Seasonal Prediction of Spring Dust Weather Frequency in Beijing

In this paper, seasonal prediction of spring dust weather frequency (DWF) in Beijing during 1982-2008 has been performed. First, correlation analyses are conducted to identify antecedent climate signals during last winter that are statistically significantly related to spring DWF in Beijing. Then, a seasonal prediction model of spring DWF in Beijing is established through multivariate linear regression analysis, in which the systematic error between the result of original prediction model and the observation, averaged over the last 10 years, is corrected. In addition, it is found that climate signals occurring synchronously with spring dust weather, particularly meridional wind at 850 hPa over western Mongolian Plateau, are also linked closely to spring DWF in Beijing. As such, statistical and dynamic prediction approaches should be combined to include these synchronous predictors into the prediction model in the real-time operational prediction, so as to further improve the prediction accuracy of spring DWF in Beijing, even over North China. However, realizing such a prediction idea in practice depends essentially on the ability of climate models in predicting key climate signals associated with spring DWF in Beijing.     

亚高斯贝叶斯预报处理器及其初步试验

为用户提供概率天气预报信息是公共气象服务的发展趋势,概率天气预报技术的不断改进实现了概率天气预报信息的不断优化。在众多概率天气预报技术方法中,贝叶斯预报处理器是一种新近出现的、基于贝叶斯统计理论的概率预报技术;贝叶斯预报处理器可以根据一个确定性预报系统的预报值与观测值之间代表着这个系统预报性能的统计关系,借助于贝叶斯统计理论,把一个确定性预报转化为一个概率预报,从而实现对预报不确定性的定量化。由于亚高斯似然模型可以适用于多种单调似然比随机依赖结构,故采用该似然模型的亚高斯贝叶斯预报处理器,它在气象、水文等领域具有较强的适用性。在简要介绍了连续型二维随机变量情形下的贝叶斯定理及正态-线性贝叶斯预报处理器之后,详细论述了采用单一预报因子的连续型预报量亚高斯贝叶斯预报处理器,并以长沙站和武汉站2008年1月每日00时(世界时)地面气温(T2m)的中国国家气象中心、欧洲中期天气预报中心、美国国家环境预测中心集合预报中的控制预报资料(预报时效选为96h)作为确定性预报样本,对亚高斯贝叶斯预报处理器进行了初步试验。结果表明,亚高斯贝叶斯预报处理器可以将T2m各集合预报中的控制预报转化为能定量地表达各控制预报不确定性的T2...     

Multi-model projection of July�CAugust climate extreme changes over China under CO2 doubling. Part I: Precipitation

Potential changes in precipitation extremes in July–August over China in response to CO 2 doubling are analyzed based on the output of 24 coupled climate models from the Twentieth-Century Climate in Coupled Models (20C3M) experiment and the 1% per year CO 2 increase experiment (to doubling) (1pctto2x) of phase 3 of the Coupled Model Inter-comparison Project (CMIP3). Evaluation of the models’ performance in simulating the mean state shows that the majority of models fairly reproduce the broad spatial pattern of observed precipitation. However, all the models underestimate extreme precipitation by ～50%. The spread among the models over the Tibetan Plateau is ～2–3 times larger than that over the other areas. Models with higher resolution generally perform better than those with lower resolutions in terms of spatial pattern and precipitation amount. Under the 1pctto2x scenario, the ratio between the absolute value of MME extreme precipitation change and model spread is larger than that of total precipitation, indicating a relatively robust change of extremes. The change of extreme precipitation is more homogeneous than the total precipitation. Analysis on the output of Geophysical Fluid Dynamics Laboratory coupled climate model version 2.1 (GFDL-CM2.1) indicates that the spatially consistent increase of surface temperature and water vapor content contribute to the large increase of extreme precipitation over contiguous China, which follows the Clausius–Clapeyron relationship. Whereas, the meridionally tri-polar pattern of mean precipitation change over eastern China is dominated by the change of water vapor convergence, which is determined by the response of monsoon circulation to global warming.     

云凝结核浓度对WRF模式模拟飑线降水的影响：不同云微物理参数化方案的对比研究

采用WRF模式模拟一次影响中国广东省的飑线过程, 分别选取Morrison、 Thompson07、 Thompson09和WDM6云微物理方案实施了四组试验, 每组试验包括不同云凝结核（CCN）浓度的三次模拟, 称为 “低浓度”、 “中浓度” 和 “高浓度”, 将模拟区域划分为深对流、 浅对流和层云区域, 对比分析四组试验中CCN浓度变化对模拟的总降水量、 不同区域降水率和不同区域面积的影响, 进一步分析了云微物理过程、 动力环流强度等受CCN浓度变化的影响。发现: （1） 由于不同云微物理过程与CCN浓度有着直接或间接的联系、 不同云微物理过程之间存在复杂的关联、 云微物理过程与动力环流之间发生非线性耦合, 采用不同的云微物理方案导致模拟的CCN—降雨影响既有相似、 也有差异; （2）模拟的CCN—降水影响在采用Thompson09和Thompson07方案时更显著, 采用WDM6方案时最小; （3）四组模拟试验均出现CCN浓度增加延迟降水产生、 初期降水减弱的情况, 在模拟后期降水量也随着CCN浓度增加而减小, 而飑线成熟阶段CCN—降水影响更加复杂。     

新疆“2.28” 大风的中尺度数值模拟

受西西伯利亚较强冷空气入侵的影响,2007年2月28日02时,乌鲁木齐开往阿克苏的5807次旅客列车,在新疆三十里风区遭遇狂风,造成11节车厢脱轨侧翻。使用WRF模式对这次大风天气过程进行了数值模拟。结果表明：WRF模式较好地模拟了三十里风区大风的演变和分布特征,对逐时风速的模拟较实况偏小,但变化比较同步;很大的气压梯度和特殊的地形是大风形成的主要原因,狭管效应和下坡风同时存在。     

Effects of Crop Growth and Development on Land Surface Fluxes

In this study, the Crop Estimation through Resource and Environment Synthesis model (CERES3.0) was coupled into the Biosphere-Atmosphere Transfer Scheme (BATS), which is called BATS CERES, to represent interactions between the land surface and crop growth processes. The effects of crop growth and development on land surface processes were then studied based on numerical simulations using the land surface models. Six sensitivity experiments by BATS show that the land surface fluxes underwent substantial changes when the leaf area index was changed from 0 to 6 m2 m-2. Numerical experiments for Yucheng and Taoyuan stations reveal that the coupled model could capture not only the responses of crop growth and development to environmental conditions, but also the feedbacks to land surface processes. For quantitative evaluation of the effects of crop growth and development on surface fluxes in China, two numerical experiments were conducted over continental China: one by BATS CERES and one by the original BATS. Comparison of the two runs shows decreases of leaf area index and fractional vegetation cover when incorporating dynamic crops in land surface simulation, which lead to less canopy interception, vegetation transpiration, total evapotranspiration, top soil moisture, and more soil evaporation, surface runoff, and root zone soil moisture. These changes are accompanied by decreasing latent heat flux and increasing sensible heat flux in the cropland region. In addition, the comparison between the simulations and observations proved that incorporating the crop growth and development process into the land surface model could reduce the systematic biases of the simulated leaf area index and top soil moisture, hence improve the simulation of land surface fluxes.     

广东省后汛期强对流天气潜势预报方法研究

利用2007—2008年两年7—10月广东后汛期强对流天气出现时的雷达资料、对应的GRAPES模式资料以及地市台站上报的强对流天气发生的实况,把瞬时大风〉17.2 m·s^-1、冰雹、龙卷作为强对流发生的依据,对上述数据进行整理。根据广州热带海洋研究所中尺度模式的输出GRAPES资料,结合雷达CAPPI数据,计算单体的各层风速、温度、湿度、有效位能等环境特征量,将单体特征和模式计算的单体环境场要素以及强对流发生实况,通过多元逐步回归方法建立后汛期强对流天气潜势预报方程,据此对发生于广东省后汛期强对流天气（如雷雨大风、冰雹和龙卷风）进行0～1小时临近预报。用预报成功率（POD）、虚假警报率（FAR）和关键成功指数（CSI）衡量方法的预报性能。共有5540个有效样本参与回归计算,31个因子中有12个引入了回归方程,建立的预报方程在阈值取为0.26时,得到的预报成功率POD为0.73,虚假警报率FAR为0.61,关键成功指数CSI为0.338,各项指标均要好于前汛期预报性能;从实际的预报能力来看,在后汛期强对流潜势预报中,后汛期强对流潜势预报方法得到的空报率和漏报率都要低于前汛期,预报效果较好,可用于广东后汛期的强对流天气潜势预报中。     

WRF模式三维变分中背景误差协方差估计

利用WRF模式2008年5-10月逐日预报结果,通过NMC方法进行背景误差协方差(B)估计.给出其结构特征,进行单点数值试验,并利用不同B进行1个月的数值模拟试验,检验模拟降水效果.结果表明:通过单点数值试验验证估算的B结构合理.不同的B,资料同化过程差别较大,应用重新统计的B,同化效率更高,目标函数收敛更稳定.模式模...     

基于综合评价算法的雷电灾害易损度区划模型研究

选取落雷密度、雷灾发生率、雷灾经济损失率及雷灾生命损伤率为评价雷电灾害易损性的指标,运用解析几何的直线方程对指标数据进行了标准化,引入层次分析法对评价指标数据真实性程度对结果的影响进行了修正,采用聚类分析方法对总易损度值进行更为合理科学的区划分级,并以福建省为例对新模型做了实例计算。结果表明,综合评价算法模型在关系计算、级别区划、结果分析等方面体现出一定的数学优势,能较细致、完整地反映出雷灾易损度区划指标之间的联系及各指标因素对雷灾易损度的综合影响关系。     

一个区域气候模式对ENSO衰减年夏季中国东部降水的模拟

The performance of the Climate version of the Regional Eta-coordinate Model (CREM), a regional climate model developed by State Key Laboratory of Nu- merical modeling for Atmospheric Science and Geophysical Fluid Dynamics/Institute of Atmospheric Physics (LASG/IAP), in simulating rainfall anomalies during the ENSO decaying summers from 1982 to 2002 was evaluated. The added value of rainfall simulation relative to reanalysis data and the sources of model bias were studied. Results showed that the model simulated rainfall anomalies moderately well. The model did well at capturing the above-normal rainfall along the Yangtze River valley (YRV) during El Nio decaying summers and the below and above-normal rainfall centers along the YRV and the Huaihe River valley (HRV), respectively, during La Nia decaying summers. These features were not evident in rainfall products derived from the reanalysis, indicating that rainfall simulation did add value. The main limitations of the model were that the simulated rainfall anomalies along the YRV were far stronger and weaker in magnitude than the observations during El Nio decaying summers and La Nia decaying summers, respectively. The stronger magnitude above-normal rainfall during El Nio decaying summers was due to a stronger northward transport of water vapor in the lower troposphere, mostly from moisture advection. An artificial, above-normal rainfall center was seen in the region north to 35°N, which was associated with stronger northward water vapor transport. Both lower tropospheric circulation bias and a wetter model atmosphere contributed to the bias caused by water vapor transport. There was a stronger southward water vapor transport from the southern boundary of the model during La Nia decaying summers;less remaining water vapor caused anomalously weaker rainfall in the model as compared to observations.