近60年中国探空观测气温变化趋势及不确定性研究

基于118站探空资料研究了近60年中国850—100 hPa气温变化趋势及季节和区域特征,并通过与1979—2017年卫星微波气温的对比研究了中国探空气温均一化的不确定性。研究表明,1958—2017年中国平均对流层气温呈上升趋势,300 hPa升温最为显著,平流层下层（100 hPa）为降温趋势。冬季对流层上层升温趋势和夏季平流层下层降温趋势较强。1979—2017年较整个时段对流层升温趋势较强,平流层下层降温趋势较弱。青藏高原和西北地区对流层上层升温趋势较强。通过与卫星微波气温和邻近探空站探空气温的对比以及均一化前后日夜气温差值检测出中国探空均一化气温仍残存非均一性问题。由于参照序列的局限性,均一化未能完全去除21世纪最初10年中国探空系统变化造成的对流层中、上层至平流层下层气温系统性下降的影响,导致中国对流层上层升温趋势被低估和平流层下层降温趋势被高估。未来可通过参考卫星微波气温和邻近探空站序列调整非均一性订正顺序并增加合理性检验等方法改进中国探空气温均一化方案。      

3种方法对中国探空温度资料均一性检验对比分析

利用美国国家气候数据研究中心开发的Pairwise均一性检验订正方法,加拿大环境研究中心开发的PMFT方法和PMT方法,结合20世纪再分析资料和详细的元数据信息对1951-2008年中国123个探空台站的温度资料进行均一性检验和订正。结果表明：3种方法对中国探空温度资料订正幅度和订正前后的趋势变化存在差异。产生差异的主要原因,一方面是由于Pairwise方法设计的问题,导致对中国大部分台站同时改变辐射误差订正方法和系统升级造成的断点检测能力较弱;另一方面是由于PMFT方法未使用参考序列,不能去除气候变化本身的变化趋势,导致PMFT方法在断点判断上存在漏判的现象。而PMT方法结合20世纪再分析资料的客观判断方法较适合中国探空资料的均一性检验和订正,其订正结果表明,利用该方法得到的中国探空温度数据的统计学特征在低层小于全球尺度探空温度的订正结果,而在高层基本和全球探空数据的订正尺度相当。两个间断点和0.0-0.2℃的订正量所占的比例最大。从全国的来看,对流层为增温趋势,这种增温趋势随高度的增加逐渐减弱,至对流层顶100 hPa转为弱的降温趋势。     

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。     

基于再分析资料与观测资料的中国低温阈值变化特征研究

采用1979—2013年中国192站逐日最低温度观测资料和NCEP/NCAR、NCEP/DOE、JRA-55、ERA-Interim再分析资料及1979—2004年均一化资料,分别计算低温阈值并对比分析其气候态、年际和年代际变化、长期趋势等特征。结果表明:与观测结果相比,均一化资料阈值在东北、内蒙古西部和两广等地偏低,在青藏高原东侧、新疆北部和黄河中下游偏高,线性趋势则相反;再分析资料阈值在南方偏低、东北偏高,在东部的可信度高于西部;再分析资料能显示内蒙古中西部的降温趋势和青藏高原的增温趋势,但在数值和范围上有差异,且均低估了观测资料反映的华北地区的显著升温现象;再分析资料能体现观测资料阈值的全区一致性、东北与其他地区反相的空间分布及其年际变化特征,仅JRA-55和ERA-Interim可再现低温阈值的年代际变化特征。     

过去近50年全球变暖纬向平均模

Zonal mean annual temperature trends were estimated using four reanalysis and three analysis grid datasets. The trends over land and for the entire globe were estimated from 1958-2001 and 1979-2007, respectively. Estimates of temperature trends over land from Climate Research Unit (CRU) analysis data indicate more intense warming moving northward, at a rate of about 3.5ºC per century at 65ºN, then declining further to the north. CRU estimates indicated dramatic warming over the latitudes of the Antarctic Peninsula, with a localized cooling trend at 45ºS. A global estimate was conducted by comparing estimates of the reanalysis datasets. Temperature distribution trends of the reanalysis data were similar to those generated by land observations but with large bias in the Polar Regions. The bias could be reduced by comparing these estimates with those from the analysis data at high latitudes. Extreme warming trends were estimated at rates of 2.9ºC-3.5ºC per century in the Arctic and 3.2ºC-4.7ºC per century in the Antarctic for 1958-2001. Surface warming was even more intense in the Northern Hemisphere for 1979-2007, with extreme arctic warming rates ranging from 8.5ºC-8.9ºC per century, as estimated by the analysis and reanalysis datasets. Trends over Antarctica for this period were contradictory, as Japan Meteorological Agency (JMA) reanalysis (JRA-25) indicated a cooling trend at about -7ºC per century, while other reanalysis datasets showed sharp warming over the continent.     

中国探空观测与多套再分析资料气温序列的对比研究

为比较中国探空观测与再分析气温的差异,利用中国118站850—30 hPa经质量控制和均一化处理后逐月气温和NCEPv1、NCEPv2、ERA-40、ERA-Interim、JRA55、20CR、MERRA和CFSR等8套再分析月平均气温,通过对比1981—2010年探空观测与多套再分析气温序列的平均偏差、相关系数、标准差和变化趋势,分析两者在数值、年际变率、离散度及长期变化的差异。结果表明,中国探空温度原始序列存在较为显著的非均一性,均一化对原始气温序列总体为负订正,对流层上层至平流层下层(200—100 hPa)订正值最为显著。均一化气温去除了原始序列中由仪器换型和系统升级等因素导致的系统误差,与再分析气温相关较原始序列明显提高。再分析气温与均一化气温偏差约1℃,多数再分析气温较均一化气温在对流层偏低、平流层偏高。再分析与均一化气温年际变率较为一致,正相关达到显著。多数再分析与均一化气温均在对流层中低层呈上升趋势、平流层中层呈下降趋势。对流层上层和平流层下层不确定性较大。总体上,ERA-Interim、JRA55和MERRA与其他再分析相比更相近中国均一化探空气温。      

Effect of data homogenization on estimate of temperature trend: a case of Huairou station in Beijing Municipality

Daily minimum temperature (Tmin) and maximum temperature (Tmax) data of Huairou station in Beijing from 1960 to 2008 are examined and adjusted for inhomogeneities by applying the data of two nearby reference stations. Urban effects on the linear trends of the original and adjusted temperature series are estimated and compared. Results show that relocations of station cause obvious discontinuities in the data series, and one of the discontinuities for Tmin are highly significant when the station was moved from downtown to suburb in 1996. The daily Tmin and Tmax data are adjusted for the inhomogeneities. The mean annual Tmin and Tmax at Huairou station drop by 1.377°C and 0.271°C respectively after homogenization. The adjustments for Tmin are larger than those for Tmax, especially in winter, and the seasonal differences of the adjustments are generally more obvious for Tmin than for Tmax. Urban effects on annual mean Tmin and Tmax trends are ?0.004°C/10 year and ?0.035°C/10 year respectively for the original data, but they increase to 0.388°C/10 year and 0.096°C/10 year respectively for the adjusted data. The increase is more significant for the annual mean Tmin series. Urban contributions to the overall trends of annual mean Tmin and Tmax reach 100% and 28.8% respectively for the adjusted data. Our analysis shows that data homogenization for the stations moved from downtowns to suburbs can lead to a significant overestimate of rising trends of surface air temperature, and this necessitates a careful evaluation and adjustment for urban biases before the data are applied in analyses of local and regional climate change.     

北京1841年以来均一化最高和最低气温日值序列的构建

长期连续的日值观测资料是研究百年来极端气候事件及其变化特征的重要基础支撑.目前中外由于缺乏可靠的逐日百年尺度气候资料,使得20世纪50年代以前的极端气候变化规律仍然没有得到很好的认识.基于国家气象信息中心收集整理的日最高和最低气温观测资料,构建北京1841—2019年气温日值序列.首先,通过数据质量控制剔除原始基础资料...     

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。     

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.     

Estimation of sampling error uncertainties in observed surface air temperature change in China

This study examines the sampling error uncertainties in the monthly surface air temperature (SAT) change in China over recent decades, focusing on the uncertainties of gridded data, national averages, and linear trends. Results indicate that large sampling error variances appear at the station-sparse area of northern and western China with the maximum value exceeding 2.0 K² while small sampling error variances are found at the station-dense area of southern and eastern China with most grid values being less than 0.05 K². In general, the negative temperature existed in each month prior to the 1980s, and a warming in temperature began thereafter, which accelerated in the early and mid-1990s. The increasing trend in the SAT series was observed for each month of the year with the largest temperature increase and highest uncertainty of 0.51 ± 0.29 K (10 year)⁻¹ occurring in February and the weakest trend and smallest uncertainty of 0.13 ± 0.07 K (10 year)⁻¹ in August. The sampling error uncertainties in the national average annual mean SAT series are not sufficiently large to alter the conclusion of the persistent warming in China. In addition, the sampling error uncertainties in the SAT series show a clear variation compared with other uncertainty estimation methods, which is a plausible reason for the inconsistent variations between our estimate and other studies during this period.

     

两种再分析资料中夏季地表气温与中国测站资料的差异

采用中国194站气温观测资料(OT)、NCEP/NCAR (NT) 和ERA-40 (ET) 再分析月平均2 m温度资料, 使用线性分析、 方差分析、 小波分析、 EOF等方法, 对三种温度资料周期、 方差以及年际和年代际变化进行对比分析。结果发现: (1) ET与OT数值、 距平及变化趋势非常接近; NT低于OT, 1965年以前其数值及距平与OT、 ET差异较大; ET与OT的相似性优于NT, 对地面温度变化进行周期分析时, 使用ET资料较好。在使用NT的原始资料时需慎重, 距平值在1965年之后有一定的可信度。 (2) ET与OT线性趋势以及空间模态类似, NT变化趋势远大于OT与ET, ET对我国温度长期变化趋势的再现能力优于NT, 在研究我国温度长期变化时NT具有不确定性。 (3) ET与NT均能反映我国温度的时空分布和变化特征, 但ET更加准确; 研究我国北方 (30°N以北) 温度年代际变化时, ET较好; 研究我国温度年际变化时两种资料能力相当。 (4) 三种温度资料均显示1976年前后我国地表气温有明显差异。ET与OT在1976年前后的变化及空间分布十分一致, NT与OT不完全一致。此外, 1965年之前的NCEP/NCAR温度资料存在类似于“PSFC”的问题, 使用时应慎重。     

Temperature and Precipitation Changes in China During the Holocene

We review here proxy records of temperature and precipitation in China during the Holocene, especially the last two millennia. The quality of proxy data, methodology of reconstruction, and uncertainties in reconstruction were emphasized in comparing different temperature and precipitation reconstruction and clarifying temporal and spatial patterns of temperature and precipitation during the Holocene. The Holocene climate was generally warm and wet. The warmest period occurred in 9.6-6.2 cal ka BP, whereas a period of maximum monsoon precipitation started at about 11.0 cal ka BP and lasted until about 8.0-5.0 cal ka BP. There were a series of millennial-scale cold or dry events superimposed on the general trend of climate changes. During past two millennia, a warming trend in the 20th century was clearly detected, but the warming magnitude was smaller than the maximum level of the Medieval Warm Period and the Middle Holocene. Cold conditions occurred over the whole of China during the Little Ice Age （AD 1400-AD 1900）, but the warming of the Medieval Warm Period （AD 900-AD 1300） was not distinct in China, especially west China. The spatial pattern of precipitation showed significant regional differences in China, especially east China. The modern warm period has lasted 20 years from 1987 to 2006. Bi-decadal oscillation in precipitation variability was apparent over China during the 20th century. Solar activity and volcanic eruptions both were major forcings governing the climate variability during the last millennium.     

Underestimation of the Warming Trend over the Tibetan Plateau during 1998–2013 by Global Land Data Assimilation Systems and Atmospheric Reanalyses

Accurate surface air temperature (T2m) data are key to investigating eco-hydrological responses to global warming. Because of sparse in-situ observations, T2m datasets from atmospheric reanalysis or multi-source observation-based land data assimilation system (LDAS) are widely used in research over alpine regions such as the Tibetan Plateau (TP). It has been found that the warming rate of T2m over the TP accelerates during the global warming slowdown period of 1998–2013, which raises the question of whether the reanalysis or LDAS datasets can capture the warming feature. By evaluating two global LDASs, five global atmospheric reanalysis datasets, and a high-resolution dynamical downscaling simulation driven by one of the global reanalysis, we demonstrate that the LDASs and reanalysis datasets underestimate the warming trend over the TP by 27%–86% during 1998–2013. This is mainly caused by the underestimations of the increasing trends of surface downward radiation and nighttime total cloud amount over the southern and northern TP, respectively. Although GLDAS2.0, ERA5, and MERRA2 reduce biases of T2m simulation from their previous versions by 12%-94%, they do not show significant improvements in capturing the warming trend. The WRF dynamical downscaling dataset driven by ERA-Interim shows a great improvement, as it corrects the cooling trend in ERA-Interim to an observation-like warming trend over the southern TP. Our results indicate that more efforts are needed to reasonably simulate the warming features over the TP during the global warming slowdown period, and the WRF dynamical downscaling dataset provides more accurate T2m estimations than its driven global reanalysis dataset ERA-Interim for producing LDAS products over the TP.     

资料均一化对气温变化趋势及其城市化偏差估计的影响：以北京地区为例

当前的地面气候观测资料普遍存在非气候性因素导致的非均一性,对气候变化监测和研究结论可靠性造成重要影响。结合观测台站的历史沿革数据,使用ACMANT和Pairwise Comparisons方法以及RHtest V4软件,对北京地区20个台站均一化前的月平均气温序列进行了非均一性检验和订正,最后评估了均一化对北京地区气温序列变化趋势及其城市化偏差估算的影响。结果表明：除元数据中记录的断点外,无元数据记录的断点也会对序列的趋势变化造成明显影响,其中乡村站最显著;经过订正,1958—2018年整个北京地区、乡村站以及城市站增温趋势分别为0.27℃/(10 a)、0.10℃/(10 a)和0.32℃/(10 a),较订正前分别上升了0.03℃/(10 a)、0.06℃/(10 a)和0.02℃/(10 a)。利用均一化资料估算,1958—2018年北京观象台的城市化影响为0.24℃/(10 a),城市化贡献率为70.2%,评估结果较前人结论有所降低。可见,在现有的北京地区气温资料序列中,仍可能存在较明显的非均一性和未被记录的断点,对区域平均气温趋势估算具有显著影响。     

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.     

中国825个基准、基本站地面气压系统误差的检验与订正

使用RHtest均一化方法结合元数据信息对中国825个基准、基本站的地面气压月值数据进行均一性检验与订正,结果发现有400个站的气压数据均一,425个站存在系统误差。对于后者,使用静力模式订正可消除255个站的系统误差,另外170个站采用均值订正,均值订正的断点共245个。对气候趋势和个例的分析表明,上述方法对气压数据均一化订正效果明显。均一化之后站点气压长期趋势的空间一致性更好,中国东南沿海和西北部的新疆地区气压表现出下降趋势,中部地区主要表现出上升趋势。     

气候变化趋势分析中自相关的检验与去除

受资料本身、分析方法及未来排放情景假设等因素影响, 气候变暖幅度尚存在较大的不确定性。从分析方法入手, 探讨气象观测序列可能存在的自相关及其对气候变化趋势分析的不确定性影响。引入了Durbin-Watson一阶自相关检验方法对气象观测序列进行检验, 并用Cochrane-Orcutt方法去除存在的自相关。分析发现:浙江省平湖市气温序列存在的自相关放大了该站气温的升温趋势, 并且虚高了气温变化趋势的显著性水平。因此, 对资料序列进行自相关检验与去除是十分必要的。     

Climate variability and change in Bulgaria during the 20th century

Summary Climate data used for climate variability and change analyses, must be homogeneous, to be accurate. The data currently used in the Météo-France homogenization procedure, which does not require computation of regional reference series, was applied to precipitation and average air temperature series in Bulgaria. The Caussinus-Mestre method, with a double-step procedure, was used to detect multiple breaks and outliers in the long-term series of precipitation and average air temperature. A two factor linear model was applied for break correction. The homogenization procedure was run till all or most break risk was gone. Analysis of climate variability and change in Bulgaria during the 20^th century was done on already homogenized precipitation and average air temperature series. The statistical significance of the trends obtained was evaluated by the coefficient of Spearman rank correlation. The variations of annual precipitation in Bulgaria showed an overall decrease. The country has experienced several drought episodes during the 20^th century, most notably in the 1940s and 1980s. Seasonal precipitation in spring shows a positive trend at most weather stations across the country. The trend for summer and autumn precipitation is negative. A statistically significant increasing trend of winter precipitation in north Bulgaria was detected. No significant warming trend in the country was found during the last century inspite of the warming observed during the last two decades. Summer in Bulgaria tends to be warmer from the beginning of the 1980s. There is a statistically significant increasing trend of average air temperature during the winter season at the weather stations near the Danube river (north Bulgaria) during the periods 1901–2000 and 1931–2000.     

Climate spectra and detecting climate change

Part of the debate over possible climate changes centers on the possibility that the changes observed over the previous century are natural in origin. This raises the question of how large a change could be expected as a result of natural variability. If the climate measurement of interest is modelled as a stationary (or related) Gaussian time series, this question can be answered in terms of (a) the way in which change is estimated, and (b) the spectrum of the time series. These computations are illustrated for 128 years of global temperature data using some simple measures of change and for a variety of possible temperature spectra. The results highlight the time scales on which it is important to know the magnitude of natural variability. The uncertainties in estimates of trend are most sensitive to fluctuations in the temperature series with periods from approximately 50 to 500 years. For some of the temperature spectra, it was found that the standard error of the least squares trend estimate was 3 times the standard error derived under the naïve assumption that the temperature series was uncorrelated. The observed trend differs from zero by more than 3 times the largest of the calculated standard errors, however, and is therefore highly significant.