A hybrid dynamical-statistical downscaling approach for climate change impacts analysis on high resolution in the Greater Athens Area

The available state-of-the art Regional Climate Model (RCM) simulations from the Euro-Cordex initiative have an horizontal resolution of about 12km which although is adequate for assessing regional climate change impacts is still coarse for studying the climate change impacts in an urban environment such as the Greater Athens Area (GAA). To this aim we propose a hybrid dynamical-statistical downscaling approach that produces high resolution, in the order of 1km, climate change projections for two future periods and under two RCP scenarios. To produce the higher resolution climate projections we combine the results of the Weather Research and Forecasting model (WRF) - Version 3.9.1 -including a single-layer urban canopy model to represent the urban tile- with available RCMs simulations obtained from the Euro-Cordex database.

Initially an annual WRF, ERA interim driven, simulation for a year identified as a “representative year” for the period 1971-2000 in the GAA is performed at an horizontal resolution of 1km. Subsequently the spatial signal of the WRF simulation is passed to the ERA interim driven RCM simulations for the period 1971-2000 using the unbiasing bias adjusting method which maintains the absolute trend as well as the variability of the RCM simulated data at all time scales. In a second step the donwscaled RCM evaluation simulations are used to bias adjust the transient RCM simulations using the empirical quantile method (EQM). EQM works by matching the transient simulations empirical cumulative distributions to the evaluation ones. This is achieved by establishing a quantile-dependent correction function between them during the reference period. The correction functions are then applied to both the historical and the future periods.

In this study we present the results for temperature and precipitation but the methodology can be extended to other variables of interest assuming that the WRF and the evaluation RCM simulations adequately reproduce their spatial and temporal variability, respectively.