National Repository of Grey Literature 2 records found  Search took 0.01 seconds. 
Bias correction of regional climate model outputs: statistical transformations of precipitation series from the climate model ALADIN in the project PERUN
Martínková, Marta
The outputs of regional climate models are biased. Regarding the bias correction of outputs from a climate model, the two fundamental approaches exist. First approach (e.g., Delta change method) gets the information on climate signal from comparison of the model control and future periods. Such information (change factor) is then applied to modify the observational data. Bias correction method gets the information on model bias from comparison of observational data and model outputs for the control period. The model outputs for future period are than corrected using this information on the model bias. This contribution is focused on the possibilities for bias correction of the model ALADIN (CNRM-ESM2-1) in the project PERUN and the precipitation series in daily time step for SSP5-8.5 scenario. Different statistical transformations are compared: methods based on statistical distribution, parametric transformations and non-parametric transformations (empirical quantiles method).\n
Projections of future water-energy-vegetation regimes at the Lysina catchment, Czech Republic
Lamačová, Anna ; Yu, X. ; Duffy, Ch. ; Krám, Pavel ; Hruška, Jakub ; Farda, Aleš
Hydrologic models represent useful tools for the understanding of forest hydrological functions. At the Lysina Critical Zone Observatory (50°03’ N, 12°40’ E; area 0.293 km2), a forest catchment in the western Czech Republic, a distributed physics-based hydrologic model, the Penn State Integrated Hydrologic Model (PIHM), was used to simulate long-term hydrological change under forest management practices, and to evaluate the comparative scenarios of the hydrological consequences under anticipated climate change. Stand age-adjusted LAI (leaf area index) curves were generated from an empirical relationship to represent changes in seasonal tree growth. By considering the age-adjusted LAI, the spatially distributed model was able to successfully simulate the integrated hydrologic response from snow melt, recharge, evapotranspiration, groundwater levels, soil moisture and streamfl ow, as well as spatial patterns of each hydrologic state and fl ux variables. Corrected climatic data from the ALADIN-Climate/CZ regional climate model with SRES A1B scenario and diff erent forest age categories (Norway spruce monoculture) were used for projection of hydrologic pattern shift at the study site in the future (2025–2050, 2071–2100). Th e model projections suggested that that the decrease in mean annual runoff would be from 422 mm (observed in 1990–2011) to 361 mm (2021–2100) and 345 mm (2071–2100) with notable changes in seasonal patterns represented by a runoff decrease in the spring and summer months.

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