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RSS FeedsRemote Sensing, Vol. 10, Pages 825: Airborne Doppler Wind Lidar Observations of the Tropical Cyclone Boundary Layer (Remote Sensing)

 
 

4 june 2018 18:02:57

 
Remote Sensing, Vol. 10, Pages 825: Airborne Doppler Wind Lidar Observations of the Tropical Cyclone Boundary Layer (Remote Sensing)
 


This study presents a verification and an analysis of wind profile data collected during Tropical Storm Erika (2015) by a Doppler Wind Lidar (DWL) instrument aboard a P3 Hurricane Hunter aircraft of the National Oceanic and Atmospheric Administration (NOAA). DWL-measured winds are compared to those from nearly collocated GPS dropsondes, and show good agreement in terms of both the wind magnitude and asymmetric distribution of the wind field. A comparison of the DWL-measured wind speeds versus dropsonde-measured wind speeds yields a reasonably good correlation (r2 = 0.95), with a root mean square error (RMSE) of 1.58 m s-1 and a bias of -0.023 m s-1. Our analysis shows that the DWL complements the existing P3 Doppler radar, in that it collects wind data in rain-free and low-rain regions where Doppler radar is limited for wind observations. The DWL observations also complement dropsonde measurements by significantly enlarging the sampling size and spatial coverage of the boundary layer winds. An analysis of the DWL wind data shows that the boundary layer of Erika was much deeper than that of a typical hurricane-strength storm. Streamline and vorticity analyses based on DWL wind observations explain why Erika maintained intensity in a sheared environment. This study suggests that DWL wind data are valuable for real-time intensity forecasts, basic understanding of the boundary layer structure and dynamics, and offshore wind energy applications under tropical cyclone conditions.


 
98 viewsCategory: Geology, Physics
 
Remote Sensing, Vol. 10, Pages 827: The Impact of Hurricane Maria on the Vegetation of Dominica and Puerto Rico Using Multispectral Remote Sensing (Remote Sensing)
Remote Sensing, Vol. 10, Pages 826: A New Single-Band Pixel-by-Pixel Atmospheric Correction Method to Improve the Accuracy in Remote Sensing Estimates of LST. Application to Landsat 7-ETM+ (Remote Sensing)
 
 
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