Homogeneous long-term surface air temperature (SAT) observations are essential for the assessment and attribution of global and regional climate change. However, inhomogeneity is difficult to avoid because of non-natural changes, such as those at the observing location, and those related to the environment, instruments, and algorithms used for calculating any particular climate variable.
A set of homogenized monthly mean SAT series at 32 stations in China dating back to the 19th century had previously been developed based on the RHtest method, but some inhomogeneities remained in the dataset. Dr. LI Zhen from the Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences, explained the possible reasons:
"First, the preconditions applied for the data processing might be too strict, e.g., a detected break point needed to be confirmed by the metadata. Second, there were no reference data for many cases for the early period before 1950, due to sparse observations. Third, incomplete metadata, especially before 1950, might further increase the probability of overlooking some detected break points. Therefore, it is beneficial to further adjust the long-term SAT series in order to improve the dataset for studying large-scale climate change in the region.”
In a recently published data description article in Advances in Atmospheric Sciences, Dr. LI Zhen, Prof. YAN Zhongwei (IAP), Dr. CAO Lijuan (National Meteorological Information Center), and Prof. Phil D. JONES (University of East Anglia, UK), describe a further-adjusted and updated dataset based on the Multiple Analysis of Series for Homogenization (MASH) method. The MASH procedure detects 33 monthly temperature records as erroneous outliers and 152 meaningful break points in the monthly SAT series since 1924 at 28 stations. The inhomogeneous parts are then adjusted relative to the latest homogeneous part of the series.
The new data show significant warming trends during 1924–2016 at all the stations, ranging from 0.48 to 3.57°C (100 yr)-1 (Fig. 1a), with a regional mean trend of 1.65°C (100 yr)-1; whereas, the previous results ranged from a slight cooling at two stations to considerable warming, up to 4.5°C (100 yr)-1 (Fig. 1b). It is suggested that the further-adjusted data are a better representation of the large-scale pattern of climate change in the region for the past century. The new data are available online at http://www.dx.doi.org/10.11922/sciencedb.516 .
Fig. 1. Linear trends in the annual SAT series at 28 stations during 1924–2016 based on the (a) previous and (b) new data. (Image by Li et al.)
Citation: Li, Z., Z. W. Yan, L. J. Cao, and P. D. Jones, 2018: Further-adjusted long-term temperature series in China based on MASH. Adv. Atmos. Sci., 35(8), 909–917, https://doi.org/10.1007/s00376-018-7280-x .
Data URL: http://www.sciencedb.cn/dataSet/handle/516.