气候模式中云的垂直重叠及其辐射传输问题研究进展

概述了全球气候模式中云的垂直重叠的处理方法及其辐射物理过程的最新研究进展。从云垂直重叠模型的构造、模型在气候模式中的实现方式,得到与观测一致的云重叠结构所采用的数据和方法、重叠云的辐射传输等方面,给出了针对这一国际研究难点问题的最新研究进展。关于气候模式中云的垂直重叠问题的研究至今已取得了许多成果,表现在:重叠模型上有了更为科学的描述形式(如指数衰减重叠);重叠云的辐射传输也有了更快速的处理方法(如蒙特卡洛独立柱近似)并被广泛应用;连续的三维云遥感观测(如CloudSat/CALIPSO)和云分辨尺度的三维云模式的发展为在气候模式中精确描述云的垂直结构提供了丰富的观测资料和模式数据。但是,气候模式中现有的云重叠结构处理及其辐射传输方法还远不够完善,仍然存在很多没有解决的问题需要在未来进行探索。     

Anomalous Western Pacific Subtropical High during Late Summer in Weak La Nia Years: Contrast between 1981 and 2013

Both 1981 and 2013 were weak La Niña years with a similar sea surface temperature (SST) anomaly in the tropical Pacific, yet the western Pacific subtropical high (WPSH) during August exhibited an opposite anomaly in the two years. A comparison indicates that, in the absence of a strong SST anomaly in the tropics, the cold advection from Eurasian high latitudes and the convection of the western Pacific warm pool play important roles in influencing the strength and position of the WPSH in August. In August 1981, the spatial pattern of 500 hPa geopotential height was characterized by a meridional circulation with a strong ridge in the Ural Mountains and a deep trough in Siberia, which provided favorable conditions for cold air invading into the lower latitudes. Accordingly, the geopotential height to the north of the WPSH was reduced by the cold advection anomaly from high latitudes, resulting in an eastward retreat of the WPSH. Moreover, an anomalous cyclonic circulation in the subtropical western Pacific, excited by enhanced warm pool convection, also contributed to the eastward retreat of the WPSH. By contrast, the influence from high latitudes was relatively weak in August 2013 due to a zonal circulation pattern over Eurasia, and the anomalous anticyclonic circulation induced by suppressed warm pool convection also facilitated the westward extension of the WPSH. Therefore, the combined effects of the high latitude and tropical circulations may contribute a persistent anomaly of the WPSH in late summer, despite the tropical SST anomaly being weak.     

Recent significant tornadoes in China

正1.Introduction Compared with the United States,whose annual number of tornadoes can exceed 1000,the average number of tornadoes per year in China over the past half a century is estimated to be fewer than 100(Fan and Yu,2015),even though both countries are located in a similar latitudinal zone of the Northern Hemisphere.The annual average recorded number of F1(Fujita scale)or EF1(enhanced Fujita scale)intensity or higher tornadoes in China between 1961 and 2010 is about     

A timescale decomposed threshold regression downscaling approach to forecasting South China early summer rainfall

A timescale decomposed threshold regression(TSDTR) downscaling approach to forecasting South China early summer rainfall(SCESR) is described by using long-term observed station rainfall data and NOAA ERSST data. It makes use of two distinct regression downscaling models corresponding to the interannual and interdecadal rainfall variability of SCESR.The two models are developed based on the partial least squares(PLS) regression technique, linking SCESR to SST modes in preceding months on both interannual and interdecadal timescales. Specifically, using the datasets in the calibration period 1915–84, the variability of SCESR and SST are decomposed into interannual and interdecadal components. On the interannual timescale, a threshold PLS regression model is fitted to interannual components of SCESR and March SST patterns by taking account of the modulation of negative and positive phases of the Pacific Decadal Oscillation(PDO). On the interdecadal timescale, a standard PLS regression model is fitted to the relationship between SCESR and preceding November SST patterns. The total rainfall prediction is obtained by the sum of the outputs from both the interannual and interdecadal models. Results show that the TSDTR downscaling approach achieves reasonable skill in predicting the observed rainfall in the validation period 1985–2006, compared to other simpler approaches. This study suggests that the TSDTR approach,considering different interannual SCESR-SST relationships under the modulation of PDO phases, as well as the interdecadal variability of SCESR associated with SST patterns, may provide a new perspective to improve climate predictions.     

含AgI焰剂成冰性能与物化特征的实验研究

利用CAMS的1 m~3等温云室系统筛选出新型高效AgI焰剂WMC-IN-001和WMG-IN-002。检测结果表明,它们具有较高的成核率,在-15℃时达到10~(15)g~(-1)AgI量级,尤其在-7℃时WMC-IN-001的成核率仍可达到10~(14)g~(-1)AgI量级。同时给出对节银剂配方和2011年市场上主要的几种催化剂的检测结果进行对比。WMC-IN-001和WMC-IN-002的成冰速率较慢,在各检测温度的成冰速率差异较小,均在40~55 min。利用冷场发射扫描电镜和能谱仪对WMC-IN-001燃烧产生的气溶胶粒子作了物化特征分析,粒子分布在0.02~0.60μm,具有两个典型的模态:0.02~0.10μm的较小的粒子和0.20~0.55μm的较大的粒子,均立方直径为0.2472μm。WMC-IN-001气溶胶粒子明显偏大,小粒子相对较少,这可能是其成冰速率偏慢的原因之一。     

基于改进综合气象干旱指数的2011年和2013年长江中下游干旱低频振荡特征分析

利用NCEP/NCAR逐日再分析资料和地面观测资料,基于改进的综合气象干旱指数（I_C）对长江中下游地区2011年春季和2013年夏季干旱过程的低频振荡特征进行了分析。结果表明：2011年春季干旱过程的主要低频I_C周期为30~60 d,西太平洋500 hPa正异常低频高度场系统的西移、南支锋区上游500 hPa正异常低频高度场系统的东移和北扩、西北地区东部低层低频反气旋的向南移动可能是低频I_C传播变化特征的重要原因。2013年夏季干旱过程的主要低频I_C周期也为30~60 d,西亚和西北太平洋500 hPa正异常低频高度场向我国南方地区移动、孟加拉湾和西北太平洋的低层低频反气旋向西和向北移动与低频I_C传播变化特征有重要联系。     

京津冀地区中α尺度飑线过程中大风特征分析及成因初探

应用常规天气观测资料、地面加密自动气象站资料、大风灾情报资料、京津冀地区7部多普勒天气雷达组网观测资料及VDRAS资料,从多个角度对2013年8月4日京津冀地区一次飑线过程产生的大范围大风天气过程进行了分析,结果显示:此次过程是在高空冷空气南下、低层暖湿气流北上、系统前倾及位势不稳定的有利层结条件下,由多单体风暴演变为中α尺度的强飑线所致。飑线形成于低层垂直切变加强、冷池合并之后;大风主要发生在飑线主体回波中,其次是主体回波前和中前,主体回波后很少发生。大风发生的位置取决于飑线结构中气流的性质,气流的性质与冷池前进的程度和对流的强度关系密切。大风大部分由下沉冷气流产生,少数为近地面上升暖气流导致。大风发生的范围和强度与低层风垂直切变的强度呈正比,大范围低层风垂直切变的加强增强了飑线入流和出流的强度,是大范围大风、局部强风形成的重要原因。大风发生站次与冷池的强度和范围密切相关,冷池的加强和范围的扩大加强了后侧冷入流和前侧暖入流的强度和范围,也是大范围大风形成的重要因素。     

1999年北京持续高温天气过程的诊断分析

利用北京观象台观测资料和NCEP/NCAR再分析数据,对1999年6月24日至7月2日北京一次持续性高温天气的演变和发展过程及非绝热加热作用对系统的影响进行诊断分析,结果表明：在此次高温天气发生前,欧亚大陆中高纬度环流经向度很大,欧洲北部和贝加尔湖以南为高压脊控制,中亚和我国东北地区则处于低压槽内。贝加尔湖南部的高压脊纬向延伸范围较广,在东移过程中长时间影响北京。随着贝加尔湖以南的高压脊逐渐东移,北京上空下沉增温与非绝热加热作用有所增强,北京逐渐受到高温天气影响。在高温天气发生的后半阶段,我国东北的低压槽入海后在120130°E附近维持并发展,槽前非绝热加热率很大。从垂直方向来看,加热率在500 hPa以下随高度迅速增加,根据全型涡度方程,强烈的非绝热加热率垂直分布不均作为一个明显的涡度源区,对入海低压槽的稳定维持有显著的作用。而入海低压槽的稳定维持,又阻碍了华北高压脊的东移,使其在北京地区长时间稳定少动,为北京带来多日的持续性高温天气。     

Erratum to: Climate change projections over India by a downscaling approach using PRECIS

The author “Bhaski Bhaskaran” and his affiliation “Fujitsu Laboratory of Europe, Middlesex, UK” should be replaced by “Balakrishnan Bhaskaran”, “Fujitsu Laboratories of Europe Limited, Hayes Park, Middlesex, UK”, respectively.The corrected name and affiliation are shown in this erratum.     

Comparison of prediction performance using statistical postprocessing methods

As the 2018 Winter Olympics are to be held in Pyeongchang, both general weather information on Pyeongchang and specific weather information on this region, which can affect game operation and athletic performance, are required. An ensemble prediction system has been applied to provide more accurate weather information, but it has bias and dispersion due to the limitations and uncertainty of its model. In this study, homogeneous and nonhomogeneous regression models as well as Bayesian model averaging (BMA) were used to reduce the bias and dispersion existing in ensemble prediction and to provide probabilistic forecast. Prior to applying the prediction methods, reliability of the ensemble forecasts was tested by using a rank histogram and a residualquantile-quantile plot to identify the ensemble forecasts and the corresponding verifications. The ensemble forecasts had a consistent positive bias, indicating over-forecasting, and were under-dispersed. To correct such biases, statistical post-processing methods were applied using fixed and sliding windows. The prediction skills of methods were compared by using the mean absolute error, root mean square error, continuous ranked probability score, and continuous ranked probability skill score. Under the fixed window, BMA exhibited better prediction skill than the other methods in most observation station. Under the sliding window, on the other hand, homogeneous and non-homogeneous regression models with positive regression coefficients exhibited better prediction skill than BMA. In particular, the homogeneous regression model with positive regression coefficients exhibited the best prediction skill.