Modelling monthly Boundary Layer Height maps combining radiosonde, satellite, and reanalysis over Europe
Abstract
Abstract. The height of the planetary boundary layer directly influences local and regional climatic phenomena, making its study and estimation of vital importance for environmental sciences. The main objective of this work was to create a gridded map of planetary boundary layer height across the European continent, with a spatial resolution of 25 km and monthly mean values at two synoptic hours (12:00 and 00:00 UTC). We implemented the regression kriging method by combining various data sources, including observations, climatic and topographic variables, and reanalysis data (ERA5), and different regression methods (linear, random forest, and gradient boosting) for the 2010–2020 period. In both UTC hours, combining reanalysis, land surface temperature and topographic covariates with random forest regression provided the best performance. However, the models' performance at night declined considerably compared with midday. Then, we compared our seasonal predictions with reanalysis data and found a consistently higher spatio-temporal accuracy than that of the ERA5 reanalysis. For example, at 12:00 UTC, spatial variability in winter showed RMSE values ≤170 m, compared with ≥250 m for ERA5, while temporal variability in summer reached RMSE values ≤260 m, versus 340 m for ERA5. At 00:00 UTC, spatial variability in summer achieved RMSE values = 14 m, whereas ERA5 exhibited RMSE = 60 m, while temporal variability in winter reached RMSE values ≤176 m, versus 200 m for ERA5. The proposed regression kriging method thus performed well in estimating the height of the boundary layer at 12:00 UTC, and to a lesser extent at 00:00 UTC.