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Trends of Convective and Stratiform Precipitation in the Czech Republic, 1982–2010

Trends of Convective and Stratiform Precipitation in the Czech Republic, 1982–2010 Hindawi Publishing Corporation Advances in Meteorology Volume 2014, Article ID 647938, 11 pages http://dx.doi.org/10.1155/2014/647938 Research Article Trends of Convective and Stratiform Precipitation in the Czech Republic, 1982–2010 1,2,3 1,2 Zuzana Rulfová and Jan Kyselý Technical University of Liberec, Studentska´ 1402/2, 461 17 Liberec, Czech Republic Institute of Atmospheric Physics AS CR, Boˇcn´ıII1401, 14131Prague4,Czech Republic Faculty of Mathematics and Physics, Charles University, V Holeˇsoviˇckac ´ h 2, 180 00 Prague 8, Czech Republic Correspondence should be addressed to Zuzana Rulfova; ´ rulfova@ufa.cas.cz Received 6 November 2013; Accepted 20 January 2014; Published 2 March 2014 Academic Editor: Eduardo Garc´ıa-Ortega Copyright © 2014 Z. Rulfovaa ´ nd J. Kysely. ´ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. eTh study examines trends in characteristics of convective and stratiform precipitation in the Czech Republic over 1982–2010. eTh spatially averaged trends in convective precipitation are rising for indices of mean precipitation, and the increases are significant in all seasons except for winter. For extremes, the trends are spatially much more variable and insignificant, but increases tend to prevail as well. The trends in convective precipitation are larger in the western part of the country where Atlantic influences are stronger. For characteristics of stratiform precipitation, the trends are usually smaller compared to those of convective precipitation, but increases prevail too. eTh y are significant in autumn, especially for extremes, and larger in the eastern part of the country where Mediterranean cyclones play more important role. eTh trends in convective precipitation tend to be more pronounced at lowland than higher-elevated stations while an opposite pattern prevails for stratiform precipitation. eTh results suggest that in spring and summer, when convective precipitation represents an important fraction of the total amounts in central Europe (around 30% and 50%, respectively), the observed increases in total precipitation are mainly due to increases in convective precipitation. In autumn, increases in both convective and stratiform precipitation are important, and the trends are weakest and least pronounced in winter. 1. Introduction Little attention has been paid to the question whether these trends are related to changes in the proportion of Significant trends in characteristics of atmospheric precipi- precipitation falling from convective and stratiform clouds. tation were observed in Europe in recent decades. Predomi- The probable reason is the lack of long-term series of nantly increasing trends were reported in winter (e.g., [1–3]) precipitation data disaggregated according to their origin except for the Mediterranean [4–6]. In spring and summer, into convective and stratiform. Although the concepts of trends of extreme and mean precipitation are spatially less stratiform and convective precipitation are simplified and coherent. In spring, decreasing trends were observed in the there is no clear borderline between the two (e.g., in the southern Iberian Peninsula [6, 7], in Italy [5], andinthe case of embedded convection within large-scale stratiform Czech Republic [3] while increasing trends were observed in clouds and related spatial patterns of precipitation), these Germany and the United Kingdom (e.g., [2, 8]). In summer, two types are associated with different precipitation growth decreasing trends were found over northern part of Europe mechanisms and both play important roles in precipitation while increasing trends over central and western part of amounts falling during warm half-year in central Europe. Europe (e.g., [9]) except for Germany (e.g., [10]), Poland In recent years, several studies have aimed at discrimi- [11, 12], and the Iberian Peninsula (e.g., [13]). In autumn, nating convective and stratiform precipitation on the basis increasing trends of extreme precipitation prevail in many of different instruments and techniques. Many methods European regions except in north-eastern Germany (e.g., originate from studies of ground-based observations, but [2, 3, 8, 14]). more recent methods devised for disaggregating rainfall oeft n 2 Advances in Meteorology use data from radar and satellite measurements (e.g., [15, The majority of stations have a negligible percentage of 16]). Although methods based on radar and satellite data missing 6-hour precipitation data (less than 0.1%). Exceptions provide useful tools for such meteorological applications were stations 11698, with 4 months of missing data (January– as forecasting precipitation and analysing development of April 1989), and 11406, with 3 months of missing data precipitation systems (e.g., [17]), they are not applicable to (October–December 1993). eTh aeff cted seasons (winter and climatological studies because of the short records of available spring 1989, autumn and winter 1993) were omitted from the data. analysis at the given stations. Ruiz-Leo et al. [18]presented arelativelynew method based on 6-hour precipitation amounts from stations (stan- 2.2. Precipitation Patterns in the Czech Republic. Precipi- dard synoptic data) that provides the opportunity to acquire tation in the Czech Republic has large spatial and tem- long-time series of convective and stratiform precipitation for poralvariability.Theannualcycle hasasingle maximum analyses of changes in precipitation regimes. They examined in June and July and minimum in January and February trends of convective and stratiform precipitation for the [20]. Stratiform precipitation predominates in all seasons Spanish Mediterranean coast over 1998–2008 and found that except summer, at which time the proportion of convective the increasing trends of total precipitation were due to trends precipitation increases and leads to slightly higher amounts of in convective precipitation in autumn while stratiform pre- convective than stratiform origin at most stations [19]. Daily cipitation in spring. In winter and summer, neither convective precipitation amounts are greater in the warm half of the year nor stratiform precipitation had a prevailing role in trends of while the number of days with precipitation is greater in the total precipitation. cold half of the year [20]. In this study, we analyse trends of convective and strat- Spatial variability of precipitation is caused by the inu fl - iform precipitation in the Czech Republic (central Europe) ence of the large-scale atmospheric circulation which can be over 1982–2010. Time series of convective and stratiform pre- modified by local-scale parameters such as orography, wind cipitation are obtained using a recently proposed algorithm exposure, precipitation shadow, and direction of mountain fordisaggregationofprecipitation basedonSYNOP reports range. While an inflow of moist maritime air from the (surface synoptic observations) at weather stations [19]. Our north Atlantic strongly inu fl ences the western part of the approach is basedonthe same type of data as themethod Czech Republic, an inflow of warm, moist air from the used in [18], but we relax the simplifying assumption that Mediterraneanplays amorepronouncedroleinthe eastern heavy precipitation is of convective origin only. eTh algorithm part of the country (e.g., [21]). is based on several criteria, allowing also for disaggregation of heavy precipitation into predominantly convective and stratiform. 3. Methods The paper is structured as follows. After a short descrip- tion of the data and precipitation patterns in the Czech 3.1. Algorithm for Disaggregation of Precipitation. The time Republic in Section 2, the algorithm for disaggregation of series of convective and stratiform precipitation were obtain- precipitation is presented in Section 3, together with the ed using the algorithm proposed and evaluated in detail methodology applied to trend analysis. The results of the in [19]. As convective and stratiform precipitation fall from trend analysis of convective and stratiform precipitation are different clouds (convective from Cb and Cu while stratiform reported in Section 4. Section 5 contains discussion of the from Ns, Sc, St, and As) and they are characterized by results, and conclusions follow in Section 6. different types of weather events, the algorithm disaggregates 6-hour precipitation amounts into predominantly convective andstratiformonthe basisofweather state(themain criterion) and cloud type (the secondary criterion). Showers 2. Data and Area under Study and thunderstorms are the main groups of weather states 2.1. SYNOP Data. eTh precipitation data originate from typical for convective precipitation while drizzle, rain, and SYNOP reports at 11 stations operated by the Czech Hydrom- snow (the latter two not in the form of showers) are typical for eteorological Institute (CHMI). Geographical positions of stratiform precipitation. Details on the weather state coding the examined stations are depicted in Figure 1. eTh altitudes are given in [19]. of the stations range from 241 to 1322 m a.s.l., and the The algorithm is structured into three main steps. First, stations cover different climatological regions from lowlands it searches for nonzero 6-hour precipitation amounts and to mountains. The observations span from 1982 to 2010. readsall hourly data forweather stateand cloudtypeduring The dataset includes 6-hour precipitation amounts, codes the 6-hour period. Second, it disaggregates precipitation into of present and past weather (weather state) during the 6- convective and stratiform using the main criterion. If the hour interval, and hourly data on cloud cover, cloud type, air precipitation amount is classified as mixed/unresolved at this pressure, and temperature. stage (occurrence of codes of weather state associated with The quality of the data was thoroughly checked to uncover both convective and stratiform precipitation within the 6- possible errors and suspicious 6-hour precipitation records. hour interval or the data on weather state is missing), the Some missing and incorrect precipitation readings were filled secondarycriterionbasedonthecloudtypeisused.Thisleads in by comparing the SYNOP data with daily totals from to additional disaggregation. Finally, time series of convec- climatological measurements (aggregated 24-hour amounts). tive, stratiform, and mixed/unresolved 6-hour precipitation Advances in Meteorology 3 ∘ ∘ ∘ ∘ ∘ ∘ ∘ 13 14 15 16 17 18 19 <200 Germany 200–300 301–400 Poland 401–500 501–600 601–700 701–800 801–900 901–1000 ∘ 49 49 1001–1100 1101–1200 Germany Slovakia 1201–1300 1301–1400 Austria >1400 ∘ ∘ ∘ ∘ ∘ ∘ ∘ 12 13 14 15 16 17 18 0 25 50 100 (km) Figure 1: Area under study and locations of weather stations. The grey line shows a borderline between the western and eastern parts of the Czech Republic. amounts are created. The final algorithm was selected aer ft a Table 1: Acronyms used for precipitation characteristics. number of tests, described in detail in [19]. It disaggregates Acronym Description about 95% of 6-hour precipitation amounts and performs Amount Seasonal precipitation total better for moderate to heavy than light precipitation. eTh Days Number of wet days remaining small percentage of mixed/unresolved precipita- tion amounts (around 5%) does not show signicfi ant trends R6h Maximum seasonal 6-hour precipitation amount over time and was omitted from the analysis. R1D Maximum seasonal 1-day precipitation amount 3.2. Characteristics of Precipitation. For the trend analysis, bootstrap samples. For computing the confidence interval, we four variables and indices were selected to provide infor- mation on basic climatological characteristics of convective used 1,000 bootstrap samples. and stratiform precipitation (seasonal amount, the number Second, the nonparametric Sen’s estimator of slope, also knownasthe “medianofpair-wise slopes”orTheil-Sen of wet days) and extremes (maximum seasonal 6-hour and 1- day precipitation amounts). According to [9], a wet day was estimator [3, 25], was computed. The statistical significance of the trends was evaluated using the Mann-Kendall test den fi ed as a day with (convective or stratiform) precipitation [26, 27]. This is a rank-based test that is robust to outliers and above 1.0 mm. The acronyms used for individual characteris- tics arelistedin Table 1. does not depend on the assumption of Gaussian distribution of residuals. The indices of precipitation were calculated seasonally. The statistical significance of precipitation trends is usu- The seasons analysed were spring (MAM, March-April-May), summer (JJA, June-July-August), autumn (SON, September- ally lower compared with other climate elements due to large spatial and temporal variability of precipitation. eTh refore, October-November), and winter (DJF, December-January- February). we evaluate the results at lower signicfi ance levels of 𝑝= 0.1 and𝑝 = 0.2 . All trend magnitudes were expressed as relative changes of the examined characteristics in %/10 years, 3.3. Trend Estimation. Trends of precipitation indices were allowing easier comparison among the indices and seasons. estimated using two methods. First, the trend magnitudes were estimated parametrically by the least-squares regression (e.g., [22]) and the statistical signicfi ance of the trends was 4. Results computed by the bootstrap method (e.g., [23, 24]). eTh bootstrap is a type of a Monte Carlo method which is based Since precipitation has large random spatial variability and on resampling with replacement from the data to create the study area is relatively small, we evaluate time series 4 Advances in Meteorology Table 2: Trend magnitudes (expressed as relative change of the examined ch aracteristics in %/10 years) of average precipitation characteristics ∗ ∗∗ from all stations over 1982–2010. ( ) denotes trend significant at the 0.2 (0.1) level. Convective Stratiform Total Characteristics Lin. reg. Sen Lin. reg. Sen Lin. reg. Sen Spring ∗∗ ∗ ∗ Amount 9.2 8.0 0.0 −0.7 5.6 3.9 ∗∗ ∗∗ Days 14.7 14.0 −3.1 −3.7 3.0 1.5 R6h −5.7 −4.1 3.9 5.5 −0.2 −0.7 R1D −3.8 −4.1 2.9 4.1 2.5 1.4 Summer ∗∗ ∗ Amount 7.5 4.4 3.0 2.7 6.9 5.2 Days 5.3 4.6 −4.1 −5.2 1.6 1.4 R6h 0.5 0.7 1.3 −2.9 1.9 −1.6 R1D 2.2 2.2 4.9 2.5 6.6 2.8 Autumn ∗∗ ∗∗ ∗ ∗∗ ∗∗ ∗∗ Amount 14.7 15.8 9.7 10.7 11.9 11.5 ∗∗ ∗∗ ∗ ∗ Days 23.0 21.7 3.2 4.4 6.9 5.7 ∗ ∗∗ ∗ ∗ R6h 1.3 2.2 9.3 12.6 8.6 10.4 ∗∗ ∗∗ ∗∗ ∗∗ R1D 0.0 0.2 14.6 15.2 12.9 11.6 Winter Amount 1.6 1.4 −2.2 0.5 −1.1 2.2 Days −2.0 −1.7 −4.2 −2.2 −2.7 −3.3 R6h 5.9 −2.3 2.1 0.9 2.3 1.8 R1D 3.4 −1.4 2.5 1.5 2.2 1.3 Table 3: Trend magnitudes (expressed as relative change of the examined characteristics in %/10 years, from linear regression) of average ∗ ∗∗ precipitation characteristics over 1982–2010 for the western and the eastern part of the Czech Republic. ( ) denotes trend significant at the 0.2 (0.1) level. Convective Stratiform Total Characteristics West East West East West East Spring ∗∗ ∗ ∗ ∗∗ Amount 10.1 8.6 −5.9 4.9 3.1 7.7 ∗∗ ∗∗ ∗ ∗ Days 15.1 14.4 −5.3 −1.4 2.7 3.3 ∗∗ ∗ ∗ R6h −8.1 −3.5 1.9 5.7 −2.9 2.2 ∗ ∗∗ ∗∗ R1D −2.7 −4.6 −5.7 10.0 −4.1 8.0 Summer ∗∗ ∗∗ ∗∗ ∗ Amount 7.9 7.1 3.7 2.5 7.7 6.3 ∗∗ ∗∗ ∗ Days 5.9 4.9 −5.0 −3.4 1.8 1.5 R6h 0.5 0.4 4.3 −1.2 1.8 2.0 ∗ ∗ R1D 1.5 2.8 6.3 3.7 5.8 7.3 Autumn ∗∗ ∗ ∗ ∗∗ ∗∗ ∗∗ Amount 19.2 10.9 7.2 11.7 11.0 12.6 ∗∗ ∗∗ ∗ ∗∗ ∗∗ Days 27.8 19.1 2.0 4.2 7.1 6.7 ∗∗ ∗∗ R6h 5.0 −1.9 2.2 15.1 2.2 13.9 ∗∗ ∗∗ ∗∗ ∗∗ R1D 4.5 −4.0 8.1 19.9 7.1 17.7 Winter Amount 5.7 −1.9 −6.0 1.0 −4.5 1.9 ∗∗ ∗ Days −1.0 −2.9 −5.7 −3.0 −4.2 −1.4 R6h 13.2 −0.2 1.3 2.8 2.6 2.1 ∗ ∗ R1D 10.1 −2.2 −1.2 5.7 −1.2 5.2 Advances in Meteorology 5 Total Days R6h R1D 2.5 2.5 2.5 2.5 1.5 1.5 1.5 1.5 2.0 2.0 2.0 2.0 1.0 1.0 1.0 1.0 0.5 0.5 0.5 0.5 1985 1990 1995 2000 2005 2010 1985 1990 1995 2000 2005 2010 1985 1990 1995 2000 2005 2010 1985 1990 1995 2000 2005 2010 Year Year Year Year 2.5 2.5 2.5 2.5 1.5 1.5 1.5 1.5 2.0 2.0 2.0 2.0 1.0 1.0 1.0 1.0 0.5 0.5 0.5 0.5 1985 1990 1995 2000 2005 2010 1985 1990 1995 2000 2005 2010 1985 1990 1995 2000 2005 2010 1985 1990 1995 2000 2005 2010 Year Year Year Year 2.5 2.5 2.5 2.5 1.5 1.5 1.5 1.5 2.0 2.0 2.0 2.0 1.0 1.0 1.0 1.0 0.5 0.5 0.5 0.5 1985 1990 1995 2000 2005 2010 1985 1990 1995 2000 2005 2010 1985 1990 1995 2000 2005 2010 1985 1990 1995 2000 2005 2010 Year Year Year Year 2.5 2.5 2.5 2.5 1.5 1.5 1.5 1.5 2.0 2.0 2.0 2.0 1.0 1.0 1.0 1.0 0.5 0.5 0.5 0.5 1985 1990 1995 2000 2005 2010 1985 1990 1995 2000 2005 2010 1985 1990 1995 2000 2005 2010 1985 1990 1995 2000 2005 2010 Year Year Year Year Convective Convective Convective Convective Stratiform Stratiform Stratiform Stratiform Total Total Total Total Figure 2: Time series and trend magnitudes obtained by the linear regression for convective, stratiform, and total precipitation characteristics averaged over 11 stations in the Czech Republic. obtained by averaging data from (a) all stations and (b) and in Table 3 for the western and eastern parts of the Czech stations in the western and eastern parts of the Czech Republic. Time series of the spatially averaged characteristics Republic (Figure 1). Analogous division was applied by Kysely´ are plotted in Figure 2, and dependence of the trend mag- [3] who reported the cutoff between the western and eastern nitudes on altitude is depicted in Figure 3.All gfi ures and parts of the Czech Republic in trends of precipitation char- the description of results are based on the linear regression acteristics, which may be linked to meteorological factors, because results obtained by the parametric (least-squares namely,dieff rencesintherolesofAtlanticandMediterranean regression) and nonparametric (Sen’s estimator) trend esti- influences. Herein, the averages are calculated from scaled mation are similar (Table 2). Particularly, we did not nd fi a stations’ data in order to give the same weight to all stations general tendency of the parametric estimate to be greater (in (notwithstanding the observed precipitation amounts and absolute value) than the nonparametric estimate (cf. [28]). thenumberofwet days,which arelargerathigher-elevated stations). The characteristics at individual stations were rfi st 4.1. Convective Precipitation. Trends of spatially averaged divided by their mean values over the studied period and climatological characteristics of convective precipitation (the then these scaled (dimensionless) data were averaged over the total amount and the number of wet days) are increasing and stations. statistically signicfi ant in all seasons except winter (when the The trends in spatially averaged characteristics and their proportion of convective precipitation is very low; Table 2 statistical significance are shown in Table 2 for all stations and Figure 2). The increasing trends are higher in the western Winter Autumn Summer Spring Dimensionless precipitation Dimensionless precipitation Dimensionless precipitation Dimensionless precipitation characteristic characteristic characteristic characteristic Dimensionless precipitation Dimensionless precipitation Dimensionless precipitation Dimensionless precipitation characteristic characteristic characteristic characteristic Dimensionless precipitation Dimensionless precipitation Dimensionless precipitation Dimensionless precipitation characteristic characteristic characteristic characteristic Dimensionless precipitation Dimensionless precipitation Dimensionless precipitation Dimensionless precipitation characteristic characteristic characteristic characteristic 6 Advances in Meteorology Amount Days R6h R1D 15 10 −10 −10 −20 5 −20 −30 −5 −30 −40 −10 −40 −10 200 400 600 800 1000 1200 200 400 600 800 1000 1200 200 400 600 800 1000 1200 200 400 600 800 1000 1200 Altitude (m) Altitude (m) Altitude (m) Altitude (m) 10 15 10 10 0 −5 −5 −5 −10 −10 −5 −10 −15 200 400 600 800 1000 1200 200 400 600 800 1000 1200 200 400 600 800 1000 1200 200 400 600 800 1000 1200 Altitude (m) Altitude (m) Altitude (m) Altitude (m) 20 20 −10 −10 −20 −10 −20 200 400 600 800 1000 1200 200 400 600 800 1000 1200 200 400 600 800 1000 1200 200 400 600 800 1000 1200 Altitude (m) Altitude (m) Altitude (m) Altitude (m) 40 40 40 30 −10 −20 −20 −20 −20 −40 −40 −30 200 400 600 800 1000 1200 200 400 600 800 1000 1200 200 400 600 800 1000 1200 200 400 600 800 1000 1200 Altitude (m) Altitude (m) Altitude (m) Altitude (m) Convective Convective Convective Convective Stratiform Stratiform Stratiform Stratiform Total Total Total Total Figure 3: Dependence between trend magnitudes and altitude for characteristics of convective, stratiform, and total precipitation. Trends estimated by the linear regression and their 95% confidence bounds are plotted. than eastern part of the Czech Republic in all seasons (Table 3, spatially averaged indices, increasing trends prevail as well. Figure 4). Spatially averaged extreme precipitation indices The largest and statistically significant trends are found in of convective precipitation (seasonal maxima of 6-hour and autumn, particularly for extremes. The tendency to increases 1-day precipitation, R6 h, and R1D) increase in all seasons is more pronounced in the eastern part of the Czech Republic except spring but the trends are smaller and insignificant. in all seasons except for summer (Table 3,Figures 4 and 5). The trends of extreme precipitation tend to have opposite eTh trends of stratiform precipitation tend to be of opposite signs in autumn and winter in the western (positive) and signs in the western (negative) and eastern (positive) part eastern (negative) part of the country (Table 3, Figure 5). of the country in winter and spring, which leads to very The climatological characteristics of convective precipitation small trends for the country as a whole. By contrast to increase faster in lowlands than in highlands in all seasons convective precipitation, stratiform precipitation has usually while for extremes such pattern is found only in summer and more pronounced positive trends in highlands (Figure 3). winter (Figure 3). Differences between lowlands and highlands are larger in spring and summer. 4.2. Stratiform Precipitation. The trends in characteristics of stratiform precipitation are usually smaller compared 4.3. Total Precipitation. Increasing trends of total precipita- to those of convective precipitation (Table 2, Figure 2). For tion prevail in all seasons except winter (Table 2,Figures 2, Winter Autumn Summer Spring Magnitude of trend (%/10 yrs) Magnitude of trend (%/10 yrs) Magnitude of trend (%/10 yrs) Magnitude of trend (%/10 yrs) Magnitude of trend (%/10 yrs) Magnitude of trend (%/10 yrs) Magnitude of trend (%/10 yrs) Magnitude of trend (%/10 yrs) Magnitude of trend (%/10 yrs) Magnitude of trend (%/10 yrs) Magnitude of trend (%/10 yrs) Magnitude of trend (%/10 yrs) Magnitude of trend (%/10 yrs) Magnitude of trend (%/10 yrs) Magnitude of trend (%/10 yrs) Magnitude of trend (%/10 yrs) Advances in Meteorology 7 Spring Summer Autumn Winter Trend (%/10 yrs) <−10 0 >10 −10–−6 0–3 p = 0.2 −6–−3 3–6 p = 0.1 −3–0 6–10 Figure 4: Trends in seasonal amounts of convective, stratiform, and total precipitation computed by the linear regression. Trend magnitudes are expressed as relative changes of the examined characteristics in %/10 years over 1982–2010. 4,and 5). The largest and statistically significant trends are autumn), convective precipitation increases (in averaged found in autumn, which corresponds with increasing trends precipitation characteristics from all stations) more than of both convective and stratiform precipitation. eTh trends stratiform for seasonal precipitation amounts as well as the of total precipitation are by far weakest in winter, when also number of wet days. Our results contrast with those reported trends of convective and stratiform precipitation are rarely by Ruiz-Leo et al. [18], who found steeper (positive) trends significant. In spring and summer, some characteristics of for stratiform than convective precipitation in the eastern convective precipitation increase while of stratiform precipi- Spanishcoast.They,however,had examinednot only a tation decrease and vice versa. es Th e counterbalancing trends different area but also a much shorter time period (1998– of convective and stratiform precipitation lead to relatively 2008) and used a different algorithm for disaggregating small trends of total precipitation. The trend magnitudes precipitation, as reported above. Our algorithm is based on of total precipitation depend on altitude similarly as those different criteria, allowing also for disaggregation of heavy of stratiform precipitation in all seasons except summer precipitation into predominantly convective and stratiform (Figure 3), when theroleofconvectiveprecipitationis largest. [19], while Ruiz-Leo et al. [18] considered heavy precipitation eTh ratio between convective and stratiform precipitation to be of convective origin only. eTh ir approach was reasonable increases in all seasons, especially in summer (Figure 6). It for the specific study area (north-eastern coast of Spain) but is particularly noteworthy that the four highest values over it is not generally applicable in other regions. 1982–2010occurredinthe last 8years,and thedominance Mean convective precipitation increases significantly in of convective precipitation was greatest in the 2003 spring all seasons except winter while heavy precipitation decreases and summer that were characterized by severe heat waves in spring or has small insignificant trends in summer and in Europe and large precipitation deficits (e.g., [ 29–32]). Our autumn. Our results are in agreement with [33, 34], where results show that the deficits over central Europe were mainly climatological characteristics and trends of thunderstorms duetothe lack of stratiform precipitation(cf.also Figure 2). over Poland were studied and increasing trends of days with lightthunderstormatthe endofthe 20th century while decreasing or no clear trends of days with heavy 5. Discussion thunderstorm were reported. There is an ongoing discussion concerning possible In all seasons in which convective precipitation represents changes in precipitation rates and relative contributions an important part of total amounts (spring, summer, and Total Stratiform Convective 8 Advances in Meteorology Spring Summer Autumn Winter Trend (%/10 yrs) <−10 0 >10 −10–−6 0–3 p = 0.2 −6–−3 3–6 p = 0.1 −3–0 6–10 Figure 5: Same as in Figure 4 but for maximum seasonal 1-day precipitation amount (R1D). of convective and stratiform precipitation with increasing continental influence) parts of the Czech Republic. A ten- surface temperatures (e.g., [35, 36]). Increasing proportion dency to more pronounced trends in convective (stratiform) of convective precipitation, found in all seasons, corresponds precipitation in the west (east) may be related to changes with increasing trends of surface air temperature [19]. This of large-scale circulation influencing differently precipitation may suggest that the changing ratio of convective and over these two regions of central Europe; however, the stratiform precipitation is related to climate change and may links between large-scale circulation and precipitation are continue (with increasing temperature) in future. However, weakest in the convective season (cf. [38]). Increasing trends our results show that this does not necessarily mean more of stratiform precipitationinautumninthe easternpart heavy convective precipitation, because intensity of precipi- of the country may be due to enhanced occurrence of tation depends on a number of factors such as atmospheric cyclones of the Mediterranean origin (typically associated humidity andstability,CAPE, andwindshear (e.g., [37]). with widespread and heavy stratiform rainfall). Detailed eTh trends of total precipitation are predominantly study of the links between precipitation changes and the increasing in all seasons except winter (and 6-hour maxima large-scale circulation deserves further investigation. in spring). The overall tendency to prevailing positive trends Similar analyses for other parts of Europe are needed in agrees with Kysely[ ´ 3] who examined trends in characteristics order to reveal whether the reported differences (in trends of of mean and heavy (total) precipitation in the Czech Repub- convective/stratiform precipitation and mean/extreme char- licover1961–2005 andreportedpredominantly increasing acteristics) and the cutoff between the western and eastern trends in all seasons except spring. eTh differences are related parts of the examined area are related to larger-scale patterns to different studied periods, different sets of stations, and the over Europe. Such studies should be straightforward because fact that trend estimates may be strongly influenced by values the necessary data (SYNOP reports) are available, and the at the beginning and the end of time series. However, our proposed algorithm [19] is universal and does not involve any results also show that the overall tendency to rising trends “local” settings. in precipitation characteristics does not depend substantially on the time window. 6. Conclusions A distinct differentiation in the predominant trend directions of convective, stratiform, and total precipitation Using the recently proposed algorithm for disaggregating emerges when comparing the western (with stronger Atlantic precipitation into predominantly convective and stratiform influence) and the eastern (with stronger Mediterranean and [19], we analysed trends in characteristics of convective and Total Stratiform Convective Advances in Meteorology 9 Spring Summer 1.5 1.0 0.5 0.0 1985 1990 1995 2000 2005 2010 1985 1990 1995 2000 2005 2010 Year Year Autumn Winter 0.20 0.6 0.15 0.4 0.10 0.2 0.05 0.0 0.00 1985 1990 1995 2000 2005 2010 1985 1990 1995 2000 2005 2010 Year Year Figure 6: Ratio of convective and stratiform precipitation (averages over 11 stations in the Czech Republic) and trend estimated by the linear regression. stratiform precipitation and their influence on trends of total are significant in autumn, especially for extremes, precipitation at weather stations in the Czech Republic over and larger in the eastern part of the country where 1982–2010. eTh trendanalysiswas basedonthe least-squares Mediterranean cyclones play more important role. regression and the Sen’s estimator of slope but the results (iii) The trends in convective precipitation tend to be more depend little on the method used. pronounced at lowland than higher-elevated stations The main findings are as follows. while an opposite pattern prevails for stratiform precipitation. This indicates that the increases in con- (i) Spatially averaged trends in convective precipitation are increasing and statistically significant for precip- vective precipitation are not related to orographically triggered convection. The largest differences in trend itation amounts and the number of wet days in all magnitudes of convective and stratiform precipitation seasons except for winter. eTh trends of extreme con- vective precipitation (seasonal maxima) are spatially between lowlands and highlands occur in spring and summer. much more variable and insignicfi ant, but increases tend to prevail as well. The trends in convective (iv) In spring and summer, when convective precipitation precipitation are larger in the western part of the represents an important fraction of the total amounts country where Atlantic influences are stronger. in central Europe (around 30% and 50%, resp., when (ii) For characteristics of stratiform precipitation, the averaged over the stations under study), the observed trends are usually smaller compared to those of con- increases in total precipitation are mainly due to vective precipitation, but increases prevail too. They increases in convective precipitation. 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Matschullat, “Precipitation trend anisms of observed changes in precipitation characteristics. analysis for central eastern Germany 1851–2006,” in Bioclima- eTh topic is particularly appealing in the context of climate tology and Natural Hazards,K.Strelcova´, C. Matyas,A.Kleidon change, as climate models simulate convective and stratiform et al., Eds., pp. 29–38, Springer, Amsterdam, eTh Netherlands, precipitation separately through different parameterizations. eTh projectedchanges in thetwo components maybe [11] E. Łupikasza, “Spatial and temporal variability of extreme precipitation in poland in the period 1951–2006,” International compared with the recently observed trend, which might help Journal of Climatology,vol.30, no.7,pp. 991–1007,2010. understand whether the increasing proportion of convective [12] E. B. Łupikasza, S. Ha¨nsel, and J. 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Trends of Convective and Stratiform Precipitation in the Czech Republic, 1982–2010

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Copyright © 2014 Zuzana Rulfová and Jan Kyselý. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Hindawi Publishing Corporation Advances in Meteorology Volume 2014, Article ID 647938, 11 pages http://dx.doi.org/10.1155/2014/647938 Research Article Trends of Convective and Stratiform Precipitation in the Czech Republic, 1982–2010 1,2,3 1,2 Zuzana Rulfová and Jan Kyselý Technical University of Liberec, Studentska´ 1402/2, 461 17 Liberec, Czech Republic Institute of Atmospheric Physics AS CR, Boˇcn´ıII1401, 14131Prague4,Czech Republic Faculty of Mathematics and Physics, Charles University, V Holeˇsoviˇckac ´ h 2, 180 00 Prague 8, Czech Republic Correspondence should be addressed to Zuzana Rulfova; ´ rulfova@ufa.cas.cz Received 6 November 2013; Accepted 20 January 2014; Published 2 March 2014 Academic Editor: Eduardo Garc´ıa-Ortega Copyright © 2014 Z. Rulfovaa ´ nd J. Kysely. ´ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. eTh study examines trends in characteristics of convective and stratiform precipitation in the Czech Republic over 1982–2010. eTh spatially averaged trends in convective precipitation are rising for indices of mean precipitation, and the increases are significant in all seasons except for winter. For extremes, the trends are spatially much more variable and insignificant, but increases tend to prevail as well. The trends in convective precipitation are larger in the western part of the country where Atlantic influences are stronger. For characteristics of stratiform precipitation, the trends are usually smaller compared to those of convective precipitation, but increases prevail too. eTh y are significant in autumn, especially for extremes, and larger in the eastern part of the country where Mediterranean cyclones play more important role. eTh trends in convective precipitation tend to be more pronounced at lowland than higher-elevated stations while an opposite pattern prevails for stratiform precipitation. eTh results suggest that in spring and summer, when convective precipitation represents an important fraction of the total amounts in central Europe (around 30% and 50%, respectively), the observed increases in total precipitation are mainly due to increases in convective precipitation. In autumn, increases in both convective and stratiform precipitation are important, and the trends are weakest and least pronounced in winter. 1. Introduction Little attention has been paid to the question whether these trends are related to changes in the proportion of Significant trends in characteristics of atmospheric precipi- precipitation falling from convective and stratiform clouds. tation were observed in Europe in recent decades. Predomi- The probable reason is the lack of long-term series of nantly increasing trends were reported in winter (e.g., [1–3]) precipitation data disaggregated according to their origin except for the Mediterranean [4–6]. In spring and summer, into convective and stratiform. Although the concepts of trends of extreme and mean precipitation are spatially less stratiform and convective precipitation are simplified and coherent. In spring, decreasing trends were observed in the there is no clear borderline between the two (e.g., in the southern Iberian Peninsula [6, 7], in Italy [5], andinthe case of embedded convection within large-scale stratiform Czech Republic [3] while increasing trends were observed in clouds and related spatial patterns of precipitation), these Germany and the United Kingdom (e.g., [2, 8]). In summer, two types are associated with different precipitation growth decreasing trends were found over northern part of Europe mechanisms and both play important roles in precipitation while increasing trends over central and western part of amounts falling during warm half-year in central Europe. Europe (e.g., [9]) except for Germany (e.g., [10]), Poland In recent years, several studies have aimed at discrimi- [11, 12], and the Iberian Peninsula (e.g., [13]). In autumn, nating convective and stratiform precipitation on the basis increasing trends of extreme precipitation prevail in many of different instruments and techniques. Many methods European regions except in north-eastern Germany (e.g., originate from studies of ground-based observations, but [2, 3, 8, 14]). more recent methods devised for disaggregating rainfall oeft n 2 Advances in Meteorology use data from radar and satellite measurements (e.g., [15, The majority of stations have a negligible percentage of 16]). Although methods based on radar and satellite data missing 6-hour precipitation data (less than 0.1%). Exceptions provide useful tools for such meteorological applications were stations 11698, with 4 months of missing data (January– as forecasting precipitation and analysing development of April 1989), and 11406, with 3 months of missing data precipitation systems (e.g., [17]), they are not applicable to (October–December 1993). eTh aeff cted seasons (winter and climatological studies because of the short records of available spring 1989, autumn and winter 1993) were omitted from the data. analysis at the given stations. Ruiz-Leo et al. [18]presented arelativelynew method based on 6-hour precipitation amounts from stations (stan- 2.2. Precipitation Patterns in the Czech Republic. Precipi- dard synoptic data) that provides the opportunity to acquire tation in the Czech Republic has large spatial and tem- long-time series of convective and stratiform precipitation for poralvariability.Theannualcycle hasasingle maximum analyses of changes in precipitation regimes. They examined in June and July and minimum in January and February trends of convective and stratiform precipitation for the [20]. Stratiform precipitation predominates in all seasons Spanish Mediterranean coast over 1998–2008 and found that except summer, at which time the proportion of convective the increasing trends of total precipitation were due to trends precipitation increases and leads to slightly higher amounts of in convective precipitation in autumn while stratiform pre- convective than stratiform origin at most stations [19]. Daily cipitation in spring. In winter and summer, neither convective precipitation amounts are greater in the warm half of the year nor stratiform precipitation had a prevailing role in trends of while the number of days with precipitation is greater in the total precipitation. cold half of the year [20]. In this study, we analyse trends of convective and strat- Spatial variability of precipitation is caused by the inu fl - iform precipitation in the Czech Republic (central Europe) ence of the large-scale atmospheric circulation which can be over 1982–2010. Time series of convective and stratiform pre- modified by local-scale parameters such as orography, wind cipitation are obtained using a recently proposed algorithm exposure, precipitation shadow, and direction of mountain fordisaggregationofprecipitation basedonSYNOP reports range. While an inflow of moist maritime air from the (surface synoptic observations) at weather stations [19]. Our north Atlantic strongly inu fl ences the western part of the approach is basedonthe same type of data as themethod Czech Republic, an inflow of warm, moist air from the used in [18], but we relax the simplifying assumption that Mediterraneanplays amorepronouncedroleinthe eastern heavy precipitation is of convective origin only. eTh algorithm part of the country (e.g., [21]). is based on several criteria, allowing also for disaggregation of heavy precipitation into predominantly convective and stratiform. 3. Methods The paper is structured as follows. After a short descrip- tion of the data and precipitation patterns in the Czech 3.1. Algorithm for Disaggregation of Precipitation. The time Republic in Section 2, the algorithm for disaggregation of series of convective and stratiform precipitation were obtain- precipitation is presented in Section 3, together with the ed using the algorithm proposed and evaluated in detail methodology applied to trend analysis. The results of the in [19]. As convective and stratiform precipitation fall from trend analysis of convective and stratiform precipitation are different clouds (convective from Cb and Cu while stratiform reported in Section 4. Section 5 contains discussion of the from Ns, Sc, St, and As) and they are characterized by results, and conclusions follow in Section 6. different types of weather events, the algorithm disaggregates 6-hour precipitation amounts into predominantly convective andstratiformonthe basisofweather state(themain criterion) and cloud type (the secondary criterion). Showers 2. Data and Area under Study and thunderstorms are the main groups of weather states 2.1. SYNOP Data. eTh precipitation data originate from typical for convective precipitation while drizzle, rain, and SYNOP reports at 11 stations operated by the Czech Hydrom- snow (the latter two not in the form of showers) are typical for eteorological Institute (CHMI). Geographical positions of stratiform precipitation. Details on the weather state coding the examined stations are depicted in Figure 1. eTh altitudes are given in [19]. of the stations range from 241 to 1322 m a.s.l., and the The algorithm is structured into three main steps. First, stations cover different climatological regions from lowlands it searches for nonzero 6-hour precipitation amounts and to mountains. The observations span from 1982 to 2010. readsall hourly data forweather stateand cloudtypeduring The dataset includes 6-hour precipitation amounts, codes the 6-hour period. Second, it disaggregates precipitation into of present and past weather (weather state) during the 6- convective and stratiform using the main criterion. If the hour interval, and hourly data on cloud cover, cloud type, air precipitation amount is classified as mixed/unresolved at this pressure, and temperature. stage (occurrence of codes of weather state associated with The quality of the data was thoroughly checked to uncover both convective and stratiform precipitation within the 6- possible errors and suspicious 6-hour precipitation records. hour interval or the data on weather state is missing), the Some missing and incorrect precipitation readings were filled secondarycriterionbasedonthecloudtypeisused.Thisleads in by comparing the SYNOP data with daily totals from to additional disaggregation. Finally, time series of convec- climatological measurements (aggregated 24-hour amounts). tive, stratiform, and mixed/unresolved 6-hour precipitation Advances in Meteorology 3 ∘ ∘ ∘ ∘ ∘ ∘ ∘ 13 14 15 16 17 18 19 <200 Germany 200–300 301–400 Poland 401–500 501–600 601–700 701–800 801–900 901–1000 ∘ 49 49 1001–1100 1101–1200 Germany Slovakia 1201–1300 1301–1400 Austria >1400 ∘ ∘ ∘ ∘ ∘ ∘ ∘ 12 13 14 15 16 17 18 0 25 50 100 (km) Figure 1: Area under study and locations of weather stations. The grey line shows a borderline between the western and eastern parts of the Czech Republic. amounts are created. The final algorithm was selected aer ft a Table 1: Acronyms used for precipitation characteristics. number of tests, described in detail in [19]. It disaggregates Acronym Description about 95% of 6-hour precipitation amounts and performs Amount Seasonal precipitation total better for moderate to heavy than light precipitation. eTh Days Number of wet days remaining small percentage of mixed/unresolved precipita- tion amounts (around 5%) does not show signicfi ant trends R6h Maximum seasonal 6-hour precipitation amount over time and was omitted from the analysis. R1D Maximum seasonal 1-day precipitation amount 3.2. Characteristics of Precipitation. For the trend analysis, bootstrap samples. For computing the confidence interval, we four variables and indices were selected to provide infor- mation on basic climatological characteristics of convective used 1,000 bootstrap samples. and stratiform precipitation (seasonal amount, the number Second, the nonparametric Sen’s estimator of slope, also knownasthe “medianofpair-wise slopes”orTheil-Sen of wet days) and extremes (maximum seasonal 6-hour and 1- day precipitation amounts). According to [9], a wet day was estimator [3, 25], was computed. The statistical significance of the trends was evaluated using the Mann-Kendall test den fi ed as a day with (convective or stratiform) precipitation [26, 27]. This is a rank-based test that is robust to outliers and above 1.0 mm. The acronyms used for individual characteris- tics arelistedin Table 1. does not depend on the assumption of Gaussian distribution of residuals. The indices of precipitation were calculated seasonally. The statistical significance of precipitation trends is usu- The seasons analysed were spring (MAM, March-April-May), summer (JJA, June-July-August), autumn (SON, September- ally lower compared with other climate elements due to large spatial and temporal variability of precipitation. eTh refore, October-November), and winter (DJF, December-January- February). we evaluate the results at lower signicfi ance levels of 𝑝= 0.1 and𝑝 = 0.2 . All trend magnitudes were expressed as relative changes of the examined characteristics in %/10 years, 3.3. Trend Estimation. Trends of precipitation indices were allowing easier comparison among the indices and seasons. estimated using two methods. First, the trend magnitudes were estimated parametrically by the least-squares regression (e.g., [22]) and the statistical signicfi ance of the trends was 4. Results computed by the bootstrap method (e.g., [23, 24]). eTh bootstrap is a type of a Monte Carlo method which is based Since precipitation has large random spatial variability and on resampling with replacement from the data to create the study area is relatively small, we evaluate time series 4 Advances in Meteorology Table 2: Trend magnitudes (expressed as relative change of the examined ch aracteristics in %/10 years) of average precipitation characteristics ∗ ∗∗ from all stations over 1982–2010. ( ) denotes trend significant at the 0.2 (0.1) level. Convective Stratiform Total Characteristics Lin. reg. Sen Lin. reg. Sen Lin. reg. Sen Spring ∗∗ ∗ ∗ Amount 9.2 8.0 0.0 −0.7 5.6 3.9 ∗∗ ∗∗ Days 14.7 14.0 −3.1 −3.7 3.0 1.5 R6h −5.7 −4.1 3.9 5.5 −0.2 −0.7 R1D −3.8 −4.1 2.9 4.1 2.5 1.4 Summer ∗∗ ∗ Amount 7.5 4.4 3.0 2.7 6.9 5.2 Days 5.3 4.6 −4.1 −5.2 1.6 1.4 R6h 0.5 0.7 1.3 −2.9 1.9 −1.6 R1D 2.2 2.2 4.9 2.5 6.6 2.8 Autumn ∗∗ ∗∗ ∗ ∗∗ ∗∗ ∗∗ Amount 14.7 15.8 9.7 10.7 11.9 11.5 ∗∗ ∗∗ ∗ ∗ Days 23.0 21.7 3.2 4.4 6.9 5.7 ∗ ∗∗ ∗ ∗ R6h 1.3 2.2 9.3 12.6 8.6 10.4 ∗∗ ∗∗ ∗∗ ∗∗ R1D 0.0 0.2 14.6 15.2 12.9 11.6 Winter Amount 1.6 1.4 −2.2 0.5 −1.1 2.2 Days −2.0 −1.7 −4.2 −2.2 −2.7 −3.3 R6h 5.9 −2.3 2.1 0.9 2.3 1.8 R1D 3.4 −1.4 2.5 1.5 2.2 1.3 Table 3: Trend magnitudes (expressed as relative change of the examined characteristics in %/10 years, from linear regression) of average ∗ ∗∗ precipitation characteristics over 1982–2010 for the western and the eastern part of the Czech Republic. ( ) denotes trend significant at the 0.2 (0.1) level. Convective Stratiform Total Characteristics West East West East West East Spring ∗∗ ∗ ∗ ∗∗ Amount 10.1 8.6 −5.9 4.9 3.1 7.7 ∗∗ ∗∗ ∗ ∗ Days 15.1 14.4 −5.3 −1.4 2.7 3.3 ∗∗ ∗ ∗ R6h −8.1 −3.5 1.9 5.7 −2.9 2.2 ∗ ∗∗ ∗∗ R1D −2.7 −4.6 −5.7 10.0 −4.1 8.0 Summer ∗∗ ∗∗ ∗∗ ∗ Amount 7.9 7.1 3.7 2.5 7.7 6.3 ∗∗ ∗∗ ∗ Days 5.9 4.9 −5.0 −3.4 1.8 1.5 R6h 0.5 0.4 4.3 −1.2 1.8 2.0 ∗ ∗ R1D 1.5 2.8 6.3 3.7 5.8 7.3 Autumn ∗∗ ∗ ∗ ∗∗ ∗∗ ∗∗ Amount 19.2 10.9 7.2 11.7 11.0 12.6 ∗∗ ∗∗ ∗ ∗∗ ∗∗ Days 27.8 19.1 2.0 4.2 7.1 6.7 ∗∗ ∗∗ R6h 5.0 −1.9 2.2 15.1 2.2 13.9 ∗∗ ∗∗ ∗∗ ∗∗ R1D 4.5 −4.0 8.1 19.9 7.1 17.7 Winter Amount 5.7 −1.9 −6.0 1.0 −4.5 1.9 ∗∗ ∗ Days −1.0 −2.9 −5.7 −3.0 −4.2 −1.4 R6h 13.2 −0.2 1.3 2.8 2.6 2.1 ∗ ∗ R1D 10.1 −2.2 −1.2 5.7 −1.2 5.2 Advances in Meteorology 5 Total Days R6h R1D 2.5 2.5 2.5 2.5 1.5 1.5 1.5 1.5 2.0 2.0 2.0 2.0 1.0 1.0 1.0 1.0 0.5 0.5 0.5 0.5 1985 1990 1995 2000 2005 2010 1985 1990 1995 2000 2005 2010 1985 1990 1995 2000 2005 2010 1985 1990 1995 2000 2005 2010 Year Year Year Year 2.5 2.5 2.5 2.5 1.5 1.5 1.5 1.5 2.0 2.0 2.0 2.0 1.0 1.0 1.0 1.0 0.5 0.5 0.5 0.5 1985 1990 1995 2000 2005 2010 1985 1990 1995 2000 2005 2010 1985 1990 1995 2000 2005 2010 1985 1990 1995 2000 2005 2010 Year Year Year Year 2.5 2.5 2.5 2.5 1.5 1.5 1.5 1.5 2.0 2.0 2.0 2.0 1.0 1.0 1.0 1.0 0.5 0.5 0.5 0.5 1985 1990 1995 2000 2005 2010 1985 1990 1995 2000 2005 2010 1985 1990 1995 2000 2005 2010 1985 1990 1995 2000 2005 2010 Year Year Year Year 2.5 2.5 2.5 2.5 1.5 1.5 1.5 1.5 2.0 2.0 2.0 2.0 1.0 1.0 1.0 1.0 0.5 0.5 0.5 0.5 1985 1990 1995 2000 2005 2010 1985 1990 1995 2000 2005 2010 1985 1990 1995 2000 2005 2010 1985 1990 1995 2000 2005 2010 Year Year Year Year Convective Convective Convective Convective Stratiform Stratiform Stratiform Stratiform Total Total Total Total Figure 2: Time series and trend magnitudes obtained by the linear regression for convective, stratiform, and total precipitation characteristics averaged over 11 stations in the Czech Republic. obtained by averaging data from (a) all stations and (b) and in Table 3 for the western and eastern parts of the Czech stations in the western and eastern parts of the Czech Republic. Time series of the spatially averaged characteristics Republic (Figure 1). Analogous division was applied by Kysely´ are plotted in Figure 2, and dependence of the trend mag- [3] who reported the cutoff between the western and eastern nitudes on altitude is depicted in Figure 3.All gfi ures and parts of the Czech Republic in trends of precipitation char- the description of results are based on the linear regression acteristics, which may be linked to meteorological factors, because results obtained by the parametric (least-squares namely,dieff rencesintherolesofAtlanticandMediterranean regression) and nonparametric (Sen’s estimator) trend esti- influences. Herein, the averages are calculated from scaled mation are similar (Table 2). Particularly, we did not nd fi a stations’ data in order to give the same weight to all stations general tendency of the parametric estimate to be greater (in (notwithstanding the observed precipitation amounts and absolute value) than the nonparametric estimate (cf. [28]). thenumberofwet days,which arelargerathigher-elevated stations). The characteristics at individual stations were rfi st 4.1. Convective Precipitation. Trends of spatially averaged divided by their mean values over the studied period and climatological characteristics of convective precipitation (the then these scaled (dimensionless) data were averaged over the total amount and the number of wet days) are increasing and stations. statistically signicfi ant in all seasons except winter (when the The trends in spatially averaged characteristics and their proportion of convective precipitation is very low; Table 2 statistical significance are shown in Table 2 for all stations and Figure 2). The increasing trends are higher in the western Winter Autumn Summer Spring Dimensionless precipitation Dimensionless precipitation Dimensionless precipitation Dimensionless precipitation characteristic characteristic characteristic characteristic Dimensionless precipitation Dimensionless precipitation Dimensionless precipitation Dimensionless precipitation characteristic characteristic characteristic characteristic Dimensionless precipitation Dimensionless precipitation Dimensionless precipitation Dimensionless precipitation characteristic characteristic characteristic characteristic Dimensionless precipitation Dimensionless precipitation Dimensionless precipitation Dimensionless precipitation characteristic characteristic characteristic characteristic 6 Advances in Meteorology Amount Days R6h R1D 15 10 −10 −10 −20 5 −20 −30 −5 −30 −40 −10 −40 −10 200 400 600 800 1000 1200 200 400 600 800 1000 1200 200 400 600 800 1000 1200 200 400 600 800 1000 1200 Altitude (m) Altitude (m) Altitude (m) Altitude (m) 10 15 10 10 0 −5 −5 −5 −10 −10 −5 −10 −15 200 400 600 800 1000 1200 200 400 600 800 1000 1200 200 400 600 800 1000 1200 200 400 600 800 1000 1200 Altitude (m) Altitude (m) Altitude (m) Altitude (m) 20 20 −10 −10 −20 −10 −20 200 400 600 800 1000 1200 200 400 600 800 1000 1200 200 400 600 800 1000 1200 200 400 600 800 1000 1200 Altitude (m) Altitude (m) Altitude (m) Altitude (m) 40 40 40 30 −10 −20 −20 −20 −20 −40 −40 −30 200 400 600 800 1000 1200 200 400 600 800 1000 1200 200 400 600 800 1000 1200 200 400 600 800 1000 1200 Altitude (m) Altitude (m) Altitude (m) Altitude (m) Convective Convective Convective Convective Stratiform Stratiform Stratiform Stratiform Total Total Total Total Figure 3: Dependence between trend magnitudes and altitude for characteristics of convective, stratiform, and total precipitation. Trends estimated by the linear regression and their 95% confidence bounds are plotted. than eastern part of the Czech Republic in all seasons (Table 3, spatially averaged indices, increasing trends prevail as well. Figure 4). Spatially averaged extreme precipitation indices The largest and statistically significant trends are found in of convective precipitation (seasonal maxima of 6-hour and autumn, particularly for extremes. The tendency to increases 1-day precipitation, R6 h, and R1D) increase in all seasons is more pronounced in the eastern part of the Czech Republic except spring but the trends are smaller and insignificant. in all seasons except for summer (Table 3,Figures 4 and 5). The trends of extreme precipitation tend to have opposite eTh trends of stratiform precipitation tend to be of opposite signs in autumn and winter in the western (positive) and signs in the western (negative) and eastern (positive) part eastern (negative) part of the country (Table 3, Figure 5). of the country in winter and spring, which leads to very The climatological characteristics of convective precipitation small trends for the country as a whole. By contrast to increase faster in lowlands than in highlands in all seasons convective precipitation, stratiform precipitation has usually while for extremes such pattern is found only in summer and more pronounced positive trends in highlands (Figure 3). winter (Figure 3). Differences between lowlands and highlands are larger in spring and summer. 4.2. Stratiform Precipitation. The trends in characteristics of stratiform precipitation are usually smaller compared 4.3. Total Precipitation. Increasing trends of total precipita- to those of convective precipitation (Table 2, Figure 2). For tion prevail in all seasons except winter (Table 2,Figures 2, Winter Autumn Summer Spring Magnitude of trend (%/10 yrs) Magnitude of trend (%/10 yrs) Magnitude of trend (%/10 yrs) Magnitude of trend (%/10 yrs) Magnitude of trend (%/10 yrs) Magnitude of trend (%/10 yrs) Magnitude of trend (%/10 yrs) Magnitude of trend (%/10 yrs) Magnitude of trend (%/10 yrs) Magnitude of trend (%/10 yrs) Magnitude of trend (%/10 yrs) Magnitude of trend (%/10 yrs) Magnitude of trend (%/10 yrs) Magnitude of trend (%/10 yrs) Magnitude of trend (%/10 yrs) Magnitude of trend (%/10 yrs) Advances in Meteorology 7 Spring Summer Autumn Winter Trend (%/10 yrs) <−10 0 >10 −10–−6 0–3 p = 0.2 −6–−3 3–6 p = 0.1 −3–0 6–10 Figure 4: Trends in seasonal amounts of convective, stratiform, and total precipitation computed by the linear regression. Trend magnitudes are expressed as relative changes of the examined characteristics in %/10 years over 1982–2010. 4,and 5). The largest and statistically significant trends are autumn), convective precipitation increases (in averaged found in autumn, which corresponds with increasing trends precipitation characteristics from all stations) more than of both convective and stratiform precipitation. eTh trends stratiform for seasonal precipitation amounts as well as the of total precipitation are by far weakest in winter, when also number of wet days. Our results contrast with those reported trends of convective and stratiform precipitation are rarely by Ruiz-Leo et al. [18], who found steeper (positive) trends significant. In spring and summer, some characteristics of for stratiform than convective precipitation in the eastern convective precipitation increase while of stratiform precipi- Spanishcoast.They,however,had examinednot only a tation decrease and vice versa. es Th e counterbalancing trends different area but also a much shorter time period (1998– of convective and stratiform precipitation lead to relatively 2008) and used a different algorithm for disaggregating small trends of total precipitation. The trend magnitudes precipitation, as reported above. Our algorithm is based on of total precipitation depend on altitude similarly as those different criteria, allowing also for disaggregation of heavy of stratiform precipitation in all seasons except summer precipitation into predominantly convective and stratiform (Figure 3), when theroleofconvectiveprecipitationis largest. [19], while Ruiz-Leo et al. [18] considered heavy precipitation eTh ratio between convective and stratiform precipitation to be of convective origin only. eTh ir approach was reasonable increases in all seasons, especially in summer (Figure 6). It for the specific study area (north-eastern coast of Spain) but is particularly noteworthy that the four highest values over it is not generally applicable in other regions. 1982–2010occurredinthe last 8years,and thedominance Mean convective precipitation increases significantly in of convective precipitation was greatest in the 2003 spring all seasons except winter while heavy precipitation decreases and summer that were characterized by severe heat waves in spring or has small insignificant trends in summer and in Europe and large precipitation deficits (e.g., [ 29–32]). Our autumn. Our results are in agreement with [33, 34], where results show that the deficits over central Europe were mainly climatological characteristics and trends of thunderstorms duetothe lack of stratiform precipitation(cf.also Figure 2). over Poland were studied and increasing trends of days with lightthunderstormatthe endofthe 20th century while decreasing or no clear trends of days with heavy 5. Discussion thunderstorm were reported. There is an ongoing discussion concerning possible In all seasons in which convective precipitation represents changes in precipitation rates and relative contributions an important part of total amounts (spring, summer, and Total Stratiform Convective 8 Advances in Meteorology Spring Summer Autumn Winter Trend (%/10 yrs) <−10 0 >10 −10–−6 0–3 p = 0.2 −6–−3 3–6 p = 0.1 −3–0 6–10 Figure 5: Same as in Figure 4 but for maximum seasonal 1-day precipitation amount (R1D). of convective and stratiform precipitation with increasing continental influence) parts of the Czech Republic. A ten- surface temperatures (e.g., [35, 36]). Increasing proportion dency to more pronounced trends in convective (stratiform) of convective precipitation, found in all seasons, corresponds precipitation in the west (east) may be related to changes with increasing trends of surface air temperature [19]. This of large-scale circulation influencing differently precipitation may suggest that the changing ratio of convective and over these two regions of central Europe; however, the stratiform precipitation is related to climate change and may links between large-scale circulation and precipitation are continue (with increasing temperature) in future. However, weakest in the convective season (cf. [38]). Increasing trends our results show that this does not necessarily mean more of stratiform precipitationinautumninthe easternpart heavy convective precipitation, because intensity of precipi- of the country may be due to enhanced occurrence of tation depends on a number of factors such as atmospheric cyclones of the Mediterranean origin (typically associated humidity andstability,CAPE, andwindshear (e.g., [37]). with widespread and heavy stratiform rainfall). Detailed eTh trends of total precipitation are predominantly study of the links between precipitation changes and the increasing in all seasons except winter (and 6-hour maxima large-scale circulation deserves further investigation. in spring). The overall tendency to prevailing positive trends Similar analyses for other parts of Europe are needed in agrees with Kysely[ ´ 3] who examined trends in characteristics order to reveal whether the reported differences (in trends of of mean and heavy (total) precipitation in the Czech Repub- convective/stratiform precipitation and mean/extreme char- licover1961–2005 andreportedpredominantly increasing acteristics) and the cutoff between the western and eastern trends in all seasons except spring. eTh differences are related parts of the examined area are related to larger-scale patterns to different studied periods, different sets of stations, and the over Europe. Such studies should be straightforward because fact that trend estimates may be strongly influenced by values the necessary data (SYNOP reports) are available, and the at the beginning and the end of time series. However, our proposed algorithm [19] is universal and does not involve any results also show that the overall tendency to rising trends “local” settings. in precipitation characteristics does not depend substantially on the time window. 6. Conclusions A distinct differentiation in the predominant trend directions of convective, stratiform, and total precipitation Using the recently proposed algorithm for disaggregating emerges when comparing the western (with stronger Atlantic precipitation into predominantly convective and stratiform influence) and the eastern (with stronger Mediterranean and [19], we analysed trends in characteristics of convective and Total Stratiform Convective Advances in Meteorology 9 Spring Summer 1.5 1.0 0.5 0.0 1985 1990 1995 2000 2005 2010 1985 1990 1995 2000 2005 2010 Year Year Autumn Winter 0.20 0.6 0.15 0.4 0.10 0.2 0.05 0.0 0.00 1985 1990 1995 2000 2005 2010 1985 1990 1995 2000 2005 2010 Year Year Figure 6: Ratio of convective and stratiform precipitation (averages over 11 stations in the Czech Republic) and trend estimated by the linear regression. stratiform precipitation and their influence on trends of total are significant in autumn, especially for extremes, precipitation at weather stations in the Czech Republic over and larger in the eastern part of the country where 1982–2010. eTh trendanalysiswas basedonthe least-squares Mediterranean cyclones play more important role. regression and the Sen’s estimator of slope but the results (iii) The trends in convective precipitation tend to be more depend little on the method used. pronounced at lowland than higher-elevated stations The main findings are as follows. while an opposite pattern prevails for stratiform precipitation. This indicates that the increases in con- (i) Spatially averaged trends in convective precipitation are increasing and statistically significant for precip- vective precipitation are not related to orographically triggered convection. The largest differences in trend itation amounts and the number of wet days in all magnitudes of convective and stratiform precipitation seasons except for winter. eTh trends of extreme con- vective precipitation (seasonal maxima) are spatially between lowlands and highlands occur in spring and summer. much more variable and insignicfi ant, but increases tend to prevail as well. The trends in convective (iv) In spring and summer, when convective precipitation precipitation are larger in the western part of the represents an important fraction of the total amounts country where Atlantic influences are stronger. in central Europe (around 30% and 50%, resp., when (ii) For characteristics of stratiform precipitation, the averaged over the stations under study), the observed trends are usually smaller compared to those of con- increases in total precipitation are mainly due to vective precipitation, but increases prevail too. They increases in convective precipitation. 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