Abstract
High-resolution synthetic aperture radar (SAR) wind observations provide fine structural information for tropical cycles and could be assimilated into numerical weather prediction (NWP) models. However, in the conventional method assimilating the u and v components for SAR wind observations (SAR_uv), the wind direction is not a state vector and its observational error is not considered during the assimilation calculation. In this paper, an improved method for wind observation directly assimilates the SAR wind observations in the form of speed and direction (SAR_sd). This method was implemented to assimilate the sea surface wind retrieved from Sentinel-1 synthetic aperture radar (SAR) in the basic three-dimensional variational system for the Weather Research and Forecasting Model (WRF 3DVAR). Furthermore, a new quality control scheme for wind observations is also presented. Typhoon Lionrock in August 2016 is chosen as a case study to investigate and compare both assimilation methods. The experimental results show that the SAR wind observations can increase the number of the effective observations in the area of a typhoon and have a positive impact on the assimilation analysis. The numerical forecast results for this case show better results for the SAR_sd method than for the SAR_uv method. The SAR_sd method looks very promising for winds assimilation under typhoon conditions, but more cases need to be considered to draw final conclusions.
Highlights
Sea surface wind is the primary power source for atmospheric movement over the ocean surface [1] and remarkably affects the air-sea exchange process
For SAR_sd assimilation, if we use the Quality Controlled corporately (QC_co) method for quality control, only observation 1 (OBS1) and observation 2 (OBS2) of the four observations are accepted in dir quality control, as their wind direction innovations are less than 100◦, like all the observations distributed in the right hand angle between the green boundary lines Boundary1 and
To investigate the impact of the assimilation of synthetic aperture radar (SAR) sea surface wind observations on the wind analysis at 10 m by the two different assimilation methods, the National Centers for Environmental Prediction (NCEP) final Design (FNL) data at 0900 UTC 29 August is used as the true wind field as the FNL data at the time of analysis time is of high accuracy [39]
Summary
Sea surface wind is the primary power source for atmospheric movement over the ocean surface [1] and remarkably affects the air-sea exchange process. The accuracy of sea surface wind data retrieved from SAR is comparable with scatterometer data [11,12], and these wind fields can be used with a data assimilation system to provide the initial conditions for the numerical weather prediction (NWP) model [13]. An improved method is proposed based on Huang et al, which can assimilate the SAR wind data under typhoon conditions. The impact of assimilation of SAR sea surface winds on the typhoon track and intensity will be examined using different methods.
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