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首页> 外文期刊>Journal of Climate >Atmospheric climate change detection by radio occultation data using a fingerprinting method.
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Atmospheric climate change detection by radio occultation data using a fingerprinting method.

机译:使用指纹法通过无线电掩星数据检测大气气候变化。

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摘要

The detection of climate change signals in rather short satellite datasets is a challenging task in climate research and requires high-quality data with good error characterization. Global Navigation Satellite System (GNSS) radio occultation (RO) provides a novel record of high-quality measurements of atmospheric parameters of the upper-troposphere-lower-stratosphere (UTLS) region. Because of characteristics such as long-term stability, self calibration, and a very good height resolution, RO data are well suited to investigate atmospheric climate change. This study describes the signals of ENSO and the quasi-biennial oscillation (QBO) in the data and investigates whether the data already show evidence of a forced climate change signal, using an optimal-fingerprint technique. RO refractivity, geopotential height, and temperature within two trend periods (1995-2010 intermittently and 2001-10 continuously) are investigated. The data show that an emerging climate change signal consistent with the projections of three global climate models from the Coupled Model Intercomparison Project cycle 3 (CMIP3) archive is detected for geopotential height of pressure levels at a 90% confidence level both for the intermittent and continuous period, for the latter so far in a broad 50 degrees S-50 degrees N band only. Such UTLS geopotential height changes reflect an overall tropospheric warming. 90% confidence is not achieved for the temperature record when only large-scale aspects of the pattern are resolved. When resolving smaller-scale aspects, RO temperature trends appear stronger than GCM-projected trends, the difference stemming mainly from the tropical lower stratosphere, allowing for climate change detection at a 95% confidence level. Overall, an emerging trend signal is thus detected in the RO climate record, which is expected to increase further in significance as the record grows over the coming years. Small natural changes during the period suggest that the detected change is mainly caused by anthropogenic influence on climate.
机译:在相当短的卫星数据集中检测气候变化信号是气候研究中的一项艰巨任务,需要具有良好误差特征的高质量数据。全球导航卫星系统(GNSS)无线电掩星(RO)为高对流层-低平流层(UTLS)区域的大气参数测量提供了新颖的记录。由于长期稳定性,自我校准和非常好的高度分辨率等特性,反渗透数据非常适合研究大气气候变化。这项研究在数据中描述了ENSO和准两年一次振荡(QBO)的信号,并使用最佳指纹技术研究了数据是否已经显示出强迫气候变化信号的证据。研究了两个趋势时期(1995-2010年间断和2001-10年间连续)的反渗透率,地势高度和温度。数据显示,对于间歇性和连续性,在90%置信度下,检测到的压力水平的地势高度与耦合模型互作项目周期3(CMIP3)档案中的三个全球气候模型的预测一致的新兴气候变化信号。期间,到目前为止,后者仅在50度S-50度N波段内。这样的UTLS地势高度变化反映了对流层总体变暖。当仅解决图案的大规模方面时,温度记录无法获得90%的置信度。解决较小规模的问题时,反渗透温度趋势似乎比GCM预测的趋势强,差异主要来自热带平流层较低,允许以95%的置信度检测气候变化。总体而言,因此在反渗透气候记录中发现了一个新兴的趋势信号,随着记录在未来几年的增长,预计其重要性将进一步增加。在此期间较小的自然变化表明,探测到的变化主要是由人为因素对气候造成的。

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