Statistics/Finance Seminar with Thordis Linda Thorarinsdottir, University of Oslo
The Department of Finance and Center for Statistics are proud to announce the upcoming seminar with Thordis Linda Thorarinsdottir, University of Oslo.
Thordis Linda Thorarinsdottir will present: Statistical contributions in climate research: The importance of stochastic modelling, uncertainty quantification and model evaluation
Abstract:
High-resolution unbiased information on future climate change is commonly required for local impact assessment and adaptation decision-making. While climate models are our primary source of knowledge about future climate change, global and regional climate models are generally biased and their resolution is often lower than desired. Furthermore, not all climate variables are included in the climate model simulations. When producing climate projections at fine grid resolutions or individual locations, it is imperative to include stochastic components to model local variability not accounted for by the lower resolution model. This involves developing space-time models that are consistent with observational data over historical periods and the available information on future climate for future periods, while also being computationally feasible. Similarly, it is important to evaluate the climate change information at the level it is later used in further modelling. In subsequent decision problems it is imperative to propagate the uncertainty in the climate projections and other model components through the decision-making framework even if the resulting answer should be given by a single number. We discuss these aspects and show examples involving future projections of temperature and precipitation as well as sea level adaptation decision-making.
The talk will be based on the following papers:
Thorarinsdottir, T. L., Guttorp, P., Drews, M., Kaspersen, P. S., & de Bruin, K. (2017). Sea level adaptation decisions under uncertainty. Water Resources Research, 53(10), 8147-8163.
Thorarinsdottir, T. L., Sillmann, J., Haugen, M., Gissibl, N., & Sandstad, M. (2020). Evaluation of CMIP5 and CMIP6 simulations of historical surface air temperature extremes using proper evaluation methods. Environmental Research Letters, 15(12), 124041.
Yuan, Q., Thorarinsdottir, T. L., Beldring, S., Wong, W. K., Huang, S., & Xu, C. Y. (2019). New approach for bias correction and stochastic downscaling of future projections for daily mean temperatures to a high-resolution grid. Journal of Applied Meteorology and Climatology, 58(12), 2617-2632.
Yuan, Q., Thorarinsdottir, T. L., Beldring, S., Wong, W. K., & Xu, C. Y. (2021). Bridging the scale gap: obtaining high-resolution stochastic simulations of gridded daily precipitation in a future climate. Hydrology and Earth System Sciences, 25(9), 5259-5275.
Location:
Solbjerg Plads 3
2000 Frederiksberg
Room: SPs03