2000年北京沙尘暴源地解析

2000年我国北方春季干旱少雨,气温回升快,低涡频繁侵入,4月3～9日连续3次冷空气活动,造成了北京地区严重的沙尘暴天气。笔者利用卫星云图和中尺度数值模式MM5,分析了该次沙尘暴源地及沙尘输送机制。结果证明,北京沙尘暴初始源地为蒙古高原及冷涡移动路径上的沙漠戈壁地区;北京周边地区裸露地的沙尘在气旋尾部上升气流的扰动下,亦形成了边界层的近距离输送。      

An improved grey wolf optimizer algorithm for identification and location of gas emission

Identification of the leakage of hazardous gases plays an important role in the environment protection, human health and safety of industry production. However, lots of current optimization algorithms, such as particle swarm optimization (PSO) and Grey Wolf Optimizer (GWO), suffer from poor global optimization capability and estimation accuracy. In this work, a hybrid differential evolutionary and GWO (DE-GWO) algorithm is proposed. Tested by simulation cases and Prairie Grass emission experimental data, DE-GWO shows higher estimation accuracy than GWO. Compared with the other four optimization algorithms, DE-GWO exhibits finer robust stability under different population sizes, fewer iterations, as well as higher estimation accuracy with fewer search agents. Importantly, simulation results demonstrate that DE-GWO is more suitable to apply in the scene with a small number of sensors. Therefore, the proposed in this paper outperforms other optimization algorithms for the gas emission inverse problem. DE-GWO can provide reliable estimation towards gas emission identification and positioning, which shows huge potential as the data analysis module of real-time monitoring and early warning system.