Assessment of surface air warming in northeast China, with emphasis on the impacts of urbanization

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

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。     

Improved estimation of average warming trend of China from 1951–2010 based on satellite observed land-use data

This paper provides new evidence of regional warming trends from local Chinese observations covering the period 1951–2010. We used satellite-derived land data and weighted urban and rural temperature records (a weighted method) and estimate the regional warming trend, which involves natural climate change and human impact. The annual warming rate over the whole of China is 0.21?±?0.02 °C/decade. The seasonal warming is 0.30?±?0.05 °C/decade (Winter), 0.24 °C?±?0.03 °C/decade (Spring); 0.16?±?0.02 °C/decade (Summer) and 0.21?±?0.03 °C/decade (Autumn). The mean warming trend is lower than previous estimates (e.g. NMIC, CRU-China) using un-weighted methods (arithmetic average of all records). The warming difference between the weighted and un-weighted accounts for 27 % (12 %) of the NMIC (CRU-China) un-weighted estimate on the total warming. This indicates that previous estimations overestimated a regional warming trend. The differences can be partly attributed to the weighting of the urban effect which is taken into consideration in this study, resulting in a much slower temperature increase. Spatially, the northern part of China shows a larger difference than the south especially for winter and spring. We argue that it is of importance to take into consideration the influence of urban land-use change to improve the physical understanding of surface warming in China over past decades.     

Detecting climate change signals in Saudi Arabia using mean annual surface air temperatures

Climate change signals in Saudi Arabia are investigated using the surface air temperature (SAT) data of 19 meteorological stations, well distributed across the country. Analyses are performed using cumulative sum, cumulative annual mean, and the Mann–Kendall rank statistical test for the period of 1978–2010. A notable change in SAT for the majority of stations is found around 1997. The results show a negative temperature trend (cooling) for all stations during the first period (1978–1997), followed by a positive trend (warming) in the second period (1998–2010) with reference to the entire period of analysis. The Mann–Kendall test confirms that there is no abrupt cooling at any station during the analysis period, reflecting the warming trend across the country. The warming trend is found to be 0.06 °C/year, while the cooling trend is 0.03 °C/year, which are statistically significant.     

Urban heat island effect on annual mean temperature during the last 50 years in China

Summary Based on Chinas fifth population survey (2000) data and homogenized annual mean surface air temperature data, the urban heat island (UHI) effect on the warming during the last 50 years in China was analyzed in this study. In most cities with population over 10⁴, where there are national reference stations and principal stations, most of the temperature series are inevitably affected by the UHI effect. To detect the UHI effect, the annual mean surface air temperature (SAT) time series were firstly classified into 5 subregions by using Rotated Principal Components Analysis (RPCA) according to its high and low frequency climatic change features. Then the average UHI effect on each subregions regional annual mean STA was studied. Results indicate that the UHI effect on the annual mean temperatures includes three aspects: increase of the average values, decrease of variances and change of the climatic trends. The effect on the climatic trends is different from region to region. In the Yangtze River Valley and South China, the UHI effect enhances the warming trends by about 0.011°C/decade. In the other areas, such as Northeast, North-China, and Northwest, UHI has little impact on the warming trends of the regional annual temperature; while in the Southwest of China, introducing UHI stations slows down the warming trend by –0.006°C/decade. But no matter what subregion it is, the total warming/cooling of these effects is much smaller than the background change in regional temperature. The average UHI effect for the entire country, during the last 50 years is less than 0.06°C, which agrees well with the IPCC (2001). This suggests that we cannot conclude that urbanization during the last 50 years has had much obvious effect on the observed warming in China.     

北京地区城市热岛强度变化对区域温度序列的影响

通过对北京地区20个台站1961~2000年月平均温度资料的对比分析,证实热岛效应对城市气象站记录的地表平均气温的绝对影响随时间显著增大,近20 a尤为突出,但其相对影响即热岛增温对全部增暖的贡献却呈下降趋势。近40 a来,北京地区的国家基本、基准站平均温度距平序列与被认为不受城市热岛影响的郊区站平均温度距平序列差异明显,由于热岛效应加强因素引起的国家基本、基准站平均年温度变化速率为0.16℃/(10 a),对整个时期全部增温的贡献达到71%;近20 a来热岛效应加强因素使北京地区国家基本、基准站年平均温度每10 a增暖0.33℃,对该时期全部增温的贡献达到49%。城市热岛效应加强因素对国家基本、基准站季节平均温度上升的贡献在夏、秋季高,冬季最小。本文的结果说明,目前根据国家基本、基准站资料建立的全国或较大区域平均温度序列可能在很大程度上保留着城市化的影响,有必要做进一步的检验和订正。     

1960-2009年咸宁市气候变化特征分析

利用1960-2009年咸宁市3个地面气象站气象资料,统计分析近50 a来该区域气温、降水等主要气候要素的年变化、四季变化及年代际变化的趋势特征。结果表明：近50 a研究区气温有上升趋势,气候倾向率为0.23℃/10a,年平均气温在20世纪90年代末发生突变。春秋季平均气温分别在2002年和1999年发生突变,夏季平均气温在2006年发生突变,冬季平均气温早在1990年发生突变。春季与秋季平均气温的变化比较一致,冬季平均气温对全球变暖响应最敏感,春秋与秋季对气候变暖的响应是比较敏感,而夏季对气候变暖的响应最为迟缓。近50 a年降水量呈波动但无明显增降的趋势,其中春夏两季变化趋势较为一致并有下降的趋势,且春夏降水量的变化主导着年降水量的变化;而冬季降水量有上升的趋势。通过对气温与降水变化趋势的比较,发现冬季对气候变化的响应最显著、其余季节无明显相关性。     

1960—2009年咸宁市气候变化特征

利用1960—2009年咸宁市3个地面气象站气象资料,统计分析近50 a来该区域气温、降水等主要气候要素的年变化、四季变化及年代际变化的趋势特征。结果表明：近50 a研究区气温有上升趋势,气候倾向率为0.23℃/10 a,年平均气温在20世纪90年代末发生突变。春秋季平均气温分别在2002年和1999年发生突变,夏季平均气温在2006年发生突变,冬季平均气温在1990年发生突变。春季与秋季平均气温的变化较一致,冬季平均气温对全球变暖响应最敏感,春季与秋季对气候变暖的响应较敏感,而夏季对气候变暖的响应最为迟缓。近50 a咸宁市年降水量呈波动但无明显增降的趋势,其中春夏两季变化趋势较为一致并有下降的趋势,且春夏降水量的变化主导着年降水量的变化;而冬季降水量有上升的趋势。通过对气温与降水变化趋势的比较,发现冬季对气候变化的响应最显著,其余季节无明显相关性。     

城市化进程对安徽省风速的影响

利用1981-2010年安徽省61个站的逐日风速资料,结合卫星遥感台站分类方法,统计分析了城市化进程对年、季节平均风速、最大风速和小风日数的影响和贡献。结果表明：(1) 近30年安徽省年、季节平均风速和最大风速呈显著减少趋势,小风日数呈显著增加趋势。城市站的变化速率明显大于乡村站,郊区站基本介于二者之间。(2) 2000年开始安徽省城市化进程加快,导致城市站与乡村站平均风速及小风日数距平的差异有明显增大趋势。(3) 城市站与乡村站年平均风速的趋势系数之差为-0.10 (m/s) /10a,城市化对年平均风速减弱的贡献率为40.0%,春季更明显;城市站与乡村站年小风日数的趋势系数之差为15.58 d/10a,城市化对年小风日数增多的贡献率为46.9%,秋、冬季更明显;城市化对年最大风速的影响不明显。     

Variations and trends in annual and seasonal air temperatures in Greece determined from ground and satellite measurements

Summary The variations and trends in annual and seasonal air temperatures in Greece were examined on the basis of ground measurements for 25 stations during the period 1951–1993, and satellite measurements for the south eastern Mediterranean during the period 1979–1991. Data were smoothed using a 5-year running mean and were thereafter examined by regression analysis to define trends in the long duration time series. Data were also examined to detect abrupt changes and trends in the long duration annual, winter and summer series of mean maximum, mean minimum and mean temperatures. An overall cooling trend was detected for the majority of stations in winter over the entire period; the same cooling trend was also recognised for the annual and summer mean values, although a reverse warming trend was detected around the mid-70s at several stations. Satellite measurements indicate a slight warming trend, although this is not statistically significant. Considering the results of the regression analysis and the statistical tests applied to the 25 stations, it may be concluded that annual mean temperatures are dominated by an overall cooling trend, with the exception of stations in urban areas where urbanisation effects may have resulted in a warming trend. Summer temperatures, however, exhibit a warming trend roughly after 1975 at most stations.With 5 Figures     

Trend analysis of long-term temperature time series in the Greater Toronto Area (GTA)

As the majority of the world’s population is living in urban environments, there is growing interest in studying local urban climates. In this paper, for the first time, the long-term trends (31–162 years) of temperature change have been analyzed for the Greater Toronto Area (GTA). Annual and seasonal time series for a number of urban, suburban, and rural weather stations are considered. Non-parametric statistical techniques such as Mann–Kendall test and Theil-Sen slope estimation are used primarily for the assessing of the significance and detection of trends, and the sequential Mann test is used to detect any abrupt climate change. Statistically significant trends for annual mean and minimum temperatures are detected for almost all stations in the GTA. Winter is found to be the most coherent season contributing substantially to the increase in annual minimum temperature. The analyses of the abrupt changes in temperature suggest that the beginning of the increasing trend in Toronto started after the 1920s and then continued to increase to the 1960s. For all stations, there is a significant increase of annual and seasonal (particularly winter) temperatures after the 1980s. In terms of the linkage between urbanization and spatiotemporal thermal patterns, significant linear trends in annual mean and minimum temperature are detected for the period of 1878–1978 for the urban station, Toronto, while for the rural counterparts, the trends are not significant. Also, for all stations in the GTA that are situated in all directions except south of Toronto, substantial temperature change is detected for the periods of 1970–2000 and 1989–2000. It is concluded that the urbanization in the GTA has significantly contributed to the increase of the annual mean temperatures during the past three decades. In addition to urbanization, the influence of local climate, topography, and larger scale warming are incorporated in the analysis of the trends.     

资料均一化对气温变化趋势及其城市化偏差估计的影响：以北京地区为例

当前的地面气候观测资料普遍存在非气候性因素导致的非均一性,对气候变化监测和研究结论可靠性造成重要影响。结合观测台站的历史沿革数据,使用ACMANT和Pairwise Comparisons方法以及RHtest V4软件,对北京地区20个台站均一化前的月平均气温序列进行了非均一性检验和订正,最后评估了均一化对北京地区气温序列变化趋势及其城市化偏差估算的影响。结果表明：除元数据中记录的断点外,无元数据记录的断点也会对序列的趋势变化造成明显影响,其中乡村站最显著;经过订正,1958—2018年整个北京地区、乡村站以及城市站增温趋势分别为0.27℃/(10 a)、0.10℃/(10 a)和0.32℃/(10 a),较订正前分别上升了0.03℃/(10 a)、0.06℃/(10 a)和0.02℃/(10 a)。利用均一化资料估算,1958—2018年北京观象台的城市化影响为0.24℃/(10 a),城市化贡献率为70.2%,评估结果较前人结论有所降低。可见,在现有的北京地区气温资料序列中,仍可能存在较明显的非均一性和未被记录的断点,对区域平均气温趋势估算具有显著影响。     

Characterization and estimation of urban heat island at Toronto: impact of the choice of rural sites

In this study, the urban heat island of Toronto was characterized and estimated in order to examine the impact of the selection of rural sites on the estimation of urban heat island (UHI) intensity (?T _u-r). Three rural stations, King Smoke Tree (KST), Albion Hill, and Millgrove, were used for the analysis of UHI intensity for two urban stations, Toronto downtown (Toronto) and Toronto Pearson (Pearson) using data from 1970 to 2000. The UHI intensity was characterized as winter dominating and summer dominating, depending on the choice of the rural station. The analyses of annual and seasonal trends of ?T _u-r suggested that urban heat island clearly appears in winter at both Toronto and Pearson. However, due to the mitigating effect on temperature from Lake Ontario, the estimated trend of UHI intensity was found to be less at Toronto compared to that at Pearson which has no direct lake effect. In terms of the impacts of the rural stations, for both KST and Millgrove, the trends in UHI intensity were found to be statistically significant and also were in good agreement with the estimates of UHI intensities reported for other large cities in the USA. Depending on the choice of the rural station, the estimated trend for the UHI intensity at Toronto ranges from 0.01°C/decade to 0.02°C/decade, and that at Pearson ranges from 0.03°C/decade to 0.035°C/decade during 1970–2000. From the analysis of the seasonal distribution of ?T _u-r, the UHI intensity was found to be higher at Toronto in winter than that at Pearson for all three rural stations. This was likely accounted for by the lower amount of anthropogenic heat flux at Pearson. Considering the results from the statistical analysis with respect to the geographic and surface features for each rural station, KST was suggested to be a better choice to estimate UHI intensity at Toronto compared to the other rural stations. The analysis from the current study suggests that the selection of a unique urban–rural pair to estimate UHI intensity for a city like Toronto is a critical task, as it will be for any city, and it is imperative to consider some key features such as the physiography, surface characteristics of the urban and rural stations, the climatology such as the trends in annual and seasonal variation of UHI with respect to the physical characteristics of the stations, and also more importantly the objectives of a particular study in the context of UHI effect.     

城市化对华北地区最高, 最低气温和日较差变化趋势的影响

利用华北地区255个一般站和国家基本、 基准站1961\_2000年的实测资料, 经过质量检验和均一性订正后, 将所有台站根据人口和台站地理位置分为5个类别, 分析了这5个类别台站和国家基本、 基准站地面平均气温、 最高、 最低气温的年和季节变化趋势以及城市化影响。结果表明： 华北全部台站的年平均气温、 最高、 最低气温均呈增加趋势, 且以最低气温上升最为明显, 导致年平均日较差呈现明显下降。就城市化影响而言, 平均气温、 最低气温变化趋势中城市热岛效应加强因素的影响明显, 但城市化对最高气温趋势影响微弱, 个别台站和季节甚至可能造成降温。在国家基本、 基准站观测的年平均气温和年平均最低气温上升趋势中, 城市化造成的增温分别为0.11℃·(10a)-1和0.20℃·(10a)-1, 对全部增温的贡献率分别达39.3%和52.6%。各类台站的四季平均气温和最低气温序列中城市化影响均造成增温。城市化增温以冬季为最大, 夏季最小。城市化还导致乡村站以外的各类台站日较差减小, 近40年华北地区国家基本、 基准站年平均和秋、 冬季平均气温日较差明显下降均由城市化影响造成的。     

Internal variability in multidecadal trends of surface air temperature over antarctica in austral winter in model simulations

The surface air temperature (SAT) exhibits pronounced warming over West Antarctica in recent decades, especially in austral spring and winter. Using a 30-member ensemble of simulations by Community Earth System Model (CESM), two reanalysis datasets, and observed station data, this study investigates the relative contributions of internally generated low-frequency climate variability and externally forced climate change to the austral winter SAT trend in Antarctica. Although these simulations share the same external forcing, the SAT trends during 1979–2005 show large diversity among the individual members in the CESM ensemble simulations, suggesting that internally generated variability contributes a considerable part to the multidecadal SAT change in Antarctica. Quantitatively, the total forced contribution to the SAT (1979–2005) change is about 0.53 k/27 yr, and the internal variability can be strong enough to double or cancel the externally forced warming trend. A method called “dynamical adjustment” is utilized to further divide the forced response. We find both the forced thermodynamically-induced and the forced dynamically-induced SAT trends are positive over all the regions in Antarctica, with the regional mean values of 0.20 k /27 yr and 0.33 k/27 yr, respectively. The diversity of SAT trends among the simulations is closely linked to a Southern hemisphere Annular Mode (SAM)-like atmospheric circulation multidecadal change in the Southern Hemisphere. When there exists a positive–negative seesaw of pressure trend between Antarctica and the mid-latitudes, the SAT trend is positive over most of Antarctica but negative over the Antarctic Peninsula, and vice versa. The SAM-like atmospheric circulation multidecadal change mainly arises from atmospheric internal variability rather than remote tropical Sea Surface Temperature (SST).

     

Temperature projection in a tropical city using remote sensing and dynamic modeling

Recent temperature projections for urban areas have only been able to reflect the expected change due to greenhouse-induced warming, with little attempt to predict urbanisation effects. This research examines temperature changes due to both global warming and urbanisation independently and applies them differentially to urban and rural areas over a sub-tropical city, Hong Kong. The effect of global warming on temperature is estimated by regressing IPCC data from eight Global Climate Models against the background temperature recorded at a rural climate station. Results suggest a mean background temperature increase of 0.67 °C by 2039. To model temperature changes for different degrees of urbanization, long-term temperature records along with a measureable urbanisation parameter, plot ratio surrounding different automatic weather stations (AWS) were used. Models representing daytime and nighttime respectively were developed, and a logarithmic relationship between the rate of temperature change and plot ratio (degree of urbanisation) is observed. Baseline air temperature patterns over Hong Kong for 2009 were derived from two ASTER thermal satellite images, for summer daytime and nighttime respectively. Dynamic raster modeling was employed to project temperatures to 2039 in 10-year intervals on a per-pixel basis according to the degree of urbanization predicted. Daytime and nighttime temperatures in the highly urbanized areas are expected to rise by ca. 2 °C by 2039. Validation by projecting observed temperature trends at AWS, gave low average RMS errors of 0.19 °C for daytime and 0.14 °C for nighttime, and suggests the reliability of the method.     

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.     

1961—2010年德州市地温变化特征

在全球气候变暖的大背景下,研究大气下垫面的地表面温度及深层地温的变化,对工农业生产有重要意义。利用1961—2010年德州市0 cm地面温度,最高温度、地面最低温度4,0 cm和80 cm地温;1980—2010年160 cm和320 cm地温观测数据,采用最小二乘法,探讨了德州市地面及各深层地温的变化趋势特征。结果表明：地面温度及各深层地温均有增温趋势,明显增温主要出现在冬季,夏季多为降温。地面最低温度增温最显著,倾向率为0.47℃/10 a,冬季倾向率最大为0.74℃/10 a;地面最高温度增温最不显著,倾向率为0.15℃/10 a。0 cm地面温度变化倾向率为0.27℃/10 a,夏季降温为-0.04℃/10 a,冬季升温明显为0.51℃/10 a。40 cm和80 cm地温变化倾向率基本一致,明显小于地面温度升温幅度,也小于160 cm和320cm地温升温幅度。     

武汉市城市热岛强度非对称性变化

利用武汉市区气象站及其周边4个县气象站1960-2005年的气温资料,计算了46 a及分时段的季节和年平均气温、平均最高和最低气温倾向率,城市热岛强度倾向率及其贡献率。结果表明：46 a来,城区和郊区的平均气温均以上升趋势为主,最低气温增幅最大,最高气温增幅最小,甚至下降;冬季增幅最快,夏季增幅最慢,甚至下降,这是第一类非对称性。 城市热岛效应也存在增强趋势,以年平均、最低和最高气温表示的城市热岛强度倾向率分别为0.235℃/10 a、0.425℃/10 a和0.034℃/10 a,热岛效应贡献率分别达到60.4%、67.7%和21.8%,这是第二类非对称性。 46 a来的增温和城市热岛强度加强主要是最近23 a快速增温所致,进入本世纪增温进一步加剧。 摘要 计算了武汉市气象站、周边4县气象站平均的1960～2005年间以及前后两半时段四季和年平均、最高、最低气温倾向率,城市热岛强度倾向率和贡献率。结果表明：1）46年来,城区和郊区的平均气温均以增趋势为主,平均气温倾向率为正,最低气温增幅最大,最高气温增幅最小甚至下降,冬季增幅最快,夏季增幅最慢甚至下降,这是第一类非对称性;2）城市热岛效应也存在增趋势,以年平均、最低、最高气温表示的城市热岛强度倾向率分别为0.235、0.425、0.034 ℃/10a,热岛效应贡献率分别达到60.4%、67.7%、21.8%,这是第二类非对称性,3）46年来的增温和城市热岛强度加强主要是后23年快速增温所致,前23年气温变化不明显。武汉市气象站气温资料严重地保留着城市化影响,建议尽快迁站。 关键词 城市热岛强度 最高气温 最低气温 非对称性变化     

Changes in daily climate extremes in the arid area of northwestern China

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