A high-resolution precipitation scenario for the European Alps

Transcription

1 GEOPHYSICAL RESEARCH LETTERS, VOL.???, XXXX, DOI: /, 1 2 A high-resolution precipitation scenario for the European Alps A. Beck, 1 A. Gobiet, 2 P. Haas, 3 H. Formayer, 3 and H. Truhetz 2 A. Beck, Department of Meteorology and Geophysics, University of Vienna, Althanstrasse 14, A-1090 Wien, Austria. (alexander.beck@univie.ac.at) 1 Department of Meteorology and Geophysics, University of Vienna, Wien, Austria 2 Wegener Center for Climate and Global Change, University of Graz, Graz, Austria 3 Institute of Meteorology, University of Natural Resources and Applied Life Sciences, Wien, Austria

2 X-2 BECK ET AL.: A HIGH-RESOLUTION PRECIPITATION SCENARIO Climate impact studies require high-resolution data sets in particular for orographically complex terrain such as the European Alps. Focusing on precipitation, we report on a couple of recently finished high-resolution (i.e., 10 km grid spacing) climate simulations covering the Greater Alpine Region for the period These simulations are based on dynamical downscaling of a global GCM simulation (under emission scenario IS92a) using two different mesoscale models. Following an evaluation of reanalyses-driven runs for the period , regional control and scenario simulations are carried out using both models operated in different setups. Despite different error characteristics, both models agree on the climate-change signal: The spatial pattern resembles the shape of the Alps with sharp gradients across the Alpine ridge. The results indicate an increase in winter precipitation (10-15%) in the vicinity of the Alps but a strong decrease south of the Alps (regionally up to -26%) in summer and autumn.

3 1. Introduction BECK ET AL.: A HIGH-RESOLUTION PRECIPITATION SCENARIO X The increasing demand for high resolution atmospheric data for both the present and possible future climates has fostered the field of regional climate modeling (RCM; Giorgi [2006]). Since the pioneering work of Girogi [1990] and Dickinson et al. [1989] limited area models (LAMs) have been increasingly applied for climate downscaling studies by nesting them into general circulation models (GCM). The high resolution of the LAMs allows for a more precise description of regional forcings such as orography, vegetation or land-sea interaction. Thus, the description of processes related to these forcings such 24 as precipitation improve at higher resolutions [e.g. Denis et al., 2002]. Nevertheless, there is an ongoing debate about the uncertainties related to regional climate simulations. As an attempt to quantify these uncertainties an ensemble of RCMs with about 50 km grid point distance ( x) has recently been analyzed in the framework of the European PRUDENCE project [Deque et al., 2007]. Currently, regional climate models with grid distances of about 25 km are evaluated in the ENSEMBLES project [Murphy et al., 2004; Hewitt, 2005]. The results of the former project indicate that, given the two main sources of uncertainty, namely errors from the driving data and errors in the regional models ( downscaling uncertainty ), the larger uncertainties stem from the driving data [Rowell, 2006; Deque et al., 2007]. With increasing computer power even finer regional climate simulations on the 10 km scale become feasible and are currently performed for various regions of the Earth. It remains to demonstrate wether such simulations carry significantly more information than the coarser PRUDENCE or ENSEMBLES simulations in order to justify the enormous computational costs related with them. Further, it is currently

4 X-4 BECK ET AL.: A HIGH-RESOLUTION PRECIPITATION SCENARIO unclear whether the increased resolution increases the downscaling uncertainty in a way that simulated climate change signals become insignificant. This study is intended to be a first step towards gaining confidence in high resolution climate scenarios and demonstrating their usefulness in orographically complex terrain. Focusing on precipitation, the performance and climate change signal of two high-resolution ( x=10 km) 10-year timeslice simulations from two different models (operated in different setups) over the Greater Alpine Region are investigated. Despite having only one pair of simulations available, this configuration should give first insights as well in the performance of very high resolution climate simulations as in the downscaling uncertainty on top of the inherent uncertainty associated with the global GCM data. 2. Model Experiments 2.1. Domain of Interest The Alpine region has been the focus of many investigations related to climate research in particular with emphasis to precipitation [e.g., Rotach et al., 1997; Frei et al., 2003; Pal et al., 2004]. The complex topography and the vicinity of the Mediterranean sea strongly influence all climate parameters and generate a complex precipitation pattern featuring large differences on small spatial scales. Fig. 1 shows the average annual precipitation for the period derived from the HISTALP dataset ([Auer et al., 2007], see section 3) for the target domain of this study. The realistic simulation of this highly structured pattern is a serious challenge for RCMs requiring high-resolution models capable of simulating the complex interaction with orography. Table 1 summarizes the climatological seasonal precipitation amounts for the whole domain (denoted Reg 0) as

5 BECK ET AL.: A HIGH-RESOLUTION PRECIPITATION SCENARIO X well as four climate-subregions (Regions 1 to 4; Auer et al. [2007], their coarse resolution subregions ) Regional Model Setup We consider 10-year time-slice simulations over Europe with two different models for a past period ( ) and a future period ( ) under IPCC emission scenario IS92a driven by boundary conditions from the ECHAM5 GCM. The past period was additionally simulated in a perfect boundary setup [Christensen et al., 1997] driven by the ERA-40 reanalysis for evaluation purposes. Details about the driving data are given in Section 2.3. The simulations are carried out using the PSU/NCAR mesoscale model (MM5) and the European ALADIN model with a grid resolution of approximately 10 km driven by global data with a 6h-update interval in a one-way nesting setup. MM5 [Dudhia, 1993] is a non hydrostatic model with terrain-following coordinates and was operated using a convection scheme including shallow convection (Kain-Fritsch 2), a mixed phase explizit moisture scheme (Reisner 1), the ETA boundary layer scheme, the Rapit Radiative Transfer Model RRTM, and the NOAH land surface model. The spatial setup consists of two nested domains (30 km and 10 km grid spacing) with 29 levels in the vertical. Both domains are centered on the European Alps with spatial extent of roughly km and km, respectively (for details, see Gobiet et al. [2006]). ALADIN is a spectral LAM developed for operational NWP purposes with a terrain following hybrid pressure coordinate, a semi implicit semi Lagrangian advection scheme and comprehensive physics (Bubnova et al. [1995]). The model domain encloses Central Europe with a spatial extent of roughly 2800 km 2500 km and an equivalent grid point

6 X-6 BECK ET AL.: A HIGH-RESOLUTION PRECIPITATION SCENARIO resolution of approximately 12 km as well as 41 hybrid levels in the vertical (see Beck et al. [2004] for further details). The nesting setup is different for the two models: MM5 is applied in climate-mode forced at the lateral boundaries only using two nested domains whereas ALADIN is applied in a pure downscaling-mode with daily reinitialization of the entire atmospheric fields. Thus, by construction, the ALADIN simulations are stronger constrained by the driving data than the MM5 runs Driving data Driving data for the evaluation simulations ( ) are derived from the ERA40 reanalysis [Uppala et al., 2005]. The two GCM time-slice simulations ( and ) use ECHAM5 [Roeckner et al., 2006] (version 5.2) with T106 spectral truncation, 31 vertical levels and three years spin-up time: For the control-run the observed sea surface temperatures (SSTs) and sea-ice distributions for have been used. The scenario run is based on the IS92a emission scenario [IPCC, 2001] with climatological SST and sea-ice distributions (constant annual cycle) derived from a coupled ECHAM4 run (ECHAM4-OPYC-T42) archived in the CERA database [Bengtsson, 2001]. Since the used ECHAM5 model integration and the regional simulations are 10-year time slice experiments, no direct information about the influence of decadal variability on the results can be derived. In order to qualitatively judge how the modeled future decade fits into the general trend of the 21st century, the SST data of the coupled ECHAM4-run delivering the SST boundary conditions for the time slice experiment were analyzed by comparing the seasonal SST anomalies relative to the reference period. The

7 BECK ET AL.: A HIGH-RESOLUTION PRECIPITATION SCENARIO X SSTs show a clear warming trend during the period 2000 to A substantial part of the seasonal and annual variability can be explained by a linear trend (R 2 0.9). The absolute differences are very small and always below 0.1 K. The climate change signal of the SST ranges from 1.81 K in spring up to 2.16 K in summer. The SST forcing of our time slice experiment for the period 2041 to 2050 is therefore in good agreement with the average development within the first 70 years of the 21st century. This implies, that also the downscaled scenarios for the Alpine region are not heavily disturbed by decadal variations around the average climate state. 3. Evaluation For evaluation we used the gridded precipitation data set for the Greater Alpine region [Efthymiadis et al., 2006] based on the HISTALP database [Auer et al., 2007] with monthly temporal resolution and a grid spacing of 10 min. Both the model simulations and the observational reference are aggregated on a common 25 km grid to avoid spoiling the higher-order statistics due to the different resolution of the individual datasets. Comparisons are carried out for mean seasonal fields in the entire Greater Alpine Region as well as in climate subregions indicated in Fig. 1. Table 2 summarizes the results of the comparison against the HISTALP dataset for both models driven by ERA40 reanalyses. Shown are relative biases (rbias), variance ratios (varr), and pattern correlations (pcor) for MM5 and ALADIN (values separated by forward slash) with respect to the HISTALP data for the subregions (Reg1 to Reg4) and the entire domain (Reg0). The statistics are calculated as averages over the period

8 X-8 BECK ET AL.: A HIGH-RESOLUTION PRECIPITATION SCENARIO Broadly speaking, MM5 shows smaller precipitation biases (2 % in the annual mean over the entire region) compared to ALADIN (19 %) and a more realistic spatial variability on the 25 km scale (varr: 1.0 for MM5, 1.7 for ALADIN). The pattern correlation is roughly similar for both models (0.7) and shows that the precipitation pattern is simulated remarkably well. Nevertheless substantial biases are found for individual seasons and regions: ALADIN substantially overestimates summer precipitation amounts for all regions except region 3. MM5 overestimates winter-time precipitation except for region 3. Closer inspection of region 3 reveals that both models perform very well except for an underestimation of the rainfall amounts in autumn. This indicates that locally important Mediterranean cyclonic activity in autumn is under-represented in both models. A first indication of downscaling-uncertainty on the 10 km scale for subregional-seasonal precipitation can be derived from statistics over the individual seasonal biases in the subregions: The mean rbias amounts to 11 % with a standard deviation (σ) of 17%. Even higher values result from inter-comparing the two models (mean difference in rbias: 14 %, σ = 21 %) which shows that the two models feature very different error characteristics presumably spanning a substantial fraction of the uncertainty range of a larger model ensemble. For the climate change signal, derived from the difference between two simulations however, large parts of these errors (i.e., systematic model errors not related to climate change) are expected to cancel out. The evaluation results for the perfect-boundary simulations presented above are comparable to those of the GCM-driven control simulation (not shown), except that the precipitation amounts are generally higher in the control simulation due to higher moisture

9 BECK ET AL.: A HIGH-RESOLUTION PRECIPITATION SCENARIO X content of the atmosphere introduced by the boundary conditions. The spatial precipita- tion pattern is almost unchanged. 4. Precipitation scenario Figure 2 shows the change in precipitation [%] simulated for the period compared to the control simulation ( ) for all seasons and both models. The importance of the Alps for regional climate change is clearly visible in the change pattern with the Alps acting as a barrier for the climate change signal, particularly separating the strong decrease in summer and autumn precipitation in the south-eastern part from a moderate increases in the north-western part of the region. Perhaps the most striking feature is the similarity of the pattern between the MM5 (left column) and the ALADIN simulations (right column), particularly regarding the considerably different precipitation biases and operating modes of the two models. This similarity clearly indicates a rather small downscaling-uncertainty. Table 3 summarizes the change in precipitation for all seasons and subregions. The quantitative comparison confirms the similarity of the two simulations for all subregions. The subregional-seasonal differences between the MM5 and ALADIN change signals amount to 0.6 % in the mean with a standard deviation of 4.7 %. Comparing these values to the model biases relative to HISTALP and and the inter-model biases (Section 3) shows that indeed the change in precipitation is associated with considerably less uncertainty than the modeled precipitation. The largest changes are simulated for southern regions (3 and 4) in summer and autumn with a reduction of rainfall of up to 25%. An increase in winter precipitation of up to

10 X-10 BECK ET AL.: A HIGH-RESOLUTION PRECIPITATION SCENARIO % is simulated for all regions, except region 2. From an annual perspective the most notable feature is the abrupt change of the spatial patterns from autumn to winter. In terms of 2 m-temperature (not shown), a general increase is simulated for all seasons with a stronger signal in summer and autumn than in winter and an annual mean of 2.3 K (MM5) and 2.2 K (ALADIN). The spatial pattern of the change signal is fairly uniform with slightly increased values over the Alpine ridge in the MM5 simulations whereas in the ALADIN simulations the largest increase occurs south of the Alps. On the larger scale, the results are qualitatively comparable to other studies for the end of the 21st century ( ) performed at lower resolution where the entire Alpine region is generally regarded as one region and no reasonable distinction between Alpine subregions can be drawn (e.g., Deque et al. [1998]; Räisänen et al. [2004]; Giorgi et al. [2004]; Rowell [2005]). Particularly the Alpine region often shows statistically insignificant climate change signals in such studies. The presented high resolution simulations show much more details and are capable to distinguish subregions, e.g., different signals for the Alpine ridge than in the surrounding areas. In view of these result, regarding the mean change over the entire Greater Alpine Region can be misleading since slight increases or neutral conditions north of the Alps are canceled by strong decreases south of the Alps. The numbers presented above (the inter-model differences in the climate change signal) indicate a significance on the 2σ level of precipitation changes larger than 10 %. This estimation of significance does, of course, not regard any uncertainties related to the driving data. 5. Conclusions

11 BECK ET AL.: A HIGH-RESOLUTION PRECIPITATION SCENARIO X High-resolution regional climate simulations over the European Alps have been carried out for the 10y-period 2041 to 2050 using two LAMs nested into a global climate scenario run (IS92a) from the ECHAM5 model. The evaluation of the perfect-boundary simulations for individual climate subregions indicate the applicability of both regional models for climate studies regarding precipitation on the 10 km scale. The similar performance of both models despite the different setup strategies suggests, that the uncertainty associated with the dynamical downscaling is small. Particularly the climate change signal shows much smaller inter-model differences than the precipitation bias and a significant 60-year seasonal precipitation change of 10 to 15% in winter in most regions and up to -26% in summer and autumn south and south-east of the Alps is indicated. The much higher agreement in the precipitation changes compared to the precipitation biases due to canceling of systematic error components shows that climate change signals are more reliable than direct model results. The value of the high resolution simulations compared to simulations with 25 or 50 km grid spacing is particularly visible regarding the sharp gradients in the climate change signal across the Alpine ridge. It is demonstrated that simply regarding the mean change over the entire Greater Alpine Region can be misleading due to cancelation of positive or neutral signals north of the Alps and negative signals south of the Alps. The presented 10 km simulations are capable to resolve climatic sub-regions in the Greater Alpine Region which feature very different characteristics with regard to expected changes in precipitation.

12 X-12 BECK ET AL.: A HIGH-RESOLUTION PRECIPITATION SCENARIO Acknowledgments. This research has been carried out in the framework of the project reclip-more (please refer to for further details) of the Austrian Research Centers, systems research. ECHAM5 simulations have been carried out by Drs. M. Wild and P. Tschuck (ETH Zurich). AB received funding from the Austrian Science Fund FWF under grant P16815-N10, AG and HT received funding from the WegCenter s startup support for its Regional and Local Climate Modeling and Analysis Research Group (ReLoClim). References Auer, I., et al. (2007), HISTALP - historical instrumental climatological surface time series of the Greater Alpine Region, Int. J. Climatol., 47, Beck, A., B. Ahrens, and K. Stadlbacher (2004), Impact of nesting strategies on precipitation forecasting in dynamical downscaling of reanalysis data, Geophys. Res. Lett., 31, pp. 5, doi: /2004gl Bengtsson, L. (2001), ECHAM4 OPYC T Scenario: Greenhouse Gas Experiment (GHG), available from: Bubnova, R., G. Hello, P. Bernard, and J.-F. Geleyn (1995), Integration of the fully elastic equations cast in the hydrostatic pressure terrain following coordinate in the framework of the ARPEGE/Aladin NWP system, Mon. Weather Rev., 123, Christensen, J., B. Machenhauer, R. Jones, C. Schär, P. Ruti, M. Castro, and G. Visconti (1997), Validation of present-day regional climate simulations over Europe: LAM simulations with observed boundary conditions, Climate Dyn., 13,

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16 X-16 BECK ET AL.: A HIGH-RESOLUTION PRECIPITATION SCENARIO [mm/d] Reg0 Reg1 Reg2 Reg3 Reg4 YEAR MAM JJA SON DJF Table 1. Precipitation climatology [mm/d] for the period derived from HISTALP data for the whole region (Reg0) and all subregions (Reg1...4) and seasons. Reg0 Reg1 Reg2 Reg3 Reg4 rbias [%] MM/AL MM/AL MM/AL MM/AL MM/AL YEAR 2/19 3/19 7/37-6/-1 3/14 MAM 10/31 18/39 12/51 6/6 7/24 JJA -4/33-8/31-1/58-6/3-2/28 SON -11/4-5/-5-4/22-21/-11-11/0 DJF 16/7 14/1 23/18-1/-2 22/0 varr [1] YEAR 1.0/ / / / /1.3 MAM 1.1/ / / / /1.6 JJA 0.8/ / / / /1.7 SON 0.8/ / / / /1.2 DJF 1.5/ / / / /1.4 pcor [1] YEAR 0.7/ / / / /0.8 MAM 0.8/ / / / /0.8 JJA 0.8/ / / / /0.8 SON 0.7/ / / / /0.7 DJF 0.7/ / / / /0.7 Table 2. Summary of evaluation statistics for all (sub)regions: Shown are relative bias (rbias), variance ratio (varr), and pattern correlation (cor) for both models (in the format MM/AL) and all seasons. change Reg0 Reg1 Reg2 Reg3 Reg4 [%] MM/AL MM/AL MM/AL MM/AL MM/AL YEAR -4/-4-3/1 5/6-9/-11-12/-15 MAM 1/1 4/2 8/8-2/-3-6/-10 JJA -12/-15-7/2 2/-4-19/-25-26/-26 SON -14/-12-18/-8 0/3-22/-22-23/-26 DJF 9/13 11/10 1/0 10/9 8/15 Table 3. Precipitation change [%] for compared to present day climate for both regional models.

17 BECK ET AL.: A HIGH-RESOLUTION PRECIPITATION SCENARIO X Figure 1. Annual precipitation climatology [mm] derived from HISTALP data for The four climate subregions (following Auer et al. [2007]) are indicated as red lines. Black isolines indicate 800 m height contour.

18 X - 18 BECK ET AL.: A HIGH-RESOLUTION PRECIPITATION SCENARIO MM5 ALADIN MAM JJA SON DJF Figure 2. Climate-change signal [%] in terms of precipitation derived from MM5 (left) and ALADIN simulations (right panel) for all seasons. D R A F T April 23, 2007, 11:18am D R A F T