1. Federal Department of Home Affairs FDHA Federal Office of Meteorology and Climatology MeteoSwiss Synthetic future weather time-series at the local scale D. E. Keller, A. M. Fischer, C. Frei, M. A. Liniger, C. Appenzeller, R. Knutti CH2018 Workshop, 2 nd July 2015

2. 2 Denise KellerCH2018 Workshop, 2nd July 2015 Motivation  Future daily weather data at the local scale are required for many applications & impact models  Currently available daily climate change scenarios for Switzerland (CH2011) were derived by delta-change approach  does not account for changing temporal structures  Different studies found evidence for future changes in wet/dry spell lengths (e.g. Fischer et al., 2014, CH2011, 2011 ) (C. Schaer 2003)

3. 3 Denise KellerCH2018 Workshop, 2nd July 2015 Simulation of daily weather time-series Single-site Precipitation occurrence (Richardson, 1981) Model: 1 st order two-state Markov chain Parameters: transition probabilities p 11 & p 01 wet 1 dry 0 p 11 p 01 p 10 p 00 Precipitation amount (Wilks, 1998) Model: Mixture of two exp. distributions Parameters: β 1, β 2 & w Min. & max. temperature (Richardson, 1981) Model: first-order auto-regressive model Parameters: μ dry, σ dry, μ wet, σ wet & Φ Temp

4. 4 Denise KellerCH2018 Workshop, 2nd July 2015 Stochastic simulation at multiple sites Spatial consistency Wilks (1998, 1999) ObservationsSingle-site WGsMulti-site WG  Independent simulation at site A & B  Incorporation of spatial correlation  Time-series are correlated days mm/day days mm/day days mm/day

5. 5 Denise KellerCH2018 Workshop, 2nd July 2015 Hydrological application River runoff

6. 6 Denise KellerCH2018 Workshop, 2nd July 2015 Simulation of future weather data Perturbation of current WG parameter WG parameters current climate WG parameters future climate Change in parameters Simulation of future daily weather Δs from 12 RCMs ENSEMBLES (A1B) …… 12 future climatologies observed climatology @ station 12 * 100 ts of future daily data … … … No emission scenario uncertainty included, e.g. Knutti (2010)

7. 7 Denise KellerCH2018 Workshop, 2nd July 2015 Summary Statistical downscaling tool to provide ensemble of future time-series at the local scale inter-annual variability precipitation & temperature extremes  floods persistent phenomena  droughts, heat waves transient simulations mean characteristics of future climate changes in temporal structure  dry/wet & warm spells inter-variable consistency  compound events spatially consistent  precipitation sums over area, hydrology

8. 8 Denise KellerCH2018 Workshop, 2nd July 2015 Further developments Stochastic MOS Modelled variable is used to predict WG parameters @ station WG parameters used for stochastic simulation of time- series inter-annual variability adopted from climate model temporal structure adopted from climate model transient simulations Logistic regression

9. 9 Denise KellerCH2018 Workshop, 2nd July 2015  D.E. Keller, A.M. Fischer, C. Frei, M.A. Liniger, C. Appenzeller, R. Knutti. 2015a. Implementation and validation of a Wilks-type multi-site daily precipitation generator over a typical Alpine river catchment, HESS, doi:10.5194/hess-19-2163- 2015.  D.E. Keller, A.M. Fischer, C. Frei, M.A. Liniger, C. Appenzeller, R. Knutti. 2015b. Synthetic daily weather time-series for future climate in Switzerland. Int. Journal of Climatology, submitted  A.M. Fischer, D.E. Keller, M.A. Liniger, J. Rajczak, C. Schär, C. Appenzeller. 2014. Projected changes in precipitation intensity and frequency in Switzerland: a multi-model perspective, Int. Journal of Climatology, doi: 10.1002/joc.4162 THANK YOU