摘要
We describe a dynamic-parameter aggregation scheme to estimate hourly turbulent heat fluxes over landfast sea ice during the transition from winter to spring. Hourly albedo measurements are used to track the morphology of the surface as it evolved from a fairly smooth homogeneous dry snow surface to a rougher heterogeneous surface with spatially differential melting and melt ponds. The estimates of turbulent heat fluxes for 928 h are compared with eddy-covariance measurements. The model performance metrics (W?m \(^{-2}\) ) for sensible heat flux were found to be: mean bias? \(=\) ? \(-3\) , root-mean-square error? \(=\) ?6 and absolute accuracy? \(=\) ?4, and for latent heat flux near zero, 3 and 2, respectively. The correlation coefficient between modelled and measured sensible heat fluxes was 0.82, and for latent heat fluxes 0.88. The turbulent heat fluxes were estimated more accurately without adjustments than with adjustments for atmospheric stability based on the bulk Richardson number. Overall, and across all metrics for both sensible and latent heat fluxes, the dynamic-parameter aggregation scheme outperformed the static Community Ice (C-ICE) scheme, part of the Community Climate System model, applied to the same winter-to-spring transition period.