Quantile mapping bias correction methods to IMDAA reanalysis for calibrating NCMRWF unified model operational forecasts

ABSTRACT

This study focuses on assessing different quantile mapping (QM) bias correction approaches based on empirical and parametric methods to bias-correct the Indian Monsoon Data Assimilation and Analysis (IMDAA) precipitation data and subsequently calibrate the National Centre for Medium Range Weather Forecasting (NCMRWF) Unified Model operational forecasts. The two coastal cities Chennai and Mumbai, India, are chosen here to support the Integrated Flood Warning System (IFLOWS), initiated by the Ministry of Earth Sciences, Government of India, which provides early warning and decision support during flooding. The empirical QM methods are relatively better in correcting the quantiles with calibrated precipitation close to the observed cumulative distribution at these coastal cities. However, in extreme rainfall cases, the skill of calibrated precipitation through parametric methods seems promising and suitable for flood forecasting applications. Hence, this study demonstrates QM methods’ performance and their potential in downscaling precipitation that has significant implications for urban flood models.

KEYWORDS:

• quantile mapping
• bias correction
• rainfall
• floods
• urban cities

Editor A. Castellarin; Associate editor M. Batalini de Macedo

Editor A. Castellarin; Associate editor M. Batalini de Macedo

Acknowledgements

The IMDAA regional reanalysis dataset is the result of the National Monsoon Mission Programme of the Ministry of Earth Sciences, Government of India; the Met Office, UK; and many individuals who have contributed directly or indirectly to setting up and running this complex reanalysis system. The authors acknowledge the use of GHCN-Daily rainfall data obtained from ftp://ftp.ncdc.noaa.gov/pub/data/ghcn/daily/all/.

Disclosure statement

No potential conflict of interest was reported by the authors.

Supplementary material

Supplemental data for this article can be accessed here.

Additional information

Funding

This work is supported by the Ministry of Earth Sciences, Government of India.