Outlook for Exploiting Artificial Intelligence in the Earth and Environmental Sciences

Boukabara, Sid-Ahmed; Krasnopolsky, Vladimir; Penny, Stephen G.; Stewart, Jebb Q.; McGovern, Amy; Hall, David; Ten Hoeve, John E.; Hickey, Jason; Allen Huang, Hung-Lung; Williams, John K.; Ide, Kayo; Tissot, Philippe; Haupt, Sue Ellen; Casey, Kenneth S.; Oza, Nikunj; Geer, Alan J.; Maddy, Eric S.; Hoffman, Ross N.

doi:10.1175/BAMS-D-20-0031.1

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Outlook for Exploiting Artificial Intelligence in the Earth and Environmental Sciences

2021
By Boukabara, Sid-Ahmed ; Krasnopolsky, Vladimir ; Penny, Stephen G. ; ...

Details

Journal Title:

Bulletin of the American Meteorological Society
Personal Author:

Boukabara, Sid-Ahmed ; Krasnopolsky, Vladimir ; Penny, Stephen G. ; Stewart, Jebb Q. ; McGovern, Amy ; Hall, David ; Ten Hoeve, John E. ; Hickey, Jason ; Allen Huang, Hung-Lung ; Williams, John K. ; Ide, Kayo ; Tissot, Philippe ; Haupt, Sue Ellen ; Casey, Kenneth S. ; Oza, Nikunj ; Geer, Alan J. ; Maddy, Eric S. ; Hoffman, Ross N.
NOAA Program & Office:

OAR (Oceanic and Atmospheric Research) ; GSL (Global Systems Laboratory) ; CIRES (Cooperative Institute for Research in Environmental Sciences) ; CISESS (Cooperative Institute for Satellite Earth System Studies) ; WPO (Weather Program Office) ; NESDIS (National Environmental Satellite, Data, and Information Service) ; STAR (Center for Satellite Applications and Research) ; NCEI (National Centers for Environmental Information)
Description:

Promising 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.
Keywords:

Accurate Artificial Intelligence Climate Data Assimilation Data Mining Forecasting Forecasts Machine Learning Meteorology & Atmospheric Sciences Models Neural-network Numerical Parameterization Remote Sensing Satellite Observations System Weak Weather Weather Prediction
Source:

Bulletin of the American Meteorological Society, 102(5)
DOI:

https://doi.org/10.1175/BAMS-D-20-0031.1
Document Type:

Journal Article
Rights Information:

CC BY-NC-ND
Compliance:

Submitted
Main Document Checksum:

urn:sha256:e0777b85a7c42040c0c30072fa845e172e8f6835ec8054eb1350d218f691bca7
Download URL:

https://repository.library.noaa.gov/view/noaa/30973/noaa_30973_DS1.pdf
File Type:

[PDF - 2.33 MB ]

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