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First Outcomes from the Cnr-isac Monthly Forecasting System : Volume 8, Issue 1 (16/04/2012)

By Mastrangelo, D.

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Book Id: WPLBN0003991188
Format Type: PDF Article :
File Size: Pages 6
Reproduction Date: 2015

Title: First Outcomes from the Cnr-isac Monthly Forecasting System : Volume 8, Issue 1 (16/04/2012)  
Author: Mastrangelo, D.
Volume: Vol. 8, Issue 1
Language: English
Subject: Science, Advances, Science
Collections: Periodicals: Journal and Magazine Collection (Contemporary), Copernicus GmbH
Historic
Publication Date:
2012
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: copernicus

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Rendina, C., Malguzzi, P., Drofa, O., Buzzi, A., & Mastrangelo, D. (2012). First Outcomes from the Cnr-isac Monthly Forecasting System : Volume 8, Issue 1 (16/04/2012). Retrieved from http://members.worldlibrary.net/


Description
Description: Institute of Atmospheric Sciences and Climate, National Research Council, Bologna, Italy. 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.

Summary
First outcomes from the CNR-ISAC monthly forecasting system

Excerpt
Chen, M., Wang, W., and Kumar, A.: Prediction of monthly-mean temperature: the roles of atmospheric and land initial conditions and sea surface temperature, J. Climate, 23, 717–725, 2010.; Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N. and Vitart, F.: The ERA-Interim reanalysis: configuration and performance of the data assimilation system, Q. J. Roy. Meteor. Soc., 137, 553–597, 2011.; Hudson, D., Alves, O., Hendon, H. H., and Marshall, A. G.: Bridging the gap between weather and seasonal forecasting: Intraseasonal forecasting for Australia, Q. J. Roy. Meteor. Soc., 137, 673–689, 2011.; Malguzzi, P., Buzzi, A., and Drofa, O.: The meteorological global model GLOBO at the ISAC-CNR of Italy: Assessment of 1.5 years of experimental use for medium range weather forecast, Weather Forecast., 26, 1045–1055, 2011.; Palmer, T. and Hagedorn, R. (Eds.): Predictability of Weather and Climate, Cambridge University Press, 702 pp., 2006.; Reichler, T. J. and Roads, J. O.: The role of boundary and initial conditions for dynamical seasonal predictability, Nonlin. Processes Geophys., 10, 211–232, doi:10.5194/npg-10-211-2003, 2003.; Rendina, C.: Study of the impact of modelling sea surface temperature in a monthly atmospheric ensemble prediction system, Ph.D. thesis, University of Ferrara, Italy, 2011.; Saha, S., Moorthi, S., Wu, X., Wang, J., Nadiga, S., Tripp, P., Pan, H.-L., Behringer, D., Hou, Y.-T., Chuang, H.-Y., Iredell, M., Ek, M., Meng, J., Yang, R., van den Dool, H., Zhang, Q., Wang, W., and Chen, M.: The NCEP Climate Forecast System Version 2, J. Climate, to be submitted, 2012.; Simmons, A., Uppala, S., Dee, D. P., and Kobayashi, S.: ERA-Interim: New ECMWF reanalysis products from 1989 onwards, ECMWF Newsletter, 110, 25–35, 2007.; Vitart, F. and Molteni, F.: Simulation of the Madden-Julian Oscillation and its teleconnections in the ECMWF forecast system, Q. J. Roy. Meteor. Soc., 136, 842–855, doi:10.1002/qj.623, 2010.; Vitart, F., Buizza, R., Balmaseda, M. A., Balsamo, G., Bidlot, J.-R., Bonet, A., Fuentes, M., Hofstadler, A., Molteni, F., and Palmer, T. N.: The new VAREPS-monthly forecasting system: A first step towards seamless prediction, Q. J. Roy. Meteor. Soc., 134, 1789–1799, 2008.; Wilks, D. S.: Statistical Methods in the Atmospheric Sciences, 2nd Edn., Academic Press, 627 pp., 2006.

 

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