|
|
Article: Fluctuating Arctic Sea Ice Thickness Changes Estimated by an In Situ Learned and Empirically Forced Neural Network Model
- Article from:
- Journal of Climate
- Article date:
- February 15, 2008
- Author:
CopyrightCopyright American Meteorological Society Feb 15, 2008. Provided by ProQuest LLC. (Hide copyright information)
|
ABSTRACT
Sea ice thickness (SIT) is a key parameter of scientific interest because understanding the natural spatiotemporal variability of ice thickness is critical for improving global climate models. In this paper, changes in Arctic SIT during 1982-2003 are examined using a neural network (NN) algorithm trained with in situ submarine ice draft and surface drilling data. For each month of the study period, the NN individually estimated SIT of each ice-covered pixel (25-km resolution) based on seven geophysical parameters (four shortwave and longwave radiative fluxes, surface air temperature, ice drift velocity, and ice divergence/ convergence) that were cumulatively summed at each monthly ...