Journal Article

FZJ-2024-06919

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Exascale Computing and Data Handling: Challenges and Opportunities for Weather and Climate Prediction

Govett, M. (Corresponding author) ; Bah, B. ; Bauer, P. ; Berod, D. ; Bouchet, V. ; Corti, S. ; Davis, C. ; Duan, Y. ; Graham, T. ; Honda, Y. ; Hines, A. ; Jean, M. ; Ishida, J. ; Lawrence, B. ; Li, J. ; Luterbacher, J. ; Muroi, C. ; Rowe, K. ; Schultz, M.FZJ* ; Visbeck, M. ; Williams, K.

2024
ASM Boston, Mass.

This record in other databases:    

Please use a persistent id in citations: doi:10.1175/BAMS-D-23-0220.1

Abstract: The emergence of exascale computing and artificial intelligence offer tremendous potential to significantly advance Earth system prediction capabilities. However, enormous challenges must be overcome to adapt models and prediction systems to use these new technologies effectively. A 2022 WMO report on exascale computing recommends “urgency in dedicating efforts and attention to disruptions associated with evolving computing technologies that will be increasingly difficult to overcome, threatening continued advancements in weather and climate prediction capabilities.” Further, the explosive growth in data from observations, model and ensemble output, and postprocessing threatens to overwhelm the ability to deliver timely, accurate, and precise information needed for decision-making. Artificial intelligence (AI) offers untapped opportunities to alter how models are developed, observations are processed, and predictions are analyzed and extracted for decision-making. Given the extraordinarily high cost of computing, growing complexity of prediction systems, and increasingly unmanageable amount of data being produced and consumed, these challenges are rapidly becoming too large for any single institution or country to handle. This paper describes key technical and budgetary challenges, identifies gaps and ways to address them, and makes a number of recommendations.

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Contributing Institute(s):

1. Jülich Supercomputing Center (JSC)

Research Program(s):

1. 5111 - Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups (POF4-511) (POF4-511)
2. Earth System Data Exploration (ESDE) (ESDE)

Appears in the scientific report 2024

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Database coverage:
; Clarivate Analytics Master Journal List ; Current Contents - Physical, Chemical and Earth Sciences ; Ebsco Academic Search ; Essential Science Indicators ; IF >= 5 ; JCR ; National-Konsortium ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection

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