1979-2012年中国探空温度资料中非均一性问题的检验与分析

利用加拿大环境部气候研究中心研发的PMTred(penalized maximum t test)非均一性检验方法,以ERA-interim资料作为参考序列,以中国各探空台站详细的元数据信息为主要断点判断依据,对1979-2012年中国125个探空台站7个标准等压面月平均探空温度资料进行了非均一性检验、订正,并结合详细的元数据信息分析了造成中国探空温度序列非均一问题的主要原因。研究表明,中国探空温度资料中存在由于人为因素造成的断点,整套探空资料中非均一的台站数和断点数所占的百分比呈低层少、高层多的趋势。各标准等压面上月平均温度序列非均一的探空台站平均订正幅度也随着高度的升高而增大,并且订正量为负值在整套订正资料中所占的比例较高,说明中国的探空月平均温度原始观测资料存在系统性偏高的问题。订正后200 hPa的温度变化趋势接近0,以200 hPa为转折点,100 hPa的降温趋势较订正前明显减弱,100 hPa以下为升温趋势,300-700 hPa的增温趋势加强。1979-2012年中国探空月平均温度资料的非均一问题主要来源于2000-2001年探测系统的升级(包括辐射误差订正方法的变化),其次是2002年之后观测仪器的换型。这两次连续的元数据变化均造成了之后中国探空月平均温度出现了系统性的降低,这也是造成订正前后温度变化趋势存在差异的主要原因。

Homogenization and analysis of China radiosonde temperature data from 1979 to 2012

Using the PMTred (penalized maximum t test) method developed by the Environment Canada with the ERA-interim reanalysis data as the reference series and first using the detailed metadata of each radiosonde station in China as the judging basis, the inhomogeneity test and corrections are carried out on the monthly temperature data at mandatory levels at the 125 radiosonde stations in China. And combining with the detailed metadata, the main reasons causing the homogenization problem of the radiosonde temperature data in China have been analysed. The result shows that there are break points due to human factors in the radiosonde temperature data of China. With the height increasing, a general trend is presented, that is, both the number of the inhomogeneous stations and break points show less in lower levels and more in high levels. Also, the mean magnitude of correction increases with height and the negative correction values have the high proportion in the whole dataset, implying that the radiosonde temperature data in China is systematically higher. After adjustment, the temperature trend on 200 hPa level becomes close to zero. The cooling trend on 100 hPa level weakens after adjustment, but the warming trend strengthens on 300-700 hPa. The update of the sounding systems in 2000 and 2001 including the radiation correction method is the main reason of the inhomogeneity in Chinese radiosonde temperature data. Another reason is the shifts of the radiosonde instrument. This two consecutive metadata changes caused the following monthly mean temperature data appears systematically lower. This is also the main reason why there are some differences in the temperature trend between before and after adjustment.