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Ensemble spread and systematic errors in the medium-range predictions during the Indian summer monsoon

"For preparing medium range weather forecasts, two global coarse resolution models at different resolutions were used at the National Centre for Medium Range Weather Forecasting (NCMRWF), India. In order to improve the forecasting skill, an ensemble prediction system (EPS) was implemented on ex...

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Vydáno v:Atmósfera Atmósfera (México) Num.2 Vol.24
Hlavní autoři: S. C. KAR, G. R. IYENGAR, A. K. BOHRA
Médium: Článek
Jazyk:English
Vydáno: Universidad Nacional Autónoma de México 2011
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On-line přístup:https://www.redalyc.org/articulo.oa?id=56519370002
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spelling oai:redalyc.org:565193700022015-03-20T06:00:00Z Ensemble spread and systematic errors in the medium-range predictions during the Indian summer monsoon S. C. KAR G. R. IYENGAR A. K. BOHRA Ciencias de la Tierra skill model spread global Forecast "For preparing medium range weather forecasts, two global coarse resolution models at different resolutions were used at the National Centre for Medium Range Weather Forecasting (NCMRWF), India. In order to improve the forecasting skill, an ensemble prediction system (EPS) was implemented on experimental basis. For generating initial perturbations a breeding method was implemented. Experimental forecast runs with 8-member ensemble were carried out and results are analyzed for a monsoon season. The ensemble mean of rainfall forecasts shows that over the broad region of Gangetic Plains, the EPS brings out the monsoon activity (active and weak spell) reasonably well six days in advance. However, over the eastern parts of India, the ensemble mean rainfall is good only in short-range. The ensemble spread becomes quite large from about day-4 forecast and beyond. An examination of the rainfall pattern from day-1 to day-6 forecasts by the model and the ensemble spread shows there is no linearity in the increase of spread with the rainfall amount. The model has a systematic tendency to enhance rainfall activity over the central Bay of Bengal and eastern parts of India as the length of forecast is increased. At the same time, the model tends to dry up over the equatorial Indian Ocean region, however, in the high-resolution model, the same tendency is not seen. In circulation fields, the model also has large systematic errors. These results suggest that to obtain maximum benefit from the ensemble prediction system, the systematic biases in the model must be reduced as the breeding method only takes care of the uncertainties in the initial conditions." 2011 artículo científico 0187-6236 https://www.redalyc.org/articulo.oa?id=56519370002 en http://www.redalyc.org/revista.oa?id=565 Atmósfera application/pdf Universidad Nacional Autónoma de México Atmósfera (México) Num.2 Vol.24
institution Sistema de Información Científica Redalyc
collection Redalyc
language English
format Article
author S. C. KAR
G. R. IYENGAR
A. K. BOHRA
spellingShingle S. C. KAR
G. R. IYENGAR
A. K. BOHRA
Ensemble spread and systematic errors in the medium-range predictions during the Indian summer monsoon
Ciencias de la Tierra
Skill
Model
Spread
Global
Forecast
Atmósfera
author_facet S. C. KAR
G. R. IYENGAR
A. K. BOHRA
author_sort S. C. KAR
title Ensemble spread and systematic errors in the medium-range predictions during the Indian summer monsoon
title_short Ensemble spread and systematic errors in the medium-range predictions during the Indian summer monsoon
title_full Ensemble spread and systematic errors in the medium-range predictions during the Indian summer monsoon
title_fullStr Ensemble spread and systematic errors in the medium-range predictions during the Indian summer monsoon
title_full_unstemmed Ensemble spread and systematic errors in the medium-range predictions during the Indian summer monsoon
title_sort ensemble spread and systematic errors in the medium-range predictions during the indian summer monsoon
topic Ciencias de la Tierra
Skill
Model
Spread
Global
Forecast
topic_facet Ciencias de la Tierra
Skill
Model
Spread
Global
Forecast
description "For preparing medium range weather forecasts, two global coarse resolution models at different resolutions were used at the National Centre for Medium Range Weather Forecasting (NCMRWF), India. In order to improve the forecasting skill, an ensemble prediction system (EPS) was implemented on experimental basis. For generating initial perturbations a breeding method was implemented. Experimental forecast runs with 8-member ensemble were carried out and results are analyzed for a monsoon season. The ensemble mean of rainfall forecasts shows that over the broad region of Gangetic Plains, the EPS brings out the monsoon activity (active and weak spell) reasonably well six days in advance. However, over the eastern parts of India, the ensemble mean rainfall is good only in short-range. The ensemble spread becomes quite large from about day-4 forecast and beyond. An examination of the rainfall pattern from day-1 to day-6 forecasts by the model and the ensemble spread shows there is no linearity in the increase of spread with the rainfall amount. The model has a systematic tendency to enhance rainfall activity over the central Bay of Bengal and eastern parts of India as the length of forecast is increased. At the same time, the model tends to dry up over the equatorial Indian Ocean region, however, in the high-resolution model, the same tendency is not seen. In circulation fields, the model also has large systematic errors. These results suggest that to obtain maximum benefit from the ensemble prediction system, the systematic biases in the model must be reduced as the breeding method only takes care of the uncertainties in the initial conditions."
publisher Universidad Nacional Autónoma de México
publisher_facet Universidad Nacional Autónoma de México
publishDate 2011
container_title Atmósfera
container_title_facet Atmósfera
container_reference Atmósfera (México) Num.2 Vol.24
issn 0187-6236
url https://www.redalyc.org/articulo.oa?id=56519370002
work_keys_str_mv AT sckar ensemblespreadandsystematicerrorsinthemediumrangepredictionsduringtheindiansummermonsoon
AT griyengar ensemblespreadandsystematicerrorsinthemediumrangepredictionsduringtheindiansummermonsoon
AT akbohra ensemblespreadandsystematicerrorsinthemediumrangepredictionsduringtheindiansummermonsoon
first_indexed 2023-04-23T21:36:35Z
last_indexed 2023-04-23T21:36:35Z
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