Application of Multiple Analysis of Series for Homogenization to Beijing Daily Temperature Series （1960-2006）

Homogenization of climate observations remains a challenge to climate change researchers, especially in cases where metadata (e.g., probable dates of break points) are not always available. To examine the influence of metadata on homogenizing climate data, the authors applied the recently developed Multiple Analysis of Series for Homogenization (MASH) method to the Beijing (BJ) daily temperature series for 1960--2006 in three cases with different references: (1) 13M---considering metadata at BJ and 12 nearby stations; (2) 13NOM---considering the same 13 stations without metadata; and (3) 21NOM---considering 20 further stations and BJ without metadata. The estimated mean annual, seasonal, and monthly inhomogeneities are similar between the 13M and 13NOM cases, while those in the 21NOM case are slightly different. The detected biases in the BJ series corresponding to the documented relocation dates are as low as -0.71^oC, -0.79^oC, and -0.5^oC for the annual mean in the 3 cases, respectively. Other biases, including those undocumented in metadata, are minor. The results suggest that any major inhomogeneity could be detected via MASH, albeit with minor differences in estimating inhomogeneities based on the different references. The adjusted annual series showed a warming trend of 0.337, 0.316, and 0.365^oC (10 yr)^-1 for the three cases, respectively, smaller than the estimate of 0.453^oC (10 yr)^-1 in the original series, mainly due to the relocation-induced biases. The impact of the MASH-type homogenization on estimates of climate extremes in the daily temperature series is also discussed.     

中国均一化日平均温、最高温和最低温序列1960-2008

Inhomogeneities in the daily mean/maximum/ minimum temperature （Tm/Tmax/Tmin） series from 1960- 2008 at 549 National Standard Stations （NSSs） in China were analyzed by using the Multiple Analysis of Series for Homogenization （MASH） software package. Typical biases in the dataset were illustrated via the cases of Beijing （B J）, Wutaishan （WT）, Urumqi （UR） and Henan （HN） stations. The homogenized dataset shows a mean warming trend of 0.261/0.193/0.344℃/decade for the annual series of Tm/Tmax/Tmin, slightly smaller than that of the original dataset by 0.006/0.009/0.007℃/decade. However, considerable differences between the adjusted and original datasets were found at the local scale. The adjusted Tmin series shows a significant warming trend almost everywhere for all seasons, while there are a number of stations with an insignificant trend in the original dataset. The adjusted Tm data exhibit significant warming trends annually as well as for the autumn and winter seasons in northern China, and cooling trends only for the summer in the middle reaches of the Yangtze River and parts of central China and for the spring in southwestern China, while the original data show cooling trends at several stations for the annual and seasonal scales in the Qinghai, Shanxi, Hebei, and Xinjiang provinces. The adjusted Tmax data exhibit cooling trends for summers at a number of stations in the mid-lower reaches of the Yangtze and Yellow Rivers and for springs and winters at a few stations in southwestern China, while the original data show cooling trends at three/four stations for the annual/autumn periods in the Qinghai and Yunnan provinces. In general, the number of stations with a cooling trend was much smaller in the adjusted Tm and Tmax dataset than in the original dataset. The cooling trend for summers is mainly due to cooling in August. The results of homogenization using MASH appear to be robust; in particular, different groups of stations with consideration of elevation led to minor effects i     

Homogenization of the Daily Land Surface Temperature over the Mainland of China from 1960 through 2017

Land surface temperature(LST) is one of the most important factors in the land-atmosphere interaction process. Raw measured LSTs may contain biases due to instrument replacement, changes in recording procedures, and other non-climatic factors. This study attempts to reduce the above biases in raw daily measurements and achieves a homogenized daily LST dataset over China using 2360 stations from 1960 through 2017. The high-quality land surface air temperature(LSAT)dataset is used to correct the LST warming biases especially evident during cold months in regions north of 40°N due to the replacement of observation instruments around 2004. Subsequently, the Multiple Analysis of Series for Homogenization(MASH) method is adopted to detect and then adjust the daily observed LST records. In total, 3.68 × 103 effective breakpoints in 1.65 × 106 monthly records(about 20%) are detected. A large number of these effective breakpoints are located over large parts of the Sichuan Basin and southern China. After the MASH procedure, LSTs at more than 80% of the breakpoints are adjusted within +/– 0.5°C, and of the remaining breakpoints, only 10% are adjusted over 1.5°C.Compared to the raw LST dataset over the whole domain, the homogenization significantly reduces the mean LST magnitude and its interannual variability as well as its linear trend at most stations. Finally, we perform preliminary analysis upon the homogenized LST and find that the annual mean LST averaged across China shows a significant warming trend [0.22°C(10 yr)–1]. The homogenized LST dataset can be further adapted for a variety of applications(e.g.,model evaluation and extreme event characterization).     

The Assessment of Global Surface Temperature Change from 1850s:The C-LSAT2.0 Ensemble and the CMST-Interim Datasets

Based on C-LSAT2.0,using high-and low-frequency components reconstruction methods,combined with observation constraint masking,a reconstructed C-LSAT2.0 with 756 ensemble members from the 1850s to 2018 has been developed.These ensemble versions have been merged with the ERSSTv5 ensemble dataset,and an upgraded version of the CMSTInterim dataset with 5°×5°resolution has been developed.The CMST-Interim dataset has significantly improved the coverage rate of global surface temperature data.After reconstruction,the data coverage before 1950 increased from 78%?81%of the original CMST to 81%?89%.The total coverage after 1955 reached about 93%,including more than 98%in the Northern Hemisphere and 81%?89%in the Southern Hemisphere.Through the reconstruction ensemble experiments with different parameters,a good basis is provided for more systematic uncertainty assessment of C-LSAT2.0 and CMSTInterim.In comparison with the original CMST,the global mean surface temperatures are estimated to be cooler in the second half of 19th century and warmer during the 21st century,which shows that the global warming trend is further amplified.The global warming trends are updated from 0.085±0.004℃(10 yr)^–1and 0.128±0.006℃(10 yr)^–1to 0.089±0.004℃(10 yr)^–1and 0.137±0.007℃(10 yr)^–1,respectively,since the start and the second half of 20th century.     

Characterizing the urban temperature trend using seasonal unit root analysis: Hong Kong from 1970 to 2015

This paper explores urban temperature in Hong Kong using long-term time series. In particular, the characterization of the urban temperature trend was investigated using the seasonal unit root analysis of monthly mean air temperature data over the period January 1970 to December 2013. The seasonal unit root test makes it possible to determine the stochastic trend of monthly temperatures using an autoregressive model. The test results showed that mean air temperature has increased by0.169?C(10 yr)~(-1)over the past four decades. The model of monthly temperature obtained from the seasonal unit root analysis was able to explain 95.9% of the variance in the measured monthly data — much higher than the variance explained by the ordinary least-squares model using annual mean air temperature data and other studies alike. The model accurately predicted monthly mean air temperatures between January 2014 and December 2015 with a root-mean-square percentage error of 4.2%.The correlation between the predicted and the measured monthly mean air temperatures was 0.989. By analyzing the monthly air temperatures recorded at an urban site and a rural site, it was found that the urban heat island effect led to the urban site being on average 0.865?C warmer than the rural site over the past two decades. Besides, the results of correlation analysis showed that the increase in annual mean air temperature was significantly associated with the increase in population, gross domestic product, urban land use, and energy use, with the R~2 values ranging from 0.37 to 0.43.     

Homogenized Daily Relative Humidity Series in China during 1960?2017

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.     

URBAN HEAT ISLAND EFFECT AND ITS CONTRIBUTION TO OBSERVED TEMPERATURE INCREASE AT WUHAN STATION, CENTRAL CHINA

Based on an in-homogeneity adjusted dataset of the monthly mean temperature, minimum and maximum temperature, this paper analyzes the temporal characteristics of Urban Heat Island (UHI) intensity at Wuhan Station, and its impact on the long-term trend of surface air temperature change recorded during 1961–2015 by using an urban-rural method. Results show that UHI effect is obvious near Wuhan Station in the past 55 years, especially for minimum temperature. The strongest UHI intensity occurs in summer and the weakest in winter. For the period 1961–2004, UHI intensity undergoes a significant increase near the urban station, with the increase especially large for the period 1988–2004, but the last 10 years witness a significant decrease, with the decrease in minimum temperature being more significant than that of maximum temperature. The annual mean urban warming and its contribution to overall warming are 0.18?C/10yr and 48.8% respectively for the period 1961–2015, with a more significant and larger urbanization effect seen in Tmin than Tmax. Thus, a large proportion warming, about half of the overall increase in annual mean temperature, as observed at the urban station, can be attributed to the rapid urbanization in the past half a century.     

Variability of maximum and mean average temperature across Libya (1945–2009)

Spatial and temporal variability in daily maximum and mean average daily temperature, monthly maximum and mean average monthly temperature for nine coastal stations during the period 1956–2009 (54 years), and annual maximum and mean average temperature for coastal and inland stations for the period 1945–2009 (65 years) across Libya are analysed. During the period 1945–2009, significant increases in maximum temperature (0.017 °C/year) and mean average temperature (0.021 °C/year) are identified at most stations. Significantly, warming in annual maximum temperature (0.038 °C/year) and mean average annual temperatures (0.049 °C/year) are observed at almost all study stations during the last 32 years (1978–2009). The results show that Libya has witnessed a significant warming since the middle of the twentieth century, which will have a considerable impact on societies and the ecology of the North Africa region, if increases continue at current rates.     

Analysis of Sampling Error Uncertainties and Trends in Maximum and Minimum Temperatures in China简

In this paper we report an analysis of sampling error uncertainties in mean maximum and minimum temperatures （Tmax and Tmin） carried out on monthly,seasonal and annual scales,including an examination of homogenized and original data collected at 731 meteorological stations across China for the period 1951-2004.Uncertainties of the gridded data and national average,linear trends and their uncertainties,as well as the homogenization effect on uncertainties are assessed.It is shown that the sampling error variances of homogenized Tmax and Tmin,which are larger in winter than in summer,have a marked northwest-southeast gradient distribution,while the sampling error variances of the original data are found to be larger and irregular.Tmax and Tmin increase in all months of the year in the study period 1951-2004,with the largest warming and uncertainties being 0.400℃ （10 yr）-1 ＋ 0.269℃ （10 yr）-1 and 0.578℃ （10 yr）-1 ＋ 0.211℃ （10 yr）-1 in February,and the least being 0.022℃ （10 yr）-1 ＋ 0.085℃ （10 yr）-1 and 0.104℃ （10 yr）-1 ＋0.070℃ （10 yr）-1 in August.Homogenization can remove large uncertainties in the original records resulting from various non-natural changes in China.     

英国CRU高分辨率格点资料揭示的20世纪中国气候变化

中国覆盖比较完整的台站观测始于1951年,1951年之前虽然有一些观测记录,但是残缺不全.所以要建立更长的气候序列就要吸收代用资料,但是代用资料可能与气候要素仅有一定程度的相关,不可能一一对应,因此应用代用资料重建的气候序列有一定的不确定性.英国East Anglia大学的Climatic Research Unit(简称CRU)通过整合已有的若干个知名数据库,重建了一套覆盖完整、高分辨率、且无缺测的月平均地表气候要素数据集,时间范围覆盖1901～2003年,空间为0.5°×0.5°经纬网格覆盖所有陆地.这套资料和中国已有的气候数据相比具有如下优点: 第一,中国西部20世纪前半期非常缺少观测,CRU资料尽管包含插值带来的误差,经比较仍可作为有一定信度的参考; 第二,中国现有的百年温度序列只是年或季分辨率,而CRU资料达到月分辨率; 第三,建立这个序列仅使用观测结果,做统计内插,不包括代用资料所带来的不确定性.因此,CRU的序列与用代用资料补充得到的序列在资料方面有较大不同,比较这两个序列,不仅可以进一步确认中国气候变化的特征,也可以彼此校正.结果表明:(1)CRU资料反映的全国年平均温度年际变化和考虑代用资料重建的序列吻合得很好,相关系数达到0.84;(2)区域尺度上,两者在10个典型分区的气温变率也相当一致,相关整体保持在0.8左右,仅新疆西南部和西藏西北部两者差异较大;(3)CRU资料揭示的中国年总降水量在1951～2000年的变化与160站观测吻合,相关系数达到0.93;(4)CRU资料的中国东部四季降水量和重建资料十分一致,秋季一致性最好,相关0.93;(5)CRU资料和重建的序列比较一致地表现出中国温度和降水年代际变化的主要特征,其给出的20世纪20年代中国大旱和20世纪40年代中国高温的空间分布与作者过去的结论相一致.这表明,作者过去重建的中国气候序列有比较大的可靠性,而CRU资料也提供了新的信息,特别是在20世纪前半期和中国西部.     

青藏高原1951—2006年气温距平序列的建立与分析

依照气候距平法,基于"中国均一化历史气温数据集(1951—2004年)1.0版"与2005—2006年逐日平均气温资料,对青藏高原及其邻近区域123个测站的逐月平均气温网格化,进而以面积加权法建立高原1951—2006年逐月平均气温距平序列。最大限度地利用观测资料,着重探讨了利用参考站订正短序列气温资料气候标准值的方法。所建序列的奇异谱分析表明,青藏高原平均气温年际变化的近1/2可解释为非线性上升趋势,近1/5的变化可解释为白噪声。与同期北半球陆地区域相比,二者的年平均气温距平序列的趋势非常相近,高原并未显示变暖的超前性;高原序列中的噪声比率和强度却要大得多,对高原序列线性倾向率的估计有较大的影响。     

洞庭湖区近百年气温序列构建及其变化特征

采用统计方法并结合气象台站历史沿革信息,对1910-2010年洞庭湖区气温观测资料进行均一性检验和订正,并利用洞庭湖区周边气象台站资料对洞庭湖区1951年以前缺测的气温资料进行插补,构成完整的气温序列。基于洞庭湖区完整气温序列,构建洞庭湖区近百年气温序列并分析其变化特征。结果表明：1910-2010年洞庭湖区年平均气温呈显著上升趋势,其中冬季和春季平均气温上升幅度最大,秋季次之,夏季变化趋势不显著;气温变化存在明显的冷暖交替,冷暖期交替比中国地区更频繁;近百年洞庭湖区年和冬季、春季、秋季平均气温均存在一个显著增暖的突变点;小波分析表明,近百年洞庭湖区年和四季平均气温均经历了冷-暖-冷-暖4个阶段的交替。     

城市热岛效应对甘肃省温度序列的影响

对甘肃省若干国家基本/基准站、城市站和乡村站1961—2002年共42年季、年平均温度资料等进行了对比分析。结果表明:城市站和国家基本/基准站比乡村站增温趋势显著。近40多年来城市热岛效应对基本/基准站年平均温度的增温贡献率为18.5%,对城市站年平均温度的增温贡献率为37.6%。季节增温率冬季最大,秋季次之,春夏季最小;城市热岛效应对季节增暖的贡献率则为春季最大,夏季次之,秋冬季最小。     

城市热岛强度变化对安徽省气温序列的影响

根据安徽省81个气象台站的资料研究了其气温序列特点,并选取了其中46个台站,划分为城市站、乡村站、国家基本/基准站等类别,对1966～2005年期间平均、最高、最低气温的年、季变化进行了分析比较.结果表明:两个时段各类型台站3项气温的增温率、热岛增温率、热岛增温贡献率均表现为城市站最大,国家基本/基准站次之,乡村站最小...     

中国1940年代“偏暖”的资料问题

利用多套中国近百年气温观测资料和台站历史沿革信息,通过还原和对比分析早期发表的百年气温序列,探讨分析了20世纪40年代“偏暖”记录的资料问题。结果表明:20世纪50年代初大量台站迁移造成观测序列非均一性问题,导致了早期气温记录相对偏高。因而,基于原始资料构建的中国百年气温序列在20世纪40年代有一个明显的暖峰,而基于均一化资料构建的序列则无此暖峰,由此估算的中国百年气候增暖趋势（1.41 ℃/100 a）大于早期的大部分估算结果。     

中国60城市站1901—2019年日降水数据集的构建

近年来中国区域降水的极端化问题得到学术界的广泛关注,有关研究也获得了大量成果。但是,目前国内外常用的高分辨率降水资料序列多从1951年左右开始,普遍缺少20世纪早期中国的逐日降水资料,对于近一百多年中国极端降水变化特征及其机理,目前还不清楚。基于多来源的1901—1950年原始观测报表数字化逐日降水资料,补充先前未录入的“无降水”和缺测数据,研发质量控制方案并开展质量控制,补充录入检出的缺失和错误数据并再次质控,结合1951年以来的现代降水日值资料,建立中国60个城市站1901—2019年降水日值数据集。数据集评估结果显示,早期中国东部地区的台站较为密集,数据完整性和正确性较好,但中国西部的台站数量少且完整性和正确性偏低。本数据集构建的年总降水量累积值序列与已有的月降水量数据基本一致。基于该数据集,研究发现重庆站近百年来的降水未出现显著的趋势性变化。该数据集使后续分析研究中国极端降水的百年尺度长期变化特征成为可能。     

河北保定气象站长序列气温资料缺测记录插补和非均一性订正

基于多源的气温月值资料,在数据整合和初步质量控制基础上,同时采用标准化序列法和多元线性回归法对河北保定气象站1913-2014 年月平均气温、最高气温和最低气温资料进行了插补。通过交叉检验法分析发现,标准化序列法插补得到的气温序列效果较好,并且气候统计特征与同区域周边站的研究结果更具一致性。利用惩罚最大F 检验（PMF）对插补后序列的均一性进行了检验,结果表明：通过插补得到的保定站百年气温月值序列的均一性相对较好,仅月平均最低气温序列存在2 个显著间断点,分别由同类型仪器的更换和台站迁移导致,研究中采用分位数匹配（QM）对其进行了订正,建立了保定站百年气温月值序列。通过与邻近单站及我国中东部区域均一化百年气温序列的综合对比显示,本文建立的保定站百年气温月值序列与邻近单站的相关性基本达到0.8 以上;从增暖趋势来看,保定站与中东部区域平均序列分别达0.121 ℃/10a、0.204 ℃/10a,基本在同一量级内：这一定程度上说明建立的保定站百年气温序列相对合理。     

Change trends of air temperature and precipitation over Shanxi Province, China

A dataset of air temperature and precipitation time series (1959?C2008) from 61 stations across Shanxi, China is used to analyze the climate change. The monotonic trends and step (abrupt) trends for annual and seasonal series data of mean air temperature and total precipitation are tested by using Mann?CKendall test and Mann?CWhitney test, respectively. The results show that annual mean air temperature has increased by 1.20°C during the past 50?years. Winter, spring, and autumn have experienced a significant increase in air temperature. The step trend for annual mean air temperature is different from, but closely related with, those for seasonal mean air temperature. Spatially, there is an enhanced warming trend from south to north in Shanxi, and the most remarkable warming occurs in northern Shanxi. Annual precipitation has decreased by 99.20?mm during the past half century. The decrease is mainly caused by precipitation decline in rainy season (June?CSeptember), though precipitation in post-rainy season (October?CNovember) also tended to decrease. An abrupt decrease in precipitation has occurred since late 1970s. Decrease in precipitation is highest in central Shanxi and in the area along the west fringe between Sanchuan River and Fenhe River in western Shanxi.     

北京地区城市热岛强度变化对区域温度序列的影响

通过对北京地区20个台站1961~2000年月平均温度资料的对比分析,证实热岛效应对城市气象站记录的地表平均气温的绝对影响随时间显著增大,近20 a尤为突出,但其相对影响即热岛增温对全部增暖的贡献却呈下降趋势。近40 a来,北京地区的国家基本、基准站平均温度距平序列与被认为不受城市热岛影响的郊区站平均温度距平序列差异明显,由于热岛效应加强因素引起的国家基本、基准站平均年温度变化速率为0.16℃/(10 a),对整个时期全部增温的贡献达到71%;近20 a来热岛效应加强因素使北京地区国家基本、基准站年平均温度每10 a增暖0.33℃,对该时期全部增温的贡献达到49%。城市热岛效应加强因素对国家基本、基准站季节平均温度上升的贡献在夏、秋季高,冬季最小。本文的结果说明,目前根据国家基本、基准站资料建立的全国或较大区域平均温度序列可能在很大程度上保留着城市化的影响,有必要做进一步的检验和订正。     

Trends and uncertainties in surface air temperature over the Tibetan Plateau, 1951–2013

Trends and uncertainties of surface air temperature over the Tibetan Plateau (TP) are evaluated by using observations at 100 meteorological stations during the period 1951–2013. The sampling error variances of gridded monthly data are estimated for every month and every grid box of data. The gridded data and their sampling error variances are used to calculate TP averages, their trends, and associated uncertainties. It is shown that large sampling error variances dominate northern and western TP, while small variances appear over southern and eastern TP. Every month from January to December has a positive linear trend during the study period. February has the largest trend of 0.34 ± 0.18°C (10 yr)^–1, and April the smallest at 0.15 ± 0.11°C (10 yr)^–1. The uncertainties decrease steadily with time, implying that they are not large enough to alter the TP warming trend.