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First 901 results for ” PM Stepanian”

  1. Significant atmospheric nonlinearities in the ENSO cycle

    The nonlinearities that cause El Nino events to deviate more from the mean state than La Nina ev...

    SY Philip, GJ van Oldenborgh | Status: published | Journal: J. Climate | Volume: 22 | Year: 2009 | First page: 4014 | Last page: 4028 | doi: 10.1175/2009JCLI2716.1

    Publication

  2. Earth observation Water Cycle Multi-Mission Observation Strategy (WACMOS)

    Observing and monitoring the different components of the global water cycle and their dynamics ar...

    Z Su, RA Roebeling, P Stammes, P Wang, E Wolters, et. al | Journal: Hydrol. Earth Syst. Sci. Discuss., | Volume: 7 | Year: 2011 | First page: 7899 | Last page: 7956 | doi: doi:10.5194/hessd-7-7899-2010

    Publication

  3. Measuring Low-Altitude Winds with a Hot-Air Balloon and Their Validation with Cabauw Tower Observations

    A field experiment with a hot-air balloon was conducted in the vicinity of the meteorological obs...

    EIF de Bruijn, FC Bosveld, S de Haan, BG Heusinkveld | Status: published | Journal: J. Atm. Oceanic Technol. | Volume: 37 | Year: 2020 | First page: 263 | Last page: 277 | doi: https://doi.org/10.1175/JTECH-D-19-0043.1

    Publication

  4. Extracting low signal-to-noise ratio events with the Hough transform from sparse array data

    Low-frequency acoustic, i.e., infrasound, waves are measured by sparse arrays of microbarometers....

    G Averbuch, JD Assink, PSM Smets, LG Evers | Status: published | Journal: Geophysics | Year: 2018 | doi: 10.1190/GEO2017-0490.1

    Publication

  5. dispel4py: An agile framework for data-intensive escience

    We present dispel4py a versatile data-intensive kit presented as a standard Python library. It em...

    Rosa Filgueira, Alessandro Spinuso | Journal: IEEE 11th International Conference on e-Science | Year: 2015 | doi: https://doi.org/10.1109/eScience.2015.40

    Publication