3 research outputs found
Improvement and Sensitivity Analysis of Thermal Thin-Ice Thickness Retrievals
Considering the sea ice decline in the Arctic during the last decades, polynyas are of high research interest since these features are core areas of new ice formation. The determination of ice formation requires accurate retrieval of polynya area and thin-ice thickness (TIT) distribution within the polynya. We use an established energy balance model to derive TITs with MODIS ice surface temperatures and NCEP/DOE Reanalysis II in the Laptev Sea for two winter seasons. Improvements of the algorithm mainly concern the implementation of an iterative approach to calculate the atmospheric flux components taking the atmospheric stratification into account. Furthermore, a sensitivity study is performed to analyze the errors of the ice thickness. The results are the following: 1) 2-m air temperatures and have the highest impact on the retrieved ice thickness; 2) an overestimation of yields smaller ice thickness errors as an underestimation of ; 3) NCEP shows often a warm bias; and 4) the mean absolute error for ice thicknesses up to 20 cm is 4.7 cm. Based on these results, we conclude that, despite the shortcomings of the NCEP data (coarse spatial resolution and no polynyas), this data set is appropriate in combination with MODIS for the retrieval of TITs up to 20 cm in the Laptev Sea region. The TIT algorithm can be applied to other polynya regions and to past and future time periods. Our TIT product is a valuable data set for verification of other model and remote sensing ice thickness data
Sea ice surface temperatures from helicopter-borne thermal infrared imaging during the MOSAiC expedition
The sea ice surface temperature is important to understand the Arctic winter heat budget. We conducted 35 helicopter flights with an infrared camera in winter 2019/2020 during the Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. The flights were performed from a local, 5 to 10 km scale up to a regional, 20 to 40 km scale. The infrared camera recorded thermal infrared brightness temperatures, which we converted to surface temperatures. More than 150000 images from all flights can be investigated individually. As an advanced data product, we created surface temperature maps for every flight with a 1 m resolution. We corrected image gradients, applied an ice drift correction, georeferenced all pixels, and corrected the surface temperature by its natural temporal drift, which results in time-fixed surface temperature maps for a consistent analysis of one flight. The temporal and spatial variability of sea ice characteristics is an important contribution to an increased understanding of the Arctic heat budget and, in particular, for the validation of satellite products
Improvement and sensitivity analysis of thermal thin-ice thickness retrievals
Considering the sea ice decline in the Arctic during
the last decades, polynyas are of high research interest since these
features are core areas of new ice formation. The determination
of ice formation requires accurate retrieval of polynya area and
thin-ice thickness (TIT) distribution within the polynya.We use an
established energy balance model to derive TITs with MODIS ice
surface temperatures (Ts) and NCEP/DOE Reanalysis II in the
Laptev Sea for two winter seasons. Improvements of the algorithm
mainly concern the implementation of an iterative approach to
calculate the atmospheric flux components taking the atmospheric
stratification into account. Furthermore, a sensitivity study is
performed to analyze the errors of the ice thickness. The results
are the following: 1) 2-m air temperatures (Ta) and Ts have the
highest impact on the retrieved ice thickness; 2) an overestimation
of Ta yields smaller ice thickness errors as an underestimation
of Ta; 3) NCEP Ta shows often a warm bias; and 4) the mean
absolute error for ice thicknesses up to 20 cm is ±4.7 cm. Based
on these results, we conclude that, despite the shortcomings of the
NCEP data (coarse spatial resolution and no polynyas), this data
set is appropriate in combination with MODIS Ts for the retrieval
of TITs up to 20 cm in the Laptev Sea region. The TIT algorithm
can be applied to other polynya regions and to past and future time
periods. Our TIT product is a valuable data set for verification of
other model and remote sensing ice thickness data