This study deals with the optima] strategy for setting up the ALADIN model for the purpose of dynamic downscaling of ERA40 over the Alpine region. The mesoscale model wind field is compared with MAP-SOP reanalysis data and with wind observations at eleven Slovenian stations. As expected, there is an improvement in the conventional statistics at a 10-km grid as compared to the 40-km analyses. However, the differences between the mesoscale model scores at various domains can be greater than the difference between the MAP-SOP reanalyses and a particular mesoscale simulation

Gregor Gregorič

Jože Rakovec

Jure Cedilnik

Mark Žagar

Nedjeljka Žagar

English

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DOWNSCALING OF ERA4O TOR TIIE WIND FIELD IN A COMPLEXTERRAINNedjeljka Zagart, Mark Zagaf ,Jure Ceditnik2, Gregor Gregorid2 and JoZe RakovecrI Chair of Meteorology, Faculfy of Mathematics and Physics, University of Ljubljana2 Meteorological Offiie, Environmental Agency of Slovinia, 1000 Ljubijana, SloveniaE-mail: nedjeljka.zagar@fnf.uni-lj. siAbstract: This study deals wilh the optimal strategy for setting up the ALADIN model fbr the purpose of dynamicdownscaling of 5RA40 over the Alpine region. The mesoscale model wind field is compared with MAp-SOpreanalysis data and with wind observations at elever Slovenian stations. As expected, there is an improvement in thecoaventional slatistics at a 10-km grid as compared to the 40-km analyser. Aorteuer, the differences between thenesoscale model scores at various domains can be greater than the difference between the MAP-SOP reanalyses anda particular mesoscale simulation.Keywords - downscaling, nesting strategt, ALADIN, MAp-SOp reanalysesI.INTRODUCTIONRegional wind cliriates at mesoscale resolutions are usually based on downscaling the globalgeneral circulation models or reanalysis data sets. For the purpose of the wind climatology of Slovenia weapply an operational NWP mode| the ALADIN model, to dynamically donmscale 4}-year reanalysis dataof the European Centre for Medium-Range Weather Forecast (ECMWF) (ERA40) from -120 km ao -10km horizontal resolution. In the present paper, we deal with the optimal strategy for setting up theALADIN model by investigating the impact of the domain size, the lenglh of the spin-up period and thes&ategy for reinitialization.A comparison with observations is carried out for the Mesoscale Alpine Program-SpecialObserving Period (MAP-SOP), for which reanalysis including MAP-SOP observaiions (hereafterMAPERA) are available every three hours on a .'40 km grid (Keil and cardinali,20a4).2. METTIODOLOGY OF DOWNSCALINGDriving ERA40 fields have a higher vertical but a much lower horizontal resolution thanALADIN. The ratio of the horizontal resolutions in ERA40 and ALADIN is 12, a factor that has beenfound sufficient for the purpose of inilializing/coupling regional models (Denis et. al., 2003). The wholeSlovenia is situated inside 3x2 grid boxes of ERA40, as crin be noticed in Fig. 1 (left). This figure alsoshows various domains used for simulation experiments. For one out of three simulations, the nesting iscarried out in two steps. The outer domain (EUROI) covers Europe with a 30-km gdd and contains one-way nested domain SLOV that rnimics an earlier operational ALADIN domain fo: Slovenia with I1.2-kmresolution. Two other domains, denoted EURO and ALPS, are nested directly into ERA40 and they havea horizontal resolution of 10 km.3. Rf,SULTSlnitial conditions for ALADIN are interpolated Aom ERA40 and they hardly contain significaniinformation on the mesoscale. But after the forecast has started the mesoscaie part;f the kinetic energyspectrum is expected to develop quickly. This is shown in Fig. 2 (left). The energy is generated at most ofscales during the first ten hours ald changes after 12 hours are negligible. Thus we take a l2-hour period608for the model spin-up time. lt can also be noticed in Fig. 2 (middle) that the slope of the average$opospheric kinetic "n.rgy spectrum has a wavenumber dependence in the mesoscale range closet to t3than to the expecled k5/3 taw.uols5l46.8lllm,,.,l]*'ll:"MSa50io;s 45:40146.4jEo45.8 it':1:45.6; .ll';*as.a I :l-10 0 10 20 30 13.5 a4:ongitude16 16.5Figure 1. Left: ALADIN domains used for sensitivity experiments, nested ia ERA40. Right: The modelorography over Slovenia in 10-km resolution wiih locations ofthe verification stations overlaid.However, a very different spectrum is found close to the surface, illustrating the stren$h of thesurface forcing. Here, much less energy, as compared to the tropospheric average, is found above -100km (9Ax), and there is relatively rnore energy below this scale. It is similar for the vorticity anddivergence, but the scale is -180 km; i.e., the divergence dominales over vorticity close to the surface atthe mesoscale (Fig. 2, right).14.5 15 15.5:ongit!de1ooci rc-'- - 131 vo.lro".t o'1oo€'o-'310'1o-'1010 -10-10 '1o-t'aE16o10 - 10wvsumber (€dians/m)lo-t to-o to-u to'mvenumbs {6dians/m} wavsumbff (6dla.s/m)Figure 2. ALADIN spectra. Left: kinetic energy spectra at model levels l0 {thin black) and 20 (thickgrey) at the start of the forecast (fl:ll line) and after 12 hours (dashed line) for a single simulationexperiment. Middle: kinetic energy spectra averaged for the 7O-days period and within model levels 8 to18 (4-9 km) (thick line) and for the lowest model level (level 31, at *20 m) (thin line). Right: as in themiddle figure, but for the vorticity (dashed linc) and the divergence (full line).Downscaling is carried out by reinitializing model every two days. An option with dailyreinitialization has been tested but it did not bring improvements. Another option is a continuous run, butthe results of this test were negative, in agreement with other studies indicating that periodicreinitialization of regional models provides better downscaling resulis than the continuous simulation(e.g. Qian et. al., 2003).Three colventional scores are shown in Fig. 3 for the meridional wind componenl during theMAP-SOP. They illustrate the impact of the horizontal resolution (MAPLRA vs. SLOV/EURO/ALPS)and the impact of the lateral boundary conditions {LBC) (SLOV vs. EURO vs. ALPS). A score based onthe 24-hour persistence is also added in figures. Comparing the ALADIN results with the diurnal609persistonce-based score and MAP-SOP reanalyses, it can be concluded that the downscaling to 10 lqrr hasbeen successful. In particular, stations well exposed to the synoptic forcing (RO, KM, LI) and with meanwind speed over 3 ms-l ale characterized by a large anomaly correlation (AC) and a poor persistencescore. For other stations the persistence score is between ALADIN and MAPIRA. At several stations themeaa absolute elror (MAE) is the lowest for the persistence-based forecast, a result associated with veryweak winds ai these locations.EE3t50.1ot.8IFigure 3. scores ar rri--"noionat wird ."-n"r"J"l*ng the MAP-soP. r"n1""unl*ury correlation(AC), middle: mean absolute error (MAE), righl root mean square error (RMSE).While it is expected that the ALADIN scores are better than MAPERA, aless expected outcorae isa spread of scores for various ALADIN domains. The MAE and RMSE scores indicate ihat differencesbetween ALADIN simulations can be greater than the diffurence between one of them and MAP-reanalyses at four times lower resolution.Both ALPS and 9URO have a better performance than the SLOV simulation, which suggests thatthe two-step nesting is not needed. Sensitivity of the statistics to the model domain carries a messageabout the stations' representativity and about the model. In particular, the largest domain (EURO) givesbest results at three mountain stations with little local impact (RO, KM, LI). Other locations, to a largerdegree exposed to autochthonous fealures, are best simulaled r4,ith the smallest domain (ALPS), this factindicating both a positive effect of rhe LBC and deficiencies of the model physics and of a 10-km spacingfor the wind climate in the complex Alpine terrain.4. CONCLUSIONAs expected, there is a clear improvement in the conventional measures of a lO-km NWP modelsuccess as compared to the 40-km MAP-SOP reanalyses. A more interesting feature of the results is thefact that differences between the scores of the sarne model at various domains can be greater than thedifference between the MAP-SOP reanalysis data and a particular mesoscale simulation. It is thusimportant to study the optimal mesoscale model domain fo: the region of interest in prior thedownscaling.RNFARENCESDenis 8., R. Larprise and D. Caya,20A3: Sensitivity of a regional climate model to the resolutioa of thelateral boundary condition s. C lim. Dyn., 20, 1 B7 - 126.Keil C. and C. Ca:dinali, 2004: The ECMWF reanalysis of the MAP Special Observing Period. Q. J. R.Meteorol. Soc., 130, 2821 -2849.Qian, J.-H., A. Seth and S. Zebiak,200l: Reinitialized versus continuous simslaiions for regional climatedownscaling. Mon. l(ea. Rev., l3l, 2857 -287 4.o3Et ,oP ^^Itf!$i.itIMRTII+rpsI r srovI ! €URoI r PERSsi{.rlROtrBINMUBRSGMSPSPO'IrlE+EsrovEUROPERS.t,+i+,-ltln"t,,!o+RO KM 3I {[ U ER S6 MS PS PO II4!-r9 IEURo I|ls! I!,q++ait{4Qfiti,''t 'SoxratNu!aRSGMssrc!r610

DOWNSCALING OF ERA40 FOR THE WIND FIELD IN A COMPLEX TERRAIN

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