MOS guidance using a neural network for the rainfall forecast over India View Full Text


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Article Info

DATE

2019-05-13

AUTHORS

Ashok Kumar, Ch Sridevi, V R Durai, K K Singh, P Mukhopadhyay, N Chattopadhyay

ABSTRACT

In the present study, a model output statistics (MOS) guidance model was developed by using the neural network technique for a bias-corrected rainfall forecast. The model was developed over the Indian window (0–40∘N\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$40{^{\circ }}\hbox {N}$$\end{document} and 60–100∘E\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$100{^{\circ }}\hbox {E}$$\end{document}) by using the observed and global forecast system (GFS) T-1534 model output (up to 5 days) at a 0.125∘×0.125∘\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$0.125{^{\circ }} \times \,0.125{^{\circ }}$$\end{document} regular grid during the summer monsoon (June–September) 2016. The skill of the developed MOS model forecast against the observed 0.125∘×0.125∘\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$0.125{^{\circ }} \times 0.125{^{\circ }}$$\end{document} grid rainfall data is obtained for the summer monsoon (June–September) 2017. The skill of the MOS model rainfall forecast is found to show good improvement over the T-1534 model’s direct forecast over the Indian window. In general, the T-1534 model’s direct forecast shows high skill but the forecast obtained by using the MOS model shows better skill than the direct model’s forecast, although a major improvement is seen for the Day 1 forecast at the national level. So the skill of the bias-corrected rainfall forecast by using the MOS guidance and the T-1534 model output is high and has the potential of being used as an operational forecast over the Indian region. More... »

PAGES

130

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s12040-019-1149-y

DOI

http://dx.doi.org/10.1007/s12040-019-1149-y

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1114222015


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164 India Meteorological Department, 411 005, Pune, India
165 schema:name India Meteorological Department, 110 003, New Delhi, India
166 India Meteorological Department, 411 005, Pune, India
167 rdf:type schema:Organization
 




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