Corroboration of Location Specific Seasonal Rainfall Forecast Using Australian Rainman for Tamil Nadu

Abstract

Skillful weather and seasonal predictions have significant socio-economic potential and could provide evocative information to farmers and decision-makers towards agricultural planning. The present study evaluates the Australian seasonal rainfall forecast model for the southwest and northeast monsoon of Tamil Nadu over the period from 2016 to 2020.. Different skill scores viz., Nash-Sutcliffe Efficiency (NSE), Ratio of Root Mean Square Error (RMSE) to the standard deviation of the observations (RSR), Per cent Bias (PBIAS), and Kling-Gupta Efficiency (KGE) were used for the present study to evaluate the performance of seasonal rainfall prediction by the Australian Rainman Software. The verification skill scores for both monsoons indicated that for southwest monsoon, especially the drought incidence (2016) was well captured by the Software. Inculcation of new climatic drivers, the performance of the northeast monsoon was also found to be within the acceptable range limit in recent years.

DOI

https://doi.org/10.29321/MAJ.10.000678

Pages

46 - 50

Creative Commons

Copyright

© The Author(s), 2025. Published by Madras Agricultural Students' Union in Madras Agricultural Journal (MAJ). This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited by the user.

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