Abstract
We have evaluated three prognostic variables in Weather Research and Forecasting (WRF) model, mean daily temperature, daily maximum temperature, and daily minimum temperature using 9 months of model simulations at 36 and 12 km resolution, and compared the results with 1182 observational sites in north and central Europe. The quality of the results is then determined in the context of the governing variables used in crop science, forestry, and aerobiological models. We use the results to simulate the peak of the birch pollen season (aerobiology), growth of barley (crop science), and development of the invasive plant pathogenHymenoscyphus pseudoalbidus(the cause of ash-dieback). The results show that the crop and aerobiological models are particularly sensitive to grid resolution and much higher quality is obtained from the 12 km simulations compared to 36 km. The results also show that the summer months have a bias, in particular for maximum and minimum temperatures, and that the low/high bias is clustered in two areas: continental and coastal influenced areas. It is suggested that the use of results from meteorological models as an input into biological models needs particular attention in the quality of the modelled surface data as well as the applied land surface modules.
Highlights
Weather models are used for a number of applications such as air quality studies [1,2,3,4], weather [5, 6], hydrological [7, 8] and air pollution forecasting [9,10,11], crop science [12, 13], and recently aerobiology [14,15,16] and ecology [17]
Recent studies with Weather Research and Forecasting (WRF)-Chem have focused on emission input [25,26,27,28], planetary boundary layer and surface layer parameterisations [29], chemistry-aerosol mechanisms and sensitivities [30,31,32], meteorology in relation to atmospheric chemistry [33, 34], feedback effects between chemistry and weather [25, 27, 35], the effect of topography and land use input [36, 37], and initial conditions [38]
The bias in mean surface temperature between the WRF calculations and global surface summary of day data (GSOD) data is unevenly distributed over both model domains for Q1, Q2, and Q3 (Figure 2)
Summary
Weather models are used for a number of applications such as air quality studies [1,2,3,4], weather [5, 6], hydrological [7, 8] and air pollution forecasting [9,10,11], crop science [12, 13], and recently aerobiology [14,15,16] and ecology [17]. Validation and sensitivity in relation to the biosphere have had limited attention in modelling
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