Evaluation of regional climate model simulations versus gridded observed and regional reanalysis products using a combined weighting scheme

This study presents a combined weighting scheme which contains five attributes that reflect accuracy of climate data, i.e. short-term (daily), mid-term (annual), and long-term (decadal) timescales, as well as spatial pattern, and extreme values, as simulated from Regional Climate Models (RCMs) with respect to observed and regional reanalysis products. Southern areas of Quebec and Ontario provinces in Canada are used for the study area. Three series of simulation from two different versions of the Canadian RCM (CRCM4.1.1, and CRCM4.2.3) are employed over 23?years from 1979 to 2001, driven by both NCEP and ERA40 global reanalysis products. One series of regional reanalysis dataset (i.e. NARR) over North America is also used as reference for comparison and validation purpose, as well as gridded historical observed daily data of precipitation and temperatures, both series have been beforehand interpolated on the CRCM 45-km grid resolution. Monthly weighting factors are calculated and then combined into four seasons to reflect seasonal variability of climate data accuracy. In addition, this study generates weight averaged references (WARs) with different weighting factors and ensemble size as new reference climate data set. The simulation results indicate that the NARR is in general superior to the CRCM simulated precipitation values, but the CRCM4.1.1 provides the highest weighting factors during the winter season. For minimum and maximum temperature, both the CRCM4.1.1 and the NARR products provide the highest weighting factors, respectively. The NARR provides more accurate short- and mid-term climate data, but the two versions of the CRCM provide more precise long-term data, spatial pattern and extreme events. Or study confirms also that the global reanalysis data (i.e. NCEP vs. ERA40) used as boundary conditions in the CRCM runs has non-negligible effects on the accuracy of CRCM simulated precipitation and temperature values. In addition, this study demonstrates that the proposed weighting factors reflect well all five attributes and the performances of weighted averaged references are better than that of the best single model. This study also found that the improvement of WARs’ performance is due to the reliability (accuracy) of RCMs rather than the ensemble size.     

Variability and trends in daily minimum and maximum temperatures and in the diurnal temperature range in Lithuania,Latvia and Estonia in 1951–2010

Spatial distribution and trends in mean and absolute maximum and minimum temperatures and in the diurnal temperature range were analysed at 47 stations in the eastern Baltic region (Lithuania, Latvia and Estonia) during 1951–2010. Dependence of the studied variables on geographical factors (latitude, the Baltic Sea, land elevation) is discussed. Statistically significant increasing trends in maximum and minimum temperatures were detected for March, April, July, August and annual values. At the majority of stations, the increase was detected also in February and May in case of maximum temperature and in January and May in case of minimum temperature. Warming was slightly higher in the northern part of the study area, i.e. in Estonia. Trends in the diurnal temperature range differ seasonally. The highest increasing trend revealed in April and, at some stations, also in May, July and August. Negative and mostly insignificant changes have occurred in January, February, March and June. The annual temperature range has not changed.     

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.     

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.     

A diagnosis of twentieth century temperature records at West Lafayette,Indiana

A diagnostic study of 80 yrs(1901–80) of surface temperatures collected at West Lafayette, Indiana, has been found to be in tune with the global trend and that for the eastern two-thirds of the United States, namely, cold at the turn of the century, warming up to about 1940, and then cooling to present. The study was divided into two cold periods (1901–18, 1947–80) and a warm period (1919–46), based on the distribution of annual mean temperature. Decadal mean annual temperatures ranged from 10 °C in period I to 12.2 °C in period II, to 9.4 °C during the present cold period. Themean annual temperature for the 80 yr ranged from the coldest of 8.7 °C in 1979 to the warmest of 13.6 °C in 1939. Thedaily mean temperature for the entire 80-yr ranged from -4.7 °C on 31 January to 25.1 °C on 27 July. Thecoldest daily mean was -26.7 °C on 17 January, 1977, and thewarmest daily mean was 35 °C on 14 July, 1936. The range of values for thedaily mean maximum temperatures was -.2 °C on 31 January to 31.4 °C on 27 July. Corresponding values for thedaily mean minimum are -9.2 °C on 31 January and 18.7 °C on 27 July. The all-time extreme temperatures are -30.6 °C on 26 February, 1963 and 43.9 °C on 14 July, 1936. Climatic variability has been considered by computing the standard deviations of a) the daily mean maximum and minimum temperature per year, and b) the daily mean maximum and minimum temperatures for each day of the year for the 80-yr period. These results have shown that there is more variability in the daily mean maximum per year than in the daily mean minimum, for each year of the 80-yr period. Also the variability for both extremes has been greater in each of the two cold periods than in the warm period. Particularly noticeable has been theincrease in the variability of the daily mean minima per year during the current cooling trend. Further, it has been determined that the variability in the daily mean maxima and minima for each day of the year (based on the entire 80 yrs is a) two times greater in the winter than in the summer for both extremes, and b) about the same for each in the summer, greater for daily maximum in the spring and fall, but greater for the daily minimum during the winter. The latter result is undoubtedly related to the effect of snow cover on daily minimum temperatures. An examination of daily record maximum and minimum temperatures has been made to help establish climatic trends this century. For the warm period, 175 record maxima and 68 record minima were set, compared to 213 record minima and 105 record maxima during the recent cold period. For West Lafayette, the present climatic trend is definitely one of extreme record-breaking cold. Evidence has also been presented to show the substantial increases in snowfall amounts in the lee regions of the Great Lakes during the present cold period, due to the lake-induced snow squalls associated with cold air mass intrusions. The possible impact of the cooling trend on agricultural activities has also been noted, due to a reduced growing season.     

1955-2005年中国极端气温的变化

利用1955-2005年中国234站逐日最高、最低气温资料,通过计算趋势系数等,研究了中国年、季极端气温变化趋势的时空特征。结果表明：空间分布上,我国年和四季的极端低温均表现出稳定的增温趋势;年、春季和夏季极端高温在黄河下游地区出现了较明显的降温趋势,而在华南地区增温趋势较显著;时间演变上,无论年还是四季,极端低温的增温幅度明显大于极端高温的增幅;极端气温在四季均有增温趋势,尤其以冬季的升温最明显;年极端高温和低温的年代际变化基本一致。     

Analysis of recent trends in mean maximum and minimum temperatures in a region of the NW of Spain (Castilla y León)

Summary The present paper is an analysis of mean maximum and minimum temperatures carried out on monthly, seasonal and annual time-scales examining the data collected at 171 meteorological stations over a region in the North West of Spain (Castilla y León) for the period 1961–1997. Various statistical tools were used to detect and describe significant trends in these data. The magnitude of the trends was derived from the slopes of the regression lines using the least squares method, and the statistical significance was determined by means of the non-parametric Mann-Kendall test. The pattern obtained is quite similar for mean maximum and minimum temperatures with increases in all months of the year, and in the annual series. The seasonal series corresponding to winter and summer also followed this same pattern. Spring and autumn were found to be more irregular. Because maximum temperature increased at a higher rate than minimum temperature in this period, an increase in the annual diurnal temperature range (DTR) was observed. The correlation between the North Atlantic Oscillation (NAO) and the regional maximum and minimum temperatures and DTR series for the period 1961–1997 have also be studied in this paper.     

1951～2002年中国平均最高、最低气温及日较差变化

利用1951～2002年全国733个台站的月平均最高、最低气温资料,对我国年、季平均最高、最低气温变化趋势的空间分布状况和时间变化特征进行了分析.结果表明:近52年来,我国平均最高气温的变化特征呈现北方增暖明显、南方变化不明显或呈弱降温趋势;年平均最低气温全国各地基本一致,呈明显的变暖趋势;无论是年还是季,平均最低气温的增暖幅度明显大于平均最高气温的增幅;我国年平均日较差多呈下降趋势,并在我国北方地区尤为明显,各季平均日较差亦均呈下降趋势,并以冬季的下降幅度为最大;年平均最高气温和最低气温的变化在年代际变化上基本呈现较为一致的步伐,即52年来主要的变暖均是从20世纪80年代中期开始,均在90年代后期达到了近52年来的历史新高,近年来又略有回落.     

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.     

Observed temperature evolution in the City of Sfax (Middle Eastern Tunisia) for the period 1950–2007

This paper studies temperature evolution in the city of Sfax (Middle Eastern Tunisia, with more than 600 000 people) from 1950 to 2007. Daily maximum and minimum temperatures recorded at Sfax observatory from 1950 to 2007 are analysed by studying their homogeneity, possible trends and their statistical significance. Linear regression, Student and Mann–Kendall trend test were applied to annual mean minimum and maximum temperature data to determine the existence and significance of trends. Using a number of statistical tests, it is found that the data measured at the surface station represent a non homogenous time-series. Furthermore, mean annual and monthly temperatures are evaluated and a statistically significant trend starting from year 1950 was found. Important increase of the surface temperature in the City of Sfax was found after 1984. The increase in the surface temperature in the city of Sfax is further associated with global, regional (e.g. Mediterranean area) and meso-scale temperature increase. In addition, the spatial pattern of surface temperature in the city of Sfax from 1982 to 2007 shows that the overall land surface temperature increased with the expansion of Urban Heat Island (UHI) from urban areas to suburban districts.     

基于卫星遥感揭示长三角台站周边城市土地利用扩张及其对气温记录的影响

台站温度记录中的城市化信号对于气候变化研究影响重大并仍存在很大争议,尤其是在经历快速城市化的区域。本研究利用遥感影像分类的方法,提取了1980~2009年期间长江三角洲城市群93个气象台站周边10 km×10 km范围的城市土地利用信息,并按照城市土地利用扩张速率对站点进行分类,研究了1980~2009年期间快速城市化站点、中速城市化站点和慢速城市化站点的年和季节平均温度、最低温度和最高温度变化特征,并分析了快速和中速城市化站点城市化影响和城市化影响贡献率。结果表明:全部93个气象站点周边自20世纪80年代起均经历了城市土地利用扩张过程,全部站点周边的平均城市土地利用扩张速率为1.00% a-1;近30年来,各类型站点年和各季节的平均温度、最低温度和最高温度均表现出增加趋势;城市化效应增强因素对快速城市化站点年平均温度贡献率为35.06%,对年平均最低温度的增温贡献率为34.67%,对年平均最高温度增温贡献率最小,仅为18.42%;城市化效应增强因素对中速城市化站点的影响程度小于快速城市化站点,对平均温度、最低温度和最高温度的贡献率分别为19.35%,22.22%和3.13%。在季节变异方面,长江三角洲区域各类型站点冬季的城市化影响贡献率在平均温度、最低温度和最高温度均表现为最低值。     

Variations and trends in annual and seasonal air temperatures in Greece determined from ground and satellite measurements

Summary The variations and trends in annual and seasonal air temperatures in Greece were examined on the basis of ground measurements for 25 stations during the period 1951–1993, and satellite measurements for the south eastern Mediterranean during the period 1979–1991. Data were smoothed using a 5-year running mean and were thereafter examined by regression analysis to define trends in the long duration time series. Data were also examined to detect abrupt changes and trends in the long duration annual, winter and summer series of mean maximum, mean minimum and mean temperatures. An overall cooling trend was detected for the majority of stations in winter over the entire period; the same cooling trend was also recognised for the annual and summer mean values, although a reverse warming trend was detected around the mid-70s at several stations. Satellite measurements indicate a slight warming trend, although this is not statistically significant. Considering the results of the regression analysis and the statistical tests applied to the 25 stations, it may be concluded that annual mean temperatures are dominated by an overall cooling trend, with the exception of stations in urban areas where urbanisation effects may have resulted in a warming trend. Summer temperatures, however, exhibit a warming trend roughly after 1975 at most stations.With 5 Figures     

Detection of urbanization signals in extreme winter minimum temperature changes over Northern China

Although previous studies show that urbanization contributes to less than 10 % of the long-term regional total warming trend of mean surface air temperature in northeast China (Li et al. 2010), the urban heat island (UHI) impact on extreme temperatures could be more significant. This paper examines the urbanization impact on extreme winter minimum temperatures from 33 stations in North China during the period of 1957–2010. We use the Generalized Extreme Value (GEV) distribution to analyze the distribution of extreme minimum temperatures and the long-term variations of the three distributional characteristics parameters. Results suggest that among the three distribution parameters, the position parameter is the most representative in terms of the long-term extreme minimum temperature change. A new classification method based on the intercommunity (factors analysis method) of the temperature change is developed to detect the urbanization effect on winter extreme minimum temperatures in different cities. During the period of rapid urbanization (after 1980), the magnitude of variations of the three distribution parameters for the urban station group is larger than that for the reference station group, indicating a higher chance of occurrence of warmer weather and a larger fluctuation of temperatures. Among different types of cities, the three parameters of extreme minimum temperature distribution of the urban station group are, without exception, higher than those of the reference station group. The urbanization of different types of cities all show a warming effect, with small-size cities have the most evident effects on extreme minimum temperatures.     

Spatial distribution of temperature trends and extremes over Maharashtra and Karnataka States of India

Earth surface temperatures are changing worldwide together with the changes in the extreme temperatures. The present study investigates trends and variations of monthly maximum and minimum temperatures and their effects on seasonal fluctuations at different climatological stations of Maharashtra and Karnataka states of India. Trend analysis was performed on annual and seasonal mean maximum temperature (TMAX) and mean minimum temperature (TMIN) for the period 1969 to 2006. During the last 38 years, an increase in annual TMAX and TMIN has occurred. At most of the locations, the increase in TMAX was faster than the TMIN, resulting in an increase in diurnal temperature range. At the same time, annual mean temperature (TM) showed a significant increase over the study area. Percentiles were used to identify extreme temperature indices. An increase in occurrence of warm extremes was observed at southern locations, and cold extremes increased over the central and northeastern part of the study area. Occurrences of cold wave conditions have decreased rapidly compared to heat wave conditions.     

The semiannual oscillation and Antarctic climate, part 5: impact on the annual temperature cycle as derived from NCEP/NCAR re-analysis

We use NCEP/NCAR reanalysis data to study the impact of the semiannual oscillation (SAO) on the annual cycle of Antarctic near-surface temperature. When the SAO is weak, the contracted phases (March/April and September/October) are warm and the expanded phases (December/January and June/July) cold. This pattern is explained in terms of the changing meridional fetch of the circumpolar pressure trough. Because of the wave number three character of the SAO, large regional deviations are found. For instance, enhanced north-westerly flow in the second expansion phase (June/July) of weak SAO years limits the growth of the sea ice in the Amundsen and Bellingshausen seas, leading to anomalously high temperatures in the Antarctic Peninsula region. The short (<50 year) temperature records at Antarctic stations still carry the fingerprint of decadal SAO variability. By matching the observed monthly temperature trends to the patterns derived from the gridded re-analysis, we propose a background Antarctic warming trend for the second expansion phase (June/July) of 4.62 ± 1.02 °C per century, four times the annual value. Received: 23 August 1999 / Accepted: 28 October 1999     

Present and future Laurentian Great Lakes hydroclimatic conditions as simulated by regional climate models with an emphasis on Lake Michigan-Huron

Regional climate modelling represents an appealing approach to projecting Great Lakes water supplies under a changing climate. In this study, we investigate the response of the Great Lakes Basin to increasing greenhouse gas and aerosols emissions using an ensemble of sixteen climate change simulations generated by three different Regional Climate Models (RCMs): CRCM4, HadRM3 and WRFG. Annual and monthly means of simulated hydro-meteorological variables that affect Great Lakes levels are first compared to observation-based estimates. The climate change signal is then assessed by computing differences between simulated future (2041–2070) and present (1971–1999) climates. Finally, an analysis of the annual minima and maxima of the Net Basin Supply (NBS), derived from the simulated NBS components, is conducted using Generalized Extreme Value distribution. Results reveal notable model differences in simulated water budget components throughout the year, especially for the lake evaporation component. These differences are reflected in the resulting NBS. Although uncertainties in observation-based estimates are quite large, our analysis indicates that all three RCMs tend to underestimate NBS in late summer and fall, which is related to biases in simulated runoff, lake evaporation, and over-lake precipitation. The climate change signal derived from the total ensemble mean indicates no change in future mean annual NBS. However, our analysis suggests an amplification of the NBS annual cycle and an intensification of the annual NBS minima in future climate. This emphasizes the need for an adaptive management of water to minimize potential negative implications associated with more severe and frequent NBS minima.     

Estimation of urban heat island intensity using biases in surface air temperature simulated by a nonhydrostatic regional climate model

This study demonstrates that urban heat island (UHI) intensity can be estimated by comparing observational data and the outputs of a well-developed high-resolution regional climate model. Such an estimate is possible because the observations include the effects of UHI, whereas the model used does not include urban effects. Therefore, the errors in the simulated surface air temperature, defined as the difference between simulated and observed temperatures (simulated minus observed), are negative in urban areas but 0 in rural areas. UHI intensity is estimated by calculating the difference in temperature error between urban and rural areas. Our results indicate that overall UHI intensity in Japan is 1.5 K and that the intensity is greater in nighttime than in daytime, consistent with the previous studies. This study also shows that root mean square error and the magnitude of systematic error for the annual mean temperature are small (within 1.0 K).     

Climatic timescale temperature and precipitation increases on long Island,New York

Abstract

Global warming due to increased greenhouse gases is believed to result in not only higher surface temperatures but also an acceleration of the hydrological cycle leading to increased precipitation. Although climate models consistently predict increases in global temperatures due to increasing greenhouse gases and the accompanying global warming, observations at the climatic timescales necessary to confirm the models are rare. Multidecadal studies at global and regional scales are necessary to determine whether the presently observed changes in temperature and precipitation are due to short‐term fluctuations or long‐term trends. In this study, we address this issue by examining changes in temperature and precipitation on Long Island, New York over a 74‐year time period (1931 to 2004) using a network of rain gauges and temperature measurements. The mean annual temperature on Long Island has increased at a rate of 0.05°C per decade, which is less than that of observed global values and is most likely due to the urban warming effects of New York City, not large‐scale climate change. The mean total annual precipitation has increased at a rate of 0.71 cm per decade during the study period, which is consistent with global observations. Intra‐annual temperature fluctuations are decreasing at a rate of 0.36% per decade, while precipitation variations are increasing at a rate of 0.91% per decade. Empirical orthogonal function analysis indicates that variations in temperature and precipitation on Long Island are dominated by island‐wide fluctuations that are directly related to the North Atlantic Oscillation, the Arctic Oscillation, and the El Niño Southern Oscillation.     

北京1960—2008年气候变暖及极端气温指数变化特征

应用均一化逐日气象观测资料,分析了北京地区1960—2008年气候变暖及主要极端气温指数的统计特征。结果表明：近49年来北京年平均气温增温速率约为0.39℃/10a,最高、最低气温变化具有明显的非对称性。霜冻日数和气温年较差呈现下降趋势,暖夜指数及热浪指数呈现上升趋势,除气温年较差外,其他极端气温指数的气候变率均在加大。北京年平均气温及极端气温指数主要存在21年、15～17年及准10年周期特征。年平均气温与极端气温指数之间存在较强相关性,气候变暖突变发生前后某些极端气温指数发生频率表现出明显差异。自1980年起,北京市区极端最高气温及其增温率明显高于近郊和远郊,高温日数市区多于近郊,近郊多于远郊;近、远郊极端最低气温温差高于城、近郊温差。     

Urban heat island effect on annual mean temperature during the last 50 years in China

Summary Based on Chinas fifth population survey (2000) data and homogenized annual mean surface air temperature data, the urban heat island (UHI) effect on the warming during the last 50 years in China was analyzed in this study. In most cities with population over 10⁴, where there are national reference stations and principal stations, most of the temperature series are inevitably affected by the UHI effect. To detect the UHI effect, the annual mean surface air temperature (SAT) time series were firstly classified into 5 subregions by using Rotated Principal Components Analysis (RPCA) according to its high and low frequency climatic change features. Then the average UHI effect on each subregions regional annual mean STA was studied. Results indicate that the UHI effect on the annual mean temperatures includes three aspects: increase of the average values, decrease of variances and change of the climatic trends. The effect on the climatic trends is different from region to region. In the Yangtze River Valley and South China, the UHI effect enhances the warming trends by about 0.011°C/decade. In the other areas, such as Northeast, North-China, and Northwest, UHI has little impact on the warming trends of the regional annual temperature; while in the Southwest of China, introducing UHI stations slows down the warming trend by –0.006°C/decade. But no matter what subregion it is, the total warming/cooling of these effects is much smaller than the background change in regional temperature. The average UHI effect for the entire country, during the last 50 years is less than 0.06°C, which agrees well with the IPCC (2001). This suggests that we cannot conclude that urbanization during the last 50 years has had much obvious effect on the observed warming in China.