Abstract
Documentation of the skill of a prediction system and its comparison with those of leading modelling centres are crucial in model development. This facilitates understanding the limitations of the existing prediction system and aids in its improvement. The current study compares the extended range prediction skill of the Indian Institute of Tropical Meteorology (IITM) generated real-time forecast with that of the UK Met Office (UKMO) forecast during the boreal summer monsoon season. It is found that both models suffer from biases in the climatological mean state of the monsoon. IITM forecast possesses a skill comparable to UKMO coupled seasonal forecast as compared to the observation in the first two weeks leads over most of the meteorological subdivisions during the monsoon months of June to September. However, at longer leads, the UKMO model outperforms the IITM model, which could be credited to its enhanced skill in predicting the monsoon intraseasonal oscillations and the better representation of monsoon variability at the intraseasonal time scale.
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Funds availability
This work is done under the WCSSP-India Project, and with the exception of GMM, the authors have not received any funding for this.
Data and code availability
The observational datasets used for this study are available free from the respective websites (i) the daily IMD rainfall dataset from http://www.imdpune.gov.in/Clim_Pred_LRF_New/Grided_Data_Download.html (Pai et al. 2021), and (ii) atmospheric fields from the National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis datasets https://psl.noaa.gov/data/gridded/data.ncep.reanalysis.html (Kalnay et al. 1996). The GloSea5 and IITM model outputs used in this study are archived at the UK Met Office and IITM, Pune. These as well as the codes used are available to research collaborators upon reasonable request for scientific purposes.
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Acknowledgements
We express gratitude to the Director, IITM, for all the support in carrying out this work. The Ministry of Earth Sciences (MoES), under the Government of India supports IITM. This work, and the contribution by GM Martin, was conducted through the Weather and Climate Science for Service Partnership (WCSSP) India, a collaborative initiative between the Met Office, supported by the UK Government’s Newton Fund, and MoES. We thank NCEP/NCAR, NOAA, and IMD for freely providing the observational data. The free plotting software, GrADS (available at http://iges.org/grads/) and GRACE, and free writing assistant Grammarly are duly acknowledged. Special thanks to Dr Manpreet Kaur for proofreading the initial draft. We sincerely thank the Editor and two anonymous reviweres for their insightful and constructive comments, which helped considerably in improving the scientific content of our work.
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The study was conceptualised by Susmitha Joseph, Rajib Chattopadhyay and AK Sahai. The GloSea5 model data was provided by Gill M Martin as part of the WCSSP-India Project. Material preparation and analysis were performed by Susmitha Joseph and Rajib Chattopadhyay. Avijit Dey, Raju Mandal and R Phani contributed to the IITM model runs. Susmitha Joseph wrote the initial draft of the manuscript, and all authors commented on previous versions of the manuscript. All authors have read and approved the final manuscript.
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Joseph, S., Chattopadhyay, R., Sahai, A.K. et al. Evaluation and comparison of the subseasonal prediction skill of Indian summer monsoon in IITM CFSv2 and UKMO GloSea5. Clim Dyn 61, 1683–1696 (2023). https://doi.org/10.1007/s00382-022-06650-1
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DOI: https://doi.org/10.1007/s00382-022-06650-1