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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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 |
work_keys_str_mv |
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