Global and Planetary Change 63 (2008) 152–162

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Global and Planetary Change

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The Mediterranean surface wave climate inferred from future scenario simulations

P. Lionello a,⁎, S. Cogo b, M.B. Galati a, A. Sanna a,1

a University of Salento, Department of Material Sciences, Italyb University of Padua, Department of Physics, Italy

⁎ Corresponding author. Department of Material ScieLecce, Italy. Tel.: +39 0832 297085; fax: +39 083229710

E-mail address: piero.lionello@unile.it (P. Lionello).1 Presently at CMCC, Bologna, Italy.

0921-8181/$ – see front matter © 2008 Elsevier B.V. Aldoi:10.1016/j.gloplacha.2008.03.004

A B S T R A C T

A R T I C L E I N F O

Article history:

This study is based on 30-ye Accepted 20 March 2008Available online 3 April 2008

Keywordswave climateMediterranean Seaclimate changeclimate scenariosmodel simulations

ar long simulations of the wind-wave field in the Mediterranean Sea carried outwith the WAM model. Wave fields have been computed for the 2071–2100 period of the A2, B2 emissionscenarios and for the 1961–1990 period of the present climate (REF). The wave model has been forced by thewind field computed by a regional climate model with 50 km resolution. The mean SWH (Significant WaveHeight) field over large fraction of the Mediterranean sea is lower for the A2 scenario than for the presentclimate during winter, spring and autumn. During summer the A2 mean SWH field is also lower everywhere,except for two areas, those between Greece and Northern Africa and between Spain and Algeria, where it issignificantly higher. All these changes are similar, though smaller and less significant, in the B2 scenario,except during winter in the north-western Mediterranean Sea, when the B2 mean SWH field is higher than inthe REF simulation. Also extreme SWH values are smaller in future scenarios than in the present climate andsuch SWH change is larger for the A2 than for the B2 scenario. The only exception is the presence of higherSWH extremes in the central Mediterranean during summer for the A2 scenario. In general, changes of SWH,wind speed and atmospheric circulation are consistent, and results show milder marine storms in futurescenarios than in the present climate.

© 2008 Elsevier B.V. All rights reserved.

1. Introduction

Ocean waves are an important component of the Mediterraneanenvironment and changes of their characteristics or intensity can haveimportant consequences on the management of off-shore activities, ofship traffic and, most importantly, of the long coastline (46,000 km)surrounding the basin and its protection. It is therefore important toidentify changes of thewavefields produced by future emission scenarios.

Waves are the consequence of the strong winds (such as Bora,Mistral-Tramontana, Etesianwinds, Sirocco, Libeccio) blowing over thebasin (see Lionello et al., 2006), and are associated with the passage ofcyclones in the region. The Mediterranean Sea is characterized byintense synoptic scale activity and the Northern Hemisphere stormtrack presents a separate branch crossing the Mediterranean region,with areas of cyclogenesis in the western Mediterranean and ofprevalent cyclolysis in the Central and EasternMediterranean (Lionelloet al 2006). Therefore, waves provide an indirect estimate of windintensity at the daily scale,which is the time scale typical ofwind-wavegeneration, and of frequency and intensity of cyclones.

Until now no study has analyzed the climate change signal in thewhole Mediterranean Sea. A previous study (Lionello et al., 2003)analyzed the change in the Adriatic Sea, using a downscaling

nce, Via per Arnesano, 731000.

l rights reserved.

procedure for computing the forcing wind fields, which wereotherwise underestimated because of the too low resolution of theglobal model used for the scenario computation. Presently, theavailability of high resolution regional climate simulation makespossible to provide an adequate wind forcing over the whole basinwithout the need of a further downscaling.

In fact, the complex land–sea distribution, with narrow basins andhigh steep mountain ridges, implies that high resolution is needed forcomputing thewind field in theMediterranean Sea and the availabilityof correct high resolution winds is a basic requirement for wavemodelling. Generally, underestimate of the wind speed and missingsharp features in the wind fields are source of similar shortcomings inthe computed SWH (Significant Wave Height) fields (Cavaleri andBertotti, 2004). These errors remain large in global climate simulationswhich, because of their rough resolution, are affected by systematicsurface wind underestimate. However, it has been shown that, themodel setup adopted in this study, with a 50 km resolution of theforcingwind field and 0.25° resolution of thewavemodel, is capable ofcorrectly evaluating the observed inter-monthly and inter-annualvariability of the wave field (Lionello and Sanna, 2005). Under theassumption that in the future climate such variability will be similar tothe present, these considerations suggest that the model setupadopted in this study can be used for a correct evaluation of theeffects of climate change on the wave field in the Mediterranean Sea.

A previous study (Lionello and Sanna, 2005) has shown that twomain patterns, corresponding to two EOFs (Empirical OrthogonalFunction) resulting from the PCA (Principal Component Analysis) of

Fig. 1. Comparison between satellite data (SAT_K and SAT_Cdenote theK andCbandof theTopex altimeter for theperiod 1993–2002) andmodel results of theREF simulation.Annualcycles are plotted separately for each decade of the REF simulation (denoted as REF_61,REF_71, and REF_81). Vertical bars show the standard deviation (values in metres).

Fig. 2. Annual average SWH field (top, values in metres), first (middle) and second EOF(bottom) in the REF simulation. EOFs are normalized with their maximum absolutevalue.

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the mean SWH fields describe their inter-monthly variability. The firstpattern has a positive/negative phase which is dominated by theaction of the Mistral wind/Etesian winds. This regime determines awave field which during the positive phase (Mistral) propagatessouth-eastward in the western part and turns eastward over the restof the Mediterranean, reaching its eastern coast. The negative phase isdominated by the presence of high southward propagating waves inthe Aegean Sea and Levantine basin which are linked with the actionof the Etesian winds. The second pattern reflects the effect of bothLibeccio (in the Tyrrenian Sea) and Sirocco (in the Ionian Sea), whichdetermine north-eastward and northward propagatingwaves, respec-tively, mainly in the western and central areas of the Mediterranean.Two main seasons are recognizable: winter (Dec–Jan–Feb–Mar) andsummer (Jun–Jul–Aug–Sep), characterized by the positive andnegative phase of Mistral–Etesian pattern, respectively. Fall (Oct–Nov) and spring (Apr–May) are, instead, characterized by a positivephase of the Libeccio–Sirocco pattern. This study aims to investigatethe presence, the characteristics and the timing of these patterns alsoin future emission scenarios. Moreover, it has been shown (Lionelloand Sanna, 2005) that the intensity of the SWH field presents largeinter-annual and inter-decadal variability and a statistically significantdecreasing trend of mean winter values, whose variability is antic-orrelated with the NAO (North Atlantic Oscillation) pattern.

SWH maxima are located where high wind speed and long fetchare simultaneously present. The largest maxima (Lionello et al., 2006)are located in the western Mediterranean and in the Ionian Sea, underthe action of the Mistral. Two separate maxima are located in theEastern Mediterranean Sea, where the Island of Crete interrupts thefetch of the Etesian winds: one in the Aegean and another in theLevantine basin. Sirocco produces SWH maxima in the NorthernIonian Sea and in the Southern Adriatic. Themaximumdue to the Borawind is present in the Northern Adriatic Sea and that due to theVendavales in the Alboran Sea. SWH extremes show little significanttrends in the present climate. The two main features correspond toSWH reduction in the Ionian and Alboran Sea. Significant SWHincrease is limited to a very small region near the coast of France(Lionello et al., 2006). Unfortunately, all these estimates are based onmodel simulations which are likely unable to fully reproduce theintensity and variability of SWH extremes. This study aims toinvestigate whether in scenarios a climate change signal correspondsto the present trends of the monthly mean SWH fields and there is aneffect of climate change on SWH extremes.

This paper is organized in the following sections. Section 2describes the data and the model used in this study and discusses

their reliability for reproducing the wave climate. Section 3describes the climate change signal present in the mean wavefields. Section 4 describes the results of the GEV (GeneralizedExtreme Value) analysis and the climate change signal for extremeSWH values. Section 5 discusses the results of this study andincludes a summary of its main outcomes.

2. Wave scenario simulations

The present analysis is based on the results of 3 simulations carriedout with the WAM model (WAMDI Group, 1988). Each simulation is30 yr long. The REF simulation considers the 1961–1990 period, the A2and B2 simulations consider the respective scenarios (Nakićenovićet al., 2000) for the period 2071–2100. Note that A2 is a high emissionscenario, while B2 is a low emission scenario. In all simulations theWAM model is implemented in the whole basin with a 0.25° lat–lon

Fig. 3. Annual cycle of monthly average values of first (upper panel) and second (lowerpanel) principal components for REF, A2 and B2 simulations. Vertical bars show thestandard deviation (values in meters).

Fig. 4.Monthly average SWH of REF, A2 and B2 scenario simulations (values in metres).Top panel: annual cycle; vertical bars show the monthly standard deviation. Middlepanel: single monthly values. Bottom panel: results of the Mann–Whitney test;horizontal lines denote threshold values for the 90% confidence level.

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resolution. Output fields (SWH, Significant Wave Height, and direc-tion) are available with a 3-hour interval.

The WAM simulations are forced by the wind fields computed bythe regional climate model RegCM (Giorgi et al., 1993a,b; Pal et al.,2000) driven at the lateral boundaries by the meteorological fieldsfrom the Hadley Centre global atmospheric model HadAM3H at1.25×1.875 lat–lon horizontal resolution (Jones et al., 2001). Seasurface temperature is extracted from corresponding simulations withthe Hadley Centre global coupled model HadCM3 (Jones et al., 2001),which also have provided the SST to the HadAM3Hmodel. The RegCMmodel grid spacing is 50 km and the model domain covers the wholeEuropean region and adjacent Atlantic ocean. A general description ofthe RegCM simulations can be found in Giorgi et al. (2004a,b) and inPal et al. (2004). The forcing is produced by wind fields at the σ= .995level, corresponding at about 50 m above the sea surface. Actually, theWAM model is tuned for using winds at the 10 m level. However, asthis study is focused on the identification of the climate change signal,the choice of the actual level is not important as far as it is within thesurface layer, where the Coriolis effect is negligible. Moreover, thehigher wind level compensates for the underestimate of the windspeed (which is a common feature of atmospheric circulation modelsin the Mediterranean region, see Section 1), so that the monthlyaverage wave height computed by WAM results substantially correct.This is shown in Fig. 1, which compares the annual cycle of themonthly average SWH in the Mediterranean Sea computed by theWAM model with that derived from satellite altimeter observations(available from 1993) for the period 1993–2002. Two annual cycles areshown referring to the C and K band of the Topex-altimeter. Modelresults are shown separately for three different 9-year long periods.Model and observations cannot be reconciled for April and May (and

marginally for March), but for the rest of the annual cycle alldifferences can be explained by inter-decadal variability. Therefore,with the exception of an overestimate in spring, themodel reproducescorrectly the observed SWH annual cycle in the Mediterranean Sea.

It is interesting to evaluate whether the climatology of the wavefield produced by the present climate simulation agrees with thatproduced for Mediterranean Sea and the second half of the 20thcentury by Lionello and Sanna (2005), and whether their definition ofseasons is valid also for scenario simulations. Following the sameapproach, the PCA (Principal Component Analysis) of the monthlymeanwave fields has been carried out. Figs. 2 and 3 show the averagewave fields, the first two EOFs of the REF simulation and the respective

Fig. 5. Top-left panel: Winter SWH (metres) for the REF simulation. The thick contour line denotes the 1.2 m level. Top-right and bottom-right panels: SWH (m) and friction velocity(m/s) differences between A2 and REF. Arrows denote the direction of the SWH difference and wind speed. Negative values denote areas where the SWH is lower in the A2 scenariothan in REF. The thick line close to the Italian coast in the SWH plot denotes the 0 level. Values are everywhere negative for the friction velocity. Differences are significant in the areasfilled with grey values (The MW test with a 90% significance level has been used). Bottom-left panel: SLP differences between A2 and REF (hPa). The thick contour line denotes the−8 hPa level.

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average annual cycles resulting from the WAM REF, A2, B2 simula-tions. The maps show the wave height (contour lines, values inmetres) and the mean wave direction (arrows). Comparison withLionello and Sanna (2005) shows that the present climate simulationreproduces acceptably well the structure and the inter-seasonalvariability of the wave field in the Mediterranean Sea. The A2 andB2 simulations produce EOFs similar to those of the REF simulationand their components follow an annual cycle with a seasonalitysimilar to that of the REF, so that the definition of wave seasonsdescribed in the introduction (Section 1) can be maintained in thisstudy. Actually, some details of the REF climatology differ from thatprevious study. The main difference is the presence in the second EOFof a stronger signature produced by the westerly (named Vendavales)wind in the western Mediterranean between Iberia and the Africacoast. Moreover, the B2 and A2 scenarios present some differencewithrespect to REF which might be suggestive of a change in seasonality: alater transition of the first PC to a positive phase, shifted fromNovember to December, meaning a later onset of the winter mistralregime, its higher value in late winter, meaning a stronger signature ofthe Mistral regime, a lower value of the second PC in spring and earlysummer, meaning a reduction of the southerly wind in spring,particularly in the A2 simulation.

In this study, the MW (Mann–Whitney, e.g. Von Storch and Zwiers,1999) test is used for the assessment of the statistical significance ofthe differences between the REF and the two A2, B2 simulations. Theadvantage of the MW test is that it is non-parametric and, therefore, itallows to attribute a statistical significance to the differences betweentwo samples, without knowing their statistical distribution. The MWtest requires only that the deviations of two samples, whose elementsare denoted as Xi, i=1,..., NX and Yj, j=1,..., NY, from the relative mean

Xi−bXN and Yj−bYN, have the same distribution (without assumptionon its shape) in order to evaluate the significance of the test statistics,which are the so-called ranks of the distributions. In order to computethe ranks, the values Xi and Yj assumed by the variable in the twosamples are set in decreasing order and the rank RX of X is defined asthe sum of the positions of the relative values in this list. Note that thehigher rank corresponds to the sample with the lower values. Theranks can be used for defining the dimensionless variable.

SX ¼ RX � NX NX þ NY þ 1ð Þ=2NXNY NX þ NY þ 1ð Þ=12ð Þ1=2

ð1Þ

The variable SX can be proven to follow a Gaussian distribution,with zero mean and unit variance if NX and NYare large enough, whichis true in this study in which 30 yr are available. Practically, values ofSX higher/lower than +/−1.645 allow to conclude that the values Xi aresignificantly lower/higher than Yj with a 95% confidence level.

3. Climate change of the monthly average SWH fields

The mean annual cycle of the average SWH value over the wholebasin is shown in Fig. 4 for the REF, A2 and B2 scenario simulations. Thetop panel shows themeanmonthly SWHwith vertical bars representingthe corresponding standard deviation. The middle panel shows singlemonthly values and the bottom panel shows the MW test statistics. Inscenarios, there is clear SWHreductionduringNovemberandDecember,with the lowest values produced by the A2 scenario. The isolated SWHincrease during February for the B2 scenario is difficult to interpret interms of climate change signal increasingwith the emission level, and isonly marginally present in the north-western Mediterranean if the

Fig. 6. Same as Fig. 5 except that it refers to spring. The thick line in the SLP difference panel denotes the 0 level.

Fig. 7. Same as Fig. 6 except that it refers to summer. In the top-right and bottom-right panels the thick line denote the 0 level.

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Fig. 8. Same as Fig. 6 except that it refers to autumn.

Fig. 9. SWH differences between B2 and REF. Negative values denote areas where the SWH is lower in the B2 scenario than in REF. Differences are significant in the areas filled withgrey values. White contour lines are used in the areas where differences are significant and negative. Top-left: winter, top-right: spring, bottom-left: summer, bottom-right: autumn.

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whole winter season is considered (see discussion in the nextparagraph). Note that in general SWH tends to be lower in the scenariosimulations, as it is shown by the small number of negative results forthe MW test. Variations are most of time not statistically significant forsinglemonths, but the large prevalence of smaller SWHvalues in A2 andB2 scenarios shows that the reduction is a significant climate changesignal.

Fig. 5 shows thewinter average SWH fields SWH (top-left panel) ofthe REF simulation, the difference A2–REF fields for SWH (top-rightpanel), SLP (Sea Level Pressure, bottom-left panel), and frictionvelocity (bottom-right panel). The SWH difference field is almosteverywhere negative, denoting lower values in the A2 scenario than inthe REF simulation. The main feature is the reduction of the north-westerly wave systems in the Levantine basin and in the Gulf of Lion(north-western Mediterranean). The effect is associated with atendency of the wave mean propagation direction to become moresouthwards in the eastern and more westwards in the north-westernareas of the Mediterranean. The changes of the average surface windare consistent with those of the waves and with those of the averagepressure field, which has a maximum over the Balkan peninsula,implying a clockwise reduction of the atmospheric circulation at thesurface of the Mediterranean Sea.

In spring (Fig. 6) the reduction is even larger than in winter and itaffects the whole Mediterranean basin, with tendency to lower SWHand wind speed, and more northerly directions in both fields,especially in the Levantine basin. Reduction is largest in Ionian Seaat the coast of Greece, where the SWH of the westward wave systemsis much smaller. An isolated intensification of the north-easterlywaves near the Gibraltar Strait is present. Similarly to winter, also for

Fig. 10. Top-left panel: average SWH field used for GEV computation. Each value represents tValues inmetres. The thick contour line, which in this figure is present only in small areas neavalue difference between A2 and REF for SWH (metres) and friction velocity (m/s). Bottom-rZ0.5 in number of cyclone/(deg 2 months). In all panels negative values denote areas where vthe areas filled with grey values. The thick contour line denote the 0 level. White contour l

spring the SWH reduction is associated with a reduction of theclockwise circulation, in turn linkedwith a SLP difference patternwitha maximum over south-eastern Europe.

In summer (Fig. 7) the northerly waves in the Levantine basin(producedby theactionof theEtesianwinds) arehigher in theA2scenario,but significant reduction of SWH continues being present in the westernbasin. The increased SWH in the Levantine basin is associatedwith a localpressure minimum in the SLP difference map, which intensifies thenortherly winds between Greece and Northern Africa.

In autumn (Fig. 8) the reduction of SWH is large over thewhole basinand it is due to a reduction of the westerly component of the wind,particularly large in the central and western Mediterranean areas.

Fig. 9 shows that the differences between B2 and REF are muchsmaller (and less significant) than those between A2 and REF, but theyhave similar characteristics for spring, summer and autumn. Thewinter SWH change (top-left panel) shows that in the western basinthe mistral regime is more intense in the B2 scenario than in REF,showing that the waves in the north-western area are responsible forthe increased average SWH in winter, that is present in Fig. 4. Thissuggests that the climate change signal increases with the emissionlevel, but for the western basin inwinter, where the B2 climate changesignal has the opposite sign. However, this single specific case could beattributed to inter-decadal variability, issue that cannot be addressedin this study.

4. SWH extremes

The GEV (Generalized Extreme Value, Smith, 1986) analysis hasbeen carried out in order to evaluate the distribution of extreme SWH.

he average of the 3 highest SWH events in each winter for every year of the simulation.r the coast, denotes the 4mvalue. Top-right panel and bottom-left panel: 10-year returnight panel: difference of monthly frequency of cyclone centers for cyclones deeper thanalues are lower in the A2 scenario than in REF. Differences are statistically significant inines are used in the areas where differences are significant and positive.

Fig. 12. Same as Fig. 10, except that summer is shown.

Fig. 11. Same as Fig. 10, except that spring is shown.

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Fig. 13. Same as Fig. 10, except that autumn is shown.

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For each point of the grid and for each season the 3 highest SWHevents have been selected. The selection procedure identifiesindependent events in the SWH time series available at each gridpoints, by searching for peaks separated by a minimum 2-day timeinterval. The method of maximum likelihood has been used for thedetermination of the GEV parameters that best fit the observeddistribution. The average value of the SWH events used for theevaluation of the GEV distribution of the REF simulation is shown inthe top-left panels of Figs. 10–13. The plots show that the highestevents are generated by north-westerly and westerly winds over mostof the Mediterranean Sea, with an annual cycle reaching the largestSWH in winter.

Figs. 10–13 refer to the A2 scenario and to winter, spring, summerand autumn in this order. They show the average values of the eventsused for the GEV analysis (top-left), the differences (A2–REF) in thefield of the 10-year return values for SWH (top-right panel) andfriction velocity (bottom-left panel). The bottom-right panel showsthe change of spatial distribution (A2–REF) of cyclone centers forcyclones reaching a depth larger than Z0.5. This value is the criticalthreshold which is exceeded on average every second year in each

Table 1Critical values used for the computation of the cyclone center frequency

Season Thresholds (Z0.5)

Winter 15.2 hPaSpring 13.8 hPaSummer 9.5 hPaAutumn 12.0 hPa

Each value represents the critical threshold which is exceeded on average every secondyear in each month, therefore having a frequency fc=0.5yr−1 for the correspondingseason.

month, therefore having a frequency fc=0.5 yr−1 (see Table 1). Thevalue shown is the number of cyclone centers per square of one degreeper month. Note that the 10-year return2 value has been chosen inorder to provide a representation of the intensity of extreme events,avoiding the extrapolation of the observed distribution which isimplicit when longer return values are considered. These are certainlynecessary for application to coastal defense management andplanning of off-shore structures, but the purpose of this study is toidentify changes of the intensity of extremes and not to providethresholds for engineeristic applications.

During winter the SWH extremes in the A2 scenario are almosteverywhere smaller than those in the present climate. Significantreduction is obtained for the eastward propagating waves in thenorthern areas of the Levantine basin and for the south-eastwardpropagatingwaves in theNorthwesternMediterranean Sea (Fig.10, top-left and top-right). This reduction is consistent with that of the frictionvelocity (Fig. 10, bottom-left) and with the reduction of frequency ofintense cyclones (Fig. 10, bottom-right). Note that the link between theposition of the cyclone centers and thatof the extremewaves is not local,but it corresponds to that found in a previous study (Lionello et al., 2006)and high waves are producedwhen, accounting for the geometry of thebasin, wind is strong and simultaneously fetch is long. The reducedfrequency of intense cyclones in the A2 scenario with respect to REF inthe western Mediterranean produces lower waves at the Italian coast.Similarly, the lower SWH extremes in the Levantine basin are linkedwith the lower frequency of intense cyclones over Greece, Turkey andthe Aegean Sea.

2 The 10-year return value represents the threshold that is on average exceeded oncein a 10-year long period. It gives an estimate of the extreme, potentially damaging anddangerous SWH values that are likely to occur.

Fig. 14. SWH 10-year return value difference between B2 and REF (values in metres) Top-left: winter, top-right: spring, bottom-left: summer, bottom-right: autumn.

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In spring (Fig. 11) SWH extremes are smaller than in winter. Theirreduction in the A2 scenario is large and significant over most of thewestern Mediterranean, in a large area between Greece and theAfrican coast, and around Cyprus. This change is associatedwith lowerwind speed extremes and frequency of cyclones over most of theMediterranean region.

In summer (Fig. 12) extreme SWH increase is observed in two areas.Higher SWHextremesbetweenSpain andAfrica are due to the increasedfrequency of cyclone centers over the surrounding areas. Higher SWHatthe African coast in the central Mediterranean is associated with theintensification ofwestward travelingwave systems, due to higherwindsin the central Ionian Sea and more frequent cyclones between Greeceand the African coast. These are clear examples of the non-localconnection between cyclone frequency and waves.

Reduction of extremes is the main feature of autumn (Fig. 13), withlowerwinds and cyclone frequency overmost of theMediterranean Sea.

In the B2 scenario (Fig. 14) changes with respect to REF are smallerthan in the A2 scenario, and some details differ. However, thereduction of SWH extremes is the largely dominant characteristic alsofor the B2 scenario simulation.

5. Discussion and conclusions

The reduction of the seasonal average SWH is common to winter,spring and autumn in the A2 and B2 scenarios with respect to thepresent climate. This reduction is larger in theA2 than in theB2 scenario,and has a maximum in autumn. It is the general consequence of a meanatmospheric circulationwhich isweaker in scenarios than in thepresentclimate. The SLP pattern producing this change corresponds to an anti-cyclonic feature in the Mediterranean area, whose center is locatednorth-east of the basin inwinter and spring and north-west in autumn.The net effect is the reduction of the zonal eastward component of thesurface winds, with details on directionwith small changes of directiondepending on the season and the basin which are considered. In

summer, when the average circulation has a large meridional compo-nent, with intense southward winds (namely, the Etesian winds in theeastern Mediterranean Sea), the mean SWH increases in both westernand eastern Mediterranean areas, while SWH reduction persists in thecentral Mediterranean Sea.

During winter the B2 scenario has a specific feature not present inthe A2 scenario, which is the increase of SWH in the north-westernMediterranean.

Whether this is a robust feature or a consequence of inter-decadalvariability cannot be assessed within this single study. If confirmed, itwould imply higherwaves in thenorth-westernMediterranean Sea for amoderate increase of green house gas concentration in the atmosphere.

Note that, though in general wind fields and SLP variation can belinked by the geostrophic balance over large areas of the Mediterra-nean Sea, the presence of mountains ridges and surface frictionimplies large deviations from it, so that over small basins and close tothe coast, mainly in the western Mediterranean, the wind componentalong the SLP gradient is very important for difference betweenscenario and present climate wind fields.

Statistically significant changes of the SWH extremes are almosteverywhere negative for all seasons in both A2 and B2 scenarios. Thismeans that high SWH values are likely to become less frequent in thefuture climate. There are very few exceptions where extreme SWHincrease in future scenarios: in the B2 scenario in the Gulf of Lionduring autumn, in the A2 scenario in summer close to the African coastin the Central Mediterranean and near to the Gibraltar strait. Since theassociation between cyclone center positions and large SWH values isnot local and it reflects the presence of intensewind and long fetch thatis required for the production of high waves, there is a space shiftbetween significant changes of SWH extremes and those of cyclonecenter frequency. Moreover as wave growth is an integral response tothe action of the wind along the whole fetch, location of changes ofwind speed and SWH extremes do not match, and, in general,variations of SWH tend to reach the maximum amplitude downwind

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those of the wind speed producing them. When the presence of thesenon-local effects in the response of waves to winds and cyclones areaccounted for, changes in extremes SWH are consistent with those ofwinds and with variations of the intense cyclone frequency, producinga general pattern of milder marine storm extremes, but in summer.

Recent studies have established that the winter seasonal meanSWH has been decreasing during the second half of the 20th century(Lionello and Sanna, 2005). Moreover, maximum SWH has been founddecreasing over small areas of the central and western Mediterranean(Lionello et al., 2006). These former results are consistent with thisstudy and they could be initial signals of a larger climate change,which would be caused by future emission scenarios. Note, however,that multidecadal climate variability is an issue to be accounted for inthe interpretation of the results and is not addressed in this study.However, there is a clear need for multiple climate simulations inorder to filter out inter-decadal variability, which needs to be assessedand might produce large departures from the mean climate state.

This analysis suggests amilder future storm climate, as the dominantSWH reduction can be linked to diminished surface wind and stormactivity. A reduction of cyclone intensity is, moreover, consistent withthe overall decrease of the precipitation which most models predict intheMediterranean area (Giorgi and Lionello, submitted for publication).However, caution is required for associating spatial and seasonaldistribution changes of completely different processes, such as cyclones,SWH and precipitation. In fact, the link with cyclone characteristics andpositions is different between SWH and precipitation. Waves areobviously sensitive to winds over sea, precipitation is sensitive to theadvection of moisture by the wind towards the steep features along thecoasts of the Mediterranean basin. Drier summer conditions, such asthose predicted by most models are not necessarily linked with mildersummermarine storms and the lowerwinter SWH in the north-westernMediterranean Sea cannot be used for inferring lower precipitation inthe northern part of the Mediterranean region.

In summary, with respect to the present climate, future SWHscenarios are characterized by milder marine storms and wave condi-tions, both for average and extreme values inwinter, spring, and autumn,while in summer in some areas mean and extreme SWH are are higher.Most changes appear to increase with the emission level and some ofthem can already be detected, though with a very small intensity, in thepresent climate trends.

Acknowledgements

Authors thank Dr. F. Giorgi and X. Bi for the wind fields producedby the RegCM model and used for the wave simulations carried out inthis study.

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