TY - JOUR
T1 - Simulated Geophysical Noise in Sea Ice Concentration Estimates of Open Water and Snow-covered Sea Ice
AU - Tonboe, Rasmus
AU - Nandan, Vishnu
AU - Makynen, Marko P.
AU - Pedersen, Leif Toudal
AU - Kern, Stefan
AU - Lavergne, Thomas
AU - elund, Johanne
AU - Dybkjar, Gorm
AU - Saldo, Roberto
AU - Huntemann, Marcus
N1 - Publisher Copyright:
Author
PY - 2022
Y1 - 2022
N2 - Sea ice concentration algorithms using brightness temperatures ( TB ) from satellite microwave radiometers are used to compute sea ice concentration ( cice ), sea ice extent, and generate sea ice climate data records. Therefore, it is important to minimize the sensitivity of cice estimates to geophysical noise caused by snow/sea ice thermal microwave emission signature variations, and presence of WV and clouds in the atmosphere and/or near-surface winds. In this study, we investigate the effect of geophysical noise leading to systematic cice biases and affecting cice standard deviations (STD) using simulated top of the atmosphere TB s over open water and 100% sea ice. We consider three case studies for the Arctic and the Antarctic and eight different cice algorithms, representing different families of algorithms based on the selection of channels and methodologies. Our simulations show that, over open water and low cice , algorithms using gradients between V-polarized 19-GHz and 37-GHz TB s show the lowest sensitivity to the geophysical noise, while the algorithms exclusively using near-90-GHz channels have by far the highest sensitivity. Over sea ice, the atmosphere plays a much smaller role than over open water, and the cice STD for all algorithms is smaller than over open water. The hybrid and low-frequency (6 GHz) algorithms have the lowest sensitivity to noise over sea ice, while the polarization type of algorithms has the highest noise levels.
AB - Sea ice concentration algorithms using brightness temperatures ( TB ) from satellite microwave radiometers are used to compute sea ice concentration ( cice ), sea ice extent, and generate sea ice climate data records. Therefore, it is important to minimize the sensitivity of cice estimates to geophysical noise caused by snow/sea ice thermal microwave emission signature variations, and presence of WV and clouds in the atmosphere and/or near-surface winds. In this study, we investigate the effect of geophysical noise leading to systematic cice biases and affecting cice standard deviations (STD) using simulated top of the atmosphere TB s over open water and 100% sea ice. We consider three case studies for the Arctic and the Antarctic and eight different cice algorithms, representing different families of algorithms based on the selection of channels and methodologies. Our simulations show that, over open water and low cice , algorithms using gradients between V-polarized 19-GHz and 37-GHz TB s show the lowest sensitivity to the geophysical noise, while the algorithms exclusively using near-90-GHz channels have by far the highest sensitivity. Over sea ice, the atmosphere plays a much smaller role than over open water, and the cice STD for all algorithms is smaller than over open water. The hybrid and low-frequency (6 GHz) algorithms have the lowest sensitivity to noise over sea ice, while the polarization type of algorithms has the highest noise levels.
KW - Microwave radiometry
KW - Sea ice concentration
KW - Sea ice emission modelling
U2 - 10.1109/JSTARS.2021.3134021
DO - 10.1109/JSTARS.2021.3134021
M3 - Journal article
AN - SCOPUS:85121383164
SN - 1939-1404
VL - 15
SP - 1309
EP - 1326
JO - IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
JF - IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
ER -