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- ItemUnderstanding the Drivers of Coastal Flood Exposure and Risk From 1860 to 2100(Hoboken, NJ : Wiley-Blackwell, 2022) Lincke, Daniel; Hinkel, Jochen; Mengel, Matthias; Nicholls, Robert J.Global coastal flood exposure (population and assets) has been growing since the beginning of the industrial age and is likely to continue to grow through 21st century. Three main drivers are responsible: (a) climate-related mean sea-level change, (b) vertical land movement contributing to relative sea-level rise, and (c) socio-economic development. This paper attributes growing coastal exposure and flood risk from 1860 to 2100 to these three drivers. For historic flood exposure (1860–2005) we find that the roughly six-fold increase in population exposure and 53-fold increase in asset exposure are almost completely explained by socio-economic development (>97% for population and >99% for assets). For future exposure (2005–2100), assuming a middle-of-the-road regionalized socio-economic scenario (SSP2) without coastal migration and sea-level rise according to RCP2.6 and RCP6.0, climate-change induced sea-level rise will become the most important driver for the growth in population exposure, while growth in asset exposure will still be mainly determined by socio-economic development.
- ItemA High-End Estimate of Sea Level Rise for Practitioners(Hoboken, NJ : Wiley-Blackwell, 2022) van de Wal, R.S.W.; Nicholls, R J.; Behar, D.; McInnes, K.; Stammer, D.; Lowe, J.A.; Church, J.A.; DeConto, R.; Fettweis, X.; Goelzer, H.; Haasnoot, M.; Haigh, I.D.; Hinkel, J.; Horton, B.P.; James, T.S.; Jenkins, A.; LeCozannet, G.; Levermann, A.; Lipscomb, W.H.; Marzeion, B.; Pattyn, F.; Payne, A.J.; Pfeffer, W.T.; Price, S.F.; Seroussi, H.; Sun, S.; Veatch, W.; White, K.Sea level rise (SLR) is a long-lasting consequence of climate change because global anthropogenic warming takes centuries to millennia to equilibrate for the deep ocean and ice sheets. SLR projections based on climate models support policy analysis, risk assessment and adaptation planning today, despite their large uncertainties. The central range of the SLR distribution is estimated by process-based models. However, risk-averse practitioners often require information about plausible future conditions that lie in the tails of the SLR distribution, which are poorly defined by existing models. Here, a community effort combining scientists and practitioners builds on a framework of discussing physical evidence to quantify high-end global SLR for practitioners. The approach is complementary to the IPCC AR6 report and provides further physically plausible high-end scenarios. High-end estimates for the different SLR components are developed for two climate scenarios at two timescales. For global warming of +2°C in 2100 (RCP2.6/SSP1-2.6) relative to pre-industrial values our high-end global SLR estimates are up to 0.9 m in 2100 and 2.5 m in 2300. Similarly, for a (RCP8.5/SSP5-8.5), we estimate up to 1.6 m in 2100 and up to 10.4 m in 2300. The large and growing differences between the scenarios beyond 2100 emphasize the long-term benefits of mitigation. However, even a modest 2°C warming may cause multi-meter SLR on centennial time scales with profound consequences for coastal areas. Earlier high-end assessments focused on instability mechanisms in Antarctica, while here we emphasize the importance of the timing of ice shelf collapse around Antarctica. This is highly uncertain due to low understanding of the driving processes. Hence both process understanding and emission scenario control high-end SLR.
- ItemTrade-Offs for Climate-Smart Forestry in Europe Under Uncertain Future Climate(Hoboken, NJ : Wiley-Blackwell, 2022) Gregor, Konstantin; Knoke, Thomas; Krause, Andreas; Reyer, Christopher P. O.; Lindeskog, Mats; Papastefanou, Phillip; Smith, Benjamin; Lansø, Anne‐Sofie; Rammig, AnjaForests mitigate climate change by storing carbon and reducing emissions via substitution effects of wood products. Additionally, they provide many other important ecosystem services (ESs), but are vulnerable to climate change; therefore, adaptation is necessary. Climate-smart forestry combines mitigation with adaptation, whilst facilitating the provision of many ESs. This is particularly challenging due to large uncertainties about future climate. Here, we combined ecosystem modeling with robust multi-criteria optimization to assess how the provision of various ESs (climate change mitigation, timber provision, local cooling, water availability, and biodiversity habitat) can be guaranteed under a broad range of climate futures across Europe. Our optimized portfolios contain 29% unmanaged forests, and implicate a successive conversion of 34% of coniferous to broad-leaved forests (11% vice versa). Coppices practically vanish from Southern Europe, mainly due to their high water requirement. We find the high shares of unmanaged forests necessary to keep European forests a carbon sink while broad-leaved and unmanaged forests contribute to local cooling through biogeophysical effects. Unmanaged forests also pose the largest benefit for biodiversity habitat. However, the increased shares of unmanaged and broad-leaved forests lead to reductions in harvests. This raises the question of how to meet increasing wood demands without transferring ecological impacts elsewhere or enhancing the dependence on more carbon-intensive industries. Furthermore, the mitigation potential of forests depends on assumptions about the decarbonization of other industries and is consequently crucially dependent on the emission scenario. Our findings highlight that trade-offs must be assessed when developing concrete strategies for climate-smart forestry.