首页|Investigators at Ilmenau University of Technology Discuss Findings in Machine Le arning (Generative Convective Parametrization of a Dry Atmospheric Boundary Laye r)
Investigators at Ilmenau University of Technology Discuss Findings in Machine Le arning (Generative Convective Parametrization of a Dry Atmospheric Boundary Laye r)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Research findings on Machine Learning are discuss ed in a new report. According to news reporting originating from Ilmenau, German y, by NewsRx correspondents, research stated, “Turbulence parametrizations will remain a necessary building block in kilometer-scale Earth system models. In con vective boundary layers, where the mean vertical gradients of conserved properti es such as potential temperature and moisture are approximately zero, the standa rd ansatz which relates turbulent fluxes to mean vertical gradients via an eddy diffusivity has to be extended by mass-flux parametrizations for the typically a symmetric up- and downdrafts in the atmospheric boundary layer.” Financial support for this research came from Ministerio de Ciencia e Innovacion .
IlmenauGermanyEuropeAlgorithmsCy borgsEmerging TechnologiesMachine LearningIlmenau University of Technology
NETL
NSTL
