The impact of climate change on extreme precipitation in Sicily,Italy          下载免费PDF全文

Angelo Forestieri  Elisa Arnone  Stephen Blenkinsop  Angela Candela  Hayley Fowler  Leonardo V. Noto 《水文研究》2018,32(3):332-348

Increasing precipitation extremes are one of the possible consequences of a warmer climate. These may exceed the capacity of urban drainage systems, and thus impact the urban environment. Because short‐duration precipitation events are primarily responsible for flooding in urban systems, it is important to assess the response of extreme precipitation at hourly (or sub‐hourly) scales to a warming climate. This study aims to evaluate the projected changes in extreme rainfall events across the region of Sicily (Italy) and, for two urban areas, to assess possible changes in Depth‐Duration‐Frequency (DDF) curves. We used Regional Climate Model outputs from Coordinated Regional Climate Downscaling Experiment for Europe area ensemble simulations at a ~12 km spatial resolution, for the current period and 2 future horizons under the Representative Concentration Pathways 8.5 scenario. Extreme events at the daily scale were first investigated by comparing the quantiles estimated from rain gauge observations and Regional Climate Model outputs. Second, we implemented a temporal downscaling approach to estimate rainfall for sub‐daily durations from the modelled daily precipitation, and, lastly, we analysed future projections at daily and sub‐daily scales. A frequency distribution was fitted to annual maxima time series for the sub‐daily durations to derive the DDF curves for 2 future time horizons and the 2 urban areas. The overall results showed a raising of the growth curves for the future horizons, indicating an increase in the intensity of extreme precipitation, especially for the shortest durations. The DDF curves highlight a general increase of extreme quantiles for the 2 urban areas, thus underlining the risk of failure of the existing urban drainage systems under more severe events.  相似文献   

基于CMIP5模式鄱阳湖流域未来参考作物蒸散量预估   总被引：3，自引：0，他引：3  

刘子豪  陆建忠  黄建武  陈晓玲  张玲  盛颖东 《湖泊科学》2019,31(6):1685-1697

预测未来气候情境下鄱阳湖流域参考作物蒸散量(Reference crop Evapotranspiration,ET0)的时空分布可为流域水资源的优化管理,为科学应对气候变化对农业生产的影响提供基础数据支撑.利用鄱阳湖流域14个气象站点1961-2014年逐日气象数据,采用Penman-Monteith公式计算出历史ET0;基于同期美国环境中心(NCEP)再分析数据及2006-2100年CMIP5中CNRM-CM5模式在RCP4. 5和RCP8. 5情景下的预测数据,经统计降尺度模型(statistical downscaling model,SDSM)模拟和偏差校正,预测流域未来ET0;通过Mann-Kendall检验、普通克里金插值和空间自相关法分析了流域1961-2100年ET0的时空演变特征.结果表明:NCEP再分析资料与流域ET0建立的逐步回归降尺度模型模拟效果较好,CNRMCM5模式降尺度模拟结果经偏差校正后,精度明显提高,适宜流域未来ET0的预估.鄱阳湖流域在基准期1961-2010年ET0整体上呈减小趋势,空间分布上呈南北高、中间低的特点,表现出明显的空间差异性.RCP4.5、RCP8.5情景下未来3个时期鄱阳湖流域ET0较基准期均呈不同程度的增加趋势,其空间分布整体表现为东高西低、局地略有突出;无论是在基准期或是未来情景下的3个时期,ET0均具有较强的空间自相关性.在RCP8.5情景下,鄱阳湖1961-2100年干旱指数呈现出较为明显的上升趋势,流域的干旱状况随时间加剧,2011-2100年间流域绝大部分地区由湿润区转为半湿润区,干旱指数自南向北递减,赣江流域将是鄱阳湖流域未来干旱风险的重点防范区.  相似文献   

Assessing regression‐based statistical approaches for downscaling precipitation over North America          下载免费PDF全文

Jie Chen  François P. Brissette  Robert Leconte 《水文研究》2014,28(9):3482-3504

This paper assesses linear regression‐based methods in downscaling daily precipitation from the general circulation model (GCM) scale to a regional climate model (RCM) scale (45‐ and 15‐km grids) and down to a station scale across North America. Traditional downscaling experiments (linking reanalysis/dynamical model predictors to station precipitation) as well as nontraditional experiments such as predicting dynamic model precipitation from larger‐scale dynamic model predictors or downscaling dynamic model precipitation from predictors at the same scale are conducted. The latter experiments were performed to address predictability limit and scale issues. The results showed that the downscaling of daily precipitation occurrence was rarely successful at all scales, although results did constantly improve with the increased resolution of climate models. The explained variances for downscaled precipitation amounts at the station scales were low, and they became progressively better when using predictors from a higher‐resolution climate model, thus showing a clear advantage in using predictors from RCMs driven by reanalysis at its boundaries, instead of directly using reanalysis data. The low percentage of explained variances resulted in considerable underestimation of daily precipitation mean and standard deviation. Although downscaling GCM precipitation from GCM predictors (or RCM precipitation from RCM predictors) cannot really be considered downscaling, as there is no change in scale, the exercise yields interesting information as to the limit in predictive ability at the station scale. This was especially clear at the GCM scale, where the inability of downscaling GCM precipitation from GCM predictors demonstrates that GCM precipitation‐generating processes are largely at the subgrid scale (especially so for convective events), thus indicating that downscaling precipitation at the station scale from GCM scale is unlikely to be successful. Although results became better at the RCM scale, the results indicate that, overall, regression‐based approaches did not perform well in downscaling precipitation over North America. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   

GRAPES区域集合预报两种侧边界扰动方法对比试验     

范宇恩  陈静  邓国  陈法敬  刘雪晴  徐致真 《气象》2019,45(12):1629-1641

中国气象局数值预报中心自2014年建立了区域集合预报业务系统,其使用的侧边界扰动由全球集合预报系统动力降尺度得到。为深入了解侧边界扰动对区域集合预报的影响,基于15 km水平分辨率的区域集合预报模式,使用动力降尺度方法和尺度化滞后平均法(scaled lagged average forecasting,SLAF)设计构造了两种侧边界扰动方案,并开展了2015年7月共6天的集合预报试验,利用集合均方根误差、集合离散度、连续分级概率评分、离群值、Brier Score及相对作用特征曲线面积等概率预报检验方法进行了多方面检验,分析了两种侧边界扰动方案对区域集合预报质量的影响。结果表明:动力降尺度侧边界扰动方案(DOWN)的扰动总能量在各垂直层次均大于SLAF方案,使得边界上前者的离散度大于后者,集合扰动增长更为合理;对于等压面要素和地面要素,DOWN方案的离散度、Outlier、CRPS等评分优于SLAF方案,反映了DOWN方案构造的侧边界扰动更加合理;在降水概率预报技巧方面,SLAF方案在评分上具有一定优势,但评分的提高没有通过显著性水平检验,因此认为两种方案对降水预报的改进基本相当。  相似文献   

中国中东部区域TRMM降水产品降尺度研究及其时空特征分析   总被引：1，自引：0，他引：1  

何其全  史岚  谭璐璐  万逸波  王茜雯 《气象科学》2019,39(3):312-321

该研究以中国中东部区域(17°～50°N,98°～135°E)为研究范围,在前人研究基础上,根据水汽与降水之间的关系,基于MOD05水汽产品,采用偏最小二乘法,对中国中东部区域2001—2010年10 a平均TRMM3B43_V 7月降水产品进行降尺度,旨在得到空间分辨率为1 km×1 km的月降水空间分布。通过比较分析,发现该降尺度模型能大幅提高TRMM产品空间分辨率,估算结果平均相对误差为15.35%,与地面观测较接近,能体现中国中东部区域降水宏观分布趋势,且估算结果精度高于前人基于归一化植被指数(NDVI)的降尺度模型,能满足降水产品的精细化需求。  相似文献   

未来气候情景下气候变化响应过程研究综述   总被引：7，自引：0，他引：7  

成爱芳  冯起  张健恺  李宗省  王岗 《地理科学》2015,(1)

气候变化将会对生态系统、自然资源、极端气候和人类社会产生一定的影响,科学评估未来气候变化响应是应对气候变化的前提。通过对当前研究成果的回顾,建立未来气候情景下气候变化响应研究的系统思路,并总结了研究所涉及的方法。系统论述了应用第5阶段耦合模式比较计划(CMIP5)气候模式前进行适用性评价的必要性;分析了当前降尺度方法尤其是统计降尺度的主要方法及进展;归纳了偏差校正过程中普遍使用的方法,最后,综合分析了整个研究过程中的不确定性。研究将为气候变化响应分析提供方法和思路指导。  相似文献   

黄淮地区夏季日降水分区概率预报方法研究     

赵琳娜  董航宇  吴亮  王彬雁  白雪梅  党皓飞 《气象》2015,41(12):1503-1513

利用我国黄淮地区1961—2010年50年6—8月的日降水资料,采用REOF和t检验的方法,将中国黄淮地区夏季降水分成Ⅰ—Ⅴ区。5个区域进行差异性t检验表明5个区域之间（彼此）差异显著,说明了区域划分的正确性。在此基础上利用1999—2007年6—8月站点日降水资料以及CFSv2模式后预报的日降水资料建立了5个区域内共5个代表站点的夏季日降水概率预报方程,并进行了确定性、概率性预报检验和业务试用检验。对各区域内5个代表站日降水量的确定性预报检验表明：Logistic回归降水概率预报方程的TS评分要高于CFSv2模式预报和T213的集合预报平均,空报率也低于CFSv2模式预报和T213集合预报平均,但是漏报率却略高。各区域代表站日降水量的概率预报Brier评分检验表明：Brier评分均不超过0.2,大大低于T213集合预报所得概率预报的Brier评分分值,说明本文Logistic回归方程的概率预报较为可靠。Brier技巧评分表明：Logistic回归降水概率预报方程各站的BSS技巧评分都大于0.0,说明各站的预报技巧高于检验样本气候概率的预报技巧,且高于T213集合预报的Brier技巧评分,说明在分区基础上建立Logistic回归降水概率预报方程的方法是有预报意义的。  相似文献   

华东地区月平均气温统计降尺度方法比较   总被引：1，自引：0，他引：1  

高红霞  汤剑平 《气象科学》2015,35(6):760-768

用中国地面气象观测站的逐日气温观测资料和NCEP/NCAR再分析资料,分别使用基于多元线性回归(MLR)和3种主成分分析(PCA)的统计降尺度方法,对1959-2008年的华东地区的月平均气温分两个时段进行统计降尺度分析并加以检验,比较了不同降尺度方法的结果。结果表明:对于华东地区气温的统计降尺度预报,基于MLR的统计降尺度方法相对于3种PCA方法而言,对单站年际变化模拟方面有一定优势。PCA方法应用于统计降尺度时,预报因子的区域选择是影响统计降尺度结果的重要因素之一。对于温度进行统计降尺度分析时,预报因子中包含温度因子是非常必要的;所试验的4种降尺度方法,对各站点多年平均情况的模拟要好于对区域平均的年际变化的模拟。  相似文献   

Influence of future tropical cyclone track changes on their basin-wide intensity over the western North Pacific: Downscaled CMIP5 projections     

Chao Wang  Liguang Wu 《大气科学进展》2015,32(5):613-623

The possible changes of tropical cyclone(TC) tracks and their influence on the future basin-wide intensity of TCs over the western North Pacific(WNP) are examined based on the projected large-scale environments derived from a selection of CMIP5(Coupled Model Intercomparison Project Phase 5) models. Specific attention is paid to the performance of the CMIP5 climate models in simulating the large-scale environment for TC development over the WNP. A downscaling system including individual models for simulating the TC track and intensity is used to select the CMIP5 models and to simulate the TC activity in the future.The assessment of the future track and intensity changes of TCs is based on the projected large-scale environment in the21 st century from a selection of nine CMIP5 climate models under the Representative Concentration Pathway 4.5(RCP4.5)scenario. Due to changes in mean steering flows, the influence of TCs over the South China Sea area is projected to decrease,with an increasing number of TCs taking a northwestward track. Changes in prevailing tracks and their contribution to basin-wide intensity change show considerable inter-model variability. The influences of changes in prevailing track make a marked contribution to TC intensity change in some models, tending to counteract the effect of SST warming. This study suggests that attention should be paid to the simulated large-scale environment when assessing the future changes in regional TC activity based on climate models. In addition, the change in prevailing tracks should be considered when assessing future TC intensity change.  相似文献   

Seasonal prediction of June rainfall over South China: Model assessment and statistical downscaling     

Kun-Hui Ye  Chi-Yung Tam  Wen Zhou  Soo-Jin Sohn 《大气科学进展》2015,32(5):680-689

The performances of various dynamical models from the Asia-Pacific Economic Cooperation(APEC) Climate Center(APCC) multi-model ensemble(MME) in predicting station-scale rainfall in South China(SC) in June were evaluated.It was found that the MME mean of model hindcasts can skillfully predict the June rainfall anomaly averaged over the SC domain.This could be related to the MME's ability in capturing the observed linkages between SC rainfall and atmospheric large-scale circulation anomalies in the Indo-Pacific region.Further assessment of station-scale June rainfall prediction based on direct model output(DMO) over 97 stations in SC revealed that the MME mean outperforms each individual model.However,poor prediction abilities in some in-land and southeastern SC stations are apparent in the MME mean and in a number of models.In order to improve the performance at those stations with poor DMO prediction skill,a station-based statistical downscaling scheme was constructed and applied to the individual and MME mean hindcast runs.For several models,this scheme can outperform DMO at more than 30 stations,because it can tap into the abilities of the models in capturing the anomalous Indo-Paciric circulation to which SC rainfall is considerably sensitive.Therefore,enhanced rainfall prediction abilities in these models should make them more useful for disaster preparedness and mitigation purposes.  相似文献