EGU26-12477, updated on 14 Mar 2026
https://doi.org/10.5194/egusphere-egu26-12477
EGU General Assembly 2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Oral | Thursday, 07 May, 11:05–11:15 (CEST)
 
Room -2.15
Data-driven seasonal weather forecast: An application to the Indian summer monsoon rain
Tamas Bodai
Tamas Bodai
  • Hungarian University of Agriculture and Life Sciences, Budapest, Hungary (bodai.tamas@uni-mate.hu)

I present a data-driven forecast system applied to the Indian summer monsoon rain. By forecasting pentads, 5-day rain totals, the system is well suited to forecasting the monsoon onset/withdrawal as well as its progression, also known as intra-seasonal variability. I will provide a comparison of the forecast skill with those of other systems, both physics-based NWP and AI systems. The skill of the JJA seasonal forecast issued on 1 May in terms of the Pearson correlation coefficient far surpasses that of GLOSEA5. I will also discuss delicate questions about forecast skill, as to what is concepotually sound and what can be computed.

How to cite: Bodai, T.: Data-driven seasonal weather forecast: An application to the Indian summer monsoon rain, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12477, https://doi.org/10.5194/egusphere-egu26-12477, 2026.