Ice cover persistence in the lower reaches of the Nemunas River has decreased during the last 150 yr. The variation in the river freeze-and break-up dates is related to climatic variables. The significance of the negative break-up trend exceeds that of the positive freeze-up trend. Lowfrequency large-scale atmospheric circulation patterns such as the North Atlantic Oscillation and Arctic Oscillation (NAO/AO) appear to have more influence on the break-up date than on the freezeup date. Different classification methods applied to the atmospheric patterns prevailing in the early freeze-up events reveal similar results; however, differences arising between classifications are attributable to non-persistent and high frequency patterns. KEY WORDS: River ice cover · Freeze up · Break up · Atmospheric forcing Resale or republication not permitted without written consent of the publisherClim Res 36: [17][18][19][20][21][22][23][24][25][26][27][28] 2008 was forced primarily by El Niño and its mid-latitude teleconnections.Kilkus (1989, 1992, 1998) and Rainys (1975) examined the ice regime of rivers and lakes in Lithuania. Kilkus & Valiuskevicius (2001) were the first to analyse long-term ice cover parameters and their trends in various national inland water bodies, while Bukantis & Kilkus (2004) were the first to relate the North Atlantic Oscillation (NAO) to the hydrological regime of various water bodies in Lithuania.Anthropogenic influences on the Nemunas River ice regime are examined in only a small number of papers. Rainys (1975) asserted that changes in the river ice cover formation were observed 20-30 km downstream of the Kaunas Hydropower Plant (HPP). Using a variety of statistical techniques, Stonevicius (2004) found that the main turning point in the ice regimes of the Nemunas and Neris rivers occurred in 1972 (Kaunas HPP was built in 1960), and that this turning point was probably caused by climate change. Of all ice cover break-up events during 1950-2000 in the Nemunas River lower reaches, 91.7% were forced by a rapid rise in water level (34 spring runoff events and 10 wintertime events).The most recent results for Canada show an interesting regional difference, with rivers over the western regions generally showing trends toward earlier break up, and rivers over the eastern regions showing later break up (Zhang et al. 2001).Many factors influence river and lake ice break up, i.e. air temperature, ice thickness, snow cover, wind, water temperature and depth of water below the ice. In fact, river ice is affected by several meteorological variables that define the surface energy balance. Air temperature is the most important variable affecting lake ice, strongly influencing freeze up, growth, duration, and break up (Barry & Maslanik 1993). For rivers, air temperature dominates ice formation and growth, while rainfall and snowmelt control basin runoff, flow, and ice break up.In many temperate regions, water temperatures in rivers respond rapidly to changing air temperatures, causing frequent cycles...

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Abstract. Hydrological ensemble prediction systems (HEPS) have in recent years been increasingly used for the operational forecasting of floods by European hydrometeorological agencies. The most obvious advantage of HEPS is that more of the uncertainty in the modelling system can be assessed. In addition, ensemble prediction systems generally have better skill than deterministic systems both in the terms of the mean forecast performance and the potential forecasting of extreme events. Research efforts have so far mostly been devoted to the improvement of the physical and technical aspects of the model systems, such as increased resolution in time and space and better description of physical processes. Developments like these are certainly needed; however, in this paper we argue that there are other areas of HEPS that need urgent attention. This was also the result from a group exercise and a survey conducted to operational forecasters within the European Flood Awareness System (EFAS) to identify the top priorities of improvement regarding their own system. They turned out to span a range of areas, the most popular being to include verification of an assessment of past forecast performance, a multi-model approach for hydrological modelling, to increase the forecast skill on the medium range (>3 days) and more focus on education and training on the interpretation of forecasts. In light of limited resources, we suggest a simple model to classify the identified priorities in terms of their cost and complexity to decide in which order to tackle them. This model is then used to create an action plan of short-, medium- and long-term research priorities with the ultimate goal of an optimal improvement of EFAS in particular and to spur the development of operational HEPS in general.

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The climate continentality or oceanity is one of the main characteristics of the local climatic conditions, which varies with global and regional climate change. This paper analyzes indexes of continentality and oceanity, as well as their variations in the middle and high latitudes of the Northern Hemisphere in the period 1950–2015. Climatology and changes in continentality and oceanity are examined using Conrad’s Continentality Index (CCI) and Kerner’s Oceanity Index (KOI). The impact of Northern Hemisphere teleconnection patterns on continentality/oceanity conditions was also evaluated. According to CCI, continentality is more significant in Northeast Siberia and lower along the Pacific coast of North America as well as in coastal areas in the northern part of the Atlantic Ocean. However, according to KOI, areas of high continentality do not precisely correspond with those of low oceanity, appearing to the south and west of those identified by CCI. The spatial patterns of changes in continentality thus seem to be different. According to CCI, a statistically significant increase in continentality has only been found in Northeast Siberia. In contrast, in the western part of North America and the majority of Asia, continentality has weakened. According to KOI, the climate has become increasingly continental in Northern Europe and the majority of North America and East Asia. Oceanity has increased in the Canadian Arctic Archipelago and in some parts of the Mediterranean region. Changes in continentality were primarily related to the increased temperature of the coldest month as a consequence of changes in atmospheric circulation: the positive phase of North Atlantic Oscillation (NAO) and East Atlantic (EA) patterns has dominated in winter in recent decades. Trends in oceanity may be connected with the diminishing extent of seasonal sea ice and an associated increase in sea surface temperature.