We introduce the open-source tool noisi for the forward and inverse modeling of ambient seismic cross-correlations with spatially varying source spectra. It utilizes pre-computed databases of Green's functions to represent seismic wave propagation between ambient seismic sources and seismic receivers, which can be obtained from existing repositories or imported from the output of wave propagation solvers. The tool was built with the aim of studying ambient seismic sources while accounting for realistic wave propagation effects. Furthermore, it may be used to guide the interpretation of ambient seismic auto- and cross-correlations, which have become preeminent seismological observables, in light of nonuniform ambient seismic sources. Written in the Python language, it is accessible for both usage and further development and efficient enough to conduct ambient seismic source inversions for realistic scenarios. Here, we introduce the concept and implementation of the tool, compare its model output to cross-correlations computed with SPECFEM3D_globe, and demonstrate its capabilities on selected use cases: a comparison of observed cross-correlations of the Earth's hum to a forward model based on hum sources from oceanographic models and a synthetic noise source inversion using full waveforms and signal energy asymmetry.

中文翻译：

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Noisi简介：用于环境噪声互相关建模和噪声源反演的Python工具

我们介绍开源工具 noisi用空间变化的源谱对环境地震互相关进行正向和逆向建模。它利用格林函数的预先计算的数据库来表示周围地震源和地震接收器之间的地震波传播，这可以从现有存储库中获取，也可以从波传播求解器的输出中导入。该工具旨在研究环境地震源，同时考虑实际的波传播效应。此外，它可以用来指导环境地震自相关和互相关的解释，鉴于不均匀的环境地震源，这些自相关和互相关已成为卓越的地震可观察性。用Python语言编写，它既可以使用，也可以进行进一步开发，并且效率足够高，可以针对实际情况进行环境地震源反演。在这里，我们介绍该工具的概念和实现，将其模型输出与使用SPECFEM3D_globe计算的互相关进行比较，并展示其在选定用例上的功能：将观察到的地球嗡嗡声的互相关与基于的正向模型进行比较来自海洋学模型的嗡嗡声源，以及使用完整波形和信号能量不对称的合成噪声源反演。