Evolution and spatial variability of small-scale surface roughness of snow and sea ice during MOSAiC

Small-scale surface roughness (on an area of about 0.5 m x 0.5 m) affects remote sensing retrieval algorithms and radiative transfer models, yet data of snow and ice surface roughness over sea ice is scarce. Microwave emissivity, important for satellite retrievals of sea ice concentration, type, thi...

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Bibliographic Details
Main Authors: Dadic, Ruzica, Schneebeli, Martin, Hannula, Henna-Reetta, Pirazzini, Roberta, Macfarlane, Amy, Wigmore, Oliver, Vargo, Lauren, Wagner, David, Brus, David, Arndt, Stefanie, Jaggi, Matthias, Krampe, Daniela, Lehning, Michael, Spreen, Gunnar, Stroeve, Julienne
Format: Text
Language:unknown
Published: 2022
Subjects:
Sea ice
Online Access:https://agu.confex.com/agu/fm21/meetingapp.cgi/Paper/912805
http://infoscience.epfl.ch/record/292653
Description
Summary:Small-scale surface roughness (on an area of about 0.5 m x 0.5 m) affects remote sensing retrieval algorithms and radiative transfer models, yet data of snow and ice surface roughness over sea ice is scarce. Microwave emissivity, important for satellite retrievals of sea ice concentration, type, thickness, etc., is a function of ice/snow and snow/air interface roughness (amongst other factors). During MOSAiC, we collected data to determine the small-scale surface roughness of the surface (snow and surface scattering layer) and the snow/sea-ice interface using a rapid photogrammetric method. Surface roughness data was collected with most snow pits as well as on some transects to account for temporal and spatial variability. Here, we present the surface roughness evolution for the year-long snow pit observations and discuss the applicability and relevance of this dataset for remote sensing and radiative transfer studies. We will consider the spatial variability and anisotropy of surface roughness for different snow and surface types. Furthermore, we will compare this small-scale surface roughness to ∼100m-scale surface roughness obtained from UAVs to determine relevant roughness scales for different applications. We will also discuss other potential applications for this dataset, such as correlations between the small-scale surface roughness and specific surface area (from near-infrared photography, SnowMicroPen, and microCT), shear strength (from SnowMicroPen), or aerodynamic roughness for turbulent fluxes.

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