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基于测量、建模和理论方法的太阳辐照光谱特征。

Characteristics of solar-irradiance spectra from measurements, modeling, and theoretical approach.

作者信息

Thuillier Gerard, Zhu Ping, Snow Martin, Zhang Peng, Ye Xin

机构信息

Physikalisch-Meteorologisches Observatorium Davos World Radiation Centre (PMOD/WRC), Davos Dorf, Switzerland.

Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Science, 3888 Dong Nanhu Road, Changchun, 130033, China.

出版信息

Light Sci Appl. 2022 Mar 29;11(1):79. doi: 10.1038/s41377-022-00750-7.

DOI:10.1038/s41377-022-00750-7
PMID:35351849
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8964690/
Abstract

An accurate solar-irradiance spectrum is needed as an input to any planetary atmosphere or climate model. Depending on the spectral characteristics of the chosen model, uncertainties in the irradiance may introduce significant differences in atmospheric and climate predictions. This is why several solar spectral-irradiance data sets have been published during the last decade. They have been obtained by different methods: either measurements from a single instrument or a composite of different spectra, or they are theoretical or semi-empirical solar models. In this paper, these spectral datasets will be compared in terms of irradiance, power per spectral interval, their derived solar-atmosphere brightness temperature, and time series. Whatever the different sources of these spectra are, they generally agree to within their quoted accuracy. The solar-rotation effect simultaneously observed by SORCE and PREMOS-PICARD is accurately measured. The 11-year long-term variability remains a difficult task, given the weak activity of solar cycle 24 and long-term instrument aging.

摘要

准确的太阳辐照度光谱是任何行星大气或气候模型的输入所需。根据所选模型的光谱特性,辐照度的不确定性可能会在大气和气候预测中引入显著差异。这就是为什么在过去十年中已经发布了几个太阳光谱辐照度数据集。它们是通过不同的方法获得的:要么是来自单个仪器的测量数据,要么是不同光谱的合成数据,或者是理论或半经验太阳模型。在本文中,将根据辐照度、每个光谱区间的功率、它们推导的太阳大气亮度温度和时间序列对这些光谱数据集进行比较。无论这些光谱的来源如何不同,它们通常在其引用的精度范围内是一致的。太阳辐射和PREMOS - PICARD同时观测到的太阳自转效应得到了精确测量。鉴于太阳活动周期24的活动较弱以及仪器的长期老化,11年的长期变化仍然是一项艰巨的任务。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fed1/8964690/e2fa68343fbe/41377_2022_750_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fed1/8964690/a7ea3216bf8f/41377_2022_750_Fig1_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fed1/8964690/38ab1d57126b/41377_2022_750_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fed1/8964690/47a6e2e6415a/41377_2022_750_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fed1/8964690/4874b47593e4/41377_2022_750_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fed1/8964690/b0c7c912001a/41377_2022_750_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fed1/8964690/e2fa68343fbe/41377_2022_750_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fed1/8964690/a7ea3216bf8f/41377_2022_750_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fed1/8964690/2210dca7e5b2/41377_2022_750_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fed1/8964690/af3c392f9213/41377_2022_750_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fed1/8964690/38ab1d57126b/41377_2022_750_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fed1/8964690/47a6e2e6415a/41377_2022_750_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fed1/8964690/4874b47593e4/41377_2022_750_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fed1/8964690/b0c7c912001a/41377_2022_750_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fed1/8964690/e2fa68343fbe/41377_2022_750_Fig8_HTML.jpg

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