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Early Warning of Drought in Europe Using the Monthly Ensemble System from Ecmwf : Volume 12, Issue 2 (13/02/2015)

By Lavaysse, C.

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Book Id: WPLBN0004012275
Format Type: PDF Article :
File Size: Pages 37
Reproduction Date: 2015

Title: Early Warning of Drought in Europe Using the Monthly Ensemble System from Ecmwf : Volume 12, Issue 2 (13/02/2015)  
Author: Lavaysse, C.
Volume: Vol. 12, Issue 2
Language: English
Subject: Science, Hydrology, Earth
Collections: Periodicals: Journal and Magazine Collection (Contemporary), Copernicus GmbH
Historic
Publication Date:
2015
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications

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Vogt, J., Pappenberger, F., & Lavaysse, C. (2015). Early Warning of Drought in Europe Using the Monthly Ensemble System from Ecmwf : Volume 12, Issue 2 (13/02/2015). Retrieved from http://hawaiilibrary.net/


Description
Description: European Commission, Joint Research Centre, Ispra (Va), Italy. Timely forecasts of the onset or possible evolution of droughts are an important contribution to mitigate their manifold negative effects. In this paper we therefore analyse and compare the performance of the first month of the probabilistic extended range forecast and of the seasonal forecast from ECMWF in predicting droughts over the European continent. The Standardized Precipitation Index (SPI) is used to quantify the onset and severity of droughts.

It can be shown that on average the extended range forecast has greater skill than the seasonal forecast whilst both outperform climatology. No significant spatial or temporal patterns can be observed but the scores are improved when focussing on large-scale droughts. In a second step we then analyse several different methods to convert the probabilistic forecasts of SPI into a Boolean drought warning. It can be demonstrated that methodologies which convert low percentiles of the forecasted SPI cumulative distribution function into warnings are superior in comparison with alternatives such as the mean or the median of the ensemble. The paper demonstrates that up to 40% of droughts are correctly forecasted one month in advance. Nevertheless, during false alarms or misses, we did not find significant differences in the distribution of the ensemble members that would allow for a quantitative assessment of the uncertainty.


Summary
Early warning of drought in Europe using the monthly ensemble system from ECMWF

Excerpt
McKee, T. B., Doesken, N. J., and Kleist, J.: The relationship of drought frequency and duration to time scales, in: Proceedings of the 8th Conference on Applied Climatology, Anaheim, CA, USA, Am. Meteorol. Soc., 179–184, 1993.; Mishra, A. and Desai, V.: Drought forecasting using feed-forward recursive neural network, Ecol. Model., 198, 127–138, 2006.; Mishra, A., Desai, V., and Singh, V.: Drought forecasting using a hybrid stochastic and neural network model, J. Hydrol. Eng., 12, 626–638, 2007.; Molteni, F., Buizza, R., Palmer, T. N., and Petroliagis, T.: The ECMWF ensemble prediction system: methodology and validation, Q. J. Roy. Meteor. Soc., 122, 73–119, 1996.; Molteni, F., Stockdale, T., Balmaseda, M., Balsamo, G., Buizza, R., Ferranti, L., Magnusson, L., Mogensen, K., Palmer, T., and Vitart, F.: The new ECMWF seasonal forecast system (System 4), European Centre for Medium-Range Weather Forecasts, Reading, UK, 2011.; Nurmi, P.: Recommendations on the verification of local weather forecasts, ECMWF Tech. Memo. 430, 18 pp., 2003.; Palmer, T. N.: Predicting uncertainty in forecasts of weather and climate, Rep. Prog. Phys., 63, 71, doi:10.1088/0034-4885/63/2/201, 2000.; Pereira, S. C., Carvalho, A. C., Ferreira, J., Nunes, J. P., Keizer, J. J., and Rocha, A.: Simulation of a persistent medium-term precipitation event over the western Iberian Peninsula, Hydrol. Earth Syst. Sci., 17, 3741–3758, doi:10.5194/hess-17-3741-2013, 2013.; Richardson, D., Bidlot, J., Ferranti, L., Haiden, T., Hewson, T., Janousek, M., Prates, F., and Vitart, F.: Evaluation of ECMWF forecasts, including 2012–2013 upgrades, Tech. rep., ECMWF Technical Memo, Reading, UK, 2013.; Singleton, A.: Forecasting drought in Europe with the Standardized Precipitation Index, Tech. rep., JRC Sctintific and Technical Reports, Italy, 2012.; Stockdale, T., Anderson, D., Alves, J., and Balmaseda, M.: Global seasonal rainfall forecasts using a coupled ocean–atmosphere model, Nature, 392, 370–373, 1998.; Sunyer, M. A., Sørup, H. J. D., Christensen, O. B., Madsen, H., Rosbjerg, D., Mikkelsen, P. S., and Arnbjerg-Nielsen, K.: On the importance of observational data properties when assessing regional climate model performance of extreme precipitation, Hydrol. Earth Syst. Sci., 17, 4323–4337, doi:10.5194/hess-17-4323-2013, 2013.; Van den Besselaar, E., Haylock, M., Van der Schrier, G., and Klein Tank, A.: A European daily high-resolution observational gridded data set of sea level pressure, J. Geophys. Res.-Atmos., 116, D11110, doi:10.1029/2010JD015468, 2011.; Vicente-Serrano, S. M.: Differences in spatial patterns of drought on different time scales: an analysis of the Iberian Peninsula, Water Resour. Manag., 20, 37–60, 2006.; Buizza, R., Houtekamer, P., Pellerin, G., Toth, Z., Zhu, Y., and Wei, M.: A comparison of the ECMWF, MSC, and NCEP global ensemble prediction systems, Mon. Weather Rev., 133, 1076–1097, 2005.; Cacciamani, C., Morgillo, A., Marchesi, S., and Pavan, V.: Monitoring and forecasting drought on a regional scale: Emilia-Romagna Region, in: Methods and Tools for Drought Analysis and Management, Springer, 29–48, 2007.; Doblas-Reyes, F., Weisheimer, A., Déqué, M., Keenlyside, N., McVean, M., Murphy, J., Rogel, P., Smith, D., and Palmer, T.: Addressing model uncertainty in seasonal and annual dynamical ensemble forecasts, Q. J. Roy. Meteor. Soc., 135, 1538–1559, 2009.; Arribas, A., Glover, M., Maidens, A., Peterson, K., Gordon, M., MacLachlan, C., Graham, R., Fereday, D., Camp, J., Scaife, A., Xavier, P., McLean, P., Colman, A., and Cusack, S.: The GloSea4 ensemble prediction system for seasonal forecasting, Mon. Weather Rev., 139, 1891–1910, 2011.; Barnston, A. G., Tippett, M. K., L'Heureux, M. L., L

 

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