[A-CG41] Satellite Earth Environment Observation

[ACG41-P19] Simulation and Evaluation of Wind Observation Performance of Satellite-based Coherent Doppler Wind Lidar using Linear Error Analysis

*MERU MIYAO¹, Shoken Ishii¹, Hideki Takenaka¹, Izumi Okabe², Syugo Hayashi², Kozo OKAMOTO² (1.Tokyo Metropolitan University , 2.Meteorological Research Institute of Japan Meteorological Agency)

Keywords:Earth Observation System, Doppler wind lidar, lidar simulator, linear error analysis, wind measurement performance

Earth observation satellites are important infrastructure for continuously monitoring essential climate variables, which is vital for ensuring sustainable coexistence and prosperity with the natural environment. The purpose of EOS is not only to understand and respond to long-term changes in the global environment such as extreme weather events and improvement of environmental problems but also to improve economic activities such as industry and transportation operations. The World Meteorological Organization (WMO) with meteorological agencies of each country is promoting the Global Atmosphere Watch, and various meteorological elements collected will be provided to the meteorological agencies, and researchers for the numerical weather prediction (NWP) and other applications. One of current satellite-based wind observation systems is the atmospheric tracking wind system, which has problems with the accuracy of height estimation and vertical resolution and has not been able to meet the user observation requirements of the WMO. Japanese working group is conducting the feasibility study of a satellite-based coherent Doppler wind lidar (SCDWL), which would significantly contribute to improving the accuracy of NWP forecasts. In this paper, we investigate how close the observed values by SCDWL can be to the background values by the existing models using the method of linear error analysis, and evaluate wind measurement performance of the SCDWL. Linear error analysis is a method for obtaining optimal estimates (analytical values by weighted average) from a priori information (background values) such as models and information obtained by observation (observed values). The ratio of the analysis error variance to the background error variance is defined as the Relative Error Reduction (RER) score, which is the ratio of how much the line-of-sight wind speed error has changed from the model by the analysis. The smaller this value is, the more significant the error reduction due to the analysis, suggesting that the analysis value can be obtained closer to the actual value. In this paper, the backscatter coefficient and wind velocity field were constant at each altitude, giving a one-dimensional model. The analytical error obtained from the simulation is smaller than the background and observed errors, confirming that adding the observed values to the model and performing a linear error analysis can provide a more accurate value than the first estimate. Further details will be described on the day of the presentation.