Title: Developing Bulk Turbulent Surface Flux Algorithms over Surfaces Consisting of Liquid or Frozen Water

Abstract: 
Bulk flux algorithms predict the turbulent surface fluxes of momentum and sensible and 
latent heat (and even trace gases) from the bulk properties of the air and surface—namely, 
wind speed, air temperature and humidity, and surface temperature and salinity.  Some 
algorithms also consider the morphological properties of the surface.  Bulk flux 
algorithms find use for estimating the surface fluxes when they cannot be measured 
directly.  More importantly, a form of bulk flux algorithm is always used in numerical 
weather prediction, global climate, and hurricane forecasting models, where it couples the 
atmosphere and the surface through flux boundary conditions.
From thousands of hours of eddy-covariance measurements of the surface fluxes, I have 
developed bulk flux algorithms for various water and ice surfaces.  My inventory of 
algorithms covers the open ocean; large lakes and reservoirs; sea ice in winter, when it 
is compact and snow-covered; sea ice in summer, when it is more open and includes melt 
ponds; and the marginal ice zone, which consists of ice floes and open water in comparable 
proportions.  The winter sea ice algorithm is also appropriate for glaciers and extensive 
terrestrial snow fields.  Developing bulk flux algorithms for such water and ice surfaces 
is possible because the surface temperature, a key variable in these algorithms, is 
straightforward to define and relatively easy to measure. In this talk, I will review the 
general theoretical foundation for bulk turbulent flux algorithms but will also highlight 
differences among the algorithms that I have developed.  I will also discuss the 
measurements required for developing turbulent flux algorithms and focus on the lingering 
conceptual issues that keep flux algorithms a hot topic in micrometeorology.