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Mid-high latitude Northern Asia is one of the most vulnerable and sensitive areas to global warming, but relatively less studied previously. We used an ensemble of a regional climate model (RegCM4) projections to assess future changes in surface air temperature, precipitation and Köppen‒Trewartha (K‒T) climate types in Northern Asia under the 1.5–4 °C global warming targets. RegCM4 is driven by five CMIP5 global models over an East Asia domain at a grid spacing of 25 km. Validation of the present day (1986–2005) simulations shows that the ensembles of RegCM4 (ensR) and driving GCMs (ensG) reproduce the major characters of the observed temperature, precipitation and K‒T climate zones reasonably well. Greater and more realistic spatial detail is found in RegCM4 compared to the driving GCMs. A general warming and overall increases in precipitation are projected over the region, with these changes being more pronounced at higher warming levels. The projected warming by ensR shows different spatial patterns, and is in general lower, compared to ensG in most months of the year, while the percentage increases of precipitation are maximum during the cold months. The future changes in K‒T climate zones are characterized by a substantial expansion of Dc (temperature oceanic) and retreat of Ec (sub-arctic continental) over the region, reaching ∼20% under the 4 °C warming level. The most notable change in climate types in ensR is found over Japan (∼60%), followed by Southern Siberia, Mongolia, and the Korean Peninsula (∼40%). The largest change in the K‒T climate types is found when increasing from 2 to 3 °C. The results will help to better assess the impacts of climate change and in implementation of appropriate adaptation measures over the region.

Climate change adaptation and relevant policy-making need reliable projections of future climate. Methods based on multi-model ensemble are generally considered as the most efficient way to achieve the goal. However, their efficiency varies and inter-comparison is a challenging task, as they use a variety of target variables, geographic regions, time periods, or model pools. Here, we construct and use a consistent framework to evaluate the performance of five ensemble-processing methods, i.e., multi-model ensemble mean (MME), rank-based weighting (RANK), reliability ensemble averaging (REA), climate model weighting by independence and performance (ClimWIP), and Bayesian model averaging (BMA). We investigate the annual mean temperature (Tav) and total precipitation (Prcptot) changes (relative to 1995–2014) over China and its seven subregions at 1.5 and 2 °C warming levels (relative to pre-industrial). All ensemble-processing methods perform better than MME, and achieve generally consistent results in terms of median values. But they show different results in terms of inter-model spread, served as a measure of uncertainty, and signal-to-noise ratio (SNR). ClimWIP is the most optimal method with its good performance in simulating current climate and in providing credible future projections. The uncertainty, measured by the range of 10th-90th percentiles, is reduced by about 30% for Tav, and 15% for Prcptot in China, with a certain variation among subregions. Based on ClimWIP, and averaged over whole China under 1.5/2 °C global warming levels, Tav increases by about 1.1/1.8 °C (relative to 1995–2014), while Prcptot increases by about 5.4%/11.2%, respectively. Reliability of projections is found dependent on investigated regions and indices. The projection for Tav is credible across all regions, as its SNR is generally larger than 2, while the SNR is lower than 1 for Prcptot over most regions under 1.5 °C warming. The largest warming is found in northeastern China, with increase of 1.3 (0.6-1.7)/2.0 (1.4-2.6) °C(ensemble's median and range of the 10th–90th percentiles) under 1.5/2 °C warming, followed by northern and northwestern China. The smallest but the most robust warming is in southwestern China, with values exceeding 0.9 (0.6–1.1)/1.5 (1.1–1.7) °C. The most robust projection and largest increase is achieved in northwestern China for Prcptot, with increase of 9.1%(-1.6–24.7%)/17.9% (0.5–36.4%) under 1.5/2 °C warming. Followed by northern China, where the increase is 6.0%(-2.6–17.8%)/11.8% (2.4–25.1%), respectively. The precipitation projection is of large uncertainty in southwestern China, even with uncertain sign of variation. For the additional half-degree warming, Tav increases more than 0.5 °C throughout China. Almost all regions witness an increase of Prcptot, with the largest increase in northwestern China. [ABSTRACT FROM AUTHOR]

Climate change will bring huge risks to human society and the economy. Regional climate change risk assessment is an important basic analysis for addressing climate change, which can be expressed as a regional system of comprehensive climate change risk. This study establishes regional systems of climate change risks under the proposed global warming targets. Results of this work are spatial patterns of climate change risks in China, indicated by the degree of climate change and the status of the risk receptors. Therefore, the risks show significant spatial differences. The high-risk regions are mainly distributed in East, South, and central China, while the medium-high risk regions are found in North and southwestern China. Under the 2°C warming target, more than 1/4 of China's area would be at high and medium-high risk, which is more severe than under the 1.5°C warming target, and would extend to the western and northern regions. This work provides regional risk characteristics of climate change under different global warming targets as a foundation for dealing with climate change. [ABSTRACT FROM AUTHOR]

This paper presents projections of climate extremes over China under global warming of 1.5, 2, and 3 °C above pre-industrial (1861–1900), based on the latest Coupled Model Intercomparison Project phase 6 (CMIP6) simulations. Results are compared with what produced by the precedent phase of the project, CMIP5. Model evaluation for the reference period (1985–2005) indicates that CMIP6 models outperform their predecessors in CMIP5, especially in simulating precipitation extremes. Areal averages for changes of most indices are found larger in CMIP6 than in CMIP5. The emblematic annual mean temperature, when averaged over the whole of China in CMIP6, increases by 1.49, 2.21, and 3.53 °C (relative to 1985–2005) for 1.5, 2, and 3 °C above-preindustrial global warming levels, while the counterpart in CMIP5 is 1.20, 1.93 and 3.39 °C respectively. Similarly, total precipitation increases by 5.3%, 8.6%, and 16.3% in CMIP6 and by 4.4%, 7.0% and 12.8% in CMIP5, respectively. The spatial distribution of changes for extreme indices is generally consistent in both CMIP5 and CMIP6, but with significantly higher increases in CMIP6 over Northeast and Northwest China for the hottest day temperature, and South China for the coldest night temperature. In the south bank of the Yangtze River, and most regions around 40°N, CMIP6 shows higher increases for both total precipitation and heavy precipitation. The projected difference between CMIP6 and CMIP5 is mainly attributable to the physical upgrading of climate models and largely independent from their emission scenarios. [ABSTRACT FROM AUTHOR]

Assessing multiple climatic and non-climatic variables affecting one region at the same time is a crucial aspect to support climate adaptation action. This publication presents a method to display relevant measures of any three adaptation relevant parameters (or optionally their projected future changes) at once on a map by allocating them to multiple transparency levels of the three primary colors of additive color mixing (red, green, and blue). The overlay of information allows the combined assessment of the regional exposures. The method is demonstrated by two examples based on an ensemble of regional climate projections analyzed for 1.5 °C, 2 °C, and 3 °C global warming periods. The first example shows the increasing number of people at risk for summer climate extremes under 1.5 °C, 2 °C, and 3 °C global warming by combining projected increases in tropical nights and summer intense precipitation days with today's population density. Under 3 °C global warming, many heavily populated areas across Europe are affected by both heat stress and summer precipitation extremes, whereas under 1.5 °C global warming, heat stress regions are restricted to southern Europe and the large settlements along the Eastern Mediterranean coast. A second example combines daily mean and minimum and maximum summer temperatures and highlights the regional expansion and the increasing robustness of projected mean summer warming with rising global warming levels, as well as the regional day to night differences of the warming signal. [ABSTRACT FROM AUTHOR]

Abstract Comparable estimates of the heat-related work productivity loss (WPL) in different countries over the world are difficult partly due to the lack of exact measures and comparable data for different counties. In this study, we analysed 4363 responses to a global online survey on the WPL during heat waves in 2016. The participants were from both developed and developing countries, facilitating estimates of the heat-related WPL across the world for the year. The heat-related WPL for each country involved was then deduced for increases of 1.5, 2, 3 and 4 °C in the global mean surface temperature under the representative concentration pathway scenarios in climate models. The average heat-related WPL in 2016 was 6.6 days for developing countries and 3.5 days for developed countries. The estimated heat-related WPL was negatively correlated with the gross domestic product per capita. When global surface temperatures increased by 1.5, 2, 3 and 4 °C, the corresponding WPL was 9 (19), 12 (31), 22 (61) and 33 (94) days for developed (developing) countries, quantifying how developing countries are more vulnerable to climate change from a particular point of view. Moreover, the heat-related WPL was unevenly distributed among developing countries. In a 2°C-warmer world, the heat-related WPL would be more than two months in Southeast Asia, the most influenced region. The results are considerable for developing strategy of adaptation especially for developing countries. Highlights • We demonstrated a worldwide pattern of the heat-related loss of work productivity (WP) based on an extensive global survey. • Regions vulnerable in this way to heat waves such as Central Asia might have been overlooked in previous studies. • The heat-related loss of WP has significant negative correlation with the level of development of the region. • The loss of WP increases when global warming reaches 1.5, 2, 3 and 4 °C, much more profoundly in developing regions. [ABSTRACT FROM AUTHOR]

Abstract: To avoid the most dangerous consequences of anthropogenic climate change, the Paris Agreement provides a clear and agreed climate mitigation target of stabilizing global surface warming to under 2.0°C above preindustrial, and preferably closer to 1.5°C. However, policy makers do not currently know exactly what carbon emissions pathways to follow to stabilize warming below these agreed targets, because there is large uncertainty in future temperature rise for any given pathway. This large uncertainty makes it difficult for a cautious policy maker to avoid either: (1) allowing warming to exceed the agreed target or (2) cutting global emissions more than is required to satisfy the agreed target, and their associated societal costs. This study presents a novel Adjusting Mitigation Pathway (AMP) approach to restrict future warming to policy‐driven targets, in which future emissions reductions are not fully determined now but respond to future surface warming each decade in a self‐adjusting manner. A large ensemble of Earth system model simulations, constrained by geological and historical observations of past climate change, demonstrates our self‐adjusting mitigation approach for a range of climate stabilization targets ranging from 1.5°C to 4.5°C, and generates AMP scenarios up to year 2300 for surface warming, carbon emissions, atmospheric CO2, global mean sea level, and surface ocean acidification. We find that lower 21st century warming targets will significantly reduce ocean acidification this century, and will avoid up to 4 m of sea‐level rise by year 2300 relative to a high‐end scenario. [ABSTRACT FROM AUTHOR]

Multi-hazard assessment is needed to understand compound risk. Yet, modelling of multiple climate hazards has been limitedly applied at the global scale to date. Here we provide a first comprehensive assessment of global population exposure to hydro-meteorological extremes—floods, drought and heatwaves—under different temperature increase targets. This study shows how limiting temperature increase to 1.5 and 2 °C, as for the goals of the Paris Agreement, could substantially decrease the share of global population exposed compared to a 3 °C scenario. In a 2 °C world, population exposure would drop by more than 50%, in Africa, Asia and the Americas, and by about 40% in Europe and Oceania. A 1.5 °C stabilization would further reduce exposure of about an additional 10% to 30% across the globe. As the Parties of the Paris Agreement are expected to communicate new or updated nationally determined contributions by 2020, our results powerfully indicate the benefits of ratcheting up both mitigation and adaptation ambition.

The need to restrict global mean temperature to avoid irreversible climate change is supported by scientific evidence. The need became political practice at the Conference of the Parties in 2015, where the participants decided to limit global warming to not more than +2.0 °C compared to pre-industrial times and to rather aim for a limit of +1.5 °C global warming. Nevertheless, a clear picture of what European climate would look like under +1.5 °C, +2.0 °C and +3.0 °C global warming level (GWL) is still missing. In this study, we will fill this gap by assessing selected climate indices related to temperature and precipitation extremes, based on state of the art regional climate information for Europe taken from the European branch of the World Climate Research Program Coordinated Regional Downscaling Experiment (EURO-CORDEX) ensemble. To assess the impact of these indices under climate change, we investigate the spatial extent of the area of the climate change signal in relation to the affected population. This allows us to demonstrate which climate extremes could be avoided when global warming is kept well below +2.0 °C or even +1.5 °C compared to higher GWLs. The European north–south gradient of tropical nights and hot days is projected to be intensified with an increasing global warming level. For precipitation-related indices, an overall increase in precipitation extremes is simulated, especially under +3.0 °C GWL, for mid- and northern Europe, whereas an increase in dry days is projected for many regions in southern Europe. The benefit of staying below +1.5 °C GWL compared to +2.0 °C GWL is the avoidance of an additional increase in tropical nights and hot days parallel to an increase in dry days in parts of southern Europe as well as an increase in heavy precipitation in parts of Scandinavia. Compared to +3.0 °C GWL, the benefit of staying at +1.5 °C GWL is to avoid a substantial increase (i.e., an increase of more than five dry days and ten tropical nights) in dry days and tropical nights in southern European regions, while, in several European regions and especially in northern Europe, a substantial increase (i.e., more than two heavy precipitation days) in heavy precipitation days could be avoided. This study shows that a statistically significant change in the investigated climate indices can be avoided under +1.5 °C GWL compared to the investigated higher GWLs +2.0 °C and +3.0 °C for the majority of the population in almost all regions. Future studies will investigate compound events where the severity of single extreme events is intensified.

Since the ‘Paris agreement’ in 2015 there has been much focus on what a +1.5 °C or +2 °C warmer world would look like. Since the focus lies on policy relevant global warming targets, or specific warming levels (SWLs), rather than a specific point in time, projections are pooled together to form SWL ensembles based on the target temperature rather than emission scenario. This study uses an ensemble of CMIP5 global model projections to analyse how well SWL ensembles represent the stabilized climate of global warming targets. The results show that the SWL ensembles exhibit significant trends that reflect the transient nature of the RCP scenarios. These trends have clear effect on the timing and clustering of monthly cold and hot extremes, even though the effect on the temperature of the extreme months is less visible. In many regions there is a link between choice of RCP scenario used in the SWL ensemble and climate change signal in the highest monthly temperatures. In other regions there is no such clear-cut link. From this we conclude that comprehensive analyses of what prospects the different global warming targets bring about will require stabilization scenarios. Awaiting such targeted scenarios we suggest that prudent use of SWL scenarios, taking their characteristics and limitations into account, may serve as reasonable proxies in many situations.

Since the Industrial Revolution, greenhouse gas emissions have caused global temperatures to rise gradually. The Paris Agreement aims to limit the global mean surface temperature increase to less than 2.0 °C relative to pre-industrial levels. China's land area accounts for ∼7% of the global land (65Ñ59S) area, and the arid area of China accounts for 12.41% of the total global arid area. Therefore, the degree of aridification/humidification in China is of great significance to climate change in China and the world. This paper evaluates the regional changes of drylands and humid lands in China based on the 1.5 °C and 2.0 °C increase targets for global mean surface warming(GMSW). We find a suitable warming target for China's climate from the perspective of aridification. The results show the following: 1) If the global mean surface temperature rises by 1.5 °C and 2.0 °C above pre-industrial levels, the mean surface temperature in China will increase by 2.0 °C and 2.8 °C, respectively. 2) Under the two GMSW targets, the degree of drought in some extremely arid areas in China was projected to decrease, which means that these areas may gradually be suitable for human habitation. 3) Regardless of which global surface temperature target is maintained, the humid lands in China will bear greater risks from warming than the drylands. Under these circumstances, the 1.5 °Ctargetwill lead to better outcomes for China than the 2.0 °C target. • The degree of drought in some extremely arid areas in China has decreased under global warming targets. • Humid lands in China will bear greater warming risks than the dry lands. • Global warming limited within 1.5 °C target for will lead to better outcomes for China than the 2.0 °C. [ABSTRACT FROM AUTHOR]

The need to restrict global mean temperature to avoid irreversible climate change is supported by scientific evidence. The need became political practice at the Conference of the Parties in 2015, where the participants decided to limit global warming to not more than +2.0 °C compared to pre-industrial times and to rather aim for a limit of +1.5 °C global warming. Nevertheless, a clear picture of what European climate would look like under +1.5 °C, +2.0 °C and +3.0 °C global warming level (GWL) is still missing. In this study, we will fill this gap by assessing selected climate indices related to temperature and precipitation extremes, based on state of the art regional climate information for Europe taken from the European branch of the World Climate Research Program Coordinated Regional Downscaling Experiment (EURO-CORDEX) ensemble. To assess the impact of these indices under climate change, we investigate the spatial extent of the area of the climate change signal in relation to the affected population. This allows us to demonstrate which climate extremes could be avoided when global warming is kept well below +2.0 °C or even +1.5 °C compared to higher GWLs. The European north–south gradient of tropical nights and hot days is projected to be intensified with an increasing global warming level. For precipitation-related indices, an overall increase in precipitation extremes is simulated, especially under +3.0 °C GWL, for mid- and northern Europe, whereas an increase in dry days is projected for many regions in southern Europe. The benefit of staying below +1.5 °C GWL compared to +2.0 °C GWL is the avoidance of an additional increase in tropical nights and hot days parallel to an increase in dry days in parts of southern Europe as well as an increase in heavy precipitation in parts of Scandinavia. Compared to +3.0 °C GWL, the benefit of staying at +1.5 °C GWL is to avoid a substantial increase (i.e., an increase of more than five dry days and ten tropical nights) in dry days and tropical nights in southern European regions, while, in several European regions and especially in northern Europe, a substantial increase (i.e., more than two heavy precipitation days) in heavy precipitation days could be avoided. This study shows that a statistically significant change in the investigated climate indices can be avoided under +1.5 °C GWL compared to the investigated higher GWLs +2.0 °C and +3.0 °C for the majority of the population in almost all regions. Future studies will investigate compound events where the severity of single extreme events is intensified. [ABSTRACT FROM AUTHOR]