Climate and Land Surface Changes in Hydrology Proceedings of H01, IAHS-IAPSO-IASPEI Assembly, Gothenburg, Sweden, July 2013 (IAHS Publ. 359, 2013). Copyright  2013 IAHS Press 3 Seamless forecasting of extreme events on a global scale FLORIAN PAPPENBERGER 1 , FREDRIK WETTERHALL 1 , EMANUEL DUTRA 1 , FRANCESCA DI GIUSEPPE 1 , KONRAD BOGNER 1 , LORENZO ALFIERI 1 & HANNAH L. CLOKE 2,3 1 European Centre for Medium-Range Weather Forecasts, Reading, UK florian.pappenberger@ecmwf.int 2 Department of Geography and Environmental Science, University of Reading, Reading, UK 3 Department of Meteorology, University of Reading, Reading, UK Abstract Early warning systems of extreme events, such as floods, droughts, strong winds and wild fires as well as vector-borne diseases, at the global scale, are essential due to the combined threat of increased population settlement in vulnerable areas and potential increase in the intensity of extreme weather due to climate change. The European Centre for Medium-Range Weather Forecasts (ECMWF) has in the last year developed prototype early warning systems for floods, droughts, extreme winds, wild forest fires and malaria transmission. This paper assesses the performance of these systems. By providing a comprehensive skill assessment both on a global level and in selected regions, we aim to assess their suitability for eventual integration into decision-support frameworks. Key words floods; droughts; fire; malaria; forecasting; ensemble; ECMWF INTRODUCTION The skill of weather forecasting has steadily improved over the last decades (Simmons et al., 2002, Hoskins, 2012) and this has led to the application of weather forecasts in the anticipation of disasters. Webster (2012) has pointed to the huge potential that numerical weather predictions (NWP) have for the reduction of damage caused by floods, droughts and tropical cyclones, especially in the developing world. ECMWF issues the world’s best numerical ensemble weather forecast on the medium range (Haiden et al., 2012; Hagedorn, 2013). It also has a range of different forecast products with lead times of up to seven months (see Table 1 for a full list of available products). The use of these products of varying time ranges can be termed “seamless”. The ECMWF high resolution forecast has a lead time of 10 days and a horizontal resolution of ~16 km (ECMWF, 2013b). Weather forecasts are often based on ensemble techniques to adequately represent uncertainties (Palmer & Leutbecher, 2008) and the ECMWF ensemble consists of 51 forecasts issued twice a day with a lead time of 15 days. The monthly forecast is integrated into this 15-day forecast by extending the forecast range to 32 days twice a week. The seasonal forecasting system is run once a month with a lead time up to seven months (S4, Molteni et al., 2011). These systems are supplemented with a set of hindcasts which are forecasts run for the past 18 years with the current prediction model. Hindcasts are used to calculate model climatologies, or to calibrate the forecast before its use in driving applications. In addition to forecasting products, ECMWF produces re-analysis products, which can be used for real-time monitoring, or for analysis of past events. Re-analysis produces global fields of atmospheric, land and ocean properties using available observations assimilated by the numerical weather prediction system. The current ECMWF re-analysis product is called ERA-Interim (ERAI, Dee et al., 2011) and is available from 1979 until today with a spatial resolution of ~80 km. ERA-Interim superseded the earlier ERA-40 (Uppala et al., 2005). The next generation re-analysis product will be ERA-20C, which is a global re-analysis for the whole 20th century (ECMWF, 2013c). This paper describes the latest development of seamless applications of ECMWF forecasts to natural hazards, such as floods, droughts, wild fire and malaria. CASE STUDIES There is a large range of forecast products which can be used and developed into applications, as illustrated in Table 1. ECMWF end-users use the NWP forecasts and re-analysis in many different