Vol. 11, Issue 10 (2022)

Author(s):
Pujyasmita Nayak, Anupama Baliarsingh, Chinmaya Kumar Swain and BS Rath

Abstract:
Validation of the qualitative and quantitative district level weather forecast under extended range forecast, one month leading to 15-30 days active or break period is required. Since 2011, the IITM's Extended Range Prediction group has been offering experimental real-time forecasts for up to 20 days, primarily concentrating on the weekly variations in the weather. The farming community benefits from medium and long-range weather forecasts because they reduce production losses brought on by unfavourable conditions. In this study, the accuracy of the long-range weather forecast for Cuttack, Odisha for the years 2017-18 is discussed in relation to temperature and rainfall, and it is contrasted with the medium-range forecast. Pre-monsoon, monsoon, post-monsoon, and winter season forecasts' accuracy was assessed individually using real-time data gathered from the station observatory. The investigation of the Cuttack district's weather forecasts revealed that, when compared to MRF, ERF provided the highest forecast accuracy for rainfall and minimum temperature. Rainfall prediction was tested using the ratio scores on a Yes/No basis, i.e. Heidke Skill Score (HSS), Hansen and Kuiper's (HK) ratings. The accuracy of rainfall predictions on a Yes/No basis for all seasons was 80.3%, while for the post-monsoon period in 2017-18, it was 95.3% and 90.2%. The Critical Values for Error Structure provided by NCMRWF was used to assess the weather forecast for additional parameters. For example, the useful forecast for rainfall is 85.9 for the post monsoon in 2017 and 77.1 for the monsoon in 2018. Lower prediction accuracy was shown by a higher Root Mean Square Error (RMSE) of rainfall during the monsoon season (19.2). Like that correct error structure for maximum temperature in monsoon and minimum temperatures for summer that indicated higher RMSE accuracy. Accurate weather forecasting with regard to a variety of meteorological criteria is crucial because it may be used to help farmers make strategic decisions about how to manage their crops.