Future Climate Change Hotspots Under Different 21st Century Warming Scenarios. Issue 6 (7th June 2021) - Fan, Xuewei; Miao, Chiyuan; Duan, Qingyun; Shen, Chenwei; Wu, Yi
Abstract: Identifying climate change hotspot regions is critical for planning effective mitigation and adaptation activities. We use standard Euclidean distance (SED) to calculate integrated changes in precipitation and temperature means, interannual variability, and extremes between different future warming levels and a baseline period (1995–2014) using the Coupled Model Intercomparison Project Phase 6 (CMIP6) climate model ensemble. We find consistent hotspots in the Amazon, central and western Africa, Indonesia and the Tibetan Plateau at warming levels of 1.5°C, 2°C, and 3°C for all scenarios explored; the Arctic, Central America and southern Africa emerge as hotspots at 4°C warming and at the end of the 21st century under two Shared Socioeconomic Pathways scenarios, SSP3‐7.0 and SSP5‐8.5. CMIP6 models show higher SED values than CMIP5, suggesting stronger aggregated effects of climate change under the new scenarios. Hotspot time of emergence (TOE) is further investigated; TOE is defined as the year when the climate change signal first exceeds the noise of natural variability in 21st century projections. The results indicate that TOEs for warming would occur over all primary hotspots, with the earliest occurring in the Arctic and Indonesia. For precipitation, TOEs occur before 2100 in the Arctic, the Tibetan Plateau and Central America. Results using a geographical detector model show that patterns of SED are shaped by extreme hot and dry occurrences at low‐to‐medium warming, while precipitation and temperature means and extreme precipitation occurrences are the dominant influences under the high emission scenario and at high warming levels. Plain Language Summary: The magnitudes and spatial patterns associated with regional responses of climate change vary strongly due to highly localized physical, biological and human factors. We call the regions with the strongest response to global warming hotspots. Identifying the locations and characteristics of hotspots at specific warming levels is a crucial step in designing appropriate adaptation and mitigation strategies. Here, we use the CMIP6 climate model ensemble to identify climate change hotspots over the global land surface based on a statistical metric, the standard Euclidean distance (SED). The SED takes into account the combined changes in the means, variability and extremes of seasonal temperature and precipitation. The results show consistent hotspots in the Amazon, central and western Africa, Indonesia and the Tibetan Plateau, while the Arctic, Central America and southern Africa emerge as hotspot regions under SSP3‐7.0 and SSP5‐8.5 at high warming levels. Key Points: The aggregate impacts of climate change suggest that the hotspot regions will keep largely consistent in the future Time of emergence (TOE) for temperature will occur before 2100 across all the hotspot regions, while TOE for precipitation will only occur in ARC, TP, and CAM The hotspot regions show large relative changes in multiple precipitation and temperature indicators