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We examined 3 years of measured daily values of all major water budget components (precipitation P, potential evapotranspiration PET, actual evapotranspiration ET, and runoff R) and volumetric soil water content h of a small, forested catchment located in the west of Germany. The spatial distribution of h was determined from a wireless sensor network of 109 points with 3 measurement depths each; ET was calculated from eddy-covariance tower measurements. The water budget was dominantly energy limited, with ET amounting to approximately 90% of PET, and a runoff ratio R/P of 56%. P, ET, and R closed the long-term water budget with a residual of 2% of precipitation. On the daily time scale, the residual of the water budget was larger than on the annual time scale, and explained to a moderate extent by h (R 2 5 0.40). Wavelet analysis revealed subweekly time scales, presumably dominated by unaccounted fast-turnover storage terms such as interception, as a major source of uncertainty in water balance closure. At weekly resolution, soil water content explained more than half (R 2 5 0.62) of the residual. By means of combined empirical orthogonal function and cluster analysis, two slightly different spatial patterns of h could be identified that were associated with mean h values below and above 0.35 cm 3 /cm 3 , respectively. The timing of these patterns as well as the varying coherence between PET, ET, and soil water content responded to changes in water availability, including a moderate response to the European drought in spring 2011.

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AMDAR (Aircraft Meteorological DAta Relay) automated weather reports from commercial aircraft provide an increasing amount of input data for numerical weather prediction models. Previous studies have investigated the quality of AMDAR data. Few of these studies, however, have revealed indications of systematic errors dependent upon the aircraft type. Since different airlines use different algorithms to generate AMDAR reports, it has remained unclear whether a dependency on the aircraft type is caused by physical properties of the aircraft or by different data processing algorithms. In the present study, a special AMDAR dataset was used to investigate the physical type-dependent errors of AMDAR reports. This dataset consists of AMDAR measurements by Lufthansa aircraft performing over 300 landings overall at Frankfurt Rhein/Main (EDDF/FRA) on 22 days in 2004. All of this data has been processed by the same software, implying that influences from different processing algorithms should not be expected. From the comparison of single descents to hourly averaged vertical profiles, it is shown that temperature measurements by different aircraft types can have systematic differences of up to 1 K. In contrast, random temperature errors of most types are estimated to be less than 0.3 K. It is demonstrated that systematic deviations in AMDAR wind measurements can be regarded as an error vector, which is fixed to the aircraft reference system. The largest systematic deviations in wind measurements from different aircraft types (more than 0.5 m s −1 ) were found to exist in the longitudinal direction (i.e. parallel to the flight direction).