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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).

[1] In this study we use large-eddy simulations (LES) to model roll convection within the convective atmospheric boundary-layer (CBL) during strong cold-air outbreaks (CAO). Previous LES were mostly unsuccessful in reproducing clear signals of roll convection, especially in case of strong surface heating and weak vertical wind shear in the CBL. In nature however, this phenomenon is very robust and roll convection can be observed as cloud streets in satellite pictures of almost any CAO. Previous LES studies assumed homogeneous sea-ice, unlike the current study, where under strong surface heating clear signals of rolls appear only when introducing sea-ice inhomogeneities in the marginal ice zone. For weaker surface heating, rolls also appear without sea-ice inhomogeneities. The results of this study suggest that in case of strong surface heating and weak vertical wind shear surface inhomogeneities increase the chance of roll formation. Citation: Gryschka, M., C. Drüe, D. Etling, and S. Raasch (2008), On the influence of sea-ice inhomogeneities onto roll convection in cold-air outbreaks,

Abstract. The quantification of sea-ice production in the Laptev Sea polynyas is important for the Arctic sea-ice budget and the heat loss to the atmosphere. We estimated the ice production for the winter season 2007/2008 (NovemberApril) based on simulations with the regional climate model COSMO-CLM at a horizontal resolution of 5 km and compared it to remote sensing estimates. A reference and five sensitivity simulations were performed with different assumptions on grid-scale and subgrid-scale ice thickness considered within polynyas, using a tile approach for fractional sea ice. In addition, the impact of heat loss on the atmospheric boundary layer was investigated.About 29.1 km 3 of total winter ice production was estimated for the reference simulation, which varies by up to +124 % depending on the thin-ice assumptions. For the most realistic assumptions based on remote sensing of ice thickness the ice production increases by +39 %. The use of the tile approach enlarges the area and enhances the magnitude of the heat loss from polynyas up to +110 % if subgrid-scale open water is assumed and by +20 % for realistic assumptions. This enhanced heat loss causes in turn higher ice production rates and stronger impact on the atmospheric boundary layer structure over the polynyas. The study shows that ice production is highly sensitive to the thin-ice parameterizations for fractional sea-ice cover. In summary, realistic ice production estimates could be retrieved from our simulations. Neglecting subgrid-scale energy fluxes might considerably underestimate the ice production in coastal polynyas, such as in the Laptev Sea, with possible consequences on the Arctic sea-ice budget.

[1] This paper presents a comparison of a regional lightning detection network based on SAFIR sensors (Surveillance et Alerte Foudre par Interférometrie Radioélectrique) with the operational German lightning detection system (BLIDS) that uses LPATS (Lightning Positioning and Tracking System) and IMPACT (Improved Performance from Combined Technology) sensors. The Institute for Meteorology and Climatology (IMUK) of the University of Hannover runs a regional lightning detection network in northern Germany (UHSN). It consists of three SAFIR receiving stations in a triangle of about 180 km side-length. As an a priori assumption that either BLIDS or UHSN represents the truth is not possible, the relative performance of each system in comparison with the other one is investigated. Probability of detection (POD) is used to investigate flash events simultaneously sensed by both networks. POD of UHSN was calculated assuming BLIDS measurements as true and, vice versa, POD of BLIDS was calculated assuming UHSN measurements as true. This comparison yielded that UHSN, as expected, is far more sensitive to intracloud lightning. In contrast, the sensitivity of UHSN for cloud-to-ground lightning was much lower than that of the BLIDS network. Hence the sensitivity of UHSN for both lightning types together (total lightning) is dominated by intracloud lightning and is consequently higher than that for BLIDS. The sensitivity of UHSN was found to exhibit strong horizontal variations. These are dominated by the network geometry and data processing procedures. The present study shows strengths and weaknesses of both systems and contributes to a better assessment of the potentials of each system.