预先计算的相关k系数的谱合并
Spectral binning of precomputed correlated-k coefficients
摘要：
随着进行精确辐射转移计算所需的光谱谱线列表数量的大幅增加，传播精确的辐射数据几乎与计算辐射数据一样成为一个挑战。考虑到许多行星科学应用只是寻找加热率或中低分辨率光谱，任何能够以精确和灵活的方式以计算和存储成本的一小部分实现这种计算的方法都是非常有价值的。由于许多这些原因，相关k方法已经变得非常流行。它的主要弱点是缺乏适应预先计算的k系数的谱网格/分辨率的方法，使得难以分发适合于许多不同应用的通用数据库。目前，大多数用户仍然需要访问具有相关线列表或高分辨率截面的逐线传输代码，以在所需分辨率下计算k系数表。在这项工作中，我们证明了预先计算的k系数可以在没有任何额外假设的情况下被合并到较低的频谱分辨率，并展示了如何在实践中做到这一点。然后，我们表明，这种分仓过程不会引入任何显着的损失的准确性。在此过程中，我们量化了这种方法与采样截面方法相比如何非常有利。这开辟了一个新的途径，提供准确的辐射转移数据，提供中等分辨率的k系数表，用户谁可以在以后定制这些表，以满足他们的需要在飞行中。为了帮助完成这最后一步，我们简要介绍了Exo_k，这是一个开放访问的开源Python库，旨在以一种简单且计算效率高的方式处理、定制和使用许多不同格式的k系数和截面表。
英文摘要：
With the major increase in the volume of the spectroscopic line lists needed to perform accurate radiative transfer calculations, disseminating accurate radiative data has become almost as much a challenge as computing it. Considering that many planetary science applications are only looking for heating rates or mid-to-low resolution spectra, any approach enabling such computations in an accurate and flexible way at a fraction of the computing and storage costs is highly valuable. For many of these reasons, the correlated-k approach has become very popular. Its major weakness has been the lack of ways to adapt the spectral grid/resolution of precomputed k-coefficients, making it difficult to distribute a generic database suited for many different applications. Currently, most users still need to have access to a line-by-line transfer code with the relevant line lists or high-resolution cross sections to compute k-coefficient tables at the desired resolution. In this work, we demonstrate that precomputed k-coefficients can be binned to a lower spectral resolution without any additional assumptions, and show how this can be done in practice. We then show that this binning procedure does not introduce any significant loss in accuracy. Along the way, we quantify how such an approach compares very favorably with the sampled cross section approach. This opens up a new avenue to deliver accurate radiative transfer data by providing mid-resolution k-coefficient tables to users who can later tailor those tables to their needs on the fly. To help with this final step, we briefly present Exo_k, an open-access, open-source Python library designed to handle, tailor, and use many different formats of k-coefficient and cross-section tables in an easy and computationally efficient way.
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