Inter-annual Variability of Moisture Flux from the Prairie Agro-ecosystem: Impact of Crop Phenology on the Seasonal Pattern of Tornado Days

This study, through the inclusion of a simpleparameterization of the phenologicaldevelopment of spring wheat in evapotranspirationsimulations for 1988–2000, at a representativearid grassland and a representative transitionalgrassland site, delineated the inter-annualvariability of the seasonal moisture flux from theCanadian Prairie agro-ecosystem. Theagro-ecosystem's contribution to atmospheric boundary-layermoisture, at these representative sites, wasrelated to the seasonal pattern of tornado days in thegrassland eco-climatic zone for the averageyear, for a warmer/drier year and for a cooler/wetteryear. The following conclusions were drawn:(1) The moisture flux from the Prairie agro-ecosystemdisplays considerable inter-annualvariability due, in the main, to the rate andtiming of crop phenological development andassociated biophysical parameters, and (2) themoisture flux from the Prairie agro-ecosystemtranslates directly into changes in atmosphericboundary-layer moisture, which subsequentlyaffects the magnitude of the potential energyavailable for deep convection and the seasonalpattern of tornado days. For expansive agriculturalareas, representing the inter-annual variabilityof crop phenological development in land surfacemodels is critical to the successful simulationof the surface moisture flux, and thus thethermodynamic properties of the atmospheric boundarylayer. Therefore, it is of particularimportance to Prairie climate and climate change modelling.     

考虑雷暴活动的全球近地稳态大气电场的精确数学解

全球大气电模式是指大气和地表构成的闭合回路,其中考虑雷暴为主要充电电源,并将雷暴作为一个垂直电偶极子来考虑.本文从电流连续方程出发,采用球谐函数展开法,边界条件采用下边界为地表大气电势,上边界为电离层底部电势,非齐次电流源函数项采用垂直偶极子假设.通过所做的非线性函数变换,得出了考虑雷暴活动的全球电模式的近地稳态解析解,并证明其能展开为有限多项式级数之和.所得结论与过去的理论分析结果和实验观测是一致的.该文的工作是对以前相关工作仅能得到近似解的一种改进,同时本文所得公式可用于今后对大气电参量进行相关的数值计算及模拟之中.     

Markov chain model to study the occurrence of pre-monsoon thunderstorms over Bhubaneswar,India

The present work deals with pre-monsoon thunderstorms over Bhubaneswar belonging to the state of Orissa, India. A Markovian approach has been adopted to discern the probabilistic behavior of the time series of the occurrence and non-occurrence of this hazardous weather event by introducing a dichotomy within the time series. After a painstaking analysis through chi-square tests, we have identified serial independence in a few years and first-order two-state Markovian dependence in a few years (2000, 2001, 2004 and 2006). Finally, for the years of first-order two-state Markovian dependence, it has been observed that the probability of occurrence or non-occurrence of thunderstorm gets higher if the state of the previous day is similar to that of the current day. Furthermore, the probability of getting non-thunderstorm day followed by non-thunderstorm day is higher than the probability of getting thunderstorm day followed by thunderstorm day. It has been also observed that the unconditional climatological probability of the occurrence of severe pre-monsoon thunderstorm implied by the Markov chain is closely in agreement with the observed relative frequencies. However, it could be revealed that Markov chain cannot, in general, be suggested as a predictive tool for pre-monsoon thunderstorms under study without investigating the serial dependence inherent in the time series.     

三维强风暴动力-电耦合数值模拟研究Ⅱ:电结构形成机制

文中利用文献 [1]所建立的三维强风暴动力 -电耦合模式模拟研究了CCOPE(CooperativeConvectivePrecipita tionExperiment)计划 1981年 7月 19日的一次强雷暴过程 ,分析了该雷暴云中电结构的时空演变特征和形成机制 ,讨论了起电、降水和对流三者间的相互关系。结果表明 ,感应和非感应起电机制是雷暴云电结构形成的主要机制 ,冰相物的出现大大增强了雷暴中的起电过程。雷暴云中最大电场出现的时间与最大固态降水强度的出现基本同时 ,但比最大液态降水强度和最大上升速度出现的时间略有滞后 ,云中最大上升速度与最大液态降水强度基本同时出现。云中最大电场出现的时段正好是最大上升速度达到最大值后回落的阶段。雷暴云中起电活动的强弱还受云中微物理过程的发展和冰相物出现时间的影响 ,对流运动与起电过程的关系主要体现在对流运动影响着云中的凝结和冻结过程 ,从而与冰相物出现的时间有关。而仅仅依靠对流运动对正负离子的输送机制不可能产生云中接近放电的临界电场。     

基于WRF模式的对流尺度边界层方案参数随机扰动方法研究

边界层参数化方案的准确性会影响模式对近地面变量和大气低层热动力结构的模拟,对雷暴等强对流天气的预报非常重要,但边界层方案内在的不确定性使得单一预报具有局限性。为了提高对流尺度数值模式中边界层方案的预报效果,基于WRF（The Weather Research and Forecasting Model）模式,应用随机参数扰动（SPP）方法对Mellor-Yamada-Nakanishi-Niino（MYNN）边界层方案中重要的3个不确定参数进行扰动,探究了该方法对北京地区一次雷暴过程模拟的影响。同时考虑了对流尺度集合预报系统的特点,调整随机参数扰动方法的3个参量（去相关时间尺度、空间尺度和格点标准差）探究了对流尺度中对MYNN方案参数进行扰动的最优设置。结果显示:随机扰动MYNN边界层方案参数（SPPM）方法可以有效提高近地面变量和700 hPa以下低层变量的离散度,同时提高了短时强降水位置和强度的预报技巧。3个参量的试验说明,去相关时间尺度增大到12 h集合离散度有明显提高;格点标准差增大到0.20,预报技巧也略有提高;去相关空间尺度维持在默认值700 km较好,尺度过小（150 km）预报技巧明显降低。上述结果表明,在对流尺度中SPPM方法可以有效表达边界层参数化方案的不确定性,提高集合预报系统的预报技巧。