Extreme precipitation in Europe: statistical threshold selection based on climatological criteria

In the present study, both parametric (peak over threshold: mean residual life, dispersion index, threshold choice) and non-parametric (percentiles indices 95% and 99%) statistical techniques are employed, aiming at the identification of rainfall thresholds above which a precipitation event can be characterized as extreme. The analysis is based on 45?years (1960–2004) rain gauge daily records from 65 meteorological stations over the European region. According to two climatologically based criteria that were introduced in the study, it was found that a combined peak over threshold methodology has been shown to yield higher threshold values above which extreme precipitation events occur, in comparison to the 95th percentile indices. Overall, concerning northern Europe, it was found that in the majority of the stations, the threshold values vary from 20 to 30?mm, while the results concerning the Mediterranean region are less coherent and the selection of extreme precipitation thresholds differs from region to region. Stations over eastern Mediterranean appear to have thresholds higher than 30?mm, while stations located over the main cyclone trajectories and the cyclogenesis zone of Mediterranean are those with the higher extreme precipitation thresholds (higher than 45?mm).     

Decadal oscillations in rainfall and air temperature in the Paute River Basin—Southern Andes of Ecuador

In the Andes environment, rainfall and temperature can be extremely variable in space and time. The determination of climate variability and climate change needs a special assessment for water management. This paper examines the anomalies of observed monthly rainfall and temperature data from 25 to 16 stations, respectively, from the early 1960s to the 1990s. The stations are located in the Rio Paute Basin in the Ecuador’s Southern Andes. All stations are within the elevation band 1,800 and 4,200?m?a.s.l. and affected by the Tropical Pacific, Amazon, and Tropical Atlantic climate. Anomalies in quantiles were determined for each station and their significance tested. In addition, their correlations with different external climatic influences were studied for anomalies in annual and 3-month seasonal block periods. The results show similar temperature variations for the entire region, which are highly influenced by the El Ni?o–Southern Oscillation, especially during the December–February season. During June–August, the correlation is weaker showing the influence of other climate factors. Higher temperature anomalies are found at the high elevation sites while at deep valley sites the anomalies are less significant. Rainfall variations depend, in addition to elevation, on additional factors such as the aspect orientation, slope, and hydrological regime. The highest and most significant rainfall anomalies are found in the eastern sites.     

Trend analysis of precipitation in Jharkhand State,India

Jharkhand is one of the eastern states of India which has an agriculture-based economy. Uncertain and erratic distribution of precipitation as well as a lack of state water resources planning is the major limitation to crop growth in the region. In this study, the spatial and temporal variability in precipitation in the state was examined using a monthly precipitation time series of 111 years (1901–2011) from 18 meteorological stations. Autocorrelation and Mann–Kendall/modified Mann–Kendall tests were utilized to detect possible trends, and the Theil and Sen slope estimator test was used to determine the magnitude of change over the entire time series. The most probable change year (change point) was detected using the Pettitt–Mann–Whitney test, and the entire time series was sub-divided into two parts: before and after the change point. Arc-Map 9.3 software was utilized to assess the spatial patterns of the trends over the entire state. Annual precipitation exhibited a decreasing trend in 5 out of 18 stations during the whole period. For annual, monsoon and winter periods of precipitation, the slope test indicated a decreasing trend for all stations during 1901–2011. The highest variability was observed in post-monsoon precipitation (77.87 %) and the lowest variability was observed in the annual series (15.76 %) over the 111 years. An increasing trend in precipitation in the state was found during the period 1901–1949, which was reversed during the subsequent period (1950–2011).     

An analysis of daily and monthly precipitation seasonality and regimes in Iran and the associated changes in 1951–2014

Daily and monthly total precipitation of 155 synoptic stations with relatively regular distribution over Iran, covering the 1990–2014 period, were used to investigate the spatial pattern of precipitation seasonality and regimes over Iran, using a set of precipitation seasonality indices. The results suggest a strong agreement between the indices computed at monthly time scale. The result also shows a latitudinal decreasing gradient from the lower index values in the north to the highest values in the south of Iran, suggesting a strong negative relationship between the latitude and the indices. A weak but statistically significant association was also found between the indices and the longitude, showing a gradual west-east contrast between the mountainous western Iran and the central-eastern lowlands and deserts of the country. The spatial patterns of the indices well agree in revealing different precipitation regimes in Iran, in spite of the observed discrepancies in their areal extent of the regions identified. All the indices characterized northern Iran by a precipitation regime having a moderate seasonality, while the mountainous areas of the western and northern Iran are featured by a marked precipitation regime possessing a longer dry season. However, the most seasonal precipitation regime with the longest dry period describes the southern country and some spot areas of the central-eastern Iran. The spatial distribution of the seasonal precipitation regimes and the month and season of maximum precipitation amounts across Iran was also identified, suggesting that from the 24 possible precipitation regimes over the globe, eight were found in Iran, from which a precipitation regime with the highest precipitation amount in winter, followed by autumn, spring, and summer characterized most parts of the country. January and JFM were also found as the month and season of maximum precipitation in a majority of stations distributed over Iran, respectively. The precipitation concentration index (DPCI) computed using daily precipitation data ranges between 0.56 and 0.76 across the country; nonetheless, the values between 0.64 and 0.70 characterized a majority of stations distributed over most parts of Iran. Contrarily to the indices computed at monthly time scale, the DPCI does not show a clear latitudinal pattern over the country. The Mann–Kendal trend test and the Sen slope estimator were applied to the computed indices relative to 16 stations with the longest and complete precipitation records during 1951–2014 time period. The indices time series showed no significant trend in the majority of the stations, indicating that the precipitation regimes of the studied stations did not change over 1951–2014 period.     

Temporal change of climate zones in China in the context of climate warming

In China, ten climate types were classified using the K-means cluster analysis based on monthly temperature and precipitation data from 753 national meteorological stations for the period 1966–2005. However, 11 mountain climate stations, which are located in southeast China, were classified as one type due to their distinct climate characteristic that differentiated them from other stations. This type could not represent the climate characteristic of this region because all climate stations in this type were located at high-elevation mountains. Thus, it was eliminated when defining climate zones based on climate types. Therefore, nine climate zones were defined in China. Moreover, the temporal change of climate zones was detected in 20-year intervals (1966–1985 and 1986–2005). Although 48 stations changed their climate zones between these two periods, the whole pattern of all climate zones remained stable in these two periods. However, the boundaries between some climate zones changed slightly due to inconsistent variation of regional temperature and precipitation. The most obvious change was the eastern movement of the boundary between an arid temperate zone and a sub-humid temperate zone. There was also a northern shift of the boundary between a tropic zone and a southern subtropic zone. All these changes were probably connected with the climate change in recent 40 years.     

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.     

Rainfall uncertainty in the Mediterranean: time series, uncertainty, and extreme events

Temporal precipitation irregularities, extreme rainfall, or droughts represent great climate concerns and have major impacts on the natural environment. The present study focuses on 41 stations spread over the entire Mediterranean region. The datasets contain daily rainfall totals, with a median length of 56?years within the period of 1931?C2006. The study aims at detecting significant trends in the time series and the uncertainties of four parameters: annual rainfall total, number of rain spells, the rain-spells yields, and rainy season length. In addition, it aims to detect significant temporal changes in the occurrence of extreme events of these parameters. Several methodologies have been used in this study, and the main conclusion is that despite the general assumption of tremendous changes in the rainfall regime, no significant temporal trends or uncertainty trends were found in most of the stations, neither in their annual totals, their number of rain spells, and their rain-spell yields, nor in their rainy season length. However, in the few cases that a significant trend was detected, former years tended to be wetter, longer, and with more abundant rain spells, while the opposite is seen in the later years; and uncertainty, tends to increase more than to decrease.     

辽宁地区夏季高温极值预测模型

利用1957-2006年辽宁地区夏季23站极端最高气温资料和国家气候中心气候监测室的74项环流特征量资料,应用EOF方法对高温极值样本进行分解,研究辽宁极端高温的时空分布规律。结果表明：第一特征向量表现为区域整体一致的特征,中心区位于辽西北、辽北,第二、三特征向量空间分布表现为东西部反位相和南北反位相的特征。普查了前3个时间系数与前期环流指数的相关关系,认为前3个时间系数的显著影响因子是不同的。采用CSC准则确定最优预测因子,分别建立各时间系数的回归统计模型,并对高温极值历史拟合序列进行回报检验和预测检验。回报结果表明,各站的历史拟合率都保持在一定水平,但拟合率在辽西地区较差。各年的历史拟合率极不均衡,多数年份较为稳定,但个别年份拟合率较低。未来3 a试验性预测效果逐年下降,模型对未来1 a预测能力较好,可以作为业务预测的参考。     

Evaluating persistence and identifying trends and abrupt changes in monthly and annual rainfalls of a semi-arid region in Western India

In this study, 43-year (1965–2007) monthly and annual rainfall time series of ten rainfall stations in a semi-arid region of western India are analyzed by adopting three tests for testing normality and by applying autoregressive technique for exploring persistence. Gradual trends are identified by three tests, and their magnitudes are assessed by the Sen’s slope estimator. Also, abrupt changes are detected by using four tests and they are further confirmed by two tests. Box-whisker plots revealed that the rainfalls of June and September are right skewed for all the stations. The annual rainfalls of Bhinder, Dhariawad, and Gogunda stations are found considerably right skewed. The normality tests indicated that the rainfall of July does not deviate from the normal distribution at all the stations. However, the annual rainfall is found non-normal at five stations. The monthly rainfalls of June, July, and August have persistence respectively at three (Mavli, Salumber, and Sarada), two (Kherwara and Sarada), and one (Mavli) stations, whereas the annual rainfall has persistence at Girwa and Mavli stations. Significantly increasing trend is detected at Mavli in the rainfall of July and in the annual rainfall (p value?>?0.05), while the negative trend in August rainfall at Dhariawad is found significant (p value?>?0.10). This study revealed that the presence of serial correlation does not affect the performance of the Mann-Kendall test. Mean values of trend magnitudes for the rainfalls of June, July, August, and September are 0.3, 0.8, ?0.4, and 0.4 mm year^?1, respectively, and the overall mean value for the annual rainfall is 0.9 mm year^?1. It is found that the standard normal homogeneity test and the Pettitt test are biased towards the end of the series to locate a change point. Conversely, the Bayesian test has a tendency to look for a change point in the beginning of time series. Confirmed abrupt changes in the rainfall time series are found in the year 2003 (Bhinder) in June; years 1974 (Mavli) and 1989 (Dhariawad and Salumber) in July; years 1972 (Sarada), 1990 (Dhariawad), and 2003 (Mavli) in August; years 1977 (Dhariawad), 1991 (Sarada), and 2004 (Kotra) in September; and in the year 1972 (Mavli and Sarada stations) in the annual series. It is emphasized that the significantly increasing trend of rainfall may have linkages with climate change and/or variability. Finally, this study recommends use of multiple statistical tests for analyzing hydrologic time series in order to ensure reliable decisions.     

Impacts of climate change on August stream discharge in the Central-Rocky Mountains

In the snowmelt dominated hydrology of arid western US landscapes, late summer low streamflow is the most vulnerable period for aquatic ecosystem habitats and trout populations. This study analyzes mean August discharge at 153 streams throughout the Central Rocky Mountains of North America (CRMs) for changes in discharge from 1950–2008. The purpose of this study was to determine if: (1) Mean August stream discharge values have decreased over the last half-century; (2) Low discharge values are occurring more frequently; (3) Climatic variables are influencing August discharge trends. Here we use a strict selection process to characterize gauging stations based on amount of anthropogenic impact in order to identify heavily impacted rivers and understand the relationship between climatic variables and discharge trends. Using historic United States Geologic Survey discharge data, we analyzed data for trends of 40–59 years. Combining of these records along with aerial photos and water rights records we selected gauging stations based on the length and continuity of discharge records and categorized each based on the amount of diversion. Variables that could potentially influence discharge such as change in vegetation and Pacific Decadal Oscillation (PDO) were examined, but we found that that both did not significantly influence August discharge patterns. Our analyses indicate that non-regulated watersheds are experiencing substantial declines in stream discharge and we have found that 89% of all non-regulated stations exhibit a declining slope. Additionally our results here indicate a significant (α?≤?0.10) decline in discharge from 1951–2008 for the CRMs. Correlations results at our pristine sites show a negative relationship between air temperatures and discharge and these results coupled with increasing air temperature trends pose serious concern for aquatic ecosystems in CRMs.     

Streamflow drought severity analysis by percent of normal index (PNI) in northwest Iran

The streamflow drought is the most important type of drought due to the high dependence of many activities on surface water resources. The streamflow drought severity was identified by the percent of normal index (PNI) in the western basins of the Lake Urmia located in northwest Iran. The streamflow records were obtained from 14 hydrometric stations for the period October 1975–September 2009. The temporal trends of the streamflow drought severity were detected by the parametric Student’s t test and the nonparametric Mann–Kendall and Sen’s tests. The worst streamflow droughts at almost all the stations occurred in 1999–2000 and 2000–2001. The streamflow drought severity based on the PNI increased during the last 34 years. The results also indicated that the temporal dependency of time series had a dominant role in detecting trend by the parametric Student’s t test.     

Is adjustment of breeding phenology keeping pace with the need for change? Linking observed response in woodland birds to changes in temperature and selection pressure

Despite the recent plethora of studies investigating biotic implications of climate change, most research has been undertaken without the need for change being quantified. Failure to link observed responses to selection pressure is a fundamental omission because whether change is appropriate cannot then be determined. We use almost 7,000 records to analyse long-term (1974–2004) changes in breeding phenology for six co-occurring woodland birds at a site with significantly increasing spring temperatures. We link observed change to changes in selection for early laying (calculated using differential breeding success as the season progresses) to determine whether change is: (1) necessary, (2) appropriate, and (3) sufficient. Three (resident) species—blue tit, great tit, and nuthatch—started clutches significantly earlier over time without selection for early laying becoming stronger over the same period. This suggests that observed advancements are appropriate, and sufficient, to track climate change. For another species—coal tit—there was no change in lay date, and although there was always selection to lay early, selection intensity did not change over time. For this, the earliest-laying species, bet-hedging to prevent maladaptation (laying too early) or stabilising selection may be acting to maintain phenological inertia, even when phenological change could be adaptive. For the final two (migratory) species—pied flycatcher and redstart—there was no temporal change in lay date, despite selection for early laying becoming significantly stronger over time. This study indicates that some species are tracking climate change successfully while ecologically-similar species, at the same study site, are failing to do so.     

Scaling behaviors of precipitation over China

Scaling behaviors in the precipitation time series derived from 1951 to 2009 over China are investigated by detrended fluctuation analysis (DFA) method. The results show that there exists long-term memory for the precipitation time series in some stations, where the values of the scaling exponent α are less than 0.62, implying weak persistence characteristics. The values of scaling exponent in other stations indicate random behaviors. In addition, the scaling exponent α in precipitation records varies from station to station over China. A numerical test is made to verify the significance in DFA exponents by shuffling the data records many times. We think it is significant when the values of scaling exponent before shuffled precipitation records are larger than the interval threshold for 95 % confidence level after shuffling precipitation records many times. By comparison, the daily precipitation records exhibit weak positively long-range correlation in a power law fashion mainly at the stations taking on zonal distributions in south China, upper and middle reaches of the Yellow River, northern part of northeast China. This may be related to the subtropical high. Furthermore, the values of scaling exponent which cannot pass the significance test do not show a clear distribution pattern. It seems that the stations are mainly distributed in coastal areas, southwest China, and southern part of north China. In fact, many complicated factors may affect the scaling behaviors of precipitation such as the system of the east and south Asian monsoon, the interaction between sea and land, and the big landform of the Tibetan Plateau. These results may provide a better prerequisite to long-term predictor of precipitation time series for different regions over China.     

龙岩市降水时空分布及趋势研究

利用龙岩市1960—2013年7个国家级气象站的逐日降水资料,采用Mann-Kendall趋势和突变检验法及Morlet小波功率谱分析方法,分析龙岩市降水的时空分布规律。结果表明,龙岩市年降水量呈微弱增加趋势,年际波动振幅较大。年降水量多年平均值为1 641 mm,最小值出现在1991年(1 139.9 mm),最大值则出现在1975年(2 286.9 mm),年降水时间序列存在显著的2~8 a的周期。降水主要集中在春季,春季降水量占全年降水量的38.2%左右,其次是夏季和秋季,冬季降水量最少,仅占全年降水量的11.5%。1—6月月平降水量呈现增长趋势,8—12月呈现递减趋势。北部和南部年降水量整体变化趋势基本一致,南部地区总体小于北部地区,只有极个别年份南部地区降水量大于北部地区。     

西安市气候变暖与城市热岛效应问题研究

选取1961—2003年西安站和周围4站月平均气温资料, 利用西安站与周围4站气温距平滑动平均变化趋势的差异, 发现该站平均气温有两个明显的上升期, 热岛效应使西安站平均升温1.07 ℃, 并建立了西安市城市热岛效应模型。在此基础上分离了气候变暖过程中由于城市热岛效应引起的增温作用。     

Temperature trends in the skin/surface, mid-troposphere and low stratosphere near Korea from satellite and ground measurements

Various types of satellite (AIRS/AMSU, MODIS) and ground measurements are used to analyze temperature trends in the four vertical layers (skin/surface, mid-troposphere, and low stratosphere) around the Korean Peninsula (123–132°E, 33–44°N) during the period from September 2002 to August 2010. The ground-based observations include 72 Surface Meteorological Stations (SMSs), 6 radiosonde stations (RAOBs), 457 Automatic Weather Stations (AWSs) over the land, and 5 buoy stations over the ocean. A strong warming (0.052 K yr^?1) at the surface, and a weak warming (0.004～0.010 K yr^?1) in the mid-troposphere and low stratosphere have been found from satellite data, leading to an unstable atmospheric layer. The AIRS/AMSU warming trend over the ocean surface around the Korean Peninsula is about 2.5 times greater than that over the land surface. The ground measurements from both SMS and AWS over the land surface of South Korea also show a warming of 0.043～0.082 K yr^?1, consistent with the satellite observations. The correlation average (r = 0.80) between MODIS skin temperature and ground measurement is significant. The correlations between AMSU and RAOB are very high (0.91～0.95) in the anomaly time series, calculated from the spatial averages of monthly mean temperature values. However, the warming found in the AMSU data is stronger than that from the RAOB at the surface. The opposite feature is present above the mid-troposphere, indicating that there is a systematic difference. Warming phenomena (0.012～0.078 K yr^?1) are observed from all three data sets (SMS, AWS, MODIS), which have been corroborated by the coincident measurements at five ground stations. However, it should also be noted that the observed trends are subject to large uncertainty as the corresponding 95% confidence intervals tend to be larger than the observed signals due to large thermal variability and the relatively short periods of the satellitebased temperature records. The EOF analysis of monthly mean temperature anomalies indicates that the tropospheric temperature variability near Korea is primarily linked to the Arctic Oscillation (AO), and secondarily to ENSO (El Niño and Southern Oscillation). However, the low stratospheric temperature variability is mainly associated with Southern Oscillation and then additionally with Quasi-Biennial Oscillation (QBO). Uncertainties from the different spatial resolutions between satellite data are discussed in the trends.     

Seasonal variation of rain-belts over China

Decadal rainfall data of 228 stations in 1951–1970 and upper-wind records in 1960–1969 published by the Central Meteorological Bureau and relevant provincial organizations are employed in the analysis. It is found that the characteristic features of seasonal variation of the main rain-belts over eastern China to the east of 105°F are quite different from those to the west, over the Qinghai-Xizhang (Tibetan) Plateau. The eastern rain-belts are closely related to the low level flow convergence lines and significantly influenced by the south Asian high and the western Pacific subtropical high.     

Spatial and temporal variability of precipitation indices during 1961–2010 in Hunan Province,central south China

Based on daily precipitation records at 75 meteorological stations in Hunan Province, central south China, the spatial and temporal variability of precipitation indices is analyzed during 1961–2010. For precipitation extremes, most of precipitation indices suggest that both the amount and the intensity of extreme precipitation are increasing, especially the mean precipitation amount on a wet day, showing a significant positive trend. Meanwhile, both of the monthly rainfall heterogeneity and the contribution of the days with the greatest rainfall show an upward trend. When it comes to rainfall erosivity, most of this province is characterized by high values of annual rainfall erosivity. Although the directions of trends in annual rainfall erosivity at most stations are upward, only 6 of the 75 stations have significant trends. Furthermore, the spatial and temporal variation of dryness/wetness has been assessed by the standardized precipitation index (SPI). The principal component analysis (PCA) was applied to the SPI series computed on 24-month time scales. The results demonstrated a noticeable spatial variability with three subregions characterized by different trends: a remarkable wet tendency prevails in the central and southern areas, while the northern areas are dominated by a remarkable dry tendency.     

On detecting long-term changes in atmospheric moisture

Long-term temperature changes are expected to give rise to changes in the water vapor content of the atmosphere, which in turn would accentuate the temperature change. It is thus important to monitor water vapor in the troposphere and lower stratosphere. This paper reviews existing data for such an endeavor and the prospects for improvement in monitoring.In general, radiosondes provide the longest record but the data are fraught with problems, some arising from the distribution of stations and some from data continuity questions arising from the use of different measuring devices over both time at one place and over space at any one time. Satellite records are now of limited duration but they will soon be useful in detecting changes. Satellite water vapor observations have their own limitations; there is no one system capable of measuring water vapor over all surfaces in all varieties of weather. Among the needs are careful analysis of existing records, the collection of metadata about the measuring systems, the development of a transfer standard radiosonde system, and the commitment to maintaining an observing system dedicated to describing any climate changes worldwide.     

Assessment of CMIP3 climate models and projected changes of precipitation and temperature in the Yangtze River Basin, China

The projected changes of precipitation and temperature in the Yangtze River Basin in the 20th Century from 20 models of the CMIP3 (phase 3 of the Coupled Model Inter-comparison Project) dataset are analyzed based on the observed precipitation and temperature data of 147 meteorological stations in the Yangtze River Basin. The results show that all models tend to underestimate the annual mean temperature over the Yangtze River Basin, and to overestimate the annual mean precipitation. The temporal changes of simulated annual mean precipitation and temperature are broadly comparable with the observations, but with large variability among the results of the models. Most of the models can reproduce maximum precipitation during the monsoon season, while all models tend to underestimate the mean temperature of each month over the Yangtze River Basin. The Taylor diagram shows that the differences between modeled and observed temperature are relatively smaller as compared to differences in precipitation. For a detailed investigation of regional characteristics of climate change in the Yangtze River Basin during 2011–2050, the multi-model ensembles produced by an upgraded REA method are carried out for more reliable projections. The projected precipitation and temperature show large spatial variability in the Yangtze River Basin. Mean precipitation will increase under the A1B and B1 scenarios and decrease under the A2 scenario, with linear trends ranging from ?21 to 28.5?mm/decade. Increasing mean temperature can be found in all scenarios with linear trends ranging from 0.15 to 0.48°C/decade. Grids in the head region of the Jingshajiang catchment show distinct increasing trends for all scenarios. Some physical processes associated with precipitation are not well represented in the models.