Abstract
The STatistical Analogue Resampling Scheme (STARS) has already been used for several climate projection studies in different parts of the world and climate projections obtained by STARS play an important role in several impact studies. Thus, it is crucial to provide results that are reasonable in terms of physical consistency. This also includes the annual cycle of the different variables. In this paper, we address the seasonal inconsistency that appears in the results if a demanding setting is used. This is shown on the example of applying STARS to the entire European continent, where the size and the climatological variety of the region determine the demanding setting. In this setting, the current model is not able to provide results with a realistic annual cycle, as it replaces days in autumn with days from spring. This problem is solved by an adaptation of the resampling method, resulting in a new model version of STARS which yields physically reasonable annual cycles. This model adaptation and its effects on the model results are presented in this work. While the old model results show a large overestimation of shortwave radiation in autumn, the annual cycles provided by the new model version are in agreement with observations.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Gädeke A , Hölzel H, Koch H , Pohle I , Grünewald U (2013) Analysis of uncertainties in the hydrological response of a model-based climate change impact assessment in a subcatchment of the Spree River, Germany. Hydrol Process. doi:10.1002/hyp.9933. doi:10.1002/hyp.9933
Hartigan JA (1975) Clustering Algorithms., 99th. Wiley, New York
Hattermann F, Gömann H, Conradt T, Kaltofen M, Kreins P, Wechsung F (2007) Impacts of global change on water-related sectors and society in a trans-boundary central European river basin – part 1: project framework and impacts on agriculture. Adv Geosci 11(11):85–92
Hattermann FF, Post J, Krysanova V, Conradt T, Wechsung F (2008) Assessment of water availability in a Central-European river basin (Elbe) under climate change. Adv Clim Change Res 4:42–50
Huang S, Krysanova V, Österle H, Hattermann FF (2010) Simulation of spatiotemporal dynamics of water fluxes in Germany under climate change. Hydrol Process 24(23):3289–3306
Koch H, Vögele S, Kaltofen M , Grünewald U (2012) Trends in water demand and water availability for power plants—scenario analyses for the German capital Berlin. Clim Change 110(3-4):879–899. doi:10.1007/s10584-011-0110-0. doi:10.1007/s10584-011-0110-0
Liersch S, Cools J, Kone B, Koch H, Diallo M, Reinhardt J, Fournet S, Aich V, Hattermann F (2012) Vulnerability of rice production in the Inner Niger Delta to water resources management under climate variability and change. Environmental Science & Policy
Lutz J, Volkholz J, Gerstengarbe FW (2013) Climate projections for southern Africa using complementary methods. Int J Clim Change Strateg Manag 5(2):130–151
Orlowsky B, Fraedrich K (2009) Upscaling European surface temperatures to North Atlantic circulation-pattern statistics. Int J climatol 29(6):839–849
Orlowsky B, Gerstengarbe FW , Werner PC (2008) A resampling scheme for regional climate simulations and its performance compared to a dynamical RCM. Theor Appl Climatol 92:209–223
Orlowsky B, Bothe O, Fraedrich K, Gerstengarbe FW, Zhu X (2010) Future climates from bias-bootstrapped weather analogs: an application. J Clim 23(13):3509–3524
Stoner AMK, Hayhoe K , Yang X, Wuebbles DJ (2013) An asynchronous regional regression model for statistical downscaling of daily climate variables. Int J Climatol 33(11):2473–2494. doi:10.1002/joc.3603. doi:10.1002/joc.3603
Uppala SM , Kållberg PW, Simmons AJ , Andrae U, Bechtold VDC , Fiorino M, Gibson JK , Haseler J, Hernandez A , Kelly GA, Li X , Onogi K, Saarinen S, Sokka N, Allan RP, Andersson E, Arpe K, Balmaseda MA, Beljaars ACM, Berg LVD, Bidlot J, Bormann N, Caires S, Chevallier F, Dethof A, Dragosavac M, Fisher M, Fuentes M, Hagemann S, Hlm E, Hoskins BJ, Isaksen L, Janssen PAEM, Jenne R, Mcnally AP, Mahfouf JF , Morcrette JJ, Rayner NA, Saunders RW, Simon P, Sterl A, Trenberth KE, Untch A, Vasiljevic D, Viterbo P, Woollen J (2005) The era-40 re-analysis. Q J Roy Meteorol Soc 131 (612): 2961–3012. doi:10.1256/qj.04.176. doi:10.1256/qj.04.176
Weedon G, Gomes S, Viterbo P, Shuttleworth W, Blyth E, Österle H, Adam J, Bellouin N, Boucher O, Best M (2011) Creation of the WATCH forcing data and its use to assess global and regional reference crop evaporation over land during the twentieth century. J Hydrometeorol 12(5):823–848
Werner PC, Gerstengarbe FW (1997) Proposal for the development of climate scenarios. Clim Res 8:171–182
Wilby RL, Wigley TML, Conway D, Jones PD, Hewitson BC, Main J , Wilks DS (1998) Statistical downscaling of general circulation model output: A comparison of methods. Water Res Res 34(11):2995–3008
Wilks DS (2010) Use of stochastic weathergenerators for precipitation downscaling. Wiley Interdisciplinary Reviews:. Clim Change 1(6):898–907. doi:10.1002/wcc.85. doi:10.1002/wcc.85
Wilks DS, Wilby RL (1999) The weather generation game: a review of stochastic weather models. Prog Phys Geogr 23(3):329–357
Zhu X, Wang W, K F (2013) Future climate in the Tibetan plateau from a statistical regional climate model. J Clim. doi:10.1175/JCLI-D-13-00187.1
Zorita E, von Storch H (1999) The analog method as a simple statistical downscaling technique: comparison with more complicated methods. J Clim 12(8):2474–2489
Acknowledgments
This work was funded by the European Community’s 7th Framework Program project FUME, contract 243888.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Lutz, J., Gerstengarbe, FW. Improving seasonal matching in the STARS model by adaptation of the resampling technique. Theor Appl Climatol 120, 751–760 (2015). https://doi.org/10.1007/s00704-014-1205-0
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00704-014-1205-0