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欧研究开发的AI模型可检测农业相关的多种气候灾害 快报文章
气候变化快报，2025年第8期
作者:  董利苹 杜海霞
Microsoft Word(16Kb)  |  收藏  |  浏览/下载：422/0  |  提交时间：2025/04/20
Expert-driven  Artificial Intelligence Model  Detect  Climate Hazards  
国际组织分析气候变化对可再生能源供需的影响 快报文章
气候变化快报，2025年第6期
作者:  廖琴
Microsoft Word(17Kb)  |  收藏  |  浏览/下载：391/0  |  提交时间：2025/03/20
Climate-driven  Renewable Energy  Energy Demand  
美国资助2278万美元推进与水资源相关的气候影响研究 快报文章
资源环境快报，2024年第20期
作者:  魏艳红
Microsoft Word(18Kb)  |  收藏  |  浏览/下载：482/1  |  提交时间：2024/10/30
NOAA  Water-driven Climate Impacts  Prediction and Resilience Strategies  
基于生态系统的渔业管理可以在短期内阻止气候驱动的崩溃 快报文章
气候变化快报，2020年第19期
作者:  董利苹
Microsoft Word(14Kb)  |  收藏  |  浏览/下载：416/1  |  提交时间：2020/09/29
Ecosystem-based Fisheries Management  Climate-driven  Collapse  Bering Sea  
Abrupt increase in harvested forest area over Europe after 2015 期刊论文
NATURE, 2020, 583 (7814) : 72-+
作者:  Guido Ceccherini;  Gregory Duveiller;  Giacomo Grassi;  Guido Lemoine;  Valerio Avitabile;  Roberto Pilli;  Alessandro Cescatti
收藏  |  浏览/下载：51/0  |  提交时间：2020/07/06

Fine-scale satellite data are used to quantify forest harvest rates in 26 European countries, finding an increase in harvested forest area of 49% and an increase in biomass loss of 69% between 2011-2015 and 2016-2018.


Forests provide a series of ecosystem services that are crucial to our society. In the European Union (EU), forests account for approximately 38% of the total land surface(1). These forests are important carbon sinks, and their conservation efforts are vital for the EU'  s vision of achieving climate neutrality by 2050(2). However, the increasing demand for forest services and products, driven by the bioeconomy, poses challenges for sustainable forest management. Here we use fine-scale satellite data to observe an increase in the harvested forest area (49 per cent) and an increase in biomass loss (69 per cent) over Europe for the period of 2016-2018 relative to 2011-2015, with large losses occurring on the Iberian Peninsula and in the Nordic and Baltic countries. Satellite imagery further reveals that the average patch size of harvested area increased by 34 per cent across Europe, with potential effects on biodiversity, soil erosion and water regulation. The increase in the rate of forest harvest is the result of the recent expansion of wood markets, as suggested by econometric indicators on forestry, wood-based bioenergy and international trade. If such a high rate of forest harvest continues, the post-2020 EU vision of forest-based climate mitigation may be hampered, and the additional carbon losses from forests would require extra emission reductions in other sectors in order to reach climate neutrality by 2050(3).


  
Natural resources and conflict: A meta-analysis of the empirical literature 期刊论文
ECOLOGICAL ECONOMICS, 2020, 172
作者:  Vesco, Paola;  Dasgupta, Shouro;  De Cian, Enrica;  Carraro, Carlo
收藏  |  浏览/下载：19/0  |  提交时间：2020/07/02
Natural resources  Conflict  Meta-analysis  Meta-research  Climate-conflict nexus  Resources-driven issues  
Comparative assessment of environmental variables and machine learning algorithms for maize yield prediction in the US Midwest 期刊论文
ENVIRONMENTAL RESEARCH LETTERS, 2020, 15 (6)
作者:  Kang, Yanghui;  Ozdogan, Mutlu;  Zhu, Xiaojin;  Ye, Zhiwei;  Hain, Christopher;  Anderson, Martha
收藏  |  浏览/下载：29/0  |  提交时间：2020/07/02
crop yields  climate impact  machine learning  deep learning  data-driven  
Patterns and trends of Northern Hemisphere snow mass from 1980 to 2018 期刊论文
NATURE, 2020, 581 (7808) : 294-+
作者:  Ibrahim, Nizar;  Maganuco, Simone;  Dal Sasso, Cristiano;  Fabbri, Matteo;  Auditore, Marco;  Bindellini, Gabriele;  Martill, David M.;  Zouhri, Samir;  Mattarelli, Diego A.;  Unwin, David M.;  Wiemann, Jasmina;  Bonadonna, Davide;  Amane, Ayoub;  Jakubczak, Juliana;  Joger, Ulrich;  Lauder, George V.;  Pierce, Stephanie E.
收藏  |  浏览/下载：34/0  |  提交时间：2020/05/25

Warming surface temperatures have driven a substantial reduction in the extent and duration of Northern Hemisphere snow cover(1-3). These changes in snow cover affect Earth'  s climate system via the surface energy budget, and influence freshwater resources across a large proportion of the Northern Hemisphere(4-6). In contrast to snow extent, reliable quantitative knowledge on seasonal snow mass and its trend is lacking(7-9). Here we use the new GlobSnow 3.0 dataset to show that the 1980-2018 annual maximum snow mass in the Northern Hemisphere was, on average, 3,062 +/- 35 billion tonnes (gigatonnes). Our quantification is for March (the month that most closely corresponds to peak snow mass), covers non-alpine regions above 40 degrees N and, crucially, includes a bias correction based on in-field snow observations. We compare our GlobSnow 3.0 estimates with three independent estimates of snow mass, each with and without the bias correction. Across the four datasets, the bias correction decreased the range from 2,433-3,380 gigatonnes (mean 2,867) to 2,846-3,062 gigatonnes (mean 2,938)-a reduction in uncertainty from 33% to 7.4%. On the basis of our bias-corrected GlobSnow 3.0 estimates, we find different continental trends over the 39-year satellite record. For example, snow mass decreased by 46 gigatonnes per decade across North America but had a negligible trend across Eurasia  both continents exhibit high regional variability. Our results enable a better estimation of the role of seasonal snow mass in Earth'  s energy, water and carbon budgets.


Applying a bias correction to a state-of-the-art dataset covering non-alpine regions of the Northern Hemisphere and to three other datasets yields a more constrained quantification of snow mass in March from 1980 to 2018.


  
Extreme rainfall triggered the 2018 rift eruption at Kilauea Volcano 期刊论文
NATURE, 2020, 580 (7804) : 491-+
作者:  Cloutier, Richard;  Clement, Alice M.;  Lee, Michael S. Y.;  Noel, Roxanne;  Bechard, Isabelle;  Roy, Vincent;  Long, John A.
收藏  |  浏览/下载：60/0  |  提交时间：2020/05/13

The May 2018 rift intrusion and eruption of Kilauea Volcano, Hawai'  i, represented one of its most extraordinary eruptive sequences in at least 200 years, yet the trigger mechanism remains elusive(1). The event was preceded by several months of anomalously high precipitation. It has been proposed that rainfall can modulate shallow volcanic activity(2,3), but it remains unknown whether it can have impacts at the greater depths associated with magma transport. Here we show that immediately before and during the eruption, infiltration of rainfall into Kilauea Volcano'  s subsurface increased pore pressure at depths of 1 to 3 kilometres by 0.1 to 1 kilopascals, to its highest pressure in almost 50 years. We propose that weakening and mechanical failure of the edifice was driven by changes in pore pressure within the rift zone, prompting opportunistic dyke intrusion and ultimately facilitating the eruption. A precipitation-induced eruption trigger is consistent with the lack of precursory summit inflation, showing that this intrusion-unlike others-was not caused by the forceful intrusion of new magma into the rift zone. Moreover, statistical analysis of historic eruption occurrence suggests that rainfall patterns contribute substantially to the timing and frequency of Kilauea'  s eruptions and intrusions. Thus, volcanic activity can be modulated by extreme rainfall triggering edifice rock failure-a factor that should be considered when assessing volcanic hazards. Notably, the increasingly extreme weather patterns associated with ongoing anthropogenic climate change could increase the potential for rainfall-triggered volcanic phenomena worldwide.


Immediately before and during the eruption of Ki & x304  lauea Volcano in May 2018, anomalously high rainfall increased the pore pressure in the subsurface to its highest level in 50 years, causing weakening and mechanical failure of the edifice.


  
The projected timing of abrupt ecological disruption from climate change 期刊论文
NATURE, 2020, 580 (7804) : 496-+
作者:  Gorgulla, Christoph;  Boeszoermenyi, Andras;  Wang, Zi-Fu;  Fischer, Patrick D.;  Coote, Paul W.;  Padmanabha Das, Krishna M.;  Malets, Yehor S.;  Radchenko, Dmytro S.;  Moroz, Yurii S.;  Scott, David A.;  Fackeldey, Konstantin;  Hoffmann, Moritz;  Iavniuk, Iryna;  Wagner, Gerhard;  Arthanari, Haribabu
收藏  |  浏览/下载：80/0  |  提交时间：2020/05/13

As anthropogenic climate change continues the risks to biodiversity will increase over time, with future projections indicating that a potentially catastrophic loss of global biodiversity is on the horizon(1-3). However, our understanding of when and how abruptly this climate-driven disruption of biodiversity will occur is limited because biodiversity forecasts typically focus on individual snapshots of the future. Here we use annual projections (from 1850 to 2100) of temperature and precipitation across the ranges of more than 30,000 marine and terrestrial species to estimate the timing of their exposure to potentially dangerous climate conditions. We project that future disruption of ecological assemblages as a result of climate change will be abrupt, because within any given ecological assemblage the exposure of most species to climate conditions beyond their realized niche limits occurs almost simultaneously. Under a high-emissions scenario (representative concentration pathway (RCP) 8.5), such abrupt exposure events begin before 2030 in tropical oceans and spread to tropical forests and higher latitudes by 2050. If global warming is kept below 2 degrees C, less than 2% of assemblages globally are projected to undergo abrupt exposure events of more than 20% of their constituent species  however, the risk accelerates with the magnitude of warming, threatening 15% of assemblages at 4 degrees C, with similar levels of risk in protected and unprotected areas. These results highlight the impending risk of sudden and severe biodiversity losses from climate change and provide a framework for predicting both when and where these events may occur.


Using annual projections of temperature and precipitation to estimate when species will be exposed to potentially harmful climate conditions reveals that disruption of ecological assemblages as a result of climate change will be abrupt and could start as early as the current decade.