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Calibrated probabilistic sub-seasonal forecasting for Pakistan’s monsoon rainfall in 2022

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Abstract

In 2022, a record-breaking monsoon caused flooding throughout Pakistan, particularly in the southern regions, resulting in deaths, property losses, and severe crop damage, affecting the food supply chain that could last for years. This study assesses the accuracy of sub-seasonal calibrated probabilistic rainfall forecasts for Pakistan. The evaluation focuses on forecasts initialized throughout the summer monsoon season (June–September) and utilizes the European Center for Medium Range Forecast (ECMWF) ensemble prediction system. Forecasts are calibrated using a canonical correlation analysis (CCA) and evaluated using cross-validated hindcasts from 2002 to 2021. The calibrated hindcasts exhibit positive ranked probability skill score and are reliable for weeks 1 (days 1–7), 2 (days 8–14), and 3 – 4 (days 15–28), lead times. In the extraordinary monsoon season of 2022, tercile-category probabilistic forecasts provided useful information up to 4 weeks ahead. Furthermore, the occurrences of intense monsoon rainfall in the highly affected southern region of Pakistan were forecasted reasonably well up to 2 weeks in advance. The ECMWF model's ability to predict sub-seasonal monsoon rainfall in Pakistan during 2022 is attributed to the model’s successful prediction of monsoonal intra-seasonal oscillations.

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Data availability

Different datasets used in this study are freely available at the following links; Model: https://iridl.ldeo.columbia.edu/SOURCES/.ECMWF/.S2S/.ECMF/. CHIRPS: https://iridl.ldeo.columbia.edu/SOURCES/.UCSB/.CHIRPS/

Code availability

IRI Sub-Seasonal forecasting tool can be found at; PyCPT: https://bitbucket.org/py-iri/iri-pycpt/downloads/

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Acknowledgements

We thank John Furlow for insightful discussion in initiating this research. The WWRP/WCRP Sub-seasonal to Seasonal (S2S) project database (http://s2sprediction.net) provided the forecast and hindcast data, which was accessed via IRI Data Library. The S2S archive in IRI Data Library is made possible through NOAA support (NA21OAR4590266).

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Authors and Affiliations

  1. International Research Institute for Climate and Society, Columbia Climate School, Columbia University, Palisades, NY, USA

    Bohar Singh, Muhammad Azhar Ehsan & Andrew W. Robertson

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  1. Bohar Singh
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  2. Muhammad Azhar Ehsan
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  3. Andrew W. Robertson
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Contributions

BS collected data, conducted experiments, and analyzed the results. MAE prepared the initial draft of the manuscript. BS, MAE, and AWR contributed to the writing of the final manuscript.

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Correspondence to Bohar Singh.

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Singh, B., Ehsan, M.A. & Robertson, A.W. Calibrated probabilistic sub-seasonal forecasting for Pakistan’s monsoon rainfall in 2022. Clim Dyn 62, 3375–3393 (2024). https://doi.org/10.1007/s00382-023-07071-4

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