近地层风能参数随高度分布的推算方法研究

应用江苏和吉林的12个测风塔资料,对两个地区的风能参数进行了统计和分析,探讨了一种用10m高度风速资料推算近地层内任意高度上平均风功率密度的新方法.结果表明:应用该方法交互拟合不同高度的平均风功率密度,平均误差4.4%,最大误差13.3%,优于指数律的平均误差7.8%,最大误差22.0%,效果较为理想.     

中国不同纬度城市群对东亚夏季风气候影响的模拟研究

该工作利用中尺度模式(MM5),通过在中国东部不同地区设置城市扩展区,进行了东亚夏季风气候的模拟对比试验,以研究不同纬度带上城市化对东亚夏季风气候的影响,并试图了解不同气候背景(不同纬度)下大规模城市群(带)的气候效应及其差异.结果表明,城市下垫面扩展使得扩展区及其周边地区的降水减少、气温升高,总体上呈现出干、暖化的趋势.城市化的气候效应通过大气环流的传输可以传播到较广阔的范围.而且不同地域(纬度)的城市下垫面扩展对大范围气候的影响也具有明显差别,北方城市带扩展比南方城市带扩展对东亚气候的影响更为显著.长江三角洲地区对城市扩展造成的下垫面改变相对不敏感,因而在长江三角洲地区比较适合发展大规模城市群,而在中国北方地区,尤其是华北平原地区,则应该对城市化的规模进行适当控制,以减小城市化发展对东亚区域气候产生的不利影响.该工作的模拟结果还表明,城市带扩展对东亚夏季风有明显影响,但由城市扩展激发出的次级大气环流具有较强区域性的特点,因而难以将城市带扩展对夏季风强度的影响概括为整体增强或减弱.     

IPCC-AR4模式对中国21世纪气候变化的情景预估

利用政府间气候变化委员会(IPCC)第四次评估报告提供的13个新一代气候系统模式的模拟结果,分析了不同情景下(高排放SRES A2、中等排放A1B、低排放B1)中国区域未来100年的气候变化。结果表明,21世纪中国气候预估显著变暖、变湿,世纪末变暖范围在1.6℃~5℃之间,年降水量增加1.5%~20%。在A2、A1B和B1情景下,21世纪末期增暖幅度依次为5.3℃、4.3℃和2.8℃,平均3.5℃,年降水量预估增加依次为11%、9.6%和6.4%,平均达7.5%。气温和降水变化的地理分布显示:北方增温幅度大于南方,降水的增加也主要集中在北方。冬季变暖最明显,降水则在冬、春季增加较显著。模式预估结果的不确定性分析表明,新一代全球系统模式对21世纪中国气候变化预估的可靠性得到了提高。     

A newly-discovered GPD-GEV relationship together with comparing their models of extreme precipitation in summer

It has been theoretically proven that at a high threshold an approximate expression for a quantile of GEV （Generalized Extreme Values） distribution can be derived from GPD （Generalized Pareto Distribution）. Afterwards, a quantile of extreme rainfall events in a certain return period is found using L-moment estimation and extreme rainfall events simulated by GPD and GEV, with all aspects of their results compared. Numerical simulations show that POT （Peaks Over Threshold）-based GPD is advantageous in its simple operation and subjected to practically no effect of the sample size of the primitive series, producing steady high-precision fittings in the whole field of values （including the high-end heavy tailed）. In comparison, BM （Block Maximum）-based GEV is limited, to some extent, to the probability and quantile simulation, thereby showing that GPD is an extension of GEV, the former being of greater utility and higher significance to climate research compared to the latter.     

近百年中国两次年代际气候变暖中的冷、暖平流背景

近百年中国气候经历了两次明显的年代际变暖,分别发生在20世纪40年代之前和70年代之后。由大气环流变化引起的冷、暖平流异常可为理解两次变暖提供参考。首先基于最新研制的近百年32站气温观测和集合经验模分解（Ensemble Empirical Mode Decomposition,EEMD）方法揭示两次变暖过程中国的冷、暖分布格局,进而利用全球格点气温和海平面气压资料计算了同期地转风导致的温度平流。结果表明,20世纪40年代中国华北北部至东北大部分地区和华南沿海局部地区偏冷而中东部至西南内陆大部分地区偏暖的年代际气候异常,站点冷、暖异常与大尺度温度平流的空间关联系数达0.85;而对于近20年中国气候变暖而言,这一关联系数仅0.49。研究结果从一个新颖的角度说明:早期变暖过程中气候系统内部过程如大气环流异常的作用较大,而近几十年气候变暖则更多地受迫于外强迫。      

Multi-sliding time windows based changing trend of mean temperature and its association with the global-warming hiatus

Based on three global annual mean surface temperature time series and three Chinese annual mean surface air temperature time series, climate change trends on multiple timescales are analyzed by using the trend estimation method of multi-sliding time windows. The results are used to discuss the so-called global-warming hiatus during 1998–2012. It is demonstrated that different beginning and end times have an obvious effect on the results of the trend estimation, and the implications are particularly large when using a short window. The global-warming hiatus during 1998–2012 is the result of viewing temperature series on short timescales; and the events similar to it, or the events with even cold tendencies, have actually occurred many times in history. Therefore, the global-warming hiatus is likely to be a periodical feature of the long-term temperature change. It mainly reflects the decadal variability of temperature, and such a phenomenon in the short term does not alter the overall warming trend in the long term.     

非齐次隐马尔可夫降尺度方法对江淮流域夏季逐日降水的模拟及其评估

引入非齐次隐马尔可夫模型(Nonhomogeneous hidden Markov model,NHMM)统计降尺度方法,利用1961—2002年江淮流域夏季逐日降水资料、欧洲中期天气预报中心(ECMWF)的ERA-40再分析资料建立模型,检验其对东部季风区(以江淮流域为代表)夏季日降水的模拟能力,并对比BCC-CSM1.1(m)模式NHMM降尺度前后的模拟效果。结果表明,NHMM降尺度方法通过建立降水概率分布态间转移参数与大尺度环流变量的联系,对江淮流域逐日降水量具有较好的降尺度效果。模拟的各站日降水量概率分布函数(PDF)曲线与观测非常接近,布赖尔评分(Brier Score,S_B)均小于0.11%,显著性评分(Significance Score,Ss)均大于0.84;夏季总降水量、降水日数、中雨日数、降水强度和95%分位降水量指数的多年平均场偏差百分率绝对值低于10%,前3个指数的空间相关系数高于0.9;该方法对各降水指数的年际变率也有一定的模拟能力,模拟得到的各指数的区域平均年际序列与观测序列的相关系数为0.62—0.87。对BCC-CSM1.1(m)模式的模拟结果进行降尺度后,SB较降尺度前平均减小0.57%,Ss平均增大0.23,皆表明降尺度后的概率分布函数曲线更接近于观测;各降水指数在多数台站的偏差百分率绝对值由大于40%降至10%以内,空间相关系数普遍提高至0.8以上。NHMM降尺度方法能够有效提高BCC-CSM1.1(m)模式对江淮流域夏季日降水的模拟能力,相对气候模式具有显著的"增值",未来可进一步利用该方法进行气候变暖背景下的日降水变化预估。     

中国低温雨雪冰冻灾害危险性评估与区划

利用1960-2009年全国542个站点的常规气象观测资料,从灾害成因角度筛选评估指标,建立灾害危险性评估的气象指标体系,基于不同强度频率的评估思路构建综合危险性指数,对中国低温雨雪冰冻灾害危险性进行评估和区划.结果表明:(1)中国大部地区属于低危险区,高危险区主要集中于黑龙江—吉林—辽宁东部—内蒙古东部、新疆北部、青海南部—西藏东北部—甘肃南部.南方绝大部分地区均处于极低危险区.(2)南方地区内部相对高危险区主要集中在四川中南部—云南东北部—贵州西部、湖南东部、安徽南部—江西北部、河南北部.(3)高危险区的分布与地形、纬度均有着密切的关系.     

A Study on the Effect of Spring Indian Ocean SSTA on Summer Extreme Precipitation Events Over the Eastern NW China

Based on monthly mean wind, geopotential height, specific humidity, and surface pressure of NCAR/NCEP reanalysis, NOAA-reconstructed sea surface temperature (SST) of the Indian Ocean, and daily precipitation data at 97 meteorological stations over the eastern NW China in the past 47 years, the threshold values for extreme precipitation events (EPE) are defined using the percentile method. Singular Value Decomposition and synthetic analysis methods are used to analyze the relationship between summer EPE in the eastern NW China and SSTA in the preceding fall, winter, spring, and the concurrent summer. The result shows that preceding spring SST anomalies (SSTA) in the Indian Ocean are clear indicators for the forecast of summer EPE in the eastern NW China, and a key area of impact is located in the equatorial Indian Ocean. When spring SST is anomalously high in the equatorial Indian Ocean, the meridional circulation averaged over 100°E–110°E will be anomalously ascending near the equator but anomalously descending near 30°N in the middle and upper troposphere from the concurrent to the subsequent summer. In the meantime, the Southwest Monsoon from the Indian Ocean will be anomalously weak and there will be no anomalous water vapor transport to the eastern NW China, resulting in a lack of EPE in the subsequent summer, and vice versa. In addition, in response to anomalously high SST in the equatorial Indian Ocean in spring, the South Asia high pressure tends to be strong in the subsequent summer and more to the west. In the anomalously low SST year, however, the South Asia high tends to be weak in the subsequent summer and more to the east. This is another possible cause of the variation of summer EPE in the eastern NW China.     

FORECASTING THE MJO INDEX BASED ON SSA-AR

Experiments of forecasting daily bi-variate index of the tropical atmospheric Madden-Julian Oscillation (MJO) are performed in the context of adaptive filtering prediction models by combining the singular spectrum analysis (SSA) with the autoregressive (AR) methods.the MJO index,a pair of empirical orthogonal function (EOF) time series,called RMM1 and RMM2,predicts by the combined statistical SSA and AR models:firstly,according to the index of historic observation decomposed by SSA and then reconstructed by selecting the first several components based on prominent variance contributions;after that,established an AR prediction model from the composite (scheme A) or built the forecast models for each of these selected reconstructed components,separately (Scheme B).Several experimental MJO index forecasts are performed based on the models.The results show that both models have useful skills of the MJO index forecast beyond two weeks.In some cases,the correlation coefficient between the observed and predicted index series stays above 0.5 in 20 leading days.The SSA-AR model,based on the reconstructed composite series,has better performance on MJO forecast than the AR model,especially for the leading time longer than 5 days.Therefore,if we build a real-time forecast system by the SSA-AR model,it might provide an applicable tool for the operational prediction of the MJO index.