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.
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.
the Creative Commons Attribution 4.0 License.
Research article
| 
30 Apr 2024
Research article |
| 30 Apr 2024
| 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
CORRESPONDING AUTHOR
Met Office, Exeter, UK
School of Earth and Environment, University of Leeds, Leeds, UK
Ankur Srivastava
Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, Pune, India
Gill M. Martin
Met Office, Exeter, UK
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GC5 is the Met Office's newest climate and weather model, combining an updated atmosphere/land component with an improved ocean and sea-ice component. Compared to its predecessor GC4, it better simulates global temperatures, winds, monsoons over India and SE Asia, and African weather, and forecasts tropical cyclones more accurately. Southern Ocean errors shrank too. Some tropical patterns and regional biases worsened slightly. A lower-resolution version will underpin the UK's Earth System Model.
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GC5 is the Met Office's newest climate and weather model, combining an updated atmosphere/land component with an improved ocean and sea-ice component. Compared to its predecessor GC4, it better simulates global temperatures, winds, monsoons over India and SE Asia, and African weather, and forecasts tropical cyclones more accurately. Southern Ocean errors shrank too. Some tropical patterns and regional biases worsened slightly. A lower-resolution version will underpin the UK's Earth System Model.
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This study documents the dynamics behind the first occurrence of a multi-year negative Indian Ocean Dipole since the 1960s, which lasted for an unprecedented 19 months, and co-occurred with the triple-dip La Niña event of 2020–2022. The co-occurrence of such extremes is rare and can exacerbate the associated climate risk. We find that Indian Ocean conditions limited the impact of La Niña on the Indian Summer Monsoon, preventing excessive monsoonal rainfall.
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Using sensitivity experiments, we show that model errors developing in the Maritime Continent region contribute substantially to the Asian summer monsoon (ASM) circulation and rainfall errors through their effects on the western North Pacific subtropical high-pressure region and the winds and sea surface temperatures in the equatorial Indian Ocean, exacerbated by local coupled feedback. Such information will inform future model developments aimed at improving model predictions for the ASM.
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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.
We evaluate the performance of two widely used models in forecasting the Indian summer monsoon,...
