Trends In Extreme Temperature Indices Research Articles

Spatiotemporal Trends of Extreme Temperature Events Along the Qinghai‐Tibet Plateau Transportation Corridor From 1981 to 2019 Based on Estimated Near‐Surface Air Temperature

AbstractThe intensification of global warming leads to the increased frequency of extreme temperature events. Many studies have reported on numerous regions facing extreme hot and cold temperatures to some degree. In this study, the daily maximum, minimum and mean near‐surface air temperatures were estimated to explore the detailed spatial trends of extreme temperature events along the Qinghai‐Tibet Plateau Transportation Corridor (QTPTC). Sixteen extreme temperature indices were used to represent extreme temperature events, and the Mann‐Kendall trend test and Sen's slope estimation method were employed to explore the spatiotemporal trends of extreme temperatures along the QTPTC during 1981–2019. The possible factors that affect the trends of extreme temperature events were also discussed, indicating that: (a) There was an exacerbation of extreme hot events, while the prevalence of extreme cold events weakened along the QTPTC. This was in accordance with the trend of global warming. (b) The trends of extreme temperature indices based on daily minimum temperature were stronger than those based on daily maximum temperature in most areas, except for the eastern region. Furthermore, as altitude increased, the amplitude of warming intensified. (c) Unlike the trend in most areas, the intensified warming trend occurred in the low‐altitude areas in the eastern region where there are more human activities and rapid urbanization, and the daily maximum temperature trend was more severe there. The results can provide references for policymakers to formulate corresponding adaptation strategies, addressing the impacts of extreme temperature events on transportation facilities with significant elevation differences.

Analysis of trends in extreme temperature indices over selected areas in Peninsular Malaysia from 1991-2020

This study investigates the temporal variations of extreme temperature trends across three stations in Peninsular Malaysia with different settings, Petaling Jaya represents urban station, while Kluang and Batu Embun represent rural areas from 1991-2020. Eleven extreme warm and cold indices trends were analysed using the Mann-Kendall test, with Sen’s slope as a magnitude estimator. The findings revealed that the annual daily mean temperature, daily mean maximum temperature, and daily mean minimum temperature increased significantly at all stations by 0.04°C yr–1, 0.02°C yr–1, and 0.05°C yr–1, respectively. The station in the rural area shows a significant increment of an average of 0.03°C yr–1 for mean and warm extreme indices. Despite that, there were no changes in the total number of warm days and nights and cold days and nights for all settings. For the cold temperature indices, there were significant decreasing trends for the annual minimum of maximum temperature in rural areas, while urban station did not exhibit changes. All stations also exhibit similar annual patterns when compared although significantly higher readings were observed during El Niño events.

Early 21st Century Trends of Temperature Extremes over the Northwest Himalayas

The rising intensity and frequency of extreme temperature events are caused due to climate change and are likely to affect the entire world. In this context, the Himalayas are reported to be very sensitive to changes in temperature extremes. In this study, we investigate the variability of temperature extremes over the Northwest Himalayas in the early 21st century (2000–2018). Here, we used 14 temperature indices recommended by ETCCDI (Expert Team on Climate Change Detection and Indices). The present study reveals the trends of extreme temperature indices on the spatial scale for the western part of the Northwest Himalayas. The 14 temperature indices were used to assess the behavior of extreme temperature trends with their significance. This study reports that the northwestern region of the study area has a cooling effect due to an increase in the trends of cold spells, cold days/nights, and frost days, while the southwestern region significantly shows the warming effects due to the increasing trends in warm spells, warm days/nights, and summer days. On the other hand, the eastern region of the study area shows mixed behavior, i.e., some places show warm effects while some reveal cold effects in the early 21st century. Overall, this study implies the northwestern parts have cooling trends while the southwestern and southeastern parts have warming trends during the early 21st century.

Trends in extreme temperature indices over Lagos, Nigeria

There is the need to understand the trend and impact of extreme temperature on coastal cities because they are generally susceptible to extreme precipitation events. This study explores the trend in extreme temperature for Lagos State, Nigeria. The indices for daily minimum and maximum temperature data was calculated for the period 1991–2015 using the RClimDex software. The result showed that both minimum value of daily minimum temperature (TNn) and cool days (TX10p) showed negative trends among the indices considered. Significant trends were observed in warm nights (TN90p), warm days (TX90p) and mean of maximum temperature (Tmax-mean). Warm nights were found to be increasing while cold nights are either unchanged or decreasing. This study reveals that there are evidences of increase in warming of Lagos State.

Possible impacts of geographical factors on long-term trends of extreme temperature indices over northern Xinjiang, China

Possible impacts of geographical factors on long-term trends of extreme temperature indices over northern Xinjiang, China

Observed trends in daily temperature extreme indices in Aguascalientes, Mexico

Climate change is a pernicious and irrefutable reality. The objective of this work was to analyze trends in extreme temperature indices in Aguascalientes. With RClimdex 1.0 and data on daily maximum (Tmax) and minimum temperature (Tmin), 16 temperature indices were calculated. The trend in indices was determined with the non-parametric Mann-Kendall test (p ≤ 0.05), while the rate of change was obtained with Theil-Sen’s trend estimator. Significant positive trends were observed in 72 time series of indices associated with Tmax and in 39 time series of indices associated with Tmin. Significant negative trends were observed in 22 time series of indices associated with Tmax, and in 45 time series of indices associated with Tmin. In some regions of Aguascalientes, diurnal warming is occurring; in others, warmer or less cold nights prevail. The changes in extreme temperature indices might have severe implications in the use of irrigation water, cause physiological stress in crops, promote respiratory and cardiac diseases, and improve the reproduction cycles and populations of insects. Also, the fruit production, such as guava, could be affected under the reduction of minimum temperature, and the increase in warm days where other fruit trees are cultivated can intensify the use of chemical compensators of cold. These results are of significance for long-term economic planning and design of strategies of adaptation/mitigation to climate change. In Aguascalientes, the changes observed in extreme temperature indices could be due to climate change of a bigger scale, either regional or at the watershed level.

Trends in Thailand’s Extreme Temperature Indices during 1955-2018 and Their Relationship with Global Mean Temperature Change

Trends in Thailand’s extreme temperature indices and their relationship with global mean temperature (GMT) change are analyzed, based on longer quality controlled temperature data during 1955–2018. Widespread significant trends of extreme temperature indices with a clear warming evident in all indices are observed, consistent with the earlier results and general global warming. Changes associated with the upper tails of the minimum and maximum temperature distributions are the dominant feature of Thailand’s extreme temperature indices accounting for more than 65% of the total variance. Analysis of the probability distribution functions (PDFs) of combined extreme temperature indices further shows significant shifts in their distributions toward warmer conditions in the recent decades. The results suggest that daytime and nighttime temperatures in Thailand have become more extreme and that the changes are related to shifts in multiple aspects of the daily temperature distributions. With long-term temperature records, this study provides more confident and robust evidence of trends in Thailand’s temperature extremes occurred since the second half of 20th century. Another noteworthy finding is that most of Thailand’s extreme temperature indices show a distinct linear relationship with GMT, indicating that local-scale changes in temperatures and its extreme at local scale are related almost linearly to GMT change. The extrapolated values of the indices with strong linearity with GMT show substantial distinction with nearly 50% increase between 2 global warming levels set by Paris Agreement, highlighting that half a degree increase in GMT will lead to greatly increase in Thailand’s temperature extremes.

Spatiotemporal Patterns of Extreme Temperature across the Huai River Basin, China, during 1961–2014, and Regional Responses to Global Changes

Global warming and its relevant effects have aroused increasing human concerns in recent decades. These anomalies are likely influencing vegetation dynamics and ecosystem stability. This paper aims to dissect extreme temperature variations in both space and time, and related regional responses to global warming in the Huai River Basin. Using the daily maximum and minimum air temperature at 153 stations across the Huai River Basin, China, covering the period of 1961–2014, trends and relations amongst extreme air temperature indices were analyzed, and regional responses of the Huai River Basin to global warming process were also investigated. The results indicated that: (1) widespread increasing trends can be observed in maximum and minimum air temperature, with the largest increasing magnitude of 0.4 °C per decade and 1.3 °C per decade, respectively. The minimum air temperature regimes have a larger increasing magnitude than the maximum air temperatures. (2) There is an increasing trend in the extreme maximum temperature indices, and the increasing rates of TN90p and TR20 are greater than those of the other extreme maximum temperature indices. However, the extreme minimum temperature indices, except for consecutive icy days (CID), show significant decreasing trends. The growing season length (GSL) would increase due to the joint action of (i) an increase in maximum temperature indices, and (ii) a decrease in minimum temperatures indices. Although increases in the GSL would be beneficial for increasing the growing time of crops, a decreased extreme minimum temperature and increased extreme maximum temperature may reduce the winter wheat yield. (3) Extreme low temperature indices show a larger changing magnitude than the extreme high temperature indices. Temporally, a larger changing magnitude can be identified for temperature indices during night-time than during daytime. Moreover, a larger changing magnitude and higher significance of trends of extreme temperature indices can be observed in the eastern Huai River Basin than in the western Huai River Basin. Particularly, we detect an even higher changing rate of extreme temperature indices in the southeastern Huai River Basin. These findings can be well explained by urban heat island effects resulting from urban aggregation across the Yangtze Delta. (4) The correlation between the extreme low temperature indices is slightly higher than that of the extreme high temperature indices. The changing trends of the most extreme temperature indices are closely related to latitude and altitude. Trends in the main extreme temperature indices of the Huai River Basin are essentially similar to those in other regions around the world, implying consistent spatial patterns of extreme temperature indices across the globe.

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.

Contribution of urbanization to the increase of extreme heat events in an urban agglomeration in east China

AbstractThe urban agglomeration of Yangtze River Delta (YRD) is emblematic of China's rapid urbanization during the past decades. Based on homogenized daily maximum and minimum temperature data, the contributions of urbanization to trends of summer extreme temperature indices (ETIs) in YRD are evaluated. Dynamically classifying the observational stations into urban and rural, this study presents unexplored changes in temperature extremes during the past four decades in YRD and quantifies the amplification of the positive trends in ETIs by the urban heat island effect. Overall, urbanization contributes to more than one third of the increase of intensity of extreme heat events in the region, which is comparable to the contribution of greenhouse gases. Compared to rural stations, more notable shifts to the right in the probability distribution of temperature and ETIs are found in urban stations. The rapid urbanization in YRD has resulted in large increases in the risk of heat extremes.

Spatial and temporal analysis of trends in extreme temperature indices in Iran over the period 1960–2014

ABSTRACTThe recent years have witnessed a rapid increase in frequency, severity, duration and geographical extent of extreme weather events. Having an area of 1 648 195 km2, Iran spans over a wide latitudinal range and enjoys a diverse terrain in terms of topography and elevation. The combination of this topographic complexity with the effects of extensive water bodies in the north and the south plays a major role in the distribution of temperature over this country. This study analysed the temporal trend of extreme temperature indices observed in 33 synoptic stations across Iran over the period 1960–2014, and then examined their relationship with elevation and latitude. The results showed a significant warming trend in extreme temperature indices of many stations, especially the indices that are based on daily minimum temperature. At low elevations, the trends of indices exhibited the features of a warming climate, but at higher elevations, these indices showed a mixture of positive and negative trends. Examining the relationship between the trends of indices and elevation showed that in the altitudinal band E1 [elevations lower than 23 m above sea level (ASL)], only the trend of growing season length is correlated with elevation; but in the altitudinal band E2 (elevations higher than 700 m ASL), elevation exhibited significant correlation with the trends of percentage of cool nights, frequency of frost days, diurnal temperature range, cold spell duration, percentage of warm nights and frequency of tropical nights. The analysis did not show any meaningful relationship between extreme temperature indices trends with latitude. Considering the high heterogeneity of the trends of indices and the limited number of stations with sufficient data, generalizing the results and predicting the wider trend patterns require further studies using a denser network of stations.

Recent trends of extreme temperature indices for the Iberian Peninsula

Climate change and extreme climate events have a significant impact on societies and ecosystems. As a result, climate change projections, especially related with extreme temperature events, have gained increasing importance due to their impacts on the well-being of the population and ecosystems. However, most studies in the field are based on coarse global climate models (GCMs). In this study, we perform a high resolution downscaling simulation to evaluate recent trends of extreme temperature indices. The model used was Weather Research and Forecast (WRF) forced by MPI-ESM-LR, which has been shown to be one of the more robust models to simulate European climate. The domain used in the simulations includes the Iberian Peninsula and the simulation covers the 1986–2005 period (i.e. recent past). In order to study extreme temperature events, trends were computed using the Theil-Sen method for a set of temperature indexes defined by the Expert Team on Climate Change Detection and Indices (ETCCDI). For this, daily values of minimum and maximum temperatures were used. The trends of the indexes were computed for annual and seasonal values and the Mann-Kendall Trend test was used to evaluate their statistical significance. In order to validate the results, a second simulation, in which WRF was forced by ERA-Interim, was performed. The results suggest an increase in the number of warm days and warm nights, especially during summer and negative trends for cold nights and cold days for the summer and spring. For the winter, contrary to the expected, the results suggest an increase in cold days and cold nights (warming hiatus). This behavior is supported by the WRF simulation forced by ERA-Interim for the autumn days, pointing to an extension of the warming hiatus phenomenon to the remaining seasons. These results should be used with caution since the period used to calculate the trends may not be long enough for this purpose. However, the general sign of trends are similar for both simulations despite some differences in their magnitudes.

Trends in extreme temperature over Nigeria from percentile‐based threshold indices

ABSTRACTThis study analyses spatial and temporal trends in extreme temperature indices over Nigeria. The percentile indices were calculated from newly homogenized daily minimum and maximum temperature data for the period 1971–2012 for 21 stations in Nigeria. Indices describing the characteristics of hot extremes and cold extremes are calculated with the RClimDex software. The annual and seasonal trends in these indices are obtained using the ordinary least square fit and the statistical significance tested using the R‐based modified Mann–Kendall test. We examine characteristics of these indices for the entire country and separately for the three geographical zones in Nigeria: Guinea, Savanna, and Sahel. The spatial and temporal patterns of trends in the indices indicate that Nigeria has experienced statistically significant increase in the frequency of hot extreme and decrease in cold extreme events. Although majority of the stations have significant trends in warm days and warm nights, the annual trend is greatest in warm nights. In addition, the rate of warming in minimum temperature (‘warm nights’) is stronger in June, July, August (JJA) and September, October, November (SON) compare with December, January, February (DJF) and March, April, May (MAM). As for the trends in cold days and cold nights, the trends in cold nights are larger than for cold days at both the annual and seasonal scales. The regional analysis indicates that trends in warm nights and cold nights are most pronounced in Guinea and Sahel regions.

Quantile Trends in Temperature Extremes in China

AbstractA number of recent studies have examined trends in extreme temperature indices using a linear regression model based on ordinary least-squares. In this study, quantile regression was, for the first time, applied to examine the trends not only in the mean but also in all parts of the distribution of several extreme temperature indices in China for the period 1960–2008. For China as a whole, the slopes in almost all the quantiles of the distribution showed a notable increase in the numbers of warm days and warm nights, and a significant decrease in the number of cool nights. These changes became much faster as the quantile increased. However, although the number of cool days exhibited a significant decrease in the mean trend estimated by classical linear regression, there was no obvious trend in the upper and lower quantiles. This finding suggests that examining the trends in different parts of the distribution of the time-series is of great importance. The spatial distribution of the trend in the 9...

Analysis and Comparison of Trends in Extreme Temperature Indices in Riyadh City, Kingdom of Saudi Arabia, 1985–2010

This study employed the time series of thirteen extreme temperature indices over the period 1985–2010 to analyze and compare temporal trends at two weather stations in Riyadh city, Saudi Arabia. The trend analysis showed warming of the local air for the city. Significant increasing trends were found in annual average maximum and minimum temperatures, maximum of minimum temperature, warm nights, and warm days for an urban and a rural station. Significant decreasing trends were detected in the number of cool nights and cool days at both stations. Comparison of the trends suggests that, in general, the station closer to the city center warmed at a slower rate than the rural station. Significant differences were found in a lot of the extreme temperature indices, suggesting that urbanization and other factors may have had negative effects on the rate of warming at the urban station.

Trends in extreme temperature indices in the Poyang Lake Basin, China

Based on daily maximum and minimum temperature records at 78 meteorological stations in the Basin of China’s largest fresh water lake (Poyang Lake Basin), the temporal and spatial variability of 11 extreme temperature indices are investigated for the period 1959–2010. The analysis indicates that the annual mean of daily minimum temperature (Tmin) has increased significantly, while no significant trends were observed in the annual mean of daily maximum temperature (Tmax), resulting in a significant decrease in the diurnal temperature range. Trends and percentages of stations with significant trends in Tmin-related indices are generally stronger and higher than those in Tmax-related indices; however, no significant trends can be found in Tmax-related indices (TXMean, TX90p, TXx and TX10p) at both seasonal and annual time scale. Low correlations with Global-SST ENSO index are also detected in Tmax-related indices. Significant positive relationships can be found in Tmin-related indices (TNMean, TNx, TNn and TN90p), however, the most significant negative coefficient was also found in cold nights (TN10p) with the Global-SST ENSO index. Singular value decomposition (SVD) correlating extreme temperatures over the Poyang Lake Basin and the North Pacific SST indicates the East China Sea, Western Pacific and Bering Sea to be stronger linked with Tmin than Tmax with the first mode (SVD-1) explaining 90 and 94 % of annual Tmax and Tmin respectively.

Urbanization Effect on Trends of Extreme Temperature Indices of National Stations over Mainland China, 1961–2008

Abstract Understanding the long-term change of extreme temperature events is important to the detection and attribution of climate change. It is unclear, however, how much effect urbanization has had on trends of the extreme temperature indices series constructed based on the commonly used datasets on a subcontinental scale. Applying a homogenized daily temperature dataset of the national reference climate stations and basic meteorological stations, and a rural station network previously developed, urbanization effects on trends of extreme temperature indices in mainland China for the time period 1961–2008 are evaluated. It is found that 1) the country-averaged annual- and seasonal-mean extreme temperature indices series generally experience statistically significant trends; 2) annual-mean urbanization effects in the country as a whole are statistically significant for daily minimum temperature (Tmin), maximum temperature (Tmax), and mean temperature of Tmin and Tmax (Tavg), reaching 0.070°, 0.023°, and 0.047°C (10 yr)−1, respectively, with the largest values for annual-mean Tmin occurring in north China; 3) annual- and seasonal-mean urbanization effects for the declining diurnal temperature range (DTR) are highly significant, and the largest seasonal-mean DTR decline because of urbanization occurs in winter and spring; 4) annual-mean urbanization effects for the lowest Tmin, summer days, tropical nights, and frost days series are significant, but an insignificant urbanization effect is detected for icing days series; 5) urbanization has led to a highly significant decline of annual cold nights at a rate of −1.485 days (10 yr)−1 and a highly significant increase of annual warm nights at a rate of 2.264 days (10 yr)−1. Although urbanization effects are also significant for cold days and warm days, they are relatively smaller, and 6) the smallest absolute values of annual-mean urbanization effects for most of the indices series are found to dominantly appear during 1966–76, a well-known deurbanization period resulting from the Cultural Revolution.

Urbanization effect on long-term trends of extreme temperature indices at Shijiazhuang station, North China

Based on daily temperature data from an urban station and four rural stations of Shijiazhuang area in Hebei Province, North China, we analyzed the trends of extreme temperature indices series of the urban station (Shijiazhuang station) and rural stations during 1962–2011 and the urbanization effect on the extreme temperature indices of the urban station. The results showed that the trends of annual extreme temperature indices of the urban station and the rural stations are significantly different in the recent 50 years. Urbanization effect on the long-term trends of hot days, cold days, frost days, diurnal temperature range (DTR), extreme maximum temperature, and extreme minimum temperature at the urban station were all statistically significant, reaching 1.10 days/10 years, −2.30 days/10 years, −2.55 days/10 years, −0.20 °C/10 years, 0.16 °C/10 years, and 0.70 °C/10 years, respectively, with the urbanization contributions to the overall trends reaching 100, 38.0, 42.2, 40.0, 94.1, and 47.0 %, respectively. The urbanization effect on trend of ice days was also significant, reaching −0.47 days/10 years. However, no significant urbanization effect on trends of minimum values of maximum temperature and maximum values of minimum temperature had been detected. The urbanization effects in the DTR and extreme minimum temperature series of Shijiazhuang station in wintertime were highly significant.

Homogenization of Chinese daily surface air temperatures and analysis of trends in the extreme temperature indices

This study first homogenizes time series of daily maximum and minimum temperatures recorded at 825 stations in China over the period from 1951 to 2010, using both metadata and the penalized maximum t test with the first‐order autocorrelation being accounted for to detect change points and using the quantile‐matching algorithm to adjust the data time series to diminish discontinuities. Station relocation was found to be the main cause for discontinuities, followed by station automation. The effects of discontinuities on estimation of long‐term trends in the annual mean and extreme indices of temperature are illustrated. The data homogenization is shown to have improved the spatial consistency of estimated trends. Using the homogenized daily minimum and daily maximum temperature data, this study also analyzes trends in extreme temperature indices. The results show that the vast majority (85%–90%) of the 825 sites have experienced significantly more warm nights and less cold nights since 1951. There have also been more warm days and less cold days since 1951, although these trends are less extensive. About 62% of the 825 sites were found to have experienced significantly more warm days and about 50% significantly less cold days. None of the 825 sites were found to have significantly more cold nights/days or less warm nights/days. These indicate that the warming is stronger in nighttime than in daytime and stronger in winter than in summer. Thus, the diurnal temperature range was found to have significantly decreased at 49% of the 825 sites, with significant increases being identified only at 3% of these sites.

Trends in extreme temperature indices in Austria based on a new homogenised dataset

AbstractInstrumental time series are often affected by inhomogeneities which can mask or amplify climate change signals. Various procedures for the detection and adjustment of breaks exist for monthly and annual time series. Homogenization methods on a daily basis are scarce and often disregard uncertainties accompanying the break adjustment. We present a complete homogenization procedure for daily extreme temperature series based on the break detection method PRODIGE and SPLIDHOM for break correction. Both parts of the homogenization rely on the existence of highly correlated reference stations. After the statistical comparison with neighbouring stations, detected breaks are verified and further localized by metadata. Uncertainties of the break adjustments are estimated by altering reference stations and by applying a bootstrapping technique providing an objective indication about the reliability of the homogenization.The method was tested and applied to 71 time series of daily minimum (TN) and maximum temperatures (TX) in Austria covering the period 1948–2009. For some series homogenization was not possible due to large uncertainties in the adjustments or a lack of suitable reference series. In the remaining 57 TN and 54 TX series a total number of 139 breaks were detected. Seventy‐five percent of those breaks are documented in the metadata archive, with most of them being caused by station relocations and instrumentation changes. In general, the mean over the temperature dependent adjustments of all stations show a temperature reduction. However, the majority of breaks have mean amplitudes of less than 0.5 °C. A comprehensive analysis was performed on the new homogenized daily dataset, showing a widespread warming trend in both TN and TX series. The warming trend is in general amplified due to the homogenization. However, significant changes in the trend are only observed at very few stations. In autumn, however, the trend is reversed in many temperature based ‘climate change detection indices’. Copyright © 2012 Royal Meteorological Society