High-Performance Computing for Atmospheric Modeling

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Atmospheric Techniques, Instruments, and Modeling".

Deadline for manuscript submissions: closed (19 April 2024) | Viewed by 1156

Special Issue Editors


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Guest Editor
Jülich Supercomputing Centre, Forschungszentrum Jülich, 52425 Jülich, Germany
Interests: atmospheric science; computational science; Earth system modeling; high performance computing
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou 510006, China
Interests: inverse problems; high-performance computing; AI for science; optimal experimental design

Special Issue Information

Dear Colleagues,

The primary objectives of atmospheric modeling are to improve our understanding, prediction, and assessment of atmospheric phenomena, ranging from short-term weather to long-term climate changes, air quality, atmospheric composition, and the interactions between the atmosphere and other components of the Earth system.

High-performance computing (HPC) empowers atmospheric modeling by enabling higher resolutions, complex configurations, ensemble simulations, data assimilation, parameter space exploration, and faster model development. It enhances the accuracy, realism, and scientific understanding of atmospheric processes, thereby improving weather prediction, climate projections, air quality assessments, and our overall knowledge of the Earth's atmosphere.

Developing and maintaining the complex software of atmospheric models for current and future HPC systems is challenging. Collaborations between atmospheric scientists and computational experts are crucial for successfully utilizing HPC in atmospheric modeling.

We invite scientists to contribute original research and review articles on future directions for HPC for atmospheric modeling. Topics of interest include, but are not limited to, the following:

  • Computational complexity and efficient HPC implementation of numerical algorithms used to simulate the behavior of the atmosphere;
  • Scalability of highly parallel codes, requiring careful load balancing, minimization of communication overhead, and optimization of data transfer between computing units;
  • Code optimization to exploit the full potential of HPC systems, including specialized hardware features such as vectorization, multi-core processors, and accelerators such as GPUs or FPGAs;
  • Studies on software complexity, considering that atmospheric models are large, complex software systems with many interacting components;
  • Efficient data transfer and storage techniques for terabytes to petabytes of data, including meteorological observations and simulation results.

Dr. Lars Hoffmann
Prof. Dr. Yi Heng
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Atmosphere is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • atmospheric modeling
  • numerical weather prediction
  • climate modeling
  • high-performance computing
  • software complexity
  • numerical algorithms
  • performance optimization
  • parallel scalability
  • data management
  • new hardware architectures

Published Papers (1 paper)

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Research

13 pages, 11891 KiB  
Article
Tracking Carbon Dioxide with Lagrangian Transport Simulations: Case Study of Canadian Forest Fires in May 2021
by Ye Liao, Xuying Deng, Mingming Huang, Mingzhao Liu, Jia Yi and Lars Hoffmann
Atmosphere 2024, 15(4), 429; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos15040429 - 29 Mar 2024
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Abstract
The large amounts of greenhouse gases, such as carbon dioxide, produced by severe forest fires not only seriously affect the ecosystems in the area where the fires occur but also cause a greenhouse effect that has a profound impact on the natural environment [...] Read more.
The large amounts of greenhouse gases, such as carbon dioxide, produced by severe forest fires not only seriously affect the ecosystems in the area where the fires occur but also cause a greenhouse effect that has a profound impact on the natural environment in other parts of the world. Numerical simulations of greenhouse gas transport processes are often affected by uncertainties in the location and timing of the emission sources and local meteorological conditions, and it is difficult to obtain accurate and credible predictions by combining remote sensing satellite data with given meteorological forecasts or reanalyses. To study the regional transport processes and impacts of greenhouse gases produced by sudden large-scale forest fires, this study applies the Lagrangian particle dispersion model Massive-Parallel Trajectory Calculations (MPTRAC) to conduct forward simulations of the CO2 transport process of greenhouse gases emitted from forest fires in the central region of Saskatchewan, Canada, during the period of 17 May to 25 May 2021. The simulation results are validated with the Orbiting Carbon Observatory-2 Goddard Earth Observing System (OCO-2 GEOS) Level 3 daily gridded CO2 product over the study area. In order to leverage the high computational costs of the numerical simulations of the model, we implement the forward simulations on the Tianhe-2 supercomputer platform and the JUWELS HPC system, which greatly improves the computational efficiency through parallel computation and makes near-real-time predictions of atmospheric transport processes feasible. Full article
(This article belongs to the Special Issue High-Performance Computing for Atmospheric Modeling)
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