Extreme climate events over northern China during the last 50 years

Climate extremes for agriculture-pasture transitional zone, northern China, are analyzed on the basis of daily mean temperature and precipitation observations for 31 stations in the period 1956-2001. Analysis season for precipitation is May-September, i.e., the rainy season. For temperature is the hottest three months, i.e., June through August. Heavy rain events, defined as those with daily precipitation equal to or larger than 50 mm, show no significant secular trend. A jump-like change, however, is found occurring in about 1980. For the period 1980-1993, the frequency of heavy rain events is significantly lower than the previous periods. Simultaneously, the occurring time of heavy rains expanded, commencing about one month early and ending one month later. Long dry spells are defined as those with longer than 10 days without rainfall. The frequency of long dry spells displays a significant (at the 99% confidence level) trend at the value of +8.3%/10a. That may be one of the major causes of the frequent droughts emerging over northern China during the last decades. Extremely hot and low temperature events are defined as the uppermost 10% daily temperatures and the lowest 10% daily temperatures, respectively. There is a weak and non-significant upward trend in frequency of extremely high temperatures from the 1950s to the mid-1990s. But the number of hot events increases as much as twice since 1997. That coincides well with the sudden rise in mean summer temperature for the same period. Contrary to that, the frequency of low temperature events have been decreasing steadily since the 1950s, with a significant linear trend of -15%/10a.     

Estimating Sea-Level Allowances for Atlantic Canada using the Fifth Assessment Report of the IPCC

Abstract

Sea-level allowances at 22 tide-gauge sites along the east coast of Canada are determined based on projections of regional sea-level rise for the Representative Concentration Pathway 8.5 (RCP8.5) from the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5) and on the statistics of historical tides and storm surges (storm tides). The allowances, which may be used for coastal infrastructure planning, increase with time during the twenty-first century through a combination of mean sea-level rise and the increased uncertainty of future projections with time. The allowances show significant spatial variation, mainly a consequence of strong regionally varying relative sea-level change as a result of glacial isostatic adjustment (GIA). A methodology is described for replacement of the GIA component of the AR5 projection with global positioning system (GPS) measurements of vertical crustal motion; this significantly decreases allowances in regions where the uncertainty of the GIA models is large. For RCP8.5 with GPS data incorporated and for the 1995–2100 period, the sea-level allowances range from about 0.5?m along the north shore of the Gulf of St. Lawrence to more than 1?m along the coast of Nova Scotia and southern Newfoundland.     

Changes in Daily Climate Extremes of Observed Temperature and Precipitation in China

Daily precipitation for 1960–2011 and maximum/minimum temperature extremes for 1960–2008 recorded at 549 stations in China are utilized to investigate climate extreme variations.A set of indices is derived and analyzed with a main focus on the trends and variabilities of daily extreme occurrences.Results show significant increases in daily extreme warm temperatures and decreases in daily extreme cold temperatures,defined as the number of days in which daily maximum temperature(Tmax)and daily minimum temperature(Tmin)are greater than the 90th percentile and less than the10th percentile,respectively.Generally,the trend magnitudes are larger in indices derived from Tmin than those from Tmax.Trends of percentile-based precipitation indices show distinct spatial patterns with increases in heavy precipitation events,defined as the top 95th percentile of daily precipitation,in western and northeastern China and in the low reaches of the Yangtze River basin region,and slight decreases in other areas.Light precipitation,defined as the tail of the5th percentile of daily precipitation,however,decreases in most areas.The annual maximum consecutive dry days(CDD)show an increasing trend in southern China and the middle-low reach of the Yellow River basin,while the annual maximum consecutive wet days(CWD)displays a downtrend over most regions except western China.These indices vary significantly with regions and seasons.Overall,occurrences of extreme events in China are more frequent,particularly the night time extreme temperature,and landmasses in China become warmer and wetter.     

基于统计降尺度模型的江淮流域极端气候的模拟与预估

利用江淮流域29个代表站点1961--2000年逐日最高温度、最低温度和逐日降水资料,以及NCEP逐日大尺度环流场资料,引入基于多元线性回归与随机天气发生器相结合的统计降尺度模型SDSM（statistical downscalingmodel）,通过对每个站点建模,确立SDSM参数,并将该模型应用于SRESA2排放情景下HadCM3和cGcM3模式,得到了江淮流域各代表台站21世纪的逐日最高、最低温度和降水序列以及热浪、霜冻、强降水等极端气候指数。结果表明,当前气候下,统计降尺度方法模拟的极端温度指数与观测值有很好的一致性,能有效纠正耦合模式的“冷偏差”,如SDSM对江淮平均的冬季最高、最低温度的模拟偏差较CGCM3模式分别减少3℃和4．5℃。对于极端降水则能显著纠正耦合模式模拟的降水强度偏低的问题,如CGCM3对江淮流域夏季降水强度的模拟偏差为-60．6％,但降尺度后SDSM—CGCM3的偏差仅为-6％,说明降尺度模型SDSM的确有“增加值”的作用。21世纪末期在未来SRESA2情景下,对于极端温度,无论Had．CM3还是CGCM3模式驱动统计模型,江淮流域所有代表台站,各个季节的最高、最低温度都显著增加,且以夏季最为显著,增幅在2—4℃;与之相应霜冻天数将大幅减少,热浪天数大幅增多,各站点冬季霜冻天数减少幅度为5—25d,夏季热浪天数增加幅度为4～14d;对于极端降水指数,在两个不同耦合模式HadCM3和CGCM3驱动下的变化尤其是变化幅度的一致性比温度差,但大部分站点各个季节极端强降水事件将增多,强度增强,SDSM—HadCM3和SDSM-CGCM3预估的夏季极端降水贡献率将分别增加26％和27％。     

IPCC AR6报告解读：极端天气气候事件变化

与IPCC第五次评估报告（AR5）相比,在第六次评估报告（AR6）评估中,观测的极端天气气候事件变化证据,特别是归因于人为影响的证据加强。人类活动造成的气候变化已影响到全球每个区域的许多极端天气气候事件。随着未来全球变暖进一步加剧,预估极端热事件、强降水、农业生态干旱的强度和频次以及强台风（飓风）比例等将增加,越罕见的极端天气气候事件,其发生频率的增长百分比越大。这些结论再次凸显了应对气候变化和极端天气气候事件的必要性和紧迫性。     

Tracking climate change in Central Asia through temperature and precipitation extremes

Journal of Geographical Sciences - Under the impacts of climate change and human activities, great uncertainties still exist in the response of climate extremes, especially in Central Asia (CA). In...     

海河流域近60 a降水极值的频率分析及时空分布特征

以海河流域为研究区域,利用MK和F检验对站点的年最大日降雨序列进行趋势、突变和跳跃分析。基于水文气象分区线性矩法进行一致区的划分、最优分布的选择和降水极值的频率估计值计算,并分析其空间分布特征。结果表明:MK趋势和突变检验显示只有8个站点(22.9%)呈现显著下降趋势,通过了信度为0.1的显著性水平检验,特别是京津唐区域具有显著的下降趋势,突变时段主要发生在1980-1990年。均值和方差的跳跃性显示大部分站点都呈现出显著的向下跳跃,主要分布在流域的滦河子流域和北三河水系;趋势和跳跃的综合分析能够对降水极值有可能引起的旱涝灾害进行更全面合理的判断。不同重现期下的频率估计值的空间分布总体趋势一致,从东南到西北、从沿海到内陆逐渐减少,并与地形表现出很好的一致性;降水极值空间分布的中心主要集中在滦河子流域的遵化和青龙附近;大部分站点50 a一遇的估计值和AMP序列的最大观测值能够保持较好的一致性,间接反映了估计值的合理准确性。     

用Gumbel极值分布推算气候极值的方法

介绍了用Gumbel极值分布理论推算气候极值的矩法、Thomas曲线公式和最小二乘法。并计算多年一遇的年最高气温、年最大均风速、年最大日降雨量和年最大波高。指出,变率小的要素极值再现期短;变率大的要素极值再现期长;Thomas曲线公式的计算结果较其它两种方法接近历史实况,且计算简便。     

Uncertainty,entropy, scaling and hydrological stochastics. 1. Marginal distributional properties of hydrological processes and state scaling / Incertitude,entropie, effet d'échelle et propriétés stochastiques hydrologiques. 1. Propriétés distributionnelles marginales des processus hydrologiques et échelle d'état

Abstract

The well-established physical and mathematical principle of maximum entropy (ME), is used to explain the distributional and autocorrelation properties of hydrological processes, including the scaling behaviour both in state and in time. In this context, maximum entropy is interpreted as maximum uncertainty. The conditions used for the maximization of entropy are as simple as possible, i.e. that hydrological processes are non-negative with specified coefficients of variation (CV) and lag one autocorrelation. In this first part of the study, the marginal distributional properties of hydrological variables and the state scaling behaviour are investigated. Application of the ME principle under these very simple conditions results in the truncated normal distribution for small values of CV and in a nonexponential type (Pareto) distribution for high values of CV. In addition, the normal and the exponential distributions appear as limiting cases of these two distributions. Testing of these theoretical results with numerous hydrological data sets on several scales validates the applicability of the ME principle, thus emphasizing the dominance of uncertainty in hydrological processes. Both theoretical and empirical results show that the state scaling is only an approximation for the high return periods, which is merely valid when processes have high variation on small time scales. In other cases the normal distributional behaviour, which does not have state scaling properties, is a more appropriate approximation. Interestingly however, as discussed in the second part of the study, the normal distribution combined with positive autocorrelation of a process, results in time scaling behaviour due to the ME principle.     

Approaches to analyse and model changes in impacts: reply to discussions of “How to improve attribution of changes in drought and flood impacts”*

ABSTRACT

We thank the authors, Brunella Bonaccorso and Karsten Arnbjerg-Nielsen for their constructive contributions to the discussion about the attribution of changes in drought and flood impacts. We appreciate that they support our opinion, but in particular their additional new ideas on how to better understand changes in impacts. It is great that they challenge us to think a step further on how to foster the collection of long time series of data and how to use these to model and project changes. Here, we elaborate on the possibility to collect time series of data on hazard, exposure, vulnerability and impacts and how these could be used to improve e.g. socio-hydrological models for the development of future risk scenarios.