qgs: A flexible Python framework of reduced-order multiscale climate models
qgs: A flexible Python framework of reduced-order multiscale climate models
复制标题
qgs：一个灵活的 Python 降阶多尺度气候模型框架
DOI：
10.21105/joss.02597
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发表时间：
2020
期刊：
影响因子：
--
通讯作者：
S. Vannitsem
中科院分区：
文献类型：
--
作者：
J. Demaeyer;L. D. Cruz;S. Vannitsem
<p>在大气和气候科学中，研究和开发通常首先使用简单的理想化系统进行，如<em>Lorenz-N</em>模型（<em>N∈</em>{63，84，96}），这是大气变化的玩具模型。另一方面，降阶谱准地转模式的大气具有足够数量的模式提供了一个很好的代表性的干大气动力学。它们使人们能够确定大气环流的典型特征，如阻塞和纬向环流制度，以及低频变率。然而，这些模型在文献中很少被考虑，尽管它们表现出更真实的行为。</p><p><strong>qgs</strong>（Demaeyer等人，2020）旨在通过为研究人员和教师提供快速易用的Python框架来推广这些系统，以集成这种模型。文档通过解释方程和参数并将其链接到代码，使处理模型变得清晰有效。160;</p><p>选择使用Python是专门为了方便它在Quixyter Notebooks中的使用，以及在这种语言中可用的多个最新机器学习库。</p><p>在这个演讲中，我们将展示qgs的建模能力<strong></strong>，并展示它在各种教学和研究用例中的使用。</p><p><strong>参考文献</strong></p><p>Demaeyer，J.，德克鲁斯湖，& Vannitsem，S.（2020年）。QGS：一个灵活的降阶多尺度气候模型Python框架。Journal of Open Source Software，5（56），2597，https://doi.org/10.21105/joss.02597. </p>
<p>In atmospheric and climate sciences, research and development is often first conducted with a simple idealized system like the Lorenz-<em>N</em> models (<em>N ∈</em> {63, 84, 96}) which are toy models of atmospheric variability. On the other hand, reduced-order spectral quasi-geostrophic models of the atmosphere with a sufficient number of modes offer a good representation of the dry atmospheric dynamics. They allow one to identify typical features of the atmospheric circulation, such as blocked and zonal circulation regimes, and low-frequency variability. However, these models are less often considered in literature, despite their demonstration of more realistic behavior.</p><p><strong>qgs</strong> (Demaeyer et al., 2020) aims to popularize these systems by providing a fast and easy-to-use Python framework for researchers and teachers to integrate this kind of model. The documentation makes it clear and efficient to handle the model, by explaining the equations and parameters and linking these to the code. </p><p>The choice to use Python was specifically made to facilitate its use in Jupyter Notebooks and with the multiple recent machine learning libraries that are available in this language.</p><p>In this talk, we will present the modeling capabilities of <strong>qgs</strong> and show its usage in a varieties of didactical and research use cases.</p><p><strong>Reference</strong></p><p>Demaeyer, J., De Cruz, L., & Vannitsem, S. (2020). qgs: A flexible Python framework of reduced-order multiscale climate models. Journal of Open Source Software, 5(56), 2597, https://doi.org/10.21105/joss.02597 .</p>
使用 CHAMP 折射率数据的数据同化实验
DOI：
--
发表时间：
2006
期刊：
CAS/JSC WGNE Research Activities in Atmospheric and Oceanic Modelling. 36
影响因子：
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作者：
Orozbaev;R.T.;Takasu;A.;Tagiri;M.;Bakirov;A.B.;Sakiev;K. S.;H.Seko;H.Seko
通讯作者：
H.Seko