First outcomes from the CNR-ISAC monthly forecasting system

A monthly probabilistic forecasting system is experimentally operated at the ISAC institute of the National Council of Research of Italy. The forecasting system is based on GLOBO, an atmospheric general circulation model developed at the same institute. The model is presently run on a monthly basis...

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Main Authors: D. Mastrangelo, P. Malguzzi, C. Rendina, O. Drofa, A. Buzzi
Format: Article
Language:English
Published: Copernicus Publications 2012-04-01
Series:Advances in Science and Research
Online Access:http://www.adv-sci-res.net/8/77/2012/asr-8-77-2012.pdf
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spelling doaj-9805332059154d918bbd01aa16167ac42020-11-24T22:50:45ZengCopernicus PublicationsAdvances in Science and Research1992-06281992-06362012-04-018778210.5194/asr-8-77-2012First outcomes from the CNR-ISAC monthly forecasting systemD. Mastrangelo0P. Malguzzi1C. Rendina2O. Drofa3A. Buzzi4Institute of Atmospheric Sciences and Climate, National Research Council, Bologna, ItalyInstitute of Atmospheric Sciences and Climate, National Research Council, Bologna, ItalyInstitute of Atmospheric Sciences and Climate, National Research Council, Bologna, ItalyInstitute of Atmospheric Sciences and Climate, National Research Council, Bologna, ItalyInstitute of Atmospheric Sciences and Climate, National Research Council, Bologna, ItalyA monthly probabilistic forecasting system is experimentally operated at the ISAC institute of the National Council of Research of Italy. The forecasting system is based on GLOBO, an atmospheric general circulation model developed at the same institute. The model is presently run on a monthly basis to produce an ensemble of 32 forecasts initialized with GFS-NCEP perturbed analyses. Reforecasts, initialized with ECMWF ERA-Interim reanalyses of the 1989–2009 period, are also produced to determine modelled climatology of the month to forecast. The modelled monthly climatology is then used to calibrate the ensemble forecast of daily precipitation, geopotential height and temperature on standard pressure levels. In this work, we present the forecasting system and a preliminary evaluation of the model systematic and forecast errors in terms of non-probabilistic scores of the 500-hPa geopotential height. Results show that the proposed forecasting system outperforms the climatology in the first two weeks of integrations. The adopted calibration based on weighted bias correction is found to reduce the systematic and the forecast errors.http://www.adv-sci-res.net/8/77/2012/asr-8-77-2012.pdf
collection DOAJ
language English
format Article
sources DOAJ
author D. Mastrangelo
P. Malguzzi
C. Rendina
O. Drofa
A. Buzzi
spellingShingle D. Mastrangelo
P. Malguzzi
C. Rendina
O. Drofa
A. Buzzi
First outcomes from the CNR-ISAC monthly forecasting system
Advances in Science and Research
author_facet D. Mastrangelo
P. Malguzzi
C. Rendina
O. Drofa
A. Buzzi
author_sort D. Mastrangelo
title First outcomes from the CNR-ISAC monthly forecasting system
title_short First outcomes from the CNR-ISAC monthly forecasting system
title_full First outcomes from the CNR-ISAC monthly forecasting system
title_fullStr First outcomes from the CNR-ISAC monthly forecasting system
title_full_unstemmed First outcomes from the CNR-ISAC monthly forecasting system
title_sort first outcomes from the cnr-isac monthly forecasting system
publisher Copernicus Publications
series Advances in Science and Research
issn 1992-0628
1992-0636
publishDate 2012-04-01
description A monthly probabilistic forecasting system is experimentally operated at the ISAC institute of the National Council of Research of Italy. The forecasting system is based on GLOBO, an atmospheric general circulation model developed at the same institute. The model is presently run on a monthly basis to produce an ensemble of 32 forecasts initialized with GFS-NCEP perturbed analyses. Reforecasts, initialized with ECMWF ERA-Interim reanalyses of the 1989–2009 period, are also produced to determine modelled climatology of the month to forecast. The modelled monthly climatology is then used to calibrate the ensemble forecast of daily precipitation, geopotential height and temperature on standard pressure levels. In this work, we present the forecasting system and a preliminary evaluation of the model systematic and forecast errors in terms of non-probabilistic scores of the 500-hPa geopotential height. Results show that the proposed forecasting system outperforms the climatology in the first two weeks of integrations. The adopted calibration based on weighted bias correction is found to reduce the systematic and the forecast errors.
url http://www.adv-sci-res.net/8/77/2012/asr-8-77-2012.pdf
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