12 research outputs found

    Four-dimensional variational data analysis of water vapor Raman lidar data and their impact on mesoscale forecasts

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    The impact of water vapor observations on mesoscale initial fields provided by a triangle of Raman lidar systems covering an area of about 200 km × 200 km is investigated. A test case during the Lindenberg Campaign for Assessment of Humidity and Cloud Profiling Systems and its Impact on High-Resolution Modeling (LAUNCH-2005) was chosen. Evaluation of initial water vapor fields derived from ECMWF analysis revealed that in the model the highly variable vertical structure of water vapor profiles was not recovered and vertical gradients were smoothed out. Using a 3-h data assimilation window and a resolution of 10-30 min, continuous water vapor data from these observations were assimilated in the fifth-generation Pennsylvania State University-NCAR Mesoscale Model (MM5) by means of a four-dimensional variational data analysis (4DVAR). A strong correction of the vertical structure and the absolute values of the initial water vapor field of the order of 1 g kg-1 was found. This occurred mainly upstream of the lidar systems within an area, which was comparable with the domain covered by the lidar systems. The correction of the water vapor field was validated using independent global positioning system (GPS) sensors. Much better agreement to GPS zenith wet delay was achieved with the initial water vapor field after 4DVAR. The impact region was transported with the mean wind and was still visible after 4 h of free forecast time.Peer reviewe

    Call diversity in the North Pacific killer whale populations: implications for dialect evolution and population history

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    Although killer whale, Orcinus orca, dialects have been studied in detail in several populations, little attempt has been made to compare dialect characteristics between populations. In this study we investigated geographical variation in monophonic and biphonic calls among four resident populations from the North Pacific Ocean: Northern and Southern residents from British Columbia and Washington State, southern Alaska residents, and eastern Kamchatka residents. We tested predictions generated by the hypothesis that call variation across populations is the result of an accumulation of random errors and innovation by vertical cultural transmission. Call frequency contours were extracted and compared using a dynamic time-warping algorithm. We found that the diversity of monophonic calls was substantially higher than that of biphonic calls for all populations. Repertoire diversity appeared to be related to population size: in larger populations, monophonic calls were more diverse and biphonic calls less diverse. We suggest that the evolution of both monophonic and biphonic calls is caused by an interaction between stochastic processes and directional selection, but the relative effect of directional selection is greater for biphonic calls. Our analysis revealed no direct correlation between call repertoire similarity and geographical distance. Call diversity within predefined call categories, types and subtypes, showed a high degree of correspondence between populations. Our results indicate that dialect evolution is a complex process influenced by an interaction among directional selection, horizontal transmission and founder effects. We suggest several scenarios for how this might have arisen and the implications of these scenarios for call evolution and population history

    Water vapour intercomparison effort in the frame of the Convective and Orographically-induced Precipitation Study

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    International audienceThe main objective of this work is to provide accurate error estimates for the different water vapour profiling sensors based on an intensive inter-comparison effort. The inter-comparison, performed in the framework of COPS--Convective and Orographically-induced Precipitation Study (01 June-31 August 2007), involves airborne and ground-based water vapour lidar systems, radiosondes with different humidity sensors, GPS and Microwave radiometers (MWR). Simultaneous and co-located data from different sensors are used to compute relative bias and root-mean square (RMS) deviations as a function of altitud

    Water vapour intercomparison effort in the frame of the Convective and Orographically-induced Precipitation Study

    No full text
    International audienceThe main objective of this work is to provide accurate error estimates for the different water vapour profiling sensors based on an intensive inter-comparison effort. The inter-comparison, performed in the framework of COPS--Convective and Orographically-induced Precipitation Study (01 June-31 August 2007), involves airborne and ground-based water vapour lidar systems, radiosondes with different humidity sensors, GPS and Microwave radiometers (MWR). Simultaneous and co-located data from different sensors are used to compute relative bias and root-mean square (RMS) deviations as a function of altitud

    Water vapour intercomparison effort in the frame of the Convective and Orographically-induced Precipitation Study

    No full text
    The main objective of this work is to provide accurate error estimates for the different water vapour profiling sensors based on an intensive inter-comparison effort. The inter-comparison, performed in the framework of COPS - Convective and Orographically-induced Precipitation Study (01 June-31 August 2007), involves airborne and ground-based water vapour lidar systems, radiosondes with different humidity sensors, GPS and Microwave radiometers (MWR). Simultaneous and co-located data from different sensors are used to compute relative bias and root-mean square (RMS) deviations as a function of altitude. Comparisons between airborne CNRS DIAL and ground-based Raman lidar BASIL from three dedicated flights performed in the frame of the H2Olidar EUFAR project indicate a mean relative bias between the two sensors of 3.9% (0.11 g/kg) and a mean RMS deviation of 13.7% (0.97 g/kg) in the altitude region 0-4.5 kin above ground level. A specific inter-comparison between radiosondes with different humidity sensors (Vaisala RS80-A, RS80-H and RS92) was also performed during COPS. Results from the radiosonde inter-comparison indicate that RS80-A and RS80-H are affected by several systematic sources of error (contamination error, time-lag error, etc.), which have been corrected through established algorithms [1, 2, 3]. After correction for these error sources, mean bias between RS80 (A&H) and RS92 is found to be reduced to -4.5%. Based on the 3 comparisons between BASIL vs airborne DLR DIAL, the mean relative bias is about -3.5% in the altitude region 0-3 Km, while the RMS is approx. 13%. There are also ongoing comparisons between BASIL vs GPS, MWR and radiosondes and between the water vapor sensors located at different sites and the airborne DIALs which will be discussed at the symposium. Thus on the present statistics of comparisons between BASIL vs both the airborne DIALs and GPS and putting equal weight on the data reliability of each instrument, it results in the bias values of. BASIL Raman Lidar-0.3%, DLR DIAL 3.2%, CNRS DIAL-3.6% and GPS 0.6%. More ongoing comparisons between water vapor profiling sensors, especially benefiting from the extraordinary performances of the ground-based UHOH DIAL system, will be discussed at the symposium

    Bildungsarmut und Ausbildungslosigkeit in der Bildungs- und Wissensgesellschaft

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