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Assessment of extreme seasonal rainfall over India in current seasonal coupled models during the recent period

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Abstract

The present study analyses the performance of recent seasonal prediction coupled models in simulate the seasonal extremes (June through September) over the India using February and May initializations (hear after FEBIC & MAYIC) for a period of 1981–2018. All the models show significant seasonal dry bias over the northern and western coast of Indian regions (associated with northerly wind bias at lower troposphere), whereas strong wet bias over the southeastern India which is associated with cyclonic circulation (at 850 hPa) over the central Bay of Bengal. CFSv2 hindcasts has more dry bias over India for FEBIC due to strong northerly wind bias over the Northern India and strong cyclonic circulation over the North West Pacific, whereas, that dry bias is reduced significantly over the Northern Indian region in all the models except GEM-NEMO in MAYIC. CFSv2 reproduces the orographic rainfall over the west coast and northeastern parts of India in both leads. The models are not able to reproduced the extreme years that are associated with El Niño, Indian Ocean Dipole and Atlantic Niño boundary forcing (BF), while the observed normal years which co-occur with these BF are represented as excess years in the models. Categorical skill scores suggest that, all the models can capture the normal years only as similar to observations whereas deficient and excess years have more false alarms mainly due to the misrepresentation of ascending and descending branches of the Walker circulation over the tropics during the extreme years.

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Availability of data and material

Three NMME model outputs are downloaded from the IRI website (http://iridl.ldeo.columbia.edu/SOURCES/.Models/.NMME). The IMD gridded is free avaible in online. SST from OISST (https://www.psl.noaa.gov/data/gridded/data.noaa.oisst.v2.html), Gobal rainfall from GPCP (https://psl.noaa.gov/data/gridded/data.gpcp.html) and monthly wind at 850 hPa obtained from ERA-5 reanalysis (https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-pressure-levels-monthly-means?tab=overview). CFSv2 model data is available from the corresponding author on reasonable request. The above datasets generated during and/or analysed during the current study.

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Acknowledgements

The Indian Institute of Tropical Meteorology (IITM) is fully supported by the Ministry of Earth Sciences (MoES), Government of India. The aucthors thank Ankur Srivastav of IITM for his help in performing CFSv2-T382 hindcasts data. All the NMME model outputs are downloaded from the IRI website (http://iridl.ldeo.columbia.edu/SOURCES/.Models/.NMME). The plots are made using Ferret. We also thank ECMWF (https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era-interim/) for providing the reanalysis data sets. All the data sources are duly acknowledged. Two anonymous reviewers are acknowledged for their insightful comments and suggestions for the improvement of the manuscript.

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Authors and Affiliations

  1. Ministry of Earth Sciences, Indian Institute of Tropical Meteorology, Dr. HomiBhabha Road, Pashan, Pune, 411008, Maharashtra, India

    Dandi A. Ramu, Ashish R. Dhakate, Prasanth A. Pillai, Rambabu G, P. Sreenivas & T. S. Saikrishna

  2. Department of Meteorology and Oceanography, Andhra University, Visakhapatnam, India

    Rambabu G

  3. Department of Earth and Atmospheric Sciences, National Institute of Technology Rourkela, Odisha, 769008, India

    T. S. Saikrishna

  4. Department of Atmospheric and Space Sciences, Savitribai Phule University, Pune, India

    Ashish R. Dhakate

  5. Center for Earth Ocean and Atmospheric Sciences, School of Physics, University of Hyderabad, Hyderabad, India

    P. Sreenivas

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  1. Dandi A. Ramu
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Contributions

All authors contributed to the study conception and design. Ideas are conceived by DAR and data collection and analysis were performed by AD, RG. DAR wrote the initial manuscript. All authors PSP, PS and TSS contributed to interpreting results and improved the manuscript. All authors read and approved the fnal manuscript.

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Appendix: The Comoposte analysis for excess and deficient years over Indain land region only

Appendix: The Comoposte analysis for excess and deficient years over Indain land region only

To see how recent seasonal prediction models ability to simulate extreme rainfall events only over Indian land mass compared to the observation in the Appendix. Here, spatial distribution of rainfall anomalies are well reproduced by CFSv2 model (PC = 0.42) than other models (PC are close to zero or negative also) by FEBCI, whereas NMME models (PC are around 0.6) remarkably simulate the rainfall anomalies over Indian land with MAYIC during the excess years except CanCM4i (PC = 13) and CFSv2 (PC = − 0.37; Fig. 17 ). Similarly, from Fig. 18, CFSv2 model is able to simulate the spatial pattern of deficient rainfall anomalies with FEBIC (PC = 0.50) than MAYIC (PC = 0.26), whereas NMME models are better captured horizontal distribution of rainfall anomalies over Indian region (PC ~ 0.75) except (CanCM4i; PC ~ 0.6; Fig. 18).

Fig. 17
figure 17

The composite of excess year’s rainfall anomalies over Indian land region with significant 90% and Pattern correlation values are placed over the plot as PC

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Fig. 18
figure 18

The composite of deficient year’s rainfall anomalies over Indian land region with significant 90% and Pattern correlation values are placed over the plot as PC

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Ramu, D.A., Dhakate, A.R., Pillai, P.A. et al. Assessment of extreme seasonal rainfall over India in current seasonal coupled models during the recent period. Clim Dyn 61, 461–487 (2023). https://doi.org/10.1007/s00382-022-06599-1

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