Abstract:This paper describes the HISTALP database, consisting of monthly homogenised records of temperature, pressure, precipitation, sunshine and cloudiness for the 'Greater Alpine Region' (GAR,(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(43)(44)(45)(46)(47)(48)(49). The longest temperature and air pressure series extend back to 1760, precipitation to 1800, cloudiness to the 1840s and sunshine to the 1880s. A systematic QC procedure has been applied to the series and a high number of inhomogeneities (more than 2500) and outliers (more than 5000) have been detected and removed. The 557 HISTALP series are kept in different data modes: original and homogenised, gap-filled and outlier corrected station mode series, grid-1 series (anomaly fields at 1°× 1°, lat × long) and Coarse Resolution Subregional (CRS) mean series according to an EOF-based regionalisation. The leading climate variability features within the GAR are discussed through selected examples and a concluding linear trend analysis for 100, 50 and 25-year subperiods for the four horizontal and two altitudinal CRSs. Among the key findings of the trend analysis is the parallel centennial decrease/increase of both temperature and air pressure in the 19th/20th century. The 20th century increase (+1.2°C/+1.1 hPa for annual GAR-means) evolved stepwise with a first peak near 1950 and the second increase (1.3°C/0.6hPa per 25 years) starting in the 1970s. Centennial and decadal scale temperature trends were identical for all subregions. Air pressure, sunshine and cloudiness show significant differences between low versus high elevations. A long-term increase of the high-elevation series relative to the low-elevation series is given for sunshine and air pressure. Of special interest is the exceptional high correlation near 0.9 between the series on mean temperature and air pressure difference (high-minus low-elevation). This, further developed via some atmospheric statics and thermodynamics, allows the creation of 'barometric temperature series' without use of the measures of temperature. They support the measured temperature trends in the region. Precipitation shows the most significant regional and seasonal differences with, e.g., remarkable opposite 20th century evolution for NW (9% increase) versus SE (9% decrease). Other long-and short-term features are discussed and indicate the promising potential of the new database for further analyses and applications.

Abstract:The processing of ombrographic data from 29 meteorological stations of the Czech Hydrometeorological Institute (CHMI), according to the terms of the Universal Soil Loss Equation for calculating long term loss of soil through water erosion, erosion hazard rains and their occurrence have been selected, with their relative amount and erosiveness -R-Factors determined for each month and years. By comparing the value of the time division of the R-Factor in the area of the Czech Republic and in selected areas of the USA it has been demonstrated that this division may be applied in the conditions of the Czech Republic. For the Czech Republic it is recommended to use the average value R = 40 based on the original evaluation.

Abstract:The rain erosivity R-factor is one of the main parameters in the Universal Soil Loss Equation (USLE). This paper describes the procedure used to update, differentiate and regionalize the rainfall erosivity R-factor. For the Czech Republic it is recommended to use the average value R = 40.

Some methodological aspects are discussed of the investigation of acute infarct myocarditis (AIM) in relation to weather fronts. Results of a new method of analysis are given. Data were analysed from about the hour of the onset of symptoms, and led to the diagnosis of AIM either immediately or within a few hours or days (3019 cases observed over 4.5 years during 1982-1986 in Plzen, Czechoslovakia). Weather classification was based on three factors (the type of the foregoing front, the type of the subsequent front, the time section of the time interval demarcated by the passage of the surfaces of the fronts). AIM occurrence increased in particular types of weather fronts: (i) by 30% during 7-12 h after a warm front, if the time span between fronts exceeded 24 h; (ii) by 10% in time at least 36 h distant from the foregoing cold or occlusion front and from the succeeding warm or occlusion front; (iii) by 20% during 0-2 h before the passage of the front, provided the foregoing front was not warm and the interval between fronts exceeded 5 h. AIM occurrence decreased by 15%-20% for time span between fronts greater than 24 h at times 6-11, 6-23 and 6-35 h before a coming warm or occlusion front (for interfrontal intervals 25-48, 49-72 and possibly greater than 72 h), and also at 12-23 and possibly 12-35 h before a cold front (for intervals 49-72 and possibly greater than 72 h), if the foregoing front was cold or an occlusion front.

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