基于国家气象信息中心＂基础气象资料建设专项＂研制的中国地面历史基础气象资料及台站元数据,利用RHtest V4软件包对天津1951-2012年的历史气温序列进行了均一性分析。结果显示,通过惩罚最大t检验（PMT）方法对12个地面站逐日平均、最...基于国家气象信息中心＂基础气象资料建设专项＂研制的中国地面历史基础气象资料及台站元数据,利用RHtest V4软件包对天津1951-2012年的历史气温序列进行了均一性分析。结果显示,通过惩罚最大t检验（PMT）方法对12个地面站逐日平均、最高、最低气温序列检验得到,迁站是导致平均气温和最低气温序列突变的主要原因,同类型仪器更换则是导致最高气温序列突变的主要原因,而2005年以后的自动站业务化并没有对天津地区气温序列的均一性造成很大影响。同时,研究中也检验出少部分未知原因的显著间断点,可能是由于观测员的误判或观测仪器翘变等因素造成的历史数据疑误。从订正量来看,逐日平均气温和最高气温序列主要以正偏差订正为主,而最低气温则主要以负偏差订正为主。其中,最高气温序列的分位数匹配（QM）订正量均值最大,90%以上集中在0.1-1.0°C,平均气温序列的QM订正量均值相对最小,90%以上的订正量在-0.7-0.7°C,而最低气温的订正量90%以上集中在-1.5-1.5°C范围中。另外,以Xu et al.（2013）研制的数据集为参照,通过误差分析,发现两类研究得到的年（季节）尺度气温数据具有较高的相符率和一致性,从而可以说明本研究订正后的天津地区1951-2012年逐日气温序列具有一定的可靠性。展开更多
Two homogenized datasets of daily maximum temperature （Tmax）, mean temperature （Tm）, and min- imum temperature （Tmin） series in China have recently been developed. One is CHTM3.0, based on the Multiple Analysis ...Two homogenized datasets of daily maximum temperature （Tmax）, mean temperature （Tm）, and min- imum temperature （Tmin） series in China have recently been developed. One is CHTM3.0, based on the Multiple Analysis of Series for Homogenization （MASH） method, and includes 753 stations for the period 1960-2013. The other is CHHTD1.0, based on the Relative Homogenization test （RHtest）, and includes 2419 stations over the period 1951-2011. The daily Tmax/Tm/Tmin series at 751 stations, which are in both datasets, are chosen and compared against the raw dataset, with regard to the number of breakpoints, long-term climate trends, and their geographical patterns. The results indicate that some robust break points associated with relocations can be detected, the inhomogeneities are removed by both the MASH and RHtest method, and the data quality is improved in both homogenized datasets. However, the differences between CHTM3.0 and CHHTD1.0 are notable. By and large, in CHHTD1.0, the break points detected are fewer, but the adjustments for inhomogeneities and the resultant changes of linear trend estimates are larger. In contrast, CHTM3.0 provides more reasonable geographical patterns of long-term climate trends over the region. The reasons for the differences between the datasets include： （1） different algorithms for creating reference series for adjusting the candidate series--more neighboring stations used in MASH and hence larger-scale regional signals retained; （2） different algorithms for cMculating the adjustments--larger adjustments in RHtest in general, partly due to the individual local reference information used; and （3） different rules for judging inhomogeneity--all detected break points are adjusted in CHTM3.0, based on MASH, while a number of break points detected via RHtest but without supporting metadata are overlooked in CHHTD1.0. The present results suggest that CHTM3.0 is more suitable for analyses of large-scale climate change in China, while CHHTD1.0 contains more original information regarding station temperature records.展开更多
文摘基于国家气象信息中心＂基础气象资料建设专项＂研制的中国地面历史基础气象资料及台站元数据,利用RHtest V4软件包对天津1951-2012年的历史气温序列进行了均一性分析。结果显示,通过惩罚最大t检验（PMT）方法对12个地面站逐日平均、最高、最低气温序列检验得到,迁站是导致平均气温和最低气温序列突变的主要原因,同类型仪器更换则是导致最高气温序列突变的主要原因,而2005年以后的自动站业务化并没有对天津地区气温序列的均一性造成很大影响。同时,研究中也检验出少部分未知原因的显著间断点,可能是由于观测员的误判或观测仪器翘变等因素造成的历史数据疑误。从订正量来看,逐日平均气温和最高气温序列主要以正偏差订正为主,而最低气温则主要以负偏差订正为主。其中,最高气温序列的分位数匹配（QM）订正量均值最大,90%以上集中在0.1-1.0°C,平均气温序列的QM订正量均值相对最小,90%以上的订正量在-0.7-0.7°C,而最低气温的订正量90%以上集中在-1.5-1.5°C范围中。另外,以Xu et al.（2013）研制的数据集为参照,通过误差分析,发现两类研究得到的年（季节）尺度气温数据具有较高的相符率和一致性,从而可以说明本研究订正后的天津地区1951-2012年逐日气温序列具有一定的可靠性。
基金Supported by the Strategic Priority Research Program of the Chinese Academy of Sciences(XDA05090100)National Science and Technology Support Program of China(2012BAC22B04)+1 种基金China Meteorological Administration Special Public Welfare Research Fund(GYHY201206013)National Natural Science Foundation of China(41505071)
文摘Two homogenized datasets of daily maximum temperature （Tmax）, mean temperature （Tm）, and min- imum temperature （Tmin） series in China have recently been developed. One is CHTM3.0, based on the Multiple Analysis of Series for Homogenization （MASH） method, and includes 753 stations for the period 1960-2013. The other is CHHTD1.0, based on the Relative Homogenization test （RHtest）, and includes 2419 stations over the period 1951-2011. The daily Tmax/Tm/Tmin series at 751 stations, which are in both datasets, are chosen and compared against the raw dataset, with regard to the number of breakpoints, long-term climate trends, and their geographical patterns. The results indicate that some robust break points associated with relocations can be detected, the inhomogeneities are removed by both the MASH and RHtest method, and the data quality is improved in both homogenized datasets. However, the differences between CHTM3.0 and CHHTD1.0 are notable. By and large, in CHHTD1.0, the break points detected are fewer, but the adjustments for inhomogeneities and the resultant changes of linear trend estimates are larger. In contrast, CHTM3.0 provides more reasonable geographical patterns of long-term climate trends over the region. The reasons for the differences between the datasets include： （1） different algorithms for creating reference series for adjusting the candidate series--more neighboring stations used in MASH and hence larger-scale regional signals retained; （2） different algorithms for cMculating the adjustments--larger adjustments in RHtest in general, partly due to the individual local reference information used; and （3） different rules for judging inhomogeneity--all detected break points are adjusted in CHTM3.0, based on MASH, while a number of break points detected via RHtest but without supporting metadata are overlooked in CHHTD1.0. The present results suggest that CHTM3.0 is more suitable for analyses of large-scale climate change in China, while CHHTD1.0 contains more original information regarding station temperature records.
