Czech Hydrometeorological Institute Research Articles

Data driven modelling of vertical atmospheric radiation

In the Czech Hydrometeorological Institute (CHMI) there exists a unique set of meteorological measurements consisting of the values of vertical atmospheric levels of beta and gamma radiation. In this paper a stochastic data-driven model based on nonlinear regression and on nonhomogeneous Poisson process is suggested. In the first part of the paper, growth curves were used to establish an appropriate nonlinear regression model. For comparison we considered a nonhomogeneous Poisson process with its intensity based on growth curves. In the second part both approaches were applied to the real data and compared. Computational aspects are briefly discussed as well. The primary goal of this paper is to present an improved understanding of the distribution of environmental radiation as obtained from the measurements of the vertical radioactivity profiles by the radioactivity sonde system.

Nowcasting of precipitation – Advective statistical forecast model (SAM) for the Czech Republic

This article describes a model SAM for nowcasting precipitation in the Czech Republic. The model is based on an advective-statistical algorithm and utilises radar, satellite, lightning and numerical weather prediction (NWP) model prognostic data. The statistical part of the model is complemented by a distribution correction of forecasted values. The model provides forecasts for mean 1-h, 2-h and 3-h precipitation totals in 9 km by 9 km grid cells. The formulation of the forecast serves the needs of operational hydrologic prediction by the Czech Hydrometeorological Institute (CHMI). The accuracy of the forecasts is evaluated with independent data by the root-mean-square error, absolute error, bias, and the critical success index (CSI) categorical skill score after transforming the quantitative forecasts into categorical forecasts. Results are also compared with the existing operational forecasts by the COTREC model calculated at the CHMI. The results of this study confirmed that the most important predictors are derived from radar data and that, in addition to rain rates, the predictors include information about the top of the radar echo. For the 2-h and 3-h precipitation totals, satellite and NWP model predictors were selected, whereas predictors derived from lightning data were not selected. Evaluation of the forecasts showed that the SAM model yielded more accurate predictions than the COTREC model for almost all forecast accuracy statistics considered. The SAM model does not change the horizontal structure of the COTREC forecasts, because both models use almost identical advection fields. However, the SAM is able to model precipitation development and, thus, improve the forecast accuracy.

Use of a soil moisture network for drought monitoring in the Czech Republic

Since 2000, the network of stations that make up the Czech Hydrometeorological Institute (CHMI) has measured the soil moisture content at the 0- to 0.9-m layer using sensors placed within the natural soil profile under closely cropped grass cover. Using information from 8 years of continuous observation at seven stations throughout the Czech Republic, we verified the usefulness of the Soil Moisture Index (SMI). The SMI is a potentially useful index for calculating the water deficit in the Czech Republic and Central Europe. During this period, a statistically significant decrease in moisture content was detected, and negative SMI values predominated. There were frequent occurrences of flash drought, defined as a very rapid decline in soil moisture during a 3-week period. The CHMI can use SMI values below −3 in the Integrated Warning Service System. The routine calculation of SMI values can alert agricultural producers to the development of flash drought conditions and provide them with information regarding the effectiveness of recent rainfall events. An increase in soil moisture, in contrast, could serve as a warning sign for hydrology because it creates the preconditions for flooding. The complex study of soil humidity regimes is becoming more significant in connection with current global climatic change warnings in hydrological cycles.

The Effects of Physical-Geographic Factors on Flood Episodes Extremity in the Vydra River Basin

The paper summarizes findings about the Vydra River basin (sw. Czechia) runoff regime including its sources with a special respect to observed flood situations formation and course. The main focus is concentrated on explanation of runoff dynamics relation to physical-geographic conditions of chosen subcatchments. In this term, special emphasis is adverted to peat land hydrological function assessment. Research is based on analyses of long-term time series of Czech Hydrometeorological Institute and of data acquired within more than three years field survey which is carried out in the study area by the Charles University in Prague, Faculty of Science, Department of Physical Geography and Geoecology.

Final report on the ongoing key comparison BIPM.QM-K1: Ozone at ambient level, comparison with CHMI, 2009

As part of the ongoing key comparison BIPM.QM-K1, a comparison has been performed between the ozone national standard of the Czech Hydrometeorological Institute (CHMI) and the common reference standard of the key comparison, maintained by the Bureau International des Poids et Mesures (BIPM). The instruments have been compared over a nominal ozone amount-of-substance fraction range of 0 nmol/mol to 500 nmol/mol.Main text.To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database kcdb.bipm.org/.The final report has been peer-reviewed and approved for publication by the CCQM, according to the provisions of the CIPM Mutual Recognition Arrangement (MRA).

The TICKPRO Computer Program for Predicting Ixodes ricinus Host-seeking Activity and the Warning System Published on Websites

The computer program with the acronym TICKPRO (tick prognosis) facilitates medium-range forecasts of the level of host-seeking activity in ticks within a 1-4 day horizon. The program is based on the medium-range weather forecast routinely produced at the Czech Hydrometeorological Institute (CHMI), as well as on previously developed mathematical models describing the correlation of meteorological factors with the host-seeking activity of Ixodes ricinus. These models are based on a 6-year whole-season monitoring of I. ricinus host-seeking activity on experimental fields in the Central Bohemia Region in a typical habitat, oakhornbeam forest, where tick-borne encephalitis (TBE) virus and Borrelia burgdorferi s.str., B. afzelii, and B. garinii have been found. Meteorological data provided by the CHMI meteorological station in Prague-Libus were used, and during the development of the forecasting algorithm micrometeorological data have been collected directly at the tick monitoring sites under selected synoptic weather situations. In the TICKPRO program, the two most successful models utilized ambient air temperature, quantity of atmospheric precipitation, and relative air humidity. The prediction determines 5 levels of risk of attack according to the current proportion of host-seeking ticks, and thus determines the risk of TBE infection. The levels of risk defined by the TICKPRO program are supplemented by instructions on how to prepare oneself for entering sites with potential tick occurrence, how to move around once there, and how to behave on returning home. This warning system is weekly published on websites of National Institute of Public Health and CHMI, Prague, over entire season (March-November).

Climatology of lightning in the Czech Republic

The Czech Hydrometeorological Institute (CHMI) has utilized lightning data from the Central European Lightning Detection Network (CELDN) since 1999. The CELDN primarily focuses on the detection of cloud-to-ground (CG) lightning but intra-cloud (IC) lightning detection is also available. Lightning detection is used by the CHMI forecasters as an additional source to radar and satellite data for nowcasting of severe storms. Lightning data are also quantitatively used in automatic nowcasting applications. The quality of lightning data can be evaluated using their climatological characteristics. Climatological characteristics are also useful for defining decision thresholds that are valuable for human forecasters as well as for automatic nowcasting applications. The seven-year period from 2002 to 2008, which had relatively even-quality lightning data, was used to calculate the spatial and temporal distributions of lightning. The monthly number of CG strokes varies depending on the season. The highest number of CG strokes occurs during summer, with more than 20 days of at least five detected CG strokes on the Czech Republic territory in June and July. The least number of CG stokes occurs in winter, with less than three days per month having at least five detected CG stokes. The mean diurnal distribution of CG strokes peaks between 1500 and 1600 UTC and reaches a minimum between 0500 and 0800 UTC. The average spatial distribution of CG strokes shows sharp local maxima corresponding with the locations of the TV broadcast towers. The average spatial distribution of CG flash density, calculated on a 20 × 20 km grid, shows the maximum (3.23 flashes km − 2 year − 1 ) in the western part of Czech Republic and the minimum (0.92 flashes km − 2 year − 1 ) in the south-southeast of the Czech Republic. In addition, lightning characteristics related to the identified convective cells, such as distribution of the lightning stroke rates or relation to the radar derived by Vertically Integrated Liquid, are presented.

The real-time stochastic flow forecast

In the Czech Republic, deterministic flow forecasts with the lead time of 48 hours, calculated by rainfall-runoff models for basins of a size of several hundreds to thousands square kilometers, are nowadays a common part of the operational hydrological service. The Czech Hydrometeorological Institute (CHMI) issues daily the discharge forecast for more than one hundred river profiles. However, the causal rainfall is a random process more than a deterministic one, therefore the deterministic discharge forecast based on one precipitation prediction is a significant simplification of the reality. Since important decisions must be done during the floods, it is necessary to take into account the indeterminity of the input meteorological data and to express the uncertainty of the resulting discharge forecast. In the paper, a solution of this problem is proposed. The time series of the input precipitation prediction data have been generated repeatedly (by the Monte Carlo method) and, subsequently, the set of discharge forecasts based on the repeated hydrological model simulations has been obtained and statistically evaluated. The resulting output can be, for example, the range of predicted peak discharges, the peak discharge exceeding curve or the outflow volume exceeding curve. The properties of the proposed generator have been tested with acceptable results on several flood events which occurred over the last years in the upper part of the Dyje catchment (Podhradí closing profile). The rainfall-runoff model HYDROG, which has been in operation in CHMI since 2003, was used for hydrological simulation.

Model ALADIN as regional climate model for Central and Eastern Europe

Results obtained with two versions of the Limited Area Model (LAM) ALADIN over differently sized integration domains (large, intermediate and small) in the European area are presented in order to investigate both the general model performance and the influence of domain choice on the quality of obtained results. The aim is also to illustrate the issues related to the strategy of selection of the optimal integration domain. Each of these studies has been performed with two versions of the ALADIN model: the first one is ALADIN-CLIMATE developed at CNRM/Meteo-France, the second one is ALADIN-CLIMATE/CZ prepared at the Czech Hydrometeorological Institute (CHMI). This leaves us with total of six experiments forced by the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-40 reanalysis data. The west Balkan domain covering Bulgaria is used as an evaluation region for investigation of the temporal and spatial properties of simulated precipitation and temperature fields. This region has been selected for its challenging orography making the results obtained here a valuable source for studies leading to further developments in climate modeling. It was found that size of the domain strongly affects the quality of obtained results. We have found that the largest domain reproduces the spatial characteristics of climate (such as bias) very well, but its use results in a poor representation of temporal aspects, which are however captured very well in experiments over both smaller domains. Our findings suggest that there is no optimal choice of domain size, securing the best results for both spatial and temporal evaluation.

Determination of the natural background content of metals in ground waters of the Czech Republic

Knowledge of the natural background content of metals is important, but can be difficult to establish because the concentrations of substances dissolved in ground waters vary considerably with time and space. The main objective of the paper is to assess the natural background of five selected elements: As, Al, Cd, Pb and Hg. Each of these elements, with the exception of Al, is included in the Minimum list of pollutants and their indicators for which the EU Member States should establish threshold values (Daughter Groundwater Directive). The data of the Czech Hydrometeorological Institute which contains analyses obtained by regular monitoring of the quality of ground waters at intervals of 6 months has been used as the source information. This system incorporates ca. 450 monitoring sites which provide information about water in all the types of rocks penetrated by individual boreholes. Because of the low concentrations of certain elements (Hg, Pb and Cd in particular) a significant number of analytical results lie below the quantification limit of the analytical methods used. Therefore, conventional statistical methods for processing data were not applicable and alternative procedures were used. The Kaplan–Meier procedure was used within the NADA module for statistical analysis of data sets containing values below the quantification limit. The concentrations of monitored elements that can be considered natural background are suggested to be values of the third quartile, i.e. values that are less than or equal to 75% of analytical results in the assessed dataset. The remaining 25% of analytical results that exceed the proposed limit can be considered to be anomalies which may be natural or anthropogenic. Based on the statistical analysis of data specific values for the natural background content of elements in ground waters within particular types of lithology have been proposed. These can be considered the natural background values that apply within the whole of the territory of the Czech Republic.

Long-lasting changes in the species spectrum of cucurbit powdery mildew in the Czech Republic - influence of air temperature changes or random effect?

Two ectoparasite powdery mildew species <i>Golovinomyces cichoracearum</i> (<i>Gc</i>) and <i>Podosphaera xanthii</i> (<i>Px</i>) occurring on cucurbits differ, besides other characteristics, by specific ecologic requirements. While <i>Px</i> is common in subtropical and tropical areas and greenhouse crops, <i>Gc</i> occurs more frequently in temperate and cooler areas under field conditions. Their presence on cucurbit field crops (<i>Cucurbita pepo</i>, <i>C. maxima</i>, <i>Cucumis sativus</i>) was monitored in the Czechoslovakia (1979–1980) and in the Czech Republic (1995–2007). Their identification was carried out by microscopic observation of the morphological characteristics of the dry conidia on 1527 leaf samples. Data on air temperature in 1979–2007 were provided by the Czech Hydrometeorological Institute. In 1979–1980 <i>Gc</i> was identified in 86.0% of samples, <i>Px</i> in 14.0% samples, there was no mixed infection; prevalence of <i>Px</i> was recorded in South Slovakia and South Moravia, and on crops under cover. Since 1995 species <i>Px</i> was recorded each year on field crops in different locations of Bohemia and Moravia, usually in mixed infection with <i>Gc</i>. The average year temperature of 8.1°C for period 1992–2007 was higher than corresponding value of 7.4°C in 1979–1983. Similarly, average temperature in vegetation season of 16.2°C in 1992–2007 was higher than corresponding value of 15.7°C in 1979–1983. The higher air temperature can positively influence spreading of <i>Px</i> in the Czech Republic. Climate variability and effect of their changes are discussed in relationship to the geographic distribution and geographic patterns of cucurbit powdery mildews.

Time variations of rainfall erosivity factor in the Czech Republic

The ombrographic data have been selected from 24 meteorological stations of the Czech Hydro Meteorological Institute (CHMI), according to the terms of the Universal Soil Loss Equation for calculating the long term loss of soil through water erosion, erosion hazard rains and their occurrence, with their relative amounts and erosiveness, R-factors determined for each month. By comparing the value of the time division of the R-factor in the area of the Czech Republic and in the selected areas of the USA, it has been demonstrated that this division may be applied in the conditions of the Czech Republic.

MATHEMATICAL MODEL FOR PREDICTION OF ALPHA ACID CONTENTS FROM METEOROLOGICAL DATA FOR 'SAAZ' AROMA VARIETY

Significant influence of weather conditions on alpha acid contents in hop cones is generally accepted. Long-term monitoring of alpha acid content in hops cultivated in the region of central Europe shows notable year to year differences. Mathematical models of the relationship between alpha acid content and meteorological parameters were worked out for 'Saaz' aroma variety using data covering the years 1981-2006. Mean alpha acid content was determined by lead conductance method (EBC 7.4, toluol). Meteorological data were provided with CHMI (Czech Hydrometeorological Institute) observatory in Doksany located approximately 2 km from the farm. Using multi-linear regression, a ten parameter model has been outlined. Average temperatures from July and August, average air humidity from June, July and August, average daily sunshine duration from June, July and August and accumulated precipitation from August have been found as key input variables of the model. Correlation coefficient of the relationship between predicted and actual alpha acid contents is r=0.914, coefficient of determinancy r 2 =0.835. The model showes that alpha acid content in 'Saaz' aroma hops is influenced by weather conditions in a relatively short time period June-August, i.e. stage of flowering, cone forming and ripening. July temperatures are the most significant weather parameter (r i =-0,24) effecting alpha acid contents in 'Saaz' hops confirming empiric experience.

Evaluation of soil temperatures at agroclimatological station Pohořelice

Soil temperatures were analysed for the climatological station Pohořelice during the period of 1961–2000. According to the agroclimatic zoning, this region is a part of warm macroarea, mainly warm area, mainly dry subarea, and a district of mainly cold winter. The average annual air temperature is 9°C and the average year precipitation total is 475 mm. For the characterisation of the soil temperature were used the average monthly soil temperature determined from daily averages, maximal monthly soil temperature determined on the basis of daily maximums, and minimal monthly value determined on the basis of daily minimums. In the Czech Hydrometeorological Institute, the soil temperature was measured in the observation terms at 7:00, 14:00 and 21:00 local mean time. These temperature characteristics were assessed for the depths of 5, 10, 20, 50, and 100 cm. The longterm average annual temperature for the depths measured varies from 10.0°C (at 20 cm) to 10.4°C (at 100 cm). From the longterm viewpoint, the warmest month for the depths of 5, 10, and 20 cm is July, the coldest one is January, and for the depths of 50 and 100 cm the warmest month is August and the coldest one is February. For the classification of single months, the average monthly soil temperature for the respective month was compared with the longterm average soil temperature of 1961–2000. According to the average monthly soil temperature and its standard deviation, the months of the evaluated period were divided into seven categories: thermally normal months, warm months, very warm months, extraordinary warm months, cold months, very cold months, and extraordinary cold months.

141 EFFECT OF ENVIRONMENTAL TEMPERATURE ON EMBRYO PRODUCTION AND CONCEPTION RATES IN BEEF AND DAIRY CATTLE

The aim of this study was to evaluate the effect of environmental temperature at the time of embryo collection and transfer on embryo quality and conception rates after transfer of fresh and frozen embryos. Purebred dairy (Holstein, Czech spotted cattle, n = 174) and beef (Charolais, Blonde d’Aquitaine, Piedmontese, Hereford, Limousin and Simmental; n = 72) donors were collected during 2005 to 2007. Donor cows received one application of PGF2α and superstimulation was initiated 9 to 11 days following estrus with pFSH (Folltropin-V; Bioniche Animal Health, Belleville, ON, Canada) given twice daily for 4 days. Prostaglandin2α was given on Day 3 of the superstimulation treatment. Donors were inseminated 3 times, with 1 unit of semen on Days 5 and 6 of treatment. Embryo recovery was carried out on Day 7 after insemination. The recipients were synchronized with PGF2α and embryos were transferred on Day 7 after estrus. The effect of temperature at the time of 246 embryo recoveries and 1338 transfers (fresh and frozen embryos) was analyzed using the GLM, assuming quasi-poisson and quasi-binomial error distribution by R software (www.r-project.org). We evaluated the total number of ova/embryos collected, embryo quality, and conception rates after transfer at the environmental temperatures shown below. Temperatures were divided into the following ranges: A) from –5 to 5°C; B) from 6 to 15°C; C) from 16 to 20°C; and D) over 20°C. The average temperature values were obtained from the Czech hydrometeorological institute and corresponded to the following seasons: winter (range A and B); spring (range B and C); summer (range C and D); fall (range C and B). Dairy cows were managed intensively in barns whereas beef cows were managed in barns during the winter and on pasture from April until October. In beef donors the mean number of total ova/embryos collected and transferable embryos were 9.1 ± 7.9 and 4.2 ± 4.5, respectively and no significant effect of temperature was detected (P > 0.05). In dairy donors the mean number of total ova/embryos collected and transferable embryos were 7.9 ± 6.0 and 4.9 ± 4.5, respectively and no significant effect of temperature was detected (P = 0.27). Conception rate was greatest (P < 0.001) in temperature range D (63.64%) compared with the other temperature ranges (A = 27.66%; B = 43.65%; C = 43.21%;) in beef cows and in the range C (65.31%) than in the other temperature ranges (A = 34.7%; B = 52.67%; D = 56.25%) in dairy cows. It was concluded that temperature at the time of embryo collection did not affect embryo production and quality. However, environmental temperature did have a significant effect on conception rates in both beef and dairy recipients. Nutritional status may also have contributed to the increased conception in beef cattle during warmer temperatures. However, the optimal period for conception in dairy cows was in temperature range from 16 to 20°C, because of the potential adverse effect of heat stress in high-yielding cows. Supported by MEYS CR MSM 2678846201, LA 330; NAZV 1B44034.

Correlation between meteorological factors and tick-borne encephalitis incidence in the Czech Republic

The objective was to discover whether there any demonstrable relationships exist between the incidence of human tick-borne encephalitis (TBE) cases and current meteorological factors and to specify their character. Epidemiological data were extracted from the EPIDAT database (National Institute of Public Health, Prague). Analyzed were a total of 4,613 TBE cases registered in the whole Czech Republic (1994-2001) and 4,637 cases registered in the territory of Bohemia (1994-2004). Meteorological data were from the database of the Czech Hydrometeorological Institute in Prague. A linear relationship has been found between TBE incidence and temperature factors in all the years under study. Lagged cross correlation was used (with the lags in time respective to incubation period from infected tick attack to initial TBE symptoms) and close relations were found for daily mean air temperature and lags 6-14 days (with a peak of 9 days). Effects of the current course of the meteorological situation (as well as long-term year-to-year changes) on TBE incidence are, foremost, mediated by the influence of climatic factors on Ixodes ricinus ticks and their host-seeking activity; under certain conditions, also by the effects of momentary weather on human behavior as TBE in the Czech Republic is a recreational disease connected with outdoor activities.

Variability of droughts in the Czech Republic, 1881–2006

We analyze droughts in the Czech Republic from 1881–2006 based on the Palmer drought severity index (PDSI) and the Z-index using averaged national temperature and precipitation series for the calculations. The standardized precipitation index (SPI), PDSI and Z-index series show an increasing tendency towards longer and more intensive dry episodes in which, for example, droughts that occurred in the mid-1930s, late 1940s–early 1950s, late 1980s–early 1990s and early 2000s were the most severe. Cycles at periods of 3.4–3.5, 4.2–4.3, 5.0–5.1 and 15.4 years exceeded 95% confidence levels in application of maximum entropy spectral analysis. These are expressed at different intensities throughout the period studied. The occurrence of extremely dry and severely dry months is associated with a higher frequency of anticyclonic situations according to the classification employed by the Czech Hydrometeorological Institute. Principal component analysis documents the importance of the ridge from the Siberian High over Central Europe when extreme and severe droughts in months of the winter half-year are considered in terms of sea-level pressure. In the summer half-year, the ridge of the Azores High over Central Europe is the most important. Drought episodes have a profound effect on national and regional agricultural production, with yields being consistently lower than in normal years, as is documented through the example of spring barley, winter wheat, forage crops on arable land, and hay from meadows. Seasons with pronounced drought during the April–June period (e.g., 1947 and 2000) show the most significant yield decreases. Forests appear to be very vulnerable to long-term drought episodes, as it was the case during the dry years of 1992–1994. This study clearly confirms the statistically significant tendency to more intensive dry episodes in the region, driven by temperature increase and precipitation decrease, which has already been suggested in other studies.

Quantitative precipitation forecast using radar echo extrapolation

The radar extrapolation method called COTREC (“Continuity of TREC vectors”, where TREC stands for “Tracking Radar Echoes by Correlation”) was originally developed in the Czech Hydrometeorological Institute for qualitative precipitation and severe storm nowcasting. New demands for better precipitation forecasts from the hydrological modeling community have led us to test quantitative precipitation forecasts (QPF) based on the COTREC method. Several case studies of flood events showed the potential benefit of COTREC-based QPF for hydrological modeling. Case study results were subsequently confirmed by statistical evaluation of the QPFs and a comparison with precipitation forecasts from the ALADIN numerical weather prediction model.

CELLTRACK — Convective cell tracking algorithm and its use for deriving life cycle characteristics

The CELLTRACK algorithm was developed in the Czech Hydrometeorological Institute (CHMI) as a complementary radar-based nowcasting tool to the COTREC algorithm for convective situations. This article contains a description of the identification, tracking and extrapolation techniques used in CELLTRACK. Also discussed is an evaluation of CELLTRACK tracking performance and a comparison of its forecast skill with the COTREC algorithm. CELLTRACK gives a performance similar to COTREC for approximately the first 30 min, however it can catch the movement of a convective storm deviating from the movement of surrounding convective storms. CELLTRACK is used operationally in the CHMI and is available to forecasters via the JSMeteoView visualisation application. It has also been used for creating a 2002–2006 statistic of radar and satellite characteristics of convective cells over the area of the Czech Republic. There are obvious dependencies of mean convective cell characteristics as maximum reflectivity level or convective cell area on convective storm lifetime and zero isotherm level.

The influence of meteorological conditions of the preceding winter on the incidences of tick-borne encephalitis and Lyme borreliosis in the Czech Republic

Data on tick-borne encephalitis (TBE: 1995–2004, 4122 cases) and Lyme borreliosis (LB: 1999–2004, 7391 cases) occurring in the Czech Republic in the territory of Bohemia were extracted from the database EPIDAT (National Institute of Public Health, Prague). The relationship of the incidence of these diseases to meteorological characteristics of the preceding winter was examined. Included were data from 22 meteorological stations distributed over the territory of Bohemia in areas of high TBE and LB incidence (from the database of the Czech Hydrometeorological Institute, Prague). Nineteen factors characterizing the severity of winter as a whole were examined. The closest correlation (statistically not significant) was between the incidence of TBE and the frost index, followed by the minimum winter temperature during the preceding winter season. Several other comparisons revealed similar correlation coefficients slightly below the limit of significance, nevertheless, even they also support the finding that the severity of winter influences TBE incidence in the following season. The occurrence of LB correlated in similar, not fully significant manner. The most distinct results were achieved with the number of days of thaw and the number of ice days. For both diseases, the meteorological parameters indicating the severity of winter are inversely proportional.