for the climate models' intra-annual variability, we produced new climate realizations using resampling techniques. We demonstrate the importance of five factors, namely climate scenarios (RCPs), intra-annual climate variability, snow processes model, and two adaptation options, in ski resorts survival under a wide range of future scenarios. In six ski resorts, strong but highly variable decreases in the future number of days with good snow conditions for skiing (GSD) are projected. However, despite the different characteristics of the resorts, responses are similar and a shrunk of up to 31, 50, and 62 days in skiing season (Dec-April) is projected for the near-future (2020–2050), mid-future (2050–2080), and far-future (2070–2100), respectively. Similarly, in all cases, the number of days with good conditions for snowmaking (GDSM) will reduce up to 30, 50, and 74 days in the skiing season in the near-, mid-, and far-future horizons, respectively. We indicate that all ski resorts will face a reduction of up to 13%, 33%, and 51% of their reference period (1981–2010) revenue from winter skiing activities in the near-, mid-, and far-future horizons. Based on the outcomes of the EMA, we identify Dynamic Adaptive Policy Pathways (DAPP) and determine the adaptation options that ski resorts could implement to avoid tipping points in the future. We highlight the advantages of adaptive planning in a first of its kind application of DMDU techniques to winter tourism. We specify the possible adaptation options ranging from “low revenue diversification and moderate snowmaking” to “high revenue diversification and large snowmaking” and demonstrate when an adaptation action fails and a change to a new plan is needed. By the end of the century, we show that only ski resorts with ski lines above 1800–2000 m elevation will survive regardless of the climate scenarios. Our approach to decision-making is highly flexible and can easily be extended to other ski resorts and account for additional adaptation options.},

keywords = {climate change, Decision making under deep uncertainty (DMDU), Dynamic adaptive policy pathways (DAPP), Scenario discovery, Tipping points, Winter tourism},

pubstate = {published},

tppubtype = {article}

}