基于不同气象数据的山地城市大气环境敏感性评估对比

Assessment and comparison of atmospheric environmental sensitivity of mountain cities based on different meteorological data

以典型低纬高原山地城市云南省德宏州为例,利用WRF_CALPUFF模型开展大气环境敏感性评估并以此为依据进行敏感区识别,分别采用WRF模拟结果和地面气象站观测资料作为模型输入地面气象数据,通过对比分析基于两种不同数据的评估结果,讨论适用于山地城市大气环境敏感性评估的数据和方法。结果表明:2种方法模拟计算的扩散指数均能反映出地形差异所致的扩散能力空间差异性,弱扩散区识别均较可靠。气象背景场采用WRF高空模拟数据和地面气象站观测数据相结合的方法,评估结果可靠,具有基础数据获取较难、技术难度较低、时间成本较低的特点,若能获取站点数据则推荐此法。气象背景场均采用WRF模拟结果的方法,在识别布局敏感区时不确定性较高,主要因地形复杂地区风场模拟不确定性较高所致,但此法具有基础数据获取较容易、技术难度较高、时间成本较高的特点,若采用此法,需提高模拟准确性以保障评估结果的可靠性。

Taking Dehong Prefecture,Yunnan Province,a typical low-latitude plateau mountain city,as an example,the WRF_CALPUFF model was used to carry out atmospheric environment sensitivity assessment and identify sensitive areas based on this model.WRF simulation results and ground meteorological station observation data were respectively used as input ground meteorological data for the model.The data and methods applicable to the assessment of atmospheric environmental sensitivity in mountain cities were discussed.The results showed that the diffusion index calculated by the two methods could reflect the spatial difference of diffusion capacity caused by terrain difference,and the identification of weak diffusion region was reliable.The meteorological background field adopts the method of combining WRF high-altitude simulation data and ground meteorological station observation data,and the evaluation results are reliable,with the characteristics of difficult-to-obtain basic data,low technical difficulty and low time cost.If station data could be obtained,this method was recommended.WRF simulation results were used for all meteorological background fields,and the uncertainty in identifying the layout-sensitive area was relatively high,mainly due to the high uncertainty in wind field simulation in complex terrain areas.However,the method was characterized by easy access to basic data,high technical difficulty and high time cost.If this method was adopted,the simulation accuracy should be improved to ensure the reliability of evaluation results.