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Zhu H, Jiang Z, Li L. Projection of climate extremes in China, an incremental exercise from CMIP5 to CMIP6. Sci Bull (Beijing) 2021; 66:2528-2537. [PMID: 36654212 DOI: 10.1016/j.scib.2021.07.026] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Revised: 06/28/2021] [Accepted: 06/28/2021] [Indexed: 02/03/2023]
Abstract
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.
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Affiliation(s)
- Huanhuan Zhu
- Joint International Research Laboratory of Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing 210044, China; Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Zhihong Jiang
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster, Nanjing University of Information Science and Technology, Nanjing 210044, China; Key Laboratory of Meteorological Disaster of Ministry of Education, Nanjing University of Information Science and Technology, Nanjing 210044, China.
| | - Laurent Li
- Laboratoire de Météorologie Dynamique, CNRS, Sorbonne Université, Ecole Normale Supérieure, Ecole Polytechnique, Paris 75005, France
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2
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Feng X, Fu B, Zhang Y, Pan N, Zeng Z, Tian H, Lyu Y, Chen Y, Ciais P, Wang Y, Zhang L, Cheng L, Maestre FT, Fernández-Martínez M, Sardans J, Peñuelas J. Recent leveling off of vegetation greenness and primary production reveals the increasing soil water limitations on the greening Earth. Sci Bull (Beijing) 2021; 66:1462-1471. [PMID: 36654372 DOI: 10.1016/j.scib.2021.02.023] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Revised: 12/25/2020] [Accepted: 12/29/2020] [Indexed: 01/20/2023]
Abstract
Global vegetation photosynthesis and productivity have increased substantially since the 1980s, but this trend is heterogeneous in both time and space. Here, we categorize the secular trend in global vegetation greenness into sustained greening, sustained browning and greening-to-browning. We found that by 2016, increased global vegetation greenness had begun to level off, with the area of browning increasing in the last decade, reaching 39.0 million km2 (35.9% of the world's vegetated area). This area is larger than the area with sustained increasing growth (27.8 million km2, 26.4%); thus, 12.0% ± 3.1% (0.019 ± 0.004 NDVI a-1) of the previous earlier increase has been offset since 2010 (2010-2016, P < 0.05). Global gross primary production also leveled off, following the trend in vegetation greenness in time and space. This leveling off was caused by increasing soil water limitations due to the spatial expansion of drought, whose impact dominated over the impacts of temperature and solar radiation. This response of global gross primary production to soil water limitation was not identified by land submodels within Earth system models. Our results provide empirical evidence that global vegetation greenness and primary production are offset by water stress and suggest that as global warming continues, land submodels may overestimate the world's capacity to take up carbon with global vegetation greening.
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Affiliation(s)
- Xiaoming Feng
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Bojie Fu
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100049, China; State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China.
| | - Yuan Zhang
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Naiqing Pan
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100049, China; International Center for Climate and Global Change Research, School of Forestry and Wildlife Sciences, Auburn University, Auburn, AL 36832, USA
| | - Zhenzhong Zeng
- School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
| | - Hanqin Tian
- International Center for Climate and Global Change Research, School of Forestry and Wildlife Sciences, Auburn University, Auburn, AL 36832, USA
| | - Yihe Lyu
- Global Ecology Unit CREAF-CEAB-UAB, Spanish National Research Council, Cerdanyola del Vallès, Catalonia 08193, Spain
| | - Yongzhe Chen
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, CEA CNRS UVSQ, Gif-sur-Yvette 91191, France
| | - Yingping Wang
- Oceans and Atmosphere, Commonwealth Scientific and Industrial Research Organisation, Aspendale, Victoria 3195, Australia; South China Botanic Garden, Chinese Academy of Sciences, Guangzhou 510650, China
| | - Lu Zhang
- Land and Water, Commonwealth Scientific and Industrial Research Organisation, Black Mountain, Canberra, ACT 2601, Australia
| | - Lei Cheng
- School of Water Resources and Hydropower Engineering, Wuhan University, Wuhan 430072, China
| | - Fernando T Maestre
- Departamento de Ecología and Instituto Multidisciplinar para el Estudio del Medio "Ramon Margalef", Universidad de Alicante, Alicante 03690, Spain
| | - Marcos Fernández-Martínez
- Global Ecology Unit CREAF-CEAB-UAB, Spanish National Research Council, Cerdanyola del Vallès, Catalonia 08193, Spain
| | - Jordi Sardans
- Global Ecology Unit CREAF-CEAB-UAB, Spanish National Research Council, Cerdanyola del Vallès, Catalonia 08193, Spain
| | - Josep Peñuelas
- Global Ecology Unit CREAF-CEAB-UAB, Spanish National Research Council, Cerdanyola del Vallès, Catalonia 08193, Spain
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3
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Contribution of Climate Extremes to Variation in Potato Tuber Yield in Prince Edward Island. SUSTAINABILITY 2020. [DOI: 10.3390/su12124937] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
Agricultural management practices are responsible for almost two-thirds of the variations in potato tuber yield. In order to answer the research question about the remaining variability of the tuber yield, we hypothesized that climate extremes partly explain the missing component of variations of the tuber yield. Therefore, this research attempts to bridge this knowledge gap in order to generate a knowledge base for future strategies. A climate extreme dataset of the Prince Edward Island (PEI) was computed by averaging the data of five meteorological stations. In detail, changing patterns of 20 climate extreme indices were computed with ClimPACT2 software for 30 years (1989-2018) data of PEI. Statistical significance of the trends and their slope values were determined with the Mann-Kendall test and Sen’s slope estimates, respectively. Average of daily mean temperature (TMm), mean daily minimum temperature (TNm) and the occurrence of continuous dry days (CDD), significantly increased by 0.77 °C, 1.17 °C and 3.33 days., respectively, during the potato growing seasons (May-October) of the past three decades. For this period daily temperature range (DTR), frost days (FD), cold days (TX10p), cold nights (TN10p) and warmest days (TXx) showed decreasing trends of −1.01 °C, −3.75 days, −5.67 days, −11.40 nights, and −2.00 days, respectively. The principal component analysis showed that DTR, TXx, CDD, and TNm were the main factors affecting seasonal variations of tuber yield. The multiple regression model attributed ~39% of tuber yield variance to DTR, TXx, CDD, and TNm. However, these indices explained individually 21%, 19%, 16%, and 4% variation to the tuber yield, respectively. The remaining variation in the tuber yield explained by other yield affecting factors. The information generated from this study can be used for future planning about agricultural management strategies in the Island, for example, the provision of water resources for supplemental irrigation of crops during dry months.
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Zhang W, Zhou T. Increasing impacts from extreme precipitation on population over China with global warming. Sci Bull (Beijing) 2020; 65:243-252. [PMID: 36659178 DOI: 10.1016/j.scib.2019.12.002] [Citation(s) in RCA: 66] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2019] [Revised: 10/13/2019] [Accepted: 10/16/2019] [Indexed: 01/21/2023]
Abstract
Precipitation-related extremes are among the most impact-relevant consequences of a warmer climate, particularly for China, a region vulnerable to global warming and with a large population. Understanding the impacts and risks induced by future extreme precipitation changes is critical for mitigation and adaptation planning. Here, extreme precipitation changes under different levels of global warming and their associated impacts on populations in China are investigated using multimodel climate projections from the Coupled Model Intercomparison Project Phase 5 and population projections under Shared Socio-economic Pathways. Heavy precipitation would intensify with warming across China at a rate of 6.52% (5.22%-8.57%) per degree of global warming. The longest dry spell length would increase (decrease) south (north) of ~34°N. The low warming target of the Paris Agreement could substantially reduce the extreme precipitation related impacts compared to higher warming levels. For the area weighted average changes, the intensification in wet extremes could be reduced by 3.22%, 9.42% and 16.70% over China, and the lengthening of dry spells could be reduced by 0.72%, 4.75% and 5.31% in southeastern China, respectively, if global warming is limited to 1.5 °C as compared to 2, 3 and 4 °C. The Southeastern China is the hotspot of enhanced impacts due to the dense population. The impacts on populations induced by extreme precipitation changes are dominated by climate change, while future population redistribution plays a minor role.
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Affiliation(s)
- Wenxia Zhang
- State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Tianjun Zhou
- State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; Center for Excellence in Tibetan Plateau Earth Sciences, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China.
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Lu C, Qiu Z, Zhu Y, Lin BL. Scalable direct N-methylation of drug-like amines using 12CO 2/ 13CO 2 by simple inorganic base catalysis. Sci Bull (Beijing) 2019; 64:723-729. [PMID: 36659542 DOI: 10.1016/j.scib.2019.04.032] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2019] [Revised: 03/31/2019] [Accepted: 04/01/2019] [Indexed: 01/21/2023]
Abstract
With the growing urgency of potential catastrophic climate changes due to anthropogenic CO2 emissions, numerous efforts have been devoted to development of synthetic protocols using CO2 as a building block in organic reactions, but the general applicability to complex drug-like substrates remains a challenge. We develop a general protocol for scalable direct N-methylation of a wide-scope drug-like amines using CO2 and polymethylhydrosiloxane-a nontoxic, aerobically-stable hydrosilane considered as an industrial waste-via simple inorganic base catalysis. A rare application of the Sabatier principle in organic chemistry led to the discovery of cheap, nontoxic K3PO4 as an efficient catalyst. Preparations of a wide-scope drug-like amines with carbon-isotope label were also successfully achieved, enabling direct use of CO2 in studies of drug absorption, distribution, metabolism and excretion.
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Affiliation(s)
- Chunlei Lu
- School of Physical Science and Technology (SPST), ShanghaiTech University, Shanghai 201210, China; Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 200032, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zetian Qiu
- School of Physical Science and Technology (SPST), ShanghaiTech University, Shanghai 201210, China
| | - Yiling Zhu
- School of Physical Science and Technology (SPST), ShanghaiTech University, Shanghai 201210, China
| | - Bo-Lin Lin
- School of Physical Science and Technology (SPST), ShanghaiTech University, Shanghai 201210, China; Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 200032, China; University of Chinese Academy of Sciences, Beijing 100049, China.
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He Q, Zhou G, Lü X, Zhou M. Climatic suitability and spatial distribution for summer maize cultivation in China at 1.5 and 2.0 °C global warming. Sci Bull (Beijing) 2019; 64:690-697. [PMID: 36659651 DOI: 10.1016/j.scib.2019.03.030] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2018] [Revised: 01/10/2019] [Accepted: 01/12/2019] [Indexed: 01/21/2023]
Abstract
Evaluating climatic suitability of crop cultivation lays a foundation for agriculture coping with climate change scientifically. Herein, we analyse changes in the climatically suitable distribution of summer maize cultivation in China at 1.5 °C (GW1.5) and 2.0 °C (GW2.0) global warming in the future according to the temperature control targets set by the Paris Agreement. Compared with the reference period (1971-2000), the summer maize cultivation climatically suitable region (CSR) in China mainly shifts eastwards, and its acreage significantly decreases at both GW1.5 and GW2.0. Despite no dramatic changes in the CSR spatial pattern, there are considerable decreases in the acreages of optimum and suitable regions (the core of the main producing region), indicating that half-a-degree more global warming is unfavourable for summer maize production in China's main producing region. When the global warming threshold increases from GW1.5 to GW2.0, the centres-of-gravity of optimum areas shift northeastward under RCP4.5 and RCP8.5, the centres-of-gravity of both suitable and less suitable areas shift northwestward, though the northward trend is more prominent for the less suitable areas, and the centre-of-gravity of unsuitable areas shifts southeastward. Generally, half-a-degree more global warming drives the cultivable areas of summer maize to shift northward in China, while the west region shows a certain potential for expansion of summer maize cultivation.
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Affiliation(s)
- Qijin He
- College of Resources and Environmental Sciences, China Agricultural University, Beijing 100193, China
| | - Guangsheng Zhou
- Chinese Academy of Meteorological Sciences, Beijing 100081, China.
| | - Xiaomin Lü
- Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Mengzi Zhou
- Chinese Academy of Meteorological Sciences, Beijing 100081, China
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7
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Liu W, Sun F. Increased adversely-affected population from water shortage below normal conditions in China with anthropogenic warming. Sci Bull (Beijing) 2019; 64:567-569. [PMID: 36659622 DOI: 10.1016/j.scib.2019.03.007] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2018] [Revised: 01/18/2019] [Accepted: 01/19/2019] [Indexed: 01/21/2023]
Affiliation(s)
- Wenbin Liu
- Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Fubao Sun
- Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 101408, China; Center for Water Resources Research, Chinese Academy of Sciences, Beijing 100101, China; Ecology Institute of Qilian Mountain, Hexi University, Zhangye 734000, China.
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8
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Teng F, He J, Dong W, Pan X. A biased fairness assessment against developing countries. Sci Bull (Beijing) 2019; 64:367-369. [PMID: 36659724 DOI: 10.1016/j.scib.2019.03.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Affiliation(s)
- Fei Teng
- Institute of Energy, Environment and Economy, Tsinghua Univesity, Beijing 100084, China.
| | - Jiankun He
- Institute of Energy, Environment and Economy, Tsinghua Univesity, Beijing 100084, China
| | - Wenjie Dong
- School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519087, China
| | - Xunzhang Pan
- Academy of Chinese Energy Strategy, China University of Petroleum, Beijing 102249, China
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9
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Jiang K, He C, Qu C, Dai C, Zhang Y, Chen S, Xiang P. Are China's Nationally Determined Contributions (NDCs) so bad? Sci Bull (Beijing) 2019; 64:364-366. [PMID: 36659723 DOI: 10.1016/j.scib.2019.01.005] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Affiliation(s)
- Kejun Jiang
- Energy Research Institute National Development and Reform Commission, Beijing 100038, China.
| | - Chenmin He
- College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Chenfei Qu
- School of Environment, Tsinghua University, Beijing 100089, China
| | - Chunyan Dai
- School of Management, Chongqing Technology and Business University, Chongqing 400020, China
| | - Yifei Zhang
- Shanghai University of International Business and Economics, Shanghai 201620, China
| | - Sha Chen
- College of Environmental and Energy Engineering, Beijing University of Technology, Beijing 100124, China
| | - Pianpian Xiang
- School of Environment, Tsinghua University, Beijing 100089, China
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Global warming weakening the inherent stability of glaciers and permafrost. Sci Bull (Beijing) 2019; 64:245-253. [PMID: 36659714 DOI: 10.1016/j.scib.2018.12.028] [Citation(s) in RCA: 72] [Impact Index Per Article: 14.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2018] [Revised: 12/25/2018] [Accepted: 12/29/2018] [Indexed: 01/21/2023]
Abstract
The Cryosphere has been undergoing a worldwide retreat, as seen in the decrease in the areal extent and volume of glaciers and in the areal extent of permafrost. This paper presents a systematic examination of the inherent stability changes of glaciers and permafrost caused by warming. Various study results suggest that over the past 30 years, the internal temperature of glaciers and permafrost exhibits an overall accelerating warming trend. The warming rate peaked in the mid-2000s and slowed slightly for several years afterward. In recent years, however, the warming rate has seemed to pick up again. The warming of glaciers and permafrost has exerted great impact on their stability, displayed as intensified melting, increased glacier surging, enlargement of supraglacial lakes, and increased permafrost degradation. Even without a future temperature increase, some glaciers will continue to shrink, and the number of surging glaciers will increase. The transition from low-temperature to high-temperature permafrost is a noticeable warning sign of a comprehensive degradation of permafrost. These results indicate that "warming" glaciers and permafrost will exert significant impacts on the hydrology, ecology, and stability of engineering in cold regions.
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Li H, Chen H, Wang H, Yu E. Future precipitation changes over China under 1.5 °C and 2.0 °C global warming targets by using CORDEX regional climate models. THE SCIENCE OF THE TOTAL ENVIRONMENT 2018; 640-641:543-554. [PMID: 29864667 DOI: 10.1016/j.scitotenv.2018.05.324] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2018] [Revised: 05/25/2018] [Accepted: 05/25/2018] [Indexed: 06/08/2023]
Abstract
This study aims to characterize future changes in precipitation extremes over China based on regional climate models (RCMs) participating in the Coordinated Regional Climate Downscaling Experiment (CORDEX)-East Asia project. The results of five RCMs involved in CORDEX-East Asia project that driven by HadGEM2-AO are compared with the simulation of CMA-RegCM driven by BCC-CSM1.1. Eleven precipitation extreme indices that developed by the Expert Team on Climate Change Detection and Indices are employed to evaluate precipitation extreme changes over China. Generally, RCMs can reproduce their spatiotemporal characteristics over China in comparison with observations. For future climate projections, RCMs indicate that both the occurrence and intensity of precipitation extremes in most regions of China will increase when the global temperature increases by 1.5/2.0 °C. The yearly maximum five-day precipitation (RX5D) averaged over China is reported to increase by 4.4% via the CMA-RegCM under the 1.5 °C warming in comparison with the baseline period (1986-2005); however, a relatively large increase of 11.1% is reported by the multi-model ensemble median (MME) when using the other five models. Furthermore, the reoccurring risks of precipitation extremes over most regions of China will further increase due to the additional 0.5 °C warming. For example, RX5D will further increase by approximately 8.9% over NWC, 3.8% over NC, 2.3% over SC, and approximately 1.0% over China. Extremes, such as the historical 20-year return period event of yearly maximum one-day precipitation (RX1D) and RX5D, will become more frequent, with occurrences happening once every 8.8 years (RX1D) and 11.5 years (RX5D) under the 1.5 °C warming target, and there will be two fewer years due to the additional 0.5 °C warming. In addition, the intensity of these events will increase by approximately 9.2% (8.5%) under the 1.5 °C warming target and 12.6% (11.0%) under the 2.0 °C warming target for RX1D (RX5D).
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Affiliation(s)
- Huixin Li
- Nansen-Zhu International Research Centre, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China
| | - Huopo Chen
- Nansen-Zhu International Research Centre, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China; Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing, China.
| | - Huijun Wang
- Nansen-Zhu International Research Centre, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China; Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing, China
| | - Entao Yu
- Nansen-Zhu International Research Centre, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China; Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing, China
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Li W, Jiang Z, Zhang X, Li L, Sun Y. Additional risk in extreme precipitation in China from 1.5 °C to 2.0 °C global warming levels. Sci Bull (Beijing) 2018; 63:228-234. [PMID: 36659011 DOI: 10.1016/j.scib.2017.12.021] [Citation(s) in RCA: 66] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2017] [Revised: 11/12/2017] [Accepted: 12/13/2017] [Indexed: 01/21/2023]
Abstract
To avoid dangerous climate change impact, the Paris Agreement sets out two ambitious goals: to limit the global warming to be well below 2 °C and to pursue effort for the global warming to be below 1.5 °C above the pre-industrial level. As climate change risks may be region-dependent, changes in magnitude and probability of extreme precipitation over China are investigated under those two global warming levels based on simulations from the Coupled Model Inter-Comparison Projects Phase 5. The focus is on the added changes due to the additional half a degree warming from 1.5 °C to 2 °C. Results show that regional average changes in the magnitude do not depend on the return periods with a relative increase around 7% and 11% at the 1.5 °C and 2 °C global warming levels, respectively. The additional half a degree global warming adds an additional increase in the magnitude by nearly 4%. The regional average changes in term of occurrence probabilities show dependence on the return periods, with rarer events (longer return periods) having larger increase of risk. For the 100-year historical event, the probability is projected to increase by a factor of 1.6 and 2.4 at the 1.5 °C and 2 °C global warming levels, respectively. The projected changes in extreme precipitation are independent of the RCP scenarios.
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Affiliation(s)
- Wei Li
- Key Laboratory of Meteorological Disaster of Ministry of Education, Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Zhihong Jiang
- Joint International Research Laboratory of Climate and Environment Change, Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster, Nanjing University of Information Science and Technology, Nanjing 210044, China.
| | - Xuebin Zhang
- Climate Research Division, Environment and Climate Change Canada, Toronto, Ontario M3H 5T4, Canada
| | - Laurent Li
- Laboratoire de Météorologie Dynamique, CNRS, Sorbonne Universités, UPMC Université Paris 06, Paris, France
| | - Ying Sun
- National Climate Center, Laboratory for Climate Studies, China Meteorological Administration, Beijing 100812, China
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