Simulation and Regionalization of Daily Global Solar Radiation: A Case Study in Quebec,Canada

Global solar radiation (GSR) is essential for agricultural and plant growth modelling, air and water heating analyses, and solar electric power systems. However, GSR gauging stations are scarce compared with stations for monitoring common meteorological variables such as air temperature and relative humidity. In this study, one power function, three linear regression, and three non-linear models based on an artificial neural network (ANN) are developed to extend short records of daily GSR for meteorological stations where predictors (i.e., temperature and/or relative humidity) are available. The seven models are then applied to 19 meteorological stations located across the province of Quebec (Canada). On average, the root-mean-square errors (RMSEs) for ANN-based models are 0.33–0.54?MJ?m^?2?d^?1 smaller than those for the power function and linear regression models for the same input variables, indicating that the non-linear ANN-based models are more efficient in simulating daily GSR. Regionalization potential of the seven models is also evaluated for ungauged stations where predictors are available. The power function and the three linear regression models are tested by interpolating spatially correlated at-site coefficients using universal kriging or by applying a leave-one-out calibration procedure for spatially uncorrelated at-site coefficients. Regional ANN-based models are also developed by training the model based on the leave-one-out procedure. The RMSEs for regional ANN models are 0.08–0.46?MJ?m^?2?d^?1 smaller than for other models using the same input conditions. However, the regional ANN-based models are more sensitive to new station input values compared with the other models. Maps of interpolated coefficients and regional equations of the power function and the linear regression models are provided for direct application to the study area.     

Shift changes and monotonic trends in autocorrelated temperature series over Iran

Temperature data from 29 synoptic stations in Iran for a period of 40?years (1966–2005) were analyzed to test for the existence of monotonic trends and shift changes in the annual, seasonal, and monthly mean air temperature series using the Mann–Kendall and Mann–Whitney tests. The influences of significant lag-1 serial correlation were eliminated from data by the trend-free pre-whitening method prior to the trend analysis. The magnitude of the temperature trends was derived from the Theil–Sen’s slope estimator. It was found that annual mean air temperature increased at 25 out of the 29 stations, of which 17 stations showed significant monotonic trends. The magnitude of the annual mean air temperature trends averagely was (+)0.224°C per decade. Most of the stations with the significant positive monotonic trends had a significant upward shift change. The analysis indicated that the change point year of the significant upward shift changes was 1972 for the whole stations except the coastal ones. Moreover, the strongest monotonic increasing trends and upward shift changes were observed in summer especially in August and September. The spatial analysis of the mean air temperature trends revealed the highest numbers of significant monotonic trends in the big cities of Iran. These findings provide more insights for better understanding of regional temperature behavior in the study area.     

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.     

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。     

Fluctuations of surface air temperature in the Eastern Mediterranean

Summary  Changes in surface air temperature during the last century are widely discussed among researchers in the field of climatic change. Using various techniques, we investigate trends and periodicity of surface air temperature series from eight meteorological stations in the Eastern Mediterranean. For the analysis, we use the Mann-Kendall rank test, low-pass filtering, autocorrelation spectral analysis and maximum entropy spectral analysis. The latter two tests are compared. The study is based on series over one hundred years in length for four stations, and over fifty years in length for the other four. Increasing and decreasing surface temperature trends were found. These trends, however, are only significant for Malta, Jerusalem, and Tripoli at the 99% confidence level (positive trend) and for Amman at the 95% confidence level (negative trend). We also found inter-decadal variations in surface air temperature, including a fairly regular quasi 20-year oscillation, although its amplitude varied between different cycles. A period of warming began around 1910 at all stations. During the 1970s, the annual mean temperature series exhibit warming, but this warming was not uniform, continuous or of the same order at all the stations. The results of the Autocorrelation Spectral Analysis and the Maximum Entropy Spectral Analysis are similar, pointing to the reliability of the results. The quasi-biennial oscillation (QBO) exists at all stations during both increasing and decreasing trends. Similarly, a broad maximum from 3–8 years (related to El Ni?o) is found at Malta, Athens, Jerusalem, Beirut, and Latakia. An inverse relationship between El Ni?o and the North Atlantic Oscillation with surface air temperature over the Eastern Mediterranean is found at a highly significant confidence level. Received November 15, 1999 Revised August 29, 2000     

Modeling the potential effects of climate change on water temperature downstream of a shallow reservoir,lower madison river,MT

A numerical stream temperature model that accounts for kinematic wave flow routing, and heat exchange fluxes between stream water and the atmosphere, and stream water and the stream bed is developed and calibrated to a data-set from the Lower Madison River, Montana, USA. Future climate scenarios were applied to the model through changes to the atmospheric input data based on air temperature and solar radiation output from four General Circulation Models (GCM) for the region under atmospheric CO₂ concentration doubling. The purpose of this study was to quantify potential climate change impacts on water temperature for the Lower Madison River, and to assess possible impacts to aquatic ecosystems. Because water temperature is a critical component of fish habitat, this information could be of use in future planning operations of current reservoirs. We applied air temperature changes to diurnal temperatures, daytime temperatures only, and nighttime temperatures only, to assess the impacts of variable potential warming trends. The results suggest that, given the potential climatic changes, the aquatic ecosystem downstream of Ennis Lake will experience higher water temperatures, possibly leading to increased stress on fish populations.Daytime warming produced the largest increases in downstream water temperature.     

Indicators of Climate Warming in Minnesota: Lake ICE Covers and Snowmelt Runoff

Records of hydrologic parameters, especially those parameters that are directly linked to air temperature, were analyzed to find indicators of recent climate warming in Minnesota, USA. Minnesota is projected to be vulnerable to climate change because of its location in the northern temperate zone of the globe. Ice-out and ice-in dates on lakes, spring (snowmelt) runoff timing, spring discharge values in streams, and stream water temperatures recorded up to the year 2002 were selected for study. The analysis was conducted by inspection of 10-year moving averages, linear regression on complete and on partial records, and by ranking and sorting of events. Moving averages were used for illustrative purposes only. All statistics were computed on annual data. All parameters examined show trends, and sometimes quite variable trends, over different periods of the record. With the exception of spring stream flow rates the trends of all parameters examined point toward a warming climate in Minnesota over the last two or three decades. Although hidden among strong variability from year to year, ice-out dates on 73 lakes have been shifting to an earlier date at a rate of −0.13 days/year from 1965 to 2002, while ice-in dates on 34 lakes have been delayed by 0.75 days/year from 1979 to 2002. From 1990 to 2002 the rates of change increased to −0.25 days/year for ice-out and 1.44 days/year for ice-in. Trend analyses also show that spring runoff at 21 stream gaging sites examined occurs earlier. From 1964 to 2002 the first spring runoff (due to snowmelt) has occurred −0.30 days/year earlier and the first spring peak runoff −0.23 days/year earlier. The stream water temperature records from 15 sites in the Minneapolis/St Paul metropolitan area shows warming by 0.11^∘C/year, on the average, from 1977 to 2002. Urban development may have had a strong influence. The analysis of spring stream flow rates was inconclusive, probably because runoff is linked as much to precipitation and land use as to air temperature. Ranking and sorting of annual data shows that a disproportionately large number of early lake ice-out dates has occurred after 1985, but also between 1940 and 1950; similarly late lake ice-in has occurred more frequently since about 1990. Ranking and sorting of first spring runoff dates also gave evidence of earlier occurrences, i.e. climate warming in late winter. A relationship of changes in hydrologic parameters with trends in air temperature records was demonstrated. Ice-out dates were shown to correlate most strongly with average March air temperatures shifting by −2.0 days for a 1^°C increase in March air temperature. Spring runoff dates also show a relationship with March air temperatures; spring runoff dates shift at a rate of −2.5 days/1^°C minimum March air temperature change. Water temperatures at seven river sites in the Minneapolis/St Paul metropolitan area show an average rise of 0.46^°C in river temperature/1^°C mean annual air temperature change, but this rate of change probably includes effects of urban development. In conclusion, records of five hydrologic parameters that are closely linked to air temperature show a trend that suggests recent climate warming in Minnesota, and especially from 1990 to 2002. The recent rates of change calculated from the records are very noteworthy, but must not be used to project future parameter values, since trends cannot continue indefinitely, and trend reversals can be seen in some of the long-term records.     

Intensified reduction in summertime light rainfall over mountains compared with plains in Eastern China

Based on daily rainfall data from 1960 to 2007, this study investigated the difference in rainfall trends between seven mountain stations and 21 nearby plain stations in eastern China for the months June–August. The amount and frequency of light rain (≤2.5 mm/day) over the mountain areas showed a greater decreasing trend than over the surrounding plain regions. The trend of light-rainfall frequency at mountain stations is ??4.8%/decade, approximately double that at plain stations (??2.3%/decade). The trend in light-rainfall amount at mountain stations is ??5.0%/decade, approximately three times that at plains station (??1.4%/decade). Reduced wind speed may explain the enhanced decrease in light rainfall over mountain areas through the weakened orographic lifting. Further study is needed to determine whether the precipitation difference between mountain and plain (urban) regions is exacerbated by air pollution in East China through its indirect effects and influence on regional air stability and wind speed.     

Detecting urban warming signals in climate records

Determining whether air temperatures recorded at meteorological stations have been contaminated by the urbanization process is still a controversial issue at the global scale. With support of historical remote sensing data, this study examined the impacts of urban expansion on the trends of air temperature at 69 meteorological stations in Beijing, Tianjin, and Hebei Province over the last three decades. There were significant positive relations between the two factors at all stations. Stronger warming was detected at the meteorological stations that experienced greater urbanization, i.e., those with a higher urbanization rate. While the total urban area affects the absolute temperature values, the change of the urban area (urbanization rate) likely affects the temperature trend. Increases of approximately 10% in urban area around the meteorological stations likely contributed to the 0.13℃ rise in air temperature records in addition to regional climate warming. This study also provides a new approach to selecting reference stations based on remotely sensed urban fractions. Generally, the urbanization-induced warming contributed to approximately 44.1% of the overall warming trends in the plain region of study area during the past 30 years, and the regional climate warming was 0.30℃ (10 yr)-1 in the last three decades.     

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.     

Streamflow trends and climate linkages in the Zagros Mountains,Iran

This paper examines trends in streamflow and their links with local climate in the Karkheh River and its major tributaries, which originate from the Zagros Mountains, Iran. Streamflow records from five mainstream stations for the period 1961–2001 were used to examine trends in a number of streamflow variables. The studied variables were mean annual and monthly flows, 1 and 7 days maximum and minimum flows, timing of the 1-day maxima and minima, and the number and duration of high and low flow pulses. Similarly, the precipitation and temperature data from seven climate stations for the period from 1950s to 2003 were used to examine trends in climatic variables and their correlation with the streamflow. The Spearman Rank test was used for the detection of trends and the correlation analysis was based on the Pearson method. The results reveal a number of significant trends in streamflow variables both increasing (e.g. December flows) and decreasing (e.g. May flows) for all stations. However, some trends were not spatially uniform. For example, decline in low flow characteristics were more significant in the upper parts of the basin, whereas increasing trends in floods and winter flows were noteworthy in the middle parts of the basin. Most of these trends could be attributed to precipitation changes. The results show that the decline in April and May precipitation causes the decline in the low flows while the increase in winter (particularly March) precipitation coupled with temperature changes lead to increase in the flood regime. The observed trends at the Jelogir station on the Karkheh River reflect the combined effect of the upstream catchments. The significant trends observed in a number of streamflow variables at Jelogir, 1-day maximum, December flow and low pulse count and duration, point to the changes in hydrological regime of the entire Karkheh River system and are attributed to the changes in climatic variables.     

Estimation of surface air temperature trends over the Russian Federation territory using the quantile regression method

The results are presented of the estimation of surface air temperature variations in different climatically quasi-homogeneous regions of Russia using the nonparametric method of regression analysis (quantile regression). Daily observation records from 517 weather stations were used. The quantile regression technique used for analyzing the trends in long-term series allows obtaining information on trends for the whole range of quantile values from 0 to 1 of dependent variable distributions. Seasonal and regional features of daily minimum, mean, and maximum air temperature trends are considered in a wide range of quantile values. The proposed method that generalizes long-term trends obt ained for groups of stations by quantile regression, is applied to quasi-homogeneous climate regions identified on the territory of Russia.     

中国夏季极端酷暑的气候统计和趋势分析

Based on the daily maximum air temperature data from 300 stations in China from 1958 to 2008, the climatological distribution of the number of days with high temperature extremes （HTEs, maximum temperatures higher than 35℃） are studied with a focus on the long-term trends. Although the number of HTE days display well-defined sandwich spatial structures with significant decreasing trends in central China and increasing trends in northern China and southern China, the authors show that the decrease of HTE days in central China occurs mainly in the early period before the 1980s, and a significant increase of HTE days dominates most of the stations after the 1980s. The authors also reveal that there is a jump-like acceleration in the number of HTE days at most stations across China since the mid 1990s, especially in South China, East China, North China, and northwest China.     

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.     

Historical Trend in River Ice Thickness and Coherence in Hydroclimatological Trends in Maine

We analyzed long-term records of ice thickness on the Piscataquis River in central Maine and air temperature in Maine to determine whether there were temporal trends that were associated with climate warming. The trend in ice thickness was compared and correlated with regional time series of winter air temperature, heating degree days (HDD), date of river ice-out, seasonal center-of-volume date (SCVD) (date on which half of the stream runoff volume during the period 1 Jan. to 31 May has occurred), water temperature, and lake ice-out date. All of these variables except lake ice-out date showed significant temporal trends during the 20th century. Average ice thickness around 28 February decreased by about 23 cm from 1912 to 2001. Over the period 1900 to 1999, winter air temperature increased by 1.7 °C and HDD decreased by about 7.5%.Final ice-out date on the Piscataquis River occurred earlier (advanced), by 0.21 days yr^–1 over the period 1931 to 2002, and the SCVD advancedby 0.11 days yr^–1 over the period 1903 to 2001. Ice thickness was significantly correlated (P-value <0.01) with winter air temperature, HDD, river ice-out, and SCVD. These systematic temporal trends in multiple hydrologic indicator variables indicate a coherent response to climate forcing.     

Climate change at the ecosystem scale: a 50-year record in New Hampshire

Observing the full range of climate change impacts at the local scale is difficult. Predicted rates of change are often small relative to interannual variability, and few locations have sufficiently comprehensive long-term records of environmental variables to enable researchers to observe the fine-scale patterns that may be important to understanding the influence of climate change on biological systems at the taxon, community, and ecosystem levels. We examined a 50-year meteorological and hydrological record from the Hubbard Brook Experimental Forest (HBEF) in New Hampshire, an intensively monitored Long-Term Ecological Research site. Of the examined climate metrics, trends in temperature were the most significant (ranging from 0.7 to 1.3 °C increase over 40–50 year records at 4 temperature stations), while analysis of precipitation and hydrologic data yielded mixed results. Regional records show generally similar trends over the same time period, though longer-term (70–102 year) trends are less dramatic. Taken together, the results from HBEF and the regional records indicate that the climate has warmed detectably over 50 years, with important consequences for hydrological processes. Understanding effects on ecosystems will require a diversity of metrics and concurrent ecological observations at a range of sites, as well as a recognition that ecosystems have existed in a directionally changing climate for decades, and are not necessarily in equilibrium with the current climate.     

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.     

1999—2008年夏季华北冷涡的异常特征

利用1999—2008年5—8月中国160站月平均气温资料、每日2次的MICAPS资料及每日4次的NCEP 1°×1°资料,通过定义一个夏季华北冷涡强度指数(NCCVI),研究了夏季华北冷涡异常年西太平洋副高、东亚季风、高空急流及低层垂直运动的异常特征。结果表明：夏季NCCVI异常强年500 hPa上贝加尔湖地区有气旋性环流发展,从贝加尔湖至我国华北地区为一显著的高空槽所控制,冷空气较活跃并随槽后引导气流扩散南下影响华北地区。对流层各层偏暖湿,200 hPa上高空急流偏强,700 hPa上高纬冷涡后部偏北气流加强,低纬偏南气流加强,冷暖空气在华北交汇,华北和东北地区低层上升运动发展。同期副热带高压偏强,位置略偏南;东亚夏季风偏强, 加强了水汽输送。夏季NCCVI异常弱年相反。     

Discrete wavelet transform-based investigation into the variability of standardized precipitation index in Northwest China during 1960–2014

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.     

Seasonal forecasts in the Sahel region: the use of rainfall-based predictive variables

In the Sahel region, seasonal predictions are crucial to alleviate the impacts of climate variability on populations' livelihoods. Agricultural planning (e.g., decisions about sowing date, fertilizer application date, and choice of crop or cultivar) is based on empirical predictive indices whose accuracy to date has not been scientifically proven. This paper attempts to statistically test whether the pattern of rainfall distribution over the May–July period contributes to predicting the real onset date and the nature (wet or dry) of the rainy season, as farmers believe. To that end, we considered historical records of daily rainfall from 51 stations spanning the period 1920–2008 and the different agro-climatic zones in Burkina Faso. We performed (1) principal component analysis to identify climatic zones, based on the patterns of intra-seasonal rainfall, (2) and linear discriminant analysis to find the best rainfall-based variables to distinguish between real and false onset dates of the rainy season, and between wet and dry seasons in each climatic zone. A total of nine climatic zones were identified in each of which, based on rainfall records from May to July, we derived linear discriminant functions to correctly predict the nature of a potential onset date of the rainy season (real or false) and that of the rainy season (dry or wet) in at least three cases out of five. These functions should contribute to alleviating the negative impacts of climate variability in the different climatic zones of Burkina Faso.