Publikationen am Institut für Meteorologie und Geophysik
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Qorbani, E., Zigone, D., Bokelmann, G., & AlpArray Working Group (2020). Crustal structures beneath the Eastern and Southern Alps from ambient noise tomography. Solid earth. https://doi.org/10.5194/se-2019-177, https://doi.org/10.5194/se-11-1947-2020
Löberich, E., & Bokelmann, G. (2020). Flow plane orientation in the upper mantle under the Western/Central United States from SKS shear-wave splitting observations. Geophysical Journal International, 221(2), 1125-1137. https://doi.org/10.1093/gji/ggaa060
Koppan, A., Benedek, J., Kis, M., Meurers, B., & Papp, G. (2020). Scale factor determination of spring type gravimeters in the amplitude range of tides by a moving mass device. Metrologia: international journal of pure and applied metrology, 57. https://iopscience.iop.org/article/10.1088/1681-7575/ab3eaf
Sodemann, H., Wernli, H., Knippertz, P., Cordeira, J., Dominguez, F., Guan, B., & Stohl, A. (2020). Structure, Process and Mechanism, in: Atmospheric Rivers. in Atmospheric Rivers (S. 284). Springer.
Pisso, I., Sollum, E., Grythe, H., Kristiansen, N. I., Cassiani, M., Eckhardt, S., Arnold, D., Morton, D., Thompson, R. L., Groot Zwaaftink, C. D., Evangeliou, N., Sodemann, H., Haimberger, L., Henne, S., Brunner, D., Burkhart, J. F., Fouilloux, A., Brioude, J., Philipp, A., ... Stohl, A. (2019). The Lagrangian particle dispersion model FLEXPART version 10.4. Geoscientific Model Development, 12(12), 4955-4997. https://doi.org/10.5194/gmd-2018-333, https://doi.org/10.5194/gmd-12-4955-2019
Mayer, M., Tietsche, S., Haimberger, L., Tsubouchi, T., Mayer, J., & Zuo, H. (2019). An improved estimate of the coupled Arctic energy budget. Journal of Climate, 32(22), 7915-7934. https://doi.org/10.1175/JCLI-D-19-0233.1
Bianchi, I., & Bokelmann, G. (2019). Probing Crustal Anisotropy by Receiver Functions at the Deep Continental Drilling Site KTB in Southern Germany. Geophysical Prospecting, 67(9), 2450-2464. https://doi.org/10.1111/1365-2478.12883
Haimberger, L., Mayer, M., Schenzinger, V., & Hersbach, H. (2019). Upper air winds. Bulletin of the American Meteorological Society, 100(9), S45-S46. https://doi.org/10.1175/2019BAMSStateoftheClimate.1
Sharifi, E., Eitzinger, J., & Dorigo, W. (2019). Performance of the State-Of-The-Art Gridded Precipitation Products over Mountainous Terrain: A Regional Study over Austria. Remote Sensing, 11(17), [2018]. https://doi.org/10.3390/rs11172018
Hossein Salimi, A., Masoompour Samakosh, J., Sharifi, E., Hassanvand, M. R., Noori, A., & von Rautenkranz , H. (2019). Optimized Artificial Neural Networks-Based Methods for Statistical Downscaling of Gridded Precipitation Data. Water, 11(8), [1653]. https://doi.org/10.3390/w11081653
Spiridonov, V., & Ćurić, M. (2019). Evaluation of Supercell Storm Triggering Factors Based on a CloudResolving Model Simulation. Asia-Pacific Journal of Atmospheric Sciences, 55(3), 439–458. https://doi.org/10.1007/s13143-018-0070-7
Spiridonov, V., Jakimovski, B., Spiridonova, I., & Pereira, G. (2019). Development of air quality forecasting system in Macedonia, based on WRF-Chem model. Air Quality, Atmosphere & Health, 12, 825-836. https://doi.org/10.1007/s11869-019-00698-5
Kolinsky, P., & Bokelmann, G. (2019). Arrival angles of teleseismic fundamental mode Rayleigh waves across the AlpArray. Geophysical Journal International, 218(1), 115-144. https://doi.org/10.1093/gji/ggz081
Cheng, L., Trenberth, K. E., Fasullo, J. T., Mayer, M., Balmaseda, M., & Zhu, J. (2019). Evolution of ocean heat content related to ENSO. Journal of Climate, 32(12), 3529-3556. https://doi.org/10.1175/JCLI-D-18-0607.1
Nabavi, S. O., Haimberger, L., & Abbasi, E. (2019). Assessing PM2.5 concentrations in Tehran, Iran, from space using MAIAC, Deep Blue, and Dark Target AOD and Machine Learning Algorithms. Atmospheric Pollution Research, 10(3), 889-903. https://doi.org/10.1016/j.apr.2018.12.017
Diaz, J. P., Expósito, F. J., Pérez, J. C., González, A., Wang, Y., Haimberger, L., & Wang, J. (2019). Long-term trends in marine boundary layer properties over the Atlantic Ocean. Journal of Climate, 32(10), 2991-3004. https://doi.org/10.1175/JCLI-D-18-0219.1
Spiridonov, V., Ćurić, M., & Jakimosvki, B. (2019). Examination of in-cloud sulfate chemistry using a different model initialization. Air Quality, Atmosphere & Health, 12(2), 137-150. https://doi.org/10.1007/s11869-018-0632-y
Sharifi, E., Saghafian, B., & Steinacker, R. (2019). Copula-based Stochastic Uncertainty Analysis of Satellite Precipitation Products. Journal of Hydrology, 570, 739-754. https://doi.org/10.1016/j.jhydrol.2019.01.035
Sharifi, E., Saghafian, B., & Steinacker, R. (2019). Downscaling Satellite Precipitation Estimates with Multiple Linear Regression, Artificial Neural Networks and Spline Interpolation Techniques. Journal of Geophysical Research: Atmospheres, 124(2), 789-805. [DOI: 10.1029/2018JD028795]. https://doi.org/10.1029/2018JD028795
Serafin, S., Strauss, L., & Dorninger, M. (2019). Ensemble reduction using cluster analysis. Quarterly Journal of the Royal Meteorological Society, 145(719), 659-674. https://doi.org/10.1002/qj.3458
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