Assimilation of satellite-derived relative humidity(Satellite-RH)is capable of improving sea fog forecasts by saturating the background in the observed foggy areas.Previous studies have achieved saturation by increasi...Assimilation of satellite-derived relative humidity(Satellite-RH)is capable of improving sea fog forecasts by saturating the background in the observed foggy areas.Previous studies have achieved saturation by increasing the moisture only(Method-q).However,this method can lead to large wetting and warming biases within the marine atmospheric boundary layer(MABL).A new method using an RH observation operator(Method-RH)is designed to alleviate these biases by simultaneously adjusting the moisture and the temperature.For comparison,saturation is also achieved by decreasing the temperature only(Method-t).The three Satellite-RH assimilation methods are implemented within the Gridpoint Statistical Interpolation-based three-dimensional variational system and examined for three sea fog cases over the Yellow Sea.The three cases on 28 April 2007,9 April 2009,and 29 March 2015 fail to be predicted without the Satellite-RH assimilation as their MABLs have both warming and drying,drying,and warming biases,respectively.Intercomparisons and evaluations show that Method-RH has the best overall performance of the three methods in terms of the forecast of sea fog and MABL structures as only Method-RH can fully or partially address all the bias scenarios in forecasting sea fog.Compared with Method-q,Method-RH produces more well-defined sea fog areas by adding a smaller amount of moisture as well as decreasing the temperature.Compared with Methodt,Method-RH enlarges the sea fog areas by increasing the amount of moisture in addition to the cooling.展开更多
基金Supported by the National Natural Science Foundation of China(42075069)Key Research and Development Program of Shandong Province(2019GSF111066)。
文摘Assimilation of satellite-derived relative humidity(Satellite-RH)is capable of improving sea fog forecasts by saturating the background in the observed foggy areas.Previous studies have achieved saturation by increasing the moisture only(Method-q).However,this method can lead to large wetting and warming biases within the marine atmospheric boundary layer(MABL).A new method using an RH observation operator(Method-RH)is designed to alleviate these biases by simultaneously adjusting the moisture and the temperature.For comparison,saturation is also achieved by decreasing the temperature only(Method-t).The three Satellite-RH assimilation methods are implemented within the Gridpoint Statistical Interpolation-based three-dimensional variational system and examined for three sea fog cases over the Yellow Sea.The three cases on 28 April 2007,9 April 2009,and 29 March 2015 fail to be predicted without the Satellite-RH assimilation as their MABLs have both warming and drying,drying,and warming biases,respectively.Intercomparisons and evaluations show that Method-RH has the best overall performance of the three methods in terms of the forecast of sea fog and MABL structures as only Method-RH can fully or partially address all the bias scenarios in forecasting sea fog.Compared with Method-q,Method-RH produces more well-defined sea fog areas by adding a smaller amount of moisture as well as decreasing the temperature.Compared with Methodt,Method-RH enlarges the sea fog areas by increasing the amount of moisture in addition to the cooling.
