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First 2371 results for ” J Valverde Canossa”

1. Unveiling spatial variability within the Dotson Melt Channel through high-resolution basal melt rates from the Reference Elevation Model of Antarctica

   The intrusion of Circumpolar Deep Water in the Amundsen and Bellingshausen Sea embayments of Anta...

   Ann-Sofie Priergaard Zinck, Bert Wouters, Erwin Lambert, and Stef Lhermitte | Journal: The Cryosphere | Volume: 17 | Year: 2023 | First page: 3785 | Last page: 3801 | doi: 10.5194/tc-17-3785-2023

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2. Modelling SARS-CoV-2 disease progression in Australia and New Zealand: an account of an agent-based approach to support public health decision-making

   Objective: In 2020, we developed a public health decision-support model for mitigating the spread...

   Jason Thompson, Rod McClure, Tony Blakely, Nick Wilson, Michael G. Baker, Jasper S. Wijnands, Thiago Herick De Sa, Kerry Nice, Camilo Cruz, Mark Stevenson | Journal: Australian and New Zealand Journal of Public Health | Volume: 46 | Year: 2022 | First page: 292 | Last page: 303 | doi: https://doi.org/10.1111/1753-6405.13221

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3. Ocean signatures in the total flux and polarization spectra of Earth-like exoplanets

   Context. Numerical simulations of starlight that is reflected by Earth-like exoplanets predict ha...

   Trees, V.J.H. and Stam, D.M | Journal: Astronomy & Astrophysics | Year: 2022 | doi: https://doi.org/10.1051/0004-6361/202243591

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4. Hurricane eye morphology extraction from SAR images by texture analysis

   Tropical hurricanes are among the most devastating hazards on Earth. Knowledge about its intense ...

   Weicheng Ni, Ad Stoffelen, Kaijun Ren | Journal: Frontiers of Earth Science | Volume: 16 | Year: 2022 | doi: https://doi.org/10.1007/s11707-021-0886-9

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5. Improvements in Ku-band scatterometer wind ambiguity removal using ASCAT-based empirical background error correlations

   Wind scatterometry is an established technique for accurately measuring wind vectors over the wor...

   Jur Vogelzang, Ad Stoffelen | Journal: Quarterly Journal of the Royal Meteorological Society | Volume: 144 | Year: 2018 | doi: https://doi.org/10.1002/qj.3349

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