地面气候资料序列均一性检验与订正系统

采用国内外常用的几种气候序列均一性检验与订正方法,研制了气候序列均一性检验与订正系统,用于检验地面测站由于迁站、仪器变更、环境恶化等因素造成气候序列的非均一性,并进行订正.使用该系统对浙江省地面36个测站的年平均温度、年平均风速及年降水量序列进行了均一性检验,效果较好.     

江淮流域年降水量和温度的均一性检验

采用SNHT方法对江淮流域内苏皖两省41个代表站1961-2003年逐年降水量和平均温度序列进行均一性检验,结果表明绝大部分台站年降水和温度资料质量基本可靠,站址迁移是引起年降水和年平均温度非均一性的主要原因.     

近40年呼伦贝尔地区气候变暖初探

选取呼伦贝尔市8个代表站1961～2000年资料,用线性拟合等方法,对呼伦贝尔市及其林、牧、农区的年平均温度、季平均温度、年平均最高温度和年平均最低温度、气温日较差、无霜期和积温等进行了分析.结果表明:(1)全市近40年气候变暖明显,年平均气温、年平均最高温度和年平均最低温度均呈升高趋势.(2)年温升高的趋势主要受到冬季气温显著变化的影响.(3)年平均最高和最低气温变化表现出非常明显的不对称性趋势,气温日较差变小趋势是以最低温度升高高于最高温度升高为特点的.(4)无霜日数显著增加,无霜期延长,≥10℃积温带有明显北移的特征.     

近4O年呼伦贝尔地区气候变暖初探

选取呼伦贝尔市8个代表站1961～2000年资料，用线性拟合等方法，对呼伦贝尔市及其林、牧、农区的年平均温度、季平均温度、年平均最高温度和年平均最低温度、气温日较差、无霜期和积温等进行了分析。结果表明：(1)全市近40年气候变暖明显，年平均气温、年平均最高温度和年平均最低温度均呈升高趋势。(2)年温升高的趋势主要受到冬季气温显变化的影响。(3)年平均最高和最低气温变化表现出非常明显的不对称性趋势，气温日较差变小趋势是以最低温度升高高于最高温度升高为特点的。(4)无霜日数显增加，无霜期延长，≥10℃积温带有明显北移的特征。     

近36年德令哈市地面温度的变化特征及突变分析

利用1981—2016年德令哈市国家基本气象站地面温度和气温数据资料,从年、季和月3个方面研究地面温度的变化特征。结果表明:近36a德令哈市年平均地面温度、地面最高温度和地面最低温度分别以0.811℃/10a、0.063℃/10a和1.247℃/10a的气候倾向率呈上升趋势;各季平均地面温度和地面最低温度呈上升趋势,春季平均地面最高温度呈上升趋势而夏秋冬三季呈下降趋势;月平均地面温度和地面最高最低温度的变化呈单峰式特点,各月平均地面温度和地面最低温度呈上升趋势,平均地面最高温度1—6月份呈上升趋势,7—12月份呈下降趋势;年平均地面温度和地面最低温度分别在1997年和2001年出现突变,年平均地面最高温度未出现突变;年、季、月平均地面温度与平均气温呈显著的正相关。     

那曲站与其相邻野外站气象要素的对比分析

利用1955-2009年西藏那曲气象站(NQ站)和2001-2009年BJ野外气象站(BJ站)的观测资料,对NQ站和BJ站气温、风速的变化特征进行了对比分析。结果表明,BJ站的年平均温度和最低温度均低于NQ站,年平均风速反之;两站(NQ站-BJ站)温度差的增长率依次为最低温度(0.117℃.a-1)>年平均温度(0.034℃.a-1)>最高温度(-0.014℃.a-1),年平均风速为0.076m.s-1.a-1;以青藏铁路正式通车的2006年为界,2001-2005年和2006-2009年分别为人类活动影响较弱期和较强期。人类活动影响较强期与较弱期相比,两站温度差异增加的幅度依次为最低温度(0.512℃)>年平均温度(0.152℃)>最高温度(-0.025℃),年平均风速为-0.198m.s-1。     

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.     

我国40年年平均风速的均一性检验

采用1951~1990年我国690个站年平均风速资料, 进行均一性检验.结果表明SNHT方法适用于风速的均一性检验.我国年平均风速质量基本可靠.仪器变化是引起非均一的主要原因.     

PMFT方法对我国年平均风速的均一性检验

利用惩罚最大F检验(PMFT)方法并结合详尽的台站历史沿革信息对我国701个气象观测台站年平均风速资料进行了均一性检验,结果表明该检验方法能够应用于对年平均风速资料进行均一性检验,我国年平均风速资料的不连续点主要集中在1～2个,已检验的701个台站中有61.3%的台站年平均风速序列是均一的,表明我国大部分台站风速资料均一性情况良好。仪器变化和台站迁移是引起年平均风速序列非均一性的主要原因,而仪器变化中的仪器换型是造成年平均风速序列非均一性的最重要原因。     

山东省45年年平均气温均一性检验

采用回归检验法对山东省120个台站1961~2005年的年平均气温序列进行了显著非均一性检验。通过与台站历史沿革信息的比较分析,表明在显著性水平α=0.01时回归检验法能有效地检验出年平均气温序列的非均一性。分析结果显示,气象台站的位置、环境、观测方法和时制、仪器类型和高度等变动,对年平均气温序列的非均一性均有不同程度的影响,其中台站迁移对温度序列的均一性影响最大。     

Trend analysis of temperature parameters in Iran

In this study, long-term annual and monthly trends in mean maximum, mean minimum and mean temperature are investigated at 35 synoptic stations in Iran. The statistical significance of trends is assessed by the Mann–Kendall test. Most stations, especially those in western and eastern parts of country, had significant positive trends in monthly temperature time series in summer season. However, the maximum number of stations with the positive trend were observed in April (30 stations), and then in August (29 stations) while the negative trends were seen in February (16 stations) and March (15 stations). On annual scale, most stations in western and southern parts of Iran had significant positive trend. Overall, about 71%, 66% and about 40% of stations had statistically significant trends in mean annual temperature, mean annual minimum temperature and in mean annual maximum temperature, respectively. These results, however, indicate that the climate in Iran is growing warmer, especially in summer.     

Recent trends in regional air temperature and precipitation and links to global climate change in the Maharlo watershed,Southwestern Iran

Trends in air temperature and precipitation data are investigated for linkages to global warming and climate change. After checking for serial correlation with trend-free pre-whitening procedure, the Mann–Kendall test is used to detect monotonic trends and the Mann–Whitney test is used for trend step change. The case study is Maharlo watershed, Southwestern Iran, representing a semi-arid environment. Data are for the 1951–2011 period, from four temperature sites and seven precipitation sites. A homogeneity test investigates regional similarity of the time series data. The results include mean annual, mean annual maximum and minimum and seasonal analysis of air temperature and precipitation data. Mean annual temperature results indicate an increasing trend, while a non-significant trend in precipitation is observed in all the stations. Furthermore, significant phase change was detected in mean annual air temperature trend of Shiraz station in 1977, indicating decreasing trend during 1951–1976 and increasing trend during 1977–2011. The annual precipitation analysis for Shiraz shows a non-significant decrease during 1951–1976 and 1977–2011. The result of homogeneity test reveals that the studied stations form one homogeneous region. While air temperature trends appear as regional linkage to global warming/global climate change, more definite outcome requires analysis of longer time series data on precipitation and air temperature.     

Climate change detection and annual extreme temperature analysis of the Irtysh Basin

As the largest tributary of the Ob River, the Irtysh River is an international river partially joining the territories of China, Kazakhstan, and Russia. Four meteorological stations in the Irtysh Basin were selected and the long-term observed daily temperature data were collected. The extreme temperature change was analyzed considering climate change. Detected by the heuristic segmentation by histogram comparison approach, climate was changed during the first half of the 1970s in terms of the increased mean value and decreased standard deviation of the daily temperature series. The noticeable change of the monthly mean temperature was the warmer winter. After climate change, the annual maximum temperature was little changed and its series was not segmented. However, the annual minimum temperature was significantly changed in terms of the increased mean value by more than 2°C, so its series was segmented to the pre- and post-change point subseries. The generalized extreme value distribution was fitted to the annual extreme temperature and the parameters were estimated by the maximum likelihood method. The return levels for 10/50/100-year return periods estimated by the profile likelihood method were obtained for the annual extreme temperature. The probability of occurrence of the cold extremes was decreased after 1970s.     

Trend analysis of long-term temperature time series in the Greater Toronto Area (GTA)

As the majority of the world’s population is living in urban environments, there is growing interest in studying local urban climates. In this paper, for the first time, the long-term trends (31–162 years) of temperature change have been analyzed for the Greater Toronto Area (GTA). Annual and seasonal time series for a number of urban, suburban, and rural weather stations are considered. Non-parametric statistical techniques such as Mann–Kendall test and Theil-Sen slope estimation are used primarily for the assessing of the significance and detection of trends, and the sequential Mann test is used to detect any abrupt climate change. Statistically significant trends for annual mean and minimum temperatures are detected for almost all stations in the GTA. Winter is found to be the most coherent season contributing substantially to the increase in annual minimum temperature. The analyses of the abrupt changes in temperature suggest that the beginning of the increasing trend in Toronto started after the 1920s and then continued to increase to the 1960s. For all stations, there is a significant increase of annual and seasonal (particularly winter) temperatures after the 1980s. In terms of the linkage between urbanization and spatiotemporal thermal patterns, significant linear trends in annual mean and minimum temperature are detected for the period of 1878–1978 for the urban station, Toronto, while for the rural counterparts, the trends are not significant. Also, for all stations in the GTA that are situated in all directions except south of Toronto, substantial temperature change is detected for the periods of 1970–2000 and 1989–2000. It is concluded that the urbanization in the GTA has significantly contributed to the increase of the annual mean temperatures during the past three decades. In addition to urbanization, the influence of local climate, topography, and larger scale warming are incorporated in the analysis of the trends.     

塔城地区1960-2018年季节性冻土的变化特征及影响因子分析

利用1960-2018年塔城地区9个气象观测站冻土深度及同期气温观测资料,采用数理统计方法分析了其分布状况、变化特征及其与气象因子的关系,结果表明：近59a塔城地区最大冻土深度均在120cm以上,大值区主要分布在中部、南部及托里,冻结初日最早出现于9月上旬,最晚结束于5月中旬;年最大冻土深度除额敏以4.00cm/10a的速率显著增多外,其余各站均表现为减少趋势,其中克拉玛依减幅最大;月际变化中1月、2月、5月、9月、10月仅个别站表现为增多趋势,其余站表现为减少趋势,而3月、4月、11月、12月9站均表现为一致的减少趋势;塔城地区最大冻土深度年际变异系数均表现为中等变异性,表明其对气候变化的响应较敏感;平均冻土深度年代际变化呈现“浅-深-浅-浅-浅-浅”的变化趋势,从1980年代开始平均冻土深度逐渐变浅;影响最大冻土深度变化的因子主要有年（月）平均气温、平均最低气温及气温日较差。     

城市化对华北地区最高, 最低气温和日较差变化趋势的影响

利用华北地区255个一般站和国家基本、 基准站1961\_2000年的实测资料, 经过质量检验和均一性订正后, 将所有台站根据人口和台站地理位置分为5个类别, 分析了这5个类别台站和国家基本、 基准站地面平均气温、 最高、 最低气温的年和季节变化趋势以及城市化影响。结果表明： 华北全部台站的年平均气温、 最高、 最低气温均呈增加趋势, 且以最低气温上升最为明显, 导致年平均日较差呈现明显下降。就城市化影响而言, 平均气温、 最低气温变化趋势中城市热岛效应加强因素的影响明显, 但城市化对最高气温趋势影响微弱, 个别台站和季节甚至可能造成降温。在国家基本、 基准站观测的年平均气温和年平均最低气温上升趋势中, 城市化造成的增温分别为0.11℃·(10a)-1和0.20℃·(10a)-1, 对全部增温的贡献率分别达39.3%和52.6%。各类台站的四季平均气温和最低气温序列中城市化影响均造成增温。城市化增温以冬季为最大, 夏季最小。城市化还导致乡村站以外的各类台站日较差减小, 近40年华北地区国家基本、 基准站年平均和秋、 冬季平均气温日较差明显下降均由城市化影响造成的。     

扎龙湿地周边区域极端气温不对称变化分析

为了了解扎龙湿地对小区域气候的调节作用及其变化趋势。利用MANN—KENDALL检验等4种气候变化趋势分析方法，分析了扎龙湿地周边区域的富裕、林甸、社蒙、泰来气象站1957--2002年最高、最低气温的变化特征。结果表明，最高、最低气温存在明显的不对称变化，在部分时段还存在着反向变化趋势；最低气温的变化还明显地存在着气候突变的特征；这种极端气温的不对称变化，使该区域气温的日较差有明显的递减趋势。R／S分析（改变尺度范围分析法）表明最高、最低气温的变化存在明显的Hurst现象，该区域气候变暖有趋于减缓的趋势。     

基于均一化观测序列的京津冀地区气候变化格局分析

利用1960~2015年京津冀地区88个国家级气象站观测资料（包括日平均气温、日最高气温、日最低气温、日降水、日平均风速等）,使用MASH（Multiple Analysis of Series for Homogenization）方法剔除台站迁址、仪器变更等因素所致偏差后,生成均一化的观测资料集。基于新资料集计算了各站气温、降水和凤速序列的线性趋势和Morlet小波等统计特征,分析了京津冀地区气候变化格局。结果表明:MASH方法能较准确地检测并校订观测序列中迁站、仪器变更等因素所导致的非均一性;1960~2015年期间京津冀年平均气温显著上升,上升幅度为0.261℃/10 a;降水减少,平均减少11.27 mm/10 a;风速显著减小,平均减小0.193 m s-1（10 a）-1。     

Mathematical modelling of the annual temperature wave based on monthly mean temperatures,and comparisons between local climate trends at seven Norwegian stations

Summary Based on observed monthly mean temperatures, it is possible to construct a simple mathematical model of the annual variation of daily mean temperature, the annual temperature wave. For periods of 15 years, the model gives a good correlation with the observed monthly values. The model may be used as a tool for the generation of daily mean temperatures for the corresponding period. It is continuous, differentiable and strictly monotonous between the unique maximum and the minimum of the curve. Consequently, climate quantities of interest for each period can be calculated by the means of simple mathematical analyses. The model was tested by reproducing values for quantities such as annual mean temperature, winter mean temperature, summer mean temperature and temperature sums. Model calculated values, fit values calculated directly from observed data well. The model was also tested by comparing results from two different but neighbouring stations. There was a good correlation between the results from the two stations. Long homogenised time series with 130 years of monthly mean temperature from seven Norwegian stations were analysed by means of the model. It was found that the Frost Free Season Length and the Growth Season Length had increased for all stations by 10–20 days/100 years in the period 1871–1990. The Summer Half-year Length, even if it was defined relative to the annual mean temperature, also increased for all stations by 4–9 days/100 years. The Hot Season Length showed positive trends as well, and for the five stations in Southern Norway, the trends were as high as 18–29 days/100 years. The Heat Sum had increased by 6–11% for southern stations and 20–22% for the northern stations. The results indicate that the level as well as the shape of the annual temperature wave changed in the period from 1871 to 1990. Some of the results for the period 1990–1999 diverge substantially from the trends, possibly indicating significant changes in the shape of the annual temperature wave in this last period.     

甘肃近40年来气温变化的研究

利用 196 0～ 1999年甘肃省 15站的月平均气温 ,平均最高、最低气温 ,极端最高、最低气温等资料 ,对近 4 0年来甘肃省气候变化特征作了分析研究。结果显示 :1985年以前甘肃年平均气温变化是平稳的 ,以后急剧增温 ,且增温并不是主要由冬季增温造成的。1985年以前是平均最低气温升高 ,以后平均最高气温也在升高 ,所以 1985年以后的气温变暖不完全是以最低气温变暖为主形成的