A New Observation Operator for the Assimilation of Satellite-Derived Relative Humidity: Methodology and Experiments with Three Sea Fog Cases over the Yellow Sea

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 Method-t, Method-RH enlarges the sea fog areas by increasing the amount of moisture in addition to the cooling.