A study of the vertical distribution of the common tick Ixodes ricinus and tick-borne pathogens -tick-borne encephalitis virus (TBEV) and genospecies of Borrelia burgdorferi s.l. -was performed in the highest part of the Jeseníky mountain area (the Hrubý Jeseník Mts. with the highest summit Praděd, 1,491 m above see level). Altogether 1,253 specimens of all tick stages (607 larvae, 614 nymphs, 8 females and 24 males) were collected at the altitude 990-1,300 m above sea level on 12 collection sites by the flagging method. Altogether 1,207 ticks (8 females, 24 males, 568 nymphs and 607 larvae) were examined for the presence of tick-borne encephalitis virus and B. burgdorferi s.l. None of the samples contained TBEV, 35 samples (6% of adult ticks, 5% of nymphs, 0.7% of larvae) were positive for B. burgdorferi s.l. The most prevalent genospecies were B. afzelii (44%), B. garinii (28%), less frequent were B. burgdorferi sensu stricto (5%), B. valaisiana (3%). The rather large number of ticks (in absolute numbers as well as recounted to the index: average number of nymphs/worker/collection hour) and the presence of all developmental stages clearly demonstrate that there are viable local tick populations in all the sites, and that recorded ticks were not randomly individuals brought into higher altitudes by birds or game animals. The results are compared with the long-term (2002)(2003)(2004)(2005)(2006)(2007) monitoring of the tick altitudinal distribution in the Krkonoše Mts. and the conditions, which allow ticks to establish local populations up to the timberline in both mountain areas, are discussed. Simultaneously, changes in climatic conditions (especially the air temperature) monitored at 3 meteorological stations in the area of the Jeseníky Mts. were compared with the records from another 8 stations in other mountain areas in the Czech Republic. A very similar statistically significant trend of increasing mean air temperatures during the last three decades is found at all analyzed stations. The trend is most pronounced in the spring and summer months with the highest activity of I. ricinus ticks.

The steep rise in the incidence of tick-borne encephalitis (TBE) in the 1990s and its subsequent high level in the Czech Republic are not even over the whole territory. It is manifested markedly in the Czech-Moravian Highland region. In the decades of 1971 through 1992, TBE incidence in the Highland Region did not reach the countrywide average. The rise has been noted only since 1997; in the year 2006 TBE incidence in that administrative region was more than double the countrywide average. Analysis of the situation have not found any socioeconomic shifts or land-use changes, or in the numbers of game animals, that could have had an effect on TBE incidence. The rise of infections in localities 500 m above sea level (a.s.l.) and more was markedly steeper than that below that altitudinal limit. At those altitudes there has been found an increase in average monthly temperatures exceeding countrywide averages namely in the period of maximum Ixodes ricinus activity (May-August). Detailed analysis of meteorological conditions and comparison with a long-term study of the influence of modifications of the mountain climate in the Krkonoše Mts. on I. ricinus tick distribution and the pathogens transmitted by them, have led to the conclusion that likewise in the Czech-Moravian Highland a marked warming had influenced the local population of the vector I. ricinus, caused an activation of foci of TBE, increased contacts of humans with the vector, consequently giving rise to an apparent increase in the incidence of human cases of TBE.

This paper analyses winter severity and snow conditions in the Karkonosze Mountains and Jizera Mountains and examines their long-term trends. The analysis used modified comprehensive winter snowiness (WSW) and winter severity (WOW) indices as defined by Paczos (1982). An attempt was also made to determine the relationship between the WSW and WOW indices. Measurement data were obtained from eight stations operated by the Institute of Meteorology and Water Management -National Research Institute (IMGW-PIB), from eight stations operated by the Czech Hydrological and Meteorological Institute (CHMI) and also from the Meteorological Observatory of the University of Wrocław (UWr) on Mount Szrenica. Essentially, the study covered the period from 1961 to 2015. In some cases, however, the period analysed was shorter due to the limited availability of data, which was conditioned, inter alia, by the period of operation of the station in question, and its type.Viewed on a macroscale, snow conditions in the Karkonosze Mountains and Jizera Mountains (in similar altitude zones) are clearly more favourable on southern slopes than on northern ones. In the study area, negative trends have been observed with respect to both the WSW and WOW indices-winters have become less snowy and warmer. The correlation between the WOW and WSW indices is positive. At stations with northern macroexposure, WOW and WSW show greater correlation than at ones with southern macroexposure. This relationship is the weakest for stations that are situated in the upper ranges (Mount Śnieżka and Mount Szrenica).

Several linear and non-linear statistical downscaling methods are compared for winter daily temperature at eight European stations. The linear methods include linear regression of gridpoint values (pointwise regression) and of predictors' principal components (PC regression). The non-linear methods are represented by artificial neural networks. The non-linearity is also achieved by a stratification of data by classification of circulation patterns and a linear regression conducted separately within each class. As predictors, gridded 500 hPa heights and 850 hPa temperature are used. The verification is conducted in the cross-validation framework. The downscaling methods are evaluated according to four criteria: (1) fit to observations (quantified by the correlation coefficient), (2) shape of the statistical distribution, namely its skewness and kurtosis, (3) temporal autocorrelations with 1 day lag, and (4) interstation correlations. Considering all the criteria together, the pointwise linear regression appears to be the best method. It achieves the best fit with the observations and possesses the best temporal structure. The deviations of statistical distributions from normality are only captured by the neural networks, while the classification methods yield the best spatial correlations.

This paper presents the results of the analysis of the Western Sudetes' snow cover temporal and spatial changes, as well as it demonstrates the research on the long-term trends in the changes of snow cover durability. In order to conduct the study, the coefficient of snow cover durability (V) was used, which was defined as the quotient of the actual and the potential time of snow cover duration and expressed in percentage (1-100%). Moreover, the frequency of total disappearance of snow cover was established for the optimal winter season (December-March). Measurement data were obtained from 17 stations in the 1961-2015 period. The snow cover on the Western Sudetes' slopes with southern (S) macro-exposure lasts longer (has greater durability) than on the slopes in analogous altitude zones with northern (N) macro-exposure. At the altitudinal level of 600-700 m a.s.l., where the differences are the biggest, the average V values range from 60% at stations N to 75% in stations S. In the analysed area, excluding the upper ranges, slight negative trends in V changes have been noted. Snow cover persists for a shorter and shorter time. For the substantial majority of the stations, the trends in these changes are not statistically significant at the 0.05 level of statistical significance. They refer to the tendencies in other mountainous regions in Poland and Europe. Analogously, the stations with S macro-exposure, located at similar altitudes as stations with N macro-exposure, are characterised by two to three times lesser frequency of total disappearance of snow cover. Coefficient V is negatively correlated with the total disappearance of snow cover. At the stations with S macroexposure in the Western Sudetes, these correlations are usually strong or very strong, whereas at the stations with N macro-exposure, at similar altitudes, they are usually moderate or very weak.

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This article discusses the reasons for shortening snow cover duration in the Western Sudetes, considering local changes in: air temperature; amount and type of precipitation; sunshine duration and atmospheric circulation leading to changes in the number of days with snow cover and its depth; and its start and end dates. All factors were linked to the exposure and relief of the study area. The analysis was made for the winter seasons (Nov–Apr) 1961/1962–2020/2021. It was found that the primary reasons for the shortening of snow cover duration in the Western Sudetes are: a multi‐year increase in air temperature and sunshine duration; changes in precipitation patterns—a decrease in the proportion of solid precipitation, changes in atmospheric circulation—including an increase in anticyclonic circulation types with sunny weather, especially in April (snow cover disappears in most of the elevation profile of the Sudetes); and less cyclonic weather types. The above factors synergistically affect the lower snow depth, and fewer days with solid precipitation, which promotes its faster spring ablation. In the subsequent 30 years (climatological norms), there is a successive shortening in its duration. On the snow cover start dates, there are no clear trends in the direction and rate of change. On end dates, negative trends are observed, in most cases statistically significant. The rate of change for the end dates of snow cover is about twice as high as the start dates. The rate of decline in snow cover is higher at stations at similar altitudes with northern macro‐exposure than southern. The results correspond with other studies from Europe and the world on the earlier disappearance of snow cover. They confirm the successive global warming and shortening snow cover duration, especially evident in the last few decades.

<p>Long range forecasts provide information about expected future atmospheric and oceanic conditions averaged over periods of one to three months and are attractive for many sectors. They have made considerable progress in recent years, but seasonal predictability remains a problem in many regions (for example in Europe). Demand is also for long range forecasts, which would predict shorter periods than months (for example 3 decades in each month).</p><p>This study considers four seasonal forecasting systems available in the Copernicus Climate Change Service (C3S) archive which provide near-surface air temperature and precipitation data at 1°by 1°spatial resolution: European Centre for Medium-range Weather Forecast System SEAS5 (ECMWF), Météo – France System 8 (MF), Deutscher Wetterdienst GCFS 2.1 (DWD) and Centro Euro-Mediterraneo sui Cambiamenti Climatici SPSv3.5 (CMCC). It quantifies their value in predicting temperature and precipitation at monthly and shorter (3 decades in each month) temporal resolution over Europe. There are two starting dates, May 1st, and November 1st, and forecasts at lead times up to 3 months for each year in the period 1993–2016 (the longest period of hindcasts common to all systems).</p><p>We focus on 2 domains: larger (Europe, latitude 42-55°N, longitude 2-30°E) and smaller (the Czech Republic, latitude 47-52°N, longitude 11-20°E). E-OBS daily gridded observational datasets for precipitation and temperature at 0.25°spatial resolution are used as a reference.</p><p>Several statistical measures such as mean bias and root mean square error are presented for temperature and precipitation at a monthly and shorter (3 decades in each month) temporal resolution over Europe and for the Czech Republic.</p>