期刊论文详细信息
Journal of Earth system science
Location specific forecasting of maximum and minimum temperatures over India by using the statistical bias corrected output of global forecasting system
V R Durai11  Rashmi Bhardwaj22 
[1] India Meteorological Department, New Delhi 110 003, India.$$;Guru Gobind Singh Indraprastha University, Dwarka, Delhi 110 078, India.$$
关键词: Statistical bias correction;    location specific forecast;    DMO;    Numerical Weather Prediction;    maximum and minimum temperature forecast.;   
DOI  :  
学科分类:天文学(综合)
来源: Indian Academy of Sciences
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【 摘 要 】

The output from Global Forecasting System (GFS) T574L64 operational at India Meteorological Department (IMD), New Delhi is used for obtaining location specific quantitative forecast of maximum and minimum temperatures over India in the medium range time scale. In this study, a statistical bias correction algorithm has been introduced to reduce the systematic bias in the 24–120 hour GFS model location specific forecast of maximum and minimum temperatures for 98 selected synoptic stations, representing different geographical regions of India. The statistical bias correction algorithm used for minimizing the bias of the next forecast is Decaying Weighted Mean (DWM), as it is suitable for small samples. The main objective of this study is to evaluate the skill of Direct Model Output (DMO) and Bias Corrected (BC) GFS for location specific forecast of maximum and minimum temperatures over India. The performance skill of 24–120 hour DMO and BC forecast of GFS model is evaluated for all the 98 synoptic stations during summer (May–August 2012) and winter (November 2012–February 2013) seasons using different statistical evaluation skill measures. The magnitude of Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) for BC GFS forecast is lower than DMO during both summer and winter seasons. The BC GFS forecasts have higher skill score as compared to GFS DMO over most of the stations in all day-1 to day-5 forecasts during both summer and winter seasons. It is concluded from the study that the skill of GFS statistical BC forecast improves over the GFS DMO remarkably and hence can be used as an operational weather forecasting system for location specific forecast over India.

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