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Homogenized Daily Relative Humidity Series in China during 1960–2017
Advances in Atmospheric Sciences ( IF 6.5 ) Pub Date : 2020-03-30 , DOI: 10.1007/s00376-020-9180-0 Zhen Li , Zhongwei Yan , Yani Zhu , Nicolas Freychet , Simon Tett
Advances in Atmospheric Sciences ( IF 6.5 ) Pub Date : 2020-03-30 , DOI: 10.1007/s00376-020-9180-0 Zhen Li , Zhongwei Yan , Yani Zhu , Nicolas Freychet , Simon Tett
Surface relative humidity (RH) is a key element for weather and climate monitoring and research. However, RH is not as commonly applied in studying climate change, partly because the observation series of RH are prone to inhomogeneous biases due to non-climate changes in the observation system. A homogenized dataset of daily RH series from 746 stations in Chinese mainland for the period 1960–2017, ChinaRHv1.0, has been developed. Most (685 or 91.82% of the total) station time series were inhomogeneous with one or more break points. The major breakpoints occurred in the early 2000s for many stations, especially in the humid and semi-humid zones, due to the implementation of automated observation across the country. The inhomogeneous biases in the early manual records before this change are positive relative to the recent automatic records, for most of the biased station series. There are more break points detected by using the MASH (Multiple Analysis of Series for Homogenization) method, with biases mainly around −0.5% and 0.5%. These inhomogeneous biases are adjusted with reference to the most recent observations for each station. Based on the adjusted observations, the regional mean RH series of China shows little long-term trend during 1960–2017 [0.006% (10 yr) −1 ], contrasting with a false decreasing trend [−0.414% (10 yr) −1 ] in the raw data. It is notable that ERA5 reanalysis data match closely with the interannual variations of the raw RH series in China, including the jump in the early 2000s, raising a caveat for its application in studying climate change in the region. 地表相对湿度(RH)是天气和气候监测与研究的关键要素. 然而, 相对湿度在气候变化研究中的应用并不普遍, 部分原因是RH观测序列由于受到观测系统中的非气候变化影响而容易产生非均一性偏差. 本文建立了中国大陆746个站1960-2017年均一化逐日相对湿度数据集ChinaRHv1.0. 结果表明: 大多数(685个, 占台站总数的91.82%)台站时间序列具有一个或多个非均一性断点. 由于在全国范围内实施了自动观测, 许多台站的主要断点出现在2000年代初, 特别是在潮湿和半湿润地区. 对于大多数有偏差的台站序列, 自动化观测之前的早期人工记录中的非均一性偏差相对于最近的自动化记录是正的. 利用MASH(序列多元分析均一化)方法检测到相对湿度序列中更多的间断点, 其非均一性偏差主要在-0.5%和0.5%左右. 这些非均一性偏差是根据每个观测站临近的几个参考站观测值进行调整的. 基于均一化序列得到1960-2017年中国区域平均相对湿度系列几乎没有长期变化趋势[0.006%(10年)-1], 而原始数据则呈虚假的下降趋势[0.414%(10年)-1]. 值得注意的是, ERA5再分析数据与中国原始相对湿度系列的年际变化(包括21世纪初的跃变)吻合得很好, 在利用其开展我国区域气候变化研究时需要谨慎.
更新日期：2020-03-30
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