论文标题

气候变化对使用高分辨率全球气候预测到2050

Impact of climate change on site characteristics of eight major astronomical observatories using high-resolution global climate projections until 2050

论文作者

Haslebacher, C., Demory, M. -E., Demory, B. -O., Sarazin, M., Vidale, P. L.

论文摘要

下一代望远镜的站点是在望远镜的第一盏灯之前数十年选择的。位点选择通常基于在一个太短的时期内的最新测量,无法说明观察条件的长期变化,例如由人为气候变化引起的条件。在这项研究中,我们分析了八个地点天文观测条件的趋势。大多数站点已经托管了可提供天气参数原位测量的望远镜,或者是用于托管下一代望远镜的候选者。为了进行地形的良好表示,我们使用高分辨率模型对比项目提供的最高分辨率全球气候模型(GCM)合奏,并作为欧盟Horizo​​n 2020 Primavera项目的一部分开发。我们对ECMWF的原位测量和第五代大气重新分析(ERA5)评估了仅大气和耦合的Primavera GCM历史模拟。然后,使用Primavera未来的气候模拟分析了2015 - 2050年期间当前现场条件变化的预测。在大多数站点上,我们发现Primavera GCMS在温度,特定的湿度和可沉淀的水蒸气中表现出良好的一致性,与原位观测和ERA5相比。 Primavera模拟这些变量的能力增加了对其预测的信心。对于这些变量,模型集成计划所有站点的趋势都在越来越多。另一方面,与观察和重新分析相比,没有预测相对湿度,云覆盖或天文观看的显着趋势,而Primavera并不能很好地模拟这些变量。因此,对这些预测几乎没有信心。我们的结果表明,气候变化可能会增加由于不良现场条件而浪费的时间。

Sites for next-generation telescopes are chosen decades before the first light of a telescope. Site selection is usually based on recent measurements over a period that is too short to account for long-term changes in observing conditions such as those arising from anthropogenic climate change. In this study, we analyse trends in astronomical observing conditions for eight sites. Most sites either already host telescopes that provide in situ measurements of weather parameters or are candidates for hosting next-generation telescopes. For a fine representation of orography, we use the highest resolution global climate model (GCM) ensemble available provided by the high-resolution model intercomparison project and developed as part of the European Union Horizon 2020 PRIMAVERA project. We evaluate atmosphere-only and coupled PRIMAVERA GCM historical simulations against in situ measurements and the fifth generation atmospheric reanalysis (ERA5) of the ECMWF. The projections of changes in current site conditions are then analysed for the period 2015-2050 using PRIMAVERA future climate simulations. Over most sites, we find that PRIMAVERA GCMs show good agreement in temperature, specific humidity, and precipitable water vapour compared to in situ observations and ERA5. The ability of PRIMAVERA to simulate those variables increases confidence in their projections. For those variables, the model ensemble projects an increasing trend for all sites. On the other hand, no significant trends are projected for relative humidity, cloud cover, or astronomical seeing and PRIMAVERA does not simulate these variables well compared to observations and reanalyses. Therefore, there is little confidence in these projections. Our results show that climate change likely increases time lost due to bad site conditions.

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