GDAS-Powered Machine Learning Weather Prediction: A Comparative Study on GraphCast initialized with GDAS States for Global Weather Forecasting

Sadegh Tabas; Jun Wang; Fanglin Yang; Jason Levit; Ivanka Stajner; Raffaele Montuoro; Vijay Tallapragada; Brian Gross

doi:https://doi.org/10.5194/egusphere-egu24-13889

[Back] [Session AS5.5]

EGU24-13889, updated on 09 Mar 2024

https://doi.org/10.5194/egusphere-egu24-13889

EGU General Assembly 2024

© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

GDAS-Powered Machine Learning Weather Prediction: A Comparative Study on GraphCast initialized with GDAS States for Global Weather Forecasting

Sadegh Tabas¹, Jun Wang², Fanglin Yang², Jason Levit², Ivanka Stajner², Raffaele Montuoro², Vijay Tallapragada², and Brian Gross²

Sadegh Tabas et al.

¹Axiom at NOAA/NWS/NCEP/EMC, College Park, MD, USA
²NOAA/NWS/NCEP/EMC, College Park, MD, USA

How to cite: Tabas, S., Wang, J., Yang, F., Levit, J., Stajner, I., Montuoro, R., Tallapragada, V., and Gross, B.: GDAS-Powered Machine Learning Weather Prediction: A Comparative Study on GraphCast initialized with GDAS States for Global Weather Forecasting, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13889, https://doi.org/10.5194/egusphere-egu24-13889, 2024.

This abstract has been withdrawn on 06 May 2024.