Abstract
Atmospheric wind is an essential parameter in the global observing system. In this study, the water vapor field in Typhoon Lekima and its surrounding areas simulated by the Weather Research and Forecasting (WRF) model is utilized to track the atmospheric motion wind through the Farneback Optical Flow (OF) algorithm. A series of experiments are conducted to investigate the influence of temporal and spatial resolutions on the errors of tracked winds. It is shown that the wind accuracy from tracking the specific humidity is higher than that from tracking the relative humidity. For fast-evolving weather systems such as typhoons, the shorter time step allows for more accurate wind retrievals, whereas for slow to moderate evolving weather conditions, the longer time step is needed for smaller retrieval errors. Compared to the traditional atmospheric motion vectors (AMVs) algorithm, the Farneback OF wind algorithm achieves a pixel-wise feature tracking and obtains a higher spatial resolution of wind field. It also works well under some special circumstances such as very low water vapor content or the region where the wind direction is parallel to the moisture gradient direction. This study has some significant implications for the configuration of satellite microwave sounding missions through their derived water vapor fields. The required temporal and spatial resolutions in the OF algorithm critically determine the satellite revisiting time and the field of view size. The brightness temperature (BT) simulated through Community Radiative Transfer Model (CRTM) is also used to track winds. It is shown that the error of tracking BT is generally larger than that of tracking water vapor. This increased error may result from the uncertainty in simulations of brightness temperatures at 183 GHz.
Highlights
The fast and accurate global 3D wind field measurements are required for improving the global forecasting as well as for utilizing wind energy and achieving sustainable energy supply [1,2]
We select four layers of 850, 500, 300, and 100 hPa for analysis as the experiment results indicate that atmospheric motion vectors (AMVs) sensitivity to the FOV sizes has obvious vertical characteristics
The Weather Research and Forecasting (WRF) wind fields of 850, 500, 300, and 100 hPa are shown as Figure 5a,c,e,g, respectively
Summary
The fast and accurate global 3D wind field measurements are required for improving the global forecasting as well as for utilizing wind energy and achieving sustainable energy supply [1,2]. Satellite wind measurement technology is widely explored to obtain the global wind field. Two types of satellite technologies are explored for atmospheric wind measurements. The active sensors such as scatterometers are well-developed for obtaining the ocean surface wind field and the Atmospheric Laser Doppler Instrument (ALADIN). Onboard the Aeolus mission provides the horizontal wind components at sub-satellite points [5,6,7]. The atmospheric motion vector (AMV) can be derived through tracking the movement of cloud or water vapor in sequences of satellite images and calculating the direction and distance of movement. The AMV technology has provided the upper-air wind observations and filled the gaps in the observation field [8]. Many studies were made to assimilate the AMVs into numerical weather prediction (NWP) models and show a positive impact on the weather forecasts [3,9,10,11,12]
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