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Now showing 1 - 4 of 4
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    Changes of snow cover in Poland
    (Heidelberg : Springer, 2017) Szwed, Małgorzata; Pin´skwar, Iwona; Kundzewicz, Zbigniew W.; Graczyk, Dariusz; Mezghani, Abdelkader
    The present paper examines variability of characteristics of snow cover (snow cover depth, number of days with snow cover and dates of beginning and end of snow cover) in Poland. The study makes use of a set of 43 long time series of observation records from the stations in Poland, from 1952 to 2013. To describe temporal changes in snow cover characteristics, the intervals of 1952–1990 and of 1991–2013 are compared and trends in analysed data are sought (e.g., using the Mann–Kendall test). Observed behaviour of time series of snow-related variables is complex and not easy to interpret, for instance because of the location of the research area in the zone of transitional moderate climate, where strong variability of climate events is one of the main attributes. A statistical link between the North Atlantic Oscillation (NAO) index and the snow cover depth, as well as the number of snow cover days is found.
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    What can we learn from the projections of changes of flow patterns? Results from Polish case studies
    (Heidelberg : Springer, 2017) Piniewski, Mikołaj; Meresa, Hadush Kidane; Romanowicz, Renata; Osuch, Marzena; Szczes´niak, Mateusz; Kardel, Ignacy; Okruszko, Tomasz; Mezghani, Abdelkader; Kundzewicz, Zbigniew W.
    River flow projections for two future time horizons and RCP 8.5 scenario, generated by two projects (CHASE-PL and CHIHE) in the Polish-Norwegian Research Programme, were compared. The projects employed different hydrological models over different spatial domains. The semi-distributed, process-based, SWAT model was used in the CHASE-PL project for the entire Vistula and Odra basins area, whilst the lumped, conceptual, HBV model was used in the CHIHE project for eight Polish catchments, for which the comparison study was made. Climate projections in both studies originated from the common EURO-CORDEX dataset, but they were different, e.g. due to different bias correction approaches. Increases in mean annual and seasonal flows were projected in both studies, yet the magnitudes of changes were largely different, in particular for the lowland catchments in the far future. The HBV-based increases were significantly higher in the latter case than the SWAT-based increases in all seasons except winter. Uncertainty in projections is high and creates a problem for practitioners.
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    Assessment of climate change and associated impact on selected sectors in Poland
    (Warsaw : De Gruyter Open, 2018) Kundzewicz, Zbigniew W.; Piniewski, Mikołaj; Mezghani, Abdelkader; Okruszko, Tomasz; Pińskwar, Iwona; Kardel, Ignacy; Hov, Øystein; Szcześniak, Mateusz; Szwed, Małgorzata; Benestad, Rasmus E.; Marcinkowski, Paweł; Graczyk, Dariusz; Dobler, Andreas; Førland, Eirik J.; O’Keefe, Joanna; Choryński, Adam; Parding, Kajsa M.; Haugen, Jan Erik
    The present paper offers a brief assessment of climate change and associated impact in Poland, based on selected results of the Polish–Norwegian CHASE-PL project. Impacts are examined in selected sectors, such as water resources, natural hazard risk reduction, environment, agriculture and health. Results of change detection in long time series of observed climate and climate impact variables in Poland are presented. Also, projections of climate variability and change are provided for time horizons of 2021–2050 and 2071–2100 for two emission scenarios, RCP4.5 and RCP8.5 in comparison with control period, 1971–2000. Based on climate projections, examination of future impacts on sectors is also carried out. Selected uncertainty issues relevant to observations, understanding and projections are tackled as well.
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    Subsampling impact on the climate change signal over poland based on simulations from statistical and dynamical downscaling
    (Boston, Mass. : AMS, 2019) Mezghani, Abdelkader; Dobler, Andreas; Benestad, Rasmus; Haugen, Jan Erik; Parding, Kajsa M.; Piniewski, Mikolaj; Kundzewicz, Zbigniew W.
    Most impact studies using downscaled climate data as input assume that the selection of few global climate models (GCMs) representing the largest spread covers the likely range of future changes. This study shows that including more GCMs can result in a very different behavior. We tested the influence of selecting various subsets of GCMs on the climate change signal over Poland from simulations based on dynamical and empirical-statistical downscaling methods. When the climate variable is well simulated by the GCM, such as temperature, results showed that both downscaling methods agree on a warming over Poland by up to 2° or 5°C assuming intermediate or high emission scenarios, respectively, by 2071-2100. As a less robust simulated signal through GCMs, precipitation is expected to increase by up to 10% by 2071-2100 assuming the intermediate emission scenario. However, these changes are uncertain when the high emission scenario and the end of the twenty-first century are of interest. Further, an additional bootstrap test revealed an underestimation in the warming rate varying from 0.5° to more than 4°C over Poland that was found to be largely influenced by the selection of few driving GCMs instead of considering the full range of possible climate model outlooks. Furthermore, we found that differences between various combinations of small subsets from the GCM ensemble of opportunities can be as large as the climate change signal. © 2019 American Meteorological Society.