Open-source stand-alone version of atmospheric model Aeolus 2.0 software

IF 3.3 3区 地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY
Masoud Rostami, Stefan Petri, Sullyandro Oliveira Guimaräes, Bijan Fallah
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Abstract

In this discourse, we present the unveiling of an open-source software package designed to facilitate engagement with the atmospheric model, Aeolus 2.0. This particular iteration stands as a self-contained model of intermediate complexity. The model's dynamical core is underpinned by a multi-layer pseudo-spectral moist-convective Thermal Rotating Shallow Water (mcTRSW) model. The pseudo-spectral problem-solving tasks are handled by the Dedalus algorithm, acknowledged for its spin-weighted spherical harmonics. The model captures the temporal and spatial evolution of vertically integrated potential temperature, thickness, water vapour, precipitation, and the intricate influence of bottom topography. It comprehensively characterizes velocity fields in both the lower and upper troposphere, employing resolutions spanning a spectrum from the smooth to the coarse, enabling the exploration of a wide range of dynamic phenomena with varying levels of detail and precision.

Abstract Image

大气模型 Aeolus 2.0 软件的开源独立版本
在这篇文章中,我们介绍了一个开源软件包,旨在促进大气模型 Aeolus 2.0 的使用。这个迭代版本是一个具有中等复杂程度的自足模型。该模式的动力学核心由多层伪谱湿对流热旋转浅水(mcTRSW)模式支撑。伪谱问题求解任务由 Dedalus 算法处理,该算法因其自旋加权球面谐波而闻名。该模型捕捉了垂直综合潜在温度、厚度、水蒸气、降水的时空演变,以及海底地形的复杂影响。它全面描述了对流层下部和上部的速度场,采用了从平滑到粗糙的分辨率,能够以不同的细节和精度探索各种动态现象。
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来源期刊
Geoscience Data Journal
Geoscience Data Journal GEOSCIENCES, MULTIDISCIPLINARYMETEOROLOGY-METEOROLOGY & ATMOSPHERIC SCIENCES
CiteScore
5.90
自引率
9.40%
发文量
35
审稿时长
4 weeks
期刊介绍: Geoscience Data Journal provides an Open Access platform where scientific data can be formally published, in a way that includes scientific peer-review. Thus the dataset creator attains full credit for their efforts, while also improving the scientific record, providing version control for the community and allowing major datasets to be fully described, cited and discovered. An online-only journal, GDJ publishes short data papers cross-linked to – and citing – datasets that have been deposited in approved data centres and awarded DOIs. The journal will also accept articles on data services, and articles which support and inform data publishing best practices. Data is at the heart of science and scientific endeavour. The curation of data and the science associated with it is as important as ever in our understanding of the changing earth system and thereby enabling us to make future predictions. Geoscience Data Journal is working with recognised Data Centres across the globe to develop the future strategy for data publication, the recognition of the value of data and the communication and exploitation of data to the wider science and stakeholder communities.
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