Blar i forfatter "Zhou, Lu"

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    • A Lagrangian Snow Evolution System for Sea Ice Applications (SnowModel‐LG): Part II - Analyses 

      Stroeve, Julienne C.; Liston, Glen E.; Buzzard, Samantha; Zhou, Lu; Mallett, Robbie; Barrett, Andrew; Tschudi, Mark; Tsamados, Michel; Itkin, Polona; Stewart, Scott (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-09-02)
      Sea ice thickness is a critical variable, both as a climate indicator and for forecasting sea ice conditions on seasonal and longer time scales. The lack of snow depth and density information is a major source of uncertainty in current thickness retrievals from laser and radar altimetry. In response to this data gap, a new Lagrangian snow evolution model (SnowModel‐LG) was developed to simulate snow ...

    • Retrieval of Snow Depth on Arctic Sea Ice From Surface-Based, Polarimetric, Dual-Frequency Radar Altimetry 

      Willatt, Rosemary; Stroeve, Julienne; Nandan, Vishnu; Newman, Thomas; Mallett, Robbie; Hendricks, Stefan; Ricker, Robert; Mead, James; Itkin, Polona; Tonboe, Rasmus; Wagner, David N.; Spreen, Gunnar; Liston, Glen; Schneebeli, Martin; Krampe, Daniela; Tsamados, Michel; Demir, Oguz; Wilkinson, Jeremy; Jaggi, Matthias; Zhou, Lu; Huntemann, Marcus; Raphael, Ian A.; Jutila, Arttu; Oggier, Marc (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-10-18)
      Snow depth on sea ice is an Essential Climate Variable and a major source of uncertainty in satellite altimetry-derived sea ice thickness. During winter of the MOSAiC Expedition, the “KuKa” dual-frequency, fully polarized Ku- and Ka-band radar was deployed in “stare” nadir-looking mode to investigate the possibility of combining these two frequencies to retrieve snow depth. Three approaches ...