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A 1-yr meteorological dataset for the terminal area of Frankfurt Airport in Germany has been generated with a numerical weather prediction system to provide a synthetic though realistic database for the evaluation of new operational aircraft arrival procedures and their associated risks. The comparison of the 1-yr dataset with a local surface wind climatology indicates that the main climatological features are recovered. A subset of 40 days is validated against measurements from a sound detection and range/radio acoustic sounding system (SODAR/RASS) taken at Frankfurt Airport. The RMS errors of wind speed and direction are between 1.5 m s Ϫ1 at the surface and 2 m s Ϫ1 at 300 m and 40°, respectively. The frequency distribution of meteorological parameters, such as the wind component perpendicular to the glide path, shear, and thermal stratification, show good agreement with observations. The magnitude of the turbulent energy dissipation rate near the surface is systematically overestimated, whereas above 100 m the authors find on average a slight underestimation. The analysis of the database with respect to crosswind conditions along the glide path indicates only a time fraction of 12% for which the crosswind is above a threshold of 2 m s Ϫ1 . A similar result is obtained using a grid point near the airport that mimics a wind profiler, which suggests that in a majority of cases a wind profiler appears sufficient to cover the expected crosswind conditions along the glide path. A simple parameterization to account for the crosswind variability along the glide path is proposed.

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The absolute calibration of a dual-polarization radar of the German Weather Service is continuously monitored using the operational birdbath scan and collocated disdrometer measurements at the Hohenpeissenberg observatory. The goal is to measure the radar reflectivity constant Z better than ±1 dB. The assumption is that a disdrometer measurement close to the surface can be related to the radar measurement at the first far-field range bin. This is verified using a Micro Rain Radar (MRR). The MRR data fill the gap between the measurement near the surface and the far-field range bin at 650 m. Using data from the first half of the warm season in 2014, a bias in radar calibration of 1.8 dB is found. Data from only stratiform precipitation events are considered. After adjusting the radar calibration and using an independent data sample, very good agreement is found between the radar, the MRR, and the disdrometer with a bias in smaller than 1 dB. The bias in is not captured with the classic one-point calibration, which is performed twice a day using a built-in test signal generator. This is attributed to the fact that the characterization of the transmit and receive path is not accurate enough. Solar interferences during the operational scanning are used to characterize the receiver. There, the bias found is small, about 0.2 dB, so that bias based on the comparison of the radar with external sensors is attributed to the transmit path. The representativeness of the disdrometer measurements are assessed using two additional disdrometers located within 200-m distance.