期刊论文详细信息
Meteorological applications | |
A soft-computing ensemble approach (SEA) to forecast Indian summer monsoon rainfall | |
article | |
Nisha Kurian1  T. Venugopal2  Jatin Singh1  M. M. Ali1  | |
[1]Skymet Weather Services | |
[2]Department of Physics, Novosibirsk State University | |
关键词: monsoon forecasting; ensemble; neural networks; | |
DOI : 10.1002/met.1650 | |
学科分类:社会科学、人文和艺术(综合) | |
来源: Wiley | |
【 摘 要 】
Agriculture is the backbone of the Indian economy and contributes ∼16% of gross domestic product and about 10% of total exports. Hence, accurate and timely forecasting of monthly Indian summer monsoon rainfall is very much in demand for economic planning and agricultural practices. Several methods and models, comprising dynamic and statistical models and combinations of the two, exist for monsoon forecasting. Here, a multi-model ensemble approach, combined with an artificial neural networking technique, was used to develop a soft-computing ensemble algorithm (SEA) to forecast the monthly and seasonal rainfall over the Indian subcontinent. Forecasts using January to May initial conditions along with observations during 1982–2014 were used to develop the model. The SEA compares well with observations.【 授权许可】
CC BY|CC BY-NC|CC BY-NC-ND
【 预 览 】
Files | Size | Format | View |
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RO202107100001879ZK.pdf | 1189KB | download |