On the Impact of Ice Emissivity on Sea Ice Temperature Retrieval Using Passive Microwave Radiance Data

Abstract

This letter examines the performance of two Advanced Microwave Scanning Radiometer-EOS (AMSR-E) ice temperature algorithms over first-year sea ice during the spring transition period where ice concentrations are close to 100%. The results showed, before snow melt, that the old AMSR-E algorithm overestimated the ice temperature by up to 18 K, which is relative to <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in</i> <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">situ</i> and thermodynamically calculated snow/ice interface temperatures ( <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">T</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">si</sub> ). An adjustment of vertically polarized ice emissivity of 6.9 GHz [epsiv <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">I</sub> (6V)] to 0.98, which was identical to the constant value used in the latest version of the AMSR-E ice temperature algorithm (posted July 2007), demonstrated a significant improvement in ice temperature retrieval. However, after snow melt, the ice temperature retrieval with any constant epsiv <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">I</sub> (6V) failed to correctly estimate the ice temperatures due to large variability in the physical properties of snow and, in turn, penetration depth and epsiv <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">I</sub> (6V). The results suggest that a local adjustment of epsiv <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">I</sub> (6V), which is by incorporating a simple thermodynamic model into the AMSR-E ice temperature algorithm, would be useful in improving the performance of the algorithm.