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https://doi.org/10.5281/zenodo.14959025

A low-level turbulence-related parameters dataset derived from the radar wind profiler and radiosonde in China during 2023

A comprehensive dataset of low-level atmospheric turbulence-related parameters was developed through synergistic analysis of Radar Wind Profiler (RWP)  and radiosonde observations from 29 co-located meteorological stations across China in 2023. Utilizing spectral width method, this resource provides vertical profiles of turbulence-related parameters twice daily (at 00 and 12 UTC) with 120 m resolution across the altitude range of 0.12 to 3.0 km above ground level. It is essential for early warning of convective initiation and provides meteorological support for low-level economic activities. More details can be found in the readme.txt file. 



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A low-level turbulence-related parameters dataset derived from the radar wind profiler and radiosonde in China during 2023

https://doi.org/10.5281/zenodo.14959025

A comprehensive dataset of low-level atmospheric turbulence-related parameters was developed through synergistic analysis of Radar Wind Profiler (RWP)  and radiosonde observations from 29 co-located meteorological stations across China in 2023. Utilizing spectral width method, this resource provides vertical profiles of turbulence-related parameters twice daily (at 00 and 12 UTC) with 120 m resolution across the altitude range of 0.12 to 3.0 km above ground level. It is essential for early warning of convective initiation and provides meteorological support for low-level economic activities. More details can be found in the readme.txt file. 



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https://doi.org/10.5281/zenodo.14959025

A low-level turbulence-related parameters dataset derived from the radar wind profiler and radiosonde in China during 2023

A comprehensive dataset of low-level atmospheric turbulence-related parameters was developed through synergistic analysis of Radar Wind Profiler (RWP)  and radiosonde observations from 29 co-located meteorological stations across China in 2023. Utilizing spectral width method, this resource provides vertical profiles of turbulence-related parameters twice daily (at 00 and 12 UTC) with 120 m resolution across the altitude range of 0.12 to 3.0 km above ground level. It is essential for early warning of convective initiation and provides meteorological support for low-level economic activities. More details can be found in the readme.txt file. 

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      A low-level turbulence-related parameters dataset derived from the radar wind profiler and radiosonde in China during 2023
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      A comprehensive dataset of low-level atmospheric turbulence-related parameters was developed through synergistic analysis of Radar Wind Profiler (RWP)  and radiosonde observations from 29 co-located meteorological stations across China in 2023. Utilizing spectral width method, this resource provides vertical profiles of turbulence-related parameters twice daily (at 00 and 12 UTC) with 120 m resolution across the altitude range of 0.12 to 3.0 km above ground level. It is essential for early warning of convective initiation and provides meteorological support for low-level economic activities. More details can be found in the readme.txt file. 
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      A low-level turbulence-related parameters dataset derived from the radar wind profiler and radiosonde in China during 2023
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      A comprehensive dataset of low-level atmospheric turbulence-related parameters was developed through synergistic analysis of Radar Wind Profiler (RWP)  and radiosonde observations from 29 co-located meteorological stations across China in 2023. Utilizing spectral width method, this resource provides vertical profiles of turbulence-related parameters twice daily (at 00 and 12 UTC) with 120 m resolution across the altitude range of 0.12 to 3.0 km above ground level. It is essential for early warning of convective initiation and provides meteorological support for low-level economic activities. More details can be found in the readme.txt file. 
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