Much attention on the extent, and changes therein, of Arctic sea ice focuses on areal coverage. Equally if not more important to consider is the thickness of the ice, which varies with age and also due to movement of the ice. Thickness is geometrically rough with ridges, rubble fields, and open-water leads. These features are asymmetrically shaped from centimeters to meters in one horizontal direction and meters to kilometers along the other. Instruments used to sense ice thickness typically have wide footprints that alias these rough features into smoother flatter features. Accurate thickness distribution of these deformed areas is needed to reduce uncertainties in global thickness data archives. Such results lead to higher accuracy in regional and global sea ice volume estimates. High precision and consistency from a single instrument cannot quantify the impact of aliasing. The sea ice community currently seeks an integrated- instrument approach to measure sea ice thickness from its components of draft, freeboard, and surface elevation (including snow loads) and thickness archives are being developed. This project would address the central question, "What is the impact of spatial aliasing when measuring sea ice thickness, its distribution, and resulting volume?" The approach is to work with datasets that include measurements made by two or more instruments with different footprints in the same location, based on a recently discovered relationship between the roughness of 5m and 40m footprints stemming from one field experiment. Using this dataset a valid correction (to better than 10 cm) was found using the roughness ratio between the two measurements. The investigator proposes that this type of relationship can be generalized for all types of sea ice thickness measurements. The investigator will organize and archive climate data records containing coincident sea ice thickness measurements from instruments of different footprints and incorporate these data with existing sea ice thickness archives. The main scientific contribution will be an improved metadata relationship to characterize properties that contribute to thickness uncertainties in climate data archive records. A Ph.D. thesis will advance the aliasing hypothesis using airborne electromagnetic (EM) measurements to devise a correction by leveraging the accompanying high-resolution laser altimeter already integrated into the EM technology. The broader impacts of the work include the improved thickness archive and the training of a Ph.D. student.