论文标题

天文云覆盖分析的天空质量表和卫星相关性

Sky Quality Meter and satellite correlation for the night cloud cover analysis at astronomical sites

论文作者

Cavazzani, S., Ortolani, S., Bertolo, A., Binotto, R., Fiorentin, P., Carraro, G., Saviane, I., Zitelli, V.

论文摘要

考虑到典型的观察时间约15分钟,并且具有夜间云覆盖的统计数据,对夜间云覆盖物的分析对于实时观察非常重要。在本文中,我们使用SQM(天空质量计)对La Silla和Asiago(Ekar天文台)天空进行高分辨率的时间分析:分别为3分钟和5分钟。我们调查了天空自然贡献的年度时间演变在不受人造光(Alan)影响的站点(艾伦)和一个高度影响的地点。我们还在GON和Aqua卫星数据和基于地面的SQM数据之间建立了相关性,以确认SQM数据和云覆盖率之间的关系。我们开发了一种允许使用SQM进行夜间云检测的算法,我们达到了La Silla的97.2 \%的相关性和Asiago的94.6 \%的相关性,并且由GOOS和Aqua Satellites检测到夜间云盖。我们的算法还对光度法(PN)和光谱夜(SN)进行了分类。我们在2018年在La Silla的晴朗夜晚的总百分比为59.1 \%Pn和21.7 \%SN。各个EKAR天文台值为31.1 \%\%Pn,24.0 \%\%\%\%\%\%\%\%\%\%\%\%\%\%。应用于SQM网络将涉及长期统计数据和大数据预测模型的开发,用于现场测试和实时天文观察。

The analysis of the night cloud cover is very important for astronomical observation in real time, considering a typical observation time of about 15 minutes, and to have a statistics of the night cloud cover. In this paper we use the SQM (Sky Quality Meter) for high resolution temporal analysis of the La Silla and Asiago (Ekar observatory) sky: 3 and 5 minutes respectively. We investigate the annual temporal evolution of the natural contributions of the sky in a site not influenced by artificial light at night (ALAN) and one highly influenced respectively. We also make a correlation between GOES and AQUA satellites data and ground-based SQM data to confirm a relationship between the SQM data and cloud cover. We develop an algorithm that allows the use of the SQM for night cloud detection and we reach a correlation of 97.2\% at La Silla and 94.6\% at Asiago with the nighttime cloud cover detected by the GOES and AQUA satellites. Our algorithm also classifies the photometric (PN) and spectroscopic nights (SN). We measure 59.1\% PN and 21.7\% SN for a total percentage of clear nights of 80.8\% at La Silla in 2018. The respective Ekar observatory values are 31.1\% PN, 24.0\% SN and 55.1\% of total clear nights time. Application to the SQM network would involve the development of long-term statistics and big data forecasting models, for site testing and real-time astronomical observation.

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