Session 7 Next-Generation Observations of Atmospheric Winds

Tuesday, 30 January 2024: 1:45 PM-3:00 PM
Key 9 (Hilton Baltimore Inner Harbor)
Host: 28th Conference on Integrated Observing and Assimilation Systems for the Atmosphere, Ocean, and Land Surface
Cochairs:
Sara C. Tucker, Ph.D., Ball Aerospace, Boulder, CO and Xuanli Li, NCEP, EMC/MDAB, College Park, MD

The need for very accurate wind observations has long been a high priority in the science community, as they have been shown to lead to increased skill in retrieving and assimilating, e.g., atmospheric motion vector (AMV) winds from space-based passive sounding and imaging instruments. However, in the current Earth observing architecture there remains a gap in direct wind observations, e.g., in the upper troposphere/lower stratosphere. To help fill this gap and address the need for highly accurate winds, ongoing international efforts are assessing the value and potential of observed winds using innovative technology, such as active wind lidar (like Aeolus) and machine learning, and include data assimilation, impact assessments, and direct wind measurement comparisons with other wind observations, including radiosondes, airborne and ground-based Doppler lidars, and those derived from satellite imagery (AMVs).

In August 2018 the European Space Agency (ESA) launched the first space-based Doppler wind lidar (DWL) onboard Aeolus in order to acquire 3D profiles of wind on a global scale. Since then, the mission has consistently provided global wind profiles and corresponding aerosol data products for research endeavors and operations. Several weather forecast centers including the European Centre for Medium-Range Weather Forecasts (ECMWF), Deutscher Wetterdienst, Météo-France, and the U.K. MetOffice, are operationally assimilating Aeolus wind observations and demonstrating their positive impact on forecast skill.

This session seeks presentations on the following: (a) activities including field campaigns involving ESA’s Aeolus wind observations, or those observed using other innovative technology; (b) impact assessment of assimilated wind observations; (c) studies using machine learning to improve wind forecasts; (d) methods to combine active and passive observations of 3D winds to increase the positive impact of both on forecast skill; (e) OSSE study results related to active and passive atmospheric wind observations; and (e) objectives and roadmaps for future Aeolus and other wind-related missions.

Papers:
1:45 PM
7.1
Assimilation of EUMETSAT IASI 3D wind product in the Navy Global Environmental Model
Brian Kenneth Blaylock, US Naval Research Laboratory, Marine Meteorology, Monterey, CA; and D. Tyndall and P. Pauley

2:00 PM
7.2
Preliminary Impact of Aeolus Doppler Wind Lidar on Forecasts from NCEP's Global Forecast System
Michael J. Mueller, UCAR, Boulder, CO; and A. Lim, S. P. F. Casey, and L. Cucurull

2:30 PM
7.4
System for Analysis of Wind Collocations (SAWC): A Novel Archive and Collocation Software Application for the Intercomparison of Winds from Multiple Observing Platforms
Katherine E. Lukens, UMD/CISESS and NOAA/NESDIS/STAR, College Park, MD; and K. Garrett, K. Ide, D. Santek, B. Hoover, D. Huber, R. N. Hoffman, and H. Liu

2:45 PM
7.5
Impact of Assimilating AMV Winds Using a Variational Feature Track Correction (VarFTC)
Ross N. Hoffman, NOAA, Cambridge, MA; and H. Liu, K. E. Lukens, K. Garrett, and K. Ide

Handout (6.2 MB)

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