%0 Book Section %1 Buontempo2010MultiScale %A Buontempo, Carlo %A Brookshaw, Anca %A Arribas, Alberto %A Mylne, Ken %B Management of Weather and Climate Risk in the Energy Industry %C Dordrecht %D 2010 %E Troccoli, Alberto %I Springer Netherlands %K MyECEMpaper climateservices colleagues decadal energy renewables seasonal textbook %P 39--50 %R 10.1007/978-90-481-3692-6_3 %T Multi-Scale Projections Of Weather And Climate At The Uk Met Office %U http://dx.doi.org/10.1007/978-90-481-3692-6_3 %X Due to the availability of unprecedented computational power, national meteorological and hydrological services have had the opportunity to push the limit of predictability beyond the 2 weeks Lorenz suggested in 1963. This has been largely possible through the use of ensemble modelling. The adoption of such a technique has had a twofold effect: by averaging out the most unpredictable scales an ensemble average could directly increase forecast skill; ensembles also provide an estimate of uncertainty. This paper analyses the sources of predictability at different time scales and shows how the ensemble technique has been successfully used to inform decisions on time scales ranging from days to centuries. %& 3 %@ 978-90-481-3691-9

@incollection{Buontempo2010MultiScale, abstract = {Due to the availability of unprecedented computational power, national meteorological and hydrological services have had the opportunity to push the limit of predictability beyond the 2 weeks Lorenz suggested in 1963. This has been largely possible through the use of ensemble modelling. The adoption of such a technique has had a twofold effect: by averaging out the most unpredictable scales an ensemble average could directly increase forecast skill; ensembles also provide an estimate of uncertainty. This paper analyses the sources of predictability at different time scales and shows how the ensemble technique has been successfully used to inform decisions on time scales ranging from days to centuries.}, added-at = {2018-06-18T21:23:34.000+0200}, address = {Dordrecht}, author = {Buontempo, Carlo and Brookshaw, Anca and Arribas, Alberto and Mylne, Ken}, biburl = {https://www.bibsonomy.org/bibtex/23f9bbcf4d6d3fc1050bf1f750d3ed3b8/pbett}, booktitle = {Management of Weather and Climate Risk in the Energy Industry}, chapter = 3, citeulike-article-id = {9558914}, citeulike-linkout-0 = {http://dx.doi.org/10.1007/978-90-481-3692-6_3}, citeulike-linkout-1 = {http://www.springerlink.com/content/m5t4371ju44m3817}, citeulike-linkout-2 = {http://link.springer.com/chapter/10.1007/978-90-481-3692-6_3}, comment = {(private-note)Cite for use of decadal forecasts for the energy sector (got whole book downloaded, Troccoli et al 2010)}, doi = {10.1007/978-90-481-3692-6_3}, editor = {Troccoli, Alberto}, interhash = {7266168759b1bdd09557a1f2f95733ea}, intrahash = {3f9bbcf4d6d3fc1050bf1f750d3ed3b8}, isbn = {978-90-481-3691-9}, keywords = {MyECEMpaper climateservices colleagues decadal energy renewables seasonal textbook}, pages = {39--50}, posted-at = {2016-02-18 17:17:31}, priority = {2}, publisher = {Springer Netherlands}, series = {NATO Science for Peace and Security Series C: Environmental Security}, timestamp = {2018-10-08T18:26:32.000+0200}, title = {Multi-Scale Projections Of Weather And Climate At The Uk Met Office}, url = {http://dx.doi.org/10.1007/978-90-481-3692-6_3}, year = 2010 }