Trends and periodicity of daily temperature and precipitation extremes during 1960–2013 in Hunan Province,central south China

In this study, the trends and periodicity in climate extremes are examined in Hunan Province over the period 1960–2013 on the basis of 27 extreme climate indices calculated from daily temperature and precipitation records at 89 meteorological stations. The results show that in the whole province, temperature extremes exhibit a warming trend with more than 50% stations being statistically significant for 7 out of 16 temperature indices, and the nighttime temperature increases faster than the daytime temperature at the annual scale. The changes in most extreme temperature indices show strongly coherent spatial patterns. Moreover, the change rates of almost all temperature indices in north Hunan are greater than those of other regions. However, the statistically significant changes in indices of extreme precipitation are observed at fewer stations than in extreme temperature indices, forming less spatially coherent patterns. Positive trends in indices of extreme precipitation show that the amount and intensity of extreme precipitation events are generally increasing in both annual and seasonal scales, whereas the significant downward trend in consecutive wet days indicates that the precipitation becomes more even over the study period. Analysis of changes in probability distributions of extreme indices for 1960–1986 and 1987–2013 also demonstrates a remarkable shift toward warmer condition and increasing tendency in the amount and intensity of extreme precipitation during the past decades. The variations in extreme climate indices exhibit inconstant frequencies in the wavelet power spectrum. Among the 16 temperature indices, 2 of them show significant 1-year periodic oscillation and 7 of them exhibit significant 4-year cycle during some certain periods. However, significant periodic oscillations can be found in all of the precipitation indices. Wet-day precipitation and three absolute precipitation indices show significant 1-year cycle and other seven provide significant power at the 4-year period, which are mainly found during 1970–1980 and after 1992.     

Trends of Temperature Extremes in Summer and Winter during 1971–2013 in China

The diurnal temperature range(DTR) has decreased dramatically in recent decades, but it is not yet obvious whether the extreme values of DTR have also reduced. Based on the daily maximum and minimum temperature data of 653 stations in China, a set of monthly indices of warm extremes, cold extremes, and DTR extremes in summer(June, July, August) and winter(December, January, February) were studied for spatial and temporal features during the period 1971–2013. Results show that the incidence of warm extremes has been increasing in most parts of China, while the opposite trend was found in the cold extremes for summer and winter months. Both increasing and decreasing trends of monthly DTR extremes were identified in China for both seasons. For high DTR extremes, decreasing trends were identified in northern China for both seasons, but increasing trends were found only in southern China in summer, while in winter, they were found in central China. Monthly low DTR extreme indices demonstrated consistent positive trends in summer and winter, while significant increases(P 0.05) were identified for only a few stations.     

Spatial and temporal temperature trends in Nigeria, 1901–2000

Trends and periodicity analyses can provide information on climate variability inherent in a particular variable. In this study, trend tests and spectral analysis are used to examine the existence of trends and cycles in temperature series (1901–2000) of Nigeria. Periods 1901–1929 and 1942–1980 exhibited cooling trends while 1930–1941 and 1981–2000 showed warming trends. The warmest years in Nigeria were 1941, 1935, 1931 and 1987. The coldest years were 1929, 1975, 1925 and 1974. Whereas no significant trends were detected for 1901–1930 period, the standard period 1931–1960 was marked by significant cooling while 1961–1990 was marked with significant warming. Annual temperature has risen by 0.03?°C/decade during the last century. The overall warming was mostly confined to the south of 12°N especially during April and June. Changes in minimum temperature are higher than that of maximum temperature. The quasi-biennial oscillation was found in annual data for all the six zones with periods of about 2–4?years. Nigeria landscape is under strong North Atlantic Oscillation influence in dry season and under ENSO influence during wet season. Annual temperature series was also found to exhibit significant negative correlation with SOI.     

Changes in Seasonal Patterns of Temperature and Precipitation in China During 1971-2000

Many studies have shown evidence for significant changes in surface climate in different regions of the world and during different seasons over the past 100 years. Based on daily temperature and precipitation data from 720 climate stations in China, cluster analysis was used to identify regions in China that have experienced similar changes in the seasonal cycle of temperature and precipitation during the 1971-2000 climate normal period. Differences in 11-day averages of daily mean temperature and total precipitation between the first （1971-1985） and second （1986-2000） halves of the record were analyzed using the Mann- Whitney U test and the global κ-means clustering algorithm. Results show that most parts of China experienced significant increases in temperature between the two periods, especially in winter, although some of this warming may be attributable to the urban heat island effect in large cities. Most of western China experienced more precipitation in 1986-2000, while precipitation decreased in the Yellow River valley. Changes in the summer monsoon were also evident, with decreases in precipitation during the onset and decay phases, and increases during the wettest period.     

Detection of trends in precipitation during 1960–2008 in Jiangxi province, southeast China

Changes in precipitation exert an enormous impact on human life, and it is of vital importance to study regular patterns of meteorological and hydrological events. In order to explore the changing spatial and temporal patterns of precipitation amounts, precipitation extremes and precipitation concentration in Jiangxi province in southeast China between 1960 and 2008, several precipitation indices series were analysed using the Mann–Kendall test in this study. Our results indicate remarkable differences among the stations with negative and positive precipitation trends at the annual, seasonal and monthly scales, significant increasing trends are mainly found during January, August, winter and summer, while significant decreasing trends mostly are observed during October and autumn. For precipitation extremes, most precipitation indices suggest that both the intensity and the days of extreme precipitation are increasing; the mean precipitation amount, especially, on a wet day shows a significant positive trend. When it comes to precipitation concentration, the monthly rainfall heterogeneity shows an insignificant downward trend, while the contribution of the days with greatest rainfall displays an insignificant upward trend. Furthermore, the long-range persistence is detected for changing process of precipitation amount, extreme precipitation and precipitation concentration using the Rescaled Range Analysis.     

Synergistic Interdecadal Evolution of Precipitation over Eastern China and the Pacific Decadal Oscillation during 1951–2015

By using the multi-taper method(MTM) of singular value decomposition(SVD), this study investigates the interdecadal evolution(10-to 30-year cycle) of precipitation over eastern China from 1951 to 2015 and its relationship with the North Pacific sea surface temperature(SST). Two significant interdecadal signals, one with an 11-year cycle and the other with a 23-year cycle, are identified in both the precipitation and SST fields. Results show that the North Pacific SST forcing modulates the precip...     

Statistical characteristics,trends, and variability of rainfall in Shanxi province,China, during the period 1957–2019

Theoretical and Applied Climatology - Under the background of global warming, an analysis of the trend and variability of rainfall time series on various timescales is very important for...     

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.     

Monthly air temperature trends in Switzerland 1901–2000 and 1975–2004

Summary We analysed long-term temperature trends based on 12 homogenised series of monthly temperature data in Switzerland at elevations between 316 m.a.s.l. and 2490 m.a.s.l for the 20^th century (1901–2000) and for the last thirty years (1975–2004). Comparisons were made between these two periods, with changes standardised to decadal trends. Our results show mean decadal trends of +0.135 °C during the 20^th century and +0.57 °C based on the last three decades only. These trends are more than twice as high as the averaged temperature trends in the Northern Hemisphere. Most stations behave quite similarly, indicating that the increasing trends are linked to large-scale rather than local processes. Seasonal analyses show that the greatest temperature increase in the 1975–2004 period occurred during spring and summer whereas they were particularly weak in spring during the 20^th century. Recent temperature increases are as much related to increases in maximum temperatures as to increases in minimum temperature, a trend that was not apparent in the 1901–2000 period. The different seasonal warming rates may have important consequences for vegetation, natural disasters, human health, and energy consumption, amongst others. The strong increase in summer temperatures helps to explain the accelerated glacier retreat in the Alps since 1980. Authors’ addresses: Martine Rebetez, WSL Swiss Federal Research Institute, 1015 Lausanne, Switzerland; Michael Reinhard, Laboratory of Ecological Systems (ECOS), EPFL Swiss Federal Institute of Technology, 1015 Lausanne, Switzerland.     

Spatial and temporal characteristics of minimum temperature in winter in China during 1961–2010 from NCEP/NCAR reanalysis

Based on the surface 2?m monthly minimum temperature from the National Centers for Environmental Prediction/National Center for Atmospheric Research reanalysis dataset, the spatial and temporal characteristics of winter minimum temperature during 1961–2010 have been analyzed in China. Results showed that the minimum temperature in China has a significant increasing rate of 0.25° per decade calculated by the Mann–Kendall statistical test, which is consistent with the global warming trend. Empirical orthogonal function (EOF) analysis reveals that there are three main patterns that can explain more than 57.6% of the total variance of the winter minimum temperature. The EOF1, EOF2, and EOF3 account for 34.8%, 13.5%, and 13.5% of the total inter-annual variance, respectively. The EOF1, EOF2, and EOF3 patterns are synchronous in northern China, central China, and on the Tibetan Plateau. There exist a decrease trend in the corresponding time coefficients of EOF1 and EOF2 and an increase trend in that of EOF3 since the 1960s. Both the corresponding time coefficients of EOF1 and EOF2 have significant positive correlations with the 500?hPa geopotential heights of the Arctic region and negative correlations in the regions lower than 40°N, while a significant positive correlation is found between the corresponding time coefficients of EOF3 and 500?hPa geopotential heights in the low latitudes. This suggests that rapid warming occurs in northern China and on the Tibetan Plateau, while the weakest trend locates in southeast China. Thus, warming in winter is more pronounced at higher altitudes and latitudes. These patterns are tightly connected with the atmospheric circulation.     

Spatiotemporal variations in rainfall erosivity during the period of 1960–2011 in Guangdong Province,southern China

Rainfall erosivity, which shows a potential risk of soil loss caused by water erosion, is an important factor in soil erosion process. In consideration of the critical condition of soil erosion induced by rainfall in Guangdong Province of southern China, this study analyzed the spatial and temporal variations in rainfall erosivity based on daily rainfall data observed at 25 meteorological stations during the period of 1960–2011. The methods of global spatial autocorrelation, kriging interpolation, Mann–Kendall test, and continuous wavelet transform were used. Results revealed that the annual rainfall erosivity in Guangdong Province, which spatially varied with the maximum level observed in June, was classified as high erosivity with two peaks that occur in spring and summer. In the direction of south–north, mean annual rainfall erosivity, which showed significant relationships with mean annual rainfall and latitude, gradually decreased with the high values mainly distributed in the coastal area and the low values mainly occurring in the lowlands of northwestern Guangdong. Meanwhile, a significant positive spatial autocorrelation which implied a clustered pattern was observed for annual rainfall erosivity. The spatial distribution of seasonal rainfall erosivity exhibited clustering tendencies, except spring erosivity with Moran’s I and Z values of 0.1 and 1.04, respectively. The spatial distribution of monthly rainfall erosivity presented clustered patterns in January–March and July–October as well as random patterns in the remaining months. The temporal trend of mean rainfall erosivity in Guangdong Province showed no statistically significant trend at the annual, seasonal, and monthly scales. However, at each station, 1 out of 25 stations exhibited a statistically significant trend at the annual scale; 4 stations located around the Pearl River Delta presented significant trends in summer at the seasonal scale; significant trends were observed in March (increasing trends at 3 stations), June (increasing trends at 4 stations located in the Beijiang River Basin), and October (decreasing trends at 4 stations) at the monthly scale. In accordance with the mean annual rainfall over Guangdong Province, the mean annual rainfall erosivity showed two significant periodicities of 3–6 and 10–12 years at a confidence level of 95 %. In conclusion, the results of this study provide insights into the spatiotemporal variation in rainfall erosivity in Guangdong Province and support for agrolandscape planning and water and soil conservation efforts in this region.     

Trends in extreme temperature indices in Huang-Huai-Hai River Basin of China during 1961–2014

Spatial and temporal characteristics of temperature extremes have been investigated in Huang-Huai-Hai (HHH) region based on the daily series of temperature observations from 162 meteorological stations. A total of 11 indices were used to assess the changes of temperature pattern. Linear trend analyses revealed that the daily maximum temperature (TXx) increased at α = 0.05 level with a magnitude of 0.15 °C per decade on the regional scale during the period of 1961–2014. More pronounced warming trend of the daily minimum temperature (TNn) was detected at a rate of 0.49 °C per decade (α = 0.01 level). Consequently, a decreasing trend of the temperature range of TXx and TNn (extreme temperature range) was observed. The frequency of hot days (TXf90) and annual average of warm events (warm spell duration indicator, WSDI) showed significant increasing trends, while that of cold nights (TNf10) and cold events (cold spell duration indicator, CSDI) showed opposite behaviors. Both warm winter (W-W) and hot summer (H-S) series displayed significant increasing trends at α = 0.01 confidence level. The cold winter (C-W) series showed a decreasing trend at α = 0.01 confidence level, while the cool summer (C-S) series showed a nonsignificant decreasing trend that is not passing the 90% confidence level (α = 0.1). Abrupt increments of warm­related extremes (TXx, TXf90, WSDI) have been detected since 1990s, and a steadily decreasing trend of cold related extremes (TNf10, CSDI) was found since 1970s. Ten hot summers out of 11 and nine warm winters out of 10 occurred after 1990s. Altitude has a large impact on spatial pattern of extreme temperature indices, and the urban heat island effect also has an impact on amplitude of variation in extreme temperature. Trend magnitudes are significantly larger at sites with high altitudes for warm­related indices (TXx, TXf90, WSDI), while those involving cold-related indices (TNn, TNf10) are remarkably larger for stations with low altitudes.     

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.     

Trend of monthly temperature and daily extreme temperature during 1951–2012 in New Zealand

A new method for calculating evaporation is proposed, using the Penman–Monteith (P-M) model with remote sensing. This paper achieved the effective estimation to daily evapotranspiration in the Ziya river catchment by using the P-M model based on MODIS remote sensing leaf area index and respectively estimated plant transpiration and soil evaporation by using coefficient of soil evaporation. This model divided catchment into seven different sub-regions which are prairie, meadow, grass, shrub, broad-leaved forest, cultivated vegetation, and coniferous forest through thoroughly considering the vegetation diversity. Furthermore, optimizing and calibrating parameters based on each sub-region and analyzing spatio-temporal variation rules of the model main parameters which are coefficient of soil evaporation f and maximum stomatal conductance g _sx . The results indicate that f and g _sx calibrated by model are basically consistent with measured data and have obvious spatio-temporal distribution characteristics. The monthly average evapotranspiration value of simulation is 37.96 mm/mon which is close to the measured value with 33.66 mm/mon and the relative error of simulation results in each subregion are within 11 %, which illustrates that simulated values and measured values fit well and the precision of model is high. In addition, plant transpiration and soil evaporation account for about 84.64 and 15.36 % respectively in total evapotranspiration, which means the difference between values of them is large. What is more, this model can effectively estimate the green water resources in basin and provide effective technological support for water resources estimation.     

Spatial and temporal features of summer extreme temperature over China during 1960–2013

Theoretical and Applied Climatology - Based on daily air temperature data from 772 stations in China, the present study uses absolute index and percentile index to investigate the spatial and...     

Comparison of two homogenized datasets of daily maximum/mean/minimum temperature in China during 1960–2013

Two homogenized datasets of daily maximum temperature (Tmax), mean temperature (Tm), and minimum temperature (Tmin) series in China have recently been developed. One is CHTM3.0, based on the Multiple Analysis of Series for Homogenization (MASH) method, and includes 753 stations for the period 1960–2013. The other is CHHTD1.0, based on the Relative Homogenization test (RHtest), and includes 2419 stations over the period 1951–2011. The daily Tmax/Tm/Tmin series at 751 stations, which are in both datasets, are chosen and compared against the raw dataset, with regard to the number of breakpoints, long-term climate trends, and their geographical patterns. The results indicate that some robust break points associated with relocations can be detected, the inhomogeneities are removed by both the MASH and RHtest method, and the data quality is improved in both homogenized datasets. However, the differences between CHTM3.0 and CHHTD1.0 are notable. By and large, in CHHTD1.0, the break points detected are fewer, but the adjustments for inhomogeneities and the resultant changes of linear trend estimates are larger. In contrast, CHTM3.0 provides more reasonable geographical patterns of long-term climate trends over the region. The reasons for the differences between the datasets include: (1) different algorithms for creating reference series for adjusting the candidate series—more neighboring stations used in MASH and hence larger-scale regional signals retained; (2) different algorithms for calculating the adjustments—larger adjustments in RHtest in general, partly due to the individual local reference information used; and (3) different rules for judging inhomogeneity—all detected break points are adjusted in CHTM3.0, based on MASH, while a number of break points detected via RHtest but without supporting metadata are overlooked in CHHTD1.0. The present results suggest that CHTM3.0 is more suitable for analyses of large-scale climate change in China, while CHHTD1.0 contains more original information regarding station temperature records.     

Precipitation extremes in the Yangtze River Basin,China: regional frequency and spatial–temporal patterns

Regional frequency analysis and spatial–temporal patterns of precipitation extremes are investigated based on daily precipitation data covering 1960–2009 using the index-flood L-moments method together with some advanced statistical tests and spatial analysis techniques. The results indicate that: (1) the entire Yangtze River basin can be divided into six homogeneous regions in terms of extreme daily precipitation index. Goodness-of-fit test indicates that Pearson type III (PE3, three parameters), general extreme-value (GEV, three parameters), and general normal (GNO, three parameters) perform well in fitting regional precipitation extremes; (2) the regional growth curves for each homogeneous region with 99 % error bands show that the quantile estimates are reliable enough and can be used when return periods are less than 100 years, and the results indicate that extreme precipitation events are highly probable to occur in regions V and VI, and hence higher risk of floods and droughts; and (3) spatial patterns of annual extreme daily precipitation with return period of 20 years indicate that precipitation amount increases gradually from the upper to the lower Yangtze River basin, showing higher risks of floods and droughts in the middle and lower Yangtze River basin, and this result is in good agreement with those derived from regional growth curves.     

Changes in the Proportion of Precipitation Occurring as Rain in Northern Canada during Spring–Summer from 1979–2015

Changes in the form of precipitation have a considerable impact on the Arctic cryosphere and ecological system by influencing the energy balance and surface runoff. In this study, station observations and ERA-Interim data were used to analyze changes in the rainfall to precipitation ratio(RPR) in northern Canada during the spring–summer season(March–July)from 1979–2015. Our results indicate that ERA-Interim describes the spring–summer variations and trends in temperature and the RPR well. Both the spring–summer mean temperature [0.4℃–1℃(10 yr)~(-1)] and the RPR [2%–6%(10 yr)~(-1)] increased significantly in the Canadian Arctic Archipelago from 1979–2015. Moreover, we suggest that, aside from the contribution of climate warming, the North Atlantic Oscillation is probably another key factor influencing temporal and spatial differences in the RPR over northern Canada.