doi:  10.3878/j.issn.1006-9895.1610.16105
风云三号微波观测资料的海雾同化模拟

Sea Fog Simulation with Assimilation of FY-3A Microwave Data
摘要点击 550  全文点击 554  投稿时间:2016-01-07  修订日期:2016-11-10
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基金:  国家自然科学基金项目41075057、41675110
中文关键词:  卫星资料  数据同化  海雾模拟  微波湿度计(MWHS)  微波温度计(MWTS)  边界层
英文关键词:  Satellite data  Data assimilation  Sea fog simulation  MicroWave Humidity Sounding (MWHS)  MicroWave Temperature Sounding (MWTS)  Boundary layer
           
作者中文名作者英文名单位
吴晓京WU Xiaojing国家卫星气象中心中国气象局中国遥感卫星辐射测量和定标重点开放实验室, 北京 100081
朱江ZHU Jiang中国科学院大气物理研究所国际气候与环境科学中心, 北京 100029
王曦WANG Xi国家卫星气象中心中国气象局中国遥感卫星辐射测量和定标重点开放实验室, 北京 100081
杨冰韵YANG Bingyun国家卫星气象中心中国气象局中国遥感卫星辐射测量和定标重点开放实验室, 北京 100081
引用:吴晓京,朱江,王曦,杨冰韵.2017.风云三号微波观测资料的海雾同化模拟[J].大气科学,41(3):421-436,doi:10.3878/j.issn.1006-9895.1610.16105.
Citation:WU Xiaojing,ZHU Jiang,WANG Xi,YANG Bingyun.2017.Sea Fog Simulation with Assimilation of FY-3A Microwave Data[J].Chinese Journal of Atmospheric Sciences (in Chinese),41(3):421-436,doi:10.3878/j.issn.1006-9895.1610.16105.
中文摘要:
      数值模式边界层物理过程和初值场条件的欠缺是海雾模拟准确率偏低的主要原因。本文为改进模式初始场,开展针对海雾模拟的卫星观测资料同化试验,将质量控制和偏差订正后的FY-3A卫星微波湿度计(MWHS)和微波温度计(MWTS)的优选通道数据,经3DVar(Three-dimensional variational data assimilation)进入WRF模式以试验其对黄、渤海海雾模拟的影响。通过分析静止气象卫星检测到的海雾区模拟大气温、湿场同化分析增量,发现代表环境场条件的海雾类型及模式对其模拟能力的差异,显著影响了同化效果,表现为同化对模式模拟能力较强的平流冷型海雾改进明显,对模拟效果不甚理想的非典型混合过程中的暖型海雾阶段则基本没有改进效果。为寻找原因,对包括海雾区低层大气模拟场逆温结构在内的温湿度场与邻近探空观测进行了对比,分析了随时间演变的海雾格点温、湿场同化分析增量,发现冷型海雾区格点同化分析增量能弥补观测—模拟差异,使气温调减,相对湿度调增,同时水汽和液态水也出现负相关的变化,边界层相关热力动力场同化分析增量在垂直方向也有配合迹象,相比而言,主体是暖型海雾的非典型过程则未见此类现象和其他的有益调整迹象。
Abstract:
      Inappropriate description of physical processes within the boundary layer and errors in the initial condition are two primary reasons for the low accuracy of sea fog simulation. In order to obtain more satellite data assimilation and simulation experience for improving the initial condition, the present paper investigates the impact of assimilation of FY-3A MicroWave Humidity Sounding (MWHS) and MicroWave Temperature Sounding (MWTS) data derived from optimal channels. The WRF-3DVar (Weather Research and Forecasting-Three-dimensional variational data assimilation) is applied to assimilate these data that have been quality controlled and bias corrected in simulation and prediction experiments of sea fog over the Yellow Sea and Bohai. Analysis of the increments of temperature and relative humidity from the assimilation system over the sea fog region detected by Geo-satellite indicates that differences in the model capability for sea fog simulation and various types of sea fog that are related to the environmental condition have significant influences on the assimilation effects, i.e. the model performance is greatly improved by assimilation for the simulation of cold-type advection sea fog, which the model already has a strong simulation ability. However, for warm-type sea fog that involves non-typical mixing processes, data assimilation results in little changes in the simulation. In order to determine the reasons, direct comparisons between the simulated temperature and relative humidity at a sea fog covered grid and standard rawinsonde observations nearby, and analysis of the evolution of the temperature and relative humidity and their increments from assimilation at all sea fog covered grids, are carried out. The results show that the increments from assimilation at the cold-type sea fog covered grids can make up the deviations between observations and simulation by reducing temperature and increasing relative humidity; meanwhile, the atmospheric water vapor and liquid water contents also appear to be adjusted by assimilation. Possible increments and adjustment in the boundary layer by assimilation are also found in the vertical direction. However, similar phenomena and other beneficial signs of adjustment are not found during the warm-type sea fog period.
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