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  • Artikel  (73)
  • Geologie und Paläontologie  (68)
  • Architektur, Bauingenieurwesen, Vermessung  (9)
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  • Artikel  (73)
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  • 1
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    Multiregional Satellite Precipitation Products Evaluation over Complex Terrain (2016)
    American Meteorological Society
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    Publikationsdatum: 2016-06-01
    Beschreibung: An extensive evaluation of nine global-scale high-resolution satellite-based rainfall (SBR) products is performed using a minimum of 6 years (within the period of 2000–13) of reference rainfall data derived from rain gauge networks in nine mountainous regions across the globe. The SBR products are compared to a recently released global reanalysis dataset from the European Centre for Medium-Range Weather Forecasts (ECMWF). The study areas include the eastern Italian Alps, the Swiss Alps, the western Black Sea of Turkey, the French Cévennes, the Peruvian Andes, the Colombian Andes, the Himalayas over Nepal, the Blue Nile in East Africa, Taiwan, and the U.S. Rocky Mountains. Evaluation is performed at annual, monthly, and daily time scales and 0.25° spatial resolution. The SBR datasets are based on the following retrieval algorithms: Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis (TMPA), the NOAA/Climate Prediction Center morphing technique (CMORPH), Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN), and Global Satellite Mapping of Precipitation (GSMaP). SBR products are categorized into those that include gauge adjustment versus unadjusted. Results show that performance of SBR is highly dependent on the rainfall variability. Many SBR products usually underestimate wet season and overestimate dry season precipitation. The performance of gauge adjustment to the SBR products varies by region and depends greatly on the representativeness of the rain gauge network.
    Print ISSN: 1525-755X
    Digitale ISSN: 1525-7541
    Thema: Geographie , Geologie und Paläontologie , Physik
    Publiziert von American Meteorological Society
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  • 2
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    Small-Scale Variability of the Raindrop Size Distribution and Its Effect on Areal Rainfall Retrieval (2016)
    American Meteorological Society
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    Publikationsdatum: 2016-07-01
    Beschreibung: The drop size distribution (DSD) describes the microstructure of liquid precipitation. The high variability of the DSD reflects the variety of microphysical processes controlling raindrop properties and affects the retrieval of rainfall. An analysis of the effects of DSD subgrid variability on areal estimation of precipitation is presented. Data used were recorded with a network of disdrometers in Ardèche, France. DSD variability was studied over two typical scales: 5 km × 5 km, similar to the ground footprint size of the Global Precipitation Measurement (GPM) spaceborne weather radar, and 2.8 km × 2.8 km, an operational pixel size of the Consortium for Small-Scale Modeling (COSMO) numerical weather model. Stochastic simulation was used to generate high-resolution grids of DSD estimates over the regions of interest, constrained by experimental DSDs measured by disdrometers. From these grids, areal DSD estimates were derived. The error introduced by assuming a point measurement to be representative of the areal DSD was quantitatively characterized and was shown to increase with the size of the considered area and with drop size and to decrease with the integration time. The controlled framework allowed for the accuracy of retrieval algorithms to be investigated. Rainfall variables derived by idealized simulations of GPM- and COSMO-style algorithms were compared to subgrid distributions of the same variables. While rain rate and radar reflectivity were well represented, the estimated drop concentration and mass-weighted mean drop diameter were often less representative of subgrid values.
    Print ISSN: 1525-755X
    Digitale ISSN: 1525-7541
    Thema: Geographie , Geologie und Paläontologie , Physik
    Publiziert von American Meteorological Society
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  • 3
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    Multifractal Analysis of Snowfall Recorded Using a 2D Video Disdrometer (2017)
    American Meteorological Society
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    Publikationsdatum: 2017-09-01
    Beschreibung: Universal multifractal (UM) analysis was used to investigate the scaling properties of snowfall at high temporal and spatial resolutions. Snowfall data were recorded using a 2D video disdrometer (2DVD) in the Swiss Alps. Six 1-h-long periods of snowfall, half in calm and half in light wind conditions, were selected for analysis. UM analysis was performed on reconstructed 35-m vertical columns of snowfall structure, snowfall time series at 100-ms resolution, and two-dimensional snowflake accumulation maps over a 5.12 5.12 cm2 area. Multifractal scaling was observed for the vertical structure of snow particle number concentration, for scales between about 35 and 4.4 m, and sometimes down to about 0.5 m. At smaller scales, no scaling was observed. In high-resolution time series of snowfall, evidence of scaling was found for scales between about 7 min and ~26 s in most of the analyzed hours. Snowflake accumulations within a subset of the small sampling area of the 2DVD showed no scaling properties, suggesting homogeneous structure in snowfall at the very small (~5 cm) scale, which agrees with the results for vertical structure and time series.
    Print ISSN: 1525-755X
    Digitale ISSN: 1525-7541
    Thema: Geographie , Geologie und Paläontologie , Physik
    Publiziert von American Meteorological Society
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  • 4
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    A Comparison between the GPM Dual-Frequency Precipitation Radar and Ground-Based Radar Precipitation Rate Estimates in the Swiss Alps and Plateau (2017)
    American Meteorological Society
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    Publikationsdatum: 2017-04-12
    Beschreibung: The Global Precipitation Measurement (GPM) mission Dual-Frequency Precipitation Radar (DPR) provides a unique set of three-dimensional radar precipitation estimates across much of the globe. Both terrain and climatic conditions can have a strong influence on the reliability of these estimates. Switzerland provides an ideal testbed to evaluate the performance of the DPR in complex terrain: it consists of a mixture of very complex terrain (the Alps) and the far flatter Swiss Plateau. It is also well instrumented, covered with a dense gauge network as well as a network of four dual-polarization C-band weather radars, with the same instrument network used in both the Plateau and the Alps. Here an evaluation of the GPM DPR rainfall rate products against the MeteoSwiss radar rainfall rate product for the first two years of the GPM DPR’s operation is presented. Errors in both detection and estimation are considered, broken down by terrain complexity, season, precipitation phase, precipitation type, and precipitation rate. Errors are considered both integrated across the entire domain and spatially, and consistent underestimation of precipitation by GPM is found. This rises to −51% in complex terrain in the winter, primarily due to the predominance of DPR measurements wholly in the solid phase, where problems are caused by lower reflectivities. The smaller vertical extent of precipitation in winter is also likely a cause. Both detection and estimation performance are found to be significantly better in summer than in winter, in liquid than in solid precipitation, and in flatter terrain than in complex terrain.
    Print ISSN: 1525-755X
    Digitale ISSN: 1525-7541
    Thema: Geographie , Geologie und Paläontologie , Physik
    Publiziert von American Meteorological Society
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  • 5
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    Synoptic conditions and atmospheric moisture pathways associated with virga and precipitation over coastal Adélie Land in Antarctica (2020)
    Copernicus
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    Publikationsdatum: 2020-05-27
    Beschreibung: Precipitation falling over the coastal regions of Antarctica often experiences low-level sublimation within the dry katabatic layer. The amount of water that reaches the ground surface is thereby considerably reduced. This paper investigates the synoptic conditions and the atmospheric transport pathways of moisture that lead to either virga – when precipitation is completely sublimated – or actual surface precipitation events over coastal Adélie Land, East Antarctica. For this purpose, the study combines ground-based lidar and radar measurements at Dumont d'Urville station (DDU), Lagrangian back trajectories, Eulerian diagnostics of extratropical cyclones and fronts, and moisture source estimations. It is found that precipitating systems at DDU are associated with warm fronts of cyclones that are located to the west of Adélie Land. Virga – corresponding to 36 % of the hours with precipitation above DDU – and surface precipitation cases are associated with the same precipitating system but they correspond to different phases of the event. Virga cases more often precede surface precipitation. They sometimes follow surface precipitation in the warm sector of the cyclone's frontal system, when the associated cyclone has moved to the east of Adélie Land and the precipitation intensity has weakened. On their way to DDU, the air parcels that ultimately precipitate above the station experience a large-scale lifting across the warm front. The lifting generally occurs earlier in time and farther from the station for virga than for precipitation. It is further shown that the water contained in the snow falling above DDU during pre-precipitation virga has an oceanic origin farther away (about 30∘ more to the west) from Adélie Land than the one contained in the snow that precipitates down to the ground surface.
    Print ISSN: 1994-0416
    Digitale ISSN: 1994-0424
    Thema: Geographie , Geologie und Paläontologie
    Publiziert von Copernicus im Namen von European Geosciences Union.
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  • 6
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    Learning about the vertical structure of radar reflectivity using hydrometeor classes and neural networks in the Swiss Alps (2020)
    Copernicus
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    Publikationsdatum: 2020-05-19
    Beschreibung: The use of radar for precipitation measurement in mountainous regions is complicated by many factors, especially beam shielding by terrain features, which, for example, reduces the visibility of the shallow precipitation systems during the cold season. When extrapolating the radar measurements aloft for quantitative precipitation estimation (QPE) at the ground, these must be corrected for the vertical change of the radar echo caused by the growth and transformation of precipitation. Building on the availability of polarimetric data and a hydrometeor classification algorithm, this work explores the potential of machine learning methods to study the vertical structure of precipitation in Switzerland and to propose a more localised vertical profile correction. It first establishes the ground work for the use of machine learning methods in this context: from volumetric data of 30 precipitation events, vertical cones with 500 m vertical resolution are extracted. It is shown that these cones can well represent the vertical structure of different types of precipitation events (stratiform, convective, snowfall). The reflectivity data and the hydrometeor proportions from the extracted cones constitute the input for the training of artificial neural networks (ANNs), which are used to predict the vertical change in reflectivity. Lower height levels are gradually removed in order to test the ANN's ability to extrapolate the radar measurements to the ground level. It is found that ANN models using the information on hydrometeor proportions can predict from altitudes between 500 and 1000 m higher than the ANN based on only reflectivity data. In comparison to more traditional vertical profile correction techniques, the ANNs show less prediction errors made from all height levels up to 4000 m a.s.l., above which the ANNs lose predictive skill and the performance levels off to a constant value.
    Print ISSN: 1867-1381
    Digitale ISSN: 1867-8548
    Thema: Geologie und Paläontologie
    Publiziert von Copernicus im Namen von European Geosciences Union.
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  • 7
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    Unsupervised classification of snowflake images using a generative adversarial network and K-medoids classification (2020)
    Copernicus
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    Publikationsdatum: 2020-06-05
    Beschreibung: The increasing availability of sensors imaging cloud and precipitation particles, like the Multi-Angle Snowflake Camera (MASC), has resulted in datasets comprising millions of images of falling snowflakes. Automated classification is required for effective analysis of such large datasets. While supervised classification methods have been developed for this purpose in recent years, their ability to generalize is limited by the representativeness of their labeled training datasets, which are affected by the subjective judgment of the expert and require significant manual effort to derive. An alternative is unsupervised classification, which seeks to divide a dataset into distinct classes without expert-provided labels. In this paper, we introduce an unsupervised classification scheme based on a generative adversarial network (GAN) that learns to extract the key features from the snowflake images. Each image is then associated with a distribution of points in the feature space, and these distributions are used as the basis of K-medoids classification and hierarchical clustering. We found that the classification scheme is able to separate the dataset into distinct classes, each characterized by a particular size, shape and texture of the snowflake image, providing signatures of the microphysical properties of the snowflakes. This finding is supported by a comparison of the results to an existing supervised scheme. Although training the GAN is computationally intensive, the classification process proceeds directly from images to classes with minimal human intervention and therefore can be repeated for other MASC datasets with minor manual effort. As the algorithm is not specific to snowflakes, we also expect this approach to be relevant to other applications.
    Print ISSN: 1867-1381
    Digitale ISSN: 1867-8548
    Thema: Geologie und Paläontologie
    Publiziert von Copernicus im Namen von European Geosciences Union.
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  • 8
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    Microphysics and dynamics of snowfall associated with a warm conveyor belt over Korea (2020)
    Copernicus
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    Publikationsdatum: 2020-06-25
    Beschreibung: On 28 February 2018, 57 mm of precipitation associated with a warm conveyor belt (WCB) fell within 21 h over South Korea. To investigate how the large-scale circulation influenced the microphysics of this intense precipitation event, we used radar measurements, snowflake photographs and radiosounding data from the International Collaborative Experiments for Pyeongchang 2018 Olympic and Paralympic Winter Games (ICE-POP 2018). The WCB was identified with trajectories computed with analysis wind fields from the Integrated Forecast System global atmospheric model. The WCB was collocated with a zone of enhanced wind speed of up to 45 m s−1 at 6500 m a.s.l., as measured by a radiosonde and a Doppler radar. Supercooled liquid water (SLW) with concentrations exceeding 0.2 g kg−1 was produced during the rapid ascent within the WCB. During the most intense precipitation period, vertical profiles of polarimetric radar variables show a peak and subsequent decrease in differential reflectivity as aggregation starts. Below the peak in differential reflectivity, the specific differential phase shift continues to increase, indicating early riming of oblate crystals and secondary ice generation. We hypothesise that the SLW produced in the WCB led to intense riming. Moreover, embedded updraughts in the WCB and turbulence at its lower boundary enhanced aggregation by increasing the probability of collisions between particles. This suggests that both aggregation and riming occurred prominently in this WCB. This case study shows how the large-scale atmospheric flow of a WCB provides ideal conditions for rapid precipitation growth involving SLW production, riming and aggregation. Future microphysical studies should also investigate the synoptic conditions to understand how observed processes in clouds are related to large-scale circulation.
    Print ISSN: 1680-7316
    Digitale ISSN: 1680-7324
    Thema: Geologie und Paläontologie
    Publiziert von Copernicus im Namen von European Geosciences Union.
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  • 9
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    Three-dimensional radiative transfer effects on airborne and ground-based trace gas remote sensing (2020)
    Copernicus
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    Publikationsdatum: 2020-08-14
    Beschreibung: Air mass factors (AMFs) are used in passive trace gas remote sensing for converting slant column densities (SCDs) to vertical column densities (VCDs). AMFs are traditionally computed with 1D radiative transfer models assuming horizontally homogeneous conditions. However, when observations are made with high spatial resolution in a heterogeneous atmosphere or above a heterogeneous surface, 3D effects may not be negligible. To study the importance of 3D effects on AMFs for different types of trace gas remote sensing, we implemented 1D-layer and 3D-box AMFs into the Monte carlo code for the phYSically correct Tracing of photons In Cloudy atmospheres (MYSTIC), a solver of the libRadtran radiative transfer model (RTM). The 3D-box AMF implementation is fully consistent with 1D-layer AMFs under horizontally homogeneous conditions and agrees very well (
    Print ISSN: 1867-1381
    Digitale ISSN: 1867-8548
    Thema: Geologie und Paläontologie
    Publiziert von Copernicus im Namen von European Geosciences Union.
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  • 10
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    Improved Estimation of the Specific Differential Phase Shift Using a Compilation of Kalman Filter Ensembles (2014)
    Institute of Electrical and Electronics Engineers
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    Publikationsdatum: 2014-08-01
    Print ISSN: 0196-2892
    Digitale ISSN: 1558-0644
    Thema: Architektur, Bauingenieurwesen, Vermessung , Geographie
    Publiziert von Institute of Electrical and Electronics Engineers
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