11:00 〜 13:00
[AAS02-P04] A Comparison of Satellite and Reanalysis Wind Products with In-Situ Wave Glider and UAV Ocean Observations
キーワード：ウェーブグライダー、ドローン、海上風
Faster and more accurate weather forecasts are needed to mitigate the damage caused by extreme weather such as typhoons, linear rainbands, and localized torrential rains. It is considered that the prediction performance can be improved by using in-situ observation data in the ocean region closer to the extreme weather source or course. Previous studies have confirmed the effectiveness of attempts to obtain in-situ observation data to predict linear rainband and localized torrential rains and typhoons using dropsondes falling from aircraft.
Conventional studies show the differences between in-situ observed data such as Argo float or wave glider (WG) data with satellite and reanalysis data. However, in the comparison of data with different spatiotemporal resolutions, the comparison is made by resampling one side, but a two-way comparison is not made. In this study, we analyze the results of upsampling (linear interpolation) and downsampling (averaging). We evaluate the accuracy of various data with different spatiotemporal resolutions.
In this study, in-situ observation data of Sea Surface Wind speed (SSW) are acquired using Wave Glider SV2 (hereinafter WG) from Liquid Robotics Co., which has a track record of typhoon observation, and an unmanned aerial vehicle (UAV) PF-2 from Autonomous Control Systems Laboratory (ACSL) Ltd. Wind product SSW of GCOM-W1/AMSR-2 is used as satellite data, and the WRF model of PacIOOS as reanalysis data for comparison.
The accuracy of SSW at 10 meters above sea level was evaluated in a calm environment in this study. In the case of extreme weather, wind speeds higher than this observation data will be targeted. In the future, we aim to establish an extreme weather observation method for not only wind speed but also various meteorological and oceanographic data and verify the accuracy of extreme weather observation data.
Conventional studies show the differences between in-situ observed data such as Argo float or wave glider (WG) data with satellite and reanalysis data. However, in the comparison of data with different spatiotemporal resolutions, the comparison is made by resampling one side, but a two-way comparison is not made. In this study, we analyze the results of upsampling (linear interpolation) and downsampling (averaging). We evaluate the accuracy of various data with different spatiotemporal resolutions.
In this study, in-situ observation data of Sea Surface Wind speed (SSW) are acquired using Wave Glider SV2 (hereinafter WG) from Liquid Robotics Co., which has a track record of typhoon observation, and an unmanned aerial vehicle (UAV) PF-2 from Autonomous Control Systems Laboratory (ACSL) Ltd. Wind product SSW of GCOM-W1/AMSR-2 is used as satellite data, and the WRF model of PacIOOS as reanalysis data for comparison.
The accuracy of SSW at 10 meters above sea level was evaluated in a calm environment in this study. In the case of extreme weather, wind speeds higher than this observation data will be targeted. In the future, we aim to establish an extreme weather observation method for not only wind speed but also various meteorological and oceanographic data and verify the accuracy of extreme weather observation data.