Abstract
ABSTRACT A reliable forecast of summer monsoon precipitation is crucial in India. To select a longer record of forecast data from the THORPEX Interactive Grand Global Ensemble (TIGGE) archives, we applied two criteria: the length of the dataset should be at least 10 years of continuous record, and the forecast product should have at least 20 ensemble members for a lead time of minimum 5 days. We evaluate the ensemble quantitative precipitation forecasts (QPFs) obtained from the four agencies throughout the monsoon season (June to September) from 2011 to 2020 in 22 river basins of India in forecasting normal and extreme precipitation events. The Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG) is used as observation data. The proficiency of QPFs is evaluated using six criteria from deterministic, dichotomous, and probabilistic error statistics. The error values are classified into three categories – low, moderate, and high. A Forecast Reliability Index is formulated using the given four QPFs, and three categories for each of the six error statistics to answer (a) which QPF shows better performance in which river basin and (b) whether any conclusion can be made on the overall performance of a QPF for all the River Basins of India.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have