# Circulation and Climate Variability in the Czech Republic between 1961 and 2020: A Comparison of Changes for Two “Normal” Periods

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## Abstract

**:**

## 1. Introduction

## 2. Materials and Methods

#### 2.1. Study Area

^{2}, is located in central Europe (Figure 1). This position is influenced by the effects of the Atlantic Ocean, the Mediterranean Sea, and the Eurasian continent, which determines the temperature and humidity of air masses moving into central Europe. These airflow effects are modified at regional/local scales by orographic patterns (altitude, leeward, and windward effects) because altitudes over the CR territory range from 115 to 1603 m (mean altitude 390 m a.s.l.). According to the Köppen classification, the major part of the CR territory corresponds to the climate category of temperate broadleaf deciduous forest (Cfb), while the remaining areas are attributed to a boreal climate (particularly Dfb—boreal climate with warm summer, and, to a lesser extent, Dfc—boreal climate with cold summer; for more detail see [13]).

#### 2.2. Meteorological Data

- (i)
- Sunshine duration—79 stations;
- (ii)
- Mean, maximum, and minimum temperatures—133 stations;
- (iii)
- Relative humidity—133 stations;
- (iv)
- Precipitation total—531 stations;
- (v)
- Wind speed—119 stations.

#### 2.3. Circulation Types

- (i)
- Nine anticyclonic types (A, AN, ANE, AE, ASE, AS, ASW, AW, ANW);
- (ii)
- Nine cyclonic types (C, CN, CNE, CE, CSE, CS, CSW, CW, CNW);
- (iii)
- Eight directional types (N, NE, E, SE, S, SW, W, NW);
- (iv)
- An unclassified type U.

#### 2.4. Methods

#### 2.4.1. Homogenisation

- (i)
- Quality control of daily data (comparison with neighbouring stations);
- (ii)
- (iii)
- Adjustment of the daily data (with respect to existing metadata and the evaluation of the importance of break-points detected, applying our own method of Distribution Adjustment by Percentile, developed from the “variable correction method” by [26]);
- (iv)
- Filling gaps (by interpolation methods from neighbouring stations with respect to differences in their distance and altitude and correlation coefficients) [21].

#### 2.4.2. Statistical Analysis

## 3. Results

#### 3.1. Circulation Patterns

#### 3.2. Sunshine

#### 3.3. Temperature

#### 3.4. Humidity

#### 3.5. Precipitation

#### 3.6. Wind Speed

^{−1}in 1991–2020 compared to the preceding 30 years, and all of these differences were statistically significant (Table 8). While in 1961–1990, none of the calculated annual and seasonal linear trends were statistically significant at the 0.05 significance level, in the second 30-year period, all except DJF were decreasing and statistically significant (c. 0.1 m s

^{−1}/10 years). Similarly, differences in trend slopes were significant for all series with the exception of DJF. Variability characterised by the coefficient of variation (Table 8) significantly increased for the annual and MAM series in the second period and the same two series indicated a significant change in asymmetry as the skewness increased from negative values to positive ones. This means a tendency toward a longer and fatter tail on the right side of the distribution where the extremely large values of mean wind speed may occur. Differences in the distribution of mean wind speeds are quite substantial. Except for DJF, the annual and remaining seasonal series show important declines in percentile values (Figure 11b). For example, the values of the upper quartile during 1991–2020 are close to or deeply below the values of lower quartiles over the preceding 30 years. It is a clear indication of important changes in the character of the distribution of annual and seasonal mean wind speeds that a shift is shown to lower values in density functions. This is remarkable, particularly for the annual and MAM series (Figure 11c). Differences in density functions were significant for all series.

#### 3.7. Spatial Patterns

## 4. Discussion

## 5. Conclusions

- (i)
- Mean frequencies of anticyclonic and cyclonic circulation types according to the objective classification express generally significant changes between both 30-year normal sub-periods. Significant increases in their 30-year means appear for frequencies of days with the occurrence of anticyclonic types and decreases for cyclonic types in the 1991–2020 period compared to 1961–1990. Directional circulation types exhibit relatively stable patterns in both periods analysed;
- (ii)
- Annual and seasonal sunshine duration series do not express significant changes between two 30-year normal periods in terms of their variability, characteristics of distribution, density functions, or linear trends. Only an increase in annual, MAM, and JJA means in 1991–2020 compared to the preceding period was statistically significant;
- (iii)
- Mean, maximum, and minimum temperatures display different patterns in two 30-year normal periods in accord with recent warming. They are reflected in statistically significant differences in means, characteristics of distribution, density functions, and significant linear trends through 1991–2020 (annual, JJA, SON). This is particularly pronounced for the JJA series;
- (iv)
- Statistically significant decreases in means of relative humidity between two 30-year normal periods (except SON) are reflected in a significant shift of density functions to lower values. However, decreasing linear trends were significant only for MAM. Increasing variability in relative humidity was significant for the annual and MAM series.
- (v)
- Precipitation totals of both 30-year periods are represented well by non-significant linear trends. There are no substantial changes in mean and variability nor in the character of their distributions represented by the density functions;
- (vi)
- Wind speed in two 30-year normal periods represents quite different patterns expressed by statistically significant decreasing linear trends over 1991–2020, significant differences in means (partly in variability and skewness, both annual and MAM), and in density functions;
- (vii)
- The recent 30-year normal 1991–2020 period is strongly influenced by recent climate change. This is reflected in statistically significant changes in means, variability, characteristics of distribution, density functions, and linear trends compared to the preceding 30-year normal of 1961–1990. These features have already become typical for many climatic variables;
- (viii)
- Spatial patterns of differences between two 30-year periods for annual series of climate variables generally confirm knowledge obtained from the mean series for the whole CR. Spatial differences for temperature characteristics are territorially the most consistent, while for other climate variables, spatial patterns are slightly complicated;
- (ix)
- All the above knowledge has to be considered when selecting a proper “baseline” or reference period for climate change impact and adaptation studies.

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Acknowledgments

## Conflicts of Interest

## Appendix A

- (i)
- Anticyclonic circulation types

- (ii)
- Cyclonic circulation types

- (iii)
- Directional circulation types

## Appendix B

## References

- Trewin, B.C. The Role of Climatological Normals in a Changing Climate; WCDMP-No. 61. WMO-TD No. 1377; World Meteorological Organization: Geneva, Switzerland, 2007. [Google Scholar]
- WMO. WMO Guidelines on the Calculation of Climate Normals; WMO-No. 1203; World Meteorological Organization: Geneva, Switzerland, 2017. [Google Scholar]
- WMO. Climatological Normals (CLINO) for Climat and Climat Ship Stations for the Period 1931–1960; WMO-No. 117; World Meteorological Organization: Geneva, Switzerland, 1962. [Google Scholar]
- WMO. 1961–1990 Global Climate Normals (CLINO); WMO-No. 847; World Meteorological Organization: Geneva, Switzerland, 1996. [Google Scholar]
- IPCC. Climate Change 2013: The Physical Science Basis; Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change; Stocker, T.F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S.K., Boschung, J., Nauels, A., Xia, Y., Bex, V., Midgley, P.M., et al., Eds.; Cambridge University Press: Cambridge, UK; New York, NY, USA, 2013. [Google Scholar]
- IPCC. Global Warming of 1.5 °C. In An IPCC Special Report on the Impacts of Global Warming of 1.5 °C above Pre-Industrial Levels and Related Global Greenhouse Gas Emission Pathways, in the Context of Strengthening the Global Response to the Threat of Climate Change, Sustainable Development, and Efforts to Eradicate Poverty; World Meteorological Organisation: Geneva, Switzerland, 2018. [Google Scholar]
- IPCC. Climate Change 2021: The Physical Science Basis; Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change; Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S.L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M.I., Eds.; Cambridge University Press: Cambridge, UK; New York, NY, USA, 2021; in press. [Google Scholar]
- Twardosz, R.; Walanus, A.; Guzik, I. Warming in Europe: Recent trends in annual and seasonal temperatures. Pure Appl. Geoph.
**2021**, 178, 4021–4032. [Google Scholar] [CrossRef] - Brázdil, R.; Zahradníček, P.; Řezníčková, L.; Tolasz, R.; Štěpánek, P.; Dobrovolný, P. Spatial and temporal variability of mean daily wind speeds in the Czech Republic, 1961–2015. Clim. Res.
**2017**, 72, 197–216. [Google Scholar] [CrossRef] [Green Version] - Brázdil, R.; Zahradníček, P.; Dobrovolný, P.; Štěpánek, P.; Trnka, M. Observed changes in precipitation during recent warming: The Czech Republic, 1961–2019. Int. J. Climatol.
**2021**, 41, 3881–3902. [Google Scholar] [CrossRef] - Zahradníček, P.; Brázdil, R.; Štěpánek, P.; Trnka, M. Reflections of global warming in trends of temperature characteristics in the Czech Republic, 1961–2019. Int. J. Climatol.
**2021**, 41, 1211–1229. [Google Scholar] [CrossRef] - Zahradníček, P.; Brázdil, R.; Řehoř, J.; Lhotka, O.; Dobrovolný, P.; Štěpánek, P.; Trnka, M. Temperature extremes and circulation types in the Czech Republic, 1961–2020. Int. J. Climatol. 2021; accepted. [Google Scholar] [CrossRef]
- Tolasz, R.; Míková, T.; Valeriánová, A.; Voženílek, V. Atlas podnebí Česka (Climate Atlas of Czechia); Český hydrometeorologický ústav, Univerzita Palackého v Olomouci: Praha–Olomouc, Czech Republic, 2007. [Google Scholar]
- Jenkinson, A.F.; Collison, F.P. An Initial Climatology of Gales over the North Sea; Synoptic Climatology Branch Memorandum No. 62; Meteorological Office: Bracknell, UK, 1977. [Google Scholar]
- Plavcová, E.; Kyselý, J. Evaluation of daily temperatures in Central Europe and their links to large-scale circulation in an ensemble of regional climate models. Tellus
**2011**, 63A, 763–781. [Google Scholar] [CrossRef] [Green Version] - Kalnay, E.; Kanamitsu, M.; Kistler, R.; Collins, W.; Deaven, D.; Gandin, L.; Iredell, M.; Saha, S.; White, G.; Woollen, J.; et al. The NCEP/NCAR 40-year reanalysis project. Bull. Am. Meteorol. Soc.
**1996**, 77, 437–471. [Google Scholar] [CrossRef] [Green Version] - Řehoř, J.; Brázdil, R.; Lhotka, O.; Trnka, M.; Balek, J.; Štěpánek, P.; Zahradníček, P. Precipitation in the Czech Republic in light of subjective and objective classifications of circulation types. Atmosphere
**2021**, 12, 1536. [Google Scholar] [CrossRef] - Řehoř, J.; Brázdil, R.; Trnka, M.; Lhotka, O.; Balek, J.; Možný, M.; Štěpánek, P.; Zahradníček, P.; Mikulová, K.; Turňa, M. Soil drought and circulation types in a longitudinal transect over central Europe. Int. J. Climatol.
**2021**, 41 (Suppl. 1), E2834–E2850. [Google Scholar] [CrossRef] - ClimaHom.eu: Tools for Processing and Homogenization of Large Climatological Dataset. Available online: www.climahom.eu (accessed on 18 October 2021).
- Štěpánek, P.; Zahradníček, P.; Brázdil, R.; Tolasz, R. Metodologie kontroly a homogenizace časových řad v klimatologii (Methodology of Data Quality Control and Homogenization of Time Series in Climatology); Český hydrometeorologický ústav: Praha, Czech Republic, 2011. [Google Scholar]
- Štěpánek, P.; Zahradníček, P.; Huth, R. Interpolation techniques used for data quality control and calculation of technical series: An example of Central European daily time series. Időjárás
**2011**, 115, 87–98. [Google Scholar] - Štěpánek, P.; Zahradníček, P.; Farda, A. Experiences with data quality control and homogenization of daily records of various meteorological elements in the Czech Republic in the period 1961–2010. Időjárás
**2013**, 117, 123–141. [Google Scholar] - Zahradníček, P.; Brázdil, R.; Štěpánek, P.; Řezníčková, L. Differences in wind speeds according to measured and homogenised series in the Czech Republic, 1961–2015. Int. J. Climatol.
**2019**, 39, 235–250. [Google Scholar] [CrossRef] [Green Version] - Alexandersson, H. A homogeneity test applied to precipitation data. J. Climatol.
**1986**, 6, 661–675. [Google Scholar] [CrossRef] - Maronna, T.; Yohai, V.J. A bivariate test for the detection of a systematic change in mean. J. Amer. Stat. Assoc.
**1978**, 73, 640–645. [Google Scholar] [CrossRef] - Squintu, A.A.; van der Schrier, G.; Štěpánek, P.; Zahradníček, P.; Klein Tank, A. Comparison of homogenization methods for daily temperature series against an observation-based benchmark dataset. Theor. Appl. Climatol.
**2020**, 140, 285–301. [Google Scholar] [CrossRef] [Green Version] - Theil, H. A Rank-Invariant Method of Linear and Polynomial Regression Analysis. In Henri Theil’s Contributions to Economics and Econometrics; Raj, B., Koerts, J., Eds.; Springer: Dordrecht, The Netherlands, 1992; pp. 345–381. [Google Scholar]
- Sen, P.K. Estimates of the regression coefficient based on Kendall’s tau. J. Amer. Stat. Assoc.
**1968**, 63, 1379–1389. [Google Scholar] [CrossRef] - Mann, H.B. Non-parametric tests against trend. Econometrica
**1945**, 13, 163–171. [Google Scholar] [CrossRef] - Kendall, M.G. Rank Correlation Methods, 4th ed.; Charles Griffin: London, UK, 1975. [Google Scholar]
- Bowman, A.W.; Azzalini, A. Applied Smoothing Techniques for Data Analysis: The Kernel Approach with S-Plus Illustrations; Oxford University Press: Oxford, UK, 1997. [Google Scholar]
- Marwick, B.; Krishnamoorthy, K. cvequality: Tests for the Equality of Coefficients of Variation from Multiple Groups. R Software Package Version 0.1.3. Available online: https://github.com/benmarwick/cvequality (accessed on 7 January 2019).
- Trnka, M.; Kyselý, J.; Možný, M.; Dubrovský, M. Changes in Central-European soil-moisture availability and circulation patterns in 1881–2005. Int. J. Climatol.
**2009**, 29, 655–672. [Google Scholar] [CrossRef] - Cahynová, M.; Huth, R. Changes of atmospheric circulation in central Europe and their influence on climatic trends in the Czech Republic. Theor. Appl. Climatol.
**2009**, 96, 57–68. [Google Scholar] [CrossRef] - Lhotka, O.; Trnka, M.; Kyselý, J.; Markonis, Y.; Balek, J.; Možný, M. Atmospheric circulation as a factor contributing to increasing drought severity in Central Europe. J. Geophys. Res. Atmos.
**2020**, 125, e2019JD032269. [Google Scholar] [CrossRef] - Wild, M. Enlightening global dimming and brightening. Bull. Am. Meteorol. Soc.
**2012**, 93, 27–37. [Google Scholar] [CrossRef] - Sanchez-Lorenzo, A.; Calbó, J.; Martin-Vide, J. Spatial and temporal trends in sunshine duration over Western Europe (1938−2004). J. Clim.
**2008**, 21, 6089–6098. [Google Scholar] [CrossRef] - Sanchez-Lorenzo, A.; Calbó, J.; Brunetti, M.; Deser, C. Dimming/brightening over the Iberian Peninsula: Trends in sunshine duration and cloud cover and their relations with atmospheric circulation. J. Geophys. Res. Atmos.
**2009**, 114, D00D09. [Google Scholar] [CrossRef] [Green Version] - Manara, V.; Beltrano, M.C.; Brunetti, M.; Maugeri, M.; Sanchez-Lorenzo, A.; Simolo, C.; Sorrenti, S. Sunshine duration variability and trends in Italy from homogenized instrumental time series (1936−2013). J. Geophys. Res. Atmos.
**2015**, 120, 3622–3641. [Google Scholar] [CrossRef] - van den Besselaar, E.J.M.; Sanchez-Lorenzo, A.; Wild, M.; Klein Tank, A.M.G.; de Laat, A.T.J. Relationship between sunshine duration and temperature trends across Europe since the second half of the twentieth century. J. Geophys. Res. Atmos.
**2015**, 120, 10823–10836. [Google Scholar] [CrossRef] [Green Version] - Urban, G.; Migala, K.; Pawliczek, P. Sunshine duration and its variability in the main ridge of the Karkonosze Mountains in relation to with atmospheric circulation. Theor. Appl. Climatol.
**2018**, 131, 1173–1189. [Google Scholar] [CrossRef] [Green Version] - Ceppi, P.; Scherrer, S.C.; Fischer, A.M.; Appenzeller, C. Revisiting Swiss temperature trends 1959–2008. Int. J. Climatol.
**2012**, 32, 203–213. [Google Scholar] [CrossRef] [Green Version] - Rottler, E.; Kormann, C.; Francke, T.; Bronstert, A. Elevation-dependent warming in the Swiss Alps 1981–2017: Features, forcings and feedbacks. Int. J. Climatol.
**2019**, 39, 2556–2568. [Google Scholar] [CrossRef] - Scorzini, A.R.; Leopardi, M. Precipitation and temperature trends over Central Italy (Abruzzo region): 1951–2012. Theor. Appl. Climatol.
**2019**, 135, 959–977. [Google Scholar] [CrossRef] - Krauskopf, T.; Huth, R. Temperature trends in Europe: Comparison of different data sources. Theor. Appl. Climatol.
**2020**, 139, 1305–1316. [Google Scholar] [CrossRef] - Cattiaux, J.; Vautard, R.; Cassou, C.; Yiou, P.; Masson-Delmotte, V.; Codron, F. Winter 2010 in Europe: A cold extreme in a warming climate. Geophys. Res. Lett.
**2010**, 37, L20704. [Google Scholar] [CrossRef] [Green Version] - Plavcová, E.; Kyselý, J. Atmospheric circulation in regional climate models over Central Europe: Links to surface air temperature and the influence of driving data. Clim. Dyn.
**2012**, 39, 1681–1695. [Google Scholar] [CrossRef] - Lhotka, O.; Kyselý, J. Circulation-conditioned wintertime temperature bias in EURO-CORDEX Regional Climate Models over Central Europe. J. Geophys. Res. Atmos.
**2018**, 123, 8661–8673. [Google Scholar] [CrossRef] - Brádka, J. Srážky na území ČSSR při jednotlivých typech povětrnostní situace (Precipitation over the territory of the CSSR for individual types of weather situation). Sbor. Prac. Hydrometeorol. Úst.
**1972**, 18, 8–62. [Google Scholar] - Brázdil, R.; Štekl, J. Cirkulační procesy a atmosférické srážky v ČSSR (Circulatory Processes and Atmospheric Precipitation on the Territory of the CSSR); Univerzita J. E. Purkyně: Brno, Czechoslovakia, 1986. [Google Scholar]
- Štekl, J.; Brázdil, R.; Kakos, V.; Jež, J.; Tolasz, R.; Sokol, Z. Extrémní denní srážkové úhrny na území ČR v období 1879–2000 a jejich synoptické příčiny (Extreme Daily Precipitation Totals during 1879–2000 in the Czech Territory and their Synoptic Causes); Národní klimatický Program České Republiky 31: Praha, Czech Republic, 2001. [Google Scholar]
- Wypych, A. Twentieth century variability of surface humidity as the climate change indicator in Kraków (Southern Poland). Theor. Appl. Climatol.
**2010**, 101, 475–482. [Google Scholar] [CrossRef] - Butler, C.J.; García-Suárez, A.M. Relative humidity at Armagh Observatory, 1838–2008. Int. J. Climatol.
**2012**, 32, 657–668. [Google Scholar] [CrossRef] [Green Version] - Vicente-Serrano, S.M.; Azorin-Molina, C.; Sanchez-Lorenzo, A.; Moran-Tejeda, E.; Lorenzo-Lacruz, J.; Revuelto, J.; Lopez-Moreno, J.I.; Espejo, F. Temporal evolution of surface humidity in Spain: Recent trends and possible physical mechanisms. Clim. Dyn.
**2014**, 42, 2655–2674. [Google Scholar] [CrossRef] [Green Version] - Fatichi, S.; Molnar, P.; Mastrotheodoros, T.; Burlando, P. Diurnal and seasonal changes in near-surface humidity in a complex orography. J. Geophys. Res. Atmos.
**2015**, 120, 2358–2374. [Google Scholar] [CrossRef] - Vicente-Serrano, S.M.; Nieto, R.; Gimeno, L. Recent changes of relative humidity: Regional connections with land and ocean processes. Earth Syst. Dyn.
**2018**, 9, 915–937. [Google Scholar] [CrossRef] [Green Version] - Razafimaharo, C.; Krähenmann, S.; Höpp, S.; Rauthe, M.; Deutschländer, M. New high-resolution gridded dataset of daily mean, minimum, and maximum temperature and relative humidity for Central Europe (HYRAS). Theor. Appl. Climatol.
**2020**, 142, 1531–1553. [Google Scholar] [CrossRef] - Ruosteenoja, K.; Räisänen, P. Seasonal changes in solar radiation and relative humidity in Europe in response to global warming. J. Clim.
**2013**, 26, 2467–2481. [Google Scholar] [CrossRef] - Scherrer, S.C.; Begert, M.; Croci-Maspoli, M.; Appenzeller, C. Long series of Swiss seasonal precipitation: Regionalization, trends and influence of large-scale flow. Int. J. Climatol.
**2016**, 36, 3673–3689. [Google Scholar] [CrossRef] [Green Version] - Jaagus, J.; Briede, A.; Rimkus, E.; Sepp, M. Changes in precipitation regime in the Baltic countries in 1966–2015. Theor. Appl. Climatol.
**2018**, 131, 433–443. [Google Scholar] [CrossRef] - Pińskwar, I.; Choryński, A.; Graczyk, D.; Kundzewicz, Z.W. Observed changes in precipitation totals in Poland. Geografie
**2019**, 124, 237–264. [Google Scholar] [CrossRef] - Tomczyk, A.M.; Szyga-Pluta, K. Variability of thermal and precipitation conditions in the growing season in Poland in the years 1966–2015. Theor. Appl. Climatol.
**2019**, 135, 1517–1530. [Google Scholar] [CrossRef] [Green Version] - Roderick, M.L.; Rotstayn, L.D.; Farquhar, G.D.; Hobbins, M.T. On the attribution of changing pan evaporation. Geophys. Res. Lett.
**2007**, 34, L17403. [Google Scholar] [CrossRef] [Green Version] - McVicar, T.R.; Roderick, M.L.; Donohue, R.J.; Li, L.T.; van Niel, T.G.; Thomas, A.; Grieser, J.; Jhajharia, D.; Himri, Y.; Mahowald, N.M.; et al. Global review and synthesis of trends in observed terrestrial near-surface wind speeds: Implications for evaporation. J. Hydrol.
**2012**, 416–417, 182–205. [Google Scholar] [CrossRef] - Azorin-Molina, C.; Guijarro, J.A.; McVicar, T.R.; Vicente-Serrano, S.M.; Chen, D.; Jerez, S.; Espírito-Santo, F. Trends of daily peak wind gusts in Spain and Portugal, 1961–2014. J. Geophys. Res. Atmos.
**2016**, 121, 1059–1078. [Google Scholar] [CrossRef] [Green Version] - Minola, L.; Azorin-Molina, C.; Chen, D.L. Homogenization and assessment of observed near-surface wind speed trends across Sweden, 1956–2013. J. Clim.
**2016**, 29, 7397–7415. [Google Scholar] [CrossRef] - Azorin-Molina, C.; Vicente-Serrano, S.M.; McVicar, T.R.; Revuelto, J.; Jerez, S.; López-Moreno, J.-I. Assessing the impact of measurement time interval when calculating wind speed means and trends under the stilling phenomenon. Int. J. Climatol.
**2017**, 37, 480–492. [Google Scholar] [CrossRef] - Brázdil, R.; Valík, A.; Zahradníček, P.; Řezníčková, L.; Tolasz, R.; Možný, M. Wind-stilling in the light of wind speed measurements: The Czech experience. Clim. Res.
**2017**, 74, 131–143. [Google Scholar] [CrossRef] - Valík, A.; Brázdil, R.; Zahradníček, P.; Tolasz, R.; Možný, M.; Řezníčková, L. Measurements of sunshine duration by automatic sensors and their effects on the homogeneity of long-term series in the Czech Republic. Clim. Res.
**2019**, 78, 83–101. [Google Scholar] [CrossRef] - Mozny, M.; Trnka, M.; Stepanek, P.; Zalud, Z.; Koznarova, V.; Hajkova, L.; Bares, D.; Semeradova, D. Long-term comparison of temperature measurements by the multi-plate shield and Czech-Slovak thermometer screen. Meteorol. Z.
**2012**, 21, 125–133. [Google Scholar] [CrossRef] - Valík, A.; Brázdil, R.; Zahradníček, P.; Tolasz, R.; Fiala, R. Precipitation measurements by manual and automatic rain gauges and their influence on homogeneity of long-term precipitation series. Int. J. Climatol.
**2021**, 41 (Suppl. 1), E2537–E2552. [Google Scholar] [CrossRef] - Trnka, M.; Balek, J.; Štěpánek, P.; Zahradníček, P.; Možný, M.; Eitzinger, J.; Žalud, Z.; Formayer, H.; Turňa, M.; Nejedlík, P.; et al. Drought trends over part of Central Europe between 1961 and 2014. Clim. Res.
**2016**, 70, 143–160. [Google Scholar] [CrossRef] [Green Version] - Moravec, V.; Markonis, Y.; Rakovec, O.; Svoboda, M.; Trnka, M.; Kumar, R.; Hanel, M. Europe under multi-year droughts: How severe was the 2014–2018 drought period? Environ. Res. Lett.
**2021**, 16, 034062. [Google Scholar] [CrossRef] - Trnka, M.; Brázdil, R.; Balek, J.; Semerádová, D.; Hlavinka, P.; Možný, M.; Štěpánek, P.; Dobrovolný, P.; Zahradníček, P.; Dubrovský, M.; et al. Drivers of soil drying in the Czech Republic between 1961 and 2012. Int. J. Climatol.
**2015**, 35, 2664–2675. [Google Scholar] [CrossRef] - Zahradníček, P.; Trnka, M.; Brázdil, R.; Možný, M.; Štěpánek, P.; Hlavinka, P.; Žalud, Z.; Malý, A.; Semerádová, D.; Dobrovolný, P.; et al. The extreme drought episode of August 2011–May 2012 in the Czech Republic. Int. J. Climatol.
**2015**, 35, 3335–3352. [Google Scholar] [CrossRef] - Řehoř, J.; Brázdil, R.; Trnka, M.; Řezníčková, L.; Balek, J.; Možný, M. Regional effects of synoptic situations on soil drought in the Czech Republic. Theor. Appl. Climatol.
**2020**, 141, 1383–1400. [Google Scholar] [CrossRef] - Urban, A.; Hanzlíková, H.; Kyselý, J.; Plavcová, E. Impacts of the 2015 heat waves on mortality in the Czech Republic–a comparison with previous heat waves. Int. J. Environ. Res. Publ. Health
**2017**, 14, 1562. [Google Scholar] [CrossRef] [Green Version] - Arsenović, D.; Lehnert, M.; Fiedor, D.; Šimáček, P.; Středová, H.; Středa, T.; Savić, S. Heat-waves and mortality in Czech cities: A case study for the summers of 2015 and 2016. Geogr. Pannonica
**2019**, 23, 162–172. [Google Scholar] [CrossRef] [Green Version] - Trnka, M.; Brázdil, R.; Možný, M.; Štěpánek, P.; Dobrovolný, P.; Zahradníček, P.; Balek, J.; Semerádová, D.; Dubrovský, M.; Hlavinka, P.; et al. Soil moisture trends in the Czech Republic between 1961 and 2012. Int. J. Climatol.
**2015**, 35, 3733–3747. [Google Scholar] [CrossRef] - Mozny, M.; Trnka, M.; Brázdil, R. Climate change driven changes of vegetation fires in the Czech Republic. Theor. Appl. Climatol.
**2021**, 143, 691–699. [Google Scholar] [CrossRef] - Hlásny, T.; Zimová, S.; Merganičová, K.; Štěpánek, P.; Modlinger, R.; Turčáni, M. Devastating outbreak of bark beetles in the Czech Republic: Drivers, impacts, and management implications. For. Ecol. Manag.
**2021**, 490, 119075. [Google Scholar] [CrossRef] - Brázdil, R.; Trnka, M.; Dobrovolný, P.; Chromá, K.; Hlavinka, P.; Žalud, Z. Variability of droughts in the Czech Republic, 1881–2006. Theor. Appl. Climatol.
**2009**, 97, 297–315. [Google Scholar] [CrossRef] - Brázdil, R.; Trnka, M.; Mikšovský, J.; Řezníčková, L.; Dobrovolný, P. Spring–summer droughts in the Czech Land in 1805–2012 and their forcings. Int. J. Climatol.
**2015**, 35, 1405–1421. [Google Scholar] [CrossRef] - Brázdil, R.; Dobrovolný, P.; Trnka, M.; Büntgen, U.; Řezníčková, L.; Kotyza, O.; Valášek, H.; Štěpánek, P. Documentary and instrumental-based drought indices for the Czech Lands back to AD 1501. Clim. Res.
**2016**, 70, 103–117. [Google Scholar] [CrossRef] [Green Version] - Brázdil, R.; Dobrovolný, P.; Mikšovský, J.; Pišoft, P.; Trnka, M.; Možný, M.; Balek, J. Documentary-based climate reconstructions in the Czech Lands 1501–2020 CE and their European context. Clim. Past, 2021; in review. [Google Scholar] [CrossRef]
- Büntgen, U.; Urban, O.; Krusic, P.J.; Rybníček, M.; Kolář, T.; Kyncl, T.; Ač, A.; Koňasová, E.; Čáslavský, J.; Esper, J.; et al. Recent European drought extremes beyond Common Era background variability. Nat. Geosci.
**2021**, 14, 190–196. [Google Scholar] [CrossRef] - Mazzarella, A.; Scafetta, N. Evidences for a quasi 60-year North Atlantic Oscillation since 1700 and its meaning for global climate change. Theor. Appl. Climatol.
**2012**, 107, 599–609. [Google Scholar] [CrossRef] [Green Version] - Scafetta, N. Discussion on climate oscillations: CMIP5 general circulation models versus a semi-empirical harmonic model based on astronomical cycles. Earth Sci. Rev.
**2013**, 126, 321–357. [Google Scholar] [CrossRef] [Green Version] - Le Mouël, J.L.; Lopes, F.; Courtillot, V. A solar signature in many climate indices. J. Geophys. Res. Atmos.
**2019**, 124, 2600–2619. [Google Scholar] [CrossRef] - Courtillot, V.; Le Mouël, J.L.; Kossobokov, V.; Gibert, D.; Lopes, F. Multi-decadal trends of global surface temperature: A broken line with alternating ~30 yr linear segments? Atmos. Clim. Sci.
**2013**, 3, 364–371. [Google Scholar] [CrossRef] [Green Version]

**Figure 1.**(

**a**) The location of the Czech Republic in Europe, (

**b**) the physical geographical map of the Czech Republic, and the network of meteorological stations of the Czech Hydrometeorological Institute used for the calculation of (

**c**) sunshine duration, (

**d**) temperatures and relative humidity, (

**e**) precipitation totals, and (

**f**) wind speed.

**Figure 2.**Annual and seasonal frequencies of days with anticyclonic circulation types according to the objective classification for the territory of the Czech Republic in the 1961–2020 period: (

**a**) fluctuations with linear trends in the entire period, 1961–1990 and 1991–2020; (

**b**) box plots (median, lower and upper quartile, minimum, and maximum) for 1961–2020 (1), 1961–1990 (2), and 1991–2020 (3); (

**c**) the density distribution of the series in 1961–1990 and 1991–2020. The density curves outside the reference band (green–blue) indicate a significant difference in the two distributions (and vice versa).

**Figure 3.**Annual and seasonal frequencies of days with cyclonic circulation types according to the objective classification for the territory of the Czech Republic in the 1961–2020 period: (

**a**) fluctuations with linear trends in the entire period, 1961–1990 and 1991–2020; (

**b**) box plots (median, lower and upper quartile, minimum, and maximum) for 1961–2020 (1), 1961–1990 (2), and 1991–2020 (3); (

**c**) the density distribution of the series in 1961–1990 and 1991–2020. The density curves outside the reference band (green–blue) indicate a significant difference in the two distributions (and vice versa).

**Figure 4.**Annual and seasonal frequencies of days with directional circulation types according to the objective classification for the territory of the Czech Republic in the 1961–2020 period: (

**a**) fluctuations with linear trends in the entire period, 1961–1990 and 1991–2020; (

**b**) box plots (median, lower and upper quartile, minimum, and maximum) for 1961–2020 (1), 1961–1990 (2), and 1991–2020 (3); (

**c**) the density distribution of the series in 1961–1990 and 1991–2020. The density curves outside the reference band (green–blue) indicate a significant difference in the two distributions (and vice versa).

**Figure 5.**Mean annual and seasonal series of sunshine duration for the territory of the Czech Republic in the 1961–2020 period: (

**a**) fluctuations with linear trends in the entire period, 1961–1990 and 1991–2020; (

**b**) box plots (median, lower and upper quartile, minimum, and maximum) for 1961–2020 (1), 1961–1990 (2), and 1991–2020 (3); (

**c**) the density distribution of the series in 1961–1990 and 1991–2020. The density curves outside the reference band (green–blue) indicate a significant difference in the two distributions (and vice versa).

**Figure 6.**Mean annual and seasonal temperature series for the territory of the Czech Republic in the 1961–2020 period: (

**a**) fluctuations with linear trends in the entire period, 1961–1990 and 1991–2020; (

**b**) box plots (median, lower and upper quartile, minimum, and maximum) for 1961–2020 (1), 1961–1990 (2), and 1991–2020 (3); (

**c**) the density distribution of the series in 1961–1990 and 1991–2020. The density curves outside the reference band (green–blue) indicate a significant difference in the two distributions (and vice versa).

**Figure 7.**Annual and seasonal mean maximum temperature series for the territory of the Czech Republic in the 1961–2020 period: (

**a**) fluctuations with linear trends in the entire period, 1961–1990 and 1991–2020; (

**b**) box plots (median, lower and upper quartile, minimum, and maximum) for 1961–2020 (1), 1961–1990 (2), and 1991–2020 (3); (

**c**) the density distribution of the series in 1961–1990 and 1991–2020. The density curves outside the reference band (green–blue) indicate a significant difference in the two distributions (and vice versa).

**Figure 8.**Annual and seasonal mean minimum temperature series for the territory of the Czech Republic in the 1961–2020 period: (

**a**) fluctuations with linear trends in the entire period, 1961–1990 and 1991–2020; (

**b**) box plots (median, lower and upper quartile, minimum, and maximum) for 1961–2020 (1), 1961–1990 (2), and 1991–2020 (3); (

**c**) the density distribution of the series in 1961–1990 and 1991–2020. The density curves outside the reference band (green–blue) indicate a significant difference in the two distributions (and vice versa).

**Figure 9.**Annual and seasonal mean relative humidity series for the territory of the Czech Republic in the 1961–2020 period: (

**a**) fluctuations with linear trends in the entire period, 1961–1990 and 1991–2020; (

**b**) box plots (median, lower and upper quartile, minimum, and maximum) for 1961–2020 (1), 1961–1990 (2), and 1991–2020 (3); (

**c**) the density distribution of the series in 1961–1990 and 1991–2020. The density curves outside the reference band (green–blue) indicate a significant difference in the two distributions (and vice versa).

**Figure 10.**Annual and seasonal series of mean precipitation totals for the territory of the Czech Republic in the 1961–2020 period: (

**a**) fluctuations with linear trends in the entire period, 1961–1990 and 1991–2020; (

**b**) box plots (median, lower and upper quartile, minimum, and maximum) for 1961–2020 (1), 1961–1990 (2), and 1991–2020 (3); (

**c**) the density distribution of the series in 1961–1990 and 1991–2020. The density curves outside the reference band (green–blue) indicate a significant difference in the two distributions (and vice versa).

**Figure 11.**Annual and seasonal series of mean wind speed for the territory of the Czech Republic in the 1961–2020 period: (

**a**) fluctuations with linear trends in the entire period, 1961–1990 and 1991–2020; (

**b**) box plots (median, lower and upper quartile, minimum, and maximum) for 1961–2020 (1), 1961–1990 (2) and 1991–2020 (3); (

**c**) the density distribution of the series in 1961–1990 and 1991–2020. The density curves outside the reference band (green–blue) indicate a significant difference in the two distributions (and vice versa).

**Figure 12.**Spatial distribution of differences between the 1991–2020 and 1961–1990 periods over the territory of the Czech Republic for the annual series of selected climate variables: (

**a**) sunshine duration, (

**b**) mean temperature, (

**c**) maximum temperature, (

**d**) minimum temperature, (

**e**) relative humidity, (

**f**) precipitation total, and (

**g**) wind speed. The individual maps were created based on the number of stations specified in Section 2.2.

**Table 1.**Selected statistical characteristics of annual (Ann) and seasonal (DJF, MAM, JJA, and SON) frequencies of days with anticyclonic, cyclonic, and directional circulation types according to the objective classification for the territory of the Czech Republic during the 1961–1990 (A) and 1991–2020 (B) periods: means are in days, variation coefficients (CV) in %, and linear trends in days/10 years (in bold statistically significant at the 0.05 significance level). An asterisk * indicates statistically significant differences of a given characteristic between two 30-year periods.

Season | Period | Mean | CV | Skewness | Kurtosis | Slope | |||
---|---|---|---|---|---|---|---|---|---|

Anticyclonic circulation types | |||||||||

Ann | A | 149.4 | * | 15.5 | −0.18 | −0.57 | 14.2 | ||

B | 167.4 | * | 13.5 | −0.09 | −0.40 | 2.5 | |||

DJF | A | 38.2 | * | 28.2 | 0.80 | 0.11 | 1.2 | ||

B | 44.2 | * | 24.1 | −0.11 | −0.17 | −2.1 | |||

MAM | A | 26.9 | * | 28.4 | 0.46 | 0.55 | 0.9 | ||

B | 33.7 | * | 25.6 | 0.76 | 0.02 | 0.9 | |||

JJA | A | 40.6 | * | 22.9 | −0.34 | −0.36 | 6.8 | ||

B | 47.8 | * | 17.0 | −0.10 | −1.12 | 1.2 | |||

SON | A | 43.8 | 27.2 | −0.18 | −0.77 | 5.0 | |||

B | 41.8 | 24.7 | 0.23 | −0.03 | 0.9 | ||||

Cyclonic circulation types | |||||||||

Ann | A | 67.6 | * | 28.1 | 0.66 | 0.42 | −14.4 | ||

B | 55.7 | * | 20.5 | 0.28 | 0.94 | 0.0 | |||

DJF | A | 12.9 | 46.9 | 0.12 | * | −0.54 | * | −1.4 | |

B | 10.5 | 52.2 | 1.92 | * | 6.00 | * | 0.8 | ||

MAM | A | 25.9 | * | 28.4 | 0.32 | 0.02 | −3.3 | ||

B | 19.5 | * | 30.3 | −0.10 | −0.06 | −1.2 | |||

JJA | A | 16.1 | * | 47.7 | 0.51 | −0.15 | −5.4 | ||

B | 12.0 | * | 45.5 | 1.10 | 0.74 | 0.5 | |||

SON | A | 12.6 | 52.4 | 0.46 | −0.59 | −3.8 | |||

B | 13.7 | 43.2 | 0.55 | −0.46 | 0.0 | ||||

Directional circulation types | |||||||||

Ann | A | 142.1 | 7.7 | 0.69 | −0.14 | 0.0 | |||

B | 136.1 | 10.6 | −0.14 | 0.12 | −3.3 | ||||

DJF | A | 38.5 | 18.5 | −0.36 | 0.37 | −0.5 | |||

B | 35.2 | 23.0 | 0.27 | 0.01 | 0.6 | ||||

MAM | A | 37.8 | 14.9 | −0.42 | 0.23 | 2.4 | |||

B | 37.3 | 14.4 | −0.42 | −0.16 | −0.5 | ||||

JJA | A | 32.2 | * | 14.7 | 0.10 | 1.00 | 0.0 | ||

B | 28.8 | * | 19.9 | −0.36 | −0.38 | −1.1 | |||

SON | A | 33.6 | 22.0 | 0.22 | −0.67 | −0.5 | |||

B | 34.8 | 20.0 | −0.27 | 0.46 | −3.2 |

**Table 2.**Selected statistical characteristics of mean annual (Ann) and seasonal (DJF, MAM, JJA, and SON) sunshine duration series in the Czech Republic during the 1961–1990 (A) and 1991–2020 (B) periods: means are in hours, coefficients of variation (CV) in %, linear trends in hours/10 years (none statistically significant at the 0.05 significance level). An asterisk * indicates statistically significant differences of a given characteristic between two 30-year periods.

Season | Period | Mean | CV | Skewness | Kurtosis | Slope | ||
---|---|---|---|---|---|---|---|---|

Ann | A | 1613.9 | * | 7.3 | −0.14 | −1.33 | −15.4 | |

B | 1687.1 | * | 7.6 | 0.50 | 0.22 | 15.3 | ||

DJF | A | 164.4 | 19.2 | 0.47 | * | −0.34 | 1.5 | |

B | 168.7 | 16.4 | −0.84 | * | 0.94 | −8.5 | ||

MAM | A | 482.5 | * | 10.8 | 0.28 | −0.20 | 11.6 | |

B | 524.9 | * | 14.8 | 0.01 | −0.10 | 13.6 | ||

JJA | A | 624.8 | * | 9.3 | −0.04 | −0.81 | −11.9 | |

B | 677.8 | * | 7.8 | 1.18 | 1.40 | –2.2 | ||

SON | A | 335.7 | 13.9 | −0.26 | −0.98 | −15.8 | ||

B | 315.9 | 18.8 | 0.29 | −0.52 | 5.8 |

**Table 3.**Selected statistical characteristics of mean annual (Ann) and seasonal (DJF, MAM, JJA, and SON) temperature series in the Czech Republic in the 1961–1990 (A) and 1991–2020 (B) periods: means and standard deviations (SD) are in °C, linear trends in °C/10 years (in bold statistically significant at the 0.05 significance level). An asterisk * indicates statistically significant differences of a given characteristic between two 30-year periods.

Season | Period | Mean | SD | Skewness | Kurtosis | Slope | |||
---|---|---|---|---|---|---|---|---|---|

Ann | A | 7.4 | * | 0.6 | 0.01 | −1.08 | * | 0.25 | |

B | 8.5 | * | 0.8 | −0.48 | 0.23 | * | 0.56 | ||

DJF | A | −1.7 | * | 2.0 | −0.66 | 0.45 | 0.59 | ||

B | −0.7 | * | 1.7 | 0.05 | −0.67 | 0.53 | |||

MAM | A | 7.3 | * | 1.0 | −0.34 | −0.68 | 0.34 | ||

B | 8.4 | * | 1.0 | −0.18 | −0.71 | 0.44 | |||

JJA | A | 16.2 | * | 0.7 | 0.02 | 0.26 | 0.02 | ||

B | 17.7 | * | 1.0 | 0.41 | −0.66 | 0.53 | |||

SON | A | 7.8 | * | 0.9 | 0.09 | −0.96 | −0.14 | * | |

B | 8.4 | * | 1.0 | 0.18 | −0.30 | 0.62 | * |

**Table 4.**Selected statistical characteristics of annual (Ann) and seasonal (DJF, MAM, JJA, and SON) mean maximum temperature series in the Czech Republic in the 1961–1990 (A) and 1991–2020 (B) periods: means and standard deviations (SD) are in °C, linear trends in °C/10 years (in bold statistically significant at the 0.05 significance level). An asterisk * indicates statistically significant differences of a given characteristic between two 30-year periods.

Season | Period | Mean | SD | Skewness | Kurtosis | Slope | ||
---|---|---|---|---|---|---|---|---|

Ann | A | 12.0 | * | 0.7 | 0.14 | −0.80 | 0.20 | |

B | 13.2 | * | 0.9 | −0.46 | 0.43 | 0.63 | ||

DJF | A | 1.3 | * | 1.9 | −0.34 | 0.29 | 0.58 | |

B | 2.4 | * | 1.7 | 0.08 | −0.78 | 0.50 | ||

MAM | A | 12.4 | * | 1.2 | −0.37 | −0.38 | 0.36 | |

B | 13.8 | * | 1.3 | −0.20 | −0.65 | 0.67 | ||

JJA | A | 21.9 | * | 0.9 | 0.32 | −0.19 | 0.02 | |

B | 23.8 | * | 1.2 | 0.59 | −0.54 | 0.62 | ||

SON | A | 12.4 | 1.0 | 0.54 | −0.22 | –0.14 | * | |

B | 12.8 | 1.2 | 0.16 | 0.03 | 0.74 | * |

**Table 5.**Selected statistical characteristics of annual (Ann) and seasonal (DJF, MAM, JJA, and SON) mean minimum temperature series in the Czech Republic in the 1961–1990 (A) and 1991–2020 (B) periods: means and standard deviations (SD) are in °C, linear trends in °C/10 years (in bold statistically significant at the 0.05 significance level). An asterisk * indicates statistically significant differences of a given characteristic between two 30-year periods.

Season | Period | Mean | SD | Skewness | Kurtosis | Slope | ||
---|---|---|---|---|---|---|---|---|

Ann | A | 3.1 | * | 0.6 | −0.10 | −0.91 | 0.24 | |

B | 4.0 | * | 0.7 | −0.37 | −0.22 | 0.51 | ||

DJF | A | −4.7 | 2.2 | −0.73 | 0.49 | 0.59 | ||

B | −3.7 | 1.8 | 0.05 | −0.71 | 0.64 | |||

MAM | A | 2.4 | * | 0.9 | −0.28 | −0.85 | 0.24 | |

B | 3.2 | * | 0.8 | −0.15 | −0.80 | 0.29 | ||

JJA | A | 10.6 | * | 0.6 | −0.88 | 0.95 | 0.05 | * |

B | 12.0 | * | 0.7 | −0.17 | −0.27 | 0.51 | * | |

SON | A | 3.9 | * | 1.0 | −0.24 | −1.15 | 0.00 | * |

B | 4.6 | * | 0.9 | 0.28 | 0.30 | 0.62 | * |

**Table 6.**Selected statistical characteristics of annual (Ann) and seasonal (DJF, MAM, JJA, and SON) mean relative humidity series in the Czech Republic in the 1961–1990 (A) and 1991–2020 (B) periods: means and standard deviations (SD) are in %, linear trends in %/10 years (in bold statistically significant at the 0.05 significance level). The asterisk * indicates statistically significant differences of a given characteristic between two 30-year periods.

Season | Period | Mean | SD | Skewness | Kurtosis | Slope | ||
---|---|---|---|---|---|---|---|---|

Ann | A | 79 | * | 1.3 | * | −0.35 | 0.11 | −0.6 |

B | 78 | * | 1.9 | * | −0.55 | −0.21 | −1.0 | |

DJF | A | 86 | * | 1.3 | –0.84 | 0.75 | –0.5 | |

B | 84 | * | 1.4 | −0.43 | −0.35 | −0.5 | ||

MAM | A | 75 | * | 2.2 | * | 0.06 | −0.16 | −1.3 |

B | 72 | * | 3.5 | * | −0.52 | −0.10 | −1.9 | |

JJA | A | 74 | * | 2.8 | −1.02 | 0.96 | −0.2 | |

B | 71 | * | 3.5 | −0.96 | −0.24 | −1.0 | ||

SON | A | 82 | 1.9 | −0.79 | 1.43 | −0.2 | ||

B | 83 | 2.2 | −0.31 | 0.58 | −0.2 |

**Table 7.**Selected statistical characteristics of annual (Ann) and seasonal (DJF, MAM, JJA, and SON) series of mean precipitation totals in the Czech Republic in the 1961–1990 (A) and 1991–2020 (B) periods: means are in mm, coefficients of variation (CV) in %, linear trends in mm/10 years (none statistically significant at the 0.05 significance level). An asterisk * indicates statistically significant differences of a given characteristic between two 30-year periods.

Season | Period | Mean | CV | Skewness | Kurtosis | Slope | |
---|---|---|---|---|---|---|---|

Ann | A | 681 | 12.8 | 0.44 | –0.84 | −2.4 | |

B | 699 | 12.7 | 0.01 | 0.06 | −1.7 | ||

DJF | A | 128 | 25.6 | −0.31 | –0.16 | 6.8 | |

B | 130 | 25.0 | −0.33 | –0.74 | 3.2 | ||

MAM | A | 162 | 18.7 | 1.60 | 4.09 | * | −8.1 |

B | 159 | 23.3 | 0.50 | –0.55 | * | −3.0 | |

JJA | A | 245 | 21.8 | 0.48 | 0.97 | −3.0 | |

B | 252 | 21.6 | 0.12 | –0.42 | −5.5 | ||

SON | A | 146 | 23.5 | 0.56 | 0.95 | 1.4 | |

B | 158 | 26.5 | 0.94 | 1.37 | 1.8 |

**Table 8.**Selected statistical characteristics of mean annual (Ann) and seasonal (DJF, MAM, JJA, and SON) wind speed series in the Czech Republic in the 1961–1990 (A) and 1991–2020 (B) periods: means are in m s

^{−1}, coefficients of variation (CV) in %, linear trends in m s

^{−1}/10 years (in bold statistically significant at the 0.05 significance level). An asterisk * indicates statistically significant differences of a given characteristic between two 30-year periods.

Season | Period | Mean | CV | Skewness | Kurtosis | Slope | ||||
---|---|---|---|---|---|---|---|---|---|---|

Ann | A | 2.5 | * | 3.2 | * | −0.15 | * | −0.83 | 0.01 | * |

B | 2.3 | * | 5.7 | * | 0.62 | * | −0.46 | −0.12 | * | |

DJF | A | 2.9 | * | 9.7 | 0.52 | −0.02 | 0.07 | |||

B | 2.6 | * | 10.4 | 0.22 | −0.95 | −0.10 | ||||

MAM | A | 2.7 | * | 4.7 | * | −0.13 | * | 0.20 | −0.01 | * |

B | 2.5 | * | 7.6 | * | 1.26 | * | 1.17 | −0.10 | * | |

JJA | A | 2.1 | * | 6.3 | −0.17 | 0.63 | −0.03 | * | ||

B | 2.0 | * | 6.0 | 0.07 | 0.06 | −0.10 | * | |||

SON | A | 2.4 | * | 7.1 | 0.22 | −0.76 | 0.02 | * | ||

B | 2.2 | * | 8.2 | 0.32 | −0.22 | −0.13 | * |

**Table 9.**Pearson correlation coefficients of annual (Ann) and seasonal (DJF, MAM, JJA, and SON) series between sunshine duration (SD) and mean maximum temperatures (TMAX) and between mean air temperature (TAVG) and relative humidity (RH) in the CR during the 1961–2020, 1991–1990, and 1991–2020 periods. Statistically significant correlation coefficients at the 0.05 significance level are in bold.

Period | Ann | DJF | MAM | JJA | SON |
---|---|---|---|---|---|

SD versus TMAX | |||||

1961–2020 | 0.58 | 0.11 | 0.70 | 0.80 | 0.46 |

1961–1990 | 0.55 | 0.18 | 0.51 | 0.75 | 0.47 |

1991–2020 | 0.52 | 0.08 | 0.78 | 0.80 | 0.55 |

TAVG versus RH | |||||

1961–2020 | −0.67 | −0.28 | −0.57 | −0.77 | −0.04 |

1961–1990 | −0.39 | −0.12 | −0.27 | −0.54 | 0.11 |

1991–2020 | −0.62 | −0.22 | −0.58 | −0.84 | −0.22 |

**Table 10.**Linear trends of selected annual (Ann) and seasonal (DJF, MAM, JJA, and SON) series of circulation types and climatic variables (Var.) in 1961–2020 (a) in comparison with signs of linear trends (+ positive, − negative, 0 no trend) in two 30-year normal periods, 1961–1990 and 1991–2020 (b): ACT—anticyclonic circulation types (days/10 years), CCT—cyclonic circulation types (days/10 years), DCT—directional circulation types (days/10 years), SD—sunshine duration (hours/10 years), TAVG—mean temperature (°C/10 years), TMAX—mean maximum temperature (°C/10 years), TMIN—mean minimum temperature (°C/10 years), RH—relative humidity (%/10 years), P—precipitation (mm/10 years), WS—wind speed (m s

^{−1}/10 years). Bold figures and signs with an asterisk * indicate statistically significant trends at the 0.05 significance level.

Var. | Ann | DJF | MAM | JJA | SON | |||||
---|---|---|---|---|---|---|---|---|---|---|

a | b | a | b | a | b | a | b | a | b | |

ACT | 6.8 | + */+ | 1.7 | +/− | 1.9 | +/+ | 2.8 | + */+ | 0.0 | +/+ |

CCT | −4.3 | − */0 | −0.6 | −/+ | −2.1 | −/− | −1.4 | − */+ | 0.0 | −/0 |

DCT | −1.7 | 0/− | −0.9 | −/+ | 0.0 | +/− | −0.9 | 0/− | 0.0 | −/− |

SD | 16.8 | −/+ | −1.2 | +/− | 14.0 | +/+ | 10.5 | −/− | −7.1 | −/+ |

TAVG | 0.37 | +/+ * | 0.36 | +/+ | 0.36 | +/+ | 0.45 | +/+ * | 0.23 | −/+ * |

TMAX | 0.42 | +/+ * | 0.39 | +/+ | 0.49 | +/+ * | 0.52 | +/+ * | 0.21 | −/+ * |

TMIN | 0.35 | +/+ * | 0.38 | +/+ | 0.25 | +/+ | 0.40 | +/+ * | 0.27 | 0/+ * |

RH | −0.6 | −/− * | −0.5 | −/− | −1.2 | − */− * | −0.9 | −/− | 0.0 | −/− |

P | 5.5 | −/− | 1.6 | +/+ | −2.6 | −/− | 1.0 | −/− | 2.8 | +/+ |

WS | −0.07 | +/− * | −0.06 | +/− | −0.07 | −/− * | −0.05 | −/− * | −0.08 | +/− * |

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**MDPI and ACS Style**

Brázdil, R.; Zahradníček, P.; Dobrovolný, P.; Řehoř, J.; Trnka, M.; Lhotka, O.; Štěpánek, P.
Circulation and Climate Variability in the Czech Republic between 1961 and 2020: A Comparison of Changes for Two “Normal” Periods. *Atmosphere* **2022**, *13*, 137.
https://doi.org/10.3390/atmos13010137

**AMA Style**

Brázdil R, Zahradníček P, Dobrovolný P, Řehoř J, Trnka M, Lhotka O, Štěpánek P.
Circulation and Climate Variability in the Czech Republic between 1961 and 2020: A Comparison of Changes for Two “Normal” Periods. *Atmosphere*. 2022; 13(1):137.
https://doi.org/10.3390/atmos13010137

**Chicago/Turabian Style**

Brázdil, Rudolf, Pavel Zahradníček, Petr Dobrovolný, Jan Řehoř, Miroslav Trnka, Ondřej Lhotka, and Petr Štěpánek.
2022. "Circulation and Climate Variability in the Czech Republic between 1961 and 2020: A Comparison of Changes for Two “Normal” Periods" *Atmosphere* 13, no. 1: 137.
https://doi.org/10.3390/atmos13010137