An Analysis of Prediction Skill of Heat Waves Over India Using TIGGE Ensemble Forecasts. Issue 3 (8th March 2023)

• Record Type: Journal Article
• Authors: Rohini, P.; Rajeevan, M.
• Is Part Of: Earth and space science. Volume 10:Issue 3(2023)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2023-03-08
• Subjects: heat wave -- TIGGE models -- forecast verification -- prediction skill; Space sciences -- Periodicals; Geophysics -- Periodicals; 500.5
• DOI: 10.1029/2020EA001545
• Languages: English
• ISSNs: 2333-5084

Abstract

Abstract: Heat wave has become a great concern for India in the recent years due to its disastrous impact on various sectors including health. Thus, accurate forecasts of heat wave events well in advance are required for preparing adequate mitigation strategies. The present study assesses the prediction skill of numerical weather prediction models in The Observing system Research and Predictability Experiment Interactive Grand Global Ensemble (TIGGE) experiments for predicting heat waves over India up to 7 days in advance. The models considered for this analysis are; the European Centre for Medium‐Range Weather Forecasts (ECMWF), the UK Met Office (UKMO) and National Centre for Environmental Prediction (NCEP). The model forecast verifications have been carried out for the hot weather season (April–June) over India for the period of 2008–2013. Fourteen heat wave events were identified during the study period using gridded daily maximum temperature ( T max ). The study reveals that the spatial distribution of maximum Temperature is well predicted by the TIGGE models for a forecast lead time of 1–7 days. The analysis suggested that the magnitude of heat wave events, even with a 7 days lead time, can be correctly predicted by more than 80% of ensemble members in all the TIGGE models. The prediction skill of the maximum temperatures over heat wave prone area during heat wave events is higher for ECMWF, then UKMO and NCEP models. The forecast verification analysis thus indicates that the TIGGE models are able to provide early warnings of heat waves with at least 5 days lead time. Plain Language Summary: Heat wave event over India are increasing in the recent years during the summer season, which have widespread and severe impacts on health and environment. Accurate forecast of heat waves in advance can reduce the impacts of these events through proper mitigation plans. Prediction skill of heat wave events was analyzed using The Observing system Research and Predictability Experiment Interactive Grand Global Ensemble (TIGGE) ensemble forecasts. TIGGE models are capable of predicting the spatial pattern of maximum temperatures reasonably well. There is a useful skill in prediction up to 5 days for Heat wave events over India. European Centre for Medium‐Range Weather Forecasts model shows a higher skill in predicting heat waves over India as compared to other two models. Key Points: The spatial pattern of T max is well predicated in the The Observing system Research and Predictability Experiment Interactive Grand Global Ensemble (TIGGE) models, though the magnitude is slightly different from India Meteorological Department observations The European Centre for Medium‐Range Weather Forecasts model performs better in predicting T max during heat wave events over the Indian region The TIGGE models are able to provide early warnings of heat waves over India with at least 5 days lead time