FY-3A卫星近海面气象要素在冬季夜间海上能见度分析中的应用

对FY-3A气象卫星大气温度湿度廓线资料进行夜间大雾低能见度分布反演计算,并运用美国LAPS(Local Analysis and Prediction System)局地分析与预报系统,与FNL再分析资料多要素反演数据进行多源要素融合分析。FY-3A卫星反演得到的大雾低能见度分布,经与Micaps(Meteorological Information Comprehensive Analysis and Process System)系统地面天气图, FY-2E地球同步卫星红外云图,要素统计气象年鉴记录等对比检验,显示反演的低能见度区范围及强度合理。尤其是对海上缺乏常规观测资料网的海域,提供了夜间海上能见度分布信息。进一步地通过LAPS系统对比卫星资料、再分析资料、以及卫星与再分析资料融合的3种方案结果,显示将卫星监测资料与FNL再分析资料的融合效果,对单来源资料反演的大雾低能见度分布有较好的改善。融合后对卫星资料而言,卫星轨道盲区已经弥合,其次,获得了海上低能见度区分布的信息,对海上和沿海雾区能见度的强度得到合理改善。对于FNL再分析资料,原有的各项要素强梯度被合理平滑。低能见度范围也有调整改善。重要的是海上大雾低能见度区的分布,得到FY-3A卫星信息和数值模拟信息的互相验证与信息综合,可信度增强。

Application of meteorological elements near the sea surface of the FY-3A satellite on the visibility analysis at nighttime in winter

The inversion calculation of the atmospheric visibility data of the FY-3A meteorological satellite was performed in this paper. The LAPS (Local Analysis and Prediction System) of the United States was used to calculate the inversion of the visibility data of the night fog and the multi-element inversion of the FNL reanalysis data. Data was analyzed by multi-source feature fusion. The low-visibility distribution of fog resulting from the inversion of FY-3A satellite was compared with the weather map of the Micaps (Meteorological Information Comprehensive Analysis and Process System) system, the infrared cloud map of the FY-2E geosynchronous satellite, and the statistical yearbook of the elemental statistics, showing that the range and intensity of the invisible low visibility area were reasonable. In particular, the absence of conventional observational data networks in the sea areas provided information on the distribution of visibility at night. Through the LAPS system comparison of satellite data, reanalysis data, and satellite and reanalysis data fusion results, the fusion effect of the satellite monitoring data and the FNL reanalysis data was shown, bringing a better improvement on the fog low visibility distribution retrieved from single-source data. After the fusion, the satellite orbital blind area had been bridged for satellite data. Secondly, information on the distribution of low-visibility areas at sea had been obtained, and the visibility of the sea and coastal fog areas had been reasonably improved. For FNL reanalysis data, the strong gradients of the original elements were reasonably smoothed. The scope of low visibility had also been improved. The distribution of low-visibility areas in the sea fog was vital, and the mutual verification and information integration of numerical simulations and FY-3A satellite information were obtained and the credibility was enhanced. Therefore, LAPS data fusion effect is worthy of recognition, and it has good reference value for forecasting and early warning.