北京地区的闪电时空分布特征及不同强度雷暴的贡献

利用北京闪电定位网(BLNET,Beijing Lightning Network)和SAFIR3000(Surveillance et Alerte Foudre par Interometrie Radioelectrique)定位网7年共423次雷暴的闪电资料,并按照雷暴产生闪电多少,同时参考雷达回波和雷暴持续时间,将雷暴划分为弱雷暴(≤1000次)、强雷暴(>1000次且≤10000次)和超强雷暴(>10000次),分析了北京地区的闪电时空分布特征及不同强度等级雷暴对闪电分布的贡献。北京总闪电密度最大值约为15.4 flashes km-2a(^-1),平均值约为1.9 flashes km^-2a(^-1),大于8 flashes km^-2a(^-1)的闪电密度高值区基本分布在海拔高度200 m等高线以下的平原地带。不同强度雷暴对总雷暴闪电总量贡献不同,弱雷暴(超强雷暴)次数多(少),产生的闪电少(多),超强雷暴和强雷暴产生的闪电分别占总雷暴闪电的37%和56%。不同强度雷暴对总雷暴的闪电密度高值中心分布和闪电日变化特征影响显著,昌平区东部、顺义区中东部和北京主城区是总雷暴闪电密度大于12 flashes km-2a(-1)的三个主要高值区中心,前两个高值中心受强雷暴影响大,而主城区高值中心主要受超强雷暴影响。总雷暴晚上频繁的闪电活动主要受超强雷暴和强雷暴影响,这两类雷暴晚上闪电活动活跃,分别占各自总闪电的69%和65%,而弱雷暴闪电活动白天陡增很快,对总雷暴午后的闪电活动影响大。另外,不同下垫面条件闪电日变化差异大,山区最强的闪电活动出现在白天,午后闪电活动增强很快,主峰值出现在北京时间18:00,而平原最强的闪电活动发生在晚上,平原(山麓)的主峰值比山区推迟了约1.5小时(1小时)。     

Lagerstroemia L. from the middle Miocene Siwalik deposits,northern India: Implication for Cenozoic range shifts of the genus and the family Lythraceae

Journal of Earth System Science - Fossil leaves of Lagerstroemia (Lythraceae) are described from the Siwalik deposits (middle Miocene) of Kathgodam, Uttarakhand, India. The fossil records of the...     

Palm leaves from the Late Oligocene sediments of Makum Coalfield, Assam, India

Two new palm leaf impressions, cf. Iguanura wallichiana and Palmacites makumensis sp. nov. are described from the Makum Coalfield, Tinsukia District, Assam. They belong to the Tikak Parbat Formation being considered as Late Oligocene (Chattian 28?C23?Myr) in age. Their presence, along with the other known fossil records indicates that CMMT (cold month mean temperature) was not less than 18°C with plenty of rainfall, in the region during the period of deposition.     

COMPARISON OF GLOBAL CLIMATE CHANGE SIMULATIONS FOR 2 × CO2-INDUCED WARMING

In this article we compile 108 national and international studies on global climate change, each projecting a quantitative impact on global surface-air temperature due to a doubling of the atmospheric CO₂ concentration. These predictions, documented between 1980 and 1995, are based primarily on climate-modeling research, including radiative-convective, energy-balance, and general circulation models. Collectively over the past 15 years, the average (mean) temperature change projection due to doubled CO₂ is +2.62°C, with a range of 0.16–8.7°C. General circulation models tend to estimate slightly higher values (2.98°C), compared with radiative-convective models (1.98°C) and energy-balance models (2.54°C). During the years 1980 through 1995, an increasing trend in predictions is noticed, although the mean temperature change prediction each year has remained fairly consistent near 2–3°C. These findings suggest that the estimated sensitivity of the climate system continues to remain comparable to the range calculated in earlier studies. However, tremendous advancements in the capacity of climate models continue to reveal important uncertainties in the dynamic nature of global atmospheric interactions. The predictions continue to validate the need for a global policy relating to human influence on global climate change.     

THE OPTIMUM GATE LENGTH FOR THE TIME-VARYING DECONVOLUTION OPERATOR1

The time-varying deconvolution operator designed by dividing time-varying sequence has been extended to include an optimal division of the input data. A numerical example illustrates that the error energy is less in the case of optimally divided input in comparison with arbitrary division.     

IDEAL PERFORMANCE CRITERIA FOR DECONVOLUTION OPERATORS*

A technique to evaluate an ideal performance of a deconvolution operator has been obtained by dividing the input trace into a number of sections. The error energy is seen to decrease with an increase in the number of sections. Numerical examples show that the error energy becomes zero following a relation between the number of sections, the length of input and the length of the filter.     

Heat islands over Mumbai as revealed by autorecorded thermograph data

This study examined hourly temperature data of two locations of Mumbai metropolitan city. One data point (Coloba, Mumbai) is in centre of the city and the other one (Santacruz, Mumbai) is at the airport. The study finds that there were many occasions when night-time hourly temperatures over the city centre were considerably higher than that of the airport, even though temperature at the time of sunset at both the places was nearly same. In this study, the occasions, when hourly night-time temperature over city was more than that of the airport by objectively defined threshold value (3.0 ^°C in this study) for most of the hours in the night, were termed as heat island events. Analysis of the study reveals that these events are mostly confined to November–February months. The study also found that frequency of such events has doubled in recent two decades in comparison to the earlier two decades.     

Lightning Nowcasting with an Algorithm of Thunderstorm Tracking Based on Lightning Location Data over the Beijing Area

A thunderstorm tracking algorithm is proposed to nowcast the possibility of lightning activity over an area of concern by using the total lightning data and neighborhood technique.The lightning radiation sources observed from the Beijing Lightning Network(BLNET)were used to obtain information about the thunderstorm cells,which are significantly valuable in real-time.The boundaries of thunderstorm cells were obtained through the neighborhood technique.After smoothing,these boundaries were used to track the movement of thunderstorms and then extrapolated to nowcast the lightning approaching in an area of concern.The algorithm can deliver creditable results prior to a thunderstorm arriving at the area of concern,with accuracies of 63%,80%,and 91%for lead times of 30,15,and 5 minutes,respectively.The real-time observations of total lightning appear to be significant for thunderstorm tracking and lightning nowcasting,as total lightning tracking could help to fill the observational gaps in radar reflectivity due to the attenuation by hills or other obstacles.The lightning data used in the algorithm performs well in tracking the active thunderstorm cells associated with lightning activities.