Exploiting Aeolus level-2b winds to better characterize atmospheric motion vector bias and uncertainty

Lukens, Katherine E.; Ide, Kayo; Garrett, Kevin; Liu, Hui; Santek, David; Hoover, Brett; Hoffman, Ross N.

doi:https://doi.org/10.5194/amt-15-2719-2022

Articles | Volume 15, issue 9

https://doi.org/10.5194/amt-15-2719-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

Aeolus data and their application (AMT/ACP/WCD inter-journal...

https://doi.org/10.5194/amt-15-2719-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 15, issue 9

Research article

|

06 May 2022

Research article |

| 06 May 2022

Exploiting Aeolus level-2b winds to better characterize atmospheric motion vector bias and uncertainty

Katherine E. Lukens, Kayo Ide, Kevin Garrett, Hui Liu, David Santek, Brett Hoover, and Ross N. Hoffman

Data sets

Aeolus L2B Earth Explorer data set ESA https://aeolus-ds.eo.esa.int/oads/access/

Short summary

Winds that are crucial to weather forecasting derived from two different techniques – tracking satellite images (AMVs) and direct measurement of molecular and aerosol motions by Doppler lidar (Aeolus satellite winds) – are compared. We find that AMVs and Aeolus winds are highly correlated. Aeolus Mie-cloudy winds have great potential value as a comparison standard for AMVs. Larger differences are found in the Southern Hemisphere related to higher wind speed and higher vertical variation in wind.