Abstract
Since prehistoric times, the clayey slopes of Orvieto (Central Italy) have been affected by slow movements directly related to soil–atmosphere interaction. Understanding how climate changes could affect future evolutions of such movements is a challenging issue; to this aim, a simulation chain is set up: General Circulation model (GCM) outputs are dynamically downscaled through regional climate models (RCMs); rainfall values are then subjected to techniques to correct biases; so obtained rainfall time series can be adopted as input for tools evaluating slope stability conditions. Three bias correction techniques (BCT) have been applied: linear-scaling, quantile mapping and Analogs method. This work analyses their strength and limitations as well as their capability for outperforming the uncalibrated RCM outputs under current climate conditions (1981–2010) for the Orvieto case study. These results suggest that the BCT may be very useful tools for climate change impact studies where users require high resolution data and systematic errors to be minimized.
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References
Berg P, Feldmann H, Panitz HJ (2012) Bias correction of high resolution regional climate model data. J Hydrol 448–449:80–92
Christensen JH, Hewitson B, Busuioc A, Chen A, Gao X, Held I, Jones R, Koli RK, Kwon W-T, Laprise R, Rueda VM, Mearns L, Menéndez CG, Räisänen J, Rinke A, Sarr A, Whetton P (2007) Regional climate projections. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds) Climate change, the physical science basis. Contribution of working group I to the fourth assessment report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, pp 847–940
Coe JA, Godt JW (2012) Review of approaches for assessing the impact of climate change on landslide hazards. In: Eberhardt E, Froese C, Turner AK, Leroueil S (eds) Landslides and engineered slopes, protecting society through improved understanding, vol 1. Proceedings of the 11th international and 2nd North American symposium on landslides and engineered slopes, Banff, Canada, 3–8 June 2012. Taylor & Francis Group, London, pp 371–377
Collison A, Wade S, Griffiths J, Dehn M (2000) Modelling the impact of predicted climate change on landslide frequency and magnitude in SE England. Eng Geol 55:205–218
Crozier MJ (2010) Deciphering the effect of climate change on landslide activity: A review. Geomorphology 124:260–267
Dee DP, Uppala SM, Simmons AJ, Berrisford P et al (2011) The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q J R Meteorol Soc 137(656):553–597
Dehn M, Burger G, Buma J, Gasparetto P (2000) Impact of climate change on slope stability. Eng Geol 55:193–204
Dixon N, Brook E (2007) Impact of predicted climate change on landslide reactivation: case study of Mam Tor, UK in Landslides. J Int Consort Landslides v 4(2):137–147
Fowler HJ, Ekström M (2009) Multi-model ensemble estimates of climate change impacts on UK seasonal precipitation extremes. Int J Climatol 29(3):385–416
Frei C, Schöll R, Fukutome S, Schmidli J, Vidale PL (2006) Future change of precipitation extremes in Europe: intercomparison of scenarios from regional climate models. J Geophys Res 111, D06105. doi:10.1029/2005JD005965
Gudmundsson L, Bremnes JB, Haugen JE, Engen Skaugen T (2012) Technical note: downscaling RCM precipitation to the station scale using statistical transformations – a comparison of methods. Hydrol Earth Syst Sci 2012(9):6185–6201. doi:10.5194/hess-16-3383-2012
Gutjahr O, Heinemann G (2013) Comparing precipitation bias correction methods for high-resolution regional climate simulations using COSMO-CLM. Theor Appl Climatol: 1–19
Kilsby CG, Jones P, Burton A, Ford A, Fowler H, Harpham C, James P, Smith A, Wilby R (2007) A daily weather generator for use in climate change studies. Environ Model Softw 22:1705–1719
Lafon T, Dadson S, Buys G, Prudhomme C (2013) Bias correction of daily precipitation simulated by a regional climate model: a comparison of methods. Int J Climatol 33(6): 1367–1381. doi: 10.1002/joc.3518, 10.1002/joc.3518#_blank
Lembo Fazio A, Manfredini M, Ribacchi R, Sciotti M (1984) Slope failure and cliff instability in the Orvieto hill. In: 4th international symposium on landslides, vol 2. Toronto, pp 115–120
Lorenz E (1969) Atmospheric predictability as revealed by naturally occurring analogues. J Atmos Sci 26(4):636–646
Maraun D, Wetterhall F, Ireson AM, Chandler RE, Kendon EJ, Widmann M, Brienen S, Rust HW, Sauter T, Themessl M, Venema VKC, Chun KP, Goodess CM, Jones RG, Onof C, Vrac M, Thiele-Eich I (2010) Precipitation downscaling under climate change. Recent developments to bridge the gap between dynamical models and the end user. Rev Geophys 48: RG3003. doi: 10.1029/2009RG000314
Maraun D (2013) Bias correction, quantile mapping and downscaling. Revisiting the inflation issue. J Clim 26:2137–2143
Piani C, Weedon GP, Best M, Gomes SM, Viterbo P, Hagemann S, Haerter JO (2010) Statistical bias correction of global simulated daily precipitation and temperature for the application of hydrological models. J Hydrol 395(3–4):199–215
Rockel B, Will A, Hense A (2008) The regional climate model COSMO-CLM (CCLM). Meteorol Z 17(4):347–348
Scoccimarro E, Gualdi S, Bellucci A, Sanna A, Fogli PG, Manzini E, Vichi M, Oddo P, Navarra A (2011) Effects of tropical cyclones on ocean heat transport in a high-resolution coupled general circulation model. J Clim 24:4368–4384
Sidle RC, Ochiai H (2006) Landslides: processes, prediction, and land use. Water Resour Monogr Ser 18:312 (AGU, Washington, DC). doi:10.1029/WM018
Themeßl MJ, Gobiet A, Heinrich G (2010) Empirical-statisticaldownscaling and error correction of daily precipitation fromregional climate models. Int J Climatol 31:1530–1544. doi:10.1002/joc.2168
Teutschbein C, Seibert J (2012) Bias correction of regional climate model simulations for hydrological climate change impact studies: Review and evaluation of different methods. J Hydrol 456–457:12–29
Tommasi P, Pellegrini P, Boldini D, Ribacchi R (2006) Influence of rainfall regime on hydraulic conditions and movement rates in the overconsolidated clayey slop of the Orvieto hill (Central Italy). Can Geotech J 43:70–86
Tommasi P, Boldini D, Caldarini G, Coli N (2012) Influence of infiltration on the periodic re-activation of slow movements in an overconsolidated clay slope. Can Geotechn J 2013 50(1):54–67. doi:10.1139/cgj-2012-0121
Turco M, Quintana-Seguì P, Llasat MC, Herrera S, Gutiérrez JM (2011) Testing MOS precipitation downscaling for ENSEMBLES regional climate models over Spain. J Geophys Res 116(D18):1–14
Acknowledgments
The authors Rianna and Zollo have developed this work within the framework of GEMINA and NextData projects, funded by the Italian Ministry of Education, University and Research and the Italian Ministry of Environment, Land and Sea.
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Zollo, A.L., Rianna, G., Mercogliano, P., Tommasi, P., Comegna, L. (2014).
Validation of a Simulation Chain to Assess Climate Change Impact on Precipitation Induced Landslides.
In: Sassa, K., Canuti, P., Yin, Y. (eds) Landslide Science for a Safer Geoenvironment. Springer, Cham. https://doi.org/10.1007/978-3-319-04999-1_39
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DOI: https://doi.org/10.1007/978-3-319-04999-1_39
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