Evaluating the Impact of Data Assimilation on Atmospheric Tidal Modes
Brandon
diLorenzo
First Author's Affiliation
University of Colorado
Abstract text:
This study addresses the challenge of accurately capturing the dynamics of Earth’s upper atmosphere by exploring how data assimilation of space-based far ultraviolet (FUV) dayglow observations influence the representation of tidal modes in a whole atmosphere model. This poster presents comparisons of Whole Atmosphere Model (WAM) modeling results with and without ensemble data assimilation of GOLD FUV disk measurements of N2 Lyman-Birge-Hopfield (LBH) bands and discusses how a prior work by Cantrall (PhD thesis, 2022) can be extended with the help of different covariance localization techniques.
Poster PDF
diLorenzo-brandon.pdf
(1.24 MB)
Student in poster competition
Poster category
DATA - Data Assimilation, Data Analytics, Methods and Management