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The Intergovernmental Panel on Climate Change (IPCC) suggests limiting global warming to 1.5 °C compared to 2 °C would avoid dangerous impacts of anthropogenic climate change and ensure a more sustainable society. As the vulnerability to global warming is regionally dependent, this study assesses the effects of 0.5 °C less global warming on climate extremes in the United States. Eight climate extreme indices are calculated based on Coupled Model Intercomparison Project—phase 5 (CMIP5), and North American—Coordinated Regional Climate Downscaling Experiments (NA-CORDEX) with and without bias correction. We evaluate the projected changes in temperature and precipitation extremes, and examine their differences between the 1.5 and 2 °C warming targets. Under a warming climate, both CMIP5 and NA-CORDEX show intensified heat extremes and reduced cold extremes across the country, intensified and more frequent heavy precipitation in large areas of the North, prolonged dry spells in some regions of the West, South, and Midwest, and more frequent drought events in the West. Results suggest that the 0.5 °C less global warming would avoid the intensification of climate extremes by 32–46% (35–42%) for heat extremes intensity (frequency) across the country and, by 23–41% for heavy precipitation intensity in the North, South, and Southeast. The changes in annual heavy precipitation intensity are mainly contributed by winter and spring. However, impacts of the limited warming on the frequency of heavy precipitation, dry spell, and drought frequency are only evident in a few regions. Although uncertainties are found among the climate models and emission scenarios, our results highlight the benefits of limiting warming at 1.5 °C in order to reduce the risks of climate extremes associated with global warming.

The continuing growth in energy demand has promoted wind energy development worldwide. As anthropogenic greenhouse gas emissions will continue to modify the atmospheric circulation and global climate, assessing the impacts of climate change on wind energy is necessary. This study uses high-resolution simulations in the North America downscaling project (NA-CORDEX) to investigate the future change in wind resources over North America. Wind power is projected to decrease over large areas of the western US and East Coast throughout the year. The central US, with the greatest potential for wind energy development, will experience stronger wind variability and significantly increased wind power during some seasons. Wind power shows a significant increase (up to 20%) in the Southern Plains during spring and summer. The Northern Plains and the Midwest may experience slightly increased wind power (within 10%) during winter and spring. The seasonal and spatial patterns in the wind power change are relatively robust among the different emission scenarios, different future periods, and simulations with different spatial resolutions. This study outlines the regions that may benefit from or be negatively impacted by global climate change. Therefore, climate effects should be considered in the future build-out of wind energy resources.

It is reported that surface warming over the Tibetan Plateau (TP) has been faster than the global average, but exactly how much faster remains controversial. This study investigates the time dependency of warming amplification over the TP using CRU_TS4.01 grid dataset during 1961–2016 with a consideration of its consistency with the global average. We find that the magnitude of warming on the TP and its consistency with the global average have been variable. Compared to the global average, the TP warming during 1983–2016 is faster than in the period of 1961–1983, and has a higher consistency with the global average in the period of 1983–2016. The TP warming has a seasonal amplification of 1.1–1.4 times than the global average during 1983–2016, while warming amplification during 1961–1983 is relatively less evident. Generally, the magnitude of warming on the TP is smaller than in the northern high‐latitudes, but larger than in the Southern Hemisphere and the Tropics. Based on current scientific understanding, the possible contribution of snow/ice‐albedo feedback may have played an important role in warming amplification on the TP since the 1980s.

Weakening of annual temperature cycle (ATC) on the Tibetan Plateau (TP) in the last decades has been identified, and there is a subsequent change in the frequency of the ATC magnitude extremes. These changes in the climate have a potential influence on biological and ecological systems. However, the frequency of occurrences of the ATC magnitude extremes in the recent decades compared to the preindustrial period, as well as the potential driving forces remains unclear. This can limit the robust predictions and risk assessments for extreme events of the ATC in the future. In this study, we analyzed the frequency of occurrence of the ATC magnitude extremes using both recent observations (1955–2011) and a tree-ring-based reconstruction covering the past three centuries over the TP. The results indicate that the ATC magnitude extremes in maximum obviously decrease and in minimum distinctly increase under climate warming, both for the instrumental period and the past three centuries. Moreover, the occurrence of the ATC magnitude extremes on the TP had a distinct regional characteristic and was mainly related to the winter temperature extremes triggered by the anomalous meridional gradient of geopotential height impelling cold air intrudes the TP. Although volcanic eruptions were expected to result in summer cooling and winter warming, and thus trigger the minimum ATC magnitude extremes, this effect only can be identified in event-specific eruptions (e.g., the 1835 Cosiguina eruption). Our study results provide an essential background for developing robust predictions and risk assessments for the ATC magnitude extremes on the TP.

The continuous global climate change has affected the living habits, morphological characteristics and spatial distribution of tree species. Chinese fir (C. lanceolata (Lamb.) Hook) is one of the most important conifer tree species in China, which plays a major role in terms of timber supplies and environment protection. Predict the potential suitable habitats of Chinese fir under different climatic scenarios, can not only provide scientific theoretical basis for the planning and planting of Chinese fir, but also have great significance for maintaining the stability of the plantation ecosystem. Here, we used the maximum entropy (Maxent) model which optimized by the ENMeval package, to predicted the potential suitable habitats for Chinese fir under current climatic conditions and two climatic scenarios in 2070s. Our results showed that the complexity of the model was relative low, when the regularization multiplier (RM) was 0.5 and feature combination (FC) was linear (L) and quadratic (Q). Under this parameter setting, the high and moderate suitable habitat area of Chinese fir were 83.90 × 104 km2 and 97.62 × 104 km2, respectively, which suggested we can carry out Chinese fir planting activities with different cultivation purposes. The minimum temperature of the coldest month, annual precipitation, annual mean temperature and mean temperature of warmest quarter were identified as the essential factors shaping habitat suitability for Chinese fir. Under future climate scenarios, the high suitable habitat was reduced and the degree of fragmentation was increased, and the total potential suitable habitat of Chinese fir had the tendency to migrate to high-altitude regions. Managers should be cautious about the cultivation area selection of Chinese fir plantation as the potential suitable habitat changed under the global climate change continuously. It is therefore imperative to adjust the long-term management and protection strategy of Chinese fir plantation.

Knowing the responses of arbuscular mycorrhizal (AM) fungi to warming and increased precipitation are critical for understanding how biodiversity is maintained and how the ecosystem functions under global climate-change scenarios in natural ecosystems. In this study, AM fungal communities were examined in a 6 year experiment with warming and increased precipitation, in a semiarid steppe in northern China. Only the increased precipitation, regardless of warming, significantly increased AM fungal extra-radical hyphal density, compared with the control treatment. AM fungal spore density was significantly increased by the combination of warming and increased precipitation, and increased precipitation-only treatments, but not by warming alone. A total of 36 operational taxonomic units (OTUs) of AM fungi were recovered by 454 pyrosequencing of 18S rDNA. Only increased precipitation, regardless of warming, significantly decreased AM fungal OTU richness and Shannon diversity index, and yet significantly increased AM fungal Bray–Curtis dissimilarity index, compared with the control treatment. AM fungal community composition was significantly affected by increased precipitation via water availability, but not by warming. Our findings demonstrated that the AM fungal community responded more strongly to water availability than to warming in the semiarid steppe ecosystem.

Understanding the response of arbuscular mycorrhizal (AM) fungi to warming and nitrogen (N) fertilization is critical to assess the impact of anthropogenic disturbance on ecosystem functioning under global climate change scenarios. In this study, AM fungal communities were examined in a full factorial design with warming and N addition in a semiarid steppe in northern China. Warming significantly increased AM fungal spore density, regardless of N addition, whilst N addition significantly decreased AM fungal extraradical hyphal density, regardless of warming. A total of 79 operational taxonomic units (OTUs) of AM fungi were recovered by 454 pyrosequencing of SSU rDNA. Warming, but not N addition, had a significant positive effect on AM fungal OTU richness, while warming and N addition significantly increased AM fungal Shannon diversity index. N addition, but not warming, significantly altered the AM fungal community composition. Furthermore, the changes in AM fungal community composition were associated with shifts in plant community composition indirectly caused by N addition. These findings highlight the different effects of warming and N addition on AM fungal communities and contribute to understanding AM fungal community responses to global environmental change scenarios in semiarid steppe ecosystems.

Arbuscular mycorrhizal (AM) fungi form mutualistic symbioses with most plant species and play important roles in ecosystems. Knowledge of the response of AM fungi to temperature change will improve our understanding of the function of AM fungal community under global climate change scenarios in ecosystems. The effects of constant warming on AM fungal communities have been investigated previously, but responses to asymmetrical warming over 24-h periods have never been documented in natural ecosystems. In this study, we examined AM fungal communities in a full factorial design including day-time and night-time warming in a semiarid steppe in northern China. Day-time and 24-h warming, but not night-time warming, significantly increased AM fungal spore density. In contrast, none of the three warming regimes had a significant effect on AM fungal extra radical hyphal density. A total of 161 operational taxonomic units (OTUs) of AM fungi were recovered by 454 pyrosequencing of 18S rDNA. Day-time, night-time, and 24-h warming all significantly increased AM fungal OTU richness. Some AM fungal OTUs showed a significant bias toward day-time, night-time or 24-h warming. The AM fungal community composition was significantly affected by night-time warming, but not by day-time and 24-h warming. Our finding highlighted different responses of AM fungal spore density and community composition to asymmetrical warming. This study might improve our understanding of ecosystem functioning of AM fungal community under global climate change scenarios in a semiarid steppe ecosystem.

This paper presents a forecast and analysis of population, economic development, energy consumption and CO2 emissions variation in China in the short- and long-term steps before 2020 with 2007 as the base year. The widely applied IPAT model, which is the basis for calculations, projections, and scenarios of greenhouse gases (GHGs) reformulated as the Kaya equation, is extended to analyze and predict the relations between human activities and the environment. Four scenarios of CO2 emissions are used including business as usual (BAU), energy efficiency improvement scenario (EEI), low carbon scenario (LC) and enhanced low carbon scenario (ELC). The results show that carbon intensity will be reduced by 40-45% as scheduled and economic growth rate will be 6% in China under LC scenario by 2020. The LC scenario, as the most appropriate and the most feasible scheme for China's low-carbon development in the future, can maximize the harmonious development of economy, society, energy and environmental systems. Assuming China's development follows the LC scenario, the paper further gives four paths of low-carbon transformation in China: technological innovation, industrial structure optimization, energy structure optimization and policy guidance.

Facing climate change and global warming, outdoor climatic environment is an important consideration factor for planners and policy makers because improving it can greatly contribute to achieve citizen's thermal comfort and create a better urban living quality for adaptation. Thus, the climatic information must be assessed systematically and applied strategically into the planning process. This paper presents a tool named Urban Climate Map System (UCMS) that has proven capable of helping compact cities to incorporate climate effects in planning processes in a systematic way. UCMS is developed and presented in a Geographic Information System (GIS) platform in which the lessons learned and experience gained from interdisciplinary studies can be included. The methodology of UCMS of compact cities, the construction procedure, and the basic input factors – including the natural climate resources and planning data – are described. Some literatures that shed light on the applicability of UMCS are reported. The Municipality of Arnhem is one of Dutch compact urban areas and still under fast urban development and urban renewal. There is an urgent need for local planners and policy makers to protect local climate and open landscape resources and make climate change adaptation in urban construction. Thus, Arnhem is chosen to carry out a case study of UCMS. Although it is the first work of Urban Climatic Mapping in The Netherlands, it serves as a useful climatic information platform to local planners and policy makers for their daily on-going works. We attempt to use a quick method to collect available climatic and planning data and create an information platform for planning use. It relies mostly on literature and theoretical understanding that has been well practiced elsewhere. The effort here is to synergize the established understanding for a case at hand and demonstrate how useful guidance can still be made for planners and policy makers.