Climate variability and climate change

Ongoing and future climate change is one of the main environmental issues of the present, attracting attention in the decision-making and political spheres, as evidenced by the Paris agreement concluded in 2016.

We deal with climate change detection, development of methods for the testing of presence and significance of trends, especially in spatial data, and relationships between trends in various variables (e.g. temperature, cloud cover, sunshine). We develop and evaluate statistical downscaling methods as well as methods for constructing climate change scenarios used in assessing climate change impacts on agricultural production and hydrological regime, among others; the main tool for the latter is the multidimensional stochastic spatial weather generator SPAGETTA.

We contributed to the formulation of the framework for validation of downscaling approaches for climate change studies and the intercomparison of a large number of statistical downscaling methods in a wide international cooperation within the COST 1102 Action VALUE. Methodologies for applying tests of the significance of trends in areas with geographically irregularly distributed data are developed, as well as methods to display a full annual cycle of trends in climate elements. Furthermore, we systematically evaluate the outputs of climate models both in terms of capturing the observed climate variability and in terms of projected future changes and their uncertainties.