First outcomes from the CNR-ISAC monthly forecasting system
| Autor: | A. Buzzi, Oxana Drofa, C. Rendina, Daniele Mastrangelo, Piero Malguzzi |
|---|---|
| Rok vydání: | 2012 |
| Předmět: |
Atmospheric Science
010504 meteorology & atmospheric sciences Meteorology Geopotential height numerical weather prediction lcsh:QC851-999 01 natural sciences 010104 statistics & probability Calibration Bias correction Monthly forecasts 0101 mathematics lcsh:Science 0105 earth and related environmental sciences Ecological Modeling Pollution lcsh:QC1-999 Geophysics Climatology General Circulation Model Quantitative precipitation forecast Environmental science lcsh:Q lcsh:Meteorology. Climatology Probabilistic forecasting lcsh:Physics |
| Zdroj: | Advances in Science and Research, Vol 8, Pp 77-82 (2012) Advances in science and research 8 (2012): 77–82. info:cnr-pdr/source/autori:D. Mastrangelo, P. Malguzzi, C. Rendina, O. Drofa, A. Buzzi/titolo:First outcomes from the CNR-ISAC monthly forecasting system/doi:/rivista:Advances in science and research (Print)/anno:2012/pagina_da:77/pagina_a:82/intervallo_pagine:77–82/volume:8 |
| ISSN: | 1992-0636 |
| DOI: | 10.5194/asr-8-77-2012 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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