Junhua Yang

Concentration, temporal variation and sources of black carbon in the Mount Everest region retrieved by real-time observation and simulation

Based on the high-resolution measurement of black carbon (BC) at the Qomolangma (Mt. Everest) Station (QOMS, 28.36 N, 86.95 E, 4276 m a.s.l.) from 15 May 2015 to 31 May 2017, we investigated the seasonal and diurnal variations in BC and its potential source regions. Both monthly and daily mean BC concentrations reached the highest values in the pre-monsoon season and the lowest values in the monsoon season. The highest monthly and daily mean BC concentrations were at least 1 order of magnitude higher than the lowest concentrations. For the diurnal variation, the BC concentrations remained significantly high from late at night to morning in the pre-monsoon season. Meanwhile, the westerly winds prevailed during this period, implying the potential for pollutants to be transported across the Himalayas from long-distance sources to QOMS along the valley. In the monsoon season, the BC concentrations remained low but peaked in the morning and at noon, which might be caused by local emissions from cooking. By analyzing the simulation results from the backward trajectories of air masses and the fire spot distribution from the MODIS data, we found that the seasonal cycle of BC was significantly influenced by the atmospheric circulation and combustion intensity in the Mt. Everest region. The transport mechanisms of BC were further revealed using a WRF-Chem simulation during severe pollution episodes. For the pollution event in the monsoon season, BC aerosols in southern Asia were uplifted and transported to the Mt. Everest region by the southerly winds in the upper atmosphere. However, for the events in the pre-monsoon season, BC from northern India was transported and concentrated on the southern slope of the Himalayas by the northwesterly winds in the lower atmosphere and then transported across the Himalayas by the mountain-valley wind. A relatively smaller amount of BC from northwestern India and central Asia was transported to the Mt. Everest region by the westerly winds in the upper atmosphere.

Improved Land Use and Leaf Area Index Enhances WRF-3DVAR Satellite Radiance Assimilation: A Case Study Focusing on Rainfall Simulation in the Shule River Basin during July 2013

The application of satellite radiance assimilation can improve the simulation of precipitation by numerical weather prediction models. However, substantial quantities of satellite data, especially those derived from low-level (surface-sensitive) channels, are rejected for use because of the difficulty in realistically modeling land surface emissivity and energy budgets. Here, we used an improved land use and leaf area index (LAI) dataset in the WRF-3DVAR assimilation system to explore the benefit of using improved quality of land surface information to improve rainfall simulation for the Shule River Basin in the northeastern Tibetan Plateau as a case study. The results for July 2013 show that, for low-level channels (e.g., channel 3), the underestimation of brightness temperature in the original simulation was largely removed by more realistic land surface information. In addition, more satellite data could be utilized in the assimilation because the realistic land use and LAI data allowed more satellite radiance data to pass the deviation test and get used by the assimilation, which resulted in improved initial driving fields and better simulation in terms of temperature, relative humidity, vertical convection, and cumulative precipitation.摘 要同化卫星辐射数据可提高数值天气模式的预测精度. 但由于地表信息的不准确, 以往研究中通常会剔除对地表较敏感的低层通道中的辐射数据, 从而大大降低了卫星数据的使用率. 本研究以青藏高原东北部疏勒河流域2013年7月份降水模拟为例, 通过更新WRF-3DVAR同化系统中下垫面土地利用类型和叶面积指数数据, 来分析改进的土地覆被对辐射资料同化的影响. 结果表明, 更新土地覆被后, 在对地表敏感的窗区通道中, 模拟的辐射亮温值与实际观测值更为接近, 使更多的卫星数据通过偏差检验并在同化系统中得到应用. 而对于非窗区通道, 土地覆被更新对辐射亮温的模拟影响较小. 同化系统中卫星辐射资料利用率的提高使WRF模式对研究区内降水的模拟得到了一定程度的改进.