The Fusion Of Air-sea Elements Near Sea Surface And Its Application On Analysis Of Sea Fog At Night

With the establishment of a variety of meteorological and marine monitoring networks in China,the monitoring data and products are rapidly growth.Then how to effectively use a variety of massive multi-source monitoring data is becoming a hot research issue for China's meteorological and oceanic research and forecasting services.This study mainly discusses the fusion technolgy on the monitoring data of Chinese marine and meteorological satellites,and the air and sea monitoring data of coastal marine automation stations.Then to apply the technolgy and methods on the eastern part of China and the Yellow Sea and East Sea areas,especially to apply on visibility distribution of sea fog at night in the regions where there is no conventional monitoring network.The data fusion system used in the research is a local analysis and prediction system(LAPS)that developed by the ESRL(Earth System Research Laboratory),a laboratory of the National Oceanic and Atmospheric Administration(NOAA)in the United States.Multi-source data comes from different monitoring devices,with their own data formats,different spatial and temporal resolutions,different reading sequences and other non-uniform features.Therefore,a preprocessing includes various raw data quality controls and data preprocessing methods are done before the multi-source data are input into LAPS system for data fusion.In addition,the LAPS system itself also has special requirements for data input,so some designs of matching schemes are made for multi-source data and LAPS input channels according to data characteristics.The fusion analysis data processed by the LAPS system are verified to determine the rationality and adaptability of the fusion product.The eastern waters of the country are busy sea areas with economic activity.Due to the time-evolution characteristics of marine elements,such as tidal activity,they have caused the night to become active working hours for offshore engineering and shipping.Therefore,there is an increased demand for forecasting and early warning of atmospheric elements and special weather at night in the sea.There is no station monitoring network and no encryption stations at sea,and their monitoring elements are limited if there is any monitoring,such as buoy..Therefore,the full use of satellite information has become one of the research focuses.In this study,a series of multi-source variable data are preprocessed including the near-sea surface air temperature,sea surface temperature,humidity,wind field,and atmospheric pressure from the coastal station and the ocean satellites and meteorological satellites,then through fusion and verification,the coordinated,standardized,high-resolution fusion element products are obtained.Further,based on the multi-element data of the atmospheric temperature and humidity profile of the FY-3 A satellite,the inversion calculation on the low visibility distribution of the night fog are done,and the verification shows the result was satisfactory.Then a three scheme processing and comparison show that among the satellite data,reanalysis data,and fusion data of satellite and reanalysis data by the LAPS system,the fusion of satellite monitoring data and FNL reanalysis data are better than single source data as inversion of fog low visibility distribution has a better improvement effect.Specially,the distribution of sea fog and low visibility areas has been verified by mutual verification and information integration of FY-3A satellite data and numerical simulation products,and their credibility have been enhanced.The research methods and process procedures have practical application value and reference significance for forecasting and early warning.