Comparison of wind and wind shear climatologies derived from high-resolution radiosondes and the ECMWF model

摘要

The climatology of atmospheric horizontal wind and its vertical gradient, i.e., wind shear, is characterized as a function of climate region. For a better representation of the average atmospheric wind and shear and their variabilities, high-resolution radiosonde wind profiles up to about 30 km altitude are compared with the collocated operational ECMWF model for short-range forecast winds. Statistics of zonal and meridional winds are established from both data sets. The results show mainly similarity in the probability distributions of the modeled and observed horizontal winds, practically at all levels of the atmosphere, while at the same time the vertical shear of the wind is substantially underestimated in the model. The comparison of shear statistics of radiosonde and ECMWF model winds shows that the model wind shear mean and variability are on average a factor of 2.5 (zonal) and 3 (meridional) smaller than of radiosondes in the free troposphere, while in the stratosphere, the planetary boundary layer results are more variable. By applying vertical averaging to the radiosonde data, it is found that the effective vertical resolution of the ECMWF model is typically 1.7 km. Moreover, it is found for individually collocated radiosonde model wind and shear profiles that the model wind may lack in some cases variability larger than 5 m s~(-1) and 0.015 s~(-1), respectively, due mainly to the effect of lacking vertical resolution, in particular near the jets. Besides the general importance of this study in highlighting the difference in the representation of the atmospheric wind shear by model and observations, it is more specifically relevant for the future Atmospheric Dynamics Mission (ADM-Aeolus) of the European Space Agency due for launch in 2012. The results presented here are used to generate a realistic global atmospheric database, which is necessary to conduct simulations of the Aeolus Doppler wind lidar in order optimize its vertical sampling and processing.