Climate fluctuations in the Czech Republic during the period 19612005

INTERNATIONAL JOURNAL OF CLIMATOLOGYInt. J. Climatol. 29: 223–242 (2009)Published online 23 May 2008 in Wiley InterScience(www.interscience.wiley.com) DOI: 10.1002/joc.1718

Climate fluctuations in the Czech Republic during the period1961–2005

Rudolf Brazdil,a* Katerina Chroma,a Petr Dobrovolnya and Radim Tolaszb

a Institute of Geography, Masaryk University, Kotlarska 2, 611 37 Brno, Czech Republicb Czech Hydrometeorological Institute, Na Sabatce 17, 143 06 Praha 4- Komorany, Czech Republic

ABSTRACT: This article addresses climatic fluctuations in the Czech Republic in the period 1961–2005. On the basisof data collected at 23 climatological stations, the fluctuations in monthly, seasonal, and annual series of selected climatevariables, homogenized by means of Standard Normal Homogeneity Test (SNHT) (after Alexandersson), are analysed. Withalmost unchanging temperature continentality expressed by the Gorczynski index, the annual series of mean air temperature,maximum and minimum temperature, daily temperature range, and sunshine duration all exhibit a rising linear trend, incontrast to dropping trends in relative air humidity, number of days with snow cover, and mean wind speed. There are nopronounced changes in precipitation totals, although their distribution over the course of the year becomes more regularin terms of the Markham seasonality index. Temperature trends, with the exception of autumn, show a clear enhancementsince the 1980s; statistically significant rising trends occur for only spring, summer and the year in a good agreement withthe Northern Hemisphere series. Linkage to fluctuation in the North Atlantic Oscillation Index (NAOI) is best expressedby the Czech temperature characteristics for January, February, and winter (in similar fashion to that for the number ofdays with snow cover), which can be ascribed to intensification of the western airflow over Central Europe. On the otherhand, linkage to NAOI for precipitation is essentially weaker, because of the role of synoptic processes in influencing theoccurrence of precipitation at the regional scale. Better relationships for temperature variables and wind speed are obtainedif the Central European Zonal Index (CEZI) is used instead of NAOI as an indicator of circulation patterns in CentralEurope. Copyright 2008 Royal Meteorological Society

KEY WORDS climatic trends; climate variability; climate continentality; Czech Republic

Received 13 June 2007; Revised 28 March 2008; Accepted 7 April 2008

1. Introduction

The current process of global warming is one of themost significant factors affecting the development of thenatural environment at local, regional, and global scales,with impacts upon human society and all its activities.It is ascribed to an intensification of the greenhouseeffect arising out of an increase in concentrations of thegreenhouse gases associated with anthropogenic activity(Houghton et al., 2001; Braganza et al., 2004; KleinTank et al., 2005; Solomon et al., 2007). Over thepast 100 years (1906–2005), the global temperaturerise has reached a value of 0.74 °C (Solomon et al.,2007) which, contrary to the preceding IPCC report(Houghton et al., 2001), means an intensification ofwarming by 0.14 °C, because the temperature rise in theperiod 1901–2000 reached a value of 0.6 °C. A long-term air temperature rise is also evident on the scaleof the Czech Republic. Thus in the mean temperatureseries for the Czech Republic determined for the period1848–2000, the statistically significant linear trend forthe year reached 0.69 °C/100 years and for the annual

* Correspondence to: Rudolf Brazdil, Institute of Geography, MasarykUniversity, Kotlarska 2, 611 37 Brno, Czech Republic.E-mail: [email protected]

period it varied between 0.36 °C/100 years for summerand 0.93 °C/100 years for winter (Brazdil and Kirchner,2007). These values may be markedly higher at individualstations.

Previous studies of climatic fluctuation in CentralEurope have centred upon the analysis of air temperaturesand precipitation (e.g. Brazdil et al., 1995, 1996, 2001;Rapp, 2000; Bohm et al., 2001; Domonkos and Tar,2003; Domonkos et al., 2003; Klein Tank and Konnen,2003; Matulla et al., 2003; Degirmendzic et al., 2004;Jones et al., 2004; Mietus and Filipiak, 2004; Pisoftet al., 2004; Auer et al., 2005; Begert et al., 2005; Castyet al., 2005; Chladova and Kalvova, 2005; Hundechaand Bardossy, 2005; Moberg and Jones, 2005; Maieret al., 2006; Moberg et al., 2006; Pısek and Brazdil,2006; Scherrer et al., 2006; Wulfmeyer and Henning-Muller, 2006; Beniston, 2007; Chladova et al., 2007);some attention has also been paid to other meteorologicalelements like snow cover, sunshine, cloudiness, and hail-storms (e.g. Brazdil et al., 1994; Falarz, 2002; Laternserand Schneebeli, 2003; Matuszko, 2003; Bednorz, 2004;Franke et al., 2004; Lapin, 2004; Scherrer et al., 2004;Chroma et al., 2005; Huth and Pokorna, 2005; Scherrerand Appenzeller, 2006; Auer et al., 2007). Great atten-tion was also devoted to the study of temporal variability

Copyright 2008 Royal Meteorological Society

224 R. BRAZDIL ET AL.

of temperature- and precipitation-related characteristicssuch as heat-waves (e.g. Kysely et al., 2000; Kysely,2002; Schar et al., 2004; Della-Marta et al., 2007a,b;Fischer et al., 2007a), particularly with respect to theextremely hot and dry summer of 2003 when between22 000 and 35 000 heat-related deaths were recordedacross Europe (e.g. Beniston, 2004; Schar and Jendritzky,2004; Schonwiese et al., 2004; Stott et al., 2004; Trigoet al., 2005; Chase et al., 2006; Fischer et al., 2007b),and droughts (e.g. Szinell et al., 1998; Rebetez, 1999;Domonkos et al., 2001; Lloyd-Hughes and Saunders,2002; Pongracz et al., 2003; Trnka et al., 2007; Brazdilet al., 2008).

The aim of the present contribution is to study recentclimatic fluctuation (1961–2005) in the Czech Republicfor homogeneous series of climate variables, to show theinterconnection of the character of fluctuation among theindividual meteorological elements and to discuss them inthe context of global warming and changes in circulationconditions.

The second section of the article includes an enu-meration of the relevant stations and climate variablesand summarizes the results of the homogenization of theseries employed. Section 3 then gives, for the period1961–2005, the results of the analysis of trends andfluctuations in selected climate variables for the seriesof monthly, seasonal, and annual values, followed by astudy of changes in the character of climate continen-tality in the Czech Republic. The results of this analysisare discussed with reference to global warming, observedcirculation changes in Europe and links between the indi-vidual meteorological elements in the concluding section.

2. Climatological data employed

Data from a total of 23 climatological stations run bythe Czech Hydrometeorological Institute (Figure 1) wereused to characterize climatic fluctuation in the territory of

the Czech Republic in the period 1961–2005, in a seriesof monthly values. The following climate variables wereassessed:

• mean air pressure• mean air temperature• mean maximum air temperature• mean minimum air temperature• sunshine duration• mean relative air humidity• precipitation totals• number of days with snow cover• mean wind speed.

Daily means for air pressure, relative humidity, andwind speed were calculated using the three daily readingsmade at 07 : 00, 14 : 00 and 21 : 00 h of the mean localtime (MLT). For air temperature, a daily weighted meanwas used on those occasions when the evening readingwas taken twice (Kamtz’s formula). Daily temperaturemaxima and minima were measured over a recording daythat ran from 21 : 00 h MLT of the previous day to 21 : 00h MLT of the given day.

The monthly series of all these characteristics weresubject to a relative homogeneity test, known as StandardNormal Homogeneity Test – (SNHT), after Alexander-sson (1986). The relevant reference series was alwaysdetermined by testing the series of any given element atthe selected station. This was calculated as the weightedmean of the data from stations situated within a radius of100 km of site under examination, with the correlationcoefficients with the tested station serving as the weight.By means of SNHT for the individual months, statis-tically significant inhomogeneities were indicated for asignificance level of α = 0.05. The subsequent homog-enization of the series, consisting of the correction ofthe established inhomogeneities, was carried out onlywhen the inhomogeneity identified could be attributedto station metadata (i.e. a shift of station, a change in its

Figure 1. Climatological stations employed in the territory of the Czech Republic (height above sea level is indicated at each station).

Copyright 2008 Royal Meteorological Society Int. J. Climatol. 29: 223–242 (2009)DOI: 10.1002/joc

CLIMATE FLUCTUATIONS IN THE CZECH REPUBLIC 225

instrumentation), or when ‘indubitable inhomogeneities’occurred (i.e. inhomogeneities that are not expressed inthe metadata of the station, but are nevertheless amenableto logical substantiation – Brazdil and Stepanek, 1998).The homogeneous series were then used to complete themissing monthly values for stations and variables men-tioned in Table I.

The share of the months with an established non-homogeneity in the total number of monthly series for thegiven element, together with the share of inhomogeneitiesthat remained uncorrected, is shown in Figure 2. Thelargest numbers of inhomogeneities were found in theseries for wind speed, most of which were also corrected.In contrast, the series for precipitation totals and numberof days with snow cover remained without correction.Among other things, these facts are a reflection of thespatial variability of the individual variables. Elementsspatially well correlated (such as temperature) exhibita higher number of inhomogeneities than variables inwhich the correlation falls away quickly with the increas-ing distance between the stations (see also Figure 3).

3. Climatic fluctuations in the Czech Republic inthe period 1961–2005

For series of monthly, seasonal (DJF, MAM, JJA andSON) and annual values of selected meteorological ele-ments, the linear trends of 23 (occasionally 22) clima-tological stations in the Czech Republic for the period1961–2005 were calculated and their statistical signifi-cance according to a t-test (α = 0.05) was evaluated. Thevalues of trends were expressed graphically by stating themean value and extreme values of trends in the set of 23(22) stations analysed. Further, the percentage share ofthe number of stations at which the positive or negativelinear trend was statistically significant was expressed.Besides this, the corresponding mean annual series wascalculated for each meteorological element throughoutthe Czech Republic to show in more detail any year-by-year fluctuations over the whole 45 years. Its degree ofrepresentation fluctuates, however, with reference to the

Table I. Overview of missing observations for climatologicalstations analysed.

Station Variables Missing data

Cervena SD Dec 1984Hradec Kralove RH Feb 2005, May 2005Kostelnı Myslova SD Mar 1999, June 1999Kucharovice WS Mar–June 1981Kralovice SD Jan 1961–Mar 1963Liberec SD Mar–Apr 1962Milesovka RH Jan 1974Svratouch SD Sep 2005Sumperk T, TMA, TMI,

RHJan 1971–Mar 1974, Oct1989–Mar 1990

PRE, DSC Oct 1989–Mar 1990SD Jan 1963–May 1963,

July 1967, Jan1971–Mar 1974, June1983, Oct 1989–Mar1990

Tabor SD Jan–Feb 1965, Nov1965–Jan 1966, Nov1966–Jan 1967, Dec1971, Dec 1972–Jan1973, Jan 1974, Jan–Feb1975

Vyssı Brod T, TMA, TMI,PRE, DSC,WS, RH

Oct–Nov 1966, Sep1970, Oct 1976

SD Oct–Nov 1966, Oct1969, Sep 1970, Oct1976, June–Sep 1985,July 1993

T, mean air temperature; TMA, mean maximum temperature; TMI,mean minimum temperature; SD, sunshine duration; RH, mean relativeair humidity; PRE, precipitation total; DSC, number of days with snowcover; WS, mean wind speed.

spatial link between individual stations for any given cli-matological characteristic (Figure 3). One representativemagnitude is, for example, mean annual air temperature,where the value of correlation coefficients between indi-vidual stations drops with increasing distance, but even at

Figure 2. Comparison of the relative number of months (%) with established (1) and uncorrected (2) inhomogeneities in series of climatevariables at 23 climatological stations in the Czech Republic (T – mean air temperature, TMA – mean maximum temperature, TMI – meanminimum temperature, SD – sunshine duration, RH – mean relative air humidity, PRE – precipitation total, DSC – number of days with snow

cover, WS – mean wind speed).



Figure 3. Change in correlation coefficients among annual series from 23 climatological stations in the Czech Republic with respect to theirdistance: annual mean air temperature and precipitation totals in the period 1961–2005.

the maximum distance between stations not below 0.80.On the other hand, annual precipitation totals are lessspatially representative, where there exists a markedlystronger drop in correlation between the stations depend-ing on distance, connected with the regionally limitedextent of precipitation events, but also with differencesconditioned by altitude and the orographic patterns (wind-ward and leeward locations) of individual stations.

3.1. Air pressure

Only the Prague-Karlov and Brno-Turany stations wereavailable for the evaluation of air pressure in theperiod 1961–2005. The two stations exhibit very sim-ilar, although statistically insignificant, trends. A risingtrend appears in the mean air pressure series for winterand spring (Table II), which is in connection with a smallchange in air pressure in the remaining seasons, also pro-jected into the rise of the annual values (Figure 4).

3.2. Air temperature

General temperature increase is a common feature influctuations of temperature characteristics studied in theCzech Republic. It is best expressed for May, August,spring, summer, and the year, when rising linear trendsare statistically significant at all stations (Figure 5). Thesignificant trend towards warming is also evident in win-ter for the mean and maximum temperatures, in January

for the maximum, and in July for the minimum. Lineartrends are negative for only some autumn months and forautumn as a whole (particularly mean maximum tempera-ture). A considerable inter-annual changeability is evidentin the variation of series of annual values (Figure 6).The period of importantly higher temperatures, beginningwith the end of the 1980s, was only impaired by the verycold year of 1996, which approached the lowest valuesfor the whole period processed.

3.3. Sunshine

Trends of sunshine duration are in agreement withrising temperature trends, with the general exception ofSeptember, October, and the autumn (Figure 7(a), (b)).At more than three-quarters of the stations employed,statistically significant positive trends prevail in February,May, August, in winter and in spring, and at almostthree-quarters of stations they do the same for the year.

Table II. Values of the linear trend of seasonal and annual seriesof mean air pressure (hPa/10 years) at the Prague-Karlov andBrno-Turany stations in the period 1961–2005. All values are

statistically insignificant at a significance level of α = 0.05.

Station Winter Spring Summer Autumn Year

Prague-Karlov 0.68 0.34 −0.00 −0.07 0.21Brno-Turany 0.72 0.33 −0.02 −0.06 0.21



Figure 4. Fluctuation of the mean annual air pressure at the Prague-Karlov and Brno-Turany stations in the period 1961–2005. Smoothed byGaussian filter over 5 years; dashes mark the linear trend.

Prolongation of annual sunshine duration is in agreementwith the rising temperature trend. The year of 2003was exceptional and surpassed by more than 200 h thenext two highest values from 1982 and from 2005(Figure 7(c)). (For the extraordinary summer of 2003 inthe Czech Republic, refer Pavlık et al., 2003).

3.4. Relative air humidity

Changes in relative air humidity reflect changes in tem-perature and the content of water vapour in the atmo-sphere. A general falling trend in relative air humidity isstatistically significant at more than a half of the stationsin February, May, August, and in spring (Figure 8(a),(b)). A lowering of the annual values of relative humidityin the mean series for the Czech Republic, with minimain 2003 and 1992 (Figure 8(c)), is associated with thisdropping trend. On the other hand, rising trends in rel-ative air humidity are perceptible in October–December(statistically significant for more than a quarter of thestations, with the exception of October) and in autumn(Figure 8(a), (b)).

3.5. Precipitation

Fluctuations in precipitation totals in the Czech Republicin the period 1961–2005 are less pronounced than thosefor air temperature. For months, seasons, and the year,mean linear trends of up to ±5 mm/10 years prevail,with the most frequently observed statistically significantdropping trend in May remaining recorded at up toa quarter of the stations processed (Figure 9(a), (b)).An insignificant trend towards a rise in precipitationis evident in winter and in autumn, with a drop inspring. Remarkable in the variation of annual totals is thesequence of the driest year 2003 after the wettest (2002),with its disastrous August flood in Bohemia (western partof the Czech Republic) – e.g. Brazdil et al. (2005). Thehighest totals in 2001–2002 were comparable with theyears 1965–1966 considered together (Figure 9(c)).

3.6. Snow cover

A lowering of the number of days with snow covermay be observed through the values of linear trendsfor December, January, March, winter, spring, and the

year, even though the trend is only statistically sig-nificant for one-fifth of stations in the annual series(Figure 10(a), (b)). The decrease in the number of thesedays (Figure 10(c)) results from an increase in temper-ature in the winter half-year and an increase in theshare of liquid precipitation at the expense of solid. Twoexceptional winters occurred outside the scope of theperiod processed. The winter of 2005/2006, which wasextraordinary in Central Europe for the great quantity ofaccumulated snow, especially in middle altitudes (Pintoet al., 2007), did not surpass the winters 1962/1963 and1969/1970 in terms of the number of days with snowcover. On the other hand, the number of these days inthe extremely warm winter of 2006/2007 was lower thanin any winter over the 1961–2005 period.

3.7. Wind speed

Falling linear trends characterize the series of mean windspeed appearing, with the exception of October, in allmonths, seasons, and in annual values (Figure 11(a),(b)). Only in the cases of February, September, andOctober are these trends statistically significant in lessthan a quarter of the stations, whereas in July, August,November, in spring, summer, and in the year they aresignificant in more than a half of the stations. A fallingtrend is evident in the series of mean annual wind speedfor the Czech Republic over the period studied, with aminimum being achieved in 1991 and then, up to thepresent, values increase on average, even though theyhave in no year reached the speed values of the 1960s(Figure 11(c)).

4. Changes in the climate continentality of theCzech Republic in the period 1961–2005

The observed fluctuations of individual climate variablesraise the question as to what extent climate continen-tality has changed in the Czech Republic. This may bedescribed in terms of various indices of temperature andprecipitation continentality from which two have beenchosen for further processing: the index of temperaturecontinentality after Gorczynski (1920), and the index ofprecipitation seasonality (Markham, 1970).



Figure 5. (a) Mean and extreme values of linear trends for mean, mean maximum, and mean minimum air temperature (°C/10 years) at 23climatological stations in the Czech Republic over the period 1961–2005 for months, seasons and the year; (b) percentage shares of the number

of stations at which the corresponding positive trend was statistically significant.

One characteristic of typical mid-latitude continen-tal variation in air temperature is a mean minimumin January and a mean maximum in July, with theconspicuous annual temperature range A. The indexof temperature continentality K is calculated from the

formula

K = 1.7(A − 12 sin ϕ)

sin ϕ, (1)

in which ϕ is the latitude of the place. The limiting indexvalues at the 23 stations analysed vary between 17.9



Figure 6. Fluctuation of the mean annual (a), maximum (b) and minimum (c) air temperature in the Czech Republic in the period 1961–2005.Smoothed by Gaussian filter over 5 years; dashes indicate linear trend.

(Churanov) and 26.8 (Brno-Turany and Kucharovice); K

rises on average with longitude and drops with increasingheight above sea level. The mean value of the index is27.2 for the Czech Republic; in the period studied it var-ied between 17.5 in 1974 and 40.0 in 1963 (Figure 12(a)).Despite considerable inter-annual variability, the value ofthe (statistically insignificant) linear trend is only 0.08per 10 years; thus in 1961–2005 no significant changesin the value of temperature continentality were evidentin the Czech Republic. This finding corresponds withthose made by Hirschi et al. (2007) who investigatedcontinentality of the global climate since 1948 based onthe NCEP/NCAR reanalysis data. The largest changesoccurred over the Arctic and Antarctica, while smallerchanges in the reduction of the differences between thewarmest and coldest months in the mean annual varia-tion were found between the northern and southern highlatitudes (i.e. also in mid-latitudes).

Mean annual precipitation variation in the area understudy, like that of air temperature, finds its minimum

concentrated in January and the maximum in July. Shiftsof these extremes to the neighbouring months (Febru-ary/March and June/August, respectively) can appeardepending on the period analysed. For example, decreasein the annual precipitation range is observed at mountainstations (Tolasz et al., 2007). This appears in the indexof precipitation seasonality F after Markham (1970),which is calculated as the vector sum R of the individ-ual monthly totals ri (i = 1, 2, . . ., 12) with the size ofthe resulting vector then divided by the annual precipita-tion sum (

∑12i=1 ri) and expressed as a percentage. Shver

(1975) expressed the value of F as:

F = R

12∑i=1

ri

× 100(%). (2)

For analytical expression of R we select two orthogo-nal axes x (α = 0°) and y (α = 90°):

R =√

R2x + R2

y, (3)



Figure 7. (a) Mean and extreme values of linear trends in sunshine duration (hours/10 years) at 22 climatological stations in the Czech Republicover the period 1961–2005 for months, seasons and the year; (b) percentage shares of the number of stations at which the corresponding trend(1 – positive, 2 – negative) was statistically significant; (c) fluctuation of the mean annual sunshine duration (hours) in the Czech Republic over

the period 1961–2005. Smoothed by Gaussian filter over 5 years; dashes indicate linear trend.

where Rx and Ry are sums of projections of all monthlyvectors on both axes calculated as:

Rx =12∑i=1

ri cos αi, Ry =12∑i=1

ri sin αi. (4)

Value αi is determined for every month as the deviationfrom the zero direction (0°) using the formula:

αi = 360

365.Si, (5)

where Si is a number of days from 1 January to the centreof the i-th month.

A lower value for the F index marks a more bal-anced annual variation of precipitation, and vice versa.The extreme values of the F index at the 23 stationsanalysed in the Czech Republic fluctuated between 9.3%(Churanov) and 31.3% (Ceske Budejovice). This reflectsthe fact that the index decreases with increasing alti-tude. Stations located in the border mountain areas ofBohemia (such as Churanov, 1118 m asl) have higher

precipitation totals in the winter half-year due to inten-sive windward exposure during westerlies episodes whileless elevated positions in the Bohemian basin (such asCeske Budejovice, 388 m asl) have at the same timelower totals due to leeward sheltering effects (Brazdil,1978). With a broad fluctuation of the index of precipi-tation seasonality, between 8.0% in 2004 and 41.8% in1972, with a mean value of 21.5% for the Czech Republicin the 1961–2005 period studied, a statistically signifi-cant falling trend with a value of −1.7% per 10 yearsis markedly expressed (Figure 12(b)). This indicates along-term tendency towards a more balanced distributionof precipitation over the course of the year.

5. Discussion of results and conclusions

As was mentioned in Section 2, analysis of fluctuationsof selected climate variables in this paper is based, incontrast to several previous studies (e.g. Chladova andKalvova, 2005; Huth and Pokorna, 2005; Chladova et al.,2007), on homogenized time series from individual sta-tions. This represents an important improvement because



Figure 8. (a) Mean and extreme values of linear trends in relative air humidity (%/10 years) at 23 climatological stations in the Czech Republicover the period 1961–2005 for months, seasons, and the year; (b) percentage shares of the number of stations at which the corresponding trend(1 – positive, 2 – negative) was statistically significant; (c) fluctuation of the mean annual relative humidity (%) in the Czech Republic over the

period 1961–2005. Smoothed by Gaussian filter over 5 years; dashes indicate linear trend.

non-adjusted inhomogeneities may exercise strong con-trol over long-term trends. This problem can be demon-strated using the example of minimum daily tempera-tures when results of linear trend analysis for originalseries (raw data) are compared with those for adjustedones. Although differences in the average trends forthe whole Czech Republic calculated from 23 stationsare not statistically significant (Figure 13(a)), trends andassociated statistical significances in individual stationscan change dramatically. For example, an increase innumber of stations with significant trends can be seenin May, July, August, spring, summer, and the year(Figure 13(b)). At the Pribyslav station, for example,linear trends for May, July, and August became sta-tistically significant after homogenization. On the otherhand, March and June trends at the Prague-Karlov sta-tion were not to be significant after adjusting. At the sametime, adjusted series show smaller range between extremevalues of linear trends in the set of stations analysed(Figure 13(a)). Measures of corresponding changes in lin-ear trends depend on the number of stations which wereadjusted (Figure 13(c)) as well as on the magnitude ofthe adjustment. It might be expected that extension of the

period under analysis would emphasize the importance ofcareful series homogenization to avoid non-climatic biasfrom calculated trends as documented in several papers(e.g. Bohm et al., 2001; Wijngaard et al., 2003; Aueret al., 2005; Begert et al., 2005; Brunetti et al., 2006;Della-Marta and Wanner, 2006).

There is a question concerned with how far Czechtemperature series reflect the warming detected in globaltemperature series. The Northern Hemisphere tempera-ture series (Brohan et al., 2006) exhibited a statisticallysignificant linear trend of 0.24 °C/10 years for annual val-ues in the period 1961–2005 (Figure 14). The largestpositive anomaly was in 1998, considered on a globalscale to be the warmest year not only since 1850, thebeginning of the time series, but also in the wholemillennium (e.g. Mann et al., 1999; Houghton et al.,2001). Since 1986, annual temperatures have not fallenbelow the 1961–1990 average, with the years 1997–2005particularly highlighting a very compact warm period.A significant temperature rise in the Northern Hemi-sphere series can also be observed for individual seasons(winter 0.32 °C/10 years, spring 0.25 °C/10 years, sum-mer 0.21 °C/10 years, autumn 0.20 °C/10 years during



Figure 9. (a) Mean and extreme values of linear trends in precipitation totals (mm/10 years) at 23 climatological stations in the Czech Republicover the period 1961–2005 for months, seasons and the year; (b) percentage shares of the number of stations at which the corresponding trend(1 – positive, 2 – negative) was statistically significant; (c) fluctuation of the mean annual precipitation totals (mm) in the Czech Republic over

the period 1961–2005. Smoothed by Gaussian filter over 5 years; dashes indicate linear trend.

1961–2005). Since the mid-1980s, not only does intensi-fication of this process appear, but there is also a changein the seasonal structure. For example, in the period1986–2005 the smallest temperature rise moved to winter(0.34 °C/10 years), while the largest became an increasein autumn (0.47 °C/10 years).

In the case of the temperature series for the CzechRepublic, positive linear temperature trends in the period1961–2005 are characteristic of the year and of allseasons (although the linear trend for autumn is only0.01 °C/10 years). Their values are higher than the cor-responding linear trends for the Northern Hemisphere,but they are statistically significant only for spring(0.34 °C/10 years), summer (0.36 °C/10 years) and theyear (0.27 °C/10 years). In these cases, it is also possi-ble to find statistically significant correlation coefficientsbetween the series for the Czech Republic and the North-ern Hemisphere, which reach 0.61 for spring, 0.46 forsummer and 0.52 for the year. On the other hand, therising linear trend of winter temperatures in the CzechRepublic (0.34 °C/10 years) is not statistically significant.As indicated in Kysely and Huth (2006), changes in atmo-spheric circulation in Europe since the 1960s have been

more pronounced in winter than in summer, includinga considerable increase in the persistence of circulationtypes during the 1990s, which may also be reflected in theincrease in the occurrence of climatic extremes observedduring recent years.

The period processed 1961–2005 falls into two partsfrom the point of view of global temperature change: inthe first part, including the 1960s–1970s, temperaturesdo not exhibit conspicuous changes, whereas in thesecond, beginning with the 1980s, significant warming isevident (Figure 14). This creates assumptions for clearlyexpressed trends in meteorological elements, includingan obvious connection with temperature, even thoughtheir seasonal changes can vary relatively considerably.Observed trends of the investigated climate variables inthe Czech Republic are consistent not only with resultsof papers dealing with the same territory (such as Huthand Pokorna, 2005) but also with analyses related toother Central European countries (for temperatures seee.g. Domonkos et al., 2003; Degirmendzic et al., 2004;Mietus and Filipiak, 2004; Begert et al., 2005; Hundechaand Bardossy, 2005; Beniston, 2007; for snow cover e.g.Falarz, 2002; Laternser and Schneebeli, 2003; Bednorz,



Figure 10. (a) Mean and extreme values of linear trends in number of days with snow cover (days/10 years) at 23 climatological stations in theCzech Republic over the period 1961–2005 for months, seasons, and the year; (b) percentage shares of the number of stations at which thecorresponding trend (1 – positive, 2 – negative) was statistically significant; (c) fluctuation of the mean annual number of days with snow cover

in the Czech Republic over the period 1961–2005. Smoothed by Gaussian filter over 5 years; dashes indicate linear trend.

2004; Scherrer et al., 2004 etc.) or to European scale (e.g.Klein Tank and Konnen, 2003; Moberg and Jones, 2005;Moberg et al., 2006). This finding confirms a notableconsistency in climatic patterns for this Central Europeanregion.

In the context of global warming, Karl et al. (1991,1993) have illustrated an asymmetrical rise in tempera-ture extremes. A swifter rise in minimum temperaturesthan in maxima, which resulted in a decrease in thediurnal temperature range (DTR), has been thought tobe a possible sign of intensified concentration of green-house gases in the atmosphere. This feature has promptedmany papers dealing with changes in the DTR and theircauses in different parts of the world (e.g. Easterlinget al., 1997; Dai et al., 1999; Heino et al., 1999; Brunettiet al., 2000, 2006; Stone and Weaver, 2002; Klein Tankand Konnen, 2003; Braganza et al., 2004; Drogue et al.,2005; del Rıo et al., 2007), including Central Europe (e.g.Brazdil et al., 1995, 1996; Weber et al., 1997; Rebetezand Beniston, 1998; Wibig and Głowicki, 2002; Maieret al., 2006). During the period 1950–2004, the trend inthe land-surface DTR (spatial coverage is 71% of the ter-restrial surface) was estimated to be −0.07 °C per decade

(0.20 °C per decade for minimum and 0.14 °C per decadefor maximum temperatures – see Vose et al., 2005). Butfrom 1979 to 2004, there was little change because ofsimilar increases in both maximum and minimum temper-atures. Changes in DTR are associated with cloud coverand atmospheric circulation variability both of which canbe affected by anthropogenic forcings (Solomon et al.,2007). In the case of the 23 studied series of the CzechRepublic during the period 1961–2005, a decreasingtendency in DTR occurs only in September, October,December, and autumn, with statistical significance at aquarter of the stations (Figure 15). On the other hand, allthe remaining seasons and individual months, especiallyFebruary, May, and August, show clear positive trendsin DTR that are significant at more than 75% (February)or 50% (May, spring) of all stations.

Changes in selected meteorological elements in theCzech Republic during 1961–2005 can be partlyexplained by fluctuations in Central European circu-lation patterns. The North Atlantic Oscillation Index(NAOI) (e.g. Wanner et al., 2001; Trigo et al., 2002;Hurrell et al., 2003) is usually used in the study ofsuch relations. The NAO influence on temperature



Figure 11. (a) Mean and extreme values of linear trends in mean wind speed (m s−1/10 years) at 22 climatological stations in the Czech Republicover the period 1961–2005 for months, seasons and the year; (b) percentage shares of the number of stations at which the corresponding trend(1 – positive, 2 – negative) was statistically significant; (c) fluctuation of the mean annual wind speed (m s−1) in the Czech Republic over the

period 1961–2005. Smoothed by Gaussian filter over 5 years; dashes indicate linear trend.

and precipitation is best expressed in winter monthsand in specific locations, which can vary over time(e.g. Jacobeit et al., 2001; Slonosky and Yiou, 2002;Werner and Schonwiese, 2002; Jones et al., 2003).With positive NAOI values (NAOI is calculated asthe standardized difference between the station pres-sure of Gibraltar and Southwest Iceland – see Joneset al., 1997; updated and revised by Vinther et al., 2003;http://www.cru.uea.ac.uk/∼timo/projpages/nao update.htm), the territory of the Czech Republic is influenced bywesterlies with advection of air masses from the AtlanticOcean region. The statistically significant positive trendsin NAOI values during the 1961–2005 period can, how-ever, be demonstrated only for winter, although fromNovember to March NAOI linear trends are also posi-tive (a statistically significant drop of NAOI appears inSeptember).

As may be expected, the link between temperature vari-ables in the Czech Republic and NAOI is the closest,expressed by statistically significant correlation coeffi-cients, for all months from August to March. The highestcorrelations for the mean air temperature occur in January

(0.74), February (0.67) and winter (0.65) (Table III). Therise in temperatures in winter months can be associatedwith an intensification of westerlies in the European-Atlantic sector in the period studied. This is in agreementwith the conclusions of Cahynova (2005), giving theclosest link between temperatures and NAOI for Cen-tral Europe from December to March in particular, withcorrelation coefficients of over 0.80.

Rather low correlation coefficients were found betweenNAOI and precipitation in the Czech Republic (Table III),although they are statistically significant for April (0.37),August (−0.37), September (−0.36), December (0.39),winter (0.32), and summer (−0.34). This indicates agreater role for regional variability in processes of syn-optic scale in the incidence of precipitation (cyclones,troughs, atmospheric fronts). Casty et al. (2005) foundnegative correlations between winter NAOI (DJFM) andAlpine precipitation but they are temporally unstable. Onthe other hand, the correlation between NAOI and thenumber of days with snow cover in the Czech Republic issubstantially higher (January −0.70, winter −0.64, year−0.61, February −0.60), when the western circulation



Figure 12. Fluctuation of the index of temperature continentality K (after Gorczynski) (a) and the index of precipitation seasonality F (%) afterMarkham (b) in the Czech Republic over the period 1961–2005.

Figure 13. Comparison of trends in original (1) and homogenized (2) series of mean minimum daily temperatures in the Czech Republic in theperiod 1961–2005: (a) mean and extreme values of linear trends; (b) percentage shares of the number of stations at which the positive linear

trend was statistically significant; (c) percentage shares of the number of adjusted series.



Figure 14. Fluctuations of anomalies (with respect to the reference period 1961–1990) of temperature series for the Northern Hemisphere andthe Czech Republic in the period 1961–2005. Smoothed by Gaussian filter over 5 years. The corresponding linear trend is marked. Temperature

scale for the Czech Republic series is doubled compared to the Northern Hemisphere series.

(positive NAOI) brings warmth and rain into CentralEurope, both of which negatively influence the durationof snow cover. Similarly high and statistically signifi-cant correlations were found for Central Europe by Bed-norz (2004) while east of 30 °E the relationship becomesinsignificant.

In addition to the NAOI, the Central European ZonalIndex (CEZI) (Jacobeit et al., 2001) can also be usedto characterize circulation patterns in the region. TheCEZI is calculated as the difference of the standard-ized mean sea-level pressure, averaged for the gridpoints 35°N/0°, 35 °N/20 °E, 40°N/0°, 40 °N/20 °E and



Tabl

eII

I.C

orre

latio

nco

effic

ient

sbe

twee

nci

rcul

atio

nin

dice

s(N

AO

I,C

EZ

I)an

dcl

imat

eva

riab

les

inth

eC

zech

Rep

ublic

inth

epe

riod

1961

–20

05(f

orC

EZ

I19

61–

2004

).

Clim

ate

vari

able

Inde

xJ

FM

AM

JJ

AS

ON

DD

JFM

AM

JJA

SON

Yea

r

PN

AO

I0.

300.

340.

450.

010.

520.

590.

540.

570.

510.

440.

390.

150.

470.

320.

450.

260.

32C

EZ

I0.

310.

160.

290.

030.

570.

350.

130.

460.

550.

420.

170.

130.

430.

300.

240.

460.

26T

NA

OI

0.74

0.67

0.46

−0.0

10.

090.

06−0

.02

0.30

0.43

0.44

0.30

0.56

0.65

0.15

−0.1

10.

390.

47C

EZ

I0.

780.

770.

58−0

.21

0.20

−0.0

2−0

.46

0.27

0.30

0.38

0.31

0.75

0.77

0.36

−0.2

70.

100.

55T

MA

NA

OI

0.77

0.69

0.45

−0.0

80.

080.

090.

010.

350.

460.

490.

260.

560.

670.

13−0

.09

0.37

0.48

CE

ZI

0.83

0.79

0.57

−0.2

50.

220.

02−0

.42

0.35

0.36

0.39

0.36

0.76

0.80

0.35

−0.2

30.

160.

53T

MI

NA

OI

0.70

0.62

0.43

0.12

0.04

−0.0

9−0

.14

0.16

0.28

0.33

0.34

0.54

0.61

0.16

−0.2

00.

330.

42C

EZ

I0.

720.

720.

56−0

.11

0.10

−0.1

2−0

.51

0.07

0.13

0.29

0.27

0.70

0.73

0.33

−0.3

00.

010.

51D

TR

NA

OI

−0.1

40.

080.

22−0

.30

0.10

0.29

0.14

0.42

0.44

0.27

−0.1

7−0

.16

0.07

0.03

0.07

0.10

0.29

CE

ZI

−0.0

30.

040.

25−0

.32

0.29

0.19

−0.2

30.

530.

400.

170.

28−0

.06

0.08

0.21

−0.0

80.

190.

25SD

NA

OI

0.20

0.19

0.22

−0.3

00.

130.

300.

080.

440.

500.

21−0

.09

−0.0

80.

230.

020.

020.

140.

24C

EZ

I0.

250.

060.

19−0

.30

0.29

0.16

−0.3

10.

500.

440.

130.

310.

040.

250.

23−0

.14

0.20

0.20

RH

NA

OI

−0.1

2−0

.13

−0.2

70.

36−0

.07

−0.2

6−0

.08

−0.3

1−0

.45

−0.0

90.

050.

03−0

.27

0.06

−0.1

7−0

.17

−0.4

4C

EZ

I−0

.10

−0.0

7−0

.22

0.30

−0.2

0−0

.17

0.26

−0.4

5−0

.45

−0.0

8−0

.49

−0.0

7−0

.20

−0.1

1−0

.01

−0.3

8−0

.42

PRE

NA

OI

0.14

0.22

0.03

0.37

0.03

−0.2

3−0

.11

−0.3

7−0

.36

−0.1

6−0

.13

0.39

0.32

0.08

−0.3

4−0

.05

−0.2

6C

EZ

I0.

180.

480.

270.

270.

00−0

.26

−0.0

2−0

.50

−0.4

3−0

.12

−0.1

00.

380.

420.

08−0

.30

−0.1

7−0

.12

DSC

NA

OI

−0.7

0−0

.60

−0.3

80.

000.

020.

11x

x−0

.26

−0.4

6−0

.36

−0.3

7−0

.64

−0.2

1−0

.04

−0.4

1−0

.61

CE

ZI

−0.6

4−0

.59

−0.3

20.

30−0

.06

−0.1

4x

x−0

.22

−0.3

3−0

.28

−0.4

6−0

.67

−0.1

8−0

.24

−0.1

9−0

.41

WS

NA

OI

0.43

0.22

0.35

−0.0

9−0

.12

0.09

−0.0

5−0

.23

0.04

−0.1

5−0

.01

0.40

0.30

0.08

−0.0

30.

330.

00C

EZ

I0.

410.

390.

580.

26−0

.08

0.18

0.42

−0.0

60.

00−0

.12

0.38

0.50

0.32

0.33

0.13

0.29

−0.1

5

P,m

ean

air

pres

sure

;T

,m

ean

air

tem

pera

ture

;T

MA

,m

ean

max

imum

tem

pera

ture

;T

MI,

mea

nm

inim

umte

mpe

ratu

re;

DT

R,

diur

nal

tem

pera

ture

rang

e;SD

,su

nshi

nedu

ratio

n;R

H,

mea

nre

lativ

eai

rhu

mid

ity;

PRE

,pr

ecip

itatio

nto

tal;

DSC

,nu

mbe

rof

days

with

snow

cove

r;W

S,m

ean

win

dsp

eed;

bold

,st

atis

tical

lysi

gnifi

cant

corr

elat

ion

coef

ficie

nts

(α=

0.05

).



Figure 15. (a) Mean and extreme values of linear trends of diurnal temperature range (°C/10 years) at 23 climatological stations in the CzechRepublic over the period 1961–2005 for months, seasons, and the year; (b) percentage shares of the number of stations at which the corresponding

trend (1 – positive, 2 – negative) was statistically significant.

60°N/0°, 60 °N/20 °E, 65°N/0°, 65 °N/20 °E. In compar-ison with NAOI, CEZI shows closer relations to fluc-tuations of mean, maximum, and minimum tempera-tures as well as with mean wind speed for particularmonths (Table III). The NAOI tends to correlate betterwith mean air pressure and mean number of days withsnow cover. Differences in correlations of the remain-ing climate variables with NAOI and CEZI are mostlyinsignificant.

Kysely and Huth (2006) analysed changes inatmospheric circulation over Europe over the period1958–2000 applying different objective and subjectivemethods. They found an increase in the frequency of anti-cyclonic circulation types in winter from the late 1960sto the early 1990s and then followed by a subsequentdecline (vice versa for cyclonic types). This finding is inagreement with the decrease in the mean wind speed inthe Czech Republic since the 1960s to the early 1990s andfollowing slightly increasing tendency (Figure 11(c)).

Statistically significant trends in a number of climato-logical variables must be taken into serious considerationwith respect to contemporary and assumed impacts ofthe climate on the natural environment and people’s eco-nomic activities. Particularly significant in this contextappears the increase of extreme meteorological and cli-matological phenomena observed in the Czech Repub-lic during the 1990s–2000s (e.g. floods, heat-waves,droughts, windstorms), accompanied in a number ofcases by losses of human life and great material dam-age (e.g. Pavlık et al., 2003; Brazdil et al., 2005; Brazdiland Kirchner, 2007). Similar extreme phenomena wereobserved at the Central European or European scale (seee.g. Ulbrich et al., 2003a,b; Schar and Jendritzky, 2004;Schonwiese et al., 2004; Pinto et al., 2007). Moreover,reconstructed seasonal temperatures for Europe indicatethat the late 20th/early 21st century was probably warmer

than that in any time during past centuries (Luterbacheret al., 2004; Xoplaki et al., 2005). This suggestion is sup-ported also by recent exceptional warmth in 2006–2007(Kundzewicz et al., 2007; Luterbacher et al., 2007; Yiouet al., 2007).

The relationships between temperature and precipita-tion have influenced the occurrence of drought eventsexpressed by Z-index and PDSI (Palmer, 1965). Theseindices demonstrate a tendency towards longer and moreintensive dry episodes in the territory of the CzechRepublic where the most severe episodes occurred inthe late 1980s, early 1990s, and early 2000s. Droughthas a profound effect on national and regional agricul-tural production, with yields being consistently lowerin dry years than in normal years, as was docu-mented for spring barley, winter wheat, forage cropson arable land and hay from meadows by Brazdilet al. (2008). The greatest yield reductions were asso-ciated with droughts in the April–June period of 1988,1992, 1993, 2000, and 2003. Anomalously dry condi-tions in 1992–1994 had a profound influence on forestry,reflected in significant increases in the value of sal-vage felling in the Czech Republic during 1993–1995caused by desiccation of many trees (Brazdil et al.,2008).

Moreover, drying in late spring and early summer canlead to depletion of soil moisture resulting in reductionlatent heat flux and its ability to cool the soil surface.This strong land-atmosphere coupling then contributes tothe amplification of summer temperature extremes andconsequently to a higher incidence of heat-waves (e.g.Schar et al., 2004; Seneviratne et al., 2006; Della-Martaet al., 2007a,b; Fischer et al., 2007a). Land-atmospherecoupling is significantly influenced by global warming,when enhanced greenhouse gas concentrations lead toa northwards shift of climatic zones in Europe. Central



Europe then becomes a new transitional zone betweendry and wet climates and thereby finds itself particularlysusceptible to the effects of land-atmosphere coupling(Seneviratne et al., 2006).

The analysis of climate in the Czech Republic inthe period 1961–2005 demonstrates regional responsesin climatic variability in Central Europe in the current,and most intensely expressed, phase of global warm-ing. In addition to behaviour consistent with globaltrends, there are numerous differences and a great inter-annual variability of the variables processed. Togetherwith virtually unchanging temperature continentality,there appears on the one hand a rise in mean, max-imum, and minimum air temperatures, DTR, air pres-sure, and sunshine duration, and on the other hand adrop in the relative air humidity, number of days withsnow cover, and mean wind speed. Precipitation totalsremain without marked changes, although their distri-bution becomes more regular over the course of theyear. New aspects of this study with regard to otherpapers related to the Czech Republic (e.g. Chladovaand Kalvova, 2005; Huth and Pokorna, 2005; Chladovaet al., 2007) can be seen in the analysis of monthlyseries as well as in those of the seasons and for theyear as a whole. New aspects are also present inrespect of the extension of the period studied and inthe use of new variables (pressure, number of days withsnow cover, wind speed). Climate continentality indices,in comparison of regional temperature trends over theNorthern Hemisphere as well as in quantification ofrelationships between climate variables and circulationpatterns expressed by NAOI and CEZI, also offer newinsights. This article also clearly demonstrates a require-ment for the utilization of homogenized data sets in trendanalyses.

Acknowledgements

This publication came into existence through the supportof research project MSM0021622412 (INCHEMBIOL).We thank anonymous reviewer and Jurg Luterbacher(Bern) for important comments to the first version of thearticle, Borivoj Herzlık (Brno) for the English translation,Tony Long (Svinosice) and Dennis Wheeler (Sunderland)for English style correction.

References

Alexandersson H. 1986. A homogeneity test applied to pre-cipitation data. Journal of Climatology 6: 661–675, DOI:10.1002/joc.3370060607.

Auer I, Bohm R, Jurkovic A, Orlik A, Potzmann R, Schoner W,Ungersbock M, Brunetti M, Nanni T, Maugeri M, Briffa K, Jones P,Efthymiadis D, Mestre O, Moisselin JM, Begert M, Brazdil R,Bochnicek O, Cegnar T, Gajic-Capka M, Zaninovic K, Majs-torovic Z, Szalai S, Szentimrey T, Mercalli L. 2005. A new instru-mental precipitation dataset for the Greater Alpine Region forthe period 1800–2002. International Journal of Climatology 25:139–166, DOI: 10.1002/joc.1135.

Auer I, Bohm R, Jurkovic A, Lipa W, Orlik A, Potzmann R,Schoner W, Ungersbock M, Matulla C, Briffa K, Jones P, Efthymi-adis D, Brunetti M, Nanni T, Maugeri M, Mercalli L, Mestre O,Moisselin JM, Begert M, Muller-Westermeier G, Kveton V,

Bochnicek O, Stastny P, Lapin M, Szalai S, Szentimrey T, Ceg-nar T, Dolinar M, Gajic-Capka M, Zaninovic K, Majstorovic Z,Nieplova E. 2007. HISTALP – historical instrumental climatologi-cal surface time series of the Greater Alpine Region. InternationalJournal of Climatology 27: 17–46, DOI: 10.1002/joc.1377.

Bednorz E. 2004. Snow cover in Eastern Europe in relation totemperature, precipitation and circulation. International Journal ofClimatology 24: 591–601, DOI: 10.1002/joc.1014.

Begert M, Schlegel T, Kirchhofer W. 2005. Homogeneous temperatureand precipitation series of Swizerland from 1864 to 2000. Interna-tional Journal of Climatology 25: 65–80, DOI: 10.1002/joc.1118.

Beniston M. 2004. The 2003 heat wave in Europe: A shape of thingsto come? An analysis based on Swiss climatological data andmodel simulations. Geophysical Research Letters 31: L02202, DOI:10.1029/2003GL018857.

Beniston M. 2007. Entering into the “greenhouse century”: recentrecord temperatures in Switzerland are comparable to the uppertemperature quantiles in a greenhouse climate. Geophysical ResearchLetters 34: L16710, DOI: 10.1029/2007GL030144.

Bohm R, Auer I, Brunetti M, Maugeri M, Nanni T, Schoner W. 2001.Regional temperature variability in the European Alps: 1760–1998from homogenized instrumental time series. International Journal ofClimatology 21: 1779–1801, DOI: 10.1002/joc.689.

Braganza K, Karoly DJ, Arblaster JM. 2004. Diurnal temperaturerange as an index of global climate change during thetwentieth century. Geophysical Research Letters 31: L13217, DOI:10.1029/2004GL019998.

Brazdil R. 1978. Stupen nerovnomernosti rocnıho chodu srazek (Thedegree of irregularity of the annual variation of precipitation).Sbornık Ceskoslovenske spolecnosti zemepisne 83: 91–103.

Brazdil R, Stepanek P. 1998. Kolısanı teploty vzduchu v Brne v obdobı1891–1995 (Fluctuation of air temperature at Brno in the period1891–1995). Geografie – Sbornık Ceske Geograficke Spolecnosti103: 13–30.

Brazdil R, Kirchner K (eds). 2007. Vybrane prırodnı extremy a jejichdopady na Morave a ve Slezsku (Selected Natural Extremes andTheir Impacts in Moravia and Silesia). Masarykova univerzita, Ceskyhydrometeorologicky ustav, Ustav geoniky Akademie ved Ceskerepubliky: Brno.

Brazdil R, Flocas AA, Sahsamanoglou HS. 1994. Fluctuation ofsunshine duration in central and south-eastern Europe. Inter-national Journal of Climatology 14: 1017–1034, DOI:10.1002/joc.3370140907.

Brazdil R, Stepanek P, Kveton V. 2001. Temperature series ofthe Czech Republic and its relation to Northern Hemispheretemperatures in the period 1961–1999. In Detecting and ModellingRegional Climate Change, Brunet India M, Lopez Bonillo D (eds)Springer: Berlin, Heidelberg, New York, Barcelona, Hong Kong,London, Milan, Paris, Tokyo; 69–80.

Brazdil R, Budıkova M, Fasko P, Lapin M. 1995. Fluctuation ofmaximum and minimum air temperatures in the Czech andthe Slovak Republics. Atmospheric Research 37: 53–65, DOI:10.1016/0169-8095(94)00068-O.

Brazdil R, Trnka M, Dobrovolny P, Chroma K, Hlavinka P, Zalud Z.2008. Variability of droughts in the Czech Republic, 1881–2006.Theoretical and Applied Climatology (in press).

Brazdil R, Dobrovolny P, Elleder L, Kakos V, Kotyza O, Kveton V,Mackova J, Muller M, Stekl J, Tolasz R, Valasek H. 2005.Historicke a soucasne povodne v Ceske republice (Historical andRecent Floods in the Czech Republic). Masarykova univerzita, Ceskyhydrometeorologicky ustav: Brno.

Brazdil R, Budıkova M, Auer I, Bohm R, Cegnar T, Fasko P,Lapin M, Gajic-Capka M, Zaninovic K, Koleva E, Niedzwiedz T,Ustrnul Z, Szalai S, Weber RO. 1996. Trends of maximumand minimum daily temperatures in Central and SoutheasternEurope. International Journal of Climatology 16: 765–782,DOI: 10.1002/(SICI)1097-0088(199607)16 : 7<765::AID-JOC46>3.0.CO;2-O.

Brohan P, Kennedy JJ, Haris I, Tett SFB, Jones PD. 2006. Uncertaintyestimates in regional and global observed temperature changes:a new dataset from 1850. Journal of Geophysical Research 111:D12106, DOI:10.1029/2005JD006548.

Brunetti M, Colacino M, Maugeri M, Nanni T. 2000. Trends ofminimum and maximum daily temperatures in Italy from 1865to 1996. Theoretical and Applied Climatology 66: 49–60, DOI:10.1007/s007040070032.

Brunetti M, Maugeri M, Monti F, Nanni T. 2006. Temperature andprecipitation variability in Italy in the last two centuries from



homogenised instrumental time series. International Journal ofClimatology 26: 345–381, DOI: 10.1002/joc.1251.

Cahynova M. 2005. Vliv Severoatlantske oscilace na sezonnıteploty vzduchu ve strednı Evrope (Influence of the NorthAtlantic Oscillation on seasonal temperatures in Central Europe).Meteorologicke Zpravy 58: 41–46.

Casty C, Wanner H, Luterbacher J, Esper J, Bohm R. 2005. Tem-perature and precipitation variability in the European Alps since1500. International Journal of Climatology 25: 1855–1880, DOI:10.1002/joc.1216.

Chase TN, Wolter K, Pielke RA Sr, Rasool J. 2006. Was the 2003European summer heat wave unusual in the global context? Geophys-ical Research Letters 33: L23709, DOI: 10.1029/2006GL027470.

Chladova Z, Kalvova J. 2005. Zmeny vybranych klimatickychcharakteristik v Ceske republice v obdobı 1961–2000 (The changesof selected climate characteristics at the Czech Republic in the period1961–2000). Meteorologicke Zpravy 58: 146–153.

Chladova Z, Kalvova J, Raidl A. 2007. The observed changesof selected climate characteristics in the period 1961–2000.Meteorologicky Casopis 10: 13–19.

Chroma K, Brazdil R, Tolasz R. 2005. Spatio-temporal variability ofhailstorms for Moravia and Silesia in the summer half-year of theperiod 1961–2000. Meteorologicky Casopis 8: 65–74.

Dai A, Trenberth KE, Karl TR. 1999. Effects of clouds, soilmoisture, precipitation and water vapor on diurnal temperaturerange. Journal of Climate 12: 2451–2473, DOI: 10.1175/1520-0442(1999)012<2451:EOCSMP>2.0.CO;2.

Degirmendzic J, Kozuchowski K, Zmudka E. 2004. Changes of airtemperature and precipitation in Poland in the period 1951–2000 andtheir relationship to atmospheric circulation. International Journal ofClimatology 24: 291–310, DOI: 10.1002/joc.1010.

del Rıo S, Fraile R, Herrero L, Penas A. 2007. Analysis of recenttrends in mean maximum and minimum temperatures in a regionof the NW of Spain (Castilla y Leon). Theoretical and AppliedClimatology 90: 1–12, DOI: 10.1007/s00704-006-0278-9.

Della-Marta PM, Wanner H. 2006. A method of homogenizing theextremes and mean of daily temperature measurements. Journal ofClimate 19: 4179–4197, DOI: 10.1175/JCLI3855.1.

Della-Marta PM, Haylock MR, Luterbacher J, Wanner H. 2007a.Doubled length of western European summer heat waves since1880. Journal of Geophysical Research 112: D15103, DOI:10.1029/2007JD008510.

Della-Marta PM, Luterbacher J, von Weissenfluh H, Xoplaki E,Brunet M, Wanner H. 2007b. Summer heat waves over westernEurope 1880–2003, their relationship to large-scale forcings and pre-dictability. Climate Dynamics 29: 251–275, DOI: 10.1007/s00382-007-0233-1.

Domonkos P, Tar K. 2003. Long-term changes in observed temperatureand precipitation series 1901–1998 from Hungary and their relationsto larger scale changes. Theoretical and Applied Climatology 75:131–147, DOI: 10.1007/s00704-002-0716-2.

Domonkos P, Szalai S, Zoboki J. 2001. Analysis of drought severityusing PDSI and SPI indices. Idojaras 195: 93–107.

Domonkos P, Kysely J, Piotrowicz K, Petrovic P, Likso T. 2003.Variability of extreme temperature events in South-Central Europeduring the 20th century and its relationship with large-scalecirculation. International Journal of Climatology 23: 987–1010,DOI: 10.1002/joc.929.

Drogue G, Mestre O, Hoffmann L, Iffly JF, Pfister L. 2005. Recentwarming in a small region with semi-oceanic climate, 1949–1998:what is the ground truth? Theoretical and Applied Climatology 81:1–10, DOI: 10.1007/s00704-004-0088-x.

Easterling DR, Horton B, Jones PD, Peterson TC, Karl TR, Parker DE,Salinger MJ, Razuvaev V, Plummer N, Jamason P, Folland CK.1997. Maximum and minimum temperature trends for the globe.Science 277: 364–367, DOI: 10.1126/science.277.5324.364.

Falarz M. 2002. Long-term variability in reconstructed and observedsnow cover over the last 100 winter seasons in Cracow andZakopane (southern Poland). Climate Research 19: 247–256, DOI:10.3354/cr019247.

Fischer EM, Seneviratne SI, Luthi D, Schar C. 2007a. Contribu-tion of land-atmosphere coupling to recent European summerheat waves. Geophysical Research Letters 34: L06707, DOI:10.1029/2006GL029068.

Fischer EM, Seneviratne SI, Vidale PL, Luthi D, Schar C. 2007b.Soil moisture–atmosphere interactions during the 2003 Europeansummer heat wave. Journal of Climate 20: 5081–5099, DOI:10.1175/JCLI4288.1.

Franke J, Goldberg V, Eichelmann U, Freydank E, Bernhofer C. 2004.Statistical analysis of regional climate trends in Saxony, Germany.Climate Research 27: 145–150, DOI: 10.3354/cr027145.

Gorczynski W. 1920. Sur le calcul du degre de continentalisme et sonapplication dans la climatologie. Geografiska Annaler 2: 324–331.

Heino R, Brazdil R, Førland E, Tuomenvirta H, Alexandersson H,Beniston M, Pfister C, Rebetez M, Rosenhagen G, Rosner S,Wibig J. 1999. Progress in the study of climatic extremes in Northernand Central Europe. Climatic Change 42: 151–181, DOI: 10.1023/A:1005420400462.

Hirschi JJM, Sinha B, Josey SA. 2007. Global warming and changesof continentality since 1948. Weather 62: 215–221, DOI:10.1002/wea.88.

Houghton JT, Ding Y, Griggs DJ, Noguer M, van der Linden PJ,Dai X, Maskell K, Johnson CA (eds). 2001. Climate Change 2001:The Scientific Basis. Cambridge University Press: Cambridge.

Hundecha Y, Bardossy A. 2005. Trends in daily precipitation andtemperature extremes across Western Germany in the second halfof the 20th century. International Journal of Climatology 25:1189–1202, DOI: 10.1002/joc.1182.

Hurrell JW, Kushnir Y, Ottersen G, Visbeck M (eds). 2003. The NorthAtlantic Oscillation: Climate Significance and Environmental Impact,Geophysical Monograph Series 134 . American Geophysical Union:Washington, DC.

Huth R, Pokorna L. 2005. Simultaneous analysis of climatic trendsin multiple variables: an example of application of multivariatestatistical methods. International Journal of Climatology 25:469–484, DOI: 10.1002/joc.1146.

Jacobeit J, Jonsson P, Barring L, Beck C, Ekstrom M. 2001. Zonalindices for Europe 1780–1995 and running correlations withtemperature. Climatic Change 48: 219–241, DOI: 10.1023/A:1005619023045.

Jones PD, Jonsson T, Wheeler D. 1997. Extension to the NorthAtlantic Oscillation using early instrumental pressure observa-tions from Gibraltar and South-West Iceland. International Jour-nal of Climatology 17: 1433–1450, DOI: 10.1002/(SICI)1097-0088(19971115)17 : 13<1433::AID-JOC203>3.0.CO;2-P.

Jones PD, Osborn TJ, Briffa KR. 2003. Pressure-based measures of theNorth Atlantic Oscillation (NAO): a comparison and an assessmentof changes in the strength of the NAO and its influence on surfaceclimate parameters. In The North Atlantic Oscillation: ClimateSignificance and Environmental Impacts, Geophysical MonographSeries 134 , Hurrell JW, Kushnir Y, Ottersen G, Visbeck M (eds).American Geophysical Union: Washington, DC; 51–62, DOI:10.1029/134GM03.

Jones PD, Moberg A, Osborn TJ, Briffa KR. 2004. Surface climateresponses to explosive volcanic eruptions seen in long Europeantemperature records in mid-to-high latitude tree-ring density aroundthe Northern Hemisphere. In Volcanism and the Earth’s Atmosphere,Geophysical Monograph Series 139 , Robock A, Oppenheimer C(eds). American Geophysical Union: Washington, DC; 239–254,DOI: 10.1029/139GM15.

Karl TR, Kukla G, Razuvayev V, Changery M, Quayle R, Heim R,Easterling D, Fu CB. 1991. Global warming: evidence forasymmetric diurnal temperature change. Geophysical ResearchLetters 18: 2253–2256.

Karl TR, Jones PD, Knight RW, Kukla G, Plummer N, Razuvaev V,Gallo KP, Lindseay J, Charlson RJ, Peterson TC. 1993. A newperspective on recent global warming: asymmetric trends of dailymaximum and minimum temperature. Bulletin of the AmericanMeteorological Society 74: 1007–1023, DOI: 10.1175/1520-0477(1993)074<1007:ANPORG>2.0.CO;2.

Klein Tank AMG, Konnen GP. 2003. Trends in indices of dailytemperature and precipitation extremes in Europe, 1946–99. Journalof Climate 16: 3665–3680, DOI: 10.1175/1520-0442(2003)016<3665:TIIODT>2.0.CO;2.

Klein Tank AMG, Konnen GP, Selten FM. 2005. Signals ofanthropogenic influence on European warming as seen in the trendpatterns of daily temperature variance. International Journal ofClimatology 25: 1–16, DOI: 10.1002/joc.1087.

Kundzewicz ZW, Jozefczyk D, Osterle H. 2007. Warmest 12 consec-utive months on record at the Potsdam meteorological station, Ger-many. Weather 62: 284–286, DOI: 10.1002/wea.133.

Kysely J. 2002. Temporal fluctuations in heat waves at Prague-Klementinum, the Czech Republic, from 1901–97, and theirrelationships to atmospheric circulation. International Journal ofClimatology 22: 33–50, DOI: 10.1002/joc.720.

Kysely J, Huth R. 2006. Changes in atmospheric circulation overEurope detected by objective and subjective methods. Theoretical



and Applied Climatology 85: 19–36, DOI: 10.1007/s00704-005-0164-x.

Kysely J, Kalvova J, Kveton V. 2000. Heat waves in the SouthMoravian region during the period 1961–1995. Studia Geophysicaet Geodaetica 44: 57–72, DOI: 10.1023/A:1022009924435.

Lapin M. 2004. Detection of changes in the regime of selectedclimatological elements at Hurbanovo. Contributions to Geophysicsand Geodesy 34: 169–193.

Laternser M, Schneebeli M. 2003. Long-term snow climate trends ofthe Swiss Alps (1931–99). International Journal of Climatology 23:733–750, DOI: 10.1002/joc.912.

Lloyd-Hughes B, Saunders MA. 2002. A drought climatology forEurope. International Journal of Climatology 22: 1571–1592, DOI:10.1002/joc.846.

Luterbacher J, Dietrich D, Xoplaki E, Grosjean M, Wanner H. 2004.European seasonal and annual temperature variability, trendsand extremes since 1500. Science 303: 1499–1503, DOI:10.1126/science.1093877.

Luterbacher J, Liniger MA, Menzel A, Estrella N, Della-Marta PM,Pfister C, Rutishauer T, Xoplaki E. 2007. Exceptional Europeanwarmth of autumn 2006 and winter 2007: historical context, theunderlaying dynamics, and its phenological impacts. GeophysicalResearch Letters 34: L12704, DOI: 10.1029/2007GL029951.

Maier U, Drohm C, Muller-Westermeier G. 2006. KlimatologischeAuswertung von Zeitreihen der Monatsmittel von Temperaturminimaund Temperaturmaxima im 20. Jahrhundert, Berichte des DeutschenWetterdienstes 229 . Deutscher Wetterdienst: Offenbach am Main.

Mann ME, Bradley RS, Hughes MK. 1999. Northern Hemispheretemperatures during the past millennium: inferences, uncertainties,and limitations. Geophysical Research Letters 26: 759–762, DOI:10.1029/1999GL900070.

Markham CG. 1970. Seasonality of precipitation in the United States.Annals of the Association of American Geographers 60: 593–597.

Matulla C, Penlap EK, Haas P, Formayer H. 2003. Comparativeanalysis of spatial and seasonal variability: Austrian precipitationduring the 20th century. International Journal of Climatology 23:1577–1588, DOI: 10.1002/joc.960.

Matuszko D. 2003. Cloudiness changes in Cracow in the 20thcentury. International Journal of Climatology 23: 975–984, DOI:10.1002/joc.887.

Mietus M, Filipiak J. 2004. The temporal and spatial patterns ofthermal conditions in the area of the southwestern coast of the Gulfof Gdansk (Poland) from 1951 to 1998. International Journal ofClimatology 24: 499–509, DOI: 10.1002/joc.1007.

Moberg A, Jones PD. 2005. Trends in indices for extremes in dailytemperature and precipitation in central and western Europe,1901–99. International Journal of Climatology 25: 1149–1171,DOI: 10.1002/joc.1163.

Moberg A, Jones PD, Lister D, Walther A, Brunet M, Jacobeit J,Alexander LV, Della-Marta PM, Luterbacher J, Yiou P, Chen D,Klein Tank AMG, Saladie O, Sigro J, Aguilar E, Alexanders-son H, Almarza C, Auer I, Barriendos M, Begert M, Bergstrom H,Bohm R, Butler CJ, Caesar J, Drebs A, Founda D, Gersten-garbe FW, Micela G, Maugeri M, Osterle H, Pandzic K, Petrakis M,Srnec L, Tolasz R, Tuomenvirta H, Werner PC, Linderholm H,Philipp A, Wanner H, Xoplaki E. 2006. Indices for daily temper-ature and precipitation extremes in Europe analyzed for the period1901–2000. Journal of Geophysical Research 111: D22106, DOI:10.1029/2006JD007103.

Palmer WC. 1965. Meteorological Drought, Office of ClimatologyResearch Paper 45 . U.S. Weather Bureau: Washington, DC.

Pavlık J, Nemec L, Tolasz R, Valter J. 2003. Mimoradne leto roku2003 v Ceske republice (Extraordinary summer 2003 in the CzechRepublic). Meteorologicke Zpravy 56: 161–165 and I–VIII.

Pinto JG, Brucher T, Fink AH, Kruger A. 2007. Extraordinary snowaccumulations over parts of central Europe during the winter of2005/06 and weather-related hazards. Weather 62: 16–21, DOI:10.1002/wea.19.

Pısek J, Brazdil R. 2006. Responses of large volcanic eruptionsin the instrumental and documentary climatic data over CentralEurope. International Journal of Climatology 26: 439–459, DOI:10.1002/joc.1249.

Pisoft P, Kalvova J, Brazdil R. 2004. Cycles and trends in the Czechtemperature series using wavelet transforms. International Journalof Climatology 24: 1661–1670, DOI: 10.1002/joc.1095.

Pongracz R, Bogardi I, Duckstein L. 2003. Climatic forcing ofdroughts: a Central European example. Hydrological SciencesJournal 48: 39–50, DOI: 10.1623/hysj.48.1.39.43480.

Rapp J. 2000. Konzeption, Problematik und Ergebnisse klimatolo-gischer Trendanalysen fur Europa und Deutschland, Berichte desDeutschen Wetterdienstes 212 . Deutscher Wetterdienst: Offenbacham Main.

Rebetez M. 1999. Twentieth century trends in droughts in southernSwitzerland. Geophysical Research Letters 26: 755–758, DOI:10.1029/1999GL900075.

Rebetez M, Beniston M. 1998. Changes in temperature variability inrelation to shifts in mean temperatures in the Swiss Alpine regionthis century. In The Impacts of Climate Variability on Forests,Beniston M, Innes JL (eds). Springer: Berlin; 49–60.

Schar C, Jendritzky G. 2004. Hot news from summer 2003. Nature432: 559–560, DOI: 10.1038/432559a.

Schar C, Vidale PL, Luthi D, Frei C, Haberli C, Liniger MA,Appenzeller C. 2004. The role of increasing temperature variabilityin European summer heatwaves. Nature 427: 332–336, DOI:10.1038/nature06012.

Scherrer SC, Appenzeller C. 2006. Swiss Alpine snow pack variability:major patterns and links to local climate and large-scale flow.Climate Research 32: 187–199, DOI: 10.3354/cr032187.

Scherrer SC, Appenzeller C, Laternser M. 2004. Trends in SwissAlpine snow days: the role of local- and large-scale climatevariability. Geophysical Research Letters 31: L13215, DOI:10.1029/2004GL020255.

Scherrer SC, Appenzeller C, Liniger MA. 2006. Temperature trends inSwitzerland and Europe: implications for climate normals. Interna-tional Journal of Climatology 26: 565–580, DOI: 10.1002/joc.1270.

Schonwiese CD, Staeger T, Tromel S. 2004. The hot summer 2003in Germany. Some preliminary results of a statistical timeseries analysis. Meteorologische Zeitschrift 13: 323–327, DOI:10.1127/0941-2948/2004/0013-0323.

Seneviratne SI, Luthi D, Litschi M, Schar C. 2006. Land-atmospherecoupling and climate change in Europe. Nature 443: 205–209, DOI:10.1038/nature05095.

Shver CA. 1975. Stepen sezonnosti osadkov (Index of precipitationseasonality). Trudy GGO 303: 93–103.

Slonosky VC, Yiou P. 2002. Does the NAO index represent zonalflow? The influence of the NAO on North Atlantic surfacetemperature. Climate Dynamics 19: 17–30, DOI: 10.1007/s00382-001-0211-y.

Solomon S, Qin D, Manning M, Marquis M, Averyt K, Tignor MMB,LeRoy Miller H, Chen Z. 2007. Climate Change 2007: The PhysicalScience Basis. Cambridge University Press: Cambridge, New York,Melbourne, Madrid, Cape Town, Singapore, Sao Paulo, Delhi.

Stone DA, Weaver AJ. 2002. Daily maximum and minimumtemperature trends in a climate model. Geophysical Research Letters29: 1356, DOI: 10.1029/2001GL014556.

Stott PA, Stone DA, Allen MR. 2004. Human contribution tothe European heatwave of 2003. Nature 432: 610–614, DOI:10.1038/nature03089.

Szinell CS, Bussay A, Szentimrey T. 1998. Drought tendencies inHungary. International Journal of Climatology 18: 1479–1491, DOI:10.1002/(SICI)1097-0088(19981115)18 : 13<1479::AID-JOC325>3.0.CO;2-P.

Tolasz R, Mıkova T, Valerianova A, Vozenılek V (eds). 2007. ClimateAtlas of Czechia. Cesky hydrometeorologicky ustav, UniverzitaPalackeho: Praha.

Trigo RM, Osborn TJ, Corte-Real JM. 2002. The North Atlantic Oscil-lation influence on Europe: climate impacts and associated physicalmechanisms. Climate Research 20: 9–17, DOI: 10.3354/cr020009.

Trigo RM, Garcıa-Herrera R, Dıaz J, Trigo IF, Valente MA. 2005.How exceptional was the early August 2003 heatwave inFrance? Geophysical Research Letters 32: L10701, DOI: 10.1029/2005GL022410.

Trnka M, Hlavinka P, Semeradova D, Dubrovsky M, Zalud Z,Mozny M. 2007. Agricultural drought and spring barley yields inthe Czech Republic. Plant Soil and Environment 53: 306–316.

Ulbrich U, Brucher T, Fink AH, Leckebusch GC, Kruger A, Pinto JG.2003a. The central European floods of August 2002: Part1 – Rainfall periods and flood development. Weather 58: 371–377,DOI: 10.1256/wea.61.03A.

Ulbrich U, Brucher T, Fink AH, Leckebusch GC, Kruger A, Pinto JG.2003b. The central European floods of August 2002: Part2 – Synoptic causes and considerations with respect to climaticchange. Weather 58: 434–441, DOI: 10.1256/wea.61.03B.

Vinther BM, Andersen KK, Hansen AW, Schmith T, Jones PD. 2003.Improving the Gibraltar/Reykjavik NAO Index. GeophysicalResearch Letters 30: 2222, DOI: 10.1029/2003GL018220.



Vose RS, Easterling DR, Gleason B. 2005. Maximum and minimumtemperature trends for the globe: an update through 2004. Geophys-ical Research Letters 32: L23822, DOI: 10.1029/2005GL024379.

Wanner H, Bronnimann S, Casty C, Gyalistras D, Luterbacher J,Schmutz C, Stephenson DB, Xoplaki E. 2001. North AtlanticOscillation – concepts and studies. Surveys in Geophysics 22:321–382, DOI: 10.1023/A:1014217317898.

Weber RO, Talkner P, Auer I, Bohm R, Gajic-Capka M, Zaninovic K,Brazdil R, Fasko P. 1997. 20th-century changes of temperature in themountain regions of central Europe. Climatic Change 36: 327–344,DOI: 10.1023/A:1005378702066.

Werner A, Schonwiese CD. 2002. A statistical analysis of the NorthAtlantic Oscillation and its impact on European temperature. GlobalAtmosphere and Ocean System 8: 293–306.

Wibig J, Głowicki B. 2002. Trends of minimum and maximumtemperature in Poland. Climate Research 20: 123–133, DOI:10.3354/cr020123.

Wijngaard JB, Klein Tank AMG, Konnen GP. 2003. Homogeneityof 20th century European daily temperature and precipitationseries. International Journal of Climatology 23: 679–692, DOI:10.1002/joc.906.

Wulfmeyer V, Henning-Muller I. 2006. The climate station ofthe University of Hohenheim: analyses of air temperature andprecipitation time series since 1878. International Journal ofClimatology 26: 113–138, DOI: 10.1002/joc.1240.

Xoplaki E, Luterbacher J, Paeth H, Dietrich D, Steiner N, Grosjean M,Wanner H. 2005. European spring and autumn temperature variabil-ity and change of extremes over the last half millennium. Geophys-ical Research Letters 32: L15713, DOI: 10.1029/2005GL023424.

Yiou P, Vautard R, Naveau P, Cassou C. 2007. Inconsistency betweenatmospheric dynamics and temperatures during the exceptional2006/2007 fall/winter and recent warming in Europe. GeophysicalResearch Letters 34: L21808, DOI:10.1029/2007GL031981.


Climate fluctuations in the Czech Republic during the period 19612005

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