Deep Learning Provides Substantial Improvements to County‐Level Fire Weather Forecasting Over the Western United States-Reference-Cited by-同舟云学术

Deep Learning Provides Substantial Improvements to County‐Level Fire Weather Forecasting Over the Western United States

Published:2022-10 Issue:10 Volume:14 Page:
ISSN:1942-2466
Container-title:Journal of Advances in Modeling Earth Systems
language:en
Short-container-title:J Adv Model Earth Syst

Author:

Son Rackhun¹²^ORCID,Ma Po‐Lun³^ORCID,Wang Hailong³^ORCID,Rasch Philp J.³⁴^ORCID,Wang Shih‐Yu (Simon)⁵^ORCID,Kim Hyungjun⁶⁷⁸^ORCID,Jeong Jee‐Hoon⁹^ORCID,Lim Kyo‐Sun Sunny¹⁰^ORCID,Yoon Jin‐Ho²^ORCID

Affiliation:

1. Department of Biogeochemical Integration Max Planck Institute for Biogeochemistry Jena Germany

2. School of Earth Sciences and Environmental Engineering Gwangju Institute of Science and Technology Gwangju Korea

3. Pacific Northwest National Laboratory Richland WA USA

4. Department of Atmospheric Science University of Washington Seattle WA USA

5. Department of Plants, Soils, and Climate Utah State University Logan UT USA

6. Moon Soul Graduate School of Future Strategy Korea Advanced Institute of Science and Technology Daejeon Korea

7. Department of Civil and Environmental Engineering Korea Advanced Institute of Science and Technology Daejeon Korea

8. Institute of Industrial Science The University of Tokyo Tokyo Japan

9. Faculty of Earth and Environmental Sciences Chonnam National University Gwangju Korea

10. Department of Atmospheric Sciences, Center for Atmospheric REmote sensing (CARE) Kyungpook National University Daegu Korea

Funder

Biological and Environmental Research

National Research Foundation of Korea

Publisher

American Geophysical Union (AGU)

Subject

General Earth and Planetary Sciences,Environmental Chemistry,Global and Planetary Change

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2022MS002995

Reference54 articles.

1. On Pixel-Wise Explanations for Non-Linear Classifier Decisions by Layer-Wise Relevance Propagation

2. The quiet revolution of numerical weather prediction

3. The 2018 Camp Fire: Meteorological Analysis Using In Situ Observations and Numerical Simulations

4. DeepDT: Generative Adversarial Network for High-Resolution Climate Prediction

5. Computational modeling of extreme wildland fire events: A synthesis of scientific understanding with applications to forecasting, land management, and firefighter safety

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