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1.
Changes in daily climate extremes in the arid area of northwestern China   总被引:3,自引:0,他引:3  
There has been a paucity of information on trends in daily climate and climate extremes, especially for the arid region. We analyzed the changes in the indices of climate extremes, on the basis of daily maximum and minimum air temperature and precipitation at 59 meteorological stations in the arid region of northwest China over the period 1960–2003. Twelve indices of extreme temperature and six indices of extreme precipitation are examined. Temperature extremes show a warming trend with a large proportion of stations having statistically significant trends for all temperature indices. The regional occurrence of extreme cool days and nights has decreased by ?0.93 and ?2.36 days/decade, respectively. Over the same period, the occurrence of extreme warm days and nights has increased by 1.25 and 2.10 days/decade, respectively. The number of frost days and ice days shows a statistically significant decrease at the rate of ?3.24 and ?2.75 days/decade, respectively. The extreme temperature indices also show the increasing trend, with larger values for the index describing variations in the lowest minimum temperature. The trends of Min Tmin (Tmax) and Max Tmin (Tmax) are 0.85 (0.61) and 0.32 (0.17)?°C/decade. Most precipitation indices exhibit increasing trends across the region. On average, regional maximum 1-day precipitation, annual total wet-day precipitation, and number of heavy precipitation days and very wet days show insignificant increases. Insignificant decreasing trends are also found for consecutive dry days. The rank-sum statistic value of most temperature indices exhibits consistent or statistically significant trends across the region. The regional medians after 1986 of Min Tmin (Tmax), Max Tmin (Tmax), warm days (nights), and warm spell duration indicator show statistically more larger than medians before 1986, but the frost days, ice days, cool days (nights), and diurnal temperature range reversed. The medians of precipitation indices show insignificant change except for consecutive dry days before and after 1986.  相似文献   

2.
Characterizing the response of temperature variables to agricultural irrigation is expected to be an important challenge for understanding the full impact of water management on regional climate change. In this paper, the trend analysis and abrupt change test were applied to detect the global warming effect. Then, the quantitative irrigation-induced cooling effects on temperature variables between April and August from 1970 to 2010 in the Lhasa River basin were estimated using historical time series of gridded meteorological records and a map of the area equipped for irrigation. Trends in the maximum temperature (Tmax) were statistically positive, and a significant increasing trend for the minimum temperature (Tmin) was detected at the 0.01 and 0.05 confidence levels. No abrupt changing point of warming was detected in the time series for Tmax. The abrupt changes in Tmin in the irrigation concentration period took place in 1995, 5 years later than the corresponding change in April. Affected by global warming, the increase in temperature was the largest in July and August, when the irrigation-induced cooling effect was also the most significant. The irrigation-induced cooling effect for Tmax and Tmin in April–August (except for June) ranged from − 0.017 to − 0.009 °C/decade and from − 0.011 to − 0.001 °C/decade, respectively, and the cooling effect for diurnal temperature range (DTR) ranged from − 0.011 to 0 °C/decade. The cooling effect on temperature reached above 0.01 °C in July and August, but for the growing seasons, the effect was weak, only 0.001 °C. The Tmax and Tmin trends during the whole growing seasons decreased by both 0.002 °C/decade, respectively, with a 10% increase in irrigation land proportion. Even in July and August, the trends were expected to decrease by about 0.005 °C/decade with a 10% increase in irrigation land proportion. The irrigation-induced cooling effect could partially slow global warming.  相似文献   

3.
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.  相似文献   

4.
利用中国691个无缺测站点的经均一化处理及质量控制的逐日最高、最低气温资料,基于冷昼日数、冷夜日数、霜冻日数、冰冻日数、月最低气温极大值以及月最低气温极小值等6个由世界气象组织定义的极端气温指数,分析了1961~2014年中国冬季的极端低温变化特征。结果表明:冷昼日数、冷夜日数、霜冻日数以及冰冻日数在全国大部分地区均呈现下降的趋势,下降趋势较为明显的区域集中在东北南部、华北、西北东部、华东、华中、西南及高原地区,全国整体上下降幅度分别为-0.9 d/10 a、-1.7 d/10 a、-1.5 d/10a和-1.4 d/10 a。最低气温极大值和最低气温极小值在全国范围内则主要呈现上升的趋势,全国整体上分别为0.4℃/10 a和0.6℃/10 a;极端低温天数在20世纪60年代至70年代中后期呈现波动状,随后自20世纪70年代末80年代初至21世纪初呈明显下降趋势,从2006年左右以后其下降趋势较之前有所减缓,是对全球变暖减缓背景下的气候响应;与其他时间段相比,20世纪60年代至70年代为冬季极端低温事件较为频发的时间段,这可能与该时段陆地冷高压频繁活动有关。  相似文献   

5.
Changes in climatic variables at the sub-basins scale (having different features of land cover) are crucial for planning, development and designing of water resources infrastructure in the context of climate change. Accordingly, to explore the features of climate changes in sub-basins of the Source Region of Yellow River (SRYR), absolute changes and trends of temperature variables, maximum temperature (Tmax), minimum temperature (Tmin), mean temperature (Tavg) and diurnal temperature range (DTR), were analyzed annually and seasonally by using daily observed air temperature dataset from 1965 to 2014. Results showed that annual Tmax, Tmin and Tavg for the SRYR were experiencing warming trends respectively at the rate of 0.28, 0.36 and 0.31°C (10 yr)?1. In comparison with the 1st period (1965-1989), more absolute changes and trends towards increasing were observed during the 2nd period (1990-2014). Apart from Tangnaihai (a low altitude sub-basin), these increasing trends and changes seemed more significant in other basins with highest magnitude during winter. Among sub-basins the increasing trends were more dominant in Huangheyan compared to other sub-basins. The largest increase magnitude of Tmin, 1.24 and 1.18°C (10 yr)?1, occurred in high altitude sub-basins Jimai and Huangheyan, respectively, while the smallest increase magnitude of 0.23°C (10 yr)?1 occurred in a low altitude sub-basin Tangnaihai. The high elevation difference in Tangnaihai probably was the main reason for the less increase in the magnitude of Tmin. In the last decade, smaller magnitude of trend for all temperature variables signified the signal of cooling in the region. Overall, changes of temperature variables had significant spatial and seasonal variations. It implies that seasonal variations of runoff might be greater or different for each sub-basin.  相似文献   

6.
The spatial and temporal variations of daily maximum temperature(Tmax), daily minimum temperature(Tmin), daily maximum precipitation(Pmax) and daily maximum wind speed(WSmax) were examined in China using Mann-Kendall test and linear regression method. The results indicated that for China as a whole, Tmax, Tmin and Pmax had significant increasing trends at rates of 0.15℃ per decade, 0.45℃ per decade and 0.58 mm per decade,respectively, while WSmax had decreased significantly at 1.18 m·s~(-1) per decade during 1959—2014. In all regions of China, Tmin increased and WSmax decreased significantly. Spatially, Tmax increased significantly at most of the stations in South China(SC), northwestern North China(NC), northeastern Northeast China(NEC), eastern Northwest China(NWC) and eastern Southwest China(SWC), and the increasing trends were significant in NC, SC, NWC and SWC on the regional average. Tmin increased significantly at most of the stations in China, with notable increase in NEC, northern and southeastern NC and northwestern and eastern NWC. Pmax showed no significant trend at most of the stations in China, and on the regional average it decreased significantly in NC but increased in SC, NWC and the mid-lower Yangtze River valley(YR). WSmax decreased significantly at the vast majority of stations in China, with remarkable decrease in northern NC, northern and central YR, central and southern SC and in parts of central NEC and western NWC. With global climate change and rapidly economic development, China has become more vulnerable to climatic extremes and meteorological disasters, so more strategies of mitigation and/or adaptation of climatic extremes,such as environmentally-friendly and low-cost energy production systems and the enhancement of engineering defense measures are necessary for government and social publics.  相似文献   

7.
Recent studies examining changes in temperature record frequency over the continental United States have reported that the number of Tmax records has been increasing over the past 50 years and occurring at twice the frequency of Tmin records. In a stationary climate, the number of records should decrease with time as 1/n, where n is the number of years of record-keeping. Here we seek to understand how European temperature records have changed during the late 20th century and how they are expected to change as greenhouse gases increase during the 21st century, using a new ensemble method to filter out the effect of the starting year in the calculation of the records. We find that until 1980, the ratio of Tmax to Tmin records remains close to one, indicating that the climate was relatively stationary. After 1980, there is a distinct positive trend where the observed ratio averages around four during the early part of the 21st century, indicative of a warming trend. We note considerable spatial variability in the observations. Further, the ratio of Tmax to Tmin records set by the year 2100 as simulated by five RCM simulations reaches values of up to several hundred by the end of the 21st century. However, the changes in record frequency vary spatially over Europe. The models project the highest numbers of Tmax records over the Mediterranean during summer, and Scandinavia during the spring and fall. Tmin records decrease most substantially over eastern Europe and western Russia, and the Mediterranean. Our analysis confirms the value of the use of maximum and minimum temperature records in regional climate change studies.  相似文献   

8.
中国均一化日平均温、最高温和最低温序列1960-2008   总被引:8,自引:0,他引:8       下载免费PDF全文
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  相似文献   

9.
In this article, the Multi-Fractal Detrended Fluctuation Analysis (MF-DFA) method is adopted to study the temperature, i. e., the maximum temperature (Tmax), mean temperature (Tavg) and minimum (Tmin) air temperature, multifractal characteristics and their formation mechanism, in the typical temperature zones in the coastal regions in Guangdong, Jiangsu and Liaoning Provinces. Following are some terms and concepts used in the present study. Multifractality is defined as a term that characterizes the complexity and self-similarity of objects, and fractal characteristics depict the distribution of probability over the whole set caused by different local conditions or different levels in the process of evolution. Fractality strength denotes the fluctuation range of the data set, and long-range correlation (LRC) measures the stability of the climate system and the trend of climate change in the future. In this research, it is found that the internal stability and feedback mechanism of climate systems in different regions show regional differences. Furthermore, the research also proves that the Tavg, Tmax and Tmin of the above three provinces are highly multifractal. The temperature series multifractality of each province decreases in the order of temperature series multifractality of Liaoning > temperature series multifractality of Guangdong > temperature series multifractality of Jiangsu, and the corresponding long-range correlations follow the same order. It reveals that the most stable temperature series is that of Liaoning, followed by the temperature series of Guangdong, and the most unstable one is that of Jiangsu. Liaoning has the most stable climate system, and it will thus be less responsive to the future climate warming. The stability of the climate system in Jiangsu is the weakest, and its temperature fluctuation will continue to increase in the future, which will probably result in the meteorological disasters of high temperature and heat wave there. Guangdong possesses the strongest degree of multifractal strength, which indicates that its internal temperature series fluctuation is the largest among the three regions. The Tmax multifractal strength of Jiangsu is stronger than that of Liaoning, while the Tavg and Tmin multifractal strength of Jiangsu is weaker than that of Liaoning, showing that Jiangsu has a larger internal Tmax fluctuation than Liaoning does, while it has a smaller fluctuation of Tavg and Tmin than Liaoning does. Guangdong and Liaoning both show the strongest Tmin multifractal strength, followed by Tavg multifractal strength, and the weakest Tmax multifractal strength. However, Jiangsu has the strongest Tmax, followed by Tavg, and the weakest Tmin. The research findings show that these phenomena are closely related to solar radiation, monsoon strength, topography and some other factors. In addition, the multifractality of the temperature time series results from the negative power-law distribution and long-range correlation, in which the long-range correlation influence of temperature series itself plays the dominant role. With the backdrop of global climate change, this research can provide a theoretical basis for the prediction of the spatial-temporal air temperature variation in the eastern coastal areas of China and help us understand its characteristics and causes, and thus the present study will be significant for the environmental protection of coastal areas.  相似文献   

10.
Recent climate change is substantially affecting the spatial pattern of geographical zones, and the temporal and spatial inconsistency of climatic warming and drying patterns contributes to the complexity of the shifting of temperature and aridity zones. Eastern Inner Mongolia, China, located in the interface region of different biomes and ecogeographic zones, has experienced dramatic drying and warming over the past several decades. In this study, the annual accumulated temperature above 10 °C (AAT10) and the aridity index, two key indicators in geographical regionalization, are used to assess warming and drying processes and track the movements of temperature and aridity zones from 1960 to 2008. The results show a significant warming at the regional level from 1960 to 2008 with an AAT10 increase rate of 7.89 °C·d/year (p?<?0.001) in Eastern Inner Mongolia, while the drying trend was not significant during this period. Spatial heterogeneity of warming and drying distributions was also evident. Analysis of warming and drying via piecewise regression revealed two separate, specific trends between the first 31 years (1960–1990) and the subsequent 18 years (1991–2008). Generally, mild warming and very slight wetting occurred prior to 1990, while after 1991 both warming and drying were significant and enhanced. Continuous warming drove a northward shift of temperature zones from the 1960s to 2000s, while aridity zones displayed enhanced temporal and spatial variability. Climate change effects on temperature and aridity zones imply that the patterns of cropping systems, macro-ecosystems, and human land use modes are potentially undergoing migration and modification due to climate change.  相似文献   

11.
Theoretical and Applied Climatology - We assessed the trends of precipitation, maximum and minimum temperature (Tmax and Tmin), diurnal temperature range (DTR), water requirement of autumn-planted...  相似文献   

12.
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.  相似文献   

13.
In this paper we report an analysis of sampling error uncertainties in mean maximum and minimum temperatures (Tmax and Tmin) carried out on monthly,seasonal and annual scales,including an examination of homogenized and original data collected at 731 meteorological stations across China for the period 1951-2004.Uncertainties of the gridded data and national average,linear trends and their uncertainties,as well as the homogenization effect on uncertainties are assessed.It is shown that the sampling error variances of homogenized Tmax and Tmin,which are larger in winter than in summer,have a marked northwest-southeast gradient distribution,while the sampling error variances of the original data are found to be larger and irregular.Tmax and Tmin increase in all months of the year in the study period 1951-2004,with the largest warming and uncertainties being 0.400℃ (10 yr)-1 + 0.269℃ (10 yr)-1 and 0.578℃ (10 yr)-1 + 0.211℃ (10 yr)-1 in February,and the least being 0.022℃ (10 yr)-1 + 0.085℃ (10 yr)-1 and 0.104℃ (10 yr)-1 +0.070℃ (10 yr)-1 in August.Homogenization can remove large uncertainties in the original records resulting from various non-natural changes in China.  相似文献   

14.
The diurnal surface temperature range(DTR) has become significantly smaller over the Tibetan Plateau(TP) but larger in southeastern China, despite the daily mean surface temperature having increased steadily in both areas during recent decades.Based on ERA-Interim reanalysis data covering 1979–2012, this study shows that the weakened DTR over TP is caused by stronger warming of daily minimum surface temperature(Tmin) and a weak cooling of the daily maximum surface temperature(Tmax); meanwhile, the enhanced DTR over southeastern China is mainly associated with a relatively stronger/weaker warming of Tmax/Tmin. A further quantitative analysis of DTR changes through a process-based decomposition method—the Coupled Surface–Atmosphere Climate Feedback Response Analysis Method(CFRAM)—indicates that changes in radiative processes are mainly responsible for the decreased DTR over the TP. In particular, the increased low-level cloud cover tends to induce the radiative cooling/warming during daytime/nighttime, and the increased water vapor helps to decrease the DTR through the stronger radiative warming during nighttime than daytime. Contributions from the changes in all radiative processes(over-2?C) are compensated for by those from the stronger decreased surface sensible heat flux during daytime than during nighttime(approximately 2.5?C), but are co-contributed by the changes in atmospheric dynamics(approximately-0.4?C) and the stronger increased latent heat flux during daytime(approximately-0.8?C). In contrast, the increased DTR over southeastern China is mainly contributed by the changes in cloud, water vapor and atmospheric dynamics. The changes in surface heat fluxes have resulted in a decrease in DTR over southeastern China.  相似文献   

15.
The spatial and temporal trends of 11 (7) temperature (precipitation) extreme indices are examined for the Loess Plateau Region (LPR) and its southeast and northwest sub-regions based on daily observations at 214 meteorological stations. Results show widespread significant warming trends for all the temperature extremes except for the diurnal temperature range (DTR) and the lowest daily maximum temperature in each year (TXn) during 1961–2010. When regionally averaged, a significant warming trend is detected for all the indices except for DTR and TXn in the past 50 years. Compared with the entire LPR, a significant warming trend is detected for all the indices except for DTR and TXn over the southeast sub-region of LPR; while it is observed for all the indices over the northwest. The trends for these indices are generally stronger in the northwest than in the southeast in the past 50 years. In contrast, for precipitation indices, only a small percentage of areas show significant drying or wetting trends and, when regionally averaged, none of them displays significant trends during the past 50 years. On the sub-regional scale, however, a larger percentage of areas show significant drying trends for precipitation indices generally over the southeast relative to the entire LPR, and noticeably, the sub-regional average heavy precipitation (R10mm) and wet day precipitation (PRCPTOT) display significant decreasing trends during the past 50 years; whereas only a slightly larger percentage of areas show significant wetting trends for these indices over the northwest compared with the entire LPR, and when sub-regionally averaged, none of the indices have significant trends during the past 50 years.  相似文献   

16.
Based on homogenized land surface air temperature (SAT) data (derived from China Homogenized Historical Temperature (CHHT) 1.0), the warming trends over Northeast China are detected in this paper, and the impacts of urban heat islands (UHIs) evaluated. Results show that this region is undergoing rapid warming: the trends of annual mean minimum temperature (MMIT), mean temperature (MT), and mean maximum temperature (MMAT) are 0.40 C decade?1, 0.32 C decade?1, and 0.23 C decade?1, respectively. Regional average temperature series built with these networks including and excluding “typical urban stations” are compared for the periods of 1954–2005. Although impacts of UHIs on the absolute annual and seasonal temperature are identified, UHI contributions to the long-term trends are less than 10% of the regional total warming during the period. The large warming trend during the period is due to a regime shift in around 1988, which accounted for about 51% of the regional warming.  相似文献   

17.
This study analyses spatio-temporal trends in precipitation, temperature, and river discharge in the northeast of Iran during recent decades (1953–2013). The Pettitt, SNHT, Buishand, Box-Pierce, Ljung-Box, and McLeod-Li methods were applied to examine homogeneity in time series studied. The nonparametric Mann-Kendall and Sen’s slope estimator tests were used to detect possible significant (p < 0.05) temporal trends in hydrometeorological time series and their magnitude, respectively. For time series with autocorrelation, the trend-free pre-whitening (TFPW) method was used to determine significant trends. To explore spatial distributions of trends, their magnitudes were interpolated by the inverse distance whitening (IDW) method. Trend analysis shows that for daily, monthly, and annual precipitation time series, 12.5, 19, and 12.5 % of the stations revealed significant increasing trends, respectively. For mean temperature, warming trends were found at 38, 23, and 31 % of the stations on daily, monthly, and annual timescales, in turn. Daily and monthly river discharge decreased at 80 and 40 % of the stations. Overall, these results indicate significant increases in precipitation and temperature but decreases in river discharge during recent decades. Hence, it can be concluded that decreasing trends in river discharge time series over the northeast of Iran during 1953–2013 are in response to warming temperatures, which increase the rate of evapotranspiration. Differences between the results of our comprehensive large-scale study and those of previous researches confirm the necessity for more model-based local studies on climatic and environmental changes across the northeast of Iran.  相似文献   

18.
近44 a中国冬夏气温变率及其对区域变暖性的影响   总被引:4,自引:2,他引:4  
利用近44a中国85个测站冬夏季逐日平均、最高和最低气温序列,研究冬夏季温度季节变率及其时空演变特征,探讨其对区域变暖稳定性的影响。结果表明:冬季,除高原、西南、东北以外的中国大部分地区,温度的季节变率存在显著下降趋势,是近期变暖的稳定区,其中变暖最为稳定、显著的区域是西北、华北地区,东北北部虽变暖幅度很大,但稳定性最差;夏季,长江中下游及其江南地区温度变率存在显著上升趋势,20世纪70年代后年际变幅明显增大,表明该地区80年代降温的稳定性差。  相似文献   

19.
Dissimilarities in temperature trends in space and time over the Indian region have been examined to look for signatures of aerosols’ influence. Separate temperature time series for North and South India were constructed for dry (November–May) and wet (June–October) seasons. Temperature trend for the entire period 1901–2007 and different subperiods of 1901–1950, 1951–1990, 1971–2007, and 1991–2007 have been examined to isolate the aerosol and other greenhouse gas influences on temperatures. Maximum (daytime) temperatures during dry season corresponding to North and South India show significant warming trend of 0.8 and 1.0?°C per hundred years during the period 1901–2007, while minimum temperature shows nebulous trend of 0.2 and 0.3?°C per hundred years over North and South India, respectively. During the wet season, maximum temperature shows nearly half of dry season maximum temperature warming trend. However, asymmetry is observed in dry season maximum temperature trend during post-industrial period 1951–1990 wherein the North/South India shows decreasing/increasing trends, while during the recent period 1991–2007 trends are uniformly positive for both the regions. Spatial and temporal asymmetry in observed trends clearly point to the role of aerosols in lowering temperature trends over northern India. Atmospheric aerosols could cause a negative climate forcing that can modulate the regional surface temperature trends in a significant way. As this forcing acts differentially on day and night temperatures, trends in diurnal temperature range (DTR) provide a direct assessment of impacts of aerosols on temperature trends. Time series of diurnal temperature range for dry and wet seasons have been examined separately for North and South India. Over North India, the DTR for dry season has increased gradually during the period 1901–1970 and thereafter showed decreasing trend, while trends in temperature range over Southern India were almost opposite in phase with North India. The aerosol and greenhouse gases seem to play an important role in the spatial and temporal variability of temperature range over India.  相似文献   

20.
Long-term variations of monthly average maximum and minimum temperature (TMAX and TMIN) and precipitation records in southern Brazil are investigated for the 1913–2006 period. These variations are carefully analyzed for seasonal and annual indices, taken as regional averages. For this purpose, the serial correlation and trend of the indices are investigated using the run and Mann–Kendall tests. The significant trends are obtained from linear least-square fits. The annual and seasonal TMIN indices show significant warming trends with magnitudes (1.7°C per 100 years for annual index) comparable to those reported by the Intergovernmental Panel on Climate Change, but lower than those found for the southern Brazil in another previous work. Regarding the two other variables, the indices show significant trends only for summer, being a cooling trend of 0.6°C per 100 years for the TMAX and an increasing trend of 93 mm per 100 years over an average summer precipitation of 367 mm. Concerning the decadal analysis, the 1920s present the lowest annual, autumn, and spring TMIN and the 1990s, the highest ones. The 1970s is the decade with the lowest summer TMAX, and the 1940s the decade with the highest one. The driest decade is the 1940s and the wettest, the 1980s.  相似文献   

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