Outlook for Exploiting Artificial Intelligence in the Earth and Environmental Sciences

Author:

Boukabara Sid-Ahmed1,Krasnopolsky Vladimir2,Penny Stephen G.3,Stewart Jebb Q.4,McGovern Amy5,Hall David6,Ten Hoeve John E.7,Hickey Jason8,Allen Huang Hung-Lung9,Williams John K.10,Ide Kayo11,Tissot Philippe12,Haupt Sue Ellen13,Casey Kenneth S.14,Oza Nikunj15,Geer Alan J.16,Maddy Eric S.17,Hoffman Ross N.18

Affiliation:

1. NOAA/NESDIS/Center for Satellite Applications and Research, College Park, Maryland

2. NOAA/Environmental Modeling Center, College Park, Maryland

3. Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, and Physical Sciences Division, NOAA/Earth System Research Laboratories, Boulder, Colorado

4. NOAA/Earth System Research Laboratories, Boulder, Colorado

5. School of Computer Science, University of Oklahoma, Norman, Oklahoma

6. NVIDIA Corporation, Lafayette, Colorado

7. NOAA/National Weather Service, Silver Spring, Maryland

8. Google Research, Kirkland, Washington

9. Space Science and Engineering Center, University of Wisconsin at Madison, Madison, Wisconsin

10. The Weather Company, an IBM Business, Andover, Massachusetts

11. University of Maryland, College Park, College Park, Maryland

12. Conrad Blucher Institute, Texas A&M University–Corpus Christi, Corpus Christi, Texas

13. Research Applications Laboratory, NCAR, Boulder, Colorado

14. NOAA/NESDIS/National Centers for Environmental Information, Silver Spring, Maryland

15. Data Sciences Group, NASA Ames Research Center, Moffett Field, California

16. ECMWF, Reading, United Kingdom

17. Riverside Technology Inc. at NOAA/NESDIS/Center for Satellite Applications and Research, College Park, Maryland

18. Cooperative Institute for Satellite Earth System Studies, University of Maryland, College Park, at NOAA/NESDIS/Center for Satellite Applications and Research, College Park, Maryland

Abstract

AbstractPromising new opportunities to apply artificial intelligence (AI) to the Earth and environmental sciences are identified, informed by an overview of current efforts in the community. Community input was collected at the first National Oceanic and Atmospheric Administration (NOAA) workshop on “Leveraging AI in the Exploitation of Satellite Earth Observations and Numerical Weather Prediction” held in April 2019. This workshop brought together over 400 scientists, program managers, and leaders from the public, academic, and private sectors in order to enable experts involved in the development and adaptation of AI tools and applications to meet and exchange experiences with NOAA experts. Paths are described to actualize the potential of AI to better exploit the massive volumes of environmental data from satellite and in situ sources that are critical for numerical weather prediction (NWP) and other Earth and environmental science applications. The main lessons communicated from community input via active workshop discussions and polling are reported. Finally, recommendations are presented for both scientists and decision-makers to address some of the challenges facing the adoption of AI across all Earth science.

Publisher

American Meteorological Society

Subject

Atmospheric Science

Cited by 47 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3