Verification and usability analysis of medium range weather forecast for the Ananthapuramu district of Scarce rainfall zone in Andhra Pradesh
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Keywords:
Medium range weather forecast, usability analysis, RMSE, atio score and correlation and regression.Abstract
Accurate weather forecast is crucial for the planning of agricultural operations during periods of increased climatic fluctuation. The value-added weather forecast issued by India Meteorological Department (IMD) for Ananthapuramu district of Andhra Pradesh from 2017 to 2021 has been verified for accuracy using statistical methods ratio score, Hanssen and Kuipers (H.K) Score and RMSE for rainfall and for other weather parameters usability, correlation and regression analysis, were used to verify forecast. The ratio score for rainfall prediction was moderate to very good, with highest for cold weather period (90.5%) and lowest during south west monsoon (36.9%). Rainfall forecast was poor during monsoon season with usability of 12.5% to 50% and higher RMSE i.e., 10 to 20 as compared to north east monsoon, hot and cold weather period with RMSE 8.1 to 14.3, 3.4 to 14.5 and 0.8 to 4.3, respectively. Performance of maximum temperature forecast was relatively higher during north east monsoon and cold weather period with usability varied from 73% to 90 % and 70% to 86%, respectively. Maximum temperature forecast was satisfactory to very good during south west and north east monsoon with correctness varies from 65 % to 92 % and 55 % to 88 %, respectively. For wind speed forecast, usability was very good during cold and hot weather period varied from 76 % to 98 % and 70% to 95 %, respectively. The usability of morning and afternoon relative humidity forecast was poor for all the seasons. The correlation study finds a strong correlation between predicted and observed weather parameters for annual forecast as compared to seasons. The forecast was highly reliable for all the parameters and farmers have realized that accurate weather forecast in advance is useful in planning for timely field operations and crop management practices.