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The mean duration of snow coverage in the West Siberian Plain is approximately eight months in the north to about five months in the south. While the period of intense snow melting is short (one or two months between March and May), snow accumulation persists for most of the cold season. Snow accumulation is associated with negative anomalies of sea level pressure, which means increased cyclonal activity and weaker than normal Siberian High. Much lower anomalies of sea level pressure occur during snow ablation. This suggests smaller influence of air circulation on snow cover reduction in spring.

The aim of the paper was to assess the robustness of four bias correction techniques: simple bias correction, distribution based bias correction, delta change and distribution based delta change. Data from nine RCM simulations of CORDEX project and 41 Polish weather stations were used. The methods were calibrated in the period 1971–1985 and evaluated in 1991–2005. The improvement in mean, 10th and 90th percentiles was shown, without significant differences among methods. For 1st and 99th percentiles the improvement was generally weaker and simple methods seem to be more robust than the distribution based ones. Strong differences between individual models were found, so the use of model ensemble is recommended.

A simple statistical model of daily precipitation based on the gamma distribution is applied to summer (JJA in Northern Hemisphere, DJF in Southern Hemisphere) data from eight countries: Canada, the United States, Mexico, the former Soviet Union, China, Australia, Norway, and Poland. These constitute more than 40% of the global land mass, and more than 80% of the extratropical land area. It is shown that the shape parameter of this distribution remains relatively stable, while the scale parameter is most variable spatially and temporally. This implies that the changes in mean monthly precipitation totals tend to have the most influence on the heavy precipitation rates in these countries. Observations show that in each country under consideration (except China), mean summer precipitation has increased by at least 5% in the past century. In the USA, Norway, and Australia the frequency of summer precipitation events has also increased, but there is little evidence of such increases in any of the countries considered during the past fifty years. A scenario is considered, whereby mean summer precipitation increases by 5% with no change in the number of days with precipitation or the shape parameter. When applied in the statistical model, the probability of daily precipitation exceeding 25.4 mm (1 inch) in northern countries (Canada, Norway, Russia, and Poland) or 50.8 mm (2 inches) in mid-latitude countries (the USA, Mexico, China, and Australia) increases by about 20% (nearly four times the increase in mean). The contribution of heavy rains (above these thresholds) to the total 5% increase of precipitation is disproportionally high (up to 50%), while heavy rain usually constitutes a significantly smaller fraction of the precipitation events and totals in extratropical regions (but up to 40% in the tropics, eg., in southern Mexico). Scenarios with moderate changes in the number of days with precipitation coupled with changes in the scale parameter were also investigated and found to produce smaller increases in heavy rainfall but still support the above conclusions. These scenarios give changes in heavy rainfall which are comparable to those observed and are consistent with the greenhouse-gas-induced increases in heavy precipitation simulated by some climate models for the next century. In regions with adequate data coverage such as the eastern two-thirds of contiguous United States, Norway, eastern Australia, and the European part of the former USSR, the statistical model helps to explain the disproportionate high changes in heavy precipitation which have been observed.

The aim of the paper was to present the temporal and spatial variability of precipitation in the Łódź province in the period 1961-2015. Daily precipitation totals from 20 precipitation stations in the province were used. It was shown that the mean yearly precipitation sum averaged across the province was 582 mm, and at particular stations ranged from 515 to 648. The totals were observed to be highest in the southern part of the province and they dropped to the north, where water deficits happened most often. Summer totals were more than double the winter ones. Spring and autumn precipitation totals were similar, with a slight advantage to spring totals. Daily sums most often fall in the range 1-10 mm. Daily totals exceeding 50 mm were extremely rare, and appeared once every few years, mainly in summer. At the moment, there are no statistically significant changes in the structure and level of precipitation, but there is a slight tendency towards increasing winter totals and decreasing summer totals. [ABSTRACT FROM AUTHOR]

This work gives an overview on how the projected changes in the extremes in Poland might impact human health and economy. For that purpose, statistically corrected data from 7 regional climate models were used. A significant increase of extreme hot events (i.e. heat waves, tropical nights) is projected for Central and Southern Poland for the end of the 21st century which might seriously affect a society living in large urban areas. Less extreme cold events improve thermal comfort in winter. The negative impact of the warming will affect energy systems with higher demand for electricity in summer and agriculture: an earlier beginning of the growing season and flower blooming will enhance the risk of frost damages in spring, whereas excessive heat will reduce yields in summer. Polish tourism should benefit from higher thermal comfort (except for hot July and August in the far future and warming in the winter season bringing snow cover depletion in the near future). [ABSTRACT FROM AUTHOR]

Credible information about the properties and changes of extreme events on the regional and local scales is of prime importance in the context of future climate change. Within the EU‐COST Action VALUE a comprehensive validation framework for downscaling methods has been developed. Here we present validation results for extremes of temperature and precipitation from the perfect predictor experiment that uses reanalysis‐based predictors to isolate downscaling skill. The raw reanalysis output reveals that there is mostly a large bias with respect to the extreme index values at the considered stations across Europe, clearly pointing to the necessity of downscaling. The performance of the downscaling methods is closely linked to their specific structure and setup. All methods using parametric distributions require non‐standard distributions to correctly represent marginal aspects of extremes. Also, the performance is much improved by explicitly including a seasonal component, particularly in case of precipitation. With respect to the marginal aspects of extremes the best performance is found for model output statistics (MOS), weather generators (WGs) as well as perfect prognosis (PP) methods using analogues. Spell‐length‐related extremes of temperature are best assessed by MOS and WGs, spell‐length‐related extremes of precipitation by MOS and PP methods using analogues. The skill of PP methods with transfer functions varies strongly across the methods and depends on the extreme index, region and season considered. [ABSTRACT FROM AUTHOR]

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