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     

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.     

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.     

近50年我国探空温度序列均一化及变化趋势

利用1958—2005年我国116个站探空温度序列研究了我国高空温度变化趋势。首先通过静力学质量控制和两相回归法对原始序列进行了均一化处理。我国探空温度序列存在明显的间断点, 间断点的订正对于序列的趋势影响较为显著。缺测率是影响我国探空温度序列应用性的重要因子, 也是区域平均趋势统计中台站取舍的指标, 减少台站总数会削弱我国对流层升温和平流层降温的变化趋势。分析表明: 70%作为最小资料有效率标准最为合理。为满足最小资料有效率, 选取92个站统计我国高空温度变化趋势的区域平均值。结果表明: 1958-2005年, 平流层下层和对流层上层降温, 对流层中、低层升温; 高空温度变化趋势与研究时段明显相关, 1958-1978年我国高空大气整层均为降温; 1979—2005年, 对流层中低层升温最为明显, 增暖的幅度随高度增加而减小, 400 hPa以上各层转为降温。对流层的升温始于20世纪80年代, 升温幅度与全球尺度的平均值有所不同。     

Long-Term Trend of Temperature Derived by Statistical Downscaling Based on EOF Analysis

This study analyzes the ability of statistical downscaling models in simulating the long-term trend of temperature and associated causes at 48 stations in northern China in January and July 1961–2006. The statistical downscaling models are established through multiple stepwise regressions of predictor principal components (PCs). The predictors in this study include temperature at 850 hPa (T850), and the combination of geopotential height and temperature at 850 hPa (H850+T850). For the combined predictors, Empirical Orthogonal Function (EOF) analysis of the two combined fields is conducted. The modeling results from HadCM3 and ECHAM5 under 20C3M and SERS A1B scenarios are applied to the statistical downscaling models to construct local present and future climate change scenarios for each station, during which the projected EOF analysis and the common EOF analysis are utilized to derive EOFs and PCs from the two general circulation models (GCMs). The results show that (1) the trend of temperature in July is associated with the first EOF pattern of the two combined fields, not with the EOF pattern of the regional warming; (2) although HadCM3 and ECHAM5 have simulated a false long-term trend of temperature, the statistical downscaling method is able to well reproduce a correct long-term trend of temperature in northern China due to the successful simulation of the trend of main PCs of the GCM predictors; (3) when the two-field combination and the projected EOF analysis are used, temperature change scenarios have a similar seasonal variation to the observed one; and (4) compared with the results of the common EOF analysis, those of the projected EOF analysis have been much more strongly determined by the observed large-scale atmospheric circulation patterns.     

Impacts of Reference Time Series on the Homogenization of Radiosonde Temperature

Using radiosonde temperatures of 92 selected stations in China,the uncertainties in homogenization processes caused by different reference series,including nighttime temperature,the NCEP (National Centers for Environmental Prediction) and ERA-40 (European Centre for Medium-Range Weather Forecasts) forecasting background,are examined via a two-phase regression approach.Although the results showed limited consistency in the temporal and spatial distribution of identified break points (BPs) in the context of metadata events of instrument model change and correction method,significant uncertainties still existed in BP identification,adjustment,and impact on the estimated trend.Reanalysis reference series generally led to more BP identification in homogenization.However,those differences were parts of global climatic shifts,which may have confused the BP calculations.Discontinuities also existed in the reanalysis series due to changes in the satellite input.The adjustment values deduced from the reanalysis series ranged widely and were larger than those from the nighttime series and,therefore,impacted the estimated temperature trend.     

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).     

利用多模式对中国气温序列中不连续点的检测

发展了一种对元数据依赖程度较小的气候序列均一化思路,在缺乏元数据的基础上,采取3种不同的方法,对中国东南部地区年平均最高、最低气温序列进行了均一性检验;并对其中不连续的气温序列进行了订正.对比表明,订正后序列较订正前更为合理.在检验过程中发现,对于最低气温检验可以明显得出比最高气温更多的不连续点.为了进一步认识这个问题,对此进行了进一步分析,认为最低温度对变化更为敏感主要是由于其物理特征:最低温度一般出现在夜间,夜间大气较为稳定,因此一些变化(如仪器,迁站)可能引起明显的不连续现象,而最高气温往往出现在白天,因此大气混合比较充分,空间的均一性要明显强于最低温度.另外,热岛现象、台站密度等因素均是影响气温序列均一化的因素.     

Long-Term Trends in Extreme Temperatures in Hong Kong and Southern China

The observed long-term trends in extreme temperatures in Hong Kong were studied based on the meteorological data recorded at the Hong Kong Observatory Headquarters from 1885-2008. Results show that, over the past 124 years, the extreme daily minimum and maximum temperatures, as well as the length of the warm spell in Hong Kong, exhibit statistically significant long-term rising trends, while the length of the cold spell shows a statistically significant decreasing trend. The time-dependent return period analysis also indicated that the return period for daily minimum temperature at 4°C or lower lengthened considerably from 6 years in 1900 to over 150 years in 2000, while the return periods for daily maximum temperature reaching 35°C or above shortened drastically from 32 years in 1900 to 4.5 years in 2000. Past trends in extreme temperatures from selected weather stations in southern China from 1951-2004 were also assessed. Over 70% of the stations studied yielded a statistically significant rising trend in extreme daily minimum temperature, while the trend for extreme maximum temperatures was found to vary, with no significant trend established for the majority of stations.     

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。     

塔克拉玛干沙漠腹地1961-1998年逐月平均气温序列的重建

 利用塔里木盆地周边27个气象站1961-2006年逐月平均气温和塔中气象站1999-2006年逐月平均气温资料,同时选取1961-2006年NCEP/NCAR 2.5°×2.5°经纬度距地表2 m的月平均气温再分析格点资料,分别用逐步回归分析、EOF分解和NCEP资料3种方法对塔中气象站1961-1998年历年逐月平均气温序列进行了恢复与重建,分析了误差,并与周边气象站的变化特征进行对比。结果表明,逐步回归和EOF法都能够作为重建塔中逐月平均气温的方法,但相对而言,逐步回归法重建的序列误差更小,平均拟合绝对误差为0.3℃,最大绝对误差为1.9℃。而NCEP/NCAR资料由于冬季存在明显的系统性误差,数值显著偏高,不能用于塔中气温序列的重建。     

Extreme Temperature Change of the Last 110 Years in Changchun,Northeast China

In China and East Asia,the long-term continuous observational data at daily resolution are insufficient,and thus there is a lack of good understanding of the extreme climate variation over the last 100 years plus.In this study,the extreme temperature indices defined by ETCCDI(Expert Team on Climate Change Detection and Indices)and local meteorological administrations were analyzed for Changchun City,Northeast China,by using the daily maximum temperature(Tmax)and daily minimum temperature(Tmin)over 1909?2018.The results showed that extreme cold events,such as cold days,cold nights,frost days,icing days,and low temperature days,decreased significantly at rates of?0.41 d(10 yr)^?1,?1.45 d(10 yr)^?1,?2.28 d(10 yr)^?1,?1.16 d(10 yr)?1 and?1.90 d(10 yr)^?1,respectively.Warm nights increased significantly at a rate of 1.71 d(10 yr)^?1,but warm days decreased slightly and the number of high temperature days decreased at a rate of?0.20 d(10 yr)?1.The frequency of cold surge events increased significantly at a rate of 0.25 d(10 yr)^?1,occurring mainly from the mid-1950s to late-1980s.The average Tmax,average Tmin and extreme Tmin increased at rates of 0.09℃(10 yr)^?1,0.36℃(10 yr)^?1 and 0.54℃(10 yr)^?1,respectively;and extreme Tmax decreased significantly at a rate of?0.17℃(10 yr)^?1.In 1909?2018,1951?2018 and 1979?2018,the indices related to cold events decreased,while the trends of the indices related to warm events were different for different periods.     

探空资料中的人为误差对中国温度长期变化趋势的影响

利用1958～2005年探空温度序列, 通过质量控制、均一化处理和序列缺测率分析, 探讨了探空资料中人为误差对中国高空气温变化趋势的影响。中国探空温度序列存在明显的间断点, 72%的序列包含2～4个间断点。相应的订正总体上降低了1958年以来平流层低层降温和对流层升温趋势, 如700 hPa和100 hPa平均趋势值分别降低0.12 K/10 a和0.04 K/10 a。缺测率是气温区域平均趋势估算的重要参数, 30%作为最大缺测率是中国探空温度序列适宜的取样标准。提高取样标准 (台站数减少) 使1958～2005年间对流层上层和平流层下层的降温趋势减弱。中国高空气温变化趋势与全球或北半球大体一致, 但也有不同特点: 500 hPa以下大气趋于升温, 以上则趋于降温, 最大降温趋势位于对流上部的300 hPa, 而且各气候区间区域差异性十分明显。     

中国东北地区近百年气温序列的小波分析

利用1905-2005年中国东北地区哈尔滨、长春、沈阳和大连的气温时间序列资料,在分析气温变化结构的基础上进行小波分析,以揭示气温变化的多时间尺度的复杂结构。同时,分析了不同时间尺度下气温序列变化的周期性变化规律和突变点。结果表明：近100 a来中国东北地区的平均气温呈升高趋势,尤其在20世纪80年代以后升高趋势更加显著,升温率达到0.165 ℃/10 a。气温存在2～3 a、8～12 a、20～25 a和45 a左右时间尺度的多重时间尺度结构的变化特征。     

中国东北地区近百年气温序列的小波分析

 利用1905-2005年中国东北地区哈尔滨、长春、沈阳和大连的气温时间序列资料,在分析气温变化结构的基础上进行小波分析,以揭示气温变化的多时间尺度的复杂结构。同时,分析了不同时间尺度下气温序列变化的周期性变化规律和突变点。结果表明：近100 a来中国东北地区的平均气温呈升高趋势,尤其在20世纪80年代以后升高趋势更加显著,升温率达到0.165 ℃/10 a。气温存在2～3 a、8～12 a、20～25 a和45 a左右时间尺度的多重时间尺度结构的变化特征。     

Updated Homogenized Chinese Temperature Series with Physical Consistency

Most methods of homogenization of climate data are applied to time series of a single variable, such as daily maximum temperature(Tmax) or daily minimum temperature(Tmin). Consequently, the physical relationship among different variables, e.g., TmaxTmin, may be distorted after homogenization of climate series of individual variables. The authors develop a solution to improve consistency among diurnal temperature records, while using the Multiple Analysis of Series for Homogenization(MASH) method to homogenize the observation series of daily mean temperature(Tm), Tmin, and Tmax at 545 stations in China for the period 1960–2011, called CHTM2.0. In the previous version of this homogenized dataset based on MASH(CHTM1.0) for the period 1960–2008, there are a few records(0.039% of the total) that are physically inconsistent. For developing CHTM2.0, the authors apply additional adjustments for each day with inconsistent temperature records, in order to hold TmaxTmTmin. Although the additional adjustments are barely influential for estimating long-term climate trends in China as a whole(because very few records are additionally adjusted), the newly introduced solution improves the physical consistency throughout the dataset. It is also helpful for developing more reasonable homogenized climate datasets with regard to physical consistency among multiple variables. Based on CHTM2.0, the annual Tmax/Tm/Tmin series averaged over China for the period 1960–2011 show significant warming trends of about 0.19/0.25/0.34°C per decade, respectively. Large warming trends of up to 0.425/0.596/ 0.704°C per decade occur in northeastern and northwestern China.     

Quantile Trends in Temperature Extremes in China

A number of recent studies have examined trends in extreme temperature indices using a linear regression model based on ordinary least-squares. In this study, quantile regression was, for the first time, applied to examine the trends not only in the mean but also in all parts of the distribution of several extreme temperature indices in China for the period 1960-2008. For China as a whole, the slopes in almost all the quantiles of the distribution showed a notable increase in the numbers of warm days and warm nights, and a significant decrease in the number of cool nights. These changes became much fas- ter as the quantile increased. However, although the number of cool days exhibited a significant decrease in the mean trend estimated by classical linear regression, there was no obvious trend in the upper and lower quantiles. This finding suggests that examining the trends in different parts of the distribution of the time-series is of great importance. The spatial distribution of the trend in the 90th quantile indicated that there was a pronounced increase in the numbers of warm days and warm nights, and a decrease in the number of cool nights for most of China, but especially in the northern and western parts of China, while there was no significant change for the number of cool days at almost all the stations.     

基于卫星观测的南海表层温度气候学特征及长期变化

利用高分辨率AVHRR Pathfinder卫星海表温度资料,分析了1982-2012年南海及其毗邻海区海表温度（SST）的变化趋势,并给出了近30年该海域SST的气候学特征。结果表明：南海年平均SST随纬度的增加而降低,且越靠近陆地海温梯度越大,等温线呈西南-东北向分布;南海最高、最低SST分别出现在夏季和冬季;夏季中南半岛和海南岛东侧存在相对低温区,应与西南季风和地转偏向力共同作用引起的深层冷水涌升有关;近30年南海及毗邻海区年平均SST增温趋势为0.100℃/10a,20世纪90年代末到21世纪初年平均SST处于高值期,最高值出现在1998年;南海海区四季均存在变暖趋势,冬季增温趋势最大,为0.194℃/10a,夏、春季次之,分别为0.121℃/10a和0.107℃/10a,秋季最小,为0.086℃/10a;近30年台湾海峡和中国大陆东南沿海增温最显著,最大增温值达到0.7℃/10a以上。     

Detection and Adjustment of Undocumented Discontinuities in Chinese Temperature Series Using a Composite Approach

Annually averaged daily maximum and minimum surface temperatures from southeastern China were evaluated for artificial discontinuities using three different tests for undocumented changepoints. Changepoints in the time series were identified by comparing each target series to a reference calculated from values observed at a number of nearby stations. Under the assumption that no trend was present in the sequence of target-reference temperature differences, a changepoint was assigned to the target series when at least two of the three tests rejected the null hypothesis of no changepoint at approximately the same position in the difference series. Each target series then was adjusted using a procedure that accounts for discontinuities in average temperature values from nearby stations that otherwise could bias estimates of the magnitude of the target series step change. A spatial comparison of linear temperature trends in the adjusted annual temperature series suggests that major relative discontinuities were removed in the homogenization process. A greater number of relative change points were detected in annual average minimum than in average maximum temperature series. Some evidence is presented which suggests that minimum surface temperature fields may be more sensitive to changes in measurement practice than maximum temperature fields. In addition, given previous evidence of urban heat island (i.e., local) trends in this region, the assumption of no slope in a target-reference difference series is likely to be violated more frequently in minimum than in maximum temperature series. Consequently, there may be greater potential to confound trend and step changes in minimum temperature series.     

中国夏季极端酷暑的气候统计和趋势分析

Based on the daily maximum air temperature data from 300 stations in China from 1958 to 2008, the climatological distribution of the number of days with high temperature extremes （HTEs, maximum temperatures higher than 35℃） are studied with a focus on the long-term trends. Although the number of HTE days display well-defined sandwich spatial structures with significant decreasing trends in central China and increasing trends in northern China and southern China, the authors show that the decrease of HTE days in central China occurs mainly in the early period before the 1980s, and a significant increase of HTE days dominates most of the stations after the 1980s. The authors also reveal that there is a jump-like acceleration in the number of HTE days at most stations across China since the mid 1990s, especially in South China, East China, North China, and northwest China.