Articles | Volume 15, issue 13
Atmos. Meas. Tech., 15, 3925–3940, 2022
https://doi.org/10.5194/amt-15-3925-2022

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

Atmos. Meas. Tech., 15, 3925–3940, 2022
https://doi.org/10.5194/amt-15-3925-2022
Research article
05 Jul 2022
Research article | 05 Jul 2022

A statistically optimal analysis of systematic differences between Aeolus horizontal line-of-sight winds and NOAA's Global Forecast System

Hui Liu et al.

Data sets

Aeolus L2B Earth Explorer data set European Space Agency (ESA) https://aeolus-ds.eo.esa.int/oads/access/

Model code and software

Preliminary code of Aeolus wind assimilation with NOAA GSI H. Liu, K. Garrett, K. Ide, and R.-N. Hoffman https://essic.umd.edu/joom2/index.php/faculty-and-staff?layout=user&user_id=1020&dir=JSROOT%2Fhliu6/CODE

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Short summary
A total least squares (TLS) regression is used to optimally estimate linear speed-dependent biases between Aeolus Level-2B winds and short-term (6 h) forecasts of NOAA’s FV3GFS. The winds for 1–7 September 2019 are examined. Clear speed-dependent biases for both Mie and Rayleigh winds are found, particularly in the tropics and Southern Hemisphere. Use of the TLS correction improves the forecast of the 26–28 November 2019 winter storm over the USA.