Physiographic factors of seasonal distribution of linear trends in air temperature on the Azov-Black sea coast

The seasonal distribution of linear trends in air temperature on the coast of the Black and Azov seas in 1936-2010 is analyzed using the quantile regression method. Monthly mean and median values of temperature as well as 10% and 90% quantiles of average daily values of temperature are considered to describe changes in extreme positive and negative temperature anomalies. It is demonstrated that besides tendencies that are common for all meteorological stations, local features and physiographic location of the stations are of great importance for the distribution of temperature trends.     

Using the quantile regression method to analyze changes in climate characteristics

Possibilities to use the non-parametric regression analysis method, named the quantile regression, for the estimation of changes in climate characteristics are considered. When analyzing the trends of climatic series, the quantile regression method enables to get the information on trends along the whole range of quantile values from 0 to 1 of dependent variable distributions, that is more informative than the use of traditional regression technique, based on the least-squares method (LSM) and enabling to obtain trend estimations for average values of the dependent variable only. Trend estimation errors for various methods are analyzed. The computation of quantile regression parameters for real climatic series is executed. Series of meteorological variables of the diurnal resolution, which characterize the surface climate (minimal, average, and maximal diurnal temperatures) and free atmosphere climate (temperature of isobaric surfaces up to 30 hPa inclusive) are considered. Seasonal peculiarities in trend manifestation at different parts of quantile range of these meteorological values are discussed. Concerning the problem of the analysis of climate trends, the quantile regression method seems to be perspective from the point of view of more detailed understanding of processes in the climate system, such as the surface and tropospheric warming, stratospheric cooling, long-period changes in characteristics of climate variability and extremity.     

Trends of surface ozone concentrations in germany and their connections with changes in meteorological variables

Changes in daily mean and daily maximum surface ozone concentrations, temperature, and relative humidity are evaluated based on the data of long-term observations (from 11 to 16 years) carried out at eight German stations. For all stations the trends of daily mean surface ozone concentration are statistically significant and positive. The trend values are different and generally range from 0 to 10% per 10 years. The trends of the maximum daily concentration are, on average, approximately 1.5 times less. Noticeable part of trends of the surface ozone concentration is connected with the trends of meteorological variables: temperature, relative humidity, and air mass transport direction. After the account of the influence of the trends of meteorological variables, the trends of the surface ozone concentration at most stations substantially decrease. The highest trend values of daily mean and daily maximum surface ozone concentrations are observed in a cold season; in a warm season, the trend values are much lower, at some stations they are statistically insignificant. A conclusion is made that for a correct revealing of reasons of long-term changes in the surface ozone concentration one should take into account changes in meteorological factors influencing its formation.     

Multiscale evolution of surface air temperature in the arid region of Northwest China and its linkages to ocean oscillations

Reference crop evapotranspiration (ETo) is one of the most important links in hydrologic circulation and greatly affects regional agricultural production and water resource management. Its variation has drawn more and more attention in the context of global warming. We used the Penman-Monteith method of the Food and Agriculture Organization, based on meteorological factors such as air temperature, sunshine duration, wind speed, and relative humidity to calculate the ETo over 46 meteorological stations located in the Yangtze River Delta, eastern China, from 1957 to 2014. The spatial distributions and temporal trends in ETo were analyzed based on the modified Mann-Kendall trend test and linear regression method, while ArcGIS software was employed to produce the distribution maps. The multiple stepwise regression method was applied in the analysis of the meteorological variable time series to identify the causes of any observed trends in ETo. The results indicated that annual ETo showed an obvious spatial pattern of higher values in the north than in the south. Annual increasing trends were found at 34 meteorological stations (73.91 % of the total), which were mainly located in the southeast. Among them, 12 (26.09 % of the total) stations showed significant trends. We saw a dominance of increasing trends in the monthly ETo except for January, February, and August. The high value zone of monthly ETo appeared in the northwest from February to June, mid-south area from July to August, and southeast coastal area from September to January. The research period was divided into two stages—stage I (1957–1989) and stage II (1990–2014)—to investigate the long-term temporal ETo variation. In stage I, almost 85 % of the total stations experienced decreasing trends, while more than half of the meteorological stations showed significant increasing trends in annual ETo during stage II except in February and September. Relative humidity, wind speed, and sunshine duration were identified as the most dominant meteorological variables influencing annual ETo changes. The results are expected to assist water resource managers and policy makers in making better planning decisions in the research region.     

Downscaling of the global seasonal forecasts of hydrometcenter of Russia for North Eurasia

Proposed is a method of downscaling of the global ensemble seasonal forecasts of air temperature computed using the SLAV model of the Hydrometcenter of Russia. The method is based on the regression and suggests a probabilistic interpretation of forecasts based on the assessment of uncertainty associated with the regression and model forecast ensemble spread. The verification of the method for 70 weather stations of North Eurasia using the rank probability skill score RPSS showed a significant advantage of downscaled forecasts over the forecasts interpolated from the model grid points. It is concluded that the use of the downscaling method is reasonable for the long-range forecasting of the station air temperature for North Eurasia.     

西南地区城市热岛强度变化对地面气温序列影响

利用1961—2004年我国西南地区322个站的气温观测资料, 分析了乡村站、小城市站、大中城市站和国家基准/基本站气温变化趋势特点, 着重研究了城市化对城镇站和国家站地面气温记录的影响程度和相对贡献比例。结果显示:区域平均的各类台站年平均气温呈现不同程度的上升趋势, 城市站、国家站的增温速率均高于乡村站。大中城市站和国家站的年平均热岛增温率分别为0.086 ℃/ 10a和0.052 ℃/10a, 其增温贡献率分别达57.6%和45.3%。与大多数地区不同, 西南地区的增温速率明显偏小。因此, 尽管平均热岛强度变化比许多地区弱, 但其相对贡献明显, 表明城市化对该区域气温趋势的绝对影响较弱, 但相对影响较强。另外, 城市热岛增温有明显的季节变化, 表现为秋季最强, 春季或冬季次之, 夏季最弱。热岛增温贡献率则为春季最大 (100%), 夏季次之 (73%以上), 秋季和冬季相对较小。这主要是因为春、夏两季背景气候变凉或趋势微弱, 热岛增温在实际增温中占有更高的比例。     

On the relation between the temperature anomaly duration and the value of its extrema

A statistical structure of the time series of air temperature with a daily resolution is studied from the data of nine meteorological stations of Russia for the period from 1961 to 2006. A quantitative relation is obtained between the temperature anomaly duration and its extrema for different seasons of the year. The analysis also enabled to reveal the increase in the duration of long-term air temperature anomalies from the west to the east.     

Climate change in the Tahoe basin: regional trends, impacts and drivers

The purpose of this study was to quantify the decadal-scale time trends in air temperature, precipitation phase and intensity, spring snowmelt timing, and lake temperature in the Tahoe basin, and to relate the trends to large-scale regional climatic trends in the western USA. Temperature data for six long-term weather stations in the Tahoe region were analyzed for trends in annual and monthly means of maximum and minimum daily temperature. Precipitation data at Tahoe City were analyzed for trends in phase (rain versus snow), decadal standard deviation, and intensity of rainfall. Daily streamflow data for nine gaging stations in and around the Tahoe basin were examined for trends in snowmelt timing, by two methods, and an existing record for the temperature of Lake Tahoe was updated. The results for the Tahoe basin, which contrast somewhat with the surrounding region, indicate strong upward trends in air temperature, a shift from snow to rain, a shift in snowmelt timing to earlier dates, increased rainfall intensity, increased interannual variability, and continued increase in the temperature of Lake Tahoe. Two hypotheses are suggested that may explain why the basin could be warming faster than surrounding regions. Continued warming in the Tahoe basin has important implications for efforts to manage biodiversity and maintain clarity of the lake.     

黄河流域平均气温变化趋势分析

采用线性倾向估计和非参数统计检验（Mann-Kendall）方法计算黄河流域78个气象站点12个月及年平均气温多年来的长期变化趋势,并在计算结果基本一致的前提下,重点对Mann-Kendall法的计算结果进行了分析.结果表明,黄河流域平均气温总体呈现上升趋势,这种趋势主要归因于1、2、12月气温的升高;气温上升趋势以12月份表现最明显,8月份表现最平缓;全流域年平均气温只有4个站点表现出下降趋势,不同月份变化趋势的地区分布亦有差异,并根据这些差异将流域进行了分区.     

How much the warming in Russia agrees with the output of coupled atmosphere-ocean general circulation models?

Climate variability parameters and air temperature trends in Russia, derived from observational data, are compared with those derived from climate modeling in the second half of the 20th-early 21st century, using the atmosphere-ocean general circulation model ensemble. The computation results from these models were used in the preparation of the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. It is demonstrated that the ensemble averaging allowed us to efficiently filter the internal climate variability and get relatively stable estimates of trends. As a whole, for Russia, these estimates are in good agreement with the observational data, both for a year on average, and in individual seasons. The comparison of model and observed air temperature trends on a regional scale turns out to be irrelevant in a number of cases because of a high inadequacy of trend estimates derived from the observational data.     

Peculiarities of surface air temperature variations over the Far East regions in 1976–2005

Peculiarities are investigated of the air temperature variation tendencies at some stations of the Far East in 1976–2005. The estimate of linear trend equation coefficients is computed according to the air temperature observation data using the least squares method. It is demonstrated that the air temperature trend in northern regions possesses a small probability at small values of residual variability. In the southern regions, the trend significance increases for almost all seasons at small values of residual variability. At midlatitude stations, the trend significance in January and February decreases considerably due to the large values of residual variability.     

以高山站为背景研究城市化对气温变化趋势的影响

本文基于1957~2005年的逐日气象资料,对比分析了中国东部7组高山气象站和山下附近的城市气象站年 与四季气温变化趋势.在此基础上,利用高山站作为气候变化背景场来分析城市化对平均气温、最高气温、最低气温变化趋势影响的性质和程度,及其对气温变化非对称性的影响.结果表明:平均气温和最低气温变化趋势城市站多比高山站大,而最高气温变化趋势高山站多比城市站大;城市站最低气温变化趋势均大于最高气温变化趋势,具有明显的非对称性现象,而高山站这种表现十分微弱.城市站气温变化受到明显的城市化影响,对于平均气温和最低气温以正影响为主,而对于最高气温为负影响为主,说明城市化对气温变化的影响也存在非对称性.城市化影响的非对称性是气温变化非对称性形成的主要因素.     

Estimation of the monthly and annual mean maximum and mean minimum air temperature values in Greece

In this study, regression equations to estimate the monthly and annual values of the mean maximum and mean minimum air temperatures in Greece are derived. For this purpose, data from 87 meteorological stations distributed all over Greece are used. Geographical parameters, i.e., altitude, latitude, longitude, minimum distance from the sea and an index of terrain morphology, are used as independent variables. These equations explain 79?C97% of the variance of the temperature values and have standard error of estimate between 0.59 and 1.20°C. Data from 37 other meteorological stations are used to validate the accuracy of the equations. Topographic or climatic factors, which could not be introduced into the equations, are responsible for most temperature residuals >0.5°C or <?0.5°C. Moreover, some particular emphasis has been given to the values of the regression coefficient for the altitude, since it is the estimator for the mean lapse rate of air temperature.     

Urbanization Effect on the Observed Change in Mean Monthly Temperatures between 1951-1980 and 1971-2000 in Korea

Gridded temperature data are necessary to run ecological models at regional scales for climate impact studies and have been generated by spatially interpolating measured values at synoptic stations. Because there are few synoptic stations with long-term records in rural areas in Korea, data from urban stations have been used for this purpose. Due to the overlapping of the rapid urbanization-industrialization period with the global warming era in Korea, climate data from these urbanized areas might be contaminated with urban heat island effect. This study was conducted to differentiate urbanization and regional climate change effects on apparent temperature change. Monthly averages of daily minimum, maximum, and mean temperature at 14 synoptic stations were prepared for 1951-1980 (past normal) and 1971-2000 (current normal) periods, respectively.Differences in two temperature normals were regressed to the logarithm of the population increase at 14 corresponding cities from 1966 to 1985. The regression equations were used to determine potential effects of urbanization and to extract the net contribution of regional climate change to the apparent temperature change. According to the model calculation, urbanization effect was common in all months except April. Up to 0.5° warming of nighttime temperature was induced by urbanization in the current normal period compared with the past normal period. There was little effect of regional climate change on local warming in the warm season (May through November). The cool season was warmed mainly by regionally increased daytime temperature. The results could be used to remove urbanization effects embedded in raw data, helping restore unbiased rural temperature trends in South Korea.     

Studying the showers and thunderstorms on the territory of Russia using the numerical model of convective cloud and the reanalysis data

The computation of thunderstorm and shower activity on the territory of Russia during the warm period (June–August) of 1981–2000 for four observation times (00:00, 06:00, 12:00, and 18:00) is carried out using the local convective cloud model (CCM) and the ERA-40 reanalysis data on the vertical distribution of temperature and humidity. The spatial grid with the resolution of 2.5 × 2.5° is used for the computation. Collected and analyzed are the long-term (1936–1965) in situ data on the distribution of the number of days with the thunderstorm on the territory of Russia using the observational data from the ground-based meteorological stations (about 600 stations located in different regions). As a result, the distribution of the number of days with the thunderstorm and with the convective precipitation on the territory of Russia is plotted and analyzed. It agrees on the whole with the observed data. It is demonstrated that the number of days with the thunderstorm and with the convective precipitation correlate well with each other, that also corresponds to the observational data. It is shown that CCM is applicable to the simulation of cloud convection and associated phenomena.     

Trends and scales of observed soil moisture variations in China

A new soil moisture dataset from direct gravimetric measurements within the top 50-cm soil layers at 178 soil moisture stations in China covering the period 1981-1998 are used to study the long-term and seasonal trends of soil moisture variations, as well as estimate the temporal and spatial scales of soil moisture for different soil layers. Additional datasets of precipitation and temperature difference between land surface and air (TDSA) are analyzed to gain further insight into the changes of soil moisture. There are increasing trends for the top 10 cm, but decreasing trends for the top 50 cm of soil layers in most regions. Trends in precipitation appear to dominantly influence trends in soil moisture in both cases. Seasonal variation of soil moisture is mainly controlled by precipitation and evaporation, and in some regions can be affected by snow cover in winter. Timescales of soil moisture variation are roughly 1-3 months and increase with soil depth. Further influences of TDSA and precipitation on soil moisture in surface layers, rather than in deeper layers, cause this phenomenon. Seasonal variations of temporal scales for soil moisture are region-dependent and consistent in both layer depths. Spatial scales of soil moisture range from 200-600 km, with topography also having an affect on these. Spatial scales of soil moisture in plains are larger than in mountainous areas. In the former, the spatial scale of soil moisture follows the spatial patterns of precipitation and evaporation, whereas in the latter, the spatial scale is controlled by topography.     

Variation in the number of days with heavy precipitation on the territory of Russia for the period of 1936–2000

Time variations in the number of days with heavy precipitation based on data of 93 stations on the territory of Russia are analyzed. Time series of precipitation, corrected by the elimination of main systematic errors of their measurement at the level of their diurnal sums, are used, when computing. The diurnal precipitation sum, exceeding the average long-term diurnal precipitation maximum by three times, was taken as the threshold quantitative criterion, defining “the day with heavy precipitation” concept. This value varies within 10–15 mm/day on the territory of Russia. Extremums fluctuate from 5 to 40 mm/day. Absolute values of linear trends of the annual number of days with heavy precipitation are comparatively small, they fluctuate within ±4 days on the whole territory of Russia. In relative terms, these variations are rather significant, reaching ±40% and more of the corresponding average value for 65 years. The comparison of the spatial distribution of characteristics of linear trends of the annual number of days with heavy precipitation and annual precipitation sum indicates their close conformity.     

近40年黄河源区气候要素分布特征及变化趋势分析

用Mann-Kendall统计检验方法对黄河源区13个气象站点1959—1997年日照、气温、降水、蒸发的分布特征和变化趋势进行了分析,结果表明:近40年黄河源区年平均日照时数表现为微弱的下降趋势,空间分布呈明显的从北部向南部减少的态势,变化趋势从中部向西部、东部、北部逐渐减少;年平均气温呈明显的上升趋势,空间分布规律从西向东、从南向北逐渐增加,变化趋势为中部、南部地区上升趋势最小,北部、东部、西部上升幅度较大;多年平均降水呈较弱的下降趋势,空间分布规律从东南向西北逐渐减少,变化趋势表现为大部分地区降水量呈下降趋势;年平均蒸发量的下降趋势幅度较大,空间分布规律从北部向南部逐渐减少,变化趋势表现为大部分地区呈减少趋势,以北部地区最为明显。另外,本文也应用线性倾向估计方法对黄河源区各气候要素进行了分析,这两种方法得到的结果基本一致。     

Resampling of network-induced variability in estimates of terrestrial air temperature change

Uneven and changing spatial distributions of air temperature stations can produce unrepresentative samples of the space-time variability of near-surface air temperature. Over the last century, station networks have varied from less than 300 stations that are largely limited to the Northern Hemisphere to nearly 1700 stations that are fairly well distributed over the terrestrial surface. As a result, estimates of air temperature change derived from historical observation networks often contain network-induced variability.Spatial resampling methods are used to estimate network-induced variability in terrestrially averaged air temperature anomalies and trends. Random resampling from the station networks allows pseudo confidence intervals and other statistics of variability to be estimated. Network-induced variability appears to be substantial during the late 1800s, especially in the Southern Hemisphere. Most networks from the 1900s and the Northern Hemisphere, however, appear to produce reliable estimates of spatially averaged air temperature anomalies and trends.A non-random, but historically appropriate, resampling method - sampling a given year's air temperature anomaly field using another year's station distribution - also is used. Using 1987 - one of the warmest years on record - as an example, station distributions from 1881-1988 are used to sample the 1987 air temperature anomaly field. This sampling procedure produces spatially averaged air temperature anomalies for 1987 that vary by over 0.3°C. A combinatorial process of resampling a given year's anomaly field is repeated for every year and every station network to produce terrestrial average air temperature anomaly estimates that vary by more than 0.3°C solely due to network changes.     

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。