Development of Indian summer monsoon precipitation biases in two seasonal forecasting systems and their response to large-scale drivers

Keane, Richard J.; Srivastava, Ankur; Martin, Gill M.

doi:https://doi.org/10.5194/wcd-5-671-2024

Articles | Volume 5, issue 2

https://doi.org/10.5194/wcd-5-671-2024

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

https://doi.org/10.5194/wcd-5-671-2024

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

Articles | Volume 5, issue 2

Research article

|

30 Apr 2024

Research article |

| 30 Apr 2024

Development of Indian summer monsoon precipitation biases in two seasonal forecasting systems and their response to large-scale drivers

Richard J. Keane, Ankur Srivastava, and Gill M. Martin

Data sets

GPM IMERG Final Precipitation L3 Half Hourly 0.1 degree x 0.1 degree V06 (GPM_3IMERGHH) GES DISC https://disc.gsfc.nasa.gov/datasets/GPM_3IMERGHH_06/summary

ERA5 hourly data on pressure levels from 1940 to present H. Hersbach et al. https://doi.org/10.24381/cds.bd0915c6

Historical BSISO text data IPRC https://iprc.soest.hawaii.edu/users/kazuyosh/ISO_index/data/BSISO_25-90bpfil_pc.extension.txt

Model code and software

NEMO ocean engine, Scientific Notes of Climate Modelling Center, 27, Institut Pierre-Simon Laplace (IPSL) NEMO System Team https://doi.org/10.5281/zenodo.1464816

CICE CICE-Consortium https://github.com/CICE-Consortium/CICE/wiki

Short summary

We evaluate the performance of two widely used models in forecasting the Indian summer monsoon, which is one of the most challenging meteorological phenomena to simulate. The work links previous studies evaluating the use of the models in weather forecasting and climate simulation, as the focus here is on seasonal forecasting, which involves intermediate timescales. As well as being important in itself, this evaluation provides insights into how errors develop in the two modelling systems.