High Resolution 3D Winds Derived from a Newly Developed WISSDOM Synthesis Scheme using Multiple Doppler Lidars and Observations

Abstract

Abstract. A WISSDOM (Wind Synthesis System using Doppler Measurements) synthesis scheme was developed to derive high-resolution 3-dimensional (3D) winds under clear-air conditions. From this variational-based scheme, detailed wind information was obtained from scanning Doppler lidars, automatic weather stations (AWSs), sounding observations, and local reanalysis datasets (LDAPS, Local Data Assimilation and Prediction System), which were utilized as constraints to minimize the cost function. The objective of this study is to evaluate the performance and accuracy of derived 3D winds from this newly developed scheme. A strong wind event was selected to demonstrate its performance over complex terrain in Pyeongchang, South Korea. The size of the test domain is 12 × 12 km2 extended up to 3 km height mean sea level (MSL) with remarkably high horizontal and vertical resolution of 50 m. The derived winds reveal that reasonable patterns were explored from a control run, as they have high similarity with the sounding observations. The results of intercomparisons show that the correlation coefficients between derived horizontal winds and sounding observations are 0.97 and 0.87 for u- and v-component winds, respectively, and the averaged bias (root mean square deviation, RMSD) of horizontal winds is between −0.78 and 0.09 (1.72 and 1.65) m s−1. The correlation coefficients between WISSDOM-derived winds and lidar QVP (quasi-vertical profile) are 0.84 and 0.35 for u- and v-component winds, respectively, and the averaged bias (RMSD) of horizontal winds is between 2.83 and 2.26 (3.69 and 2.92) m s−1. The statistical errors also reveal a satisfying performance of the retrieved 3D winds; the median values of wind directions are −5~5 (0~2.5) degrees, the wind speed is approximately −1~3 m s−1 (−1~0.5 m s−1) and the vertical velocity is −0.2~0.6 m s−1 compared with the lidar QVP (sounding observations). A series of sensitivity tests with different weighting coefficients, radius of influence (RI) in interpolation and various combination of different datasets were also performed, and the results indicate that the present setting of the control run is the best reference to WISSDOM synthesis in this event.