Evaluating decadal predictions of northern hemispheric cyclone frequencies

References

• Balmaseda M. A. , Mogensen K. , Weaver A. T . Evaluation of the ECMWF ocean reanalysis system ORAS4. Q. J. Roy. Meteorol. Soc. 2013; 139(674): 1132–1161.
   Web of Science ®Google Scholar
• Bengtsson L. , Hodges K. I. , Roeckner E . Storm tracks and climate change. J. Clim. 2006; 19(15): 3518–3543.
   Web of Science ®Google Scholar
• Boer G. , Kharin V. , Merryfield W . Decadal predictability and forecast skill. Clim. Dynam. 2013; 41: 1817–1833.
   Web of Science ®Google Scholar
• Brayshaw D. J. , Hoskins B. , Blackburn M . The basic ingredients of the North Atlantic Storm Track. Part II: sea surface temperatures. J. Atmos. Sci. 2011; 68(8): 1784–1805.
   Web of Science ®Google Scholar
• Compo G. P. , Whitaker J. S. , Sardeshmukh P. D. , Matsui N. , Allan R. J. , co-authors . The twentieth century reanalysis project. Q. J. Roy. Meteorol. Soc. 2011; 137(654): 1–28.
   Web of Science ®Google Scholar
• Dee D. P. , Uppala S. M. , Simmons A. J. , Berrisford P. , Poli P. , co-authors . The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q. J. Roy. Meteorol. Soc. 2011; 137(656): 553–597.
   Web of Science ®Google Scholar
• Doblas-Reyes F. J. , Andreu-Burillo I. , Chikamoto Y. , Garcia-Serrano J. , Guemas V. , co-authors . Initialized near-term regional climate change prediction. Nat. Commun. 2013; 4: 1715.
   Web of Science ®Google Scholar
• Donat M. G. , Leckebusch G. C. , Pinto J. G. , Ulbrich U . European storminess and associated circulation weather types: future changes deduced from a multi-model ensemble of GCM simulations. Clim. Res. 2010; 42(1): 27–43.
   Web of Science ®Google Scholar
• Eade R. , Hamilton E. , Smith D. M. , Graham R. J. , Scaife A. A . Forecasting the number of extreme daily events out to a decade ahead. J. Geophys. Res. Atmos. 2012; 117: D21110.
   Web of Science ®Google Scholar
• Ferro C. A. T . Comparing probabilistic forecasting systems with the brier score. Weather Forecast. 2007; 22(5): 1076–1088.
   Web of Science ®Google Scholar
• Ferro C. A. T. , Richardson D. S. , Weigel A. P . On the effect of ensemble size on the discrete and continuous ranked probability scores. Meteorol. Appl. 2008; 15(1): 19–24.
   Web of Science ®Google Scholar
• Fricker T. E. , Ferro C. A. T. , Stephenson D. B . Three recommendations for evaluating climate predictions. Meteorol. Appl. 2013; 20(2): 246–255.
   Web of Science ®Google Scholar
• Gangstø R. , Weigel A. P. , Liniger M. A. , Appenzeller C . Methodological aspects of the validation of decadal predictions. Clim. Res. 2013; 55(3): 181–200.
   Web of Science ®Google Scholar
• Giorgetta M. A. , Jungclaus J. , Reick C. H. , Legutke S. , Bader J. , co-authors . Climate and carbon cycle changes from 1850 to 2100 in MPI-ESM simulations for the coupled model intercomparison project phase 5. J. Adv. Model. Earth Syst. 2013; 5(3): 572–597.
   Web of Science ®Google Scholar
• Goddard L. , Kumar A. , Solomon A. , Smith D. , Boer G. , co-authors. A verification framework for interannual-to-decadal predictions experiments. Clim. Dynam. 2013; 40(1–2): 245–272.
   Web of Science ®Google Scholar
• Hanlon H. M. , Hegerl G. C. , Tett S. F. B. , Smith D. M . Can a decadal forecasting system predict temperature extreme indices?. J. Clim. 2013; 26(11): 3728–3744.
   Web of Science ®Google Scholar
• Hawcroft M. K. , Shaffrey L. C. , Hodges K. I. , Dacre H. F . How much Northern Hemisphere precipitation is associated with extratropical cyclones?. Geophys. Res. Lett. 2012; 39: L24809.
   Web of Science ®Google Scholar
• Hodges K . Feature tracking on the unit-sphere. Mon. Weather Rev. 1995; 123(12): 3458–3465.
   Web of Science ®Google Scholar
• Hodges K. I. , Hoskins B. J. , Boyle J. , Thorncroft C . A comparison of recent reanalysis datasets using objective feature tracking: storm tracks and tropical easterly waves. Mon. Weather Rev. 2003; 131(9): 2012–2037.
   Web of Science ®Google Scholar
• International CLIVAR Project Office (ICPO). Data and Bias Correction for Decadal Climate Predictions. 2011. Online at: http://www.wcrp-climate.org/decadal/references/DCPP_Bias_Correction.pdf, compiled by CMIP-WGCM-WGSIP Decadal Climate Prediction Panel.
   Google Scholar
• Jungclaus J. H. , Fischer N. , Haak H. , Lohmann K. , Marotzke J. , co-authors. Characteristics of the ocean simulations in the Max Planck Institute Ocean Model (MPIOM) the ocean component of the MPI-Earth system model. J. Adv. Model. Earth Syst. 2013; 5(2): 422–446.
   Web of Science ®Google Scholar
• Kalnay E. , Kanamitsu M. , Kistler R. , Collins W. , Deaven D. , co-authors. The NCEP/NCAR 40-year reanalysis project. Bull. Am. Meteorol. Soc. 1996; 77(3): 437–471.
   Web of Science ®Google Scholar
• Leckebusch G. C. , Ulbrich U . On the relationship between cyclones and extreme windstorm events over Europe under climate change. Global Planet. Change. 2004; 44(1–4): 181–193.
   Web of Science ®Google Scholar
• Meehl G. A. , Goddard L. , Murphy J. , Stouffer R. J. , Boer G. , co-authors. Decadal prediction – can it be skillful?. Bull. Am. Meteorol. Soc. 2009; 90(10): 1467–1485.
   Web of Science ®Google Scholar
• Meehl G. A. , Goddard L. , Boer G. , Burgman R. , Branstator G. , co-authors . Decadal climate prediction: an update from the trenches. Bull. Am. Meteorol. Soc. 2014. 95(2), 243–267.
   Google Scholar
• Müller W. A. , Appenzeller C. , Doblas-Reyes F. J. , Liniger M. A . A debiased ranked probability skill score to evaluate probabilistic ensemble forecasts with small ensemble sizes. J. Clim. 2005; 18(10): 1513–1523.
   Web of Science ®Google Scholar
• Müller W. A. , Baehr J. , Haak H. , Jungclaus J. H. , Kröger J. , co-authors. Forecast skill of multi-year seasonal means in the decadal prediction system of the Max Planck Institute for Meteorology. Geophys. Res. Lett. 2012; 39: L22707.
   Web of Science ®Google Scholar
• Munich Re Group. Knowledge Series: Highs and Lows – Weather Risks in Central Europe. 2008. Online at: http://www.mroc.com/publications.html.
   Google Scholar
• Murray R. J. , Simmonds I . A numerical scheme for tracking cyclone centres from digital data. Part I: development and operation of the scheme. Aust. Meteorol. Mag. 1991a; 39: 155–166.
   Google Scholar
• Murray R. J. , Simmonds I . A numerical scheme for tracking cyclone centres from digital data. Part II: application to January and July general circulation model simulations. Aust. Meteorol. Mag. 1991b; 39: 167–180.
   Google Scholar
• Neu U. , Akperov M. G. , Bellenbaum N. , Benestad R. S. , Blender R. , co-authors . IMILAST a community effort to intercompare extratropical cyclone detection and tracking algorithms. Bull. Am. Meteorol. Soc. 2013; 94(4): 529–547.
   Web of Science ®Google Scholar
• Nissen K. M., Leckebusch G. C., Pinto J. G., Ulbrich U. Mediterranean cyclones and windstorms in a changing climate. Reg. Environ. Change. 2013a; 1–18. Online at: http://link.springer.com/article/10.1007/s10113-012-0400-8.
   Google Scholar
• Nissen K., Ulbrich U., Leckebusch G., Kuhnel I. Decadal windstorm activity in the North Atlantic-European sector and its relationship to the meridional overturning circulation in an ensemble of simulations with a coupled climate model. Clim Dynam. 2013b; 1–11. Online at: http://dx.doi.org/10.1007/s00382-013-1975-6.
   Google Scholar
• Nissen K. M. , Leckebusch G. C. , Pinto J. G. , Renggli D. , Ulbrich S. , co-authors . Cyclones causing wind storms in the Mediterranean: characteristics, trends and links to large-scale patterns. Nat. Hazard Earth Syst. 2010; 10(7): 1379–1391.
   Web of Science ®Google Scholar
• Paredes D. , Trigo R. M. , Garcia-Herrera R. , Trigo I. F . Understanding precipitation changes in Iberia in early spring: weather typing and storm-tracking approaches. J. Hydrometeorol. 2006; 7(1): 101–113.
   Web of Science ®Google Scholar
• Pfahl S. , Wernli H . Quantifying the relevance of cyclones for precipitation extremes. J. Clim. 2012; 25(19): 6770–6780.
   Web of Science ®Google Scholar
• Pinto J. G. , Spangehl T. , Ulbrich U. , Speth P . Sensitivities of a cyclone detection and tracking algorithm: individual tracks and climatology. Meteorol. Z. 2005; 14(6): 823–838.
   Web of Science ®Google Scholar
• Pinto J. G. , Zacharias S. , Fink A. H. , Leckebusch G. C. , Ulbrich U . Factors contributing to the development of extreme North Atlantic cyclones and their relationship with the NAO. Clim. Dynam. 2009; 32(5): 711–737.
   Web of Science ®Google Scholar
• Pinto J. G. , Ulbrich U. , Leckebusch G. C. , Spangehl T. , Reyers M. , co-authors . Changes in storm track and cyclone activity in three SRES ensemble experiments with the ECHAM5/MPI-OM1 GCM. Clim. Dynam. 2007; 29(2–3): 195–210.
   Web of Science ®Google Scholar
• Pohlmann H. , Müller W. A. , Kulkarni K. , Kameswarrao M. , Matei D. , co-authors . Improved forecast skill in the tropics in the new MiKlip decadal climate predictions. Geophys. Res. Lett. 2013; 40: 5798–5802.
   Web of Science ®Google Scholar
• Raible C. C . On the relation between extremes of midlatitude cyclones and the atmospheric circulation using ERA40. Geophys. Res. Lett. 2007; 34(7): L07703.
   Web of Science ®Google Scholar
• Rayner N. A. , Parker D. E. , Horton E. B. , Folland C. K. , Alexander L. V. , co-authors . Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J. Geophys. Res. Atmos. 2003; 108(D14): 4407.
   Web of Science ®Google Scholar
• Renggli D . Seasonal predictability of wintertime windstorm climate over the North Atlantic and Europe. PhD Thesis, Department of Earth Sciences, Freie Universität Berlin . 2011b
   Google Scholar
• Renggli D. , Leckebusch G. C. , Ulbrich U. , Gleixner S. N. , Faust E . The skill of seasonal ensemble prediction systems to forecast wintertime windstorm frequency over the North Atlantic and Europe. Mon. Weather Rev. 2011a; 139(9): 3052–3068.
   Web of Science ®Google Scholar
• Richardson D. S . Measures of skill and value of ensemble prediction systems, their interrelationship and the effect of ensemble size. Q. J. Roy. Meteorol. Soc. 2001; 127(577): 2473–2489.
   Web of Science ®Google Scholar
• Solomon A. , Goddard L. , Kumar A. , Carton J. , Deser C. , co-authors . Distinguishing the roles of natural and anthropogenically forced decadal climate variability. Bull. Am. Meteorol. Soc. 2011; 92(2): 141–156.
   Web of Science ®Google Scholar
• Stevens B. , Giorgetta M. , Esch M. , Mauritsen T. , Crueger T. , co-authors . Atmospheric component of the MPI-M Earth System Model: ECHAM6. J. Adv. Model. Earth Syst. 2013; 5(2): 146–172.
   Web of Science ®Google Scholar
• Taylor K. E. , Stouffer R. J. , Meehl G. A . An overview of CMIP5 and the experiment design. Bull. Am. Meteorol. Soc. 2012; 93(4): 485–498.
   Web of Science ®Google Scholar
• Ulbrich U. , Pinto J. G. , Kupfer H. , Leckebusch G. C. , Spangehl T. , co-authors . Changing northern hemisphere storm tracks in an ensemble of IPCC climate change simulations. J. Clim. 2008; 21(8): 1669–1679.
   Web of Science ®Google Scholar
• Ulbrich U. , Leckebusch G. C. , Grieger J. , Schuster M. , Akperov M. , co-authors . Are Greenhouse Gas Signals of Northern Hemisphere winter extra-tropical cyclone activity dependent on the identification and tracking algorithm?. Meteorol. Z. 2013; 22(1): 61–68.
   Web of Science ®Google Scholar
• Uppala S. , Kållberg P. , Simmons A. , Andrae U. , da Costa Bechtold V. , co-authors . The ERA-40 re-analysis. Q. J. Roy. Meteorol. Soc. 2005; 131: 2961–3012.
   Web of Science ®Google Scholar
• van Oldenborgh G. J. , Doblas-Reyes F. J. , Wouters B. , Hazeleger W . Decadal prediction skill in a multi-model ensemble. Clim. Dynam. 2012; 38(7–8): 1263–1280.
   Web of Science ®Google Scholar
• Vecchi G. A. , Msadek R. , Anderson W. , Chang Y. S. , Delworth T. , co-authors . Multiyear predictions of North Atlantic hurricane frequency: promise and limitations. J. Clim. 2013; 26(15): 5337–5357.
   Web of Science ®Google Scholar
• Wang X. L. , Feng Y. , Compo G. , Swail V. , Zwiers F. , co-authors . Trends and low frequency variability of extra-tropical cyclone activity in the ensemble of twentieth century reanalysis. Clim. Dynam. 2013; 40(11–12): 2775–2800.
   Web of Science ®Google Scholar
• Wilks D. S . Statistical Methods in the Atmospheric Sciences. 2006; 2nd ed, Amsterdam: Elsevier.
   Google Scholar