Climate Informatics Workshop
气候信息学研讨会
基本信息
- 批准号:1345052
- 负责人:
- 金额:$ 9.07万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2013
- 资助国家:美国
- 起止时间:2013-09-15 至 2018-08-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Understanding and responding to climate change is a key scientific and societal challenge of the 21st century. Recent advances in satellites and environmental sensors have made it possible to gather vast quantities of data concerning temperature, sea ice, sea level, rainfall, vegetation, etc. There is an urgent need for scientific and technical expertise for developing and effectively applying computational tools that can make use of such data to build increasingly accurate predictive models that offer insights to inform our understanding of, and response to, climate change. This award supports a series of three workshops on Climate Informatics, an emerging discipline at the intersection of climate sciences and data sciences. The workshops, through a combination of tutorials that introduce climate scientists and data scientists to each other's disciplines, invited talks by established researchers in climate informatics, breakout sessions and for identifying research challenges and opportunities for interdisciplinary collaborations, serve a critically important role in building a vibrant Climate Informatics research community. The award provides support for the participation of approximately 60 to graduate students in each of the three workshops. The workshops contribute to the education and interdisciplinary training of a diverse workforce in STEM areas that span Climate Sciences and Data Sciences (including Machine Learning, Data Mining, Inference, Decision Making) as well as efforts to broaden the participation of women and other underrepresented groups in STEM research and education. Additional information about the Climate Informatics Workshop Series can be found at: https://sites.google.com/site/1stclimateinformatics/
理解和应对气候变化是21世纪科学和社会的一项重大挑战。卫星和环境传感器的最新进展使人们能够收集大量有关温度、海冰、海平面、降雨、植被等方面的数据。我们迫切需要科学和技术专业知识来开发和有效地应用计算工具,这些计算工具可以利用这些数据来建立越来越准确的预测模型,从而为我们理解和应对气候变化提供见解。该奖项支持一系列关于气候信息学的三个研讨会,气候信息学是气候科学和数据科学交叉的新兴学科。这些研讨会通过将气候科学家和数据科学家介绍给彼此学科的教程相结合,邀请了气候信息学领域的知名研究人员进行演讲,分组会议以及确定跨学科合作的研究挑战和机遇,在建立一个充满活力的气候信息学研究社区方面发挥了至关重要的作用。该奖项为参加三个讲习班的大约60名研究生提供支持。这些研讨会有助于教育和跨学科培训跨越气候科学和数据科学(包括机器学习、数据挖掘、推理、决策)的STEM领域的多样化劳动力,并努力扩大妇女和其他代表性不足的群体在STEM研究和教育中的参与。有关气候信息学系列研讨会的更多信息,请访问:https://sites.google.com/site/1stclimateinformatics/
项目成果
期刊论文数量(2)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Proceedings of the 7th International Workshop on Climate Informatics: CI 2017
第七届国际气候信息学研讨会论文集:CI 2017
- DOI:10.5065/d6222sh7
- 发表时间:2017
- 期刊:
- 影响因子:0
- 作者:Eds.: Lyubchich, V.;Oza, N. C.;Rhines, A.;Szekely, E.;Series Eds.: Ebert-Uphoff, I.;Monteleoni, C.;Nychka, D.
- 通讯作者:Nychka, D.
Proceedings of the Sixth International Workshop on Climate Informatics: CI 2016
第六届国际气候信息学研讨会论文集:CI 2016
- DOI:10.5065/d6k072n6
- 发表时间:2016
- 期刊:
- 影响因子:0
- 作者:Eds.: Banerjee, A.;Ding, W.;Dy, J.;Lyubchich, V.;Rhines, A.;Series Eds.: Ebert-Uphoff, I.;Monteleoni, C.;Nychka, D.
- 通讯作者:Nychka, D.
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Claire Monteleoni其他文献
Machine learning for the physics of climate
用于气候物理学的机器学习
- DOI:
10.1038/s42254-024-00776-3 - 发表时间:
2024-11-11 - 期刊:
- 影响因子:39.500
- 作者:
Annalisa Bracco;Julien Brajard;Henk A. Dijkstra;Pedram Hassanzadeh;Christian Lessig;Claire Monteleoni - 通讯作者:
Claire Monteleoni
Pushing the frontiers in climate modelling and analysis with machine learning
利用机器学习推动气候建模与分析的前沿发展
- DOI:
10.1038/s41558-024-02095-y - 发表时间:
2024-08-23 - 期刊:
- 影响因子:27.100
- 作者:
Veronika Eyring;William D. Collins;Pierre Gentine;Elizabeth A. Barnes;Marcelo Barreiro;Tom Beucler;Marc Bocquet;Christopher S. Bretherton;Hannah M. Christensen;Katherine Dagon;David John Gagne;David Hall;Dorit Hammerling;Stephan Hoyer;Fernando Iglesias-Suarez;Ignacio Lopez-Gomez;Marie C. McGraw;Gerald A. Meehl;Maria J. Molina;Claire Monteleoni;Juliane Mueller;Michael S. Pritchard;David Rolnick;Jakob Runge;Philip Stier;Oliver Watt-Meyer;Katja Weigel;Rose Yu;Laure Zanna - 通讯作者:
Laure Zanna
Claire Monteleoni的其他文献
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{{ truncateString('Claire Monteleoni', 18)}}的其他基金
EAGER: Novel sampling algorithms for scaling up spectral methods for unsupervised learning
EAGER:用于扩大无监督学习光谱方法的新型采样算法
- 批准号:
1650080 - 财政年份:2016
- 资助金额:
$ 9.07万 - 项目类别:
Standard Grant
EAGER: Collaborative Research: Learning Relations between Extreme Weather Events and Planet-Wide Environmental Trends
EAGER:合作研究:学习极端天气事件与全球环境趋势之间的关系
- 批准号:
1451954 - 财政年份:2014
- 资助金额:
$ 9.07万 - 项目类别:
Standard Grant
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