Ž .Atmospheric Research 56 2001 147–160www.elsevier.comrlocateratmos

CAPE values and hailstorms on northwestern Spain

Laura Lopez, Jose Luis Marcos, Jose Luis Sanchez, Amaya Castro,´ ´ ´ ´Roberto Fraile)

Laboratorio de Fısica de la Atmosfera, UniÕersidad de Leon, 24071 Leon, Spain´ ´ ´ ´

Accepted 21 November 2000

Abstract

Ž .A study has been carried out in Leon in the northwest of the Iberian Peninsula on´atmospheric convection during summer periods, by analyzing the values of the Convective

Ž .Available Potential Energy CAPE around 07:00 UTC. The project analyzed the data provided bya network of voluntary observers, a hailpad network, and a meteorological station on a sample of224 days. The CAPE values found were not high: they never reached 2000 Jrkg, not even on haildays, i.e. on days with high convective activity. These values are much lower than the onesmeasured in convective situations in tropical regions, but they are within the usual values found inEurope. The same happens with the wet bulb potential temperature measured in Leon. The´frequency distribution of the CAPE values shows a clear prevalence of very low or zero values.The group of days with the lowest CAPE value is that which included days with no storm. Themean value increases on storm days, and it is even higher for the days with recorded hailfalls. Allthese differences are significantly marked. Nevertheless, the differences across the years are notsignificant enough to be able to speak of an influence of the climatic change on the CAPE. Thecorrelation of the CAPE with some of the variables previously used for hail forecasts wasanalyzed, and the correlation found was higher for the lifted index. The possible use of the CAPEas a thunderstorm and hailstorm forecasting method was considered. The results were encourag-ing, especially for hail forecasting, although the CAPE should not be used as the only variable, butcombined with other parameters. Moreover, the relationships between the CAPE and the wet bulbpotential temperature and between the CAPE and the physical parameters of the hailstones werealso analyzed. A relationship was observed with the parameters of the hailstone size distribution.Nonetheless, these results are provisional, and they should be confirmed by analyzing a morerepresentative sample. With a more detailed analysis of these and other relationships, the presentforecast model used by the Laboratory for Atmospheric Physics at the University of Leon is´

) Corresponding author. Dpto. de Fısica, Fac. de CC. Biologicas y Ambientales, Universidad de Leon,´ ´ ´24071 Leon, Spain. Fax: q34-987-291-546.´

Ž .E-mail address: dfqrfl@unileon.es R. Fraile .

0169-8095r01r$ - see front matter q2001 Elsevier Science B.V. All rights reserved.Ž .PII: S0169-8095 00 00095-8

( )L. Lopez et al.rAtmospheric Research 56 2001 147–160´148

expected to be greatly improved by including the CAPE in this model. q 2001 Elsevier ScienceB.V. All rights reserved.

Keywords: CAPE; Hailstorm; Thunderstorm forecasting; Stability indices

1. Introduction

The atmospheric stability has been parameterized by means of stability indicesŽreflecting atmospheric conditions at particular levels Showalter, 1953; Galway, 1956;

George, 1960; Jefferson, 1963; Darkow, 1968; Barber, 1975; Miller, 1976; Litynska et.al., 1976; Adedokun, 1982; Triplet and Roche, 1986; Rezacova and Motl, 1990 . These´ ´

indices were calculated by taking into account differences in temperature at distinctlevels of the atmosphere, which are considered to be of crucial importance. Someforecast models for atmospheric convection have been constructed with these indices,

Ž .and the results are encouraging Sanchez et al., 1998 .´In the past few decades, the Convective Available Potential Energy or CAPE

Ž .Moncrieff and Miller, 1976 has become a widely used variable for evaluating theconvective potential of the atmosphere. Compared with the stability indices, the CAPEhas an important advantage: it does not depend on one particular atmospheric level. It iscalculated by means of an integral of the vertical profile of the atmosphere.

This parameter has been used in the past few years for different kinds of studies. ItŽwas employed to analyze the conditional instability in the tropical atmosphere Williams

. Ž .and Renno, 1993 , for studies on tropical AHot TowersB Williams et al., 1992 , and for´Ž .other research projects on atmospheric convection Renno and Ingersoll, 1996 . The´

ŽCAPE value has even been particularized for continental and oceanic regions Lucas et.al., 1994; Michaud, 1996 . The importance of the CAPE in all these projects has led to a

more precise way of calculating its value, and to certain approximations and correctionsŽ .that may be included in the general formula Doswell and Rasmussen, 1994 . Later

Ž .research into the CAPE also focused on climatic change Ye et al., 1998 , or inquiredinto the possible relationships between this and other parameters that characterize

Ž .atmospheric conditions Blanchard, 1998 .The present paper is devoted to the calculation of the CAPE during summer periods

in the atmosphere over the province of Leon, located in the northwest of Spain. The´intention is not only to outline the normal CAPE values measured both when theconditions are stable and in convective situations, but also to show the relation thatexists between this and another series of predetermined parameters. The analysis of thedifferences that exist between groups of days having varying levels of convectiveactivity, and how this is reflected in similarly differing CAPE values is also undertaken.

Whilst the study does not intend to provide a comprehensive analysis, it does attemptto shed light on the CAPE values in the province of Leon and on the variations of this´index according to different atmospheric conditions. In the future, a deeper knowledgeof these and other relationships will lead to improvements in the currently held hailforecast model developed by the Laboratory for Atmospheric Physics at the Universityof Leon.´

( )L. Lopez et al.rAtmospheric Research 56 2001 147–160´ 149

2. Data sources and methodology

The political authorities in the province of Leon decided to promote the study of the´hail climatology due to the enormous damage to crops caused by hail in this area. Thus,a project was started in 1985 to analyze the climatology of hailstorms in the province ofLeon from a scientific perspective.´

The province of Leon is situated on the northwestern border of the northern plateau´of the Iberian Peninsula. The area is framed by two mountain ranges: one along thenorth, and another along the southwestern border. The rest of the province is a plainmainly given over to farming. In order to study the extent to which hailstorms affectcrops, certain areas were selected within the province. These areas, within which more

Žthan 90% of the total agricultural production of the province is grown Sanchez et al.,´. 2 Ž .1987 and which cover approximately 7000 km , are referred to as study zones Fig. 1 .

Fig. 1. Map of the province of Leon, in the northwest of the Iberian Peninsula. The dotted area represents the´study zone with the network of voluntary observers. The grid of 250 hailpads is also represented, as well as thestation from where the daily radiosounding was launched.

( )L. Lopez et al.rAtmospheric Research 56 2001 147–160´150

In order to detect thunderstorms and hailstorms in the study zone, an infrastructurewas set up which included a vast network of observers and a dense hailpad network.

ŽThe network of observers more than 400 voluntary observers, one in each town or.village in the study zone provided sufficient data for the creation of a database, which is

representative of the atmospheric situation in the province during summer periods. Theobservers provided daily information about the storms and hailfalls, giving details suchas the area affected and the exact hour at which the storm occurred.

The hailpad network consisted of 250 hailpads evenly distributed throughout an areaof 1000 km2 within an important agricultural region. The description of the study zone,

Ž .as well as some of the results obtained has been presented by Fraile et al. 1991, 1999 .The system makes use of a Styrofoam plate, since it is a material on which the impact ofthe hailstones in easily marked. The specifications of the sensor, its calibration, thecharacteristics of the network and the method for measuring the dents have been

Ž .described in a previous paper Fraile et al., 1992 . The hailpads are very useful for ourstudy because they provide objective and precise information about the physicalparameters of hailstones.

Each summer, the Laboratory for Atmospheric Physics at the University of Leon´carries out a period of data collection. This includes daily radiosoundings, which areused to forecast the risk of hailstorms. The sounding is launched every day at 07:00UTC in order to obtain the forecast in time, since the risk of hailstorms is mainly in the

Ž .afternoon Fig. 2 .

Fig. 2. Hourly distribution of thunderstorms in the study zone during the summers from 1986 to 1999according to the data provided by the network of observers.

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The data obtained via the radiosoundings were used to calculate the CAPE valueduring the study period. Later, this parameter was related to other variables alsoobtained by means of the radiosoundings, and to variables provided by a meteorologicalstation. The CAPE was also related to the data provided by the network of observers andby the hailpad network. The variables that were analyzed in relation to the CAPE can bedivided into three groups:

v Variables measured by means of the meteorological stations:-P , Pressure at surface level;0

-T , Temperature at surface level;0

-T , Dew point temperature at surface level;d0

-T , Minimum temperature at surface level;min0v Variables calculated using the data provided by the radiosounding:

-u , wet bulb potential temperature;wŽ .-P , LCL lifted condensation level pressure;LCL

-T , LCL temperature;LCLŽ .-H , CCL convective condensation level altitude;CCL

-T , convective temperature;c

-H , Altitude of the 500 hPa level;500

-H , Altitude of the 300 hPa level;300Ž .-HT , Altitude of the level at which 08C is reached isozero ;0

-HT , Altitude where the temperature of the dew poin is 08C;d0Ž-Atmospheric stability index SW, established by Showalter 1953;

Ž . Ž .-Atmospheric stability index LI lifted index , established by Galway 1956 ;Ž .-Atmospheric stability index TT, established by Miller 1976 ;Ž .-Atmospheric stability index K , established by George 1960 ;

Ž .-Atmospheric stability index H, established by Litynska et al. 1976 .v The variables provided by the hailpad network for each hailfall were:

A , Area affected by the hailfall;h

D , Size of the biggest hailstone registered in each hailfall;max

S, Sample of hailstones measured in each hailfall;N , Average number of hailstones per surface unit;t

E , Estimated total kinetic energy of the hailstones;tŽE , Estimated density of the kinetic energy of the hailstones energy per unitd

.area ;M , Total mass of ice that fell on the ground during the hailfall;t

l, Parameter of the exponential probability density function, calculated by themethod of moments taking into account all the hailstones measured in eachhailfall;

Ž .a , Shape parameter of the gamma probability density function PDF esti-m

mated by the method of moments;b , Scale parameter of the gamma PDF, estimated by the method of moments;m

a , Shape parameter of the gamma PDF estimated by the method of maxi-ml

mum likelihood;

( )L. Lopez et al.rAtmospheric Research 56 2001 147–160´152

b , Scale parameter of the gamma PDF, estimated by the method of maxi-ml

mum likelihood;-DX, Hail size corresponding to the peak of the gamma PDF fit using themethod of moments.

Between 1991 and 1999, a total of 224 days were sampled, all within the months ofJune to September. The radiosoundings were carried out at 0700 UTC. The dataprovided by some radiosoundings carried out during the afternoon were also available.However, they were disregarded as it has been observed that the CAPE values variedgreatly during the day and so that the study remained consistent. This great variability

Ž .depending on the time of the day has also been observed by Patra and De 1998 . Nocorrections were introduced in the general formula for calculating the CAPE, since theresults have mainly been used for comparing the values between the different groupsŽ .Doswell and Rasmussen, 1994 .

Using the information provided by the hailpad network and by the voluntaryobservers, the sample was divided into four groups: days with hailfall, days with nohailfall, days with thunderstorm, and days with no thunderstorm. It is important to takeinto account that the existence of hail is the main indicator of the severity of a storm.Out of the 224 sample days, 73 were storm days in the study zone, and hail wasregistered on 42 days. The number of days with no storm is a remarkable fact whencompared to the other groups studied here. The CAPE was calculated for each one of thesample days, and compared to the four groups.

3. Results and discussion

The maximum value of the CAPE found in Leon did not surpass 2000 Jrkg. It is´Ž . Ž .somewhat below the maximum 2341 Jrkg found by Houze et al. 1993 in Switzer-

Ž .land, and it is also below the 2777 Jrkg calculated by Ducrocq et al. 1998 in France.Nevertheless, these maximum values in Europe are far below the data collected in

Žconvective situations in the USA, where 5000 Jrkg have been reached Williams and.Renno, 1993 .´

In Leon, the mean value of the whole sample is 132 Jrkg. However, it has to be´taken into account that the median is zero, due to the high number of days with nostorm, and due to the fact that on 100 days out of the 151 days with no storm the CAPEwas zero.

The mean value of the CAPE on hail days was 365 Jrkg, clearly higher than the totalŽ .mean almost three times the total , and in any case this value was much higher in this

group than in any other of the groups studied. The group of days with no hail has amean CAPE value of 69 Jrkg, which shows the difference between the two groups. By

Ž .applying the Mann–Whitney M–W test to both groups, it was observed that for asignificance level of 5% each of them showed significant differences. The M–W testalso shows significant differences between the groups of storms days and days with nostorm, with a significance level of 0.05.

In consequence, the mean values of the CAPE would, therefore, seem to follow aŽrising scale, starting with a very low value on days with no convective activity days

( )L. Lopez et al.rAtmospheric Research 56 2001 147–160´ 153

.with no storm, with a mean CAPE value of 69 Jrkg , followed by the group of stormŽ .days with 259 Jrkg , and increasing as the convective activity increases until the

Ž .highest point is reached by the group of hail days mean value of 365 Jrkg . Whendiscussing mean values, it is necessary to refer to the great dispersion of the data: thestandard deviation of the CAPE value is of almost 350 Jrkg for the whole sample, and it

Žincreases in the group of hail days. However, other authors Alexander and Young,.1992; Lucas et al., 1994 have also detected deviations of the same type.

On most days, the CAPE value was between 0 and 100 Jrkg. This result is implicitin the histogram for the whole sample shown in Fig. 3. In contrast, the number of daysin the rest of the groups of the histogram decreases sharply. The histograms thatdistinguish each group are quite similar to the total sample, since the group with thehighest number of days is again the one between 0 and 100 Jrkg, but with changes inthe data percentages included in the different groups. That is to say, 47% of the CAPEvalues on hail days are between 0 and 100 Jrkg, but this percentage rises up to 63% onstorm days, and up to 90% on days with no storm. This distribution is consistent withthe mean values mentioned in the paragraphs above.

Fig. 4 represents the percentage of days with a CAPE below 200 Jrkg and thepercentage of days with a CAPE over 1000 Jrkg, for the whole sample and for each ofthe four groups that are being considered. It can be observed that, as the convectiveactivity increases, the percentage of days with a CAPE below 200 Jrkg decreases andthe percentage of days with a value of more than 1000 Jrkg increases.

It should be mentioned here that cloud seeding using ground generators has beenŽ .carried out in Leon since 1993, with the aim of hail suppression Sanchez et al., 1994 .´ ´

Preliminary results show that a decrease has been registered in the number of hail daysas well as in the amount of damages to the crops in the area protected by the groundgenerators. An immediate question arises, however. Could this decrease be due to thefact that, because of a natural climatic change, those storms that crossed the study zoneduring the years when weather modification was being carried out, possessed less energyand a lower convective potential than storms had previously had? Taking into accountboth that no hypothesis on cloud seeding could demonstrate that these activities

Fig. 3. Histogram of the CAPE values obtained for the 224 days of the sample.

( )L. Lopez et al.rAtmospheric Research 56 2001 147–160´154

Fig. 4. Percentage of days with a CAPE below 200 Jrkg and over 1000 Jrkg for each of the groups analyzed.

influence the energy of storms, and that, in Leon, radiosounding is launched at least a´few hours before the eventual seeding activities, it is necessary to conclude that theamount of energy calculated in the atmosphere is not influenced by cloud seedingactivities. Once this principle had been established, the CAPE was used as an indicatorof the energy of the storms. Surprisingly, the mean value of the CAPE on storm daysvaried from approximately 218 Jrkg before 1993 to 285 Jrkg in the years since 1993when cloud seeding with AgI has taken place. This indicates that the mean energy washigher during the seeding program.

Obviously, the decrease in hail is not due to a decrease in the CAPE value of thestorm, for the mean value has increased. However, could this increase be due to aclimatic change in the opposite direction, towards an increasing intensity of the storms?After applying the M–W test with a significance level of 0.05 to the two groups of

Ž .storm days before and after 1993 , the hypothesis that both samples might have thesame origin cannot be rejected. As such, it can be assumed that, despite the increase inthe CAPE, the energy levels of the storms seem not to have varied significantly duringthe study period. Furthermore, despite the slight increase observed, the variations notedfrom one year to the next are those usual in such cases.

The correlation between the CAPE and the variables described above has also beendetermined. Table 1 shows the linear correlation coefficients and the variables measuredat the meteorological station and by means of the radiosoundings.

None of the coefficients of the linear correlation r in this table can be consideredhigh. However, since the amount of data is important, even a low value for r mayindicate a significant linear correlation between the variables. Thus, following TaylorŽ .1996 the probability that 224 measurements of two variables that were not correlated

< <would yield r G0.13 was calculated as 5%. As a result, the variables in Table 1 whoseabsolute value for r is more than 0.13 can be shown to have a significant correlation

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Table 1Linear correlation coefficients between the CAPE and the meteorological variables selected

Meteorological variables Correlation coefficient r

P y0.150

T 0.240

T 0.31d0

T 0.24min0

u 0.36w

P 0.03LCL

T 0.33LCL

H y0.23CCL

T y0.18c

H y0.27500

H y0.06300

HT y0.160

HT 0.15d0

SW y0.44LI y0.51TT 0.38K 0.38H y0.16

with the CAPE. It can be observed that, with two exceptions, all the variables arecorrelated with the CAPE.

The variables that show a higher frequency are four of the five stability indices,especially LI. This is not surprising, since these variables characterize the atmosphere inrelation to its convective potential. Nevertheless, the stability indices are based on thedifferent temperature characteristics of certain atmospheric levels, whereas the CAPE isan integral parameter, since it refers to the vertical profile of the atmosphere. Therefore,the correlation between the CAPE and the LI is only moderate, a fact that had already

Ž .been observed by Blanchard 1998 .After analyzing in detail the relationship between the CAPE and the presence of

thunderstorms and hailstorms in the study zone, the following contingency tables wereŽ .created Table 2 , both for the CAPE values registering zero or higher and for the

observation of storms.

Table 2Ž . Ž .Contingency tables between a CAPE value of more than zero and the observation of a thunderstorms and b

hailstorms in the study zone

CAPE No CAPE

( )aThunderstorm observed 53 20No thunderstorm observed 51 100

( )bHailstorm observed 36 6No hailstorm observed 68 114

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Table 2a shows how the CAPE functions in forecasting thunderstorms. If the forecastfor thunderstorms in the study zone had only considered the existence of a CAPE valueof more than zero, out of the total sample of 224, the forecast would only have been

Ž .correct for 153 days 68% of the total . The result would have been slightly worse forhail forecasting. Table 2b shows that the forecast would only have been correct in 67%of the total.

Some indices determine the validity of a forecast according to contingency tables,Ž . Ž .such as the True Skill Statistic TSS , the Kuipers Skill Score KSS , and the Heidke

Ž . Ž .Skill Score HSS , all three mentioned by Wilks 1995 . Nevertheless, the first twoŽindices give a different importance to the two types of misses i.e. for different forecasts

for the same sample and with the same scores, the TSS increases when the KSS.decreases, and vice versa . In contrast, the HSS gives the same degree of importance to

Ž . Žunexpected storms misses and to the non-occurrence of an expected storm false.alarm . This index accounts for the fair prediction shown in Table 2: for thunderstorms,

HSS is 0.35, whereas it is 0.31 for the forecast of hailstorms. We have to remember thatthis index has values between y1 for no correct forecasts and q1 for no incorrect

Ž .forecasts Doswell et al., 1990 .When predicting hailstorms, the wrong forecasts show a great number of false alarms

and a small number of unexpected hailstorms. Thus, a CAPE value of zero indicates thata hailfall is unlikely to occur in the following hours. As a result, it could be of interest tocombine this variable with other indices for forecasting hailstorms.

Contingency tables similar to the ones in Table 2, but with the CAPE threshold inŽ .1000 Jrkg Table 3 shows that the number of unexpected thunderstorms and hailstorms

increases, but the number of false alarms decreases considerably. The TSS alsodecreases considerably, although the KSS increases. As for the HSS, the index thatconsiders all types of misses in the same way, it only reaches 0.1 and 0.17 forthunderstorms and hailstorms, respectively, but the number of correct forecasts hasincreased.

As a result, if the threshold for the CAPE was changed to some point between 0 and1000 Jrkg, the forecast would probably be more accurate, either showing higher scoresor better HSS index for the accuracy of the forecast. Nonetheless, the change of thethreshold will not improve the quality of the forecast substantially. Thus, it can be

Table 3Ž .Contingency table between a CAPE of more or less than 1000 Jrkg and the observation of a thunderstorms

Ž .and b hailstorms in the study zone

CAPE)1000 Jrkg CAPE-1000 Jrkg

( )aThunderstorm observed 7 66No thunderstorm observed 3 148

( )bHailstorm observed 6 36No hailstorm observed 4 178

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asserted that the CAPE value alone will not be enough for the prediction of thunder-Ž .storms, a fact that has already been pointed out by Angus et al. 1988 .

Among the correlations with the CAPE shown in Table 1, the case of the wet bulbpotential temperature has to be highlighted, especially for the days with a CAPE of morethan zero. These relationships are different when considering days with or days withoutthunderstorms. The slope of the straight line in Fig. 5 represents the linear relationshipbetween the CAPE and the potential temperature for hail days, which corresponds to thehighest correlation between these two variables, followed by that of the storm days.Thus, this correlation seems to depend heavily on the atmospheric conditions, since itincreases as the atmospheric instability increases.

There are a few considerable differences between the results shown in Fig. 5 and thedata corresponding to tropical areas. Firstly, the wet bulb potential temperature in Leon´during the summer varies between 148C and 238C, whereas in the studies carried out by

Ž .Williams and Renno 1993 in tropical atmospheres, this difference varies between 238C´and 268C approximately.

Secondly, the slope of the straight line according to the data in Fig. 5 indicates thatduring the summer period a variation of 18C in the wet bulb potential temperature meansa change of approximately 0.5 kJrkg in the CAPE value. Other authors have detected

Ž .variations of up to 1 kJrkg in tropical zones Williams et al., 1992 .Group correlations were calculated for the remaining variables provided by the

radiosoundings, but the sliding scale from hail days downwards was not consistent andsuch conclusions as may be drawn are not clear.

Fig. 5. Relationship between the CAPE and the wet bulb potential temperature.

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Table 4Linear correlation coefficients of the CAPE and the wet bulb potential temperature with the meteorologicalvariables chosen

CAPE uw

A y0.06 y0.19h

D y0.25 y0.40max

N 0.15 0.16t

E y0.17 y0.23d

E y0.15 y0.31t

M y0.14 y0.28t

S y0.03 y0.16l 0.36 0.27m

a 0.38 0.68m

b 0.57 0.67m

a 0.52 0.74ml

b 0.60 0.61ml

Finally, the variables obtained from the hailpad network, do not show a goodŽ . Žrelationship with the CAPE Table 4 . The highest correlations are for alpha the shape. Ž .parameter of the gamma PDF and beta the scale parameter . As for the correlation

between the variables obtained by the hailpad network and the wet bulb potentialtemperature, significant correlations have been found between this variable and a , bm m

Ž .and a . However, the small size of the sample only 10 hailfalls on 6 different daysml

makes it impossible to draw any valid conclusion. The results are only provisional.Nevertheless, the relationships between the parameters that define the size of thehailstones and the thermodynamic variables of the thunderstorms are beyond all doubtŽ .Cheng et al., 1985; Dessens and Fraile, 1994 .

A more detailed study of the CAPE in relation to the risk of thunderstorms andŽhailstorms, as well as its relationship with other atmospheric variables for example,

.Ducroq et al., 1998 , could lead to an improvement of the forecast model for hailstormsdeveloped by the Laboratory for Atmospheric Physics at the University of Leon. This´improvement would result from introducing the CAPE value as an added variable in themodel.

4. Conclusions

v The CAPE values during summer periods in Leon, calculated with the data´provided by the radiosoundings launched in the mornings, may be considered within theusual values found in Europe. The maximum convectivity levels are reached during theafternoons.

v It was found that during the period of the hail suppression activities the mean valuesof the CAPE were higher than in the previous years, a fact that is probably due to adefinite climatic change. However, the differences in the CAPE values were notsignificant.

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v In contrast, the morning values of the CAPE differed significantly between dayswith convective activity and days with no such activity. As a result, the CAPE can beconsidered as a parameter for forecasting thunderstorms and hailstorms.

v The possible use of the CAPE as a forecasting factor is supported by its linearcorrelation with the stability indices. However, the analysis of the CAPE as the onlyforecasting variable for thunderstorms and hailstorms has been seen to only be moder-ately accurate and thus it should be used in coordination with other variables.

v Significant correlations have also been observed between the wet bulb potentialŽ .temperature a parameter that is closely related to the CAPE and some variables that

characterize the physical properties of hailstones, especially the hailstone size distribu-tion when gamma distribution is taken into account.

Acknowledgements

The authors want to thank Dr. Jean Dessens and Dr. Clemente Ramıs for their´suggestions about the calculation of the CAPE. They are also grateful to Antonio M.Ortın and Toyi del Canto for their collaboration in the final editing of this paper, and to´Noelia Ramon for translating it into English. The following people collaborated in the´data collection: Antonio Vega, Jose Luis de la Madrid, Fernando Domınguez, Cova-´ ´donga Palencia and Eduardo Garcıa. The help provided by the voluntary observers was´invaluable. The financial help was provided by the Diputacion Provincial de Leon and´ ´

Ž .by the Junta de Castilla y Leon LE 21r97 .´

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